WorldWideScience

Sample records for learning model based

  1. Model-based machine learning.

    Science.gov (United States)

    Bishop, Christopher M

    2013-02-13

    Several decades of research in the field of machine learning have resulted in a multitude of different algorithms for solving a broad range of problems. To tackle a new application, a researcher typically tries to map their problem onto one of these existing methods, often influenced by their familiarity with specific algorithms and by the availability of corresponding software implementations. In this study, we describe an alternative methodology for applying machine learning, in which a bespoke solution is formulated for each new application. The solution is expressed through a compact modelling language, and the corresponding custom machine learning code is then generated automatically. This model-based approach offers several major advantages, including the opportunity to create highly tailored models for specific scenarios, as well as rapid prototyping and comparison of a range of alternative models. Furthermore, newcomers to the field of machine learning do not have to learn about the huge range of traditional methods, but instead can focus their attention on understanding a single modelling environment. In this study, we show how probabilistic graphical models, coupled with efficient inference algorithms, provide a very flexible foundation for model-based machine learning, and we outline a large-scale commercial application of this framework involving tens of millions of users. We also describe the concept of probabilistic programming as a powerful software environment for model-based machine learning, and we discuss a specific probabilistic programming language called Infer.NET, which has been widely used in practical applications.

  2. Inquiry based learning as didactic model in distant learning

    NARCIS (Netherlands)

    Rothkrantz, L.J.M.

    2015-01-01

    Recent years many universities are involved in development of Massive Open Online Courses (MOOCs). Unfortunately an appropriate didactic model for cooperated network learning is lacking. In this paper we introduce inquiry based learning as didactic model. Students are assumed to ask themselves

  3. Prototype-based models in machine learning

    NARCIS (Netherlands)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of

  4. Prototype-based models in machine learning.

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2016-01-01

    An overview is given of prototype-based models in machine learning. In this framework, observations, i.e., data, are stored in terms of typical representatives. Together with a suitable measure of similarity, the systems can be employed in the context of unsupervised and supervised analysis of potentially high-dimensional, complex datasets. We discuss basic schemes of competitive vector quantization as well as the so-called neural gas approach and Kohonen's topology-preserving self-organizing map. Supervised learning in prototype systems is exemplified in terms of learning vector quantization. Most frequently, the familiar Euclidean distance serves as a dissimilarity measure. We present extensions of the framework to nonstandard measures and give an introduction to the use of adaptive distances in relevance learning. © 2016 Wiley Periodicals, Inc.

  5. Online constrained model-based reinforcement learning

    CSIR Research Space (South Africa)

    Van Niekerk, B

    2017-08-01

    Full Text Available Constrained Model-based Reinforcement Learning Benjamin van Niekerk School of Computer Science University of the Witwatersrand South Africa Andreas Damianou∗ Amazon.com Cambridge, UK Benjamin Rosman Council for Scientific and Industrial Research, and School... MULTIPLE SHOOTING Using direct multiple shooting (Bock and Plitt, 1984), problem (1) can be transformed into a structured non- linear program (NLP). First, the time horizon [t0, t0 + T ] is partitioned into N equal subintervals [tk, tk+1] for k = 0...

  6. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    OpenAIRE

    Hayati .; Retno Dwi Suyanti

    2013-01-01

    The objective in this research: (1) Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2) Determine the level of motivation to learn in affects physics student learning outcomes. (3) Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all s...

  7. Game Based Learning (GBL) adoption model for universities: cesim ...

    African Journals Online (AJOL)

    Game Based Learning (GBL) adoption model for universities: cesim simulation. ... The global market has escalated the need of Game Based Learning (GBL) to offer a wide range of courses since there is a ... AJOL African Journals Online.

  8. Cognitive components underpinning the development of model-based learning.

    Science.gov (United States)

    Potter, Tracey C S; Bryce, Nessa V; Hartley, Catherine A

    2017-06-01

    Reinforcement learning theory distinguishes "model-free" learning, which fosters reflexive repetition of previously rewarded actions, from "model-based" learning, which recruits a mental model of the environment to flexibly select goal-directed actions. Whereas model-free learning is evident across development, recruitment of model-based learning appears to increase with age. However, the cognitive processes underlying the development of model-based learning remain poorly characterized. Here, we examined whether age-related differences in cognitive processes underlying the construction and flexible recruitment of mental models predict developmental increases in model-based choice. In a cohort of participants aged 9-25, we examined whether the abilities to infer sequential regularities in the environment ("statistical learning"), maintain information in an active state ("working memory") and integrate distant concepts to solve problems ("fluid reasoning") predicted age-related improvements in model-based choice. We found that age-related improvements in statistical learning performance did not mediate the relationship between age and model-based choice. Ceiling performance on our working memory assay prevented examination of its contribution to model-based learning. However, age-related improvements in fluid reasoning statistically mediated the developmental increase in the recruitment of a model-based strategy. These findings suggest that gradual development of fluid reasoning may be a critical component process underlying the emergence of model-based learning. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

  9. Competition-Based Learning: A Model for the Integration of Competitions with Project-Based Learning Using Open Source LMS

    Science.gov (United States)

    Issa, Ghassan; Hussain, Shakir M.; Al-Bahadili, Hussein

    2014-01-01

    In an effort to enhance the learning process in higher education, a new model for Competition-Based Learning (CBL) is presented. The new model utilizes two well-known learning models, namely, the Project-Based Learning (PBL) and competitions. The new model is also applied in a networked environment with emphasis on collective learning as well as…

  10. LEARNING CREATIVE WRITING MODEL BASED ON NEUROLINGUISTIC PROGRAMMING

    OpenAIRE

    Rustan, Edhy

    2017-01-01

    The objectives of the study are to determine: (1) condition on learning creative writing at high school students in Makassar, (2) requirement of learning model in creative writing, (3) program planning and design model in ideal creative writing, (4) feasibility of model study based on creative writing in neurolinguistic programming, and (5) the effectiveness of the learning model based on creative writing in neurolinguisticprogramming.The method of this research uses research development of L...

  11. A Judgement-Based Model of Workplace Learning

    Science.gov (United States)

    Athanasou, James A.

    2004-01-01

    The purpose of this paper is to outline a judgement-based model of adult learning. This approach is set out as a Perceptual-Judgemental-Reinforcement approach to social learning under conditions of complexity and where there is no single, clearly identified correct response. The model builds upon the Hager-Halliday thesis of workplace learning and…

  12. A strategy learning model for autonomous agents based on classification

    Directory of Open Access Journals (Sweden)

    Śnieżyński Bartłomiej

    2015-09-01

    Full Text Available In this paper we propose a strategy learning model for autonomous agents based on classification. In the literature, the most commonly used learning method in agent-based systems is reinforcement learning. In our opinion, classification can be considered a good alternative. This type of supervised learning can be used to generate a classifier that allows the agent to choose an appropriate action for execution. Experimental results show that this model can be successfully applied for strategy generation even if rewards are delayed. We compare the efficiency of the proposed model and reinforcement learning using the farmer-pest domain and configurations of various complexity. In complex environments, supervised learning can improve the performance of agents much faster that reinforcement learning. If an appropriate knowledge representation is used, the learned knowledge may be analyzed by humans, which allows tracking the learning process

  13. DEVELOPMENT OF SCIENCE PROCESS SKILLS STUDENTS WITH PROJECT BASED LEARNING MODEL- BASED TRAINING IN LEARNING PHYSICS

    Directory of Open Access Journals (Sweden)

    Ratna Malawati

    2016-06-01

    Full Text Available This study aims to improve the physics Science Process Skills Students on cognitive and psychomotor aspects by using model based Project Based Learning training.The object of this study is the Project Based Learning model used in the learning process of Computationa Physics.The method used is classroom action research through two learning cycles, each cycle consisting of the stages of planning, implementation, observation and reflection. In the first cycle of treatment with their emphasis given training in the first phase up to third in the model Project Based Learning, while the second cycle is given additional treatment with emphasis discussion is collaboration in achieving the best results for each group of products. The results of data analysis showed increased ability to think Students on cognitive and Science Process Skills in the psychomotor.

  14. EFFECTS OF INQUIRY TRAINING LEARNING MODEL BASED MULTIMEDIA AND MOTIVATION OF PHYSICS STUDENT LEARNING OUTCOMES

    Directory of Open Access Journals (Sweden)

    Hayati .

    2013-06-01

    Full Text Available The objective in this research: (1 Determine a better learning model to improve learning outcomes physics students among learning model Inquiry Training based multimedia and Inquiry Training learning model. (2 Determine the level of motivation to learn in affects physics student learning outcomes. (3 Knowing the interactions between the model of learning and motivation in influencing student learning outcomes. This research is a quasi experimental. The population in this research was all students in class XI SMA Negeri 1 T.P Sunggal Semester I 2012/2013. The sample of this research was consisted of two classes with a sample of 70 peoples who are determined by purposive sampling, the IPA XI-2 as a class experiment using a model-based multimedia learning Training Inquiry as many as 35 peoples and XI IPA-3 as a control class using learning model Inquiry Training 35 peoples. Hypotheses were analyzed using the GLM at significant level of 0.05 using SPSS 17.0 for Windows. Based on data analysis and hypothesis testing conducted found that: (1 Training Inquiry-based multimedia learning model in improving student learning outcomes rather than learning model physics Inquiry Training. (2 The results of studying physics students who have high motivation to learn better than students who have a low learning motivation. (3 From this research there was an interaction between learning model inquiry-based multimedia training and motivation to study on learning outcomes of students.

  15. DEVELOPMENT MODEL OF PATISSERIE PROJECT-BASED LEARNING

    OpenAIRE

    Ana Ana; Lutfhiyah Nurlaela

    2013-01-01

    The study aims to find a model of patisserie project-based learning with production approach that can improve effectiveness of patisserie learning. Delphi Technique, Cohen's Kappa and percentages of agreements were used to assess model of patisserie project based learning. Data collection techniques employed in the study were questionnaire, check list worksheet, observation, and interview sheets. Subjects were 13 lectures of expertise food and nutrition and 91 students of Food and Nutrition ...

  16. Learning of Chemical Equilibrium through Modelling-Based Teaching

    Science.gov (United States)

    Maia, Poliana Flavia; Justi, Rosaria

    2009-01-01

    This paper presents and discusses students' learning process of chemical equilibrium from a modelling-based approach developed from the use of the "Model of Modelling" diagram. The investigation was conducted in a regular classroom (students 14-15 years old) and aimed at discussing how modelling-based teaching can contribute to students…

  17. A Technology-based Model for Learning

    Directory of Open Access Journals (Sweden)

    Michael Williams

    2004-12-01

    Full Text Available The Math Emporium, opened in 1997, is an open 7000-squaremeter facility with 550+ workstations arranged in an array of widely spaced hexagonal "pods", designed to support group work at the same time maintaining an academic air. We operate it 24/7 with math support personnel in attendance 12 hours per day. Students have access to online course resources at all times, from anywhere. We have used this unique asset to transform traditional classroom-based courses into technology based learning programs that have no class meetings at all. The structure of the program is very different from the conventional one, having a new set of expectations and motivations. The results include: more effective students, substantial cost savings, economies of scale and scope and a stream-lined process for creating new on-line courses.

  18. Group-Based Active Learning of Classification Models.

    Science.gov (United States)

    Luo, Zhipeng; Hauskrecht, Milos

    2017-05-01

    Learning of classification models from real-world data often requires additional human expert effort to annotate the data. However, this process can be rather costly and finding ways of reducing the human annotation effort is critical for this task. The objective of this paper is to develop and study new ways of providing human feedback for efficient learning of classification models by labeling groups of examples. Briefly, unlike traditional active learning methods that seek feedback on individual examples, we develop a new group-based active learning framework that solicits label information on groups of multiple examples. In order to describe groups in a user-friendly way, conjunctive patterns are used to compactly represent groups. Our empirical study on 12 UCI data sets demonstrates the advantages and superiority of our approach over both classic instance-based active learning work, as well as existing group-based active-learning methods.

  19. A pedagogical model for simulation-based learning in healthcare

    Directory of Open Access Journals (Sweden)

    Tuulikki Keskitalo

    2015-11-01

    Full Text Available The aim of this study was to design a pedagogical model for a simulation-based learning environment (SBLE in healthcare. Currently, simulation and virtual reality are a major focus in healthcare education. However, when and how these learning environments should be applied is not well-known. The present study tries to fill that gap. We pose the following research question: What kind of pedagogical model supports and facilitates students’ meaningful learning in SBLEs? The study used design-based research (DBR and case study approaches. We report the results from our second case study and how the pedagogical model was developed based on the lessons learned. The study involved nine facilitators and 25 students. Data were collected and analysed using mixed methods. The main result of this study is the refined pedagogical model. The model is based on the socio-cultural theory of learning and characteristics of meaningful learning as well as previous pedagogical models. The model will provide a more holistic and meaningful approach to teaching and learning in SBLEs. However, the model requires evidence and further development.

  20. Game Based Learning (GBL) Adoption Model for Universities ...

    African Journals Online (AJOL)

    pc

    2018-03-05

    Mar 5, 2018 ... faced while adopting Game Based Learning (GBL) model, its benefits and ... preferred traditional lectures styles, 7% online class and. 34% preferred .... students in developing problem-solving skills which in return may help ...

  1. Gender-related model for mobile-based learning

    Science.gov (United States)

    Simanjuntak, R. R.; Dewi, U. P.; Rifai, I.

    2018-03-01

    The study investigates gender influence on mobile-based learning. This case study of university students in Jakarta involved 235 students (128 male, 97 female). Results of this qualitative study showed 96% preference for mobile-based learning. A further 94% showed the needs for collaboration and authenticity for 92%. Hofstede’s cultural dimensions were used to identify the gender aspects of MALL. Preference for Masculinity (65%) was showed rather than Femininity (35%), even among the female respondents (70% of the population). Professions and professionalism received strongest preference (70%) while Individuality and Collectivism had equal preferences among students. Both female and male respondents requested Indulgence (84%) for mobile-based learning with more male respondents opted for Indulgence. The study provided a model for this gender sensitive mobile-based learning. Implications of implementing mobile-based learning as an ideal alternative for well-accommodated education are is also discussed.

  2. An Active Learning Exercise for Introducing Agent-Based Modeling

    Science.gov (United States)

    Pinder, Jonathan P.

    2013-01-01

    Recent developments in agent-based modeling as a method of systems analysis and optimization indicate that students in business analytics need an introduction to the terminology, concepts, and framework of agent-based modeling. This article presents an active learning exercise for MBA students in business analytics that demonstrates agent-based…

  3. The Effect of Learning Based on Technology Model and Assessment Technique toward Thermodynamic Learning Achievement

    Science.gov (United States)

    Makahinda, T.

    2018-02-01

    The purpose of this research is to find out the effect of learning model based on technology and assessment technique toward thermodynamic achievement by controlling students intelligence. This research is an experimental research. The sample is taken through cluster random sampling with the total respondent of 80 students. The result of the research shows that the result of learning of thermodynamics of students who taught the learning model of environmental utilization is higher than the learning result of student thermodynamics taught by simulation animation, after controlling student intelligence. There is influence of student interaction, and the subject between models of technology-based learning with assessment technique to student learning result of Thermodynamics, after controlling student intelligence. Based on the finding in the lecture then should be used a thermodynamic model of the learning environment with the use of project assessment technique.

  4. Collaborative learning model inquiring based on digital game

    Science.gov (United States)

    Yuan, Jiugen; Xing, Ruonan

    2012-04-01

    With the development of computer education software, digital educational game has become an important part in our life, entertainment and education. Therefore how to make full use of digital game's teaching functions and educate through entertainment has become the focus of current research. The thesis make a connection between educational game and collaborative learning, the current popular teaching model, and concludes digital game-based collaborative learning model combined with teaching practice.

  5. The "proactive" model of learning: Integrative framework for model-free and model-based reinforcement learning utilizing the associative learning-based proactive brain concept.

    Science.gov (United States)

    Zsuga, Judit; Biro, Klara; Papp, Csaba; Tajti, Gabor; Gesztelyi, Rudolf

    2016-02-01

    Reinforcement learning (RL) is a powerful concept underlying forms of associative learning governed by the use of a scalar reward signal, with learning taking place if expectations are violated. RL may be assessed using model-based and model-free approaches. Model-based reinforcement learning involves the amygdala, the hippocampus, and the orbitofrontal cortex (OFC). The model-free system involves the pedunculopontine-tegmental nucleus (PPTgN), the ventral tegmental area (VTA) and the ventral striatum (VS). Based on the functional connectivity of VS, model-free and model based RL systems center on the VS that by integrating model-free signals (received as reward prediction error) and model-based reward related input computes value. Using the concept of reinforcement learning agent we propose that the VS serves as the value function component of the RL agent. Regarding the model utilized for model-based computations we turned to the proactive brain concept, which offers an ubiquitous function for the default network based on its great functional overlap with contextual associative areas. Hence, by means of the default network the brain continuously organizes its environment into context frames enabling the formulation of analogy-based association that are turned into predictions of what to expect. The OFC integrates reward-related information into context frames upon computing reward expectation by compiling stimulus-reward and context-reward information offered by the amygdala and hippocampus, respectively. Furthermore we suggest that the integration of model-based expectations regarding reward into the value signal is further supported by the efferent of the OFC that reach structures canonical for model-free learning (e.g., the PPTgN, VTA, and VS). (c) 2016 APA, all rights reserved).

  6. The Effects of ePortfolio-Based Learning Model on Student Self-Regulated Learning

    Science.gov (United States)

    Nguyen, Lap Trung; Ikeda, Mitsuru

    2015-01-01

    Self-regulated learners are aware of their knowledge and skills and proactive in learning. They view learning as a controllable process and accept more responsibility for the results of this process. The research described in this article proposes, implements, and evaluates an ePortfolio-based self-regulated learning model. An ePortfolio system…

  7. The development of learning material using learning cycle 5E model based stem to improve students’ learning outcomes in Thermochemistry

    Science.gov (United States)

    sugiarti, A. C.; suyatno, S.; Sanjaya, I. G. M.

    2018-04-01

    The objective of this study is describing the feasibility of Learning Cycle 5E STEM (Science, Technology, Engineering, and Mathematics) based learning material which is appropriate to improve students’ learning achievement in Thermochemistry. The study design used 4-D models and one group pretest-posttest design to obtain the information about the improvement of sudents’ learning outcomes. The subject was learning cycle 5E based STEM learning materials which the data were collected from 30 students of Science class at 11th Grade. The techniques used in this study were validation, observation, test, and questionnaire. Some result attain: (1) all the learning materials contents were valid, (2) the practicality and the effectiveness of all the learning materials contents were classified as good. The conclution of this study based on those three condition, the Learnig Cycle 5E based STEM learning materials is appropriate to improve students’ learning outcomes in studying Thermochemistry.

  8. Flipped classroom model for learning evidence-based medicine.

    Science.gov (United States)

    Rucker, Sydney Y; Ozdogan, Zulfukar; Al Achkar, Morhaf

    2017-01-01

    Journal club (JC), as a pedagogical strategy, has long been used in graduate medical education (GME). As evidence-based medicine (EBM) becomes a mainstay in GME, traditional models of JC present a number of insufficiencies and call for novel models of instruction. A flipped classroom model appears to be an ideal strategy to meet the demands to connect evidence to practice while creating engaged, culturally competent, and technologically literate physicians. In this article, we describe a novel model of flipped classroom in JC. We present the flow of learning activities during the online and face-to-face instruction, and then we highlight specific considerations for implementing a flipped classroom model. We show that implementing a flipped classroom model to teach EBM in a residency program not only is possible but also may constitute improved learning opportunity for residents. Follow-up work is needed to evaluate the effectiveness of this model on both learning and clinical practice.

  9. Runtime Optimizations for Tree-Based Machine Learning Models

    NARCIS (Netherlands)

    N. Asadi; J.J.P. Lin (Jimmy); A.P. de Vries (Arjen)

    2014-01-01

    htmlabstractTree-based models have proven to be an effective solution for web ranking as well as other machine learning problems in diverse domains. This paper focuses on optimizing the runtime performance of applying such models to make predictions, specifically using gradient-boosted regression

  10. Model-Based Learning Environment Based on The Concept IPS School-Based Management

    Directory of Open Access Journals (Sweden)

    Hamid Darmadi

    2017-03-01

    Full Text Available The results showed: (1 learning model IPS-oriented environment can grow and not you love the cultural values of the area as a basis for the development of national culture, (2 community participation, and the role of government in implementing learning model of IPS-based environment provides a positive impact for the improvement of management school resources, (3 learning model IPS-based environment effectively creating a way of life together peacefully, increase the intensity of togetherness and mutual respect (4 learning model IPS-based environment can improve student learning outcomes, (5 there are differences in the expression of attitudes and results learning among students who are located in the area of conflict with students who are outside the area of conflict (6 analysis of the scale of attitudes among school students da SMA result rewards high school students to the values of unity and nation, respect for diversity and peaceful coexistence, It is recommended that the Department of Education authority as an institution of Trustees and the development of social and cultural values in the province can apply IPS learning model based environments.

  11. Theory-based Bayesian models of inductive learning and reasoning.

    Science.gov (United States)

    Tenenbaum, Joshua B; Griffiths, Thomas L; Kemp, Charles

    2006-07-01

    Inductive inference allows humans to make powerful generalizations from sparse data when learning about word meanings, unobserved properties, causal relationships, and many other aspects of the world. Traditional accounts of induction emphasize either the power of statistical learning, or the importance of strong constraints from structured domain knowledge, intuitive theories or schemas. We argue that both components are necessary to explain the nature, use and acquisition of human knowledge, and we introduce a theory-based Bayesian framework for modeling inductive learning and reasoning as statistical inferences over structured knowledge representations.

  12. Polarimetric SAR image classification based on discriminative dictionary learning model

    Science.gov (United States)

    Sang, Cheng Wei; Sun, Hong

    2018-03-01

    Polarimetric SAR (PolSAR) image classification is one of the important applications of PolSAR remote sensing. It is a difficult high-dimension nonlinear mapping problem, the sparse representations based on learning overcomplete dictionary have shown great potential to solve such problem. The overcomplete dictionary plays an important role in PolSAR image classification, however for PolSAR image complex scenes, features shared by different classes will weaken the discrimination of learned dictionary, so as to degrade classification performance. In this paper, we propose a novel overcomplete dictionary learning model to enhance the discrimination of dictionary. The learned overcomplete dictionary by the proposed model is more discriminative and very suitable for PolSAR classification.

  13. Personalised learning object based on multi-agent model and learners’ learning styles

    Directory of Open Access Journals (Sweden)

    Noppamas Pukkhem

    2011-09-01

    Full Text Available A multi-agent model is proposed in which learning styles and a word analysis technique to create a learning object recommendation system are used. On the basis of a learning style-based design, a concept map combination model is proposed to filter out unsuitable learning concepts from a given course. Our learner model classifies learners into eight styles and implements compatible computational methods consisting of three recommendations: i non-personalised, ii preferred feature-based, and iii neighbour-based collaborative filtering. The analysis of preference error (PE was performed by comparing the actual preferred learning object with the predicted one. In our experiments, the feature-based recommendation algorithm has the fewest PE.

  14. PENGGUNAAN MODEL PROBLEM BASED LEARNING BERBANTUAN E-LEARNING TERHADAP KEMANDIRIAN BELAJAR MAHASISWA

    Directory of Open Access Journals (Sweden)

    Jusep Saputra

    2017-11-01

    Full Text Available Self-regulated learning of learners can be achieved, if in the process of learning mathematics provides an open opportunity for students to learn independently. This research is a mixed method type embedded design, which aims to do studies focused on the use of the Problem Based Learning (PBL model assisted e-learning to student self-regulated learning. Sample selection is done on the purposive sampling and was taken 2 class contracting courses of school math III. Class A numbered 50 members, 24 the superior group and 26 the low group, given the treatment with PBL models assisted e-learning and class B numbered 50, 27 the superior group and 23 the low group, with expository. Instruments used in this research is self-regulated learning questionnaire with Likert scale. Based on data analysis we concluded that (1 Self-regulated learning of superior and low student who obtains aided PBL models assisted e-learning is better than self-regulated learning of superior and low superior students who obtain expository.

  15. Competence Models in Technology-enhanced Competence-based Learning

    NARCIS (Netherlands)

    Sampson, Demetrios; Fytros, Demetrios

    2008-01-01

    Please cite as: Sampson, D., & Fytros, D. (2008). Competence Models in Technology-enhanced Competence-based Learning. In H. H. Adelsberger, Kinshuk, J. M. Pawlowski & D. Sampson (Eds.), International Handbook on Information Technologies for Education and Training, 2nd Edition, Springer, June 2008

  16. Model brain based learning (BBL and whole brain teaching (WBT in learning

    Directory of Open Access Journals (Sweden)

    Baiq Sri Handayani

    2017-08-01

    Full Text Available The learning process is a process of change in behavior as a form of the result of learning. The learning model is a crucial component of the success of the learning process. The learning model is growing fastly, and each model has different characteristics. Teachers are required to be able to understand each model to teach the students optimally by matching the materials and the learning model. The best of the learning model is the model that based on the brain system in learning that are the model of Brain Based Learning (BBL and the model of Whole Brain Teaching (WBT. The purposes of this article are to obtain information related to (1 the brain’s natural learning system, (2 analyze the characteristics of the model BBL and WBT based on theory, brain sections that play a role associated with syntax, similarities, and differences, (3 explain the distinctive characteristics of both models in comparison to other models. The results of this study are: (1 the brain’s natural learning system are: (a the nerves in each hemisphere do not work independently, (b doing more activities can connect more brain nerves, (c the right hemisphere controls the left side motoric sensor of the body, and vice versa; (2 the characteristics of BBL and WBT are: (a BBL is based on the brain’s structure and function, while the model WBT is based on the instructional approach, neurolinguistic, and body language, (b the parts of the brain that work in BBL are: cerebellum, cerebral cortex, frontal lobe, limbic system, and prefrontal cortex; whereas the parts that work WBT are: prefrontal cortex, visual cortex, motor cortex, limbic system, and amygdala, (c the similarities between them are that they both rely on the brain’s system and they both promote gesture in learning, whereas the differences are on the view of the purposes of gestures and the learning theory that they rely on. BBL relies on cognitive theory while WBT relies on social theory; (3 the typical

  17. Development Of Entrepreneur Learning Model Based On Problem Based Learning To Increase Competency Independence And Creativity Students Of Industrial Engineering

    Directory of Open Access Journals (Sweden)

    Leola Dewiyani

    2017-10-01

    Full Text Available Currently it is undeniable that the competition to get a job is very tight and of course universities have an important role in printing human resources that can compete globally not least with the Department of Industrial Engineering Faculty of Engineering Muhammadiyah University of Jakarta FT UMJ. Problems that occur is based on the analysis obtained from the track record of graduates researchers found that 60 percent of students of Industrial Engineering FT UMJ work not in accordance with the level of education owned so financially their income is still below the standard. This study aims to improve the competence of students of Industrial Engineering Department FT UMJ in entrepreneurship courses especially through the development of Problem Based Learning based learning model. Specific targets of this research were conducted with the aim to identify and analyze the need to implement learning model based on Problem Based Learning Entrepreneurship and to design and develop the model of entrepreneurship based on Problem Based Learning to improve the competence independence and creativity of Industrial Engineering students of FT UMJ in Entrepreneurship course. To achieve the above objectives this research uses research and development R amp D method. The product produced in this research is the detail of learning model of entrepreneurial model based on Problem Based Learning entrepreneurship model based on Problem Based Learning and international journals

  18. Flipped classroom model for learning evidence-based medicine

    Directory of Open Access Journals (Sweden)

    Rucker SY

    2017-08-01

    Full Text Available Sydney Y Rucker,1 Zulfukar Ozdogan,1 Morhaf Al Achkar2 1School of Education, Indiana University, Bloomington, IN, 2Department of Family Medicine, School of Medicine, University of Washington, Seattle, WA, USA Abstract: Journal club (JC, as a pedagogical strategy, has long been used in graduate medical education (GME. As evidence-based medicine (EBM becomes a mainstay in GME, traditional models of JC present a number of insufficiencies and call for novel models of instruction. A flipped classroom model appears to be an ideal strategy to meet the demands to connect evidence to practice while creating engaged, culturally competent, and technologically literate physicians. In this article, we describe a novel model of flipped classroom in JC. We present the flow of learning activities during the online and face-to-face instruction, and then we highlight specific considerations for implementing a flipped classroom model. We show that implementing a flipped classroom model to teach EBM in a residency program not only is possible but also may constitute improved learning opportunity for residents. Follow-up work is needed to evaluate the effectiveness of this model on both learning and clinical practice. Keywords: evidence-based medicine, flipped classroom, residency education

  19. Learning-based stochastic object models for characterizing anatomical variations

    Science.gov (United States)

    Dolly, Steven R.; Lou, Yang; Anastasio, Mark A.; Li, Hua

    2018-03-01

    It is widely known that the optimization of imaging systems based on objective, task-based measures of image quality via computer-simulation requires the use of a stochastic object model (SOM). However, the development of computationally tractable SOMs that can accurately model the statistical variations in human anatomy within a specified ensemble of patients remains a challenging task. Previously reported numerical anatomic models lack the ability to accurately model inter-patient and inter-organ variations in human anatomy among a broad patient population, mainly because they are established on image data corresponding to a few of patients and individual anatomic organs. This may introduce phantom-specific bias into computer-simulation studies, where the study result is heavily dependent on which phantom is used. In certain applications, however, databases of high-quality volumetric images and organ contours are available that can facilitate this SOM development. In this work, a novel and tractable methodology for learning a SOM and generating numerical phantoms from a set of volumetric training images is developed. The proposed methodology learns geometric attribute distributions (GAD) of human anatomic organs from a broad patient population, which characterize both centroid relationships between neighboring organs and anatomic shape similarity of individual organs among patients. By randomly sampling the learned centroid and shape GADs with the constraints of the respective principal attribute variations learned from the training data, an ensemble of stochastic objects can be created. The randomness in organ shape and position reflects the learned variability of human anatomy. To demonstrate the methodology, a SOM of an adult male pelvis is computed and examples of corresponding numerical phantoms are created.

  20. Modeling the learning of the English past tense with memory-based learning

    NARCIS (Netherlands)

    van Noord, Rik; Spenader, Jennifer K.

    2015-01-01

    Modeling the acquisition and final state of English past tense inflection has been an ongoing challenge since the mid-eighties. A number of rule-based and connectionist models have been proposed over the years, but the former usually have no explanation of how the rules are learned and the latter

  1. The Use of Problem-Based Learning Model to Improve Quality Learning Students Morals

    Science.gov (United States)

    Nurzaman

    2017-01-01

    Model of moral cultivation in MTsN Bangunharja done using three methods, classical cultivation methods, extra-curricular activities in the form of religious activities, scouting, sports, and Islamic art, and habituation of morals. Problem base learning models in MTsN Bangunharja applied using the following steps: find the problem, define the…

  2. Use of the 5E learning cycle model combined with problem-based learning for a fundamentals of nursing course.

    Science.gov (United States)

    Jun, Won Hee; Lee, Eun Ju; Park, Han Jong; Chang, Ae Kyung; Kim, Mi Ja

    2013-12-01

    The 5E learning cycle model has shown a positive effect on student learning in science education, particularly in courses with theory and practice components. Combining problem-based learning (PBL) with the 5E learning cycle was suggested as a better option for students' learning of theory and practice. The purpose of this study was to compare the effects of the traditional learning method with the 5E learning cycle model with PBL. The control group (n = 78) was subjected to a learning method that consisted of lecture and practice. The experimental group (n = 83) learned by using the 5E learning cycle model with PBL. The results showed that the experimental group had significantly improved self-efficacy, critical thinking, learning attitude, and learning satisfaction. Such an approach could be used in other countries to enhance students' learning of fundamental nursing. Copyright 2013, SLACK Incorporated.

  3. A model for hypermedia learning environments based on electronic books

    Directory of Open Access Journals (Sweden)

    Ignacio Aedo

    1997-12-01

    Full Text Available Current hypermedia learning environments do not have a common development basis. Their designers have often used ad-hoc solutions to solve the learning problems they have encountered. However, hypermedia technology can take advantage of employing a theoretical scheme - a model - which takes into account various kinds of learning activities, and solves some of the problems associated with its use in the learning process. The model can provide designers with the tools for creating a hypermedia learning system, by allowing the elements and functions involved in the definition of a specific application to be formally represented.

  4. Perbandingan antara Keefektifan Model Guided Discovery Learning dan Project-Based Learning pada Matakuliah Geometri

    Directory of Open Access Journals (Sweden)

    Okky Riswandha Imawan

    2015-12-01

    Abstract This research aims to describe the effectiveness and effectiveness differences of the Guided Discovery Learning (GDL Model and the Project Based Learning (PjBL Model in terms of achievement, self-confidence, and critical thinking skills of students on the Solid Geometry subjects. This research was quasi experimental. The research subjects were two undergraduate classes of Mathematics Education Program, Ahmad Dahlan University, in their second semester, established at random. The data analysis to test the effectiveness of the GDL and PjBL Models in terms of each of the dependent variables used the t-test. The data analysis to test differences between effectiveness of the GDL and that of the PjBL Model used the MANOVA test. The results of this research show that viewed from achievement, self confidence, and critical thinking skills of the students are the application of the GDL Model on Solid Geometry subject is effective, the application of the PjBL Model on Solid Geometry subject is effective, and there is no difference in the effectiveness of GDL and PjBL Models on Solid Geometry subject in terms of achievement, self confidence, and critical thinking skills of the students. Keywords: guided discovery learning model, project-based learning model, achievement, self-confidence, critical thinking skills

  5. Machine learning based switching model for electricity load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Fan, Shu; Lee, Wei-Jen [Energy Systems Research Center, The University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen, Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan)

    2008-06-15

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma. (author)

  6. Machine learning based switching model for electricity load forecasting

    Energy Technology Data Exchange (ETDEWEB)

    Fan Shu [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States); Chen Luonan [Department of Electronics, Information and Communication Engineering, Osaka Sangyo University, 3-1-1 Nakagaito, Daito, Osaka 574-0013 (Japan); Lee, Weijen [Energy Systems Research Center, University of Texas at Arlington, 416 S. College Street, Arlington, TX 76019 (United States)], E-mail: wlee@uta.edu

    2008-06-15

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma.

  7. Machine learning based switching model for electricity load forecasting

    International Nuclear Information System (INIS)

    Fan Shu; Chen Luonan; Lee, Weijen

    2008-01-01

    In deregulated power markets, forecasting electricity loads is one of the most essential tasks for system planning, operation and decision making. Based on an integration of two machine learning techniques: Bayesian clustering by dynamics (BCD) and support vector regression (SVR), this paper proposes a novel forecasting model for day ahead electricity load forecasting. The proposed model adopts an integrated architecture to handle the non-stationarity of time series. Firstly, a BCD classifier is applied to cluster the input data set into several subsets by the dynamics of the time series in an unsupervised manner. Then, groups of SVRs are used to fit the training data of each subset in a supervised way. The effectiveness of the proposed model is demonstrated with actual data taken from the New York ISO and the Western Farmers Electric Cooperative in Oklahoma

  8. Variability in Dopamine Genes Dissociates Model-Based and Model-Free Reinforcement Learning.

    Science.gov (United States)

    Doll, Bradley B; Bath, Kevin G; Daw, Nathaniel D; Frank, Michael J

    2016-01-27

    Considerable evidence suggests that multiple learning systems can drive behavior. Choice can proceed reflexively from previous actions and their associated outcomes, as captured by "model-free" learning algorithms, or flexibly from prospective consideration of outcomes that might occur, as captured by "model-based" learning algorithms. However, differential contributions of dopamine to these systems are poorly understood. Dopamine is widely thought to support model-free learning by modulating plasticity in striatum. Model-based learning may also be affected by these striatal effects, or by other dopaminergic effects elsewhere, notably on prefrontal working memory function. Indeed, prominent demonstrations linking striatal dopamine to putatively model-free learning did not rule out model-based effects, whereas other studies have reported dopaminergic modulation of verifiably model-based learning, but without distinguishing a prefrontal versus striatal locus. To clarify the relationships between dopamine, neural systems, and learning strategies, we combine a genetic association approach in humans with two well-studied reinforcement learning tasks: one isolating model-based from model-free behavior and the other sensitive to key aspects of striatal plasticity. Prefrontal function was indexed by a polymorphism in the COMT gene, differences of which reflect dopamine levels in the prefrontal cortex. This polymorphism has been associated with differences in prefrontal activity and working memory. Striatal function was indexed by a gene coding for DARPP-32, which is densely expressed in the striatum where it is necessary for synaptic plasticity. We found evidence for our hypothesis that variations in prefrontal dopamine relate to model-based learning, whereas variations in striatal dopamine function relate to model-free learning. Decisions can stem reflexively from their previously associated outcomes or flexibly from deliberative consideration of potential choice outcomes

  9. Safe robot execution in model-based reinforcement learning

    OpenAIRE

    Martínez Martínez, David; Alenyà Ribas, Guillem; Torras, Carme

    2015-01-01

    Task learning in robotics requires repeatedly executing the same actions in different states to learn the model of the task. However, in real-world domains, there are usually sequences of actions that, if executed, may produce unrecoverable errors (e.g. breaking an object). Robots should avoid repeating such errors when learning, and thus explore the state space in a more intelligent way. This requires identifying dangerous action effects to avoid including such actions in the generated plans...

  10. Functional networks inference from rule-based machine learning models.

    Science.gov (United States)

    Lazzarini, Nicola; Widera, Paweł; Williamson, Stuart; Heer, Rakesh; Krasnogor, Natalio; Bacardit, Jaume

    2016-01-01

    Functional networks play an important role in the analysis of biological processes and systems. The inference of these networks from high-throughput (-omics) data is an area of intense research. So far, the similarity-based inference paradigm (e.g. gene co-expression) has been the most popular approach. It assumes a functional relationship between genes which are expressed at similar levels across different samples. An alternative to this paradigm is the inference of relationships from the structure of machine learning models. These models are able to capture complex relationships between variables, that often are different/complementary to the similarity-based methods. We propose a protocol to infer functional networks from machine learning models, called FuNeL. It assumes, that genes used together within a rule-based machine learning model to classify the samples, might also be functionally related at a biological level. The protocol is first tested on synthetic datasets and then evaluated on a test suite of 8 real-world datasets related to human cancer. The networks inferred from the real-world data are compared against gene co-expression networks of equal size, generated with 3 different methods. The comparison is performed from two different points of view. We analyse the enriched biological terms in the set of network nodes and the relationships between known disease-associated genes in a context of the network topology. The comparison confirms both the biological relevance and the complementary character of the knowledge captured by the FuNeL networks in relation to similarity-based methods and demonstrates its potential to identify known disease associations as core elements of the network. Finally, using a prostate cancer dataset as a case study, we confirm that the biological knowledge captured by our method is relevant to the disease and consistent with the specialised literature and with an independent dataset not used in the inference process. The

  11. Students’ Mathematical Problem-Solving Abilities Through The Application of Learning Models Problem Based Learning

    Science.gov (United States)

    Nasution, M. L.; Yerizon, Y.; Gusmiyanti, R.

    2018-04-01

    One of the purpose mathematic learning is to develop problem solving abilities. Problem solving is obtained through experience in questioning non-routine. Improving students’ mathematical problem-solving abilities required an appropriate strategy in learning activities one of them is models problem based learning (PBL). Thus, the purpose of this research is to determine whether the problem solving abilities of mathematical students’ who learn to use PBL better than on the ability of students’ mathematical problem solving by applying conventional learning. This research included quasi experiment with static group design and population is students class XI MIA SMAN 1 Lubuk Alung. Class experiment in the class XI MIA 5 and class control in the class XI MIA 6. The instrument of final test students’ mathematical problem solving used essay form. The result of data final test in analyzed with t-test. The result is students’ mathematical problem solving abilities with PBL better then on the ability of students’ mathematical problem solving by applying conventional learning. It’s seen from the high percentage achieved by the group of students who learn to use PBL for each indicator of students’ mathematical problem solving.

  12. Dopamine selectively remediates 'model-based' reward learning: a computational approach.

    Science.gov (United States)

    Sharp, Madeleine E; Foerde, Karin; Daw, Nathaniel D; Shohamy, Daphna

    2016-02-01

    Patients with loss of dopamine due to Parkinson's disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from 'model-free' learning. The other, 'model-based' learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson's disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson's disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson's disease may be related to an inability to pursue reward based on complete representations of the environment. © The Author (2015). Published by Oxford University Press on behalf of the Guarantors of Brain. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

  13. Improving a Deep Learning based RGB-D Object Recognition Model by Ensemble Learning

    DEFF Research Database (Denmark)

    Aakerberg, Andreas; Nasrollahi, Kamal; Heder, Thomas

    2018-01-01

    Augmenting RGB images with depth information is a well-known method to significantly improve the recognition accuracy of object recognition models. Another method to im- prove the performance of visual recognition models is ensemble learning. However, this method has not been widely explored...... in combination with deep convolutional neural network based RGB-D object recognition models. Hence, in this paper, we form different ensembles of complementary deep convolutional neural network models, and show that this can be used to increase the recognition performance beyond existing limits. Experiments...

  14. Effects of Problem-Based Learning Model versus Expository Model and Motivation to Achieve for Student's Physic Learning Result of Senior High School at Class XI

    Science.gov (United States)

    Prayekti

    2016-01-01

    "Problem-based learning" (PBL) is one of an innovative learning model which can provide an active learning to student, include the motivation to achieve showed by student when the learning is in progress. This research is aimed to know: (1) differences of physic learning result for student group which taught by PBL versus expository…

  15. Problem solving based learning model with multiple representations to improve student's mental modelling ability on physics

    Science.gov (United States)

    Haili, Hasnawati; Maknun, Johar; Siahaan, Parsaoran

    2017-08-01

    Physics is a lessons that related to students' daily experience. Therefore, before the students studying in class formally, actually they have already have a visualization and prior knowledge about natural phenomenon and could wide it themselves. The learning process in class should be aimed to detect, process, construct, and use students' mental model. So, students' mental model agree with and builds in the right concept. The previous study held in MAN 1 Muna informs that in learning process the teacher did not pay attention students' mental model. As a consequence, the learning process has not tried to build students' mental modelling ability (MMA). The purpose of this study is to describe the improvement of students' MMA as a effect of problem solving based learning model with multiple representations approach. This study is pre experimental design with one group pre post. It is conducted in XI IPA MAN 1 Muna 2016/2017. Data collection uses problem solving test concept the kinetic theory of gasses and interview to get students' MMA. The result of this study is clarification students' MMA which is categorized in 3 category; High Mental Modelling Ability (H-MMA) for 7Mental Modelling Ability (M-MMA) for 3Mental Modelling Ability (L-MMA) for 0 ≤ x ≤ 3 score. The result shows that problem solving based learning model with multiple representations approach can be an alternative to be applied in improving students' MMA.

  16. The Experimental Research on E-Learning Instructional Design Model Based on Cognitive Flexibility Theory

    Science.gov (United States)

    Cao, Xianzhong; Wang, Feng; Zheng, Zhongmei

    The paper reports an educational experiment on the e-Learning instructional design model based on Cognitive Flexibility Theory, the experiment were made to explore the feasibility and effectiveness of the model in promoting the learning quality in ill-structured domain. The study performed the experiment on two groups of students: one group learned through the system designed by the model and the other learned by the traditional method. The results of the experiment indicate that the e-Learning designed through the model is helpful to promote the intrinsic motivation, learning quality in ill-structured domains, ability to resolve ill-structured problem and creative thinking ability of the students.

  17. Strategies to Enhance Online Learning Teams. Team Assessment and Diagnostics Instrument and Agent-based Modeling

    Science.gov (United States)

    2010-08-12

    Strategies to Enhance Online Learning Teams Team Assessment and Diagnostics Instrument and Agent-based Modeling Tristan E. Johnson, Ph.D. Learning ...REPORT DATE AUG 2010 2. REPORT TYPE 3. DATES COVERED 00-00-2010 to 00-00-2010 4. TITLE AND SUBTITLE Strategies to Enhance Online Learning ...TeamsTeam Strategies to Enhance Online Learning Teams: Team Assessment and Diagnostics Instrument and Agent-based Modeling 5a. CONTRACT NUMBER 5b. GRANT

  18. Project-Based Learning Using Discussion and Lesson-Learned Methods via Social Media Model for Enhancing Problem Solving Skills

    Science.gov (United States)

    Jewpanich, Chaiwat; Piriyasurawong, Pallop

    2015-01-01

    This research aims to 1) develop the project-based learning using discussion and lesson-learned methods via social media model (PBL-DLL SoMe Model) used for enhancing problem solving skills of undergraduate in education student, and 2) evaluate the PBL-DLL SoMe Model used for enhancing problem solving skills of undergraduate in education student.…

  19. Ready to learn physics: a team-based learning model for first year university

    Science.gov (United States)

    Parappilly, Maria; Schmidt, Lisa; De Ritter, Samantha

    2015-09-01

    Team-based learning (TBL) is an established model of group work which aims to improve students' ability to apply discipline-related content. TBL consists of a readiness assurance process (RAP), student groups and application activities. While TBL has not been implemented widely in science, technology, engineering and mathematics disciplines, it has been effective in improving student learning in other disciplines. This paper describes the incorporation of TBL activities into a non-calculus based introductory level physics topic—Physics for the Modern World. Students were given pre-class preparation materials and an individual RAP online test before the workshops. The pre-workshop individual RAP test ensured that all students were exposed to concept-based questions before their workshops and motivated them to use the preparatory materials in readiness for the workshop. The students were placed into random teams and during the first part of the workshop, the teams went through a subset of the quiz questions (team RAP test) and in the remaining time, teams completed an in-class assignment. After the workshop students were allowed another attempt at the individual RAP test to see if their knowledge had improved. The ability of TBL to promote student learning of key concepts was evaluated by experiment using pre- and post- testing. The students’ perception of TBL was monitored by discussion posts and survey responses. Finally, the ability of TBL to support peer-peer interaction was evaluated by video analysis of the class. We found that the TBL process improved student learning; students did interact with each other in class; and the students had a positive view of TBL. To assess the transferability of this model to other topics, we conducted a comparison study with an environmental science topic which produced similar results. Our study supports the use of this TBL model in science topics.

  20. Towards the Sigma Online Learning Model for crowdsourced recommendations of good web-based learning resources

    OpenAIRE

    Aaberg, Robin Garen

    2016-01-01

    The web based learning resources is believed to be playing an active role in the learning environment of higher education today. This qualitative study is exploring how students at Bergen University College incorporate web-based learning resources in their learning activities. At the core of this research is the problem of retrieving good web-resources after their first discovery. Usefull and knowledge granting web-resources are discovered within a context of topics, objectives. It is here ar...

  1. Development of Learning Models Based on Problem Solving and Meaningful Learning Standards by Expert Validity for Animal Development Course

    Science.gov (United States)

    Lufri, L.; Fitri, R.; Yogica, R.

    2018-04-01

    The purpose of this study is to produce a learning model based on problem solving and meaningful learning standards by expert assessment or validation for the course of Animal Development. This research is a development research that produce the product in the form of learning model, which consist of sub product, namely: the syntax of learning model and student worksheets. All of these products are standardized through expert validation. The research data is the level of validity of all sub products obtained using questionnaire, filled by validators from various field of expertise (field of study, learning strategy, Bahasa). Data were analysed using descriptive statistics. The result of the research shows that the problem solving and meaningful learning model has been produced. Sub products declared appropriate by expert include the syntax of learning model and student worksheet.

  2. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed

    2017-02-07

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals\\'s mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users\\' check-ins and their network of friends, without impairing the model\\'s complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  3. Comparison the Application of PBL (Project Based Learning and PBL (Problem Based Learning Learning Model on Online Marketing Subjects

    Directory of Open Access Journals (Sweden)

    Agnes Dini Mardani

    2017-09-01

    Full Text Available Purpose of this study are (1 the application of learning PjBL with PBL to improve study results students, (2 assessing the domain affective, cognitive, and psychomotor, (3 the difference study results use the PjBL with PBL to improve study results students. The research is research quantitative and including research apparent experiment (quasi eksperiment by taking sample class two classes X PM 1 as a class experiment and class X PM 2 as a class control. Research instruments used for data collection namely: (1 tests to pretes and postest used to determine the cognitive assessment, (2 sheets observation affective, (3 sheets of the process for the psychomotor. The trial research instruments use the validity and reabilitas. Analysis techniques data using: (1 test a prerequisite analysis consisting of normality test and the homogeneity (2 T test unpaired which ended with the help of computer programs spss. Based on the result of this research can be concluded that: (1 the application of PjBL (Project Based Learning and PBL (Problem Based Learning should be conducted well in accordance syntax learning, (2 assessing the cognitive students have a difference and class experiment having an average higher than class control, (3 assessing the results affective students have a difference and on the application of PjBL is better than PBL.

  4. Learning Outcomes in Vocational Education: A Business Plan Development by Production-Based Learning Model Approach

    Science.gov (United States)

    Kusumaningrum, Indrati; Hidayat, Hendra; Ganefri; Anori, Sartika; Dewy, Mega Silfia

    2016-01-01

    This article describes the development of a business plan by using production-based learning approach. In addition, this development also aims to maximize learning outcomes in vocational education. Preliminary analysis of curriculum and learning and the needs of the market and society become the basic for business plan development. To produce a…

  5. Learning from Your Network of Friends: A Trajectory Representation Learning Model Based on Online Social Ties

    KAUST Repository

    Alharbi, Basma Mohammed; Zhang, Xiangliang

    2017-01-01

    Location-Based Social Networks (LBSNs) capture individuals whereabouts for a large portion of the population. To utilize this data for user (location)-similarity based tasks, one must map the raw data into a low-dimensional uniform feature space. However, due to the nature of LBSNs, many users have sparse and incomplete check-ins. In this work, we propose to overcome this issue by leveraging the network of friends, when learning the new feature space. We first analyze the impact of friends on individuals's mobility, and show that individuals trajectories are correlated with thoseof their friends and friends of friends (2-hop friends) in an online setting. Based on our observation, we propose a mixed-membership model that infers global mobility patterns from users' check-ins and their network of friends, without impairing the model's complexity. Our proposed model infers global patterns and learns new representations for both usersand locations simultaneously. We evaluate the inferred patterns and compare the quality of the new user representation against baseline methods on a social link prediction problem.

  6. Model-based and model-free Pavlovian reward learning: revaluation, revision, and revelation.

    Science.gov (United States)

    Dayan, Peter; Berridge, Kent C

    2014-06-01

    Evidence supports at least two methods for learning about reward and punishment and making predictions for guiding actions. One method, called model-free, progressively acquires cached estimates of the long-run values of circumstances and actions from retrospective experience. The other method, called model-based, uses representations of the environment, expectations, and prospective calculations to make cognitive predictions of future value. Extensive attention has been paid to both methods in computational analyses of instrumental learning. By contrast, although a full computational analysis has been lacking, Pavlovian learning and prediction has typically been presumed to be solely model-free. Here, we revise that presumption and review compelling evidence from Pavlovian revaluation experiments showing that Pavlovian predictions can involve their own form of model-based evaluation. In model-based Pavlovian evaluation, prevailing states of the body and brain influence value computations, and thereby produce powerful incentive motivations that can sometimes be quite new. We consider the consequences of this revised Pavlovian view for the computational landscape of prediction, response, and choice. We also revisit differences between Pavlovian and instrumental learning in the control of incentive motivation.

  7. Advances in Bayesian Model Based Clustering Using Particle Learning

    Energy Technology Data Exchange (ETDEWEB)

    Merl, D M

    2009-11-19

    Recent work by Carvalho, Johannes, Lopes and Polson and Carvalho, Lopes, Polson and Taddy introduced a sequential Monte Carlo (SMC) alternative to traditional iterative Monte Carlo strategies (e.g. MCMC and EM) for Bayesian inference for a large class of dynamic models. The basis of SMC techniques involves representing the underlying inference problem as one of state space estimation, thus giving way to inference via particle filtering. The key insight of Carvalho et al was to construct the sequence of filtering distributions so as to make use of the posterior predictive distribution of the observable, a distribution usually only accessible in certain Bayesian settings. Access to this distribution allows a reversal of the usual propagate and resample steps characteristic of many SMC methods, thereby alleviating to a large extent many problems associated with particle degeneration. Furthermore, Carvalho et al point out that for many conjugate models the posterior distribution of the static variables can be parametrized in terms of [recursively defined] sufficient statistics of the previously observed data. For models where such sufficient statistics exist, particle learning as it is being called, is especially well suited for the analysis of streaming data do to the relative invariance of its algorithmic complexity with the number of data observations. Through a particle learning approach, a statistical model can be fit to data as the data is arriving, allowing at any instant during the observation process direct quantification of uncertainty surrounding underlying model parameters. Here we describe the use of a particle learning approach for fitting a standard Bayesian semiparametric mixture model as described in Carvalho, Lopes, Polson and Taddy. In Section 2 we briefly review the previously presented particle learning algorithm for the case of a Dirichlet process mixture of multivariate normals. In Section 3 we describe several novel extensions to the original

  8. Design and Implementation of Mobile Blended Learning Model Based on WeChat Public Platform

    Directory of Open Access Journals (Sweden)

    Han Yanyan

    2017-01-01

    Full Text Available Merging together the ideas of mobile learning, blended learning and flipped classroom, a Mobile Blended Learning Model (MBLM is constructed. Based on WeChat Public Platform (WPP, MBLM can optimize the instructional process and improve the learning efficiency. A Mobile Blended Learning System(MBLS is implemented by using MBLM, and it is constructed by both WPP and auxiliary learning system which based on Java Web. This system has reasonable designed function, easy operation, and beautiful interface, so it can effectively promote the popularization of MBLM.

  9. The Effectiveness of Learning Model of Basic Education with Character-Based at Universitas Muslim Indonesia

    Science.gov (United States)

    Rosmiati, Rosmiati; Mahmud, Alimuddin; Talib, Syamsul B.

    2016-01-01

    The purpose of this study was to determine the effectiveness of the basic education learning model with character-based through learning in the Universitas Muslim Indonesia. In addition, the research specifically examines the character of discipline, curiosity and responsibility. The specific target is to produce a basic education learning model…

  10. Critical-Inquiry-Based-Learning: Model of Learning to Promote Critical Thinking Ability of Pre-service Teachers

    Science.gov (United States)

    Prayogi, S.; Yuanita, L.; Wasis

    2018-01-01

    This study aimed to develop Critical-Inquiry-Based-Learning (CIBL) learning model to promote critical thinking (CT) ability of preservice teachers. The CIBL learning model was developed by meeting the criteria of validity, practicality, and effectiveness. Validation of the model involves 4 expert validators through the mechanism of the focus group discussion (FGD). CIBL learning model declared valid to promote CT ability, with the validity level (Va) of 4.20 and reliability (r) of 90,1% (very reliable). The practicality of the model was evaluated when it was implemented that involving 17 of preservice teachers. The CIBL learning model had been declared practice, its measuring from learning feasibility (LF) with very good criteria (LF-score = 4.75). The effectiveness of the model was evaluated from the improvement CT ability after the implementation of the model. CT ability were evaluated using the scoring technique adapted from Ennis-Weir Critical Thinking Essay Test. The average score of CT ability on pretest is - 1.53 (uncritical criteria), whereas on posttest is 8.76 (critical criteria), with N-gain score of 0.76 (high criteria). Based on the results of this study, it can be concluded that developed CIBL learning model is feasible to promote CT ability of preservice teachers.

  11. Students' Critical Thinking Skills in Chemistry Learning Using Local Culture-Based 7E Learning Cycle Model

    Science.gov (United States)

    Suardana, I. Nyoman; Redhana, I. Wayan; Sudiatmika, A. A. Istri Agung Rai; Selamat, I. Nyoman

    2018-01-01

    This research aimed at describing the effectiveness of the local culture-based 7E learning cycle model in improving students' critical thinking skills in chemistry learning. It was an experimental research with post-test only control group design. The population was the eleventh-grade students of senior high schools in Singaraja, Indonesia. The…

  12. The Influence of Problem Based Learning Model toward Students’ Activities and Learning Outcomes on Financial Management Subject

    Directory of Open Access Journals (Sweden)

    Han Tantri Hardini

    2016-12-01

    Full Text Available This research aims to know the influence of problem based learning model toward students’ activities and achievement on Financial Management subject for undergraduate program students of Accounting Education. It was a quantitative research that used true experimental design. Samples of this study were undergraduate program students of Accounting Education in the year of 2014. Class A were control class and class B were experimental class. Data were analyzed by using t-test in order to determine the differences of learning outcomes between control class and experimental class. Then, questionnaires were distributed to gather students’ activities information in their students’ learning model. Findings show that there is an influence of Problem Based Learning model toward students’ activities and learning outcomes on Financial Management subject for undergraduate program students of Accounting Education since t-count ≥ t-table. It is 6.120 ≥ 1.9904. Students’ learning activities with Problem Based Learning model are better than students who are taught by conventional learning model.

  13. The Relationship between Shared Mental Models and Task Performance in an Online Team- Based Learning Environment

    Science.gov (United States)

    Johnson, Tristan E.; Lee, Youngmin

    2008-01-01

    In an effort to better understand learning teams, this study examines the effects of shared mental models on team and individual performance. The results indicate that each team's shared mental model changed significantly over the time that subjects participated in team-based learning activities. The results also showed that the shared mental…

  14. A Computer-Assisted Learning Model Based on the Digital Game Exponential Reward System

    Science.gov (United States)

    Moon, Man-Ki; Jahng, Surng-Gahb; Kim, Tae-Yong

    2011-01-01

    The aim of this research was to construct a motivational model which would stimulate voluntary and proactive learning using digital game methods offering players more freedom and control. The theoretical framework of this research lays the foundation for a pedagogical learning model based on digital games. We analyzed the game reward system, which…

  15. Conceptualization of an R&D Based Learning-to-Innovate Model for Science Education

    Science.gov (United States)

    Lai, Oiki Sylvia

    2013-01-01

    The purpose of this research was to conceptualize an R & D based learning-to-innovate (LTI) model. The problem to be addressed was the lack of a theoretical L TI model, which would inform science pedagogy. The absorptive capacity (ACAP) lens was adopted to untangle the R & D LTI phenomenon into four learning processes: problem-solving via…

  16. Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

    Science.gov (United States)

    Wenhui, Ma; Yu, Wang

    2017-06-01

    Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

  17. Fuzzy comprehensive evaluation model of interuniversity collaborative learning based on network

    Directory of Open Access Journals (Sweden)

    Wenhui Ma

    2017-06-01

    Full Text Available Learning evaluation is an effective method, which plays an important role in the network education evaluation system. But most of the current network learning evaluation methods still use traditional university education evaluation system, which do not take into account of web-based learning characteristics, and they are difficult to fit the rapid development of interuniversity collaborative learning based on network. Fuzzy comprehensive evaluation method is used to evaluate interuniversity collaborative learning based on the combination of fuzzy theory and analytic hierarchy process. Analytic hierarchy process is used to determine the weight of evaluation factors of each layer and to carry out the consistency check. According to the fuzzy comprehensive evaluation method, we establish interuniversity collaborative learning evaluation mathematical model. The proposed scheme provides a new thought for interuniversity collaborative learning evaluation based on network.

  18. Pengembangan Model Pembelajaran Project Based Learning pada Mata Kuliah Computer Aided Design

    Directory of Open Access Journals (Sweden)

    Satoto Endar Nayono

    2013-09-01

    Full Text Available One of the key competencies of graduates majoring in Civil Engineering and Planning Education, Faculty of Engineering, Yogyakarta State University (YSU is able to plan buildings. CAD courses aim to train students to be able to pour the planning concepts into the picture. One of the obstacles faced in the course are concepts and pictures that created by the students often do not correspond to the standards used in the field. This study aims to develop a model of project-based learning so that the students’ pictures are more in line with the actual conditions in the field. This study was carried out through the stages as follows: (1 Pre test, (2 Planning of learning, (3 Implementation of the learning model of project-based learning, (4 monitoring and evaluation (5 Reflection and revision, (6 Implementation of learning in the next cycle, and (7 Evaluation of the learning outcomes. This study was conducted for four months in 2012 in the Department of Civil Engineering and Planning Education, Faculty of Engineering, YSU. The subjects of this study are the students who took the course of Computer Aided Design. The analysis of the data used descriptive qualitative and descriptive statistics. The results of this study were: (1 The implementation of project based learning model was proven to increase the learning process and the learning outcomes of students in the subject of CAD through the provision of buildings planning pictures tasks of school buildings based on the real conditions in the field. The task was delivered in every meeting and improved based on the feedback from their lecturers, (2 the learning model of project based learning will be easier to be implemented if it is accompanied by the model of peer tutoring and the learning model of PAIKEM.

  19. Interactive ontology-based user modelling for personalized learning content management

    NARCIS (Netherlands)

    Denaux, R.O.; Dimitrova, V.; Aroyo, L.M.; Aroyo, L.; Tasso, C.

    2004-01-01

    This position paper discusses the need for using interactive ontology-based user modeling to empower on the fly adaptation in learning information systems. We outline several open issues related to adaptive learning content delivery and present an approach to deal with these issues based on the

  20. Firm performance model in small and medium enterprises (SMEs) based on learning orientation and innovation

    Science.gov (United States)

    Lestari, E. R.; Ardianti, F. L.; Rachmawati, L.

    2018-03-01

    This study investigated the relationship between learning orientation, innovation, and firm performance. A conceptual model and hypothesis were empirically examined using structural equation modelling. The study involved a questionnaire-based survey of owners of small and medium enterprises (SMEs) operating in Batu City, Indonesia. The results showed that both variables of learning orientation and innovation effect positively on firm performance. Additionally, learning orientation has positive effect innovation. This study has implication for SMEs aiming at increasing their firm performance based on learning orientation and innovation capability.

  1. Problem-Based Learning Model Used to Scientific Approach Based Worksheet for Physics to Develop Senior High School Students Characters

    Science.gov (United States)

    Yulianti, D.

    2017-04-01

    The purpose of this study is to explore the application of Problem Based Learning(PBL) model aided withscientific approach and character integrated physics worksheets (LKS). Another purpose is to investigate the increase in cognitive and psychomotor learning outcomes and to know the character development of students. The method used in this study was the quasi-experiment. The instruments were observation and cognitive test. Worksheets can improve students’ cognitive, psychomotor learning outcomes. Improvements in cognitive learning results of students who have learned using worksheets are higher than students who received learning without worksheets. LKS can also develop the students’ character.

  2. Flipped classroom model for learning evidence-based medicine

    OpenAIRE

    Rucker, Sydney Y; Ozdogan, Zulfukar; Al Achkar, Morhaf

    2017-01-01

    Sydney Y Rucker,1 Zulfukar Ozdogan,1 Morhaf Al Achkar2 1School of Education, Indiana University, Bloomington, IN, 2Department of Family Medicine, School of Medicine, University of Washington, Seattle, WA, USA Abstract: Journal club (JC), as a pedagogical strategy, has long been used in graduate medical education (GME). As evidence-based medicine (EBM) becomes a mainstay in GME, traditional models of JC present a number of insufficiencies and call for novel models of instruction. A flipped cla...

  3. A New Profile Learning Model for Recommendation System based on Machine Learning Technique

    Directory of Open Access Journals (Sweden)

    Shereen H. Ali

    2016-03-01

    Full Text Available Recommender systems (RSs have been used to successfully address the information overload problem by providing personalized and targeted recommendations to the end users. RSs are software tools and techniques providing suggestions for items to be of use to a user, hence, they typically apply techniques and methodologies from Data Mining. The main contribution of this paper is to introduce a new user profile learning model to promote the recommendation accuracy of vertical recommendation systems. The proposed profile learning model employs the vertical classifier that has been used in multi classification module of the Intelligent Adaptive Vertical Recommendation (IAVR system to discover the user’s area of interest, and then build the user’s profile accordingly. Experimental results have proven the effectiveness of the proposed profile learning model, which accordingly will promote the recommendation accuracy.

  4. A Case-Based Learning Model in Orthodontics.

    Science.gov (United States)

    Engel, Francoise E.; Hendricson, William D.

    1994-01-01

    A case-based, student-centered instructional model designed to mimic orthodontic problem solving and decision making in dental general practice is described. Small groups of students analyze case data, then record and discuss their diagnoses and treatments. Students and instructors rated the seminars positively, and students reported improved…

  5. Second Graders' Emerging Particle Models of Matter in the Context of Learning through Model-Based Inquiry

    Science.gov (United States)

    Samarapungavan, Ala; Bryan, Lynn; Wills, Jamison

    2017-01-01

    In this paper, we present a study of second graders' learning about the nature of matter in the context of content-rich, model-based inquiry instruction. The goal of instruction was to help students learn to use simple particle models to explain states of matter and phase changes. We examined changes in students' ideas about matter, the coherence…

  6. Model Integrated Problem Solving Based Learning pada Perkuliahan Dasar-dasar Kimia Analitik

    OpenAIRE

    Indarini Dwi Pursitasari; Anna Permanasari

    2013-01-01

    Abstract: Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL) model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questio...

  7. Model Integrated Problem Solving Based Learning Pada Perkuliahan Dasar-dasar Kimia Analitik

    OpenAIRE

    Pursitasari, Indarini Dwi; Permanasari, Anna

    2012-01-01

    : Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL) model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questionnaire o...

  8. Analysis of creative mathematic thinking ability in problem based learning model based on self-regulation learning

    Science.gov (United States)

    Munahefi, D. N.; Waluya, S. B.; Rochmad

    2018-03-01

    The purpose of this research identified the effectiveness of Problem Based Learning (PBL) models based on Self Regulation Leaning (SRL) on the ability of mathematical creative thinking and analyzed the ability of mathematical creative thinking of high school students in solving mathematical problems. The population of this study was students of grade X SMA N 3 Klaten. The research method used in this research was sequential explanatory. Quantitative stages with simple random sampling technique, where two classes were selected randomly as experimental class was taught with the PBL model based on SRL and control class was taught with expository model. The selection of samples at the qualitative stage was non-probability sampling technique in which each selected 3 students were high, medium, and low academic levels. PBL model with SRL approach effectived to students’ mathematical creative thinking ability. The ability of mathematical creative thinking of low academic level students with PBL model approach of SRL were achieving the aspect of fluency and flexibility. Students of academic level were achieving fluency and flexibility aspects well. But the originality of students at the academic level was not yet well structured. Students of high academic level could reach the aspect of originality.

  9. Impact of Learning Model Based on Cognitive Conflict toward Student’s Conceptual Understanding

    Science.gov (United States)

    Mufit, F.; Festiyed, F.; Fauzan, A.; Lufri, L.

    2018-04-01

    The problems that often occur in the learning of physics is a matter of misconception and low understanding of the concept. Misconceptions do not only happen to students, but also happen to college students and teachers. The existing learning model has not had much impact on improving conceptual understanding and remedial efforts of student misconception. This study aims to see the impact of cognitive-based learning model in improving conceptual understanding and remediating student misconceptions. The research method used is Design / Develop Research. The product developed is a cognitive conflict-based learning model along with its components. This article reports on product design results, validity tests, and practicality test. The study resulted in the design of cognitive conflict-based learning model with 4 learning syntaxes, namely (1) preconception activation, (2) presentation of cognitive conflict, (3) discovery of concepts & equations, (4) Reflection. The results of validity tests by some experts on aspects of content, didactic, appearance or language, indicate very valid criteria. Product trial results also show a very practical product to use. Based on pretest and posttest results, cognitive conflict-based learning models have a good impact on improving conceptual understanding and remediating misconceptions, especially in high-ability students.

  10. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Directory of Open Access Journals (Sweden)

    Nur Ihsan Halil

    2017-10-01

    Full Text Available This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by developing and constructing an existing concept, namely the concept of linguistic intelligence, which is disseminated into a literature-based learning of verbal-linguistic intelligence. The purpose of this paper is to answer the question of how to apply the literary learning model based on the verbal-linguistic intelligence. Then, regarding Gardner's concept, the author formulated a literary learning model based on the verbal-linguistic intelligence through a story-telling learning model with five steps namely arguing, discussing, interpreting, speaking, and writing about literary works. In short, the writer draw a conclusion that learning-based models of verbal-linguistic intelligence can be designed with attention into five components namely (1 definition, (2 characteristics, (3 teaching strategy, (4 final learning outcomes, and (5 figures.

  11. Design of an Effective WSN-Based Interactive u-Learning Model

    OpenAIRE

    Kim, Hye-jin; Caytiles, Ronnie D.; Kim, Tai-hoon

    2012-01-01

    Wireless sensor networks include a wide range of potential applications to improve the quality of teaching and learning in a ubiquitous environment. WSNs become an evolving technology that acts as the ultimate interface between the learners and the context, enhancing the interactivity and improving the acquisition or collection of learner's contextual information in ubiquitous learning. This paper presents a model of an effective and interactive ubiquitous learning environment system based on...

  12. Chinese Students' Goal Orientation in English Learning: A Study Based on Autonomous Inquiry Model

    Science.gov (United States)

    Zhang, Jianfeng

    2014-01-01

    Goal orientation is a kind of theory of learning motivation, which helps learners to develop their capability by emphasis on new techniques acquiring and environment adapting. In this study, based on the autonomous inquiry model, the construction of Chinese students' goal orientations in English learning are summarized according to the data…

  13. Quality prediction modeling for sintered ores based on mechanism models of sintering and extreme learning machine based error compensation

    Science.gov (United States)

    Tiebin, Wu; Yunlian, Liu; Xinjun, Li; Yi, Yu; Bin, Zhang

    2018-06-01

    Aiming at the difficulty in quality prediction of sintered ores, a hybrid prediction model is established based on mechanism models of sintering and time-weighted error compensation on the basis of the extreme learning machine (ELM). At first, mechanism models of drum index, total iron, and alkalinity are constructed according to the chemical reaction mechanism and conservation of matter in the sintering process. As the process is simplified in the mechanism models, these models are not able to describe high nonlinearity. Therefore, errors are inevitable. For this reason, the time-weighted ELM based error compensation model is established. Simulation results verify that the hybrid model has a high accuracy and can meet the requirement for industrial applications.

  14. PERLUASAN IMPLEMENTASI PENDIDIKAN KEWIRAUSAHAAN MODEL PROJECT BASED LEARNING BAGI REMAJA PUTUS SEKOLAH KORBAN GEMPA

    Directory of Open Access Journals (Sweden)

    Moerdiyanto Moerdiyanto

    2012-04-01

    Full Text Available Abstract: Widen Implementation of Entrepreneurship Education Using Project Based Learning Model for Earthquake Victim Drop Out Teenagers. This action research aims at figuring out achievement level of entrepreneurship personalities mastering and business skills held by drop out teenagers after taking part in real business learning experience using Project Based Learning. The population for this study is all of the earthquake victim drop out teenagers in Piyungan, Pleret, and Sewon Bantul Yogyakarta Special Territory.  Interviewed, questionnaire, observation, and documentation are employed to collect data. The results show that entrepreneurship education using Project Based Learning model leads to highly mastering of entrepreneurship personalities (soft skill and highly mastering of business skills (hard skill. Furthermore, through this study Kelompok Usaha Mandiri (Group of Independent Business is created, and then the drop out teenagers can run their own business.   Keyword: business skill, project based learning, soft skill, hard skill   Abstrak: Perluasan Implementasi Pendidikan Kewirausahaan Model Project Based Learning Bagi Remaja Putus Sekolah Korban Gempa. Penelitian ini merupakan penelitian tindakan dengan tujuan untuk mengetahui tingkat keberhasilan penguasaan kepribadian (jiwa kewirausahaan dan keterampilan usaha yang dimiliki Remaja Putus Sekolah (RPS setelah memperoleh pengalaman belajar bisnis riil dengan model Project Based Learning. Populasi dalam penelitian ini adalah semua remaja putus sekolah korban gempa di Kecamatan Piyungan, Kecamatan Pleret, dan Kecamatan Sewon Kabupaten Bantul DIY. Teknik pengumpulan data menggunakan wawancara, angket, observasi, dokumentasi, dan pemberian tugas. Data dianalisis menggunakan teknik deskriptif kuantitatif dan kualitatif. Hasil penelitian menunjukkan bahwa pemberian pendidikan kewirausahaan dengan menggunakan model Project Based Learning bisa berhasil dengan baik yang ditunjukkan dengan

  15. The development of learning materials based on core model to improve students’ learning outcomes in topic of Chemical Bonding

    Science.gov (United States)

    Avianti, R.; Suyatno; Sugiarto, B.

    2018-04-01

    This study aims to create an appropriate learning material based on CORE (Connecting, Organizing, Reflecting, Extending) model to improve students’ learning achievement in Chemical Bonding Topic. This study used 4-D models as research design and one group pretest-posttest as design of the material treatment. The subject of the study was teaching materials based on CORE model, conducted on 30 students of Science class grade 10. The collecting data process involved some techniques such as validation, observation, test, and questionnaire. The findings were that: (1) all the contents were valid, (2) the practicality and the effectiveness of all the contents were good. The conclusion of this research was that the CORE model is appropriate to improve students’ learning outcomes for studying Chemical Bonding.

  16. The Research on Informal Learning Model of College Students Based on SNS and Case Study

    Science.gov (United States)

    Lu, Peng; Cong, Xiao; Bi, Fangyan; Zhou, Dongdai

    2017-03-01

    With the rapid development of network technology, informal learning based on online become the main way for college students to learn a variety of subject knowledge. The favor to the SNS community of students and the characteristics of SNS itself provide a good opportunity for the informal learning of college students. This research first analyzes the related research of the informal learning and SNS, next, discusses the characteristics of informal learning and theoretical basis. Then, it proposed an informal learning model of college students based on SNS according to the support role of SNS to the informal learning of students. Finally, according to the theoretical model and the principles proposed in this study, using the Elgg and related tools which is the open source SNS program to achieve the informal learning community. This research is trying to overcome issues such as the lack of social realism, interactivity, resource transfer mode in the current network informal learning communities, so as to provide a new way of informal learning for college students.

  17. Model of Recommendation System for for Indexing and Retrieving the Learning Object based on Multiagent System

    Directory of Open Access Journals (Sweden)

    Ronaldo Lima Rocha Campos

    2012-07-01

    Full Text Available This paper proposes a multiagent system application model for indexing, retrieving and recommendation learning objects stored in different and heterogeneous repositories. The objects within these repositories are described by filled fields using different metadata standards. The searching mechanism covers several different learning object repositories and the same object can be described in these repositories by the use of different types of fields. Aiming to improve accuracy and coverage in terms of recovering a learning object and improve the signification of the results we propose an information retrieval model based on the multiagent system approach and an ontological model to describe the knowledge domain covered.

  18. The Effect of Inquiry Training Learning Model Based on Just in Time Teaching for Problem Solving Skill

    Science.gov (United States)

    Turnip, Betty; Wahyuni, Ida; Tanjung, Yul Ifda

    2016-01-01

    One of the factors that can support successful learning activity is the use of learning models according to the objectives to be achieved. This study aimed to analyze the differences in problem-solving ability Physics student learning model Inquiry Training based on Just In Time Teaching [JITT] and conventional learning taught by cooperative model…

  19. Problem Based Learning

    DEFF Research Database (Denmark)

    de Graaff, Erik; Guerra, Aida

    , the key principles remain the same everywhere. Graaff & Kolmos (2003) identify the main PBL principles as follows: 1. Problem orientation 2. Project organization through teams or group work 3. Participant-directed 4. Experiental learning 5. Activity-based learning 6. Interdisciplinary learning and 7...... model and in general problem based and project based learning. We apply the principle of teach as you preach. The poster aims to outline the visitors’ workshop programme showing the results of some recent evaluations.......Problem-Based Learning (PBL) is an innovative method to organize the learning process in such a way that the students actively engage in finding answers by themselves. During the past 40 years PBL has evolved and diversified resulting in a multitude in variations in models and practices. However...

  20. Collective learning modeling based on the kinetic theory of active particles

    Science.gov (United States)

    Burini, D.; De Lillo, S.; Gibelli, L.

    2016-03-01

    This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom.

  1. EFFECTS OF COOPERATIVE LEARNING MODEL TYPE STAD JUST-IN TIME BASED ON THE RESULTS OF LEARNING TEACHING PHYSICS COURSE IN PHYSICS SCHOOL IN PHYSICS PROGRAM FACULTY UNIMED

    Directory of Open Access Journals (Sweden)

    Teguh Febri Sudarma

    2013-06-01

    Full Text Available Research was aimed to determine: (1 Students’ learning outcomes that was taught with just in time teaching based STAD cooperative learning method and STAD cooperative learning method (2 Students’ outcomes on Physics subject that had high learning activity compared with low learning activity. The research sample was random by raffling four classes to get two classes. The first class taught with just in time teaching based STAD cooperative learning method, while the second class was taught with STAD cooperative learning method. The instrument used was conceptual understanding that had been validated with 7 essay questions. The average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,47 higher than average gain values of students learning results with STAD cooperative learning method. The high learning activity and low learning activity gave different learning results. In this case the average gain values of students learning results with just in time teaching based STAD cooperative learning method 0,48 higher than average gain values of students learning results with STAD cooperative learning method. There was interaction between learning model and learning activity to the physics learning result test in students

  2. A deep learning-based multi-model ensemble method for cancer prediction.

    Science.gov (United States)

    Xiao, Yawen; Wu, Jun; Lin, Zongli; Zhao, Xiaodong

    2018-01-01

    Cancer is a complex worldwide health problem associated with high mortality. With the rapid development of the high-throughput sequencing technology and the application of various machine learning methods that have emerged in recent years, progress in cancer prediction has been increasingly made based on gene expression, providing insight into effective and accurate treatment decision making. Thus, developing machine learning methods, which can successfully distinguish cancer patients from healthy persons, is of great current interest. However, among the classification methods applied to cancer prediction so far, no one method outperforms all the others. In this paper, we demonstrate a new strategy, which applies deep learning to an ensemble approach that incorporates multiple different machine learning models. We supply informative gene data selected by differential gene expression analysis to five different classification models. Then, a deep learning method is employed to ensemble the outputs of the five classifiers. The proposed deep learning-based multi-model ensemble method was tested on three public RNA-seq data sets of three kinds of cancers, Lung Adenocarcinoma, Stomach Adenocarcinoma and Breast Invasive Carcinoma. The test results indicate that it increases the prediction accuracy of cancer for all the tested RNA-seq data sets as compared to using a single classifier or the majority voting algorithm. By taking full advantage of different classifiers, the proposed deep learning-based multi-model ensemble method is shown to be accurate and effective for cancer prediction. Copyright © 2017 Elsevier B.V. All rights reserved.

  3. A Model of e-Learning by Constructivism Approach Using Problem-Based Learning to Develop Thinking Skills for Students in Rajaghat University

    Science.gov (United States)

    Shutimarrungson, Werayut; Pumipuntu, Sangkom; Noirid, Surachet

    2014-01-01

    This research aimed to develop a model of e-learning by using Problem-Based Learning--PBL to develop thinking skills for students in Rajabhat University. The research is divided into three phases through the e-learning model via PBL with Constructivism approach as follows: Phase 1 was to study characteristics and factors through the model to…

  4. Building v/s Exploring Models: Comparing Learning of Evolutionary Processes through Agent-based Modeling

    Science.gov (United States)

    Wagh, Aditi

    Two strands of work motivate the three studies in this dissertation. Evolutionary change can be viewed as a computational complex system in which a small set of rules operating at the individual level result in different population level outcomes under different conditions. Extensive research has documented students' difficulties with learning about evolutionary change (Rosengren et al., 2012), particularly in terms of levels slippage (Wilensky & Resnick, 1999). Second, though building and using computational models is becoming increasingly common in K-12 science education, we know little about how these two modalities compare. This dissertation adopts agent-based modeling as a representational system to compare these modalities in the conceptual context of micro-evolutionary processes. Drawing on interviews, Study 1 examines middle-school students' productive ways of reasoning about micro-evolutionary processes to find that the specific framing of traits plays a key role in whether slippage explanations are cued. Study 2, which was conducted in 2 schools with about 150 students, forms the crux of the dissertation. It compares learning processes and outcomes when students build their own models or explore a pre-built model. Analysis of Camtasia videos of student pairs reveals that builders' and explorers' ways of accessing rules, and sense-making of observed trends are of a different character. Builders notice rules through available blocks-based primitives, often bypassing their enactment while explorers attend to rules primarily through the enactment. Moreover, builders' sense-making of observed trends is more rule-driven while explorers' is more enactment-driven. Pre and posttests reveal that builders manifest a greater facility with accessing rules, providing explanations manifesting targeted assembly. Explorers use rules to construct explanations manifesting non-targeted assembly. Interviews reveal varying degrees of shifts away from slippage in both

  5. Cooperative Learning Technique through Internet Based Education: A Model Proposal

    Science.gov (United States)

    Ozkan, Hasan Huseyin

    2010-01-01

    Internet is gradually becoming the most valuable learning environment for the people which form the information society. That the internet provides written, oral and visual communication between the participants who are at different places, that it enables the students' interaction with other students and teachers, and that it does these so fast…

  6. Construction of SPOC-based Learning Model and its Application in Linguistics Teaching

    Directory of Open Access Journals (Sweden)

    Hua Lu

    2018-02-01

    Full Text Available The design of a reasonable learning model must take the new internet age into consideration. Following a contrastive study between MOOCs and SPOCs, a SPOC-based learning model is proposed in this paper. This new learning model consists of four components, the preliminary component composed of anterior analysis and course construction, the restrictive admission component for student number control, the learning procedure component which is subdivided into pre-class session, class session and post-class session, and the evaluation component which includes both online assessment and classroom assessment. This model has its advantages and is shown to be effective through the demonstration of its application in teaching linguistics to college students.

  7. Comparisons between physics-based, engineering, and statistical learning models for outdoor sound propagation.

    Science.gov (United States)

    Hart, Carl R; Reznicek, Nathan J; Wilson, D Keith; Pettit, Chris L; Nykaza, Edward T

    2016-05-01

    Many outdoor sound propagation models exist, ranging from highly complex physics-based simulations to simplified engineering calculations, and more recently, highly flexible statistical learning methods. Several engineering and statistical learning models are evaluated by using a particular physics-based model, namely, a Crank-Nicholson parabolic equation (CNPE), as a benchmark. Narrowband transmission loss values predicted with the CNPE, based upon a simulated data set of meteorological, boundary, and source conditions, act as simulated observations. In the simulated data set sound propagation conditions span from downward refracting to upward refracting, for acoustically hard and soft boundaries, and low frequencies. Engineering models used in the comparisons include the ISO 9613-2 method, Harmonoise, and Nord2000 propagation models. Statistical learning methods used in the comparisons include bagged decision tree regression, random forest regression, boosting regression, and artificial neural network models. Computed skill scores are relative to sound propagation in a homogeneous atmosphere over a rigid ground. Overall skill scores for the engineering noise models are 0.6%, -7.1%, and 83.8% for the ISO 9613-2, Harmonoise, and Nord2000 models, respectively. Overall skill scores for the statistical learning models are 99.5%, 99.5%, 99.6%, and 99.6% for bagged decision tree, random forest, boosting, and artificial neural network regression models, respectively.

  8. Analysis of e-learning implementation readiness based on integrated elr model

    Science.gov (United States)

    Adiyarta, K.; Napitupulu, D.; Rahim, R.; Abdullah, D.; Setiawan, MI

    2018-04-01

    E-learning nowadays has become a requirement for institutions to support their learning activities. To adopt e-learning, an institution requires a large strategy and resources for optimal application. Unfortunately, not all institutions that have used e-learning got the desired results or expectations. This study aims to identify the extent of the level of readiness of e-learning implementation in institution X. The degree of institutional readiness will determine the success of future e-learning utilization. In addition, institutional readiness measurement are needed to evaluate the effectiveness of strategies in e-learning development. The research method used is survey with questionnaire designed based on integration of 8 best practice ELR (e-learning readiness) model. The results showed that from 13 factors of integrated ELR model being measured, there are 3 readiness factors included in the category of not ready and needs a lot of work. They are human resource (2.57), technology skill (2.38) and content factors (2.41). In general, e-learning implementation in institutions is in the category of not ready but needs some of work (3.27). Therefore, the institution should consider which factors or areas of ELR factors are considered still not ready and needs improvement in the future.

  9. Modeling Students' Problem Solving Performance in the Computer-Based Mathematics Learning Environment

    Science.gov (United States)

    Lee, Young-Jin

    2017-01-01

    Purpose: The purpose of this paper is to develop a quantitative model of problem solving performance of students in the computer-based mathematics learning environment. Design/methodology/approach: Regularized logistic regression was used to create a quantitative model of problem solving performance of students that predicts whether students can…

  10. The Play Curricular Activity Reflection Discussion Model for Game-Based Learning

    Science.gov (United States)

    Foster, Aroutis; Shah, Mamta

    2015-01-01

    This article elucidates the process of game-based learning in classrooms through the use of the Play Curricular activity Reflection Discussion (PCaRD) model. A mixed-methods study was conducted at a high school to implement three games with the PCaRD model in a year-long elective course. Data sources included interviews and observations for…

  11. Exploring the Argumentation Pattern in Modeling-Based Learning about Apparent Motion of Mars

    Science.gov (United States)

    Park, Su-Kyeong

    2016-01-01

    This study proposed an analytic framework for coding students' dialogic argumentation and investigated the characteristics of the small-group argumentation pattern observed in modeling-based learning. The participants were 122 second grade high school students in South Korea divided into an experimental and a comparison group. Modeling-based…

  12. Effects of creating video-based modeling examples on learning and transfer

    NARCIS (Netherlands)

    Hoogerheide, Vincent; Loyens, Sofie M M; van Gog, Tamara

    2014-01-01

    Two experiments investigated whether acting as a peer model for a video-based modeling example, which entails studying a text with the intention to explain it to others and then actually explaining it on video, would foster learning and transfer. In both experiments, novices were instructed to study

  13. Hybrid forecasting of chaotic processes: Using machine learning in conjunction with a knowledge-based model

    Science.gov (United States)

    Pathak, Jaideep; Wikner, Alexander; Fussell, Rebeckah; Chandra, Sarthak; Hunt, Brian R.; Girvan, Michelle; Ott, Edward

    2018-04-01

    A model-based approach to forecasting chaotic dynamical systems utilizes knowledge of the mechanistic processes governing the dynamics to build an approximate mathematical model of the system. In contrast, machine learning techniques have demonstrated promising results for forecasting chaotic systems purely from past time series measurements of system state variables (training data), without prior knowledge of the system dynamics. The motivation for this paper is the potential of machine learning for filling in the gaps in our underlying mechanistic knowledge that cause widely-used knowledge-based models to be inaccurate. Thus, we here propose a general method that leverages the advantages of these two approaches by combining a knowledge-based model and a machine learning technique to build a hybrid forecasting scheme. Potential applications for such an approach are numerous (e.g., improving weather forecasting). We demonstrate and test the utility of this approach using a particular illustrative version of a machine learning known as reservoir computing, and we apply the resulting hybrid forecaster to a low-dimensional chaotic system, as well as to a high-dimensional spatiotemporal chaotic system. These tests yield extremely promising results in that our hybrid technique is able to accurately predict for a much longer period of time than either its machine-learning component or its model-based component alone.

  14. Technology, Demographic Characteristics and E-Learning Acceptance: A Conceptual Model Based on Extended Technology Acceptance Model

    Science.gov (United States)

    Tarhini, Ali; Elyas, Tariq; Akour, Mohammad Ali; Al-Salti, Zahran

    2016-01-01

    The main aim of this paper is to develop an amalgamated conceptual model of technology acceptance that explains how individual, social, cultural and organizational factors affect the students' acceptance and usage behaviour of the Web-based learning systems. More specifically, the proposed model extends the Technology Acceptance Model (TAM) to…

  15. Quasilinear Extreme Learning Machine Model Based Internal Model Control for Nonlinear Process

    Directory of Open Access Journals (Sweden)

    Dazi Li

    2015-01-01

    Full Text Available A new strategy for internal model control (IMC is proposed using a regression algorithm of quasilinear model with extreme learning machine (QL-ELM. Aimed at the chemical process with nonlinearity, the learning process of the internal model and inverse model is derived. The proposed QL-ELM is constructed as a linear ARX model with a complicated nonlinear coefficient. It shows some good approximation ability and fast convergence. The complicated coefficients are separated into two parts. The linear part is determined by recursive least square (RLS, while the nonlinear part is identified through extreme learning machine. The parameters of linear part and the output weights of ELM are estimated iteratively. The proposed internal model control is applied to CSTR process. The effectiveness and accuracy of the proposed method are extensively verified through numerical results.

  16. Model of Supervision Based on Primary School Teacher Professional Competency in Tematic Learning in Curriculum 2013

    Directory of Open Access Journals (Sweden)

    Meilani Hartono

    2017-08-01

    Full Text Available This study aims to find the Supervision Model Based on Primary Teacher Professional Competence which effective on integrated learning. This study use research and development with qualitative approach which will be carried out in the Palmerah, West Jakarta. The techniques used to collect data are interviews, questionnaires, observation and documentation. Data v alidity is tested with credibility, transferability, dependability, and comfortability. The model developed will be validated using the Delphi technique. The result of this research is the discovery of the model and device-based supervision model of professional competence of primary teachers in integrated learning. The long-term goal of this research is to improve the teachers’ competence and the supervision quality for primary teachers in integrated learning

  17. The Aplication of Problem Based Learning Model on Heat and Temperature

    OpenAIRE

    Simamora, Pintor; Rotua Estomihi Pardede, Victorya

    2016-01-01

    This study aims to determine the effect of Problem Based Learning model to student learning outcomes on subject of Heat and Temperature. This research is quasi-experimental. Techniques that used to gain a sample is random-cluster-sampling technique that was chosen two classes as experimental and control classes. Instruments in the form of essays tests and observation sheets to measure affectivepsychomotor of students. Pretest data on both classes showed that both classes have the same ability...

  18. Implementing learning organization components in Ardabil Regional Water Company based on Marquardt systematic model

    OpenAIRE

    Shahram Mirzaie Daryani; Azadeh Zirak

    2015-01-01

    This main purpose of this study was to survey the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Regional Water Company. Two hundred and four staff (164 employees and 40 authorities) participated in the study. For data collection Marquardt questionnaire was used which its validity and reliability had been confirmed. The results of the data analysis showed that learning organization characteristics were used more than average level in som...

  19. Application of Model Project Based Learning on Integrated Science in Water Pollution

    Science.gov (United States)

    Yamin, Y.; Permanasari, A.; Redjeki, S.; Sopandi, W.

    2017-09-01

    The function of this research was to analyze the influence model Project Based Learning (PjBl) on integrated science about the concept mastery for junior high school students. Method used for this research constitutes the quasi of experiment method. Population and sample for this research are the students junior high school in Bandung as many as two classes to be experiment and control class. The instrument that used for this research is the test concept mastery, assessment questionnaire of product and the questionnaire responses of the student about learning integrated science. Based on the result of this research get some data that with accomplishment the model of PjBl. Learning authority of integrated science can increase the concept mastery for junior high school students. The highest increase in the theme of pollution water is in the concept of mixtures and the separation method. The students give a positive response in learning of integrated science for the theme of pollution of the water used model PjBL with questionnaire of the opinion aspect in amount of 83.5%, the anxiety of the students in amount of 95.5%, the profit learning model of PjBL in amount of 96.25% and profit learning of integrated science in amount of 95.75%.

  20. Analysis of dynamic Cournot learning models for generation companies based on conjectural variations and forward expectation

    International Nuclear Information System (INIS)

    Gutierrez-Alcaraz, G.; Tovar-Hernandez, Jose H.; Moreno-Goytia, Edgar L.

    2009-01-01

    Electricity spot markets generally operate on an hourly basis; under this condition GENCOs can closely observe their competitors' market behavior. For this purposes, a detailed dynamic model is one of the tools used by GENCOs to understand the behavioral variations of competitors over time. The required abilities to rapidly adjust one's own decision-making create a need for new learning procedures and models. Conjectural variations (CV) have been proposed as a learning approach. In this paper a model based on forward expectations (FE) is proposed as a learning approach, and through illustrative examples it is shown that the market equilibria found by the CV model are also obtained by the FE model. (author)

  1. EFFECT OF PROBLEM BASED LEARNING AND MODEL CRITICAL THINKING ABILITY TO PROBLEM SOLVING SKILLS

    Directory of Open Access Journals (Sweden)

    Unita S. Zuliani Nasution

    2016-12-01

    Full Text Available The purposes of this research were to analyze the different between physic resolving problem ability by using problem based learning model and direct instruction model, the different of physic resolving problem ability between the students that have critical thinking ability upper the average and the students that have critical thinking ability under the average, and the interaction of problem based learning model toward critical thinking ability and students’ physic resolving problem ability. This research was quasy experimental research that use critical thinking ability tests and physic resolving problem ability tests as the instruments. Result of the research showed that the students’ physic resolving problem ability by using problem based learning model was better than by using direct instruction model, students’ physic resolving problem ability and critical thinking ability upper the average showed better different and result than students’ critical thinking ability under the average, besides there was an interaction between problem based learning model and critical thinking ability in improving students’ physic resolving problem ability.

  2. Parameters identification of photovoltaic models using self-adaptive teaching-learning-based optimization

    International Nuclear Information System (INIS)

    Yu, Kunjie; Chen, Xu; Wang, Xin; Wang, Zhenlei

    2017-01-01

    Highlights: • SATLBO is proposed to identify the PV model parameters efficiently. • In SATLBO, the learners self-adaptively select different learning phases. • An elite learning is developed in teacher phase to perform local searching. • A diversity learning is proposed in learner phase to maintain population diversity. • SATLBO achieves the first in ranking on overall performance among nine algorithms. - Abstract: Parameters identification of photovoltaic (PV) model based on measured current-voltage characteristic curves plays an important role in the simulation and evaluation of PV systems. To accurately and reliably identify the PV model parameters, a self-adaptive teaching-learning-based optimization (SATLBO) is proposed in this paper. In SATLBO, the learners can self-adaptively select different learning phases based on their knowledge level. The better learners are more likely to choose the learner phase for improving the population diversity, while the worse learners tend to choose the teacher phase to enhance the convergence rate. Thus, learners at different levels focus on different searching abilities to efficiently enhance the performance of algorithm. In addition, to improve the searching ability of different learning phases, an elite learning strategy and a diversity learning method are introduced into the teacher phase and learner phase, respectively. The performance of SATLBO is firstly evaluated on 34 benchmark functions, and experimental results show that SATLBO achieves the first in ranking on the overall performance among nine algorithms. Then, SATLBO is employed to identify parameters of different PV models, i.e., single diode, double diode, and PV module. Experimental results indicate that SATLBO exhibits high accuracy and reliability compared with other parameter extraction methods.

  3. Learners' Ensemble Based Security Conceptual Model for M-Learning System in Malaysian Higher Learning Institution

    Science.gov (United States)

    Mahalingam, Sheila; Abdollah, Faizal Mohd; Sahib, Shahrin

    2014-01-01

    M-Learning has a potential to improve efficiency in the education sector and has a tendency to grow advance and transform the learning environment in the future. Yet there are challenges in many areas faced when introducing and implementing m-learning. The learner centered attribute in mobile learning implies deployment in untrustworthy learning…

  4. Learning Experiences Reuse Based on an Ontology Modeling to Improve Adaptation in E-Learning Systems

    Science.gov (United States)

    Hadj M'tir, Riadh; Rumpler, Béatrice; Jeribi, Lobna; Ben Ghezala, Henda

    2014-01-01

    Current trends in e-Learning focus mainly on personalizing and adapting the learning environment and learning process. Although their increasingly number, theses researches often ignore the concepts of capitalization and reuse of learner experiences which can be exploited later by other learners. Thus, the major challenge of distance learning is…

  5. The Model of Problem Based Learning in Practice: Evidence from Aalborg University

    DEFF Research Database (Denmark)

    Turcan, Romeo V.

    into practice when they go through solving such problems. At the end of the day, the PBL based teaching is assessed based on the success of the problems solved, e.g., in the form of solution(s) provided, their creativity, innovation and applicability. Moreover, PBL-based teaching can identify theoretical gaps......The aim of this paper is to share an experience from Aalborg University on the application of Problem Based Learning (PBL) model, with a specific example from a bachelor studies. PBL model has now been acknowledged worldwide as a powerful tool that allows students, faculty members and industry...... practitioners engage in multi-disciplinary, collaborative and geographically distributed activities. The key word in the model is ‘problem’ – a problem that is correctly formulated eventually affects the process of learning. It is also linked to the intended outcome of the PBL based teaching, whereby students...

  6. A compression-based model of musical learning

    DEFF Research Database (Denmark)

    Meredith, David

    for the most satisfying (usually the most economical) interpretation of the new work. This is modelled as the modification of a pre-existing program, P, that computes some corpus (i.e., a compact encoding of the corpus), so that it can additionally compute the object to be interpreted. In other words...... in musical perception. The feasibility of this view is demonstrated in a computational model which is applied to the first book of J. S. Bach’s Das Wohltemperirte Clavier. This model pre-processes the data using the author’s PS13s1 pitch spelling algorithm [4,5], then applies a modified version of the author......’s COSIATEC algorithm [6] to derive compact encodings of works that maximise reuse of previous encodings. The resulting analyses will be presented and discussed. References [1] Pomerantz, J. R. and Kubovy, M. (1986). Theoretical approaches to perceptual organization: Simplicity and likelihood principles. In...

  7. A Day-to-Day Route Choice Model Based on Reinforcement Learning

    Directory of Open Access Journals (Sweden)

    Fangfang Wei

    2014-01-01

    Full Text Available Day-to-day traffic dynamics are generated by individual traveler’s route choice and route adjustment behaviors, which are appropriate to be researched by using agent-based model and learning theory. In this paper, we propose a day-to-day route choice model based on reinforcement learning and multiagent simulation. Travelers’ memory, learning rate, and experience cognition are taken into account. Then the model is verified and analyzed. Results show that the network flow can converge to user equilibrium (UE if travelers can remember all the travel time they have experienced, but which is not necessarily the case under limited memory; learning rate can strengthen the flow fluctuation, but memory leads to the contrary side; moreover, high learning rate results in the cyclical oscillation during the process of flow evolution. Finally, both the scenarios of link capacity degradation and random link capacity are used to illustrate the model’s applications. Analyses and applications of our model demonstrate the model is reasonable and useful for studying the day-to-day traffic dynamics.

  8. Organizational Learning, Strategic Flexibility and Business Model Innovation: An Empirical Research Based on Logistics Enterprises

    Science.gov (United States)

    Bao, Yaodong; Cheng, Lin; Zhang, Jian

    Using the data of 237 Jiangsu logistics firms, this paper empirically studies the relationship among organizational learning capability, business model innovation, strategic flexibility. The results show as follows; organizational learning capability has positive impacts on business model innovation performance; strategic flexibility plays mediating roles on the relationship between organizational learning capability and business model innovation; interaction among strategic flexibility, explorative learning and exploitative learning play significant roles in radical business model innovation and incremental business model innovation.

  9. The Effect of Model Problem Based Learning (Pbl)

    OpenAIRE

    Safrina, Safrina; Saminan, Saminan

    2015-01-01

    This study aims to determine the effect of the application of PBL models of science process skills (PPP) and the understanding of the concept of chemical substances in food at eighth grade students MTsN Meureudu. This study is a descriptive study using the research design one group pretest and posttest design. Samples were 19 eighth grade students MTsN Meureudu school year 2013/2014. Data collected by pretest and posttest to determine the effect of the application of PBL models and observatio...

  10. E-learning acceptance based on technology acceptance model (TAM)

    African Journals Online (AJOL)

    Data were collected with 95 undergraduate students at Tunku Abdul Rahman University College (TARUC), Johor. Structural Equation Modeling (SEM) was used to analyze the data. Results shown that computer self-efficacyhas significantly effects ease of use, while perceived ease of use significantly affectsintention to use ...

  11. MODEL WORK-BASED LEARNING SEBAGAI KEMITRAAN UNTUK PERSIAPAN LULUSAN PERGURUAN TINGGI MEMASUKI DUNIA KERJA

    Directory of Open Access Journals (Sweden)

    Abdul Haris Indrakusuma

    2016-08-01

    Full Text Available Penelitian ini bertujuan untuk mengetahui bagaimanakah Pola kemitraan work based learning di Perguruan Tinggi dan Kemitraannya dengan dunia kerja dalam melaksanakan pembelajaran work based learning sehingga menghasilkan lulusan sesuai dengan kebutuhan dunia kerja. Hal ini diharapkan bisa mewakili bahwa penerapan model work-based learning di Perguruan Tinggi memang sangat perlu dikembangkan karena merupakan bekal untuk menciptakan lulusan yang sudah punya kesiapan dalam memasuki dunia kerja. Metode pengumpulan data yang di gunakan dalam penelitian ini adalah triangulasi. peneliti menggunakan teknik pengumpulan data yang berbeda untuk mendapatkan data dari sumber yang sama. Peneliti menggunakan obserasi, wawancara, dan dokumentasi untuk sumber data yang sama secara serempak. Analisis data yang digunakan dalam penelitian ini adalah Analysis Interactive Model dari Miles dan Huberman yang membagi kegiatan analisis menjadi beberapa bagian yaitu: pengumpulan data, pengelompokan menurut variabel, reduksi data, penyajian data, memisahkan outlier data, dan penarikan kesimpulan atau verifikasi data. Berdasarkan analisis deskriptif menunjukan bahwa magang dalam konteks work-based learning sudah berjalan sesuai dengan karakteristik work-based learning. Dapat dilihat dalam persiapan magang (pembekalan berupa sosialisasi kepada pebelajar, sehingga pebelajar menyadari akan pentingnya magang sebagai bekal pengalaman masuk ke dalam dunia industri yang merupakan dunia kerja nyata. Keseriusan menjalankan magang terlihat mulai dari monitoring pebelajar yang dijalakan secara maksimal. Evaluasi magang sebagai umpan balik untuk magang yang telah dijalankan (feedback dan memberikan informasi yang diperlukan untuk menjalankan magang dimasa yang akan datang (feedforward sudah dilaksanakan meskipun belum maksimal dilaksanakan, mulai dari tes wawancara hingga presentasi.

  12. Learning Design of Problem Based Learning Model Based on Recommendations of Sintax Study and Contents Issues on Physics Impulse Materials with Experimental Activities

    Directory of Open Access Journals (Sweden)

    Kristia Agustina

    2017-08-01

    Full Text Available This study aims to design learning Problem Based Learning Model based on syntax study recommendations and content issues on Physics Impulse materials through experiments. This research is a development research with Kemp model. The reference for making the learning design is the result of the syntax study and the content of existing PBL implementation problems from Agustina research. This instructional design is applied to the physics material about Impulse done through experimental activity. Limited trials were conducted on the SWCU Physics Education Study Program students group Salatiga, while the validity test was conducted by high school teachers and physics education lecturers. The results of the trial evaluation are limited and the validity test is used to improve the designs that have been made. The conclusion of this research is the design of learning by using PBL model on Impuls material by referring the result of syntax study and the problem content of existing PBL implementation can be produced by learning activity designed in laboratory experiment activity. The actual problem for Impuls material can be used car crash test video at factory. The results of validation tests and limited trials conducted by researchers assessed that the design of learning made by researchers can be used with small revisions. Suggestions from this research are in making learning design by using PBL model to get actual problem can by collecting news that come from newspaper, YouTube, internet, and television.

  13. Development of syntax of intuition-based learning model in solving mathematics problems

    Science.gov (United States)

    Yeni Heryaningsih, Nok; Khusna, Hikmatul

    2018-01-01

    The aim of the research was to produce syntax of Intuition Based Learning (IBL) model in solving mathematics problem for improving mathematics students’ achievement that valid, practical and effective. The subject of the research were 2 classes in grade XI students of SMAN 2 Sragen, Central Java. The type of the research was a Research and Development (R&D). Development process adopted Plomp and Borg & Gall development model, they were preliminary investigation step, design step, realization step, evaluation and revision step. Development steps were as follow: (1) Collected the information and studied of theories in Preliminary Investigation step, studied about intuition, learning model development, students condition, and topic analysis, (2) Designed syntax that could bring up intuition in solving mathematics problem and then designed research instruments. They were several phases that could bring up intuition, Preparation phase, Incubation phase, Illumination phase and Verification phase, (3) Realized syntax of Intuition Based Learning model that has been designed to be the first draft, (4) Did validation of the first draft to the validator, (5) Tested the syntax of Intuition Based Learning model in the classrooms to know the effectiveness of the syntax, (6) Conducted Focus Group Discussion (FGD) to evaluate the result of syntax model testing in the classrooms, and then did the revision on syntax IBL model. The results of the research were produced syntax of IBL model in solving mathematics problems that valid, practical and effective. The syntax of IBL model in the classroom were, (1) Opening with apperception, motivations and build students’ positive perceptions, (2) Teacher explains the material generally, (3) Group discussion about the material, (4) Teacher gives students mathematics problems, (5) Doing exercises individually to solve mathematics problems with steps that could bring up students’ intuition: Preparations, Incubation, Illumination, and

  14. Exploring nursing e-learning systems success based on information system success model.

    Science.gov (United States)

    Chang, Hui-Chuan; Liu, Chung-Feng; Hwang, Hsin-Ginn

    2011-12-01

    E-learning is thought of as an innovative approach to enhance nurses' care service knowledge. Extensive research has provided rich information toward system development, courses design, and nurses' satisfaction with an e-learning system. However, a comprehensive view in understanding nursing e-learning system success is an important but less focused-on topic. The purpose of this research was to explore net benefits of nursing e-learning systems based on the updated DeLone and McLean's Information System Success Model. The study used a self-administered questionnaire to collected 208 valid nurses' responses from 21 of Taiwan's medium- and large-scale hospitals that have implemented nursing e-learning systems. The result confirms that the model is sufficient to explore the nurses' use of e-learning systems in terms of intention to use, user satisfaction, and net benefits. However, while the three exogenous quality factors (system quality, information quality, and service quality) were all found to be critical factors affecting user satisfaction, only information quality showed a direct effect on the intention to use. This study provides useful insights for evaluating nursing e-learning system qualities as well as an understanding of nurses' intentions and satisfaction related to performance benefits.

  15. THE IMPLEMENTATION OF JOBSHEET-BASED STUDENT TEAMS ACHIEVEMENT DIVISION LEARNING MODEL TO IMPROVE STUDENTS LEARNING OUTCOMES

    Directory of Open Access Journals (Sweden)

    Kadek Dodi Permana

    2016-09-01

    Full Text Available This study aims to improve the Information and Communications Technology (ICT learning outcomes of the students in SMA N 2 Singaraja through the learning model of Job sheet-based Student Team Achievement Division (STAD. This is a classroom action research. The data analysis reveals that learning outcomes in cycle I gain a mean score of 80. 51 and a classical provisions of 15%. There are three students who pass with a minimum score of 85 in cycle I. From these categories, the students’ learning outcomes in the first cycle have not met the criterion of 85%. The mean score of cycle II is 88. 57 and the classical provisions is 90%. In the second cycle, there are 18 students who gain a minimum score of 85. Based on the success criterion, a research study is successful if the minimum completeness criterion reaches 85 and the minimum classical completeness criterion reaches 85%. From the categories, the students’ learning outcomes have been successfully improved since the percentage of classical completeness in the second cycle has reached its expected results.

  16. A hierarchical model for structure learning based on the physiological characteristics of neurons

    Institute of Scientific and Technical Information of China (English)

    WEI Hui

    2007-01-01

    Almost all applications of Artificial Neural Networks (ANNs) depend mainly on their memory ability.The characteristics of typical ANN models are fixed connections,with evolved weights,globalized representations,and globalized optimizations,all based on a mathematical approach.This makes those models to be deficient in robustness,efficiency of learning,capacity,anti-jamming between training sets,and correlativity of samples,etc.In this paper,we attempt to address these problems by adopting the characteristics of biological neurons in morphology and signal processing.A hierarchical neural network was designed and realized to implement structure learning and representations based on connected structures.The basic characteristics of this model are localized and random connections,field limitations of neuron fan-in and fan-out,dynamic behavior of neurons,and samples represented through different sub-circuits of neurons specialized into different response patterns.At the end of this paper,some important aspects of error correction,capacity,learning efficiency,and soundness of structural representation are analyzed theoretically.This paper has demonstrated the feasibility and advantages of structure learning and representation.This model can serve as a fundamental element of cognitive systems such as perception and associative memory.Key-words structure learning,representation,associative memory,computational neuroscience

  17. Learning Physics-based Models in Hydrology under the Framework of Generative Adversarial Networks

    Science.gov (United States)

    Karpatne, A.; Kumar, V.

    2017-12-01

    Generative adversarial networks (GANs), that have been highly successful in a number of applications involving large volumes of labeled and unlabeled data such as computer vision, offer huge potential for modeling the dynamics of physical processes that have been traditionally studied using simulations of physics-based models. While conventional physics-based models use labeled samples of input/output variables for model calibration (estimating the right parametric forms of relationships between variables) or data assimilation (identifying the most likely sequence of system states in dynamical systems), there is a greater opportunity to explore the full power of machine learning (ML) methods (e.g, GANs) for studying physical processes currently suffering from large knowledge gaps, e.g. ground-water flow. However, success in this endeavor requires a principled way of combining the strengths of ML methods with physics-based numerical models that are founded on a wealth of scientific knowledge. This is especially important in scientific domains like hydrology where the number of data samples is small (relative to Internet-scale applications such as image recognition where machine learning methods has found great success), and the physical relationships are complex (high-dimensional) and non-stationary. We will present a series of methods for guiding the learning of GANs using physics-based models, e.g., by using the outputs of physics-based models as input data to the generator-learner framework, and by using physics-based models as generators trained using validation data in the adversarial learning framework. These methods are being developed under the broad paradigm of theory-guided data science that we are developing to integrate scientific knowledge with data science methods for accelerating scientific discovery.

  18. Developing Learning Model Based on Local Culture and Instrument for Mathematical Higher Order Thinking Ability

    Science.gov (United States)

    Saragih, Sahat; Napitupulu, E. Elvis; Fauzi, Amin

    2017-01-01

    This research aims to develop a student-centered learning model based on local culture and instrument of mathematical higher order thinking of junior high school students in the frame of the 2013-Curriculum in North Sumatra, Indonesia. The subjects of the research are seventh graders which are taken proportionally random consisted of three public…

  19. The Actualization of Literary Learning Model Based on Verbal-Linguistic Intelligence

    Science.gov (United States)

    Hali, Nur Ihsan

    2017-01-01

    This article is inspired by Howard Gardner's concept of linguistic intelligence and also from some authors' previous writings. All of them became the authors' reference in developing ideas on constructing a literary learning model based on linguistic intelligence. The writing of this article is not done by collecting data empirically, but by…

  20. Summer Teacher Enhancement Institute for Science, Mathematics, and Technology Using the Problem-Based Learning Model

    Science.gov (United States)

    Petersen, Richard H.

    1997-01-01

    The objectives of the Institute were: (a) increase participants' content knowledge about aeronautics, science, mathematics, and technology, (b) model and promote the use of scientific inquiry through problem-based learning, (c) investigate the use of instructional technologies and their applications to curricula, and (d) encourage the dissemination of TEI experiences to colleagues, students, and parents.

  1. Assessment of Programming Language Learning Based on Peer Code Review Model: Implementation and Experience Report

    Science.gov (United States)

    Wang, Yanqing; Li, Hang; Feng, Yuqiang; Jiang, Yu; Liu, Ying

    2012-01-01

    The traditional assessment approach, in which one single written examination counts toward a student's total score, no longer meets new demands of programming language education. Based on a peer code review process model, we developed an online assessment system called "EduPCR" and used a novel approach to assess the learning of computer…

  2. PENGEMBANGAN TUGAS AKHIR MELALUI PROJECT BASED LEARNING MODEL UNTUK MENINGKATKAN GENERIC GREEN SKILLS SISWA

    Directory of Open Access Journals (Sweden)

    Ana Ana

    2015-02-01

    Full Text Available ABSTRACT The development of students’ final project through Project-based Learning (PBLapproach was conducted in the workshop of family resource management (FRM in 7th semester.PBL approach is expected to give contribution to students’ motivation and experience to finish their final assignments of FRM workshop. The objectives of the research are to: (1 develop PBL model for the students’final project; (2 produce learning instruments of PBL such as lesson plans, manual of FRM workshop, and scientific report of FRM workshop. The method of the study was using research and development of Plomp model and quasi experiment for testing the effectiveness of the model. The research subjects were the students from the class of 2009 and 2010 who joined FRM workshop course. The study produced model, lesson plans, and manual of FRM workshop as the outputs. The result showed that project based learning model was effective to improve the students’ generic green skills for project management, collaborative skills, and communicative competence. Keywords: final project, generic green skill, family resource management, Project-Based Learning

  3. Collective learning modeling based on the kinetic theory of active particles.

    Science.gov (United States)

    Burini, D; De Lillo, S; Gibelli, L

    2016-03-01

    This paper proposes a systems approach to the theory of perception and learning in populations composed of many living entities. Starting from a phenomenological description of these processes, a mathematical structure is derived which is deemed to incorporate their complexity features. The modeling is based on a generalization of kinetic theory methods where interactions are described by theoretical tools of game theory. As an application, the proposed approach is used to model the learning processes that take place in a classroom. Copyright © 2015 Elsevier B.V. All rights reserved.

  4. Cooperative Problem-Based Learning (CPBL: A Practical PBL Model for a Typical Course

    Directory of Open Access Journals (Sweden)

    Khairiyah Mohd-Yusof

    2011-09-01

    Full Text Available Problem-Based Learning (PBL is an inductive learning approach that uses a realistic problem as the starting point of learning. Unlike in medical education, which is more easily adaptable to PBL, implementing PBL in engineering courses in the traditional semester system set-up is challenging. While PBL is normally implemented in small groups of up to ten students with a dedicated tutor during PBL sessions in medical education, this is not plausible in engineering education because of the high enrolment and large class sizes. In a typical course, implementation of PBL consisting of students in small groups in medium to large classes is more practical. However, this type of implementation is more difficult to monitor, and thus requires good support and guidance in ensuring commitment and accountability of each student towards learning in his/her group. To provide the required support, Cooperative Learning (CL is identified to have the much needed elements to develop the small student groups to functional learning teams. Combining both CL and PBL results in a Cooperative Problem-Based Learning (CPBL model that provides a step by step guide for students to go through the PBL cycle in their teams, according to CL principles. Suitable for implementation in medium to large classes (approximately 40-60 students for one floating facilitator, with small groups consisting of 3-5 students, the CPBL model is designed to develop the students in the whole class into a learning community. This paper provides a detailed description of the CPBL model. A sample implementation in a third year Chemical Engineering course, Process Control and Dynamics, is also described.

  5. Progressive sampling-based Bayesian optimization for efficient and automatic machine learning model selection.

    Science.gov (United States)

    Zeng, Xueqiang; Luo, Gang

    2017-12-01

    Machine learning is broadly used for clinical data analysis. Before training a model, a machine learning algorithm must be selected. Also, the values of one or more model parameters termed hyper-parameters must be set. Selecting algorithms and hyper-parameter values requires advanced machine learning knowledge and many labor-intensive manual iterations. To lower the bar to machine learning, miscellaneous automatic selection methods for algorithms and/or hyper-parameter values have been proposed. Existing automatic selection methods are inefficient on large data sets. This poses a challenge for using machine learning in the clinical big data era. To address the challenge, this paper presents progressive sampling-based Bayesian optimization, an efficient and automatic selection method for both algorithms and hyper-parameter values. We report an implementation of the method. We show that compared to a state of the art automatic selection method, our method can significantly reduce search time, classification error rate, and standard deviation of error rate due to randomization. This is major progress towards enabling fast turnaround in identifying high-quality solutions required by many machine learning-based clinical data analysis tasks.

  6. Implementing learning organization components in Ardabil Regional Water Company based on Marquardt systematic model

    Directory of Open Access Journals (Sweden)

    Shahram Mirzaie Daryani

    2015-09-01

    Full Text Available This main purpose of this study was to survey the implementation of learning organization characteristics based on Marquardt systematic model in Ardabil Regional Water Company. Two hundred and four staff (164 employees and 40 authorities participated in the study. For data collection Marquardt questionnaire was used which its validity and reliability had been confirmed. The results of the data analysis showed that learning organization characteristics were used more than average level in some subsystems of Marquardt model and there was a significant difference between current position and excellent position based on learning organization characteristic application. The results of this study can be used to improve work processes of organizations and institutions.

  7. PENGARUH MODEL PROJECT BASED LEARNING TERHADAP KEMAMPUAN BERPIKIR KREATIF MATEMATIKA SISWA

    Directory of Open Access Journals (Sweden)

    Hesti Noviyana

    2017-09-01

    Full Text Available Abstract: The problems in this study relate to the learning model of Project Based Learning and students' creative thinking ability in mathematics. The purpose of the research to know the influence of the model of Project Based Learning on the ability to think creatively mathematics students VIII grade even semester SMP Negeri 3 Bandar Lampung lesson 2016/2017 . The research used experimental method with the population that is all students of class VIII with the amount of 347, while the sample is taken 2 class that is class VIII A as experiment class which amounted to 31, class VIII C as control class which amounted 30. The sample was taken using Cluster Random Sampling technique. To know the ability of creative thinking mathematics students authors perform tests in the form of essays as many as 5 questions that have been tested the validity and reliability. Hypothesis testing in this study using t test. From the results of hypothesis testing using t-test obtained t value = 14.27. From the distribution table t at the significant level of 5% is known t = 2.00 means t> t, so it can be concluded "There is Influence of Model Based Project Based on the Ability of Creative Thinking Mathematics Students".Keywords: Project Based Learning, creative thinking ability of mathematics

  8. From exemplar to grammar: a probabilistic analogy-based model of language learning.

    Science.gov (United States)

    Bod, Rens

    2009-07-01

    While rules and exemplars are usually viewed as opposites, this paper argues that they form end points of the same distribution. By representing both rules and exemplars as (partial) trees, we can take into account the fluid middle ground between the two extremes. This insight is the starting point for a new theory of language learning that is based on the following idea: If a language learner does not know which phrase-structure trees should be assigned to initial sentences, s/he allows (implicitly) for all possible trees and lets linguistic experience decide which is the "best" tree for each sentence. The best tree is obtained by maximizing "structural analogy" between a sentence and previous sentences, which is formalized by the most probable shortest combination of subtrees from all trees of previous sentences. Corpus-based experiments with this model on the Penn Treebank and the Childes database indicate that it can learn both exemplar-based and rule-based aspects of language, ranging from phrasal verbs to auxiliary fronting. By having learned the syntactic structures of sentences, we have also learned the grammar implicit in these structures, which can in turn be used to produce new sentences. We show that our model mimicks children's language development from item-based constructions to abstract constructions, and that the model can simulate some of the errors made by children in producing complex questions. Copyright © 2009 Cognitive Science Society, Inc.

  9. Model Integrated Problem Solving Based Learning pada Perkuliahan Dasar-dasar Kimia Analitik

    Directory of Open Access Journals (Sweden)

    Indarini Dwi Pursitasari

    2013-07-01

    Full Text Available Abstract: Integrated Problem Solving Based Learning Model on Foundation of Analytical Chemistry. This study was conducted to know the effects of Integrated Problem Solving Based Learning (IPSBL model on problem solving skills and cognitive ability of pre-service teachers. The subjects of the study were 41 pre- service teachers, 21 in the experimental group and 20 in the control group. The data were collected through a test on problem solving skills, a test on cognitive ability, and a questionnaire on the students’opinions on the use of IPSBL model. The quantitative data were analyzed using t-test and one-way ANOVA, and the qualitative data were analyzed by counting the percentage. The results of the study show that the implementation of IPSBL model increased the problem solving skills and cognitive ability of the pre-service teachers . The model was also responded positively by the research subjects. Abstrak: Model Integrated Problem Solving Based learning pada Perkuliahan Dasar-dasar Kimia Analitik. Penelitian ini bertujuan menentukan pengaruh model Integrated Problem Solving Based Learning(IPSBL terhadap peningkatan kemampuan problem solving dan kemampuan kognitif mahasiswa calon guru. Subjek penelitian terdiri dari 21 mahasiswa kelas eksperimen dan 20 mahasiswa kelas kontrol. Data dikumpulkan menggunakan tes kemampuan problem solving, tes kemampuan kognitif, dan angket untuk menjaring pendapat mahasiswa terhadap penggunaan model IPSBL . Data kuantitatif dianalisis denga n uji- t dan Anava dengan bantuan program SPSS 16.0. Data kualitatif dihitung persentasenya. Hasil penelitian menunjukkan bahwa model IPSBL dapat meningkatkan kemampuan problem solving dan kemampuan kognitif serta mendapat tanggapan yang positif dari mahasiswa.

  10. Improving Science Process Skills for Primary School Students Through 5E Instructional Model-Based Learning

    Science.gov (United States)

    Choirunnisa, N. L.; Prabowo, P.; Suryanti, S.

    2018-01-01

    The main objective of this study is to describe the effectiveness of 5E instructional model-based learning to improve primary school students’ science process skills. The science process skills is important for students as it is the foundation for enhancing the mastery of concepts and thinking skills needed in the 21st century. The design of this study was experimental involving one group pre-test and post-test design. The result of this study shows that (1) the implementation of learning in both of classes, IVA and IVB, show that the percentage of learning implementation increased which indicates a better quality of learning and (2) the percentage of students’ science process skills test results on the aspects of observing, formulating hypotheses, determining variable, interpreting data and communicating increased as well.

  11. Force Sensor Based Tool Condition Monitoring Using a Heterogeneous Ensemble Learning Model

    Directory of Open Access Journals (Sweden)

    Guofeng Wang

    2014-11-01

    Full Text Available Tool condition monitoring (TCM plays an important role in improving machining efficiency and guaranteeing workpiece quality. In order to realize reliable recognition of the tool condition, a robust classifier needs to be constructed to depict the relationship between tool wear states and sensory information. However, because of the complexity of the machining process and the uncertainty of the tool wear evolution, it is hard for a single classifier to fit all the collected samples without sacrificing generalization ability. In this paper, heterogeneous ensemble learning is proposed to realize tool condition monitoring in which the support vector machine (SVM, hidden Markov model (HMM and radius basis function (RBF are selected as base classifiers and a stacking ensemble strategy is further used to reflect the relationship between the outputs of these base classifiers and tool wear states. Based on the heterogeneous ensemble learning classifier, an online monitoring system is constructed in which the harmonic features are extracted from force signals and a minimal redundancy and maximal relevance (mRMR algorithm is utilized to select the most prominent features. To verify the effectiveness of the proposed method, a titanium alloy milling experiment was carried out and samples with different tool wear states were collected to build the proposed heterogeneous ensemble learning classifier. Moreover, the homogeneous ensemble learning model and majority voting strategy are also adopted to make a comparison. The analysis and comparison results show that the proposed heterogeneous ensemble learning classifier performs better in both classification accuracy and stability.

  12. Identifying potential misfit items in cognitive process of learning engineering mathematics based on Rasch model

    International Nuclear Information System (INIS)

    Ataei, Sh; Mahmud, Z; Khalid, M N

    2014-01-01

    The students learning outcomes clarify what students should know and be able to demonstrate after completing their course. So, one of the issues on the process of teaching and learning is how to assess students' learning. This paper describes an application of the dichotomous Rasch measurement model in measuring the cognitive process of engineering students' learning of mathematics. This study provides insights into the perspective of 54 engineering students' cognitive ability in learning Calculus III based on Bloom's Taxonomy on 31 items. The results denote that some of the examination questions are either too difficult or too easy for the majority of the students. This analysis yields FIT statistics which are able to identify if there is data departure from the Rasch theoretical model. The study has identified some potential misfit items based on the measurement of ZSTD where the removal misfit item was accomplished based on the MNSQ outfit of above 1.3 or less than 0.7 logit. Therefore, it is recommended that these items be reviewed or revised to better match the range of students' ability in the respective course.

  13. Pengembangan Critical Thinking melalui Penerapan Model PBL (Problem Based Learning) dalam Pembelajaran Sains

    OpenAIRE

    Widowati, Asri

    2010-01-01

    This paper examines to explore how study by using model of Problem Based Learning ( PBL). Basically, this discussion is focussed at model of PBL as an effort in developing cognitive ability, especially critical thinking.Critical thinking including ability think high level (higher order of thinking) representing one of the component in issue intellegence of 21 st century ( Issue of The 21st literacy century). Development of ability of critical thinking in study of science of vital importance b...

  14. Validity of "Hi_Science" as instructional media based-android refer to experiential learning model

    Science.gov (United States)

    Qamariah, Jumadi, Senam, Wilujeng, Insih

    2017-08-01

    Hi_Science is instructional media based-android in learning science on material environmental pollution and global warming. This study is aimed: (a) to show the display of Hi_Science that will be applied in Junior High School, and (b) to describe the validity of Hi_Science. Hi_Science as instructional media created with colaboration of innovative learning model and development of technology at the current time. Learning media selected is based-android and collaborated with experiential learning model as an innovative learning model. Hi_Science had adapted student worksheet by Taufiq (2015). Student worksheet had very good category by two expert lecturers and two science teachers (Taufik, 2015). This student worksheet is refined and redeveloped in android as an instructional media which can be used by students for learning science not only in the classroom, but also at home. Therefore, student worksheet which has become instructional media based-android must be validated again. Hi_Science has been validated by two experts. The validation is based on assessment of meterials aspects and media aspects. The data collection was done by media assessment instrument. The result showed the assessment of material aspects has obtained the average value 4,72 with percentage of agreement 96,47%, that means Hi_Science on the material aspects is in excellent category or very valid category. The assessment of media aspects has obtained the average value 4,53 with percentage of agreement 98,70%, that means Hi_Science on the media aspects is in excellent category or very valid category. It was concluded that Hi_Science as instructional media can be applied in the junior high school.

  15. A Deep Learning based Approach to Reduced Order Modeling of Fluids using LSTM Neural Networks

    Science.gov (United States)

    Mohan, Arvind; Gaitonde, Datta

    2017-11-01

    Reduced Order Modeling (ROM) can be used as surrogates to prohibitively expensive simulations to model flow behavior for long time periods. ROM is predicated on extracting dominant spatio-temporal features of the flow from CFD or experimental datasets. We explore ROM development with a deep learning approach, which comprises of learning functional relationships between different variables in large datasets for predictive modeling. Although deep learning and related artificial intelligence based predictive modeling techniques have shown varied success in other fields, such approaches are in their initial stages of application to fluid dynamics. Here, we explore the application of the Long Short Term Memory (LSTM) neural network to sequential data, specifically to predict the time coefficients of Proper Orthogonal Decomposition (POD) modes of the flow for future timesteps, by training it on data at previous timesteps. The approach is demonstrated by constructing ROMs of several canonical flows. Additionally, we show that statistical estimates of stationarity in the training data can indicate a priori how amenable a given flow-field is to this approach. Finally, the potential and limitations of deep learning based ROM approaches will be elucidated and further developments discussed.

  16. Perspectives on a Learning-Model for Innovating Game-Based Movement in Sports and Health

    DEFF Research Database (Denmark)

    Elbæk, Lars; Friis, Jørgen Jakob

    2017-01-01

    science and health education. We therefore ask: Which learning approach and educational factors does a learning model need to provide, in order to establish the best foundation for learning innovation and the design of game-based movement solutions within sport and health education? This paper suggests......As fitness trackers promote the quantifiable self and exergaming and interactive playful installations find their way into the public domain, the design for movement comes into focus. New trends like mobile platforms for gamed-based interaction, such as Pokémon GO, are also attempting to promote...... an active lifestyle. Such digitally supported movement promote health and underlines a need for students to understand that movement design incorporates many aspects: technology, gamification, motivation and understanding of health. To support this, a movement innovation program was needed at our sports...

  17. A Model of Small-Group Problem-Based Learning in Pharmacy Education: Teaching in the Clinical Environment

    Science.gov (United States)

    Khumsikiew, Jeerisuda; Donsamak, Sisira; Saeteaw, Manit

    2015-01-01

    Problem-based Learning (PBL) is an alternate method of instruction that incorporates basic elements of cognitive learning theory. Colleges of pharmacy use PBL to aid anticipated learning outcomes and practice competencies for pharmacy student. The purpose of this study were to implement and evaluate a model of small group PBL for 5th year pharmacy…

  18. Analysis of factors affecting satisfaction level on problem based learning approach using structural equation modeling

    Science.gov (United States)

    Hussain, Nur Farahin Mee; Zahid, Zalina

    2014-12-01

    Nowadays, in the job market demand, graduates are expected not only to have higher performance in academic but they must also be excellent in soft skill. Problem-Based Learning (PBL) has a number of distinct advantages as a learning method as it can deliver graduates that will be highly prized by industry. This study attempts to determine the satisfaction level of engineering students on the PBL Approach and to evaluate their determinant factors. The Structural Equation Modeling (SEM) was used to investigate how the factors of Good Teaching Scale, Clear Goals, Student Assessment and Levels of Workload affected the student satisfaction towards PBL approach.

  19. A visual tracking method based on deep learning without online model updating

    Science.gov (United States)

    Tang, Cong; Wang, Yicheng; Feng, Yunsong; Zheng, Chao; Jin, Wei

    2018-02-01

    The paper proposes a visual tracking method based on deep learning without online model updating. In consideration of the advantages of deep learning in feature representation, deep model SSD (Single Shot Multibox Detector) is used as the object extractor in the tracking model. Simultaneously, the color histogram feature and HOG (Histogram of Oriented Gradient) feature are combined to select the tracking object. In the process of tracking, multi-scale object searching map is built to improve the detection performance of deep detection model and the tracking efficiency. In the experiment of eight respective tracking video sequences in the baseline dataset, compared with six state-of-the-art methods, the method in the paper has better robustness in the tracking challenging factors, such as deformation, scale variation, rotation variation, illumination variation, and background clutters, moreover, its general performance is better than other six tracking methods.

  20. Learning to maximize reward rate: a model based on semi-Markov decision processes.

    Science.gov (United States)

    Khodadadi, Arash; Fakhari, Pegah; Busemeyer, Jerome R

    2014-01-01

    WHEN ANIMALS HAVE TO MAKE A NUMBER OF DECISIONS DURING A LIMITED TIME INTERVAL, THEY FACE A FUNDAMENTAL PROBLEM: how much time they should spend on each decision in order to achieve the maximum possible total outcome. Deliberating more on one decision usually leads to more outcome but less time will remain for other decisions. In the framework of sequential sampling models, the question is how animals learn to set their decision threshold such that the total expected outcome achieved during a limited time is maximized. The aim of this paper is to provide a theoretical framework for answering this question. To this end, we consider an experimental design in which each trial can come from one of the several possible "conditions." A condition specifies the difficulty of the trial, the reward, the penalty and so on. We show that to maximize the expected reward during a limited time, the subject should set a separate value of decision threshold for each condition. We propose a model of learning the optimal value of decision thresholds based on the theory of semi-Markov decision processes (SMDP). In our model, the experimental environment is modeled as an SMDP with each "condition" being a "state" and the value of decision thresholds being the "actions" taken in those states. The problem of finding the optimal decision thresholds then is cast as the stochastic optimal control problem of taking actions in each state in the corresponding SMDP such that the average reward rate is maximized. Our model utilizes a biologically plausible learning algorithm to solve this problem. The simulation results show that at the beginning of learning the model choses high values of decision threshold which lead to sub-optimal performance. With experience, however, the model learns to lower the value of decision thresholds till finally it finds the optimal values.

  1. The effectiveness of snow cube throwing learning model based on exploration

    Science.gov (United States)

    Sari, Nenden Mutiara

    2017-08-01

    This study aimed to know the effectiveness of Snow Cube Throwing (SCT) and Cooperative Model in Exploration-Based Math Learning in terms of the time required to complete the teaching materials and student engagement. This study was quasi-experimental research was conducted at SMPN 5 Cimahi, Indonesia. All student in grade VIII SMPN 5 Cimahi which consists of 382 students is used as population. The sample consists of two classes which had been chosen randomly with purposive sampling. First experiment class consists of 38 students and the second experiment class consists of 38 students. Observation sheet was used to observe the time required to complete the teaching materials and record the number of students involved in each meeting. The data obtained was analyzed by independent sample-t test and used the chart. The results of this study: SCT learning model based on exploration are more effective than cooperative learning models based on exploration in terms of the time required to complete teaching materials based on exploration and student engagement.

  2. Mobile Inquiry Based Learning

    NARCIS (Netherlands)

    Specht, Marcus

    2012-01-01

    Specht, M. (2012, 8 November). Mobile Inquiry Based Learning. Presentation given at the Workshop "Mobile inquiry-based learning" at the Mobile Learning Day 2012 at the Fernuniversität Hagen, Hagen, Germany.

  3. Model-Based Learning of Local Image Features for Unsupervised Texture Segmentation

    Science.gov (United States)

    Kiechle, Martin; Storath, Martin; Weinmann, Andreas; Kleinsteuber, Martin

    2018-04-01

    Features that capture well the textural patterns of a certain class of images are crucial for the performance of texture segmentation methods. The manual selection of features or designing new ones can be a tedious task. Therefore, it is desirable to automatically adapt the features to a certain image or class of images. Typically, this requires a large set of training images with similar textures and ground truth segmentation. In this work, we propose a framework to learn features for texture segmentation when no such training data is available. The cost function for our learning process is constructed to match a commonly used segmentation model, the piecewise constant Mumford-Shah model. This means that the features are learned such that they provide an approximately piecewise constant feature image with a small jump set. Based on this idea, we develop a two-stage algorithm which first learns suitable convolutional features and then performs a segmentation. We note that the features can be learned from a small set of images, from a single image, or even from image patches. The proposed method achieves a competitive rank in the Prague texture segmentation benchmark, and it is effective for segmenting histological images.

  4. Deep Learning Based Solar Flare Forecasting Model. I. Results for Line-of-sight Magnetograms

    Science.gov (United States)

    Huang, Xin; Wang, Huaning; Xu, Long; Liu, Jinfu; Li, Rong; Dai, Xinghua

    2018-03-01

    Solar flares originate from the release of the energy stored in the magnetic field of solar active regions, the triggering mechanism for these flares, however, remains unknown. For this reason, the conventional solar flare forecast is essentially based on the statistic relationship between solar flares and measures extracted from observational data. In the current work, the deep learning method is applied to set up the solar flare forecasting model, in which forecasting patterns can be learned from line-of-sight magnetograms of solar active regions. In order to obtain a large amount of observational data to train the forecasting model and test its performance, a data set is created from line-of-sight magnetogarms of active regions observed by SOHO/MDI and SDO/HMI from 1996 April to 2015 October and corresponding soft X-ray solar flares observed by GOES. The testing results of the forecasting model indicate that (1) the forecasting patterns can be automatically reached with the MDI data and they can also be applied to the HMI data; furthermore, these forecasting patterns are robust to the noise in the observational data; (2) the performance of the deep learning forecasting model is not sensitive to the given forecasting periods (6, 12, 24, or 48 hr); (3) the performance of the proposed forecasting model is comparable to that of the state-of-the-art flare forecasting models, even if the duration of the total magnetograms continuously spans 19.5 years. Case analyses demonstrate that the deep learning based solar flare forecasting model pays attention to areas with the magnetic polarity-inversion line or the strong magnetic field in magnetograms of active regions.

  5. PENERAPAN MODEL PROBLEM BASED LEARNING MENINGKATKAN MOTIVASI DAN HASIL BELAJAR IPS

    Directory of Open Access Journals (Sweden)

    Auliah Sumitro H

    2017-09-01

    Full Text Available This research aims to improve motivation and student learning outcomes in applying Problem Based Learning model. This research is a classroom action research conducted in two cycles. The subjects of the reasearch was the fourth graders of SD Inpres Bangkala III Makassar city in the academic year of 2016/2017. The research data obtained through observation and test. The result showed an increase in student motivation of the fourth aspect with detail, on aspect of attention increased by 11,28% from 73,04 in the first cycle to 84,32% in the second cycle, the relevance aspect increasde by 9,64% of 76.55% in the first cycle to 86,19% in the second cycle, the aspect of confidence increased by 10,62% of 71.56% in the first cycle to 82.18% in the second cycle, and on aspects of satisfaction increased by 14,88% of 71,79% in the first cycle to 86.67% in the second cycle. Learning outcome increased by 14,29% of 71,42 in the first cycle to 85,71 in the second cycle. This result indicate problem based learning model can improve motivation and student learning outcomes. Penelitian ini bertujuan untuk meningkatkan motivasi dan hasil belajar siswa menerapkan model Problem Based Learning. Penelitian ini merupakan Penelitian Tindakan Kelas (PTK yang dilaksanakan dalam dua siklus. Subjek penelitian adalah siswa kelas IV SD Inpres Bangkala III Kota Makassar tahun pelajaran 2016/2017. Data penelitian diperoleh melalui observasi dan tes. Hasil penelitian ini terjadi peningkatan motivasi siswa pada keempat aspek dengan rincian, pada aspek attention sebesar 11,28% dari 73,04% pada siklus I menjadi 84,32% pada siklus II, pada aspek relevance meningkat sebesar 9,64% dari 76,55% pada siklus I menjadi 86,19% pada siklus II, pada aspek confidence meningkat sebesar 10,62% dari 71,56% pada siklus I menjadi 82,18% pada siklus II, dan pada aspek satisfaction meningkat sebesar 14,88% dari 71,79% pada siklus I menjadi 86,67% pada siklus II. Hasil belajar meningkat sebesar 14

  6. Prototype-based Models for the Supervised Learning of Classification Schemes

    Science.gov (United States)

    Biehl, Michael; Hammer, Barbara; Villmann, Thomas

    2017-06-01

    An introduction is given to the use of prototype-based models in supervised machine learning. The main concept of the framework is to represent previously observed data in terms of so-called prototypes, which reflect typical properties of the data. Together with a suitable, discriminative distance or dissimilarity measure, prototypes can be used for the classification of complex, possibly high-dimensional data. We illustrate the framework in terms of the popular Learning Vector Quantization (LVQ). Most frequently, standard Euclidean distance is employed as a distance measure. We discuss how LVQ can be equipped with more general dissimilarites. Moreover, we introduce relevance learning as a tool for the data-driven optimization of parameterized distances.

  7. A Deep Learning Prediction Model Based on Extreme-Point Symmetric Mode Decomposition and Cluster Analysis

    OpenAIRE

    Li, Guohui; Zhang, Songling; Yang, Hong

    2017-01-01

    Aiming at the irregularity of nonlinear signal and its predicting difficulty, a deep learning prediction model based on extreme-point symmetric mode decomposition (ESMD) and clustering analysis is proposed. Firstly, the original data is decomposed by ESMD to obtain the finite number of intrinsic mode functions (IMFs) and residuals. Secondly, the fuzzy c-means is used to cluster the decomposed components, and then the deep belief network (DBN) is used to predict it. Finally, the reconstructed ...

  8. Using an LMS for Foreign Language Teaching/Learning: An Attempt Based on the "Cyclic Model of Learning"

    OpenAIRE

    SUMI, Seijiro; TAKEUCHI, Osamu

    2008-01-01

    The purposes of the study are (a) to put the “cyclic model of learning” into practice by means of an LMS (Learning Management System) for foreign language teaching /learning, and (b) to examine how the “cyclic model of learning” influences improvement of students' English ability in both proficiency and achievement. Current major concerns of CALL (Computer Assisted Language learning) research have shifted from piecemeal and experimental tests of the use of technology in a single computer lab ...

  9. Soil-pipe interaction modeling for pipe behavior prediction with super learning based methods

    Science.gov (United States)

    Shi, Fang; Peng, Xiang; Liu, Huan; Hu, Yafei; Liu, Zheng; Li, Eric

    2018-03-01

    Underground pipelines are subject to severe distress from the surrounding expansive soil. To investigate the structural response of water mains to varying soil movements, field data, including pipe wall strains in situ soil water content, soil pressure and temperature, was collected. The research on monitoring data analysis has been reported, but the relationship between soil properties and pipe deformation has not been well-interpreted. To characterize the relationship between soil property and pipe deformation, this paper presents a super learning based approach combining feature selection algorithms to predict the water mains structural behavior in different soil environments. Furthermore, automatic variable selection method, e.i. recursive feature elimination algorithm, were used to identify the critical predictors contributing to the pipe deformations. To investigate the adaptability of super learning to different predictive models, this research employed super learning based methods to three different datasets. The predictive performance was evaluated by R-squared, root-mean-square error and mean absolute error. Based on the prediction performance evaluation, the superiority of super learning was validated and demonstrated by predicting three types of pipe deformations accurately. In addition, a comprehensive understand of the water mains working environments becomes possible.

  10. Development of Learning Management Model Based on Constructivist Theory and Reasoning Strategies for Enhancing the Critical Thinking of Secondary Students

    Science.gov (United States)

    Chaipichit, Dudduan; Jantharajit, Nirat; Chookhampaeng, Sumalee

    2015-01-01

    The objectives of this research were to study issues around the management of science learning, problems that are encountered, and to develop a learning management model to address those problems. The development of that model and the findings of its study were based on Constructivist Theory and literature on reasoning strategies for enhancing…

  11. PENGARUH MODEL PROBLEM BASED LEARNING TERHADAP KEMAMPUAN BERPIKIR ANALITIS DAN KETERAMPILAN PROSES SAINS KIMIA PESERTA DIDIK

    Directory of Open Access Journals (Sweden)

    Eli Rohaeti

    2017-10-01

    Full Text Available This research aimed to investigate the effect of PBL model on students’ analytical thinking abilities and science process skills at rate reaction. This research was quasi experimental research using posttest-only control design. The sample was consisted 2 classess, experiment class used Problem Based Learning model and control class used Direct Instruction model with a total sample of 61 students. Instruments of this research were the observation sheet for measuring science process skills and the integrated assessment instrument which involved two indicators, analytical thinking abilities and science process skills. The result of this study shows that PBL model can increase students’ analytical thinking abilities and science process skills. The mean of posttest analytical thinking abilities and science process skills in experiment class is better than control class. The result of the statistic tests using ancova analysis shows that significance 0.000 < 0.05 at 5% significance level, so there’s effect of the using of PBL model on students’ analytical thinking abilities and science process skills. Abstrak Penelitian ini bertujuan untuk menguji pengaruh model PBL terhadap kemampuan berpikir analitis dan keterampilan proses sains kimia peserta didik pada materi laju reaksi menggunakan instrumen penilaian terintegrasi. Jenis penelitian ini adalah penelitian eksperimen semu. Desain penelitian yang digunakan, yaitu posttest control group design. Sampel dalam penelitian ini sebanyak 61 peserta didik yang dibagi dalam dua kelas, yaitu kelas eksperimen dan kelas kontrol. Kelas eksperimen menggunakan model Problem Based Learning, sedangkan kelas kontrol menggunakan model Direct Instruction. Instrumen yang digunakan dalam penelitian, yaitu lembar observasi untuk mengukur keterampilan proses sains kimia dan instrumen penilaian terintegrasi yang mencakup indikator kemampuan berpikir analitis dan keterampilan proses sains kimia peserta didik. Hasil

  12. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-01-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study…

  13. The Development of Writing Learning Model Based on the Arces Motivation for Students of Senior High School

    Directory of Open Access Journals (Sweden)

    Andreas Kosasih

    2014-08-01

    Full Text Available This research obtains some of the findings which in a word can be described as follows: (1 the step of Introduction (exploration: through study library and observation, it can be found that the quality of writing learning and the need of a better writing learning model, and it is formulated the prototype of writing learning model based on the ARCES motivation, serta dirumuskan prototipe model pembelajaran menulis berbasis motivasi ARCES after the draft is validated by the Indonesian language experts and education technology experts. (2 The step of model development: through development of preliminary model and development of  main model and after it is done by  monitoring, evaluation, focus group discussion and revision, then it is produced a better writing learning model based on ARCES motivation. (3 The step of model effectiveness examination: through pre-test, treatment, and post-test which is produced writing learning model  based on ARCES motivation. From the effectiveness test result of model, it can be concluded that writing learning based on ARCES motivation is more effective (in average value of post test is 83,94 than writing learning conventionally (in average value of post-test is 75,79.

  14. Semi-active control of magnetorheological elastomer base isolation system utilising learning-based inverse model

    Science.gov (United States)

    Gu, Xiaoyu; Yu, Yang; Li, Jianchun; Li, Yancheng

    2017-10-01

    Magnetorheological elastomer (MRE) base isolations have attracted considerable attention over the last two decades thanks to its self-adaptability and high-authority controllability in semi-active control realm. Due to the inherent nonlinearity and hysteresis of the devices, it is challenging to obtain a reasonably complicated mathematical model to describe the inverse dynamics of MRE base isolators and hence to realise control synthesis of the MRE base isolation system. Two aims have been achieved in this paper: i) development of an inverse model for MRE base isolator based on optimal general regression neural network (GRNN); ii) numerical and experimental validation of a real-time semi-active controlled MRE base isolation system utilising LQR controller and GRNN inverse model. The superiority of GRNN inverse model lays in fewer input variables requirement, faster training process and prompt calculation response, which makes it suitable for online training and real-time control. The control system is integrated with a three-storey shear building model and control performance of the MRE base isolation system is compared with bare building, passive-on isolation system and passive-off isolation system. Testing results show that the proposed GRNN inverse model is able to reproduce desired control force accurately and the MRE base isolation system can effectively suppress the structural responses when compared to the passive isolation system.

  15. An analysis of mathematical connection ability based on student learning style on visualization auditory kinesthetic (VAK) learning model with self-assessment

    Science.gov (United States)

    Apipah, S.; Kartono; Isnarto

    2018-03-01

    This research aims to analyze the quality of VAK learning with self-assessment toward the ability of mathematical connection performed by students and to analyze students’ mathematical connection ability based on learning styles in VAK learning model with self-assessment. This research applies mixed method type with concurrent embedded design. The subject of this research consists of VIII grade students from State Junior High School 9 Semarang who apply visual learning style, auditory learning style, and kinesthetic learning style. The data of learning style is collected by using questionnaires, the data of mathematical connection ability is collected by performing tests, and the data of self-assessment is collected by using assessment sheets. The quality of learning is qualitatively valued from planning stage, realization stage, and valuation stage. The result of mathematical connection ability test is analyzed quantitatively by mean test, conducting completeness test, mean differentiation test, and mean proportional differentiation test. The result of the research shows that VAK learning model results in well-qualified learning regarded from qualitative and quantitative sides. Students with visual learning style perform the highest mathematical connection ability, students with kinesthetic learning style perform average mathematical connection ability, and students with auditory learning style perform the lowest mathematical connection ability.

  16. Learning Behavior and Achievement Analysis of a Digital Game-Based Learning Approach Integrating Mastery Learning Theory and Different Feedback Models

    Science.gov (United States)

    Yang, Kai-Hsiang

    2017-01-01

    It is widely accepted that the digital game-based learning approach has the advantage of stimulating students' learning motivation, but simply using digital games in the classroom does not guarantee satisfactory learning achievement, especially in the case of the absence of a teacher. Integrating appropriate learning strategies into a game can…

  17. Accelerated Monte Carlo system reliability analysis through machine-learning-based surrogate models of network connectivity

    International Nuclear Information System (INIS)

    Stern, R.E.; Song, J.; Work, D.B.

    2017-01-01

    The two-terminal reliability problem in system reliability analysis is known to be computationally intractable for large infrastructure graphs. Monte Carlo techniques can estimate the probability of a disconnection between two points in a network by selecting a representative sample of network component failure realizations and determining the source-terminal connectivity of each realization. To reduce the runtime required for the Monte Carlo approximation, this article proposes an approximate framework in which the connectivity check of each sample is estimated using a machine-learning-based classifier. The framework is implemented using both a support vector machine (SVM) and a logistic regression based surrogate model. Numerical experiments are performed on the California gas distribution network using the epicenter and magnitude of the 1989 Loma Prieta earthquake as well as randomly-generated earthquakes. It is shown that the SVM and logistic regression surrogate models are able to predict network connectivity with accuracies of 99% for both methods, and are 1–2 orders of magnitude faster than using a Monte Carlo method with an exact connectivity check. - Highlights: • Surrogate models of network connectivity are developed by machine-learning algorithms. • Developed surrogate models can reduce the runtime required for Monte Carlo simulations. • Support vector machine and logistic regressions are employed to develop surrogate models. • Numerical example of California gas distribution network demonstrate the proposed approach. • The developed models have accuracies 99%, and are 1–2 orders of magnitude faster than MCS.

  18. Estimation of the applicability domain of kernel-based machine learning models for virtual screening

    Directory of Open Access Journals (Sweden)

    Fechner Nikolas

    2010-03-01

    Full Text Available Abstract Background The virtual screening of large compound databases is an important application of structural-activity relationship models. Due to the high structural diversity of these data sets, it is impossible for machine learning based QSAR models, which rely on a specific training set, to give reliable results for all compounds. Thus, it is important to consider the subset of the chemical space in which the model is applicable. The approaches to this problem that have been published so far mostly use vectorial descriptor representations to define this domain of applicability of the model. Unfortunately, these cannot be extended easily to structured kernel-based machine learning models. For this reason, we propose three approaches to estimate the domain of applicability of a kernel-based QSAR model. Results We evaluated three kernel-based applicability domain estimations using three different structured kernels on three virtual screening tasks. Each experiment consisted of the training of a kernel-based QSAR model using support vector regression and the ranking of a disjoint screening data set according to the predicted activity. For each prediction, the applicability of the model for the respective compound is quantitatively described using a score obtained by an applicability domain formulation. The suitability of the applicability domain estimation is evaluated by comparing the model performance on the subsets of the screening data sets obtained by different thresholds for the applicability scores. This comparison indicates that it is possible to separate the part of the chemspace, in which the model gives reliable predictions, from the part consisting of structures too dissimilar to the training set to apply the model successfully. A closer inspection reveals that the virtual screening performance of the model is considerably improved if half of the molecules, those with the lowest applicability scores, are omitted from the screening

  19. Estimation of the applicability domain of kernel-based machine learning models for virtual screening.

    Science.gov (United States)

    Fechner, Nikolas; Jahn, Andreas; Hinselmann, Georg; Zell, Andreas

    2010-03-11

    The virtual screening of large compound databases is an important application of structural-activity relationship models. Due to the high structural diversity of these data sets, it is impossible for machine learning based QSAR models, which rely on a specific training set, to give reliable results for all compounds. Thus, it is important to consider the subset of the chemical space in which the model is applicable. The approaches to this problem that have been published so far mostly use vectorial descriptor representations to define this domain of applicability of the model. Unfortunately, these cannot be extended easily to structured kernel-based machine learning models. For this reason, we propose three approaches to estimate the domain of applicability of a kernel-based QSAR model. We evaluated three kernel-based applicability domain estimations using three different structured kernels on three virtual screening tasks. Each experiment consisted of the training of a kernel-based QSAR model using support vector regression and the ranking of a disjoint screening data set according to the predicted activity. For each prediction, the applicability of the model for the respective compound is quantitatively described using a score obtained by an applicability domain formulation. The suitability of the applicability domain estimation is evaluated by comparing the model performance on the subsets of the screening data sets obtained by different thresholds for the applicability scores. This comparison indicates that it is possible to separate the part of the chemspace, in which the model gives reliable predictions, from the part consisting of structures too dissimilar to the training set to apply the model successfully. A closer inspection reveals that the virtual screening performance of the model is considerably improved if half of the molecules, those with the lowest applicability scores, are omitted from the screening. The proposed applicability domain formulations

  20. Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

    Science.gov (United States)

    Said, Nadia; Engelhart, Michael; Kirches, Christian; Körkel, Stefan; Holt, Daniel V

    2016-01-01

    Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

  1. LEARNING MODEL OF SCHOOL-BASED ANTI BULLYING INTERVENTION IN EAP (ENGLISH FOR ACADEMIC PURPOSES SETTINGS

    Directory of Open Access Journals (Sweden)

    Ririn Ambarini

    2017-12-01

    Full Text Available Bilingual learning can be integrated in any subjects in school. One of the subject is Guidance and Couseling subject that provides opportunities for students to develop their social skills and communication. Today, the phenomenon of bullying often occurs in every aspect of life, and one of them is in educational institutions such as schools. School should be a place to establish a positive attitude and character, but the fact the school becomes the scene of bullying practices. The research question is how the bilingual learning of school-based anti bullying intervension integrated with Guidance and Counseling materials by using English for Academic Purposes settings is. This qualitative study used descriptive qualitative method that aims to understand the process and the outcome of bilingual learning process from the viewpoint or perspective of the participants. This research takes the view that since people are instruments, the objects of the research together with the researcher herself, their active involvement in the process is the key to any sustainable efforts. This research is aslo supposed to identify the students‘ understanding of the school-based anti bullying materials that are implemented in EAP settings. The impact of thus program implementation is certainly expected as the strategies to minimize the impacts that will occur in bullying behavior by the integration of anti-bullying bilingual learning model through guidance and counseling materials.

  2. Learning-Based Just-Noticeable-Quantization- Distortion Modeling for Perceptual Video Coding.

    Science.gov (United States)

    Ki, Sehwan; Bae, Sung-Ho; Kim, Munchurl; Ko, Hyunsuk

    2018-07-01

    Conventional predictive video coding-based approaches are reaching the limit of their potential coding efficiency improvements, because of severely increasing computation complexity. As an alternative approach, perceptual video coding (PVC) has attempted to achieve high coding efficiency by eliminating perceptual redundancy, using just-noticeable-distortion (JND) directed PVC. The previous JNDs were modeled by adding white Gaussian noise or specific signal patterns into the original images, which were not appropriate in finding JND thresholds due to distortion with energy reduction. In this paper, we present a novel discrete cosine transform-based energy-reduced JND model, called ERJND, that is more suitable for JND-based PVC schemes. Then, the proposed ERJND model is extended to two learning-based just-noticeable-quantization-distortion (JNQD) models as preprocessing that can be applied for perceptual video coding. The two JNQD models can automatically adjust JND levels based on given quantization step sizes. One of the two JNQD models, called LR-JNQD, is based on linear regression and determines the model parameter for JNQD based on extracted handcraft features. The other JNQD model is based on a convolution neural network (CNN), called CNN-JNQD. To our best knowledge, our paper is the first approach to automatically adjust JND levels according to quantization step sizes for preprocessing the input to video encoders. In experiments, both the LR-JNQD and CNN-JNQD models were applied to high efficiency video coding (HEVC) and yielded maximum (average) bitrate reductions of 38.51% (10.38%) and 67.88% (24.91%), respectively, with little subjective video quality degradation, compared with the input without preprocessing applied.

  3. The Teaching Model through Problem-Based Learning in a Course on Bibliographic Research

    Directory of Open Access Journals (Sweden)

    Ruth Cristina Hernández-Ching

    2018-02-01

    Full Text Available The experience of applying problem-based learning (PBL technique in the Bibliographic Research course from a Bachelor of English study plan of a public university during the first half of 2014 is shared. The investigation aimed to answer the following question: Does the problem-based learning technique in the Bibliographic Research course allows to implement the main tenets of the teaching model: epistemological foundation, learning theory, methodology and didactics, and communication processes? The research approach proposed was qualitative, and triangulation for measuring variables was implemented. The following instruments were applied: observation, experience record books, and focus groups. Furthermore, formative learning was measured by means of an online survey. Results of the instruments were categorized using technology-based tools such as Wordle (observation, NVivo (record books and MindNode (focus groups. A convenience sampling was used to collect data from eight students enrolled in the Bibliographic Research course, ten students of Integrated English II for non-English majors, and the researcher, as professor of the courses. It was determined that the PBL technique permitted to reach the main tenets of the teaching model. It was identified that the teacher was the main learner, and the one who benefited from the process, since a culture of knowledge, throughout the course, was created. It was also concluded that this technique allowed to develop twenty-first century skills. It would be valuable to quantify whether the development of the four basic skills of English, especially the conversation one, improves using the technique along with technologies.

  4. A Classification Model and an Open E-Learning System Based on Intuitionistic Fuzzy Sets for Instructional Design Concepts

    Science.gov (United States)

    Güyer, Tolga; Aydogdu, Seyhmus

    2016-01-01

    This study suggests a classification model and an e-learning system based on this model for all instructional theories, approaches, models, strategies, methods, and technics being used in the process of instructional design that constitutes a direct or indirect resource for educational technology based on the theory of intuitionistic fuzzy sets…

  5. Influence of Problem-Based Learning Model of Learning to the Mathematical Communication Ability of Students of Grade XI IPA SMAN 14 Padang

    Science.gov (United States)

    Nisa, I. M.

    2018-04-01

    The ability of mathematical communication is one of the goals of learning mathematics expected to be mastered by students. However, reality in the field found that the ability of mathematical communication the students of grade XI IPA SMA Negeri 14 Padang have not developed optimally. This is evident from the low test results of communication skills mathematically done. One of the factors that causes this happens is learning that has not been fully able to facilitate students to develop mathematical communication skills well. By therefore, to improve students' mathematical communication skills required a model in the learning activities. One of the models learning that can be used is Problem Based learning model Learning (PBL). The purpose of this study is to see whether the ability the students' mathematical communication using the PBL model better than the students' mathematical communication skills of the learning using conventional learning in Class XI IPA SMAN 14 Padang. This research type is quasi experiment with design Randomized Group Only Design. Population in this research that is student of class XI IPA SMAN 14 Padang with sample class XI IPA 3 and class XI IPA 4. Data retrieval is done by using communication skill test mathematically shaped essay. To test the hypothesis used U-Mann test Whitney. Based on the results of data analysis, it can be concluded that the ability mathematical communication of students whose learning apply more PBL model better than the students' mathematical communication skills of their learning apply conventional learning in class XI IPA SMA 14 Padang at α = 0.05. This indicates that the PBL learning model effect on students' mathematical communication ability.

  6. The role of inertia in modeling decisions from experience with instance-based learning.

    Science.gov (United States)

    Dutt, Varun; Gonzalez, Cleotilde

    2012-01-01

    One form of inertia is the tendency to repeat the last decision irrespective of the obtained outcomes while making decisions from experience (DFE). A number of computational models based upon the Instance-Based Learning Theory, a theory of DFE, have included different inertia implementations and have shown to simultaneously account for both risk-taking and alternations between alternatives. The role that inertia plays in these models, however, is unclear as the same model without inertia is also able to account for observed risk-taking quite well. This paper demonstrates the predictive benefits of incorporating one particular implementation of inertia in an existing IBL model. We use two large datasets, estimation and competition, from the Technion Prediction Tournament involving a repeated binary-choice task to show that incorporating an inertia mechanism in an IBL model enables it to account for the observed average risk-taking and alternations. Including inertia, however, does not help the model to account for the trends in risk-taking and alternations over trials compared to the IBL model without the inertia mechanism. We generalize the two IBL models, with and without inertia, to the competition set by using the parameters determined in the estimation set. The generalization process demonstrates both the advantages and disadvantages of including inertia in an IBL model.

  7. A learning based model for career guidance of students with disabilites

    DEFF Research Database (Denmark)

    Dræby, Anders

    must address their resources, challenges, potentialities and barriers regarding their employability from a learning based perspective. The objective of this session is to broaden the awareness of the particular challenges that career guidance for people with disabilities constitute.......The session aims at presenting a 4 stage model for career guidance for students with disabilities. In order to enable and empower the disa bled students regarding their employability and employability competencies at the labour market, the presentation shows how career guidance of these students...

  8. Developing Environmentally Responsible Behaviours Through the Implementation of Argumentation- and Problem-Based Learning Models

    Science.gov (United States)

    Fettahlıoğlu, Pınar; Aydoğdu, Mustafa

    2018-04-01

    The purpose of this research is to investigate the effect of using argumentation and problem-based learning approaches on the development of environmentally responsible behaviours among pre-service science teachers. Experimental activities were implemented for 14 weeks for 52 class hours in an environmental education class within a science teaching department. A mixed method was used as a research design; particularly, a special type of Concurrent Nested Strategy was applied. The quantitative portion was based on the one-group pre-test and post-test models, and the qualitative portion was based on the holistic multiple-case study method. The quantitative portion of the research was conducted with 34 third-year pre-service science teachers studying at a state university. The qualitative portion of the study was conducted with six pre-service science teachers selected among the 34 pre-service science teachers based on the pre-test results obtained from an environmentally responsible behaviour scale. t tests for dependent groups were used to analyse quantitative data. Both descriptive and content analyses of the qualitative data were performed. The results of the study showed that the use of the argumentation and problem-based learning approaches significantly contributed to the development of environmentally responsible behaviours among pre-service science teachers.

  9. Possible world based consistency learning model for clustering and classifying uncertain data.

    Science.gov (United States)

    Liu, Han; Zhang, Xianchao; Zhang, Xiaotong

    2018-06-01

    Possible world has shown to be effective for handling various types of data uncertainty in uncertain data management. However, few uncertain data clustering and classification algorithms are proposed based on possible world. Moreover, existing possible world based algorithms suffer from the following issues: (1) they deal with each possible world independently and ignore the consistency principle across different possible worlds; (2) they require the extra post-processing procedure to obtain the final result, which causes that the effectiveness highly relies on the post-processing method and the efficiency is also not very good. In this paper, we propose a novel possible world based consistency learning model for uncertain data, which can be extended both for clustering and classifying uncertain data. This model utilizes the consistency principle to learn a consensus affinity matrix for uncertain data, which can make full use of the information across different possible worlds and then improve the clustering and classification performance. Meanwhile, this model imposes a new rank constraint on the Laplacian matrix of the consensus affinity matrix, thereby ensuring that the number of connected components in the consensus affinity matrix is exactly equal to the number of classes. This also means that the clustering and classification results can be directly obtained without any post-processing procedure. Furthermore, for the clustering and classification tasks, we respectively derive the efficient optimization methods to solve the proposed model. Experimental results on real benchmark datasets and real world uncertain datasets show that the proposed model outperforms the state-of-the-art uncertain data clustering and classification algorithms in effectiveness and performs competitively in efficiency. Copyright © 2018 Elsevier Ltd. All rights reserved.

  10. The Game Enhanced Learning Model

    DEFF Research Database (Denmark)

    Reng, Lars; Schoenau-Fog, Henrik

    2016-01-01

    will describe the levels of the model, which is based on our experience in teaching professional game development at university level. Furthermore, we have been using the model to inspire numerous educators to improve their students’ motivation and skills. The model presents various game-based learning...... activities, and depicts their required planning and expected outcome through eight levels. At its lower levels, the model contains the possibilities of using stand-alone analogue and digital games as teachers, utilizing games as a facilitator of learning activities, exploiting gamification and motivating......In this paper, we will introduce the Game Enhanced learning Model (GEM), which describes a range of gameoriented learning activities. The model is intended to give an overview of the possibilities of game-based learning in general and all the way up to purposive game productions. In the paper, we...

  11. Implementing a Project-Based Learning Model in a Pre-Service Leadership Program

    Science.gov (United States)

    Albritton, Shelly; Stacks, Jamie

    2016-01-01

    This paper describes two instructors' efforts to more authentically engage students in a preservice leadership program's course called Program Planning and Evaluation by using a project-based learning approach. Markham, Larmer, and Ravitz (2003) describe project-based learning (PjBL) as "a systematic teaching method that engages students in…

  12. Cognitive decision modelling of emotion-based learning impairment in schizophrenia: the role of awareness.

    Science.gov (United States)

    Cella, Matteo; Dymond, Simon; Cooper, Andrew; Turnbull, Oliver H

    2012-03-30

    Individuals with schizophrenia often lack insight or awareness. Resulting impairment has been observed in various cognitive domains and, recently, linked to problems in emotion-based learning. The Iowa Gambling Task (IGT) has been used to assess emotion-based decision-making in patients with schizophrenia, but results have been inconclusive. The current study further investigates emotion-based decision-making in schizophrenia by elucidating the unique contribution of awareness. Twenty-five patients with schizophrenia and 24 healthy controls were assessed with a modified version of the IGT recording awareness at regular intervals. Symptom assessment, medication and medical history were recorded for the clinical group. Patients with schizophrenia underperformed on the IGT compared to controls. Subjective awareness levels were significantly lower in the schizophrenia group and were associated with hallucination severity. Cognitive decision modelling further indicated that patients with schizophrenia had impaired attention to losses, compared to controls. This parameter was positively correlated with awareness. We also found that positive symptoms altered awareness levels and suggest that this disruption may contribute to sub-optimal decision-making. Overall, a lack of awareness may be an important aspect in understanding impaired social cognitive functioning and emotion-based learning observed in schizophrenia. Copyright © 2011 Elsevier Ltd. All rights reserved.

  13. Machine Learning-based discovery of closures for reduced models of dynamical systems

    Science.gov (United States)

    Pan, Shaowu; Duraisamy, Karthik

    2017-11-01

    Despite the successful application of machine learning (ML) in fields such as image processing and speech recognition, only a few attempts has been made toward employing ML to represent the dynamics of complex physical systems. Previous attempts mostly focus on parameter calibration or data-driven augmentation of existing models. In this work we present a ML framework to discover closure terms in reduced models of dynamical systems and provide insights into potential problems associated with data-driven modeling. Based on exact closure models for linear system, we propose a general linear closure framework from viewpoint of optimization. The framework is based on trapezoidal approximation of convolution term. Hyperparameters that need to be determined include temporal length of memory effect, number of sampling points, and dimensions of hidden states. To circumvent the explicit specification of memory effect, a general framework inspired from neural networks is also proposed. We conduct both a priori and posteriori evaluations of the resulting model on a number of non-linear dynamical systems. This work was supported in part by AFOSR under the project ``LES Modeling of Non-local effects using Statistical Coarse-graining'' with Dr. Jean-Luc Cambier as the technical monitor.

  14. Development of Web-Based Learning Environment Model to Enhance Cognitive Skills for Undergraduate Students in the Field of Electrical Engineering

    Science.gov (United States)

    Lakonpol, Thongmee; Ruangsuwan, Chaiyot; Terdtoon, Pradit

    2015-01-01

    This research aimed to develop a web-based learning environment model for enhancing cognitive skills of undergraduate students in the field of electrical engineering. The research is divided into 4 phases: 1) investigating the current status and requirements of web-based learning environment models. 2) developing a web-based learning environment…

  15. "The Spiral Model for the Development of Coordination": A Learning Model Based on Eshkol-Wachman Movement Notation (EWMN)

    Science.gov (United States)

    Al-Dor, Nira

    2006-01-01

    The objective of this study is to present "The Spiral Model for the Development of Coordination" (SMDC), a learning model that reflects the complexity and possibilities embodied in the learning of movement notation Eshkol-Wachman (EWMN), an Israeli invention. This model constituted the infrastructure for a comprehensive study that examined the…

  16. The implementation of discovery learning model based on lesson study to increase student's achievement in colloid

    Science.gov (United States)

    Suyanti, Retno Dwi; Purba, Deby Monika

    2017-03-01

    The objectives of this research are to get the increase student's achievement on the discovery learning model based on lesson study. Beside of that, this research also conducted to know the cognitive aspect. This research was done in three school that are SMA N 3 Medan. Population is all the students in SMA N 11 Medan which taken by purposive random sampling. The research instruments are achievement test instruments that have been validated. The research data analyzed by statistic using Ms Excell. The result data shows that the student's achievement taught by discovery learning model based on Lesson study higher than the student's achievement taught by direct instructional method. It can be seen from the average of gain and also proved with t-test, the normalized gain in experimental class of SMA N 11 is (0.74±0.12) and control class (0.45±0.12), at significant level α = 0.05, Ha is received and Ho is refused where tcount>ttable in SMA N 11 (9.81>1,66). Then get the improvement cognitive aspect from three of school is C2 where SMA N 11 is 0.84(high). Then the observation sheet result of lesson study from SMA N 11 92 % of student working together while 67% less in active using media.

  17. Developing and testing transferability and feasibility of a model for educators using simulation-based learning - A European collaboration

    DEFF Research Database (Denmark)

    Bøje, Rikke Buus; Bland, Andrew; Sutton, Andrew

    2017-01-01

    of the study were to develop a model to educate the educators who deliver simulation-based learning and to test to which extent this model could be transferred to education providers in different national settings. METHODS: This model, its transferability and feasibility, was tested across three European...

  18. Meta Analisis Model Pembelajaran Problem Based Learning dalam Meningkatkan Keterampilan Berpikir Kritis di Sekolah Dasar [A Meta-analysis of Problem-Based Learning Models in Increasing Critical Thinking Skills in Elementary Schools

    Directory of Open Access Journals (Sweden)

    Indri Anugraheni

    2018-01-01

    Full Text Available This study aims to analyze Problem-based Learning models intended to improve critical thinking skills in elementary school students. Problem-based learning models are learning processes where students are open minded, reflexive, active, reflective, and critical through real-world context activities. In this study the researcher used a meta-analysis method. First, the researcher formulated the research problem, then proceeded to review the existing relevant research for analysis. Data were collected by using a non-test technique by browsing electronic journals through Google Scholar and studying documentation in the library. Seven articles were found through Google Scholar and only one was found in the library. Based on the analysis of the results, the problem-based learning model can improve students' thinking ability from as little as 2.87% up to 33.56% with an average of 14.18%. BAHASA INDONESIA ABSTRAK: Penelitian ini bertujuan untuk menganalisis kembali tentang model pembelajaran Problem Based Learning untuk meningkatkan keterampilan berpikir kritis di Sekolah Dasar. Model pembelajaran Problem Based Learning adalah proses pembelajaran dimana siswa mampu memiliki pola pikir yang terbuka, refktif, aktif, reflektif dan kritis melalui kegiatan konteks dunia nyata. Dalam penelitian ini peneliti menggunakan metode meta analisis. Pertama-tama, peneliti merumuskan masalah penelitian, kemudian dilanjutkan dengan menelusuri penelitian yang sudah ada dan relevan untuk dianalisis. Teknik pengumpulan data dengan menggunakan non tes yaitu dengan menelusuri jurnal elektronik melalui google Cendekia dan studi dokumentasi di perpustakaan. Dari hasil penelusuran diperoleh 20 artikel dari jurnal dan 3 dari repository. Berdasarkan hasil analisis ternyata model pembelajaran Problem Based Learning mampu meningkatkan kemampuan berpikir Siswa mulai dari yang terendah 2,87% sampai yang tertinggi 33,56% dengan rata-rata 12,73%.

  19. A model of human motor sequence learning explains facilitation and interference effects based on spike-timing dependent plasticity.

    Directory of Open Access Journals (Sweden)

    Quan Wang

    2017-08-01

    Full Text Available The ability to learn sequential behaviors is a fundamental property of our brains. Yet a long stream of studies including recent experiments investigating motor sequence learning in adult human subjects have produced a number of puzzling and seemingly contradictory results. In particular, when subjects have to learn multiple action sequences, learning is sometimes impaired by proactive and retroactive interference effects. In other situations, however, learning is accelerated as reflected in facilitation and transfer effects. At present it is unclear what the underlying neural mechanism are that give rise to these diverse findings. Here we show that a recently developed recurrent neural network model readily reproduces this diverse set of findings. The self-organizing recurrent neural network (SORN model is a network of recurrently connected threshold units that combines a simplified form of spike-timing dependent plasticity (STDP with homeostatic plasticity mechanisms ensuring network stability, namely intrinsic plasticity (IP and synaptic normalization (SN. When trained on sequence learning tasks modeled after recent experiments we find that it reproduces the full range of interference, facilitation, and transfer effects. We show how these effects are rooted in the network's changing internal representation of the different sequences across learning and how they depend on an interaction of training schedule and task similarity. Furthermore, since learning in the model is based on fundamental neuronal plasticity mechanisms, the model reveals how these plasticity mechanisms are ultimately responsible for the network's sequence learning abilities. In particular, we find that all three plasticity mechanisms are essential for the network to learn effective internal models of the different training sequences. This ability to form effective internal models is also the basis for the observed interference and facilitation effects. This suggests that

  20. The Integrated Model of Sustainability Perspective in Spermatophyta Learning Based on Local Wisdom

    Science.gov (United States)

    Hartadiyati, E.; Rizqiyah, K.; Wiyanto; Rusilowati, A.; Prasetia, A. P. B.

    2017-09-01

    In present condition, culture is diminished, the change of social order toward the generation that has no policy and pro-sustainability; As well as the advancement of science and technology are often treated unwisely so as to excite local wisdom. It is therefore necessary to explore intra-curricular local wisdom in schools. This study aims to produce an integration model of sustainability perspectives based on local wisdom on spermatophyta material that is feasible and effective. This research uses define, design and develop stages to an integration model of sustainability perspectives based on local wisdom on spermatophyta material. The resulting product is an integration model of socio-cultural, economic and environmental sustainability perspective and formulated with preventive, preserve and build action on spermatophyta material consisting of identification and classification, metagenesis and the role of spermatophyta for human life. The integration model of sustainability perspective in learning spermatophyta based on local wisdom is considered proven to be effective in raising sustainability’s awareness of high school students.

  1. Characteristics of Problem-Based Learning

    DEFF Research Database (Denmark)

    Kolmos, Anette

    2003-01-01

    Problem BAsed LEarning (PBL) is widely regarded as a successful and innovative method for engineering education. The article highlights the Dutch approach of directing the learning process throuogh problem analysis and the Danish model of project-organised learning...

  2. Cyber situation awareness: modeling detection of cyber attacks with instance-based learning theory.

    Science.gov (United States)

    Dutt, Varun; Ahn, Young-Suk; Gonzalez, Cleotilde

    2013-06-01

    To determine the effects of an adversary's behavior on the defender's accurate and timely detection of network threats. Cyber attacks cause major work disruption. It is important to understand how a defender's behavior (experience and tolerance to threats), as well as adversarial behavior (attack strategy), might impact the detection of threats. In this article, we use cognitive modeling to make predictions regarding these factors. Different model types representing a defender, based on Instance-Based Learning Theory (IBLT), faced different adversarial behaviors. A defender's model was defined by experience of threats: threat-prone (90% threats and 10% nonthreats) and nonthreat-prone (10% threats and 90% nonthreats); and different tolerance levels to threats: risk-averse (model declares a cyber attack after perceiving one threat out of eight total) and risk-seeking (model declares a cyber attack after perceiving seven threats out of eight total). Adversarial behavior is simulated by considering different attack strategies: patient (threats occur late) and impatient (threats occur early). For an impatient strategy, risk-averse models with threat-prone experiences show improved detection compared with risk-seeking models with nonthreat-prone experiences; however, the same is not true for a patient strategy. Based upon model predictions, a defender's prior threat experiences and his or her tolerance to threats are likely to predict detection accuracy; but considering the nature of adversarial behavior is also important. Decision-support tools that consider the role of a defender's experience and tolerance to threats along with the nature of adversarial behavior are likely to improve a defender's overall threat detection.

  3. Conjectural variation based learning model of strategic bidding in spot market

    International Nuclear Information System (INIS)

    Yiqun Song; Yixin Ni; Fushuan Wen; Wu, F.F.

    2004-01-01

    In actual electricity market, which operates repeatedly on the basis of one hour or half hour, each firm might learn or estimate other competitors' strategic behaviors from available historical market operation data, and rationally aims at its maximum profit in the repeated biddings. A conjectural variation based learning method is proposed in this paper for generation firm to improve its strategic bidding performance. In the method, each firm learns and dynamically regulates its conjecture upon the reactions of its rivals to its bidding according to available information published in the electricity market, and then makes its optimal generation decision based on the updated conjectural variation of its rivals. Through such learning process, the equilibrium reached in the market is proven a Nash equilibrium. Motivation of generation firm to learn in the changing market environment and consequence of learning behavior in the market are also discussed through computer tests. (author)

  4. Implications of Bandura's Observational Learning Theory for a Competency Based Teacher Education Model.

    Science.gov (United States)

    Hartjen, Raymond H.

    Albert Bandura of Stanford University has proposed four component processes to his theory of observational learning: a) attention, b) retention, c) motor reproduction, and d) reinforcement and motivation. This study represents one phase of an effort to relate modeling and observational learning theory to teacher training. The problem of this study…

  5. Machine learning based cloud mask algorithm driven by radiative transfer modeling

    Science.gov (United States)

    Chen, N.; Li, W.; Tanikawa, T.; Hori, M.; Shimada, R.; Stamnes, K. H.

    2017-12-01

    Cloud detection is a critically important first step required to derive many satellite data products. Traditional threshold based cloud mask algorithms require a complicated design process and fine tuning for each sensor, and have difficulty over snow/ice covered areas. With the advance of computational power and machine learning techniques, we have developed a new algorithm based on a neural network classifier driven by extensive radiative transfer modeling. Statistical validation results obtained by using collocated CALIOP and MODIS data show that its performance is consistent over different ecosystems and significantly better than the MODIS Cloud Mask (MOD35 C6) during the winter seasons over mid-latitude snow covered areas. Simulations using a reduced number of satellite channels also show satisfactory results, indicating its flexibility to be configured for different sensors.

  6. Structure Based Thermostability Prediction Models for Protein Single Point Mutations with Machine Learning Tools.

    Directory of Open Access Journals (Sweden)

    Lei Jia

    Full Text Available Thermostability issue of protein point mutations is a common occurrence in protein engineering. An application which predicts the thermostability of mutants can be helpful for guiding decision making process in protein design via mutagenesis. An in silico point mutation scanning method is frequently used to find "hot spots" in proteins for focused mutagenesis. ProTherm (http://gibk26.bio.kyutech.ac.jp/jouhou/Protherm/protherm.html is a public database that consists of thousands of protein mutants' experimentally measured thermostability. Two data sets based on two differently measured thermostability properties of protein single point mutations, namely the unfolding free energy change (ddG and melting temperature change (dTm were obtained from this database. Folding free energy change calculation from Rosetta, structural information of the point mutations as well as amino acid physical properties were obtained for building thermostability prediction models with informatics modeling tools. Five supervised machine learning methods (support vector machine, random forests, artificial neural network, naïve Bayes classifier, K nearest neighbor and partial least squares regression are used for building the prediction models. Binary and ternary classifications as well as regression models were built and evaluated. Data set redundancy and balancing, the reverse mutations technique, feature selection, and comparison to other published methods were discussed. Rosetta calculated folding free energy change ranked as the most influential features in all prediction models. Other descriptors also made significant contributions to increasing the accuracy of the prediction models.

  7. Comparison of learning models based on mathematics logical intelligence in affective domain

    Science.gov (United States)

    Widayanto, Arif; Pratiwi, Hasih; Mardiyana

    2018-04-01

    The purpose of this study was to examine the presence or absence of different effects of multiple treatments (used learning models and logical-mathematical intelligence) on the dependent variable (affective domain of mathematics). This research was quasi experimental using 3x3 of factorial design. The population of this research was VIII grade students of junior high school in Karanganyar under the academic year 2017/2018. Data collected in this research was analyzed by two ways analysis of variance with unequal cells using 5% of significance level. The result of the research were as follows: (1) Teaching and learning with model TS lead to better achievement in affective domain than QSH, teaching and learning with model QSH lead to better achievement in affective domain than using DI; (2) Students with high mathematics logical intelligence have better achievement in affective domain than students with low mathematics logical intelligence have; (3) In teaching and learning mathematics using learning model TS, students with moderate mathematics logical intelligence have better achievement in affective domain than using DI; and (4) In teaching and learning mathematics using learning model TS, students with low mathematics logical intelligence have better achievement in affective domain than using QSH and DI.

  8. Model-based iterative learning control of Parkinsonian state in thalamic relay neuron

    Science.gov (United States)

    Liu, Chen; Wang, Jiang; Li, Huiyan; Xue, Zhiqin; Deng, Bin; Wei, Xile

    2014-09-01

    Although the beneficial effects of chronic deep brain stimulation on Parkinson's disease motor symptoms are now largely confirmed, the underlying mechanisms behind deep brain stimulation remain unclear and under debate. Hence, the selection of stimulation parameters is full of challenges. Additionally, due to the complexity of neural system, together with omnipresent noises, the accurate model of thalamic relay neuron is unknown. Thus, the iterative learning control of the thalamic relay neuron's Parkinsonian state based on various variables is presented. Combining the iterative learning control with typical proportional-integral control algorithm, a novel and efficient control strategy is proposed, which does not require any particular knowledge on the detailed physiological characteristics of cortico-basal ganglia-thalamocortical loop and can automatically adjust the stimulation parameters. Simulation results demonstrate the feasibility of the proposed control strategy to restore the fidelity of thalamic relay in the Parkinsonian condition. Furthermore, through changing the important parameter—the maximum ionic conductance densities of low-threshold calcium current, the dominant characteristic of the proposed method which is independent of the accurate model can be further verified.

  9. Prediction of recombinant protein overexpression in Escherichia coli using a machine learning based model (RPOLP).

    Science.gov (United States)

    Habibi, Narjeskhatoon; Norouzi, Alireza; Mohd Hashim, Siti Z; Shamsir, Mohd Shahir; Samian, Razip

    2015-11-01

    Recombinant protein overexpression, an important biotechnological process, is ruled by complex biological rules which are mostly unknown, is in need of an intelligent algorithm so as to avoid resource-intensive lab-based trial and error experiments in order to determine the expression level of the recombinant protein. The purpose of this study is to propose a predictive model to estimate the level of recombinant protein overexpression for the first time in the literature using a machine learning approach based on the sequence, expression vector, and expression host. The expression host was confined to Escherichia coli which is the most popular bacterial host to overexpress recombinant proteins. To provide a handle to the problem, the overexpression level was categorized as low, medium and high. A set of features which were likely to affect the overexpression level was generated based on the known facts (e.g. gene length) and knowledge gathered from related literature. Then, a representative sub-set of features generated in the previous objective was determined using feature selection techniques. Finally a predictive model was developed using random forest classifier which was able to adequately classify the multi-class imbalanced small dataset constructed. The result showed that the predictive model provided a promising accuracy of 80% on average, in estimating the overexpression level of a recombinant protein. Copyright © 2015 Elsevier Ltd. All rights reserved.

  10. Applying Mathematical Optimization Methods to an ACT-R Instance-Based Learning Model.

    Directory of Open Access Journals (Sweden)

    Nadia Said

    Full Text Available Computational models of cognition provide an interface to connect advanced mathematical tools and methods to empirically supported theories of behavior in psychology, cognitive science, and neuroscience. In this article, we consider a computational model of instance-based learning, implemented in the ACT-R cognitive architecture. We propose an approach for obtaining mathematical reformulations of such cognitive models that improve their computational tractability. For the well-established Sugar Factory dynamic decision making task, we conduct a simulation study to analyze central model parameters. We show how mathematical optimization techniques can be applied to efficiently identify optimal parameter values with respect to different optimization goals. Beyond these methodological contributions, our analysis reveals the sensitivity of this particular task with respect to initial settings and yields new insights into how average human performance deviates from potential optimal performance. We conclude by discussing possible extensions of our approach as well as future steps towards applying more powerful derivative-based optimization methods.

  11. Deep learning based classification for head and neck cancer detection with hyperspectral imaging in an animal model

    Science.gov (United States)

    Ma, Ling; Lu, Guolan; Wang, Dongsheng; Wang, Xu; Chen, Zhuo Georgia; Muller, Susan; Chen, Amy; Fei, Baowei

    2017-03-01

    Hyperspectral imaging (HSI) is an emerging imaging modality that can provide a noninvasive tool for cancer detection and image-guided surgery. HSI acquires high-resolution images at hundreds of spectral bands, providing big data to differentiating different types of tissue. We proposed a deep learning based method for the detection of head and neck cancer with hyperspectral images. Since the deep learning algorithm can learn the feature hierarchically, the learned features are more discriminative and concise than the handcrafted features. In this study, we adopt convolutional neural networks (CNN) to learn the deep feature of pixels for classifying each pixel into tumor or normal tissue. We evaluated our proposed classification method on the dataset containing hyperspectral images from 12 tumor-bearing mice. Experimental results show that our method achieved an average accuracy of 91.36%. The preliminary study demonstrated that our deep learning method can be applied to hyperspectral images for detecting head and neck tumors in animal models.

  12. Effect of Internet-Based Cognitive Apprenticeship Model (i-CAM on Statistics Learning among Postgraduate Students.

    Directory of Open Access Journals (Sweden)

    Farzaneh Saadati

    Full Text Available Because students' ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is 'value added' because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students' problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students.

  13. Effect of Internet-Based Cognitive Apprenticeship Model (i-CAM) on Statistics Learning among Postgraduate Students.

    Science.gov (United States)

    Saadati, Farzaneh; Ahmad Tarmizi, Rohani; Mohd Ayub, Ahmad Fauzi; Abu Bakar, Kamariah

    2015-01-01

    Because students' ability to use statistics, which is mathematical in nature, is one of the concerns of educators, embedding within an e-learning system the pedagogical characteristics of learning is 'value added' because it facilitates the conventional method of learning mathematics. Many researchers emphasize the effectiveness of cognitive apprenticeship in learning and problem solving in the workplace. In a cognitive apprenticeship learning model, skills are learned within a community of practitioners through observation of modelling and then practice plus coaching. This study utilized an internet-based Cognitive Apprenticeship Model (i-CAM) in three phases and evaluated its effectiveness for improving statistics problem-solving performance among postgraduate students. The results showed that, when compared to the conventional mathematics learning model, the i-CAM could significantly promote students' problem-solving performance at the end of each phase. In addition, the combination of the differences in students' test scores were considered to be statistically significant after controlling for the pre-test scores. The findings conveyed in this paper confirmed the considerable value of i-CAM in the improvement of statistics learning for non-specialized postgraduate students.

  14. Cloud-Based Mobile Learning

    Directory of Open Access Journals (Sweden)

    Alexandru BUTOI

    2013-01-01

    Full Text Available As the cloud technologies are largely studied and mobile technologies are evolving, new di-rections for development of mobile learning tools deployed on cloud are proposed.. M-Learning is treated as part of the ubiquitous learning paradigm and is a pervasive extension of E-Learning technologies. Development of such learning tools requires specific development strategies for an effective abstracting of pedagogical principles at the software design and implementation level. Current paper explores an interdisciplinary approach for designing and development of cloud based M-Learning tools by mapping a specific development strategy used for educational programs to software prototyping strategy. In order for such instruments to be user effective from the learning outcome point of view, the evaluation process must be rigorous as we propose a metric model for expressing the trainee’s overall learning experience with evaluated levels of interactivity, content presentation and graphical user interface usability.

  15. From particle systems to learning processes. Comment on "Collective learning modeling based on the kinetic theory of active particles" by Diletta Burini, Silvana De Lillo, and Livio Gibelli

    Science.gov (United States)

    Lachowicz, Mirosław

    2016-03-01

    The very stimulating paper [6] discusses an approach to perception and learning in a large population of living agents. The approach is based on a generalization of kinetic theory methods in which the interactions between agents are described in terms of game theory. Such an approach was already discussed in Ref. [2-4] (see also references therein) in various contexts. The processes of perception and learning are based on the interactions between agents and therefore the general kinetic theory is a suitable tool for modeling them. However the main question that rises is how the perception and learning processes may be treated in the mathematical modeling. How may we precisely deliver suitable mathematical structures that are able to capture various aspects of perception and learning?

  16. Machine learning modeling of plant phenology based on coupling satellite and gridded meteorological dataset

    Science.gov (United States)

    Czernecki, Bartosz; Nowosad, Jakub; Jabłońska, Katarzyna

    2018-04-01

    Changes in the timing of plant phenological phases are important proxies in contemporary climate research. However, most of the commonly used traditional phenological observations do not give any coherent spatial information. While consistent spatial data can be obtained from airborne sensors and preprocessed gridded meteorological data, not many studies robustly benefit from these data sources. Therefore, the main aim of this study is to create and evaluate different statistical models for reconstructing, predicting, and improving quality of phenological phases monitoring with the use of satellite and meteorological products. A quality-controlled dataset of the 13 BBCH plant phenophases in Poland was collected for the period 2007-2014. For each phenophase, statistical models were built using the most commonly applied regression-based machine learning techniques, such as multiple linear regression, lasso, principal component regression, generalized boosted models, and random forest. The quality of the models was estimated using a k-fold cross-validation. The obtained results showed varying potential for coupling meteorological derived indices with remote sensing products in terms of phenological modeling; however, application of both data sources improves models' accuracy from 0.6 to 4.6 day in terms of obtained RMSE. It is shown that a robust prediction of early phenological phases is mostly related to meteorological indices, whereas for autumn phenophases, there is a stronger information signal provided by satellite-derived vegetation metrics. Choosing a specific set of predictors and applying a robust preprocessing procedures is more important for final results than the selection of a particular statistical model. The average RMSE for the best models of all phenophases is 6.3, while the individual RMSE vary seasonally from 3.5 to 10 days. Models give reliable proxy for ground observations with RMSE below 5 days for early spring and late spring phenophases. For

  17. Patterns of Use of an Agent-Based Model and a System Dynamics Model: The Application of Patterns of Use and the Impacts on Learning Outcomes

    Science.gov (United States)

    Thompson, Kate; Reimann, Peter

    2010-01-01

    A classification system that was developed for the use of agent-based models was applied to strategies used by school-aged students to interrogate an agent-based model and a system dynamics model. These were compared, and relationships between learning outcomes and the strategies used were also analysed. It was found that the classification system…

  18. Work stress and work-based learning in secondary education : testing the Karasek model

    NARCIS (Netherlands)

    Kwakman, Kitty

    2001-01-01

    In this study the Job Demand-Control model was used to study the quality of working life of Dutch secondary teachers. The Job Demand-Control model of Karasek is a theoretical model in which stress and learning are both considered as dependent variables which are influenced by three different task

  19. Work stress and work based learning in secondary education: Testing the Karasek model

    NARCIS (Netherlands)

    Kwakman, Kitty

    1999-01-01

    In this study the Job Demand-Control model was used to study the quality of working life of Dutch secondary teachers. The Job Demand-Control model of Karasek is a theoretical model in which stress and learning are both considered as dependent variables which are influenced by three different task

  20. Improving Junior High Schools' Critical Thinking Skills Based on Test Three Different Models of Learning

    Science.gov (United States)

    Fuad, Nur Miftahul; Zubaidah, Siti; Mahanal, Susriyati; Suarsini, Endang

    2017-01-01

    The aims of this study were (1) to find out the differences in critical thinking skills among students who were given three different learning models: differentiated science inquiry combined with mind map, differentiated science inquiry model, and conventional model, (2) to find out the differences of critical thinking skills among male and female…

  1. The Development of Learning Model Based on Problem Solving to Construct High-Order Thinking Skill on the Learning Mathematics of 11th Grade in SMA/MA

    Science.gov (United States)

    Syahputra, Edi; Surya, Edy

    2017-01-01

    This paper is a summary study of team Postgraduate on 11th grade. The objective of this study is to develop a learning model based on problem solving which can construct high-order thinking on the learning mathematics in SMA/MA. The subject of dissemination consists of Students of 11th grade in SMA/MA in 3 kabupaten/kota in North Sumatera, namely:…

  2. An Analysis on a Negotiation Model Based on Multiagent Systems with Symbiotic Learning and Evolution

    Science.gov (United States)

    Hossain, Md. Tofazzal

    This study explores an evolutionary analysis on a negotiation model based on Masbiole (Multiagent Systems with Symbiotic Learning and Evolution) which has been proposed as a new methodology of Multiagent Systems (MAS) based on symbiosis in the ecosystem. In Masbiole, agents evolve in consideration of not only their own benefits and losses, but also the benefits and losses of opponent agents. To aid effective application of Masbiole, we develop a competitive negotiation model where rigorous and advanced intelligent decision-making mechanisms are required for agents to achieve solutions. A Negotiation Protocol is devised aiming at developing a set of rules for agents' behavior during evolution. Simulations use a newly developed evolutionary computing technique, called Genetic Network Programming (GNP) which has the directed graph-type gene structure that can develop and design the required intelligent mechanisms for agents. In a typical scenario, competitive negotiation solutions are reached by concessions that are usually predetermined in the conventional MAS. In this model, however, not only concession is determined automatically by symbiotic evolution (making the system intelligent, automated, and efficient) but the solution also achieves Pareto optimal automatically.

  3. The oral case presentation: toward a performance-based rhetorical model for teaching and learning

    Directory of Open Access Journals (Sweden)

    Mei Yuit Chan

    2015-07-01

    Full Text Available The oral case presentation is an important communicative activity in the teaching and assessment of students. Despite its importance, not much attention has been paid to providing support for teachers to teach this difficult task to medical students who are novices to this form of communication. As a formalized piece of talk that takes a regularized form and used for a specific communicative goal, the case presentation is regarded as a rhetorical activity and awareness of its rhetorical and linguistic characteristics should be given due consideration in teaching. This paper reviews practitioners’ and the limited research literature that relates to expectations of medical educators about what makes a good case presentation, and explains the rhetorical aspect of the activity. It is found there is currently a lack of a comprehensive model of the case presentation that projects the rhetorical and linguistic skills needed to produce and deliver a good presentation. Attempts to describe the structure of the case presentation have used predominantly opinion-based methodologies. In this paper, I argue for a performance-based model that would not only allow a description of the rhetorical structure of the oral case presentation, but also enable a systematic examination of the tacit genre knowledge that differentiates the expert from the novice. Such a model will be a useful resource for medical educators to provide more structured feedback and teaching support to medical students in learning this important genre.

  4. Learning-based computing techniques in geoid modeling for precise height transformation

    Science.gov (United States)

    Erol, B.; Erol, S.

    2013-03-01

    Precise determination of local geoid is of particular importance for establishing height control in geodetic GNSS applications, since the classical leveling technique is too laborious. A geoid model can be accurately obtained employing properly distributed benchmarks having GNSS and leveling observations using an appropriate computing algorithm. Besides the classical multivariable polynomial regression equations (MPRE), this study attempts an evaluation of learning based computing algorithms: artificial neural networks (ANNs), adaptive network-based fuzzy inference system (ANFIS) and especially the wavelet neural networks (WNNs) approach in geoid surface approximation. These algorithms were developed parallel to advances in computer technologies and recently have been used for solving complex nonlinear problems of many applications. However, they are rather new in dealing with precise modeling problem of the Earth gravity field. In the scope of the study, these methods were applied to Istanbul GPS Triangulation Network data. The performances of the methods were assessed considering the validation results of the geoid models at the observation points. In conclusion the ANFIS and WNN revealed higher prediction accuracies compared to ANN and MPRE methods. Beside the prediction capabilities, these methods were also compared and discussed from the practical point of view in conclusions.

  5. The oral case presentation: toward a performance-based rhetorical model for teaching and learning

    Science.gov (United States)

    Chan, Mei Yuit

    2015-01-01

    The oral case presentation is an important communicative activity in the teaching and assessment of students. Despite its importance, not much attention has been paid to providing support for teachers to teach this difficult task to medical students who are novices to this form of communication. As a formalized piece of talk that takes a regularized form and used for a specific communicative goal, the case presentation is regarded as a rhetorical activity and awareness of its rhetorical and linguistic characteristics should be given due consideration in teaching. This paper reviews practitioners’ and the limited research literature that relates to expectations of medical educators about what makes a good case presentation, and explains the rhetorical aspect of the activity. It is found there is currently a lack of a comprehensive model of the case presentation that projects the rhetorical and linguistic skills needed to produce and deliver a good presentation. Attempts to describe the structure of the case presentation have used predominantly opinion-based methodologies. In this paper, I argue for a performance-based model that would not only allow a description of the rhetorical structure of the oral case presentation, but also enable a systematic examination of the tacit genre knowledge that differentiates the expert from the novice. Such a model will be a useful resource for medical educators to provide more structured feedback and teaching support to medical students in learning this important genre. PMID:26194482

  6. Working towards a scalable model of problem-based learning instruction in undergraduate engineering education

    Science.gov (United States)

    Mantri, Archana

    2014-05-01

    The intent of the study presented in this paper is to show that the model of problem-based learning (PBL) can be made scalable by designing curriculum around a set of open-ended problems (OEPs). The detailed statistical analysis of the data collected to measure the effects of traditional and PBL instructions for three courses in Electronics and Communication Engineering, namely Analog Electronics, Digital Electronics and Pulse, Digital & Switching Circuits is presented here. It measures the effects of pedagogy, gender and cognitive styles on the knowledge, skill and attitude of the students. The study was conducted two times with content designed around same set of OEPs but with two different trained facilitators for all the three courses. The repeatability of results for effects of the independent parameters on dependent parameters is studied and inferences are drawn.

  7. Design a Learning-Oriented Fall Event Reporting System Based on Kirkpatrick Model.

    Science.gov (United States)

    Zhou, Sicheng; Kang, Hong; Gong, Yang

    2017-01-01

    Patient fall has been a severe problem in healthcare facilities around the world due to its prevalence and cost. Routine fall prevention training programs are not as effective as expected. Using event reporting systems is the trend for reducing patient safety events such as falls, although some limitations of the systems exist at current stage. We summarized these limitations through literature review, and developed an improved web-based fall event reporting system. The Kirkpatrick model, widely used in the business area for training program evaluation, has been integrated during the design of our system. Different from traditional event reporting systems that only collect and store the reports, our system automatically annotates and analyzes the reported events, and provides users with timely knowledge support specific to the reported event. The paper illustrates the design of our system and how its features are intended to reduce patient falls by learning from previous errors.

  8. Equine Assisted Psychotherapy: The Equine Assisted Growth and Learning Association's Model Overview of Equine-Based Modalities

    Science.gov (United States)

    Notgrass, Clayton G.; Pettinelli, J. Douglas

    2015-01-01

    This article describes the Equine Assisted Growth and Learning Association's (EAGALA) experiential model called "Equine Assisted Psychotherapy" (EAP). EAGALA's model is based on the Association for Experiential Education's (AEE) tenets and is focused on the learner's experience with horses. Drawing on the historical use of equines in the…

  9. Emotions as a Vehicle for Rationality: Rational Decision Making Models Based on Emotion-Related Valuing and Hebbian Learning

    NARCIS (Netherlands)

    Treur, J.; Umair, M.

    2015-01-01

    In this paper an adaptive decision model based on predictive loops through feeling states is analysed from the perspective of rationality. Hebbian learning is considered for different types of connections in the decision model. To assess the extent of rationality, a measure is introduced reflecting

  10. THE EFFECTIVENESS OF WEB-BASED INTERACTIVE BLENDED LEARNING MODEL IN ELECTRICAL ENGINEERING COURSES

    Directory of Open Access Journals (Sweden)

    Hansi Effendi

    2015-12-01

    Full Text Available The study was to test the effectiveness of the Web-Based Interactive Blended Learning Model (BLIBW for subjects in the Department of Electrical Engineering, Padang State University. The design that the researcher employed was a quasi-experimental design with one group pretest-posttest, which was conducted on a group of students consisting of 30 people and the test was conducted for two times. The effectiveness of BLIBW Model was tested by comparing the average pretest scores and the average posttest scores both in the first trial and the second trial. The average prestest and posttest scores in the first trial were 14.13 and 33.80. The increase in the average score was significant at alpha 0.05. Then, the average pretest and posttest scores in the second trial were 18.67 and 47.03. The result was also significant at alpha 0.05. The effectiveness of BLIBW Model in the second trial was higher than in the first test. Those result were not entirely satisfactory and it might be caused several weaknesses in both tests such as: the number of sessions were limited, there was only one subject, and the number of students who were subjected too limited. However, the researcher would like to conclude that the BLIBW Model might be implemented as a replacement alternative for the face-to-face instruction.

  11. Nursing students learning the pharmacology of diabetes mellitus with complexity-based computerized models: A quasi-experimental study.

    Science.gov (United States)

    Dubovi, Ilana; Dagan, Efrat; Sader Mazbar, Ola; Nassar, Laila; Levy, Sharona T

    2018-02-01

    Pharmacology is a crucial component of medications administration in nursing, yet nursing students generally find it difficult and self-rate their pharmacology skills as low. To evaluate nursing students learning pharmacology with the Pharmacology Inter-Leaved Learning-Cells environment, a novel approach to modeling biochemical interactions using a multiscale, computer-based model with a complexity perspective based on a small set of entities and simple rules. This environment represents molecules, organelles and cells to enhance the understanding of cellular processes, and combines these cells at a higher scale to obtain whole-body interactions. Sophomore nursing students who learned the pharmacology of diabetes mellitus with the Pharmacology Inter-Leaved Learning-Cells environment (experimental group; n=94) or via a lecture-based curriculum (comparison group; n=54). A quasi-experimental pre- and post-test design was conducted. The Pharmacology-Diabetes-Mellitus questionnaire and the course's final exam were used to evaluate students' knowledge of the pharmacology of diabetes mellitus. Conceptual learning was significantly higher for the experimental than for the comparison group for the course final exam scores (unpaired t=-3.8, pLearning with complexity-based computerized models is highly effective and enhances the understanding of moving between micro and macro levels of the biochemical phenomena, this is then related to better understanding of medication actions. Moreover, the Pharmacology Inter-Leaved Learning-Cells approach provides a more general reasoning scheme for biochemical processes, which enhances pharmacology learning beyond the specific topic learned. The present study implies that deeper understanding of pharmacology will support nursing students' clinical decisions and empower their proficiency in medications administration. Copyright © 2017 Elsevier Ltd. All rights reserved.

  12. Biologically based neural circuit modelling for the study of fear learning and extinction

    Science.gov (United States)

    Nair, Satish S.; Paré, Denis; Vicentic, Aleksandra

    2016-11-01

    The neuronal systems that promote protective defensive behaviours have been studied extensively using Pavlovian conditioning. In this paradigm, an initially neutral-conditioned stimulus is paired with an aversive unconditioned stimulus leading the subjects to display behavioural signs of fear. Decades of research into the neural bases of this simple behavioural paradigm uncovered that the amygdala, a complex structure comprised of several interconnected nuclei, is an essential part of the neural circuits required for the acquisition, consolidation and expression of fear memory. However, emerging evidence from the confluence of electrophysiological, tract tracing, imaging, molecular, optogenetic and chemogenetic methodologies, reveals that fear learning is mediated by multiple connections between several amygdala nuclei and their distributed targets, dynamical changes in plasticity in local circuit elements as well as neuromodulatory mechanisms that promote synaptic plasticity. To uncover these complex relations and analyse multi-modal data sets acquired from these studies, we argue that biologically realistic computational modelling, in conjunction with experiments, offers an opportunity to advance our understanding of the neural circuit mechanisms of fear learning and to address how their dysfunction may lead to maladaptive fear responses in mental disorders.

  13. Improving Simulations of Extreme Flows by Coupling a Physically-based Hydrologic Model with a Machine Learning Model

    Science.gov (United States)

    Mohammed, K.; Islam, A. S.; Khan, M. J. U.; Das, M. K.

    2017-12-01

    With the large number of hydrologic models presently available along with the global weather and geographic datasets, streamflows of almost any river in the world can be easily modeled. And if a reasonable amount of observed data from that river is available, then simulations of high accuracy can sometimes be performed after calibrating the model parameters against those observed data through inverse modeling. Although such calibrated models can succeed in simulating the general trend or mean of the observed flows very well, more often than not they fail to adequately simulate the extreme flows. This causes difficulty in tasks such as generating reliable projections of future changes in extreme flows due to climate change, which is obviously an important task due to floods and droughts being closely connected to people's lives and livelihoods. We propose an approach where the outputs of a physically-based hydrologic model are used as an input to a machine learning model to try and better simulate the extreme flows. To demonstrate this offline-coupling approach, the Soil and Water Assessment Tool (SWAT) was selected as the physically-based hydrologic model, the Artificial Neural Network (ANN) as the machine learning model and the Ganges-Brahmaputra-Meghna (GBM) river system as the study area. The GBM river system, located in South Asia, is the third largest in the world in terms of freshwater generated and forms the largest delta in the world. The flows of the GBM rivers were simulated separately in order to test the performance of this proposed approach in accurately simulating the extreme flows generated by different basins that vary in size, climate, hydrology and anthropogenic intervention on stream networks. Results show that by post-processing the simulated flows of the SWAT models with ANN models, simulations of extreme flows can be significantly improved. The mean absolute errors in simulating annual maximum/minimum daily flows were minimized from 4967

  14. Strengths-based Learning

    DEFF Research Database (Denmark)

    Ledertoug, Mette Marie

    -being. The Ph.D.-project in Strength-based learning took place in a Danish school with 750 pupils age 6-16 and a similar school was functioning as a control group. The presentation will focus on both the aware-explore-apply processes and the practical implications for the schools involved, and on measurable......Strength-based learning - Children͛s Character Strengths as Means to their Learning Potential͛ is a Ph.D.-project aiming to create a strength-based mindset in school settings and at the same time introducing strength-based interventions as specific tools to improve both learning and well...

  15. Secondary Science Teachers Making Sense of Model-Based Classroom Instruction: Understanding the Learning and Learning Pathways Teachers Describe as Supporting Changes in Teaching Practice

    Science.gov (United States)

    Hvidsten, Connie J.

    Connie J. Hvidsten September 2016 Education Secondary Science Teachers Making Sense of Model-Based Classroom Instruction: Understanding the Learning and Learning Pathways Teachers Describe as Supporting Changes in Teaching Practice This dissertation consists of three papers analyzing writings and interviews of experienced secondary science teachers during and after a two-year professional development (PD) program focused on model-based reasoning (MBR). MBR is an approach to science instruction that provides opportunities for students to use conceptual models to make sense of natural phenomena in ways that are similar to the use of models within the scientific community. The aim of this research is to better understand the learning and learning pathways teachers identified as valuable in supporting changes in their teaching practice. To accomplish this aim, the papers analyze the ways teachers 1) ascribe their learning to various aspects of the program, 2) describe what they learned, and 3) reflect on the impact the PD had on their teaching practice. Twenty-one secondary science teachers completed the Innovations in Science Instruction through Modeling (ISIM) program from 2007 through 2009. Commonalities in the written reflections and interview responses led to a set of generalizable findings related to the impacts and outcomes of the PD. The first of the three papers describes elements of the ISIM program that teachers associated with their own learning. One of the most frequently mentioned PD feature was being in the position of an adult learner. Embedding learning in instructional practice by collaboratively developing and revising lessons, and observing the lessons in one-another's classrooms provided a sense of professional community, accountability, and support teachers reported were necessary to overcome the challenges of implementing new pedagogical practices. Additionally, teachers described that opportunities to reflect on their learning and connect their

  16. Using a motivation-based instructional model for teacher development and students' learning of science

    Science.gov (United States)

    Bae, Min-Jung

    2009-10-01

    Science teachers often have difficulty helping students participate in scientific practices and understand scientific ideas. In addition, they do not frequently help students value their science learning. As one way to address these problems, I designed and examined the effects of professional development using a motivation-based instructional model with teachers and students. This motivation-based inquiry and application instructional model (MIAIM) consists of four steps of activities and identifies instructional and motivational functions that teachers can use to engage their students in scientific inquiry and application and to help them value their science learning. In order to conduct this study, I worked with three teachers (4 th, 8th, and 8th) in both suburban and urban environments. This study consisted of three parts-an initial observation of teachers' classrooms, professional development with MIAIM, and an observation of teachers' classrooms after the professional development. Data analysis of class observations, interviews, and class artifacts shows that there was a moderate change in teachers' teaching approach after the intervention. The three teachers designed and enacted some inquiry and application lessons that fit the intent of MIAIM. They also used some instructional and motivational practices more frequently after the intervention than they did before the intervention. In particular, they more frequently established central questions for investigations, helped students find patterns in data by themselves, provided opportunities for application, related science to students' everyday lives, and created students' interests in scientific investigation by using interesting stories. However, there was no substantial change in teachers' use of some practices such as providing explanations, supporting students' autonomy, and using knowledge about students in designing and enacting science lessons. In addition, data analysis of students' surveys, class

  17. Disruption of model-based behavior and learning by cocaine self-administration in rats.

    Science.gov (United States)

    Wied, Heather M; Jones, Joshua L; Cooch, Nisha K; Berg, Benjamin A; Schoenbaum, Geoffrey

    2013-10-01

    Addiction is characterized by maladaptive decision-making, in which individuals seem unable to use adverse outcomes to modify their behavior. Adverse outcomes are often infrequent, delayed, and even rare events, especially when compared to the reliable rewarding drug-associated outcomes. As a result, recognizing and using information about their occurrence put a premium on the operation of so-called model-based systems of behavioral control, which allow one to mentally simulate outcomes of different courses of action based on knowledge of the underlying associative structure of the environment. This suggests that addiction may reflect, in part, drug-induced dysfunction in these systems. Here, we tested this hypothesis. This study aimed to test whether cocaine causes deficits in model-based behavior and learning independent of requirements for response inhibition or perception of costs or punishment. We trained rats to self-administer sucrose or cocaine for 2 weeks. Four weeks later, the rats began training on a sensory preconditioning and inferred value blocking task. Like devaluation, normal performance on this task requires representations of the underlying task structure; however, unlike devaluation, it does not require either response inhibition or adapting behavior to reflect aversive outcomes. Rats trained to self-administer cocaine failed to show conditioned responding or blocking to the preconditioned cue. These deficits were not observed in sucrose-trained rats nor did they reflect any changes in responding to cues paired directly with reward. These results imply that cocaine disrupts the operation of neural circuits that mediate model-based behavioral control.

  18. The effectiveness of collaborative problem based physics learning (CPBPL) model to improve student’s self-confidence on physics learning

    Science.gov (United States)

    Prahani, B. K.; Suprapto, N.; Suliyanah; Lestari, N. A.; Jauhariyah, M. N. R.; Admoko, S.; Wahyuni, S.

    2018-03-01

    In the previous research, Collaborative Problem Based Physic Learning (CPBPL) model has been developed to improve student’s science process skills, collaborative problem solving, and self-confidence on physics learning. This research is aimed to analyze the effectiveness of CPBPL model towards the improvement of student’s self-confidence on physics learning. This research implemented quasi experimental design on 140 senior high school students who were divided into 4 groups. Data collection was conducted through questionnaire, observation, and interview. Self-confidence measurement was conducted through Self-Confidence Evaluation Sheet (SCES). The data was analyzed using Wilcoxon test, n-gain, and Kruskal Wallis test. Result shows that: (1) There is a significant score improvement on student’s self-confidence on physics learning (α=5%), (2) n-gain value student’s self-confidence on physics learning is high, and (3) n-gain average student’s self-confidence on physics learning was consistent throughout all groups. It can be concluded that CPBPL model is effective to improve student’s self-confidence on physics learning.

  19. Conceptualization of an R&D Based Learning-to-Innovate Model for Science Education

    Science.gov (United States)

    Lai, Oiki Sylvia

    The purpose of this research was to conceptualize an R & D based learning-to-innovate (LTI) model. The problem to be addressed was the lack of a theoretical L TI model, which would inform science pedagogy. The absorptive capacity (ACAP) lens was adopted to untangle the R & D LTI phenomenon into four learning processes: problem-solving via knowledge acquisition, incremental improvement via knowledge participation, scientific discovery via knowledge creation, and product design via knowledge productivity. The four knowledge factors were the latent factors and each factor had seven manifest elements as measured variables. The key objectives of the non experimental quantitative survey were to measure the relative importance of the identified elements and to explore the underlining structure of the variables. A questionnaire had been prepared, and was administered to more than 155 R & D professionals from four sectors - business, academic, government, and nonprofit. The results showed that every identified element was important to the R & D professionals, in terms of improving the related type of innovation. The most important elements were highlighted to serve as building blocks for elaboration. In search for patterns of the data matrix, exploratory factor analysis (EF A) was performed. Principal component analysis was the first phase of EF A to extract factors; while maximum likelihood estimation (MLE) was used to estimate the model. EF A yielded the finding of two aspects in each kind of knowledge. Logical names were assigned to represent the nature of the subsets: problem and knowledge under knowledge acquisition, planning and participation under knowledge participation, exploration and discovery under knowledge creation, and construction and invention under knowledge productivity. These two constructs, within each kind of knowledge, added structure to the vague R & D based LTI model. The research questions and hypotheses testing were addressed using correlation

  20. From Creatures of Habit to Goal-Directed Learners: Tracking the Developmental Emergence of Model-Based Reinforcement Learning.

    Science.gov (United States)

    Decker, Johannes H; Otto, A Ross; Daw, Nathaniel D; Hartley, Catherine A

    2016-06-01

    Theoretical models distinguish two decision-making strategies that have been formalized in reinforcement-learning theory. A model-based strategy leverages a cognitive model of potential actions and their consequences to make goal-directed choices, whereas a model-free strategy evaluates actions based solely on their reward history. Research in adults has begun to elucidate the psychological mechanisms and neural substrates underlying these learning processes and factors that influence their relative recruitment. However, the developmental trajectory of these evaluative strategies has not been well characterized. In this study, children, adolescents, and adults performed a sequential reinforcement-learning task that enabled estimation of model-based and model-free contributions to choice. Whereas a model-free strategy was apparent in choice behavior across all age groups, a model-based strategy was absent in children, became evident in adolescents, and strengthened in adults. These results suggest that recruitment of model-based valuation systems represents a critical cognitive component underlying the gradual maturation of goal-directed behavior. © The Author(s) 2016.

  1. Inexpensive Videodisc for Proficiency: A Teaching Model Based on Bruner's Learning Hierarchy.

    Science.gov (United States)

    Sutherland, Richard; Knight, Richard

    1987-01-01

    Describes a German language class in which a videodisk player is used to enhance oral proficiency. The basis for this model of instruction and the structuralist theory of learning developed by Jerome Bruner are discussed. The teaching steps of the model as applied to foreign language instruction are presented. (Author/LMO)

  2. IS Success Model in E-Learning Context Based on Students' Perceptions

    Science.gov (United States)

    Freeze, Ronald D.; Alshare, Khaled A.; Lane, Peggy L.; Wen, H. Joseph

    2010-01-01

    This study utilized the Information Systems Success (ISS) model in examining e-learning systems success. The study was built on the premise that system quality (SQ) and information quality (IQ) influence system use and user satisfaction, which in turn impact system success. A structural equation model (SEM), using LISREL, was used to test the…

  3. PENGEMBANGAN PERANGKAT PEMBELAJARAN MODEL PROBLEM BASED LEARNING UNTUK MENINGKATKAN KEMAMPUAN BERPIKIR KREATIF

    Directory of Open Access Journals (Sweden)

    Ali Muntaha

    2013-03-01

    Full Text Available Penelitian ini bertujuan untuk : (1 Mengetahui proses pengembangan perangkat pembelajaran dengan model PBL berbantuan CD Pembelajaran untuk meningkatkan kemampuan berpikir kreatif siswa, (2 Menghasilkan perangkat pembelajaran dengan model PBL berbantuan CD Pembelajaran yang valid, (3 Menghasilkan perangkat pembelajaran dengan model PBL berbantuan CD Pembelajaran yang efektif. Penelitian ini merupakan penelitian pengembangan. Pengembangan yang dilakukan dalam penelitian ini meliputi Silabus, Rencana Pelaksanaan Pembelajaran (RPP,  Buku Siswa, Lembar Kegiatan Siswa (LKS,    dan Tes Kemampuan Berpikir Kreatif Siswa. Data penelitian diperoleh melalui  observasi dan tes kemampuan kognitif. Analisis statistik menggunakan uji ketuntasan (KKM hasil belajar dengan uji One sample t test, uji beda menggunakan independen sample t test, uji normalitas dan uji peningkatan kemampuan menggunakan N-gain. Hasil penelitian menunjukkan: (1 Proses pengembangan perangkat pembelajaran dilakukan melalui empat tahapan yaitu define (pendefinisian /penetapan, design (perancangan, develop (pengembangan, dan disseminate (penyebaran, (2 Hasil pengembangan perangkat pembelajaran dalam penelitian ini valid, (3 Hasil pengembangan perangkat pembelajaran dalam penelitian ini efektif untuk meningkatkan kemampuan berpikir kreatif siswa. This study aims to: (1 Knowing the software development process model of PBL assisted learning with Learning CD to enhance students’ creative thinking skills, (2 Generate the model of learning with Learning CD-assisted PBL valid, (3 Generate the model of learning with PBL CD-assisted learning effective. This research is a research development. Development conducted in this study include syllabus, lesson plan (RPP, Student Book, Student Activity Sheet (LKS, and Student Creative Thinking Ability Test. Data were obtained through observation and tests of cognitive ability. Statistical analysis using the mastery test (KKM learning outcomes to test

  4. Comparing Science Virtual and Paper-Based Test to Measure Students’ Critical Thinking based on VAK Learning Style Model

    Science.gov (United States)

    Rosyidah, T. H.; Firman, H.; Rusyati, L.

    2017-02-01

    This research was comparing virtual and paper-based test to measure students’ critical thinking based on VAK (Visual-Auditory-Kynesthetic) learning style model. Quasi experiment method with one group post-test only design is applied in this research in order to analyze the data. There was 40 eight grade students at one of public junior high school in Bandung becoming the sample in this research. The quantitative data was obtained through 26 questions about living thing and environment sustainability which is constructed based on the eight elements of critical thinking and be provided in the form of virtual and paper-based test. Based on analysis of the result, it is shown that within visual, auditory, and kinesthetic were not significantly difference in virtual and paper-based test. Besides, all result was supported by quistionnaire about students’ respond on virtual test which shows 3.47 in the scale of 4. Means that student showed positive respond in all aspet measured, which are interest, impression, and expectation.

  5. PENERAPAN MODEL CHALLENGE BASED LEARNING DENGAN METODE EKSPERIMEN DAN PROYEK DITINJAU DARI KEINGINTAHUAN DAN SIKAP ILMIAH TERHADAP PRESTASI BELAJAR SISWA

    Directory of Open Access Journals (Sweden)

    Sodikin .

    2014-09-01

    Full Text Available The purposes of the research were to know the effect of challenge based learning (CBL model by experiments method and project, learning of inquiring and scientific attitude and their interaction towards students’  achievement in cognitive, affective and psychomotoric. Data was collected using test technique for cognitive, non test technique for affective, psikomotoric, learning motivation, learning activity, and obsevation sheet is used for affective and psychomotoric. The data were analyzed by using anova test through software PASW 18.  Based on the analysis of the data concluded: 1 there was effect of CBL model by experiments method and project toward cognitive, affective and psychomotoric towards students’ achievement; 2 there was an effect of learning inquiring towards cognitive and affective students’ achievement, but there was no effect towards psychomotoric students’ achievement; 3 there was an effect of scientific attitude toward cognitive students’ achievement, but there was no effect toward affective and psychomotoric students’ achievement; 4 there was no an interaction between CBL model by experiments method and project method with learning inquiring toward cognitive, affective and psikomotoric student’ achievement; 5 there was no an interaction between CBL model by experiments method and project method with scientific attitude toward cognitive, affective and psychomotoric students’ achievement; 6 there was no an interaction between learning inquiring with scientific attitude toward cognitive, affective and psychomotoric students’ achievement;  7 there was no an interaction between CBL  model by experiments method and project with learning inquiring and scientific attitude toward cognitive, affective and psychomotoric students’ achievement.

  6. Hybrid attribute-based recommender system for learning material using genetic algorithm and a multidimensional information model

    Directory of Open Access Journals (Sweden)

    Mojtaba Salehi

    2013-03-01

    Full Text Available In recent years, the explosion of learning materials in the web-based educational systems has caused difficulty of locating appropriate learning materials to learners. A personalized recommendation is an enabling mechanism to overcome information overload occurred in the new learning environments and deliver suitable materials to learners. Since users express their opinions based on some specific attributes of items, this paper proposes a hybrid recommender system for learning materials based on their attributes to improve the accuracy and quality of recommendation. The presented system has two main modules: explicit attribute-based recommender and implicit attribute-based recommender. In the first module, weights of implicit or latent attributes of materials for learner are considered as chromosomes in genetic algorithm then this algorithm optimizes the weights according to historical rating. Then, recommendation is generated by Nearest Neighborhood Algorithm (NNA using the optimized weight vectors implicit attributes that represent the opinions of learners. In the second, preference matrix (PM is introduced that can model the interests of learner based on explicit attributes of learning materials in a multidimensional information model. Then, a new similarity measure between PMs is introduced and recommendations are generated by NNA. The experimental results show that our proposed method outperforms current algorithms on accuracy measures and can alleviate some problems such as cold-start and sparsity.

  7. Competency-based residency training and the web log: modeling practice-based learning and enhancing medical knowledge

    Directory of Open Access Journals (Sweden)

    Matthew F. Hollon

    2015-12-01

    Full Text Available Background: By using web-based tools in medical education, there are opportunities to innovatively teach important principles from the general competencies of graduate medical education. Objectives: Postulating that faculty transparency in learning from uncertainties in clinical work could help residents to incorporate the principles of practice-based learning and improvement (PBLI in their professional development, faculty in this community-based residency program modeled the steps of PBLI on a weekly basis through the use of a web log. Method: The program confidentially surveyed residents before and after this project about actions consistent with PBLI and knowledge acquired through reading the web log. Results: The frequency that residents encountered clinical situations where they felt uncertain declined over the course of the 24 weeks of the project from a mean frequency of uncertainty of 36% to 28% (Wilcoxon signed rank test, p=0.008; however, the frequency with which residents sought answers when faced with uncertainty did not change (Wilcoxon signed rank test, p=0.39, remaining high at approximately 80%. Residents answered a mean of 52% of knowledge questions correct when tested prior to faculty posts to the blog, rising to a mean of 65% of questions correct when tested at the end of the project (paired t-test, p=0.001. Conclusions: Faculty role modeling of PBLI behaviors and posting clinical questions and answers to a web log led to modest improvements in medical knowledge but did not alter behavior that was already taking place frequently among residents.

  8. [Purity Detection Model Update of Maize Seeds Based on Active Learning].

    Science.gov (United States)

    Tang, Jin-ya; Huang, Min; Zhu, Qi-bing

    2015-08-01

    Seed purity reflects the degree of seed varieties in typical consistent characteristics, so it is great important to improve the reliability and accuracy of seed purity detection to guarantee the quality of seeds. Hyperspectral imaging can reflect the internal and external characteristics of seeds at the same time, which has been widely used in nondestructive detection of agricultural products. The essence of nondestructive detection of agricultural products using hyperspectral imaging technique is to establish the mathematical model between the spectral information and the quality of agricultural products. Since the spectral information is easily affected by the sample growth environment, the stability and generalization of model would weaken when the test samples harvested from different origin and year. Active learning algorithm was investigated to add representative samples to expand the sample space for the original model, so as to implement the rapid update of the model's ability. Random selection (RS) and Kennard-Stone algorithm (KS) were performed to compare the model update effect with active learning algorithm. The experimental results indicated that in the division of different proportion of sample set (1:1, 3:1, 4:1), the updated purity detection model for maize seeds from 2010 year which was added 40 samples selected by active learning algorithm from 2011 year increased the prediction accuracy for 2011 new samples from 47%, 33.75%, 49% to 98.89%, 98.33%, 98.33%. For the updated purity detection model of 2011 year, its prediction accuracy for 2010 new samples increased by 50.83%, 54.58%, 53.75% to 94.57%, 94.02%, 94.57% after adding 56 new samples from 2010 year. Meanwhile the effect of model updated by active learning algorithm was better than that of RS and KS. Therefore, the update for purity detection model of maize seeds is feasible by active learning algorithm.

  9. A TLBO based gradient descent learning-functional link higher order ANN: An efficient model for learning from non-linear data

    Directory of Open Access Journals (Sweden)

    Bighnaraj Naik

    2018-01-01

    Full Text Available All the higher order ANNs (HONNs including functional link ANN (FLANN are sensitive to random initialization of weight and rely on the learning algorithms adopted. Although a selection of efficient learning algorithms for HONNs helps to improve the performance, on the other hand, initialization of weights with optimized weights rather than random weights also play important roles on its efficiency. In this paper, the problem solving approach of the teaching learning based optimization (TLBO along with learning ability of the gradient descent learning (GDL is used to obtain the optimal set of weight of FLANN learning model. TLBO does not require any specific parameters rather it requires only some of the common independent parameters like number of populations, number of iterations and stopping criteria, thereby eliminating the intricacy in selection of algorithmic parameters for adjusting the set of weights of FLANN model. The proposed TLBO-FLANN is implemented in MATLAB and compared with GA-FLANN, PSO-FLANN and HS-FLANN. The TLBO-FLANN is tested on various 5-fold cross validated benchmark data sets from UCI machine learning repository and analyzed under the null-hypothesis by using Friedman test, Holm’s procedure and post hoc ANOVA statistical analysis (Tukey test & Dunnett test.

  10. The development of macros program-based cognitive evaluation model via e-learning course mathematics in senior high school based on curriculum 2013

    Directory of Open Access Journals (Sweden)

    Djoko Purnomo

    2017-02-01

    Full Text Available The specific purpose of this research is: The implementation of the application of the learning tool with a form cognitive learning evaluation model based macros program via E-learning at High School grade X at july-december based on 2013 curriculum. The method used in this research followed the procedures is research and development by Borg and Gall [2]. In second year, population analysis has conducted at several universities in Semarang. The results of the research and application development of macro program-based cognitive evaluation model is effective which can be seen from (1 the student learning result is over KKM, (2 The student independency affects learning result positively, (3 the student learning a result by using macros program-based cognitive evaluation model is better than students class control. Based on the results above, the development of macros program-based cognitive evaluation model that have been tested have met quality standards according to Akker (1999. Large-scale testing includes operational phase of field testing and final product revision, i.e trials in the wider class that includes students in mathematics education major in several universities, they are the Universitas PGRI Semarang, Universitas Islam Sultan Agung and the Universitas Islam NegeriWalisongo Semarang. The positive responses is given by students at the Universitas PGRI Semarang, Universitas Islam Sultan Agung and the Universitas Islam NegeriWalisongo Semarang.

  11. Teaching Economics: A Cooperative Learning Model.

    Science.gov (United States)

    Caropreso, Edward J.; Haggerty, Mark

    2000-01-01

    Describes an alternative approach to introductory economics based on a cooperative learning model, "Learning Together." Discussion of issues in economics education and cooperative learning in higher education leads to explanation of how to adapt the Learning Together Model to lesson planning in economics. A flow chart illustrates the process for a…

  12. Learning from erroneous models using SCYDynamics

    NARCIS (Netherlands)

    Mulder, Y.G.; Bollen, Lars; de Jong, Anthonius J.M.

    2014-01-01

    Dynamic phenomena are common in science education. Students can learn about such system dynamic processes through model based learning activities. This paper describes a study on the effects of a learning from erroneous models approach using the learning environment SCYDynamics. The study compared

  13. Perceptions of the Impact of Online Learning as a Distance-Based Learning Model on the Professional Practices of Working Nurses in Northern Ontario

    Science.gov (United States)

    Carter, Lorraine; Hanna, Mary; Warry, Wayne

    2016-01-01

    Nurses in Canada face diverse challenges to their ongoing educational pursuits. As a result, they have been early adopters of courses and programs based on distance education principles and, in particular, online learning models. In the study described in this paper, nurses studying at two northern universities, in programs involving online…

  14. A Project-Based Language Learning Model for Improving the Willingness to Communicate of EFL Students

    Directory of Open Access Journals (Sweden)

    Ibrahim Farouck

    2016-04-01

    Full Text Available Anxiety and inadequate motivation due to misapplication of some language teaching methodologies and learning materials have been shown to affect the Willingness to Communicate of students in EFL programs. This study used a Project-Based Language Learning to improve learning motivation and content relevance. Students were grouped into pairs to conduct fieldwork activities on their chosen topics and learned the English language that was suitable for describing their activities and outcomes. They interacted with content and peers through Web 2.0 environments. In the classroom, they engaged in communicative tasks in a jigsaw format and presented their projects where their peers used an online rubric and forum to give feedback. They also participated in a speech contest with peers outside their class or from another university in order to broaden their confidence. Findings from this study show that students were able to develop the language and evaluation skills for presentation. Additionally, they indicated a reduction in communication anxiety.

  15. Mapping of Students’ Learning Progression Based on Mental Model in Magnetic Induction Concepts

    Science.gov (United States)

    Hamid, R.; Pabunga, D. B.

    2017-09-01

    The progress of student learning in a learning process has not been fully optimally observed by the teacher. The concept being taught is judged only at the end of learning as a product of thinking, and does not assess the mental processes that occur in students’ thinking. Facilitating students’ thinking through new phenomena can reveal students’ variation in thinking as a mental model of a concept, so that students who are assimilative and or accommodative can be identified in achieving their equilibrium of thought as well as an indicator of progressiveness in the students’ thinking stages. This research data is obtained from the written documents and interviews of students who were learned about the concept of magnetic induction through Constructivist Teaching Sequences (CTS) models. The results of this study indicate that facilitating the students’ thinking processes on the concept of magnetic induction contributes to increasing the number of students thinking within the "progressive change" category, and it can be said that the progress of student learning is more progressive after their mental models were facilitated through a new phenomena by teacher.

  16. Design, Explanation, and Evaluation of Training Model Structures Based on Learning Organization--In the Cement Industry with a Nominal Production Capacity of Ten Thousand Tons

    Science.gov (United States)

    Rahimian, Hamid; Kazemi, Mojtaba; Abbspour, Abbas

    2017-01-01

    This research aims to determine the effectiveness of training based on learning organization in the staff of cement industry with production capacity over ten thousand tons. The purpose of this study is to propose a training model based on learning organization. For this purpose, the factors of organizational learning were introduced by…

  17. A Tsallis’ statistics based neural network model for novel word learning

    Science.gov (United States)

    Hadzibeganovic, Tarik; Cannas, Sergio A.

    2009-03-01

    We invoke the Tsallis entropy formalism, a nonextensive entropy measure, to include some degree of non-locality in a neural network that is used for simulation of novel word learning in adults. A generalization of the gradient descent dynamics, realized via nonextensive cost functions, is used as a learning rule in a simple perceptron. The model is first investigated for general properties, and then tested against the empirical data, gathered from simple memorization experiments involving two populations of linguistically different subjects. Numerical solutions of the model equations corresponded to the measured performance states of human learners. In particular, we found that the memorization tasks were executed with rather small but population-specific amounts of nonextensivity, quantified by the entropic index q. Our findings raise the possibility of using entropic nonextensivity as a means of characterizing the degree of complexity of learning in both natural and artificial systems.

  18. A Novel Machine Learning Strategy Based on Two-Dimensional Numerical Models in Financial Engineering

    Directory of Open Access Journals (Sweden)

    Qingzhen Xu

    2013-01-01

    Full Text Available Machine learning is the most commonly used technique to address larger and more complex tasks by analyzing the most relevant information already present in databases. In order to better predict the future trend of the index, this paper proposes a two-dimensional numerical model for machine learning to simulate major U.S. stock market index and uses a nonlinear implicit finite-difference method to find numerical solutions of the two-dimensional simulation model. The proposed machine learning method uses partial differential equations to predict the stock market and can be extensively used to accelerate large-scale data processing on the history database. The experimental results show that the proposed algorithm reduces the prediction error and improves forecasting precision.

  19. MAP as a model for practice-based learning and improvement in child psychiatry training.

    Science.gov (United States)

    Kataoka, Sheryl H; Podell, Jennifer L; Zima, Bonnie T; Best, Karin; Sidhu, Shawn; Jura, Martha Bates

    2014-01-01

    Not only is there a growing literature demonstrating the positive outcomes that result from implementing evidence based treatments (EBTs) but also studies that suggest a lack of delivery of these EBTs in "usual care" practices. One way to address this deficit is to improve the quality of psychotherapy teaching for clinicians-in-training. The Accreditation Council for Graduate Medical Education (ACGME) requires all training programs to assess residents in a number of competencies including Practice-Based Learning and Improvements (PBLI). This article describes the piloting of Managing and Adapting Practice (MAP) for child psychiatry fellows, to teach them both EBT and PBLI skills. Eight child psychiatry trainees received 5 full days of MAP training and are delivering MAP in a year-long outpatient teaching clinic. In this setting, MAP is applied to the complex, multiply diagnosed psychiatric patients that present to this clinic. This article describes how MAP tools and resources assist in teaching trainees each of the eight required competency components of PBLI, including identifying deficits in expertise, setting learning goals, performing learning activities, conducting quality improvement methods in practice, incorporating formative feedback, using scientific studies to inform practice, using technology for learning, and participating in patient education. A case example illustrates the use of MAP in teaching PBLI. MAP provides a unique way to teach important quality improvement and practice-based learning skills to trainees while training them in important psychotherapy competence.

  20. Transferring and generalizing deep-learning-based neural encoding models across subjects.

    Science.gov (United States)

    Wen, Haiguang; Shi, Junxing; Chen, Wei; Liu, Zhongming

    2018-08-01

    Recent studies have shown the value of using deep learning models for mapping and characterizing how the brain represents and organizes information for natural vision. However, modeling the relationship between deep learning models and the brain (or encoding models), requires measuring cortical responses to large and diverse sets of natural visual stimuli from single subjects. This requirement limits prior studies to few subjects, making it difficult to generalize findings across subjects or for a population. In this study, we developed new methods to transfer and generalize encoding models across subjects. To train encoding models specific to a target subject, the models trained for other subjects were used as the prior models and were refined efficiently using Bayesian inference with a limited amount of data from the target subject. To train encoding models for a population, the models were progressively trained and updated with incremental data from different subjects. For the proof of principle, we applied these methods to functional magnetic resonance imaging (fMRI) data from three subjects watching tens of hours of naturalistic videos, while a deep residual neural network driven by image recognition was used to model visual cortical processing. Results demonstrate that the methods developed herein provide an efficient and effective strategy to establish both subject-specific and population-wide predictive models of cortical representations of high-dimensional and hierarchical visual features. Copyright © 2018 Elsevier Inc. All rights reserved.

  1. Testing the Community-Based Learning Collaborative (CBLC) implementation model: a study protocol.

    Science.gov (United States)

    Hanson, Rochelle F; Schoenwald, Sonja; Saunders, Benjamin E; Chapman, Jason; Palinkas, Lawrence A; Moreland, Angela D; Dopp, Alex

    2016-01-01

    High rates of youth exposure to violence, either through direct victimization or witnessing, result in significant health/mental health consequences and high associated lifetime costs. Evidence-based treatments (EBTs), such as Trauma-Focused Cognitive Behavioral Therapy (TF-CBT), can prevent and/or reduce these negative effects, yet these treatments are not standard practice for therapists working with children identified by child welfare or mental health systems as needing services. While research indicates that collaboration among child welfare and mental health services sectors improves availability and sustainment of EBTs for children, few implementation strategies designed specifically to promote and sustain inter-professional collaboration (IC) and inter-organizational relationships (IOR) have undergone empirical investigation. A potential candidate for evaluation is the Community-Based Learning Collaborative (CBLC) implementation model, an adaptation of the Learning Collaborative which includes strategies designed to develop and strengthen inter-professional relationships between brokers and providers of mental health services to promote IC and IOR and achieve sustained implementation of EBTs for children within a community. This non-experimental, mixed methods study involves two phases: (1) analysis of existing prospective quantitative and qualitative quality improvement and project evaluation data collected pre and post, weekly, and monthly from 998 participants in one of seven CBLCs conducted as part of a statewide initiative; and (2) Phase 2 collection of new quantitative and qualitative (key informant interviews) data during the funded study period to evaluate changes in relations among IC, IOR, social networks and the penetration and sustainment of TF-CBT in targeted communities. Recruitment for Phase 2 is from the pool of 998 CBLC participants to achieve a targeted enrollment of n = 150. Study aims include: (1) Use existing quality improvement

  2. THE EFFECTIVENESS OF CTL MODEL GUIDED INQUIRI-BASED IN THE TOPIC OF CHEMICALS IN DAILY LIFE TO IMPROVE STUDENTS’ LEARNING OUTCOMES AND ACTIVENESS

    OpenAIRE

    N. R. Fitriani; A. Widiyatmoko; M. Khusniati

    2016-01-01

    Science learning in school can be applied by connecting the material in the learning with real life. However in fact science learning process in SMP Negeri 10 Magelang has not emphasized students’ activity to relate science to real life. Learning science using CTL guided inquiry-based model implement the learning in where teacher provides initial questions related issues or events in everyday life, then students do experiments to prove concepts of science guided by teacher.The purpose of this...

  3. A Comparative Analysis of a Game-Based Mobile Learning Model in Low-Socioeconomic Communities of India

    Science.gov (United States)

    Kim, Paul; Buckner, Elizabeth; Kim, Hyunkyung; Makany, Tamas; Taleja, Neha; Parikh, Vallabhi

    2012-01-01

    This study explores the effectiveness of a game-based mobile learning model for children living in underdeveloped regions with significant contextual variations. Data for this study came from a total of 210 children between the ages of 6-14 years old from six marginalized communities in India. The findings reveal that children with little or no…

  4. Effectiveness of Facebook Based Learning to Enhance Creativity among Islamic Studies Students by Employing Isman Instructional Design Model

    Science.gov (United States)

    Alias, Norlidah; Siraj, Saedah; Daud, Mohd Khairul Azman Md; Hussin, Zaharah

    2013-01-01

    The study examines the effectiveness of Facebook based learning to enhance creativity among Islamic Studies students in the secondary educational setting in Malaysia. It describes the design process by employing the Isman Instructional Design Model. A quantitative study was carried out using experimental method and background survey. The…

  5. Biking with Particles: Junior Triathletes' Learning about Drafting through Exploring Agent-Based Models and Inventing New Tactics

    Science.gov (United States)

    Hirsh, Alon; Levy, Sharona T.

    2013-01-01

    The present research addresses a curious finding: how learning physical principles enhanced athletes' biking performance but not their conceptual understanding. The study involves a model-based triathlon training program, Biking with Particles, concerning aerodynamics of biking in groups (drafting). A conceptual framework highlights several…

  6. A Novel Extreme Learning Machine Classification Model for e-Nose Application Based on the Multiple Kernel Approach.

    Science.gov (United States)

    Jian, Yulin; Huang, Daoyu; Yan, Jia; Lu, Kun; Huang, Ying; Wen, Tailai; Zeng, Tanyue; Zhong, Shijie; Xie, Qilong

    2017-06-19

    A novel classification model, named the quantum-behaved particle swarm optimization (QPSO)-based weighted multiple kernel extreme learning machine (QWMK-ELM), is proposed in this paper. Experimental validation is carried out with two different electronic nose (e-nose) datasets. Being different from the existing multiple kernel extreme learning machine (MK-ELM) algorithms, the combination coefficients of base kernels are regarded as external parameters of single-hidden layer feedforward neural networks (SLFNs). The combination coefficients of base kernels, the model parameters of each base kernel, and the regularization parameter are optimized by QPSO simultaneously before implementing the kernel extreme learning machine (KELM) with the composite kernel function. Four types of common single kernel functions (Gaussian kernel, polynomial kernel, sigmoid kernel, and wavelet kernel) are utilized to constitute different composite kernel functions. Moreover, the method is also compared with other existing classification methods: extreme learning machine (ELM), kernel extreme learning machine (KELM), k-nearest neighbors (KNN), support vector machine (SVM), multi-layer perceptron (MLP), radical basis function neural network (RBFNN), and probabilistic neural network (PNN). The results have demonstrated that the proposed QWMK-ELM outperforms the aforementioned methods, not only in precision, but also in efficiency for gas classification.

  7. Integrated Arts-Based Teaching (IAT) Model for Brain-Based Learning

    Science.gov (United States)

    Inocian, Reynaldo B.

    2015-01-01

    This study analyzes teaching strategies among the eight books in Principles and Methods of Teaching recommended for use in the College of Teacher Education in the Philippines. It seeks to answer the following objectives: (1) identify the most commonly used teaching strategies congruent with the integrated arts-based teaching (IAT) and (2) design…

  8. Towards a Pragmatic Model for Group-Based, Technology-Mediated, Project-Oriented Learning - An Overview of the B2C Model

    Science.gov (United States)

    Lawlor, John; Conneely, Claire; Tangney, Brendan

    The poor assimilation of ICT in formal education is firmly rooted in models of learning prevalent in the classroom which are largely teacher-led, individualistic and reproductive, with little connection between theory and practice and poor linkages across the curriculum. A new model of classroom practice is required to allow for creativity, peer-learning, thematic learning, collaboration and problem solving, i.e. the skills commonly deemed necessary for the knowledge-based society of the 21st century. This paper describes the B2C model for group-based, technology-mediated, project-oriented learning which, while being developed as part of an out of school programme, offers a pragmatic alternative to traditional classroom pedagogy.

  9. Problem-Based Learning--A Corporate Training Model for Community Colleges.

    Science.gov (United States)

    Flint, Wendy

    2003-01-01

    Argues that problem-based learning, which stresses relevant learner issues and allows for the flexibility of the situation and the learners in the classroom, can be used to better prepare students for the workplace. Presents the five steps the process takes students through--engagement, inquiry, solution building, debriefing and reflection, and…

  10. Cultivating Preservice Secondary Teachers for Project-Based Learning: A Four-Step Model

    Science.gov (United States)

    Zhang, Gaoming; Ridgway, Angelia J.; Sachs, Deb

    2015-01-01

    This article describes four different mechanisms for preparing teacher candidates from a liberal arts institution to teach in project based learning (PBL) classrooms: Observe it, Experience it, Create it, and Become it. For each of the four mechanisms, the authors also provide concrete examples of candidates' PBL experiences and candidates'…

  11. Problem-based learning

    NARCIS (Netherlands)

    Loyens, Sofie; Kirschner, Paul A.; Paas, Fred

    2010-01-01

    Loyens, S. M. M., Kirschner, P. A., & Paas, F. (2011). Problem-based learning. In S. Graham (Editor-in-Chief), A. Bus, S. Major, & L. Swanson (Associate Editors), APA educational psychology handbook: Vol. 3. Application to learning and teaching (pp. 403-425). Washington, DC: American Psychological

  12. Natural Language-based Machine Learning Models for the Annotation of Clinical Radiology Reports.

    Science.gov (United States)

    Zech, John; Pain, Margaret; Titano, Joseph; Badgeley, Marcus; Schefflein, Javin; Su, Andres; Costa, Anthony; Bederson, Joshua; Lehar, Joseph; Oermann, Eric Karl

    2018-05-01

    Purpose To compare different methods for generating features from radiology reports and to develop a method to automatically identify findings in these reports. Materials and Methods In this study, 96 303 head computed tomography (CT) reports were obtained. The linguistic complexity of these reports was compared with that of alternative corpora. Head CT reports were preprocessed, and machine-analyzable features were constructed by using bag-of-words (BOW), word embedding, and Latent Dirichlet allocation-based approaches. Ultimately, 1004 head CT reports were manually labeled for findings of interest by physicians, and a subset of these were deemed critical findings. Lasso logistic regression was used to train models for physician-assigned labels on 602 of 1004 head CT reports (60%) using the constructed features, and the performance of these models was validated on a held-out 402 of 1004 reports (40%). Models were scored by area under the receiver operating characteristic curve (AUC), and aggregate AUC statistics were reported for (a) all labels, (b) critical labels, and (c) the presence of any critical finding in a report. Sensitivity, specificity, accuracy, and F1 score were reported for the best performing model's (a) predictions of all labels and (b) identification of reports containing critical findings. Results The best-performing model (BOW with unigrams, bigrams, and trigrams plus average word embeddings vector) had a held-out AUC of 0.966 for identifying the presence of any critical head CT finding and an average 0.957 AUC across all head CT findings. Sensitivity and specificity for identifying the presence of any critical finding were 92.59% (175 of 189) and 89.67% (191 of 213), respectively. Average sensitivity and specificity across all findings were 90.25% (1898 of 2103) and 91.72% (18 351 of 20 007), respectively. Simpler BOW methods achieved results competitive with those of more sophisticated approaches, with an average AUC for presence of any

  13. Students’ Perceptions About Learning Environment of a Distance Course Based on Technology Acceptance Model: A Descriptive Study

    Directory of Open Access Journals (Sweden)

    Erman UZUN

    2013-03-01

    Full Text Available Technology Acceptance Model (TAM is a measure to assess the underlying reasons about the use of a technology. In this study an extended version of TAM were used. This extended version composed of three factors. These are “perceived motivation towards learning environment”, “perceived usefulness” and “perceived ease of use”. In this study, the learning environment of a distance course was investigated to see students’ perceptions. This distance course was delivered from one university to the other university via video-conferencing with ITL Learning Gateway content management system during the whole semester. The participants were the 32 first year vocational higher education institution students. The descriptive findings revealed that each factor of TAM perceived by students as having moderate advantages. It is believed that the underlying reason of this situation was based on the students’ low computer competency and e-learning experiences.

  14. Predicting effects of noncoding variants with deep learning-based sequence model.

    Science.gov (United States)

    Zhou, Jian; Troyanskaya, Olga G

    2015-10-01

    Identifying functional effects of noncoding variants is a major challenge in human genetics. To predict the noncoding-variant effects de novo from sequence, we developed a deep learning-based algorithmic framework, DeepSEA (http://deepsea.princeton.edu/), that directly learns a regulatory sequence code from large-scale chromatin-profiling data, enabling prediction of chromatin effects of sequence alterations with single-nucleotide sensitivity. We further used this capability to improve prioritization of functional variants including expression quantitative trait loci (eQTLs) and disease-associated variants.

  15. Maximum Spanning Tree Model on Personalized Web Based Collaborative Learning in Web 3.0

    OpenAIRE

    Padma, S.; Seshasaayee, Ananthi

    2012-01-01

    Web 3.0 is an evolving extension of the current web environme bnt. Information in web 3.0 can be collaborated and communicated when queried. Web 3.0 architecture provides an excellent learning experience to the students. Web 3.0 is 3D, media centric and semantic. Web based learning has been on high in recent days. Web 3.0 has intelligent agents as tutors to collect and disseminate the answers to the queries by the students. Completely Interactive learner's query determine the customization of...

  16. Learning-based Nonlinear Model Predictive Control to Improve Vision-based Mobile Robot Path Tracking

    Science.gov (United States)

    2015-07-01

    corresponding cost function to be J(u) = ( xd − x)TQx ( xd − x) + uTRu, (20) where Qx ∈ RKnx×Knx is positive semi-definite, R and u are as in (3), xd is a...sequence of desired states, xd = ( xd ,k+1, . . . , xd ,k+K), x is a sequence of predicted states, x = (xk+1, . . . ,xk+K), and K is the given prediction...vact,k−1+b, ωact,k−1+b), based ωk θk vk xd ,i−1 xd ,i xd ,i+1 xk yk Figure 5: Definition of the robot velocities, vk and ωk, and three pose variables

  17. The development of learning model for natural science based on environmental in conservation area of Bengkulu University

    Science.gov (United States)

    Karyadi, B.; Susanta, A.; Winari, E. W.; Ekaputri, R. Z.; Enersi, D.

    2018-05-01

    Research on development of a learning model for Natural Science base on conservation area in Bengkulu University has been conducted. The research methods were referred to the standard steps of Research and Development. Stage activities were (a) analysis of needs, (b) observation of the ecological aspects of conservation area as a learning resource, and (c) instructional design based on conservation area for secondary school students. The observation results on the ecological aspects revealed that the diversity of plants and animals, at the conservation area were sufficient as a source for learning. The instructional design was prepared in three phase activities namely Introduction-Exploration-Interpretation (IEI), and then it was compiled in a teaching material Based on Surrounding Natural Environment” (BSNE). The results of a limited scale trial at secondary school students in two districts of Bengkulu province showed that, the students who learned using the IEI model at the conservation area have a good performance and critical thinking. The product from the research is a book named BSNE that can be used for teachers and conservation practitioners in doing the learning activities on environmental conservation which involved public participation.

  18. Foundations of Game-Based Learning

    Science.gov (United States)

    Plass, Jan L.; Homer, Bruce D.; Kinzer, Charles K.

    2015-01-01

    In this article we argue that to study or apply games as learning environments, multiple perspectives have to be taken into account. We first define game-based learning and gamification, and then discuss theoretical models that describe learning with games, arguing that playfulness is orthogonal to learning theory. We then review design elements…

  19. The research-based learning development model as a foundation in generating research ideas

    Science.gov (United States)

    Puspitasari, Poppy; Dika, Johan Wayan; Permanasari, Avita Ayu

    2017-09-01

    Research Based Learning is learning that requires students to have exploration skills related to their field. By doing so, students are encouraged to create skills in managing the higherorder of abstraction in order to resolve any problems encountered. The study was done to make the schemes and sequences of learning needed by the students in order to help them to explore first ideas for their upcoming thesis. The scheme development resulted in five stages consisting of 1) identifying research journals; 2) track the development of research topics; 3) reviewing research journals; 4) discussing the results of the reviews; and 5) formulating the research topic. Furthermore, the application of 5 the stage receives percentage agreement of students was 85.9%. Therefore, it can be noted that the application of the scheme is definitely a help for students to find research ideas.

  20. Professional Practice of Medical Training in the E-Learning System: The Conceptual Model Based on a Critical Review

    Directory of Open Access Journals (Sweden)

    Zohrehsadat Mirmoghtadaie

    2017-04-01

    Full Text Available Background and Purpose: In education of medical science courses, there has been a growing orientation towards replacing traditional teaching in with E-learning education. Since the modern system of education is based on self-directed learning, e-learning requires special powers to deal with new-emerging challenges and professionally encounter the learning environment. The purpose of the present research is to explain and provide a conceptual model for professional competency in this system.Methods: In this review, different internet and library resources, indexed in Scirus, Pre Quest, Scopus, IEEE, SID, Magiran, Eric, Taylor and Francis, and Google Scholar from 1990 to 2015 were searched using the following keywords: function, manner, ethics, conduct disposition, netiquette, values, academic fraud, moral professionalism, and behavior ine-learning in combination and separately. The Critical Review methodology and Carnwell and Randolph structures were used. The most recent and richest resources that were more relevant to the issue were selected and their information was extracted.Results: Among review of 98 articles, documents of 34 relevant and valid articles were extracted. Based on the results, Digital Literacy, study skills, Cyber Ethics, and Netiquette were considered the main components of scientific and ethical competency in e-learning. 40 components were included in these dimensions.Conclusions: Although there is general interest in e-learning, the target population (learners are not prepared to use such an environment and require strong support. In this paper, we provided a summarized scheme and conceptual pattern fore-learners to move towards promotion of learning.Keywords: PROFESSIONAL FUNCTION, E-LEARNER, E-LEARNING, CRITICAL REVIEW

  1. From Aspiration to Action: A Learning Intentions Model to Promote Critical Engagement with Science in the Print-Based Media

    Science.gov (United States)

    McClune, Billy; Jarman, Ruth

    2011-11-01

    Science programmes which prepare students to read critically and respond thoughtfully to science-based reports in the media could play an important role in promoting informed participation in the public debate about issues relating to science, technology and society. Evidence based guidance about the practice and pattern of use of science-based media in the classroom is limited. This study sought to identify learning intentions that teachers believe ought to underpin the development of programmes of study designed to achieve this end-result. Teachers' views of knowledge, skills and attitudes required to engage critically with science-based news served as a basis for this study. Teachers developed a pedagogical model by selecting appropriate statements of learning intentions, grouping these into coherent and manageable themes and coding them according to perceived level of difficulty. The model is largely compatible with current curricular provision in the UK, highlights opportunities for interdisciplinary collaboration and illustrates the developmental nature of the topic.

  2. BROA: An agent-based model to recommend relevant Learning Objects from Repository Federations adapted to learner profile

    Directory of Open Access Journals (Sweden)

    Paula A. Rodríguez

    2013-03-01

    Full Text Available Learning Objects (LOs are distinguished from traditional educational resources for their easy and quickly availability through Web-based repositories, from which they are accessed through their metadata. In addition, having a user profile allows an educational recommender system to help the learner to find the most relevant LOs based on their needs and preferences. The aim of this paper is to propose an agent-based model so-called BROA to recommend relevant LOs recovered from Repository Federations as well as LOs adapted to learner profile. The model proposed uses both role and service models of GAIA methodology, and the analysis models of the MAS-CommonKADS methodology. A prototype was built based on this model and validated to obtain some assessing results that are finally presented.

  3. Tracking influence between naive Bayes models using score-based structure learning

    CSIR Research Space (South Africa)

    Ajoodha, R

    2017-11-01

    Full Text Available Current structure learning practices in Bayesian networks have been developed to learn the structure between observable variables and learning latent parameters independently. One exception establishes a variant of EM for learning the structure...

  4. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Chan, Pak Kwan; Tin, Chung

    2018-02-01

    Objective. Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). Approach. The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. Main results. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. Significance. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  5. Real-time cerebellar neuroprosthetic system based on a spiking neural network model of motor learning.

    Science.gov (United States)

    Xu, Tao; Xiao, Na; Zhai, Xiaolong; Kwan Chan, Pak; Tin, Chung

    2018-02-01

    Damage to the brain, as a result of various medical conditions, impacts the everyday life of patients and there is still no complete cure to neurological disorders. Neuroprostheses that can functionally replace the damaged neural circuit have recently emerged as a possible solution to these problems. Here we describe the development of a real-time cerebellar neuroprosthetic system to substitute neural function in cerebellar circuitry for learning delay eyeblink conditioning (DEC). The system was empowered by a biologically realistic spiking neural network (SNN) model of the cerebellar neural circuit, which considers the neuronal population and anatomical connectivity of the network. The model simulated synaptic plasticity critical for learning DEC. This SNN model was carefully implemented on a field programmable gate array (FPGA) platform for real-time simulation. This hardware system was interfaced in in vivo experiments with anesthetized rats and it used neural spikes recorded online from the animal to learn and trigger conditioned eyeblink in the animal during training. This rat-FPGA hybrid system was able to process neuronal spikes in real-time with an embedded cerebellum model of ~10 000 neurons and reproduce learning of DEC with different inter-stimulus intervals. Our results validated that the system performance is physiologically relevant at both the neural (firing pattern) and behavioral (eyeblink pattern) levels. This integrated system provides the sufficient computation power for mimicking the cerebellar circuit in real-time. The system interacts with the biological system naturally at the spike level and can be generalized for including other neural components (neuron types and plasticity) and neural functions for potential neuroprosthetic applications.

  6. Collaboration model in e-learning for universities based on agents

    OpenAIRE

    Bernuy, Augusto E.; García, Víctor M.

    2006-01-01

    The paper presents the basic requirements that must cover distance education processes (“e-learning”) in universities. We show the concepts of instruction design, an adaptive learning model for evaluating necessities, accreditation, and quality proposal. The experience indicates that to obtain good results we should evaluate the differences between the criteria of the professor and the criteria of the student about: the educative aspects, the user reaction (in each perspective), the reading a...

  7. Attention, Working Memory, and Long-Term Memory in Multimedia Learning: An Integrated Perspective Based on Process Models of Working Memory

    Science.gov (United States)

    Schweppe, Judith; Rummer, Ralf

    2014-01-01

    Cognitive models of multimedia learning such as the Cognitive Theory of Multimedia Learning (Mayer 2009) or the Cognitive Load Theory (Sweller 1999) are based on different cognitive models of working memory (e.g., Baddeley 1986) and long-term memory. The current paper describes a working memory model that has recently gained popularity in basic…

  8. A new computational account of cognitive control over reinforcement-based decision-making: Modeling of a probabilistic learning task.

    Science.gov (United States)

    Zendehrouh, Sareh

    2015-11-01

    Recent work on decision-making field offers an account of dual-system theory for decision-making process. This theory holds that this process is conducted by two main controllers: a goal-directed system and a habitual system. In the reinforcement learning (RL) domain, the habitual behaviors are connected with model-free methods, in which appropriate actions are learned through trial-and-error experiences. However, goal-directed behaviors are associated with model-based methods of RL, in which actions are selected using a model of the environment. Studies on cognitive control also suggest that during processes like decision-making, some cortical and subcortical structures work in concert to monitor the consequences of decisions and to adjust control according to current task demands. Here a computational model is presented based on dual system theory and cognitive control perspective of decision-making. The proposed model is used to simulate human performance on a variant of probabilistic learning task. The basic proposal is that the brain implements a dual controller, while an accompanying monitoring system detects some kinds of conflict including a hypothetical cost-conflict one. The simulation results address existing theories about two event-related potentials, namely error related negativity (ERN) and feedback related negativity (FRN), and explore the best account of them. Based on the results, some testable predictions are also presented. Copyright © 2015 Elsevier Ltd. All rights reserved.

  9. Pulmonary emphysema classification based on an improved texton learning model by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryujiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2013-03-01

    In this paper, we present a texture classification method based on texton learned via sparse representation (SR) with new feature histogram maps in the classification of emphysema. First, an overcomplete dictionary of textons is learned via KSVD learning on every class image patches in the training dataset. In this stage, high-pass filter is introduced to exclude patches in smooth area to speed up the dictionary learning process. Second, 3D joint-SR coefficients and intensity histograms of the test images are used for characterizing regions of interest (ROIs) instead of conventional feature histograms constructed from SR coefficients of the test images over the dictionary. Classification is then performed using a classifier with distance as a histogram dissimilarity measure. Four hundreds and seventy annotated ROIs extracted from 14 test subjects, including 6 paraseptal emphysema (PSE) subjects, 5 centrilobular emphysema (CLE) subjects and 3 panlobular emphysema (PLE) subjects, are used to evaluate the effectiveness and robustness of the proposed method. The proposed method is tested on 167 PSE, 240 CLE and 63 PLE ROIs consisting of mild, moderate and severe pulmonary emphysema. The accuracy of the proposed system is around 74%, 88% and 89% for PSE, CLE and PLE, respectively.

  10. Improving Junior High Schools’ Critical Thinking Skills Based on Test Three Different Models of Learning

    Directory of Open Access Journals (Sweden)

    Nur Miftahul Fuad

    2017-01-01

    Full Text Available The aims of this study were (1 to find out the differences in critical thinking skills among students who were given three different learning models: differentiated science inquiry combined with mind map, differentiated science inquiry model, and conventional model, (2 to find out the differences of critical thinking skills among male and female students. This study is a quasi-experimental research with pretest-posttest nonequivalent control group design. The population in this research is the seventh grade students of junior high schools in Kediri, Indonesia. The sample of the research is in the number of 96 students distributed in three classes at different schools. The data of critical thinking skills are gained from test scores and then analyzed using descriptive and inferential statistics through ANCOVA. The results of research revealed that there are different skills in critical thinking in different models. The highest skills in critical thinking are reached by students who were given differentiated science inquiry model combined with mind map in their learning. There are also differences in critical thinking skills between male and female students.

  11. Perbedaan hasil belajar fisika siswa antara model pembelajaran Problem Based Learning (PBL dengan model pembelajaran Prediction, Observation, and Explanation (POE di kelas X SMA Negeri 5 Lubuklinggau

    Directory of Open Access Journals (Sweden)

    Tri Ariani

    2016-11-01

    Full Text Available Penelitian ini bertujuan untuk mengetahui Perbedaan Hasil Belajar Fisika Siswa antara Model Pembelajaran Problem Based Learning (PBL dengan Model Pembelajaran Prediction, Observation, And Explanation (POE di Kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016. Jenis penelitian ini adalah penelitian kuantitatif dengan metode penelitian eksperimen semu yang dilaksanakan dengan membandingkan kelompok eksperimen I dan kelompok eksperimen II desain penelitian  ini pre-test post-test group design. Populasi penelitian ini adalah seluruh siswa kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016, yang terdiri dari 314 siswa dari 9 kelas. Pengambilan sampel dilakukan secara acak (Simple Random Sampling dengan cara pengundian nomor kelas populasi. Pengumpulan data berupa tes, data tes yang sudah dianalisis dengan uji-t, pada taraf  a= 0,05, diperoleh thitung > ttabel (2,17 > 2,00. Rata-rata akhir hasil belajar fisika kelas eksperimen I sebesar 73,4 sedangkan pada kelas kelas eksperimen II  sebesar 69,14. Sehingga dapat disimpulkan ada Perbedaan Hasil Belajar Fisika Siswa antara Model Pembelajaran Problem Based Learning (PBL Dengan Model Pembelajaran Prediction, Observation, And Explanation (POE Di Kelas X SMA Negeri 5 Lubuklinggau Tahun Pelajaran 2015/2016. The aim of this research was to find out the Comparative Results Between Students Studying Physics Learning Model Problem Based Learning (PBL with Learning Model Prediction, Observation, And Explanation (POE in the Class X SMAN 5 Lubuklinggau 2015/2016 Academic Year . This research was a quantitative research methods of experimental research conducted by comparing the experimental group I and group II experimental research design was a pre-test post-test group design. As the population in this research were all students of class X SMA Negeri 5 Lubuklinggau Academic Year 2015/2016, consisting of 314 students from the ninth grade. Sampling is done randomly (Simple Random Sampling by

  12. Objects Classification by Learning-Based Visual Saliency Model and Convolutional Neural Network.

    Science.gov (United States)

    Li, Na; Zhao, Xinbo; Yang, Yongjia; Zou, Xiaochun

    2016-01-01

    Humans can easily classify different kinds of objects whereas it is quite difficult for computers. As a hot and difficult problem, objects classification has been receiving extensive interests with broad prospects. Inspired by neuroscience, deep learning concept is proposed. Convolutional neural network (CNN) as one of the methods of deep learning can be used to solve classification problem. But most of deep learning methods, including CNN, all ignore the human visual information processing mechanism when a person is classifying objects. Therefore, in this paper, inspiring the completed processing that humans classify different kinds of objects, we bring forth a new classification method which combines visual attention model and CNN. Firstly, we use the visual attention model to simulate the processing of human visual selection mechanism. Secondly, we use CNN to simulate the processing of how humans select features and extract the local features of those selected areas. Finally, not only does our classification method depend on those local features, but also it adds the human semantic features to classify objects. Our classification method has apparently advantages in biology. Experimental results demonstrated that our method made the efficiency of classification improve significantly.

  13. Discovering the Power of Individual-Based Modelling in Teaching and Learning: The Study of a Predator-Prey System

    Science.gov (United States)

    Ginovart, Marta

    2014-08-01

    The general aim is to promote the use of individual-based models (biological agent-based models) in teaching and learning contexts in life sciences and to make their progressive incorporation into academic curricula easier, complementing other existing modelling strategies more frequently used in the classroom. Modelling activities for the study of a predator-prey system for a mathematics classroom in the first year of an undergraduate program in biosystems engineering have been designed and implemented. These activities were designed to put two modelling approaches side by side, an individual-based model and a set of ordinary differential equations. In order to organize and display this, a system with wolves and sheep in a confined domain was considered and studied. With the teaching material elaborated and a computer to perform the numerical resolutions involved and the corresponding individual-based simulations, the students answered questions and completed exercises to achieve the learning goals set. Students' responses regarding the modelling of biological systems and these two distinct methodologies applied to the study of a predator-prey system were collected via questionnaires, open-ended queries and face-to-face dialogues. Taking into account the positive responses of the students when they were doing these activities, it was clear that using a discrete individual-based model to deal with a predator-prey system jointly with a set of ordinary differential equations enriches the understanding of the modelling process, adds new insights and opens novel perspectives of what can be done with computational models versus other models. The complementary views given by the two modelling approaches were very well assessed by students.

  14. Gold-standard evaluation of a folksonomy-based ontology learning model

    Science.gov (United States)

    Djuana, E.

    2018-03-01

    Folksonomy, as one result of collaborative tagging process, has been acknowledged for its potential in improving categorization and searching of web resources. However, folksonomy contains ambiguities such as synonymy and polysemy as well as different abstractions or generality problem. To maximize its potential, some methods for associating tags of folksonomy with semantics and structural relationships have been proposed such as using ontology learning method. This paper evaluates our previous work in ontology learning according to gold-standard evaluation approach in comparison to a notable state-of-the-art work and several baselines. The results show that our method is comparable to the state-of the art work which further validate our approach as has been previously validated using task-based evaluation approach.

  15. Penerapan Model Project Based Learning untuk Meningkatan Kinerja dan Prestasi Belajar Fisika Siswa SMK

    Directory of Open Access Journals (Sweden)

    Eko Mulyadi

    2016-01-01

    Full Text Available This study aims at improving the students’ performance and achievement in grade XI AV1 of SMK Negeri 3 Yogyakarta with the application of Project Based Learning in Physics learning for Static Electricity and Direct Current Electricity competencies. This study used a classroom action research approach implementing two cycles. Every cycle consisted of planning, action, observation and reflection. The PjBL included the steps of determining, planning, scheduling, monitoring, presentation and evaluation. The aspects of the achievement were measured by a pre-test, a product assessment, and a post-test. The results showed that the application of PjBL improved the performance up to 18.75% and improved the achievement 15.70 and 24.63 for the first cycle and the second cycle respectively.

  16. Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data.

    Science.gov (United States)

    Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

    2017-05-07

    A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

  17. Machine learning-based kinetic modeling: a robust and reproducible solution for quantitative analysis of dynamic PET data

    Science.gov (United States)

    Pan, Leyun; Cheng, Caixia; Haberkorn, Uwe; Dimitrakopoulou-Strauss, Antonia

    2017-05-01

    A variety of compartment models are used for the quantitative analysis of dynamic positron emission tomography (PET) data. Traditionally, these models use an iterative fitting (IF) method to find the least squares between the measured and calculated values over time, which may encounter some problems such as the overfitting of model parameters and a lack of reproducibility, especially when handling noisy data or error data. In this paper, a machine learning (ML) based kinetic modeling method is introduced, which can fully utilize a historical reference database to build a moderate kinetic model directly dealing with noisy data but not trying to smooth the noise in the image. Also, due to the database, the presented method is capable of automatically adjusting the models using a multi-thread grid parameter searching technique. Furthermore, a candidate competition concept is proposed to combine the advantages of the ML and IF modeling methods, which could find a balance between fitting to historical data and to the unseen target curve. The machine learning based method provides a robust and reproducible solution that is user-independent for VOI-based and pixel-wise quantitative analysis of dynamic PET data.

  18. Beyond the Central Dogma: Model-Based Learning of How Genes Determine Phenotypes

    Science.gov (United States)

    Reinagel, Adam; Speth, Elena Bray

    2016-01-01

    In an introductory biology course, we implemented a learner-centered, model-based pedagogy that frequently engaged students in building conceptual models to explain how genes determine phenotypes. Model-building tasks were incorporated within case studies and aimed at eliciting students' understanding of 1) the origin of variation in a population…

  19. Subgrid-scale scalar flux modelling based on optimal estimation theory and machine-learning procedures

    Science.gov (United States)

    Vollant, A.; Balarac, G.; Corre, C.

    2017-09-01

    New procedures are explored for the development of models in the context of large eddy simulation (LES) of a passive scalar. They rely on the combination of the optimal estimator theory with machine-learning algorithms. The concept of optimal estimator allows to identify the most accurate set of parameters to be used when deriving a model. The model itself can then be defined by training an artificial neural network (ANN) on a database derived from the filtering of direct numerical simulation (DNS) results. This procedure leads to a subgrid scale model displaying good structural performance, which allows to perform LESs very close to the filtered DNS results. However, this first procedure does not control the functional performance so that the model can fail when the flow configuration differs from the training database. Another procedure is then proposed, where the model functional form is imposed and the ANN used only to define the model coefficients. The training step is a bi-objective optimisation in order to control both structural and functional performances. The model derived from this second procedure proves to be more robust. It also provides stable LESs for a turbulent plane jet flow configuration very far from the training database but over-estimates the mixing process in that case.

  20. A Hybrid Short-Term Traffic Flow Prediction Model Based on Singular Spectrum Analysis and Kernel Extreme Learning Machine.

    Directory of Open Access Journals (Sweden)

    Qiang Shang

    Full Text Available Short-term traffic flow prediction is one of the most important issues in the field of intelligent transport system (ITS. Because of the uncertainty and nonlinearity, short-term traffic flow prediction is a challenging task. In order to improve the accuracy of short-time traffic flow prediction, a hybrid model (SSA-KELM is proposed based on singular spectrum analysis (SSA and kernel extreme learning machine (KELM. SSA is used to filter out the noise of traffic flow time series. Then, the filtered traffic flow data is used to train KELM model, the optimal input form of the proposed model is determined by phase space reconstruction, and parameters of the model are optimized by gravitational search algorithm (GSA. Finally, case validation is carried out using the measured data of an expressway in Xiamen, China. And the SSA-KELM model is compared with several well-known prediction models, including support vector machine, extreme learning machine, and single KLEM model. The experimental results demonstrate that performance of the proposed model is superior to that of the comparison models. Apart from accuracy improvement, the proposed model is more robust.

  1. A Q-learning agent-based model for the analysis of the power market dynamics

    International Nuclear Information System (INIS)

    Tellidou, A.; Bakirtzis, A.

    2006-01-01

    The introduction of deregulation in the electricity sector resulted in a different way of thinking and acting on the part of producers. Power suppliers strive to maximize their profit and their utilization rate through a bidding process. According to the pricing system, the competition conditions, the demand side bidding, and the available information, they develop different bidding strategies in order to exploit every possible advantage. This paper presents the Q-Learning algorithm in order to model the bidding strategy of suppliers in electricity auctions. The study examined players' behaviour in the spot market and the change in their policy under different conditions of demand. The Q-learning algorithm considers a novel approach to the definition of states and actions. States are not defined exclusively, as states of the environment, but rather, are different for each agent and relative to the impact the environment has on the agent. Actions are not represented by the price the agent bids, but by the variation between the previous and the new bid price. Market structure was described in this paper and the supplier's bidding problem was formulated in terms of Q-learning. A description of the test system was presented and the parameter selection of the algorithm, as well as the presentation and the results of four case study simulations were discussed. The Q-learning algorithm in supplier bidding strategy showed very promising results. it was suggested that the research should be expanded to include more producers or tests of transmission systems. 9 refs., 2 tabs., 6 figs

  2. Analisis Kemampuan Berpikir Tingkat Tinggi Mahasiswa (Higher Order Thinking dalam Menyelesaikan Soal Konsep Optika melalui Model Problem Based Learning

    Directory of Open Access Journals (Sweden)

    Nurhayati Nurhayati

    2017-12-01

    Full Text Available Abstract This study aims to describe the ability of higher order thinking students in solving the problem of the concept of optics after given the learning with problem-based learning model. This research uses a descriptive method with quantitative approach. The subjects of the research are students of the second semester of physics education study program, amounting to 19 people. Data collection techniques used are two tier multiple choice shaped test consisting of eight questions include the level of analyzing, evaluating and creating. Based on the results of data analysis, it is known that the ability of high-level thinking of students in optical learning has enough categories with the following details: (1 The percentage of students who have excellent high-level thinking skills is 15.79%, good category of 31.58%, enough category of 42.11%, and category less than 10.53%; (2 The percentage of student ability in answer about level of analyze equal to 68.42%, student ability in answer about evaluation level 57.89% and equal to 53.51% for student ability in answer level question create. Keywords: higher order thinking, optics, problem-based learning model Abstrak Penelitian ini bertujuan untuk mendeskripsikan kemampuan berpikir tingkat tinggi mahasiswa (higher order thinking dalam menyelesaikan soal konsep optika setelah diberikan pembelajaran dengan model problem based learning. Metode penelitian yang digunakan adalah metode deskriptif dengan pendekatan kuantitatif. Subjek penelitian yaitu mahasiswa semester II program studi pendidikan fisika yang berjumlah 19 orang. Teknik pengumpulan data yang digunakan adalah tes berbentuk two tier multiple choice yang terdiri dari delapan soal meliputi tingkatan menganalisis, mengevaluasi dan mencipta. Berdasarkan hasil analisis data, diketahui bahwa kemampuan berpikir tingkat tinggi mahasiswa dalam pembelajaran optika memiliki kategori cukup dengan rincian sebagai berikut: (1 Persentase mahasiswa yang

  3. An application to pulmonary emphysema classification based on model of texton learning by sparse representation

    Science.gov (United States)

    Zhang, Min; Zhou, Xiangrong; Goshima, Satoshi; Chen, Huayue; Muramatsu, Chisako; Hara, Takeshi; Yokoyama, Ryojiro; Kanematsu, Masayuki; Fujita, Hiroshi

    2012-03-01

    We aim at using a new texton based texture classification method in the classification of pulmonary emphysema in computed tomography (CT) images of the lungs. Different from conventional computer-aided diagnosis (CAD) pulmonary emphysema classification methods, in this paper, firstly, the dictionary of texton is learned via applying sparse representation(SR) to image patches in the training dataset. Then the SR coefficients of the test images over the dictionary are used to construct the histograms for texture presentations. Finally, classification is performed by using a nearest neighbor classifier with a histogram dissimilarity measure as distance. The proposed approach is tested on 3840 annotated regions of interest consisting of normal tissue and mild, moderate and severe pulmonary emphysema of three subtypes. The performance of the proposed system, with an accuracy of about 88%, is comparably higher than state of the art method based on the basic rotation invariant local binary pattern histograms and the texture classification method based on texton learning by k-means, which performs almost the best among other approaches in the literature.

  4. Applying a machine learning model using a locally preserving projection based feature regeneration algorithm to predict breast cancer risk

    Science.gov (United States)

    Heidari, Morteza; Zargari Khuzani, Abolfazl; Danala, Gopichandh; Mirniaharikandehei, Seyedehnafiseh; Qian, Wei; Zheng, Bin

    2018-03-01

    Both conventional and deep machine learning has been used to develop decision-support tools applied in medical imaging informatics. In order to take advantages of both conventional and deep learning approach, this study aims to investigate feasibility of applying a locally preserving projection (LPP) based feature regeneration algorithm to build a new machine learning classifier model to predict short-term breast cancer risk. First, a computer-aided image processing scheme was used to segment and quantify breast fibro-glandular tissue volume. Next, initially computed 44 image features related to the bilateral mammographic tissue density asymmetry were extracted. Then, an LLP-based feature combination method was applied to regenerate a new operational feature vector using a maximal variance approach. Last, a k-nearest neighborhood (KNN) algorithm based machine learning classifier using the LPP-generated new feature vectors was developed to predict breast cancer risk. A testing dataset involving negative mammograms acquired from 500 women was used. Among them, 250 were positive and 250 remained negative in the next subsequent mammography screening. Applying to this dataset, LLP-generated feature vector reduced the number of features from 44 to 4. Using a leave-onecase-out validation method, area under ROC curve produced by the KNN classifier significantly increased from 0.62 to 0.68 (p breast cancer detected in the next subsequent mammography screening.

  5. Learning Vocabulary in a Foreign Language: A Computer Software Based Model Attempt

    Science.gov (United States)

    Yelbay Yilmaz, Yasemin

    2015-01-01

    This study aimed at devising a vocabulary learning software that would help learners learn and retain vocabulary items effectively. Foundation linguistics and learning theories have been adapted to the foreign language vocabulary learning context using a computer software named Parole that was designed exclusively for this study. Experimental…

  6. Drawing-to-Learn: A Framework for Using Drawings to Promote Model-Based Reasoning in Biology

    Science.gov (United States)

    Quillin, Kim; Thomas, Stephen

    2015-01-01

    The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report’s Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. PMID:25713094

  7. The Effect of Model Fidelity on Learning Outcomes of a Simulation-Based Education Program for Central Venous Catheter Insertion.

    Science.gov (United States)

    Diederich, Emily; Mahnken, Jonathan D; Rigler, Sally K; Williamson, Timothy L; Tarver, Stephen; Sharpe, Matthew R

    2015-12-01

    Simulation-based education for central venous catheter (CVC) insertion has been repeatedly documented to improve performance, but the impact of simulation model fidelity has not been described. The aim of this study was to examine the impact of the physical fidelity of the simulation model on learning outcomes for a simulation-based education program for CVC insertion. Forty consecutive residents rotating through the medical intensive care unit of an academic medical center completed a simulation-based education program for CVC insertion. The curriculum was designed in accordance with the principles of deliberate practice and mastery learning. Each resident underwent baseline skills testing and was then randomized to training on a commercially available CVC model with high physical fidelity (High-Fi group) or a simply constructed model with low physical fidelity (Low-Fi group) in a noninferiority trial. Upon completion of their medical intensive care unit rotation 4 weeks later, residents returned for repeat skills testing on the high-fidelity model using a 26-item checklist. The mean (SD) posttraining score on the 26-item checklist for the Low-Fi group was 23.8 (2.2) (91.5%) and was not inferior to the mean (SD) score for the High-Fi group of 22.5 (2.6) (86.5%) (P Simulation-based education using equipment with low physical fidelity can achieve learning outcomes comparable with those with high-fidelity equipment, as long as other aspects of fidelity are maintained and robust educational principles are applied during the design of the curriculum.

  8. An instructional model for the teaching of physics, based on a meaningful learning theory and class experiences

    Directory of Open Access Journals (Sweden)

    Ricardo Chrobak

    1997-05-01

    Full Text Available Practically all research studies concerning the teaching of Physics point out the fact that conventional instructional models fail to achieve their objectives. Many attempts have been done to change this situation, frequently with disappointing results. This work, which is the experimental stage in a research project of a greater scope, represents an effort to change to a model based on a cognitive learning theory, known as the Ausubel-Novak-Gowin theory, making use of the metacognitive tools that emerge from this theory. The results of this work indicate that the students react positively to the goals of meaningful learning, showing substantial understanding of Newtonian Mechanics. An important reduction in the study time required to pass the course has also been reported.

  9. Research on Healthy Anomaly Detection Model Based on Deep Learning from Multiple Time-Series Physiological Signals

    Directory of Open Access Journals (Sweden)

    Kai Wang

    2016-01-01

    Full Text Available Health is vital to every human being. To further improve its already respectable medical technology, the medical community is transitioning towards a proactive approach which anticipates and mitigates risks before getting ill. This approach requires measuring the physiological signals of human and analyzes these data at regular intervals. In this paper, we present a novel approach to apply deep learning in physiological signals analysis that allows doctor to identify latent risks. However, extracting high level information from physiological time-series data is a hard problem faced by the machine learning communities. Therefore, in this approach, we apply model based on convolutional neural network that can automatically learn features from raw physiological signals in an unsupervised manner and then based on the learned features use multivariate Gauss distribution anomaly detection method to detect anomaly data. Our experiment is shown to have a significant performance in physiological signals anomaly detection. So it is a promising tool for doctor to identify early signs of illness even if the criteria are unknown a priori.

  10. What Learning Analytics‐Based Prediction Models Tell Us About Feedback Preferences of Students

    NARCIS (Netherlands)

    Nguyen, Quan; Tempelaar, Dirk; Rienties, Bart; Giesbers, Bas

    2016-01-01

    Learning analytics seeks to enhance learning processes through systematic measurements of learning-related data and to provide informative feedback to learners and educators (Siemens & Long, 2011). This study examined the use of preferred feedback modes in students by using a dispositional

  11. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    Energy Technology Data Exchange (ETDEWEB)

    Singh, Kunwar P., E-mail: kpsingh_52@yahoo.com; Gupta, Shikha

    2014-03-15

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R{sup 2}) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R{sup 2} and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  12. In silico prediction of toxicity of non-congeneric industrial chemicals using ensemble learning based modeling approaches

    International Nuclear Information System (INIS)

    Singh, Kunwar P.; Gupta, Shikha

    2014-01-01

    Ensemble learning approach based decision treeboost (DTB) and decision tree forest (DTF) models are introduced in order to establish quantitative structure–toxicity relationship (QSTR) for the prediction of toxicity of 1450 diverse chemicals. Eight non-quantum mechanical molecular descriptors were derived. Structural diversity of the chemicals was evaluated using Tanimoto similarity index. Stochastic gradient boosting and bagging algorithms supplemented DTB and DTF models were constructed for classification and function optimization problems using the toxicity end-point in T. pyriformis. Special attention was drawn to prediction ability and robustness of the models, investigated both in external and 10-fold cross validation processes. In complete data, optimal DTB and DTF models rendered accuracies of 98.90%, 98.83% in two-category and 98.14%, 98.14% in four-category toxicity classifications. Both the models further yielded classification accuracies of 100% in external toxicity data of T. pyriformis. The constructed regression models (DTB and DTF) using five descriptors yielded correlation coefficients (R 2 ) of 0.945, 0.944 between the measured and predicted toxicities with mean squared errors (MSEs) of 0.059, and 0.064 in complete T. pyriformis data. The T. pyriformis regression models (DTB and DTF) applied to the external toxicity data sets yielded R 2 and MSE values of 0.637, 0.655; 0.534, 0.507 (marine bacteria) and 0.741, 0.691; 0.155, 0.173 (algae). The results suggest for wide applicability of the inter-species models in predicting toxicity of new chemicals for regulatory purposes. These approaches provide useful strategy and robust tools in the screening of ecotoxicological risk or environmental hazard potential of chemicals. - Graphical abstract: Importance of input variables in DTB and DTF classification models for (a) two-category, and (b) four-category toxicity intervals in T. pyriformis data. Generalization and predictive abilities of the

  13. Hierarchical Bayesian Models of Subtask Learning

    Science.gov (United States)

    Anglim, Jeromy; Wynton, Sarah K. A.

    2015-01-01

    The current study used Bayesian hierarchical methods to challenge and extend previous work on subtask learning consistency. A general model of individual-level subtask learning was proposed focusing on power and exponential functions with constraints to test for inconsistency. To study subtask learning, we developed a novel computer-based booking…

  14. Experience-based Learning in Acadia National Park: a Successful, Long-running, Model Field Course

    Science.gov (United States)

    Connaughton, M.

    2015-12-01

    This two-week field course has been offered alternate summers since 2000 in Acadia National Park on Mount Desert Island, Maine and addresses the geological history, physical and biological oceanography and principles of community ecology applicable to terrestrial and/or marine communities of coastal Maine. The course is often transformative and deeply meaningful to the students, many of whom have limited travel experience. The essential components of experience-based learning are well represented in this class with multiple opportunities for abstract conceptualization, active experimentation, concrete hands-on experiences and reflective observation built into the course. Each day begins with a lecture introducing concepts, which are then made concrete though daily field trips (4-8 hours in duration) into the park that include rigorous hiking, some kayaking and one commercial nature cruise. Field trips include hands-on experience with lecture concepts, on-site lessons in field methods, and data collection for independent projects. Each field trip is tied to a specific independent project, which are generated by the instructor, but self-selected by the students. Every student is actively involved in data collection during each field trip, with one student in charge of the collection each day. Daily guided journaling in three parts (scientific, personal and creative) and evening discussions provide ample opportunity for the student to reflect on the scientific content of the course, examine their personal reactions to what they have experienced and to be creative, sharing prior experiences, prior learning and their personalities. The course includes two exams, each following a week of lecture and field experiences. Independent research projects include the production of a manuscript-formatted report complete with statistical analysis of the data and a literature-based discussion of the conclusions. The combination of experiential reinforcement of concepts, abundant

  15. Modeling Evidence-Based Application: Using Team-Based Learning to Increase Higher Order Thinking in Nursing Research

    Directory of Open Access Journals (Sweden)

    Bridget Moore

    2015-06-01

    Full Text Available Nursing practice is comprised of knowledge, theory, and research [1]. Because of its impact on the profession, the appraisal of research evidence is critically important. Future nursing professionals must be introduced to the purpose and utility of nursing research, as early exposure provides an opportunity to embed evidence-based practice (EBP into clinical experiences. The AACN requires baccalaureate education to include an understanding of the research process to integrate reliable evidence to inform practice and enhance clinical judgments [1]. Although the importance of these knowledge competencies are evident to healthcare administrators and nursing leaders within the field, undergraduate students at the institution under study sometimes have difficulty understanding the relevance of nursing research to the baccalaureate prepared nurse, and struggle to grasp advanced concepts of qualitative and quantitative research design and methodologies. As undergraduate nursing students generally have not demonstrated an understanding of the relationship between theoretical concepts found within the undergraduate nursing curriculum and the practical application of these concepts in the clinical setting, the research team decided to adopt an effective pedagogical active learning strategy, team-based learning (TBL. Team-based learning shifts the traditional course design to focus on higher thinking skills to integrate desired knowledge [2]. The purpose of this paper is to discuss the impact of course design with the integration of TBL in an undergraduate nursing research course on increasing higher order thinking. [1] American Association of Colleges of Nursing, The Essentials of Baccalaureate Education for Professional Nursing Practice, Washington, DC: American Association of Colleges of Nursing, 2008. [2] B. Bloom, Taxonomy of Educational Objectives, Handbook I: Cognitive Domain, New York: McKay, 1956.

  16. Correcting Misconceptions on Electronics: Effects of a Simulation-Based Learning Environment Backed by a Conceptual Change Model

    Science.gov (United States)

    Chen, Yu-Lung; Pan, Pei-Rong; Sung, Yao-Ting; Chang, Kuo-En

    2013-01-01

    Computer simulation has significant potential as a supplementary tool for effective conceptual-change learning based on the integration of technology and appropriate instructional strategies. This study elucidates misconceptions in learning on diodes and constructs a conceptual-change learning system that incorporates…

  17. The Conceptual Mechanism for Viable Organizational Learning Based on Complex System Theory and the Viable System Model

    Science.gov (United States)

    Sung, Dia; You, Yeongmahn; Song, Ji Hoon

    2008-01-01

    The purpose of this research is to explore the possibility of viable learning organizations based on identifying viable organizational learning mechanisms. Two theoretical foundations, complex system theory and viable system theory, have been integrated to provide the rationale for building the sustainable organizational learning mechanism. The…

  18. INFLUENCE ANALYSIS OF WATERLOGGING BASED ON DEEP LEARNING MODEL IN WUHAN

    Directory of Open Access Journals (Sweden)

    Y. Pan

    2017-09-01

    Full Text Available This paper analyses a large number of factors related to the influence degree of urban waterlogging in depth, and constructs the Stack Autoencoder model to explore the relationship between the waterlogging points’ influence degree and their surrounding spatial data, which will be used to realize the comprehensive analysis in the waterlogging influence on the work and life of residents. According to the data of rainstorm waterlogging in 2016 July in Wuhan, the model is validated. The experimental results show that the model has higher accuracy than the traditional linear regression model. Based on the experimental model and waterlogging points distribution information in Wuhan over the years, the influence degree of different waterlogging points can be quantitatively described, which will be beneficial to the formulation of urban flood control measures and provide a reference for the design of city drainage pipe network.

  19. Deep learning-based fine-grained car make/model classification for visual surveillance

    Science.gov (United States)

    Gundogdu, Erhan; Parıldı, Enes Sinan; Solmaz, Berkan; Yücesoy, Veysel; Koç, Aykut

    2017-10-01

    Fine-grained object recognition is a potential computer vision problem that has been recently addressed by utilizing deep Convolutional Neural Networks (CNNs). Nevertheless, the main disadvantage of classification methods relying on deep CNN models is the need for considerably large amount of data. In addition, there exists relatively less amount of annotated data for a real world application, such as the recognition of car models in a traffic surveillance system. To this end, we mainly concentrate on the classification of fine-grained car make and/or models for visual scenarios by the help of two different domains. First, a large-scale dataset including approximately 900K images is constructed from a website which includes fine-grained car models. According to their labels, a state-of-the-art CNN model is trained on the constructed dataset. The second domain that is dealt with is the set of images collected from a camera integrated to a traffic surveillance system. These images, which are over 260K, are gathered by a special license plate detection method on top of a motion detection algorithm. An appropriately selected size of the image is cropped from the region of interest provided by the detected license plate location. These sets of images and their provided labels for more than 30 classes are employed to fine-tune the CNN model which is already trained on the large scale dataset described above. To fine-tune the network, the last two fully-connected layers are randomly initialized and the remaining layers are fine-tuned in the second dataset. In this work, the transfer of a learned model on a large dataset to a smaller one has been successfully performed by utilizing both the limited annotated data of the traffic field and a large scale dataset with available annotations. Our experimental results both in the validation dataset and the real field show that the proposed methodology performs favorably against the training of the CNN model from scratch.

  20. Devising a New Model of Demand-Based Learning Integrated with Social Networks and Analyses of its Performance

    Directory of Open Access Journals (Sweden)

    Bekim Fetaji

    2018-02-01

    Full Text Available The focus of the research study is to devise a new model for demand based learning that will be integrated with social networks such as Facebook, twitter and other. The study investigates this by reviewing the published literature and realizes a case study analyses in order to analyze the new models’ analytical perspectives of practical implementation. The study focuses on analyzing demand-based learning and investigating how it can be improved by devising a specific model that incorporates social network use. Statistical analyses of the results of the questionnaire through research of the raised questions and hypothesis showed that there is a need for introducing new models in the teaching process. The originality stands on the prologue of the social login approach to an educational environment, whereas the approach is counted as a contribution of developing a demand-based web application, which aims to modernize the educational pattern of communication, introduce the social login approach, and increase the process of knowledge transfer as well as improve learners’ performance and skills. Insights and recommendations are provided, argumented and discussed.

  1. Evaluation of different time domain peak models using extreme learning machine-based peak detection for EEG signal.

    Science.gov (United States)

    Adam, Asrul; Ibrahim, Zuwairie; Mokhtar, Norrima; Shapiai, Mohd Ibrahim; Cumming, Paul; Mubin, Marizan

    2016-01-01

    Various peak models have been introduced to detect and analyze peaks in the time domain analysis of electroencephalogram (EEG) signals. In general, peak model in the time domain analysis consists of a set of signal parameters, such as amplitude, width, and slope. Models including those proposed by Dumpala, Acir, Liu, and Dingle are routinely used to detect peaks in EEG signals acquired in clinical studies of epilepsy or eye blink. The optimal peak model is the most reliable peak detection performance in a particular application. A fair measure of performance of different models requires a common and unbiased platform. In this study, we evaluate the performance of the four different peak models using the extreme learning machine (ELM)-based peak detection algorithm. We found that the Dingle model gave the best performance, with 72 % accuracy in the analysis of real EEG data. Statistical analysis conferred that the Dingle model afforded significantly better mean testing accuracy than did the Acir and Liu models, which were in the range 37-52 %. Meanwhile, the Dingle model has no significant difference compared to Dumpala model.

  2. Model-Based Collaborative Filtering Analysis of Student Response Data: Machine-Learning Item Response Theory

    Science.gov (United States)

    Bergner, Yoav; Droschler, Stefan; Kortemeyer, Gerd; Rayyan, Saif; Seaton, Daniel; Pritchard, David E.

    2012-01-01

    We apply collaborative filtering (CF) to dichotomously scored student response data (right, wrong, or no interaction), finding optimal parameters for each student and item based on cross-validated prediction accuracy. The approach is naturally suited to comparing different models, both unidimensional and multidimensional in ability, including a…

  3. Learning Natural Selection in 4th Grade with Multi-Agent-Based Computational Models

    Science.gov (United States)

    Dickes, Amanda Catherine; Sengupta, Pratim

    2013-01-01

    In this paper, we investigate how elementary school students develop multi-level explanations of population dynamics in a simple predator-prey ecosystem, through scaffolded interactions with a multi-agent-based computational model (MABM). The term "agent" in an MABM indicates individual computational objects or actors (e.g., cars), and these…

  4. Example-Based Learning: Effects of Model Expertise in Relation to Student Expertise

    Science.gov (United States)

    Boekhout, Paul; van Gog, Tamara; van de Wiel, Margje W. J.; Gerards-Last, Dorien; Geraets, Jacques

    2010-01-01

    Background: Worked examples are very effective for novice learners. They typically present a written-out ideal (didactical) solution for learners to study. Aims: This study used worked examples of patient history taking in physiotherapy that presented a "non"-didactical solution (i.e., based on actual performance). The effects of model expertise…

  5. PENGEMBANGAN MODEL COMPUTER-BASED E-LEARNING UNTUK MENINGKATKAN KEMAMPUAN HIGH ORDER MATHEMATICAL THINKING SISWA SMA

    OpenAIRE

    Jarnawi Afgani Dahlan; Yaya Sukjaya Kusumah; Mr Heri Sutarno

    2011-01-01

    The focus of this research is on the development of mathematics teaching and learning activity which is based on the application of computer software. The aim of research is as follows : 1) to identify some mathematics topics which feasible to be presented by computer-based e-learning, 2) design, develop, and implement computer-based e-learning on mathematics, and 3) analyze the impact of computer-based e-learning in the enhancement of SMA students’ high order mathematical thinking. All activ...

  6. The Effect of Scientific Inquiry Learning Model Based on Conceptual Change on Physics Cognitive Competence and Science Process Skill (SPS) of Students at Senior High School

    Science.gov (United States)

    Sahhyar; Nst, Febriani Hastini

    2017-01-01

    The purpose of this research was to analyze the physics cognitive competence and science process skill of students using scientific inquiry learning model based on conceptual change better than using conventional learning. The research type was quasi experiment and two group pretest-posttest designs were used in this study. The sample were Class…

  7. A Web-Based Learning Support System for Inquiry-Based Learning

    Science.gov (United States)

    Kim, Dong Won; Yao, Jingtao

    The emergence of the Internet and Web technology makes it possible to implement the ideals of inquiry-based learning, in which students seek truth, information, or knowledge by questioning. Web-based learning support systems can provide a good framework for inquiry-based learning. This article presents a study on a Web-based learning support system called Online Treasure Hunt. The Web-based learning support system mainly consists of a teaching support subsystem, a learning support subsystem, and a treasure hunt game. The teaching support subsystem allows instructors to design their own inquiry-based learning environments. The learning support subsystem supports students' inquiry activities. The treasure hunt game enables students to investigate new knowledge, develop ideas, and review their findings. Online Treasure Hunt complies with a treasure hunt model. The treasure hunt model formalizes a general treasure hunt game to contain the learning strategies of inquiry-based learning. This Web-based learning support system empowered with the online-learning game and founded on the sound learning strategies furnishes students with the interactive and collaborative student-centered learning environment.

  8. Susan Loucks-Horsley learning model in light pollution theme: based on a new taxonomy for science education

    International Nuclear Information System (INIS)

    Liliawati, W; Utama, J A; Fauziah, H

    2016-01-01

    The curriculum in Indonesia recommended that science teachers in the elementary and intermediate schools should have interdisciplinary ability in science. However, integrated learning still has not been implemented optimally. This research is designing and applying integrated learning with Susan Loucks-Horsley model in light pollution theme. It can be showed how the student's achievements based on new taxonomy of science education with five domains: knowing and understanding, science process skill, creativity, attitudinal and connecting and applying. This research use mixed methods with concurrent embedded design. The subject is grade 8 of junior high school students in Bandung as many as 27 students. The Instrument have been employed has 28 questions test mastery of concepts, observations sheet and moral dilemma test. The result shows that integrated learning with model Susan Loucks-Horsley is able to increase student's achievement and positive characters on light pollution theme. As the results are the average normalized gain of knowing and understanding domain reach in lower category, the average percentage of science process skill domain reach in good category, the average percentage of creativity and connecting domain reach respectively in good category and attitudinal domain the average percentage is over 75% in moral knowing and moral feeling. (paper)

  9. Susan Loucks-Horsley learning model in light pollution theme: based on a new taxonomy for science education

    Science.gov (United States)

    Liliawati, W.; Utama, J. A.; Fauziah, H.

    2016-08-01

    The curriculum in Indonesia recommended that science teachers in the elementary and intermediate schools should have interdisciplinary ability in science. However, integrated learning still has not been implemented optimally. This research is designing and applying integrated learning with Susan Loucks-Horsley model in light pollution theme. It can be showed how the student's achievements based on new taxonomy of science education with five domains: knowing & understanding, science process skill, creativity, attitudinal and connecting & applying. This research use mixed methods with concurrent embedded design. The subject is grade 8 of junior high school students in Bandung as many as 27 students. The Instrument have been employed has 28 questions test mastery of concepts, observations sheet and moral dilemma test. The result shows that integrated learning with model Susan Loucks-Horsley is able to increase student's achievement and positive characters on light pollution theme. As the results are the average normalized gain of knowing and understanding domain reach in lower category, the average percentage of science process skill domain reach in good category, the average percentage of creativity and connecting domain reach respectively in good category and attitudinal domain the average percentage is over 75% in moral knowing and moral feeling.

  10. Theories and models about learning in connected and ubiquitous environments. Bases for a new theoretical model from a critical vision of “connectivism”

    Directory of Open Access Journals (Sweden)

    Miguel ZAPATA-ROS

    2015-04-01

    Full Text Available This paper aims at setting the bases for the construction of a theoretical model of learning and of elaboration of knowledge, within connected learning environments. The starting point is a critical view of connectivism, and a premise: the study and recognition of existing theories, since their scope is still under development as regards their potentialities and affordances when applied in social, ubiquitous environments. The paper also includes reflections and a hypothesis on the causes that underlie in the origin of connectivism in its actual stage of development in the Information and Knowledge Society, in order to use the obtained conclusions as the bases of a new model, at a later phase.

  11. The development and evaluation of a 'blended' enquiry based learning model for mental health nursing students: "making your experience count".

    Science.gov (United States)

    Rigby, Lindsay; Wilson, Ian; Baker, John; Walton, Tim; Price, Owen; Dunne, Kate; Keeley, Philip

    2012-04-01

    To meet the demands required for safe and effective care, nurses must be able to integrate theoretical knowledge with clinical practice (Kohen and Lehman, 2008; Polit and Beck, 2008; Shirey, 2006). This should include the ability to adapt research in response to changing clinical environments and the changing needs of service users. It is through reflective practice that students develop their clinical reasoning and evaluation skills to engage in this process. This paper aims to describe the development, implementation and evaluation of a project designed to provide a structural approach to the recognition and resolution of clinical, theoretical and ethical dilemmas identified by 3rd year undergraduate mental health nursing students. This is the first paper to describe the iterative process of developing a 'blended' learning model which provides students with an opportunity to experience the process of supervision and to become more proficient in using information technology to develop and maintain their clinical skills. Three cohorts of student nurses were exposed to various combinations of face to face group supervision and a virtual learning environment (VLE) in order to apply their knowledge of good practice guidelines and evidenced-based practice to identified clinical issues. A formal qualitative evaluation using independently facilitated focus groups was conducted with each student cohort and thematically analysed (Miles & Huberman, 1994). The themes that emerged were: relevance to practice; facilitation of independent learning; and the discussion of clinical issues. The results of this study show that 'blending' face-to-face groups with an e-learning component was the most acceptable and effective form of delivery which met the needs of students' varied learning styles. Additionally, students reported that they were more aware of the importance of clinical supervision and of their role as supervisees. Copyright © 2011 Elsevier Ltd. All rights reserved.

  12. Effects of gestures on older adults' learning from video-based models

    NARCIS (Netherlands)

    Ouwehand, Kim; van Gog, Tamara|info:eu-repo/dai/nl/294304975; Paas, Fred

    2015-01-01

    This study investigated whether the positive effects of gestures on learning by decreasing working memory load, found in children and young adults, also apply to older adults, who might especially benefit from gestures given memory deficits associated with aging. Participants learned a

  13. Study of the Entrepreneurship in Universities as Learning Organization Based on Senge Model

    Science.gov (United States)

    Nejad, Bahareh Azizi; Abbaszadeh, Mir Mohammad Seiied; Hassani, Mohammad; Bernousi, Iraj

    2012-01-01

    Learning organization and entrepreneurship are the most important issues that are focused on different themes in management. The purpose of present research was to study the relationship between learning organization elements and entrepreneurship among academic faculty members of the West Azarbaijan State Universities. The research method was…

  14. Determinants of Intention to Use eLearning Based on the Technology Acceptance Model

    Science.gov (United States)

    Punnoose, Alfie Chacko

    2012-01-01

    The purpose of this study was to find some of the predominant factors that determine the intention of students to use eLearning in the future. Since eLearning is not just a technology acceptance decision but also involves cognition, this study extended its search beyond the normal technology acceptance variables into variables that could affect…

  15. Integrating Model-Based Learning and Animations for Enhancing Students' Understanding of Proteins Structure and Function

    Science.gov (United States)

    Barak, Miri; Hussein-Farraj, Rania

    2013-01-01

    This paper describes a study conducted in the context of chemistry education reforms in Israel. The study examined a new biochemistry learning unit that was developed to promote in-depth understanding of 3D structures and functions of proteins and nucleic acids. Our goal was to examine whether, and to what extent teaching and learning via…

  16. Sectoral patterns of interactive learning : an empirical exploration using an extended resource based model

    NARCIS (Netherlands)

    Meeus, M.T.H.; Oerlemans, L.A.G.; Hage, J.

    1999-01-01

    This paper pursues the development of a theoretical framework that explains interactive learning between innovating firms and external actors in the knowledge infrastructure and the production chain. The research question is: what kinds of factors explain interactive learning of innovating firms

  17. Librarian-Teacher Partnerships for Inquiry Learning: Measures of Effectiveness for a Practice-Based Model of Professional Development

    Directory of Open Access Journals (Sweden)

    Joyce Yukawa

    2009-06-01

    Full Text Available Objective – This study analyzed the effects of a practice-based model of professional development on the teaching and collaborative practices of 9 teams of librarians and teachers, who created and implemented units of inquiry-focused study with K-12 students during a yearlong course. The authors describe how the collection and analysis of evidence guided the development team in the formative and summative evaluations of the outcomes of the professional development, as well as the long-term results of participation in this initiative.Methods – The authors used an interpretive, participative approach. The first author was the external reviewer for the project; the second author headed the development team and served as a participant-observer. Triangulated data were collected from participants in the form of learning logs, discussion board postings, interviews, questionnaires, and learning portfolios consisting of unit and lesson plans and student work samples with critiques. Data were also collected from the professional development designers in the form of meeting notes, responses to participants, interviews, and course documents. For two years following the end of the formal course, the authors also conducted follow-up email correspondence with all teams and site visits with six teams to determine sustained or expanded implementation of inquiry-focused, collaborative curriculum development. Results – The practice-based approach to professional development required continual modification of the course design and timely, individualized mentoring and feedback, based on analysis and co-reflection by the developers on the evidence gathered through participant logs, reports, and school site visits. Modeling the inquiry process in their own course development work and making this process transparent to the participating community were essential to improvement. Course participants reported beneficial results in both immediate and long-term changes

  18. Drawing-to-learn: a framework for using drawings to promote model-based reasoning in biology.

    Science.gov (United States)

    Quillin, Kim; Thomas, Stephen

    2015-03-02

    The drawing of visual representations is important for learners and scientists alike, such as the drawing of models to enable visual model-based reasoning. Yet few biology instructors recognize drawing as a teachable science process skill, as reflected by its absence in the Vision and Change report's Modeling and Simulation core competency. Further, the diffuse research on drawing can be difficult to access, synthesize, and apply to classroom practice. We have created a framework of drawing-to-learn that defines drawing, categorizes the reasons for using drawing in the biology classroom, and outlines a number of interventions that can help instructors create an environment conducive to student drawing in general and visual model-based reasoning in particular. The suggested interventions are organized to address elements of affect, visual literacy, and visual model-based reasoning, with specific examples cited for each. Further, a Blooming tool for drawing exercises is provided, as are suggestions to help instructors address possible barriers to implementing and assessing drawing-to-learn in the classroom. Overall, the goal of the framework is to increase the visibility of drawing as a skill in biology and to promote the research and implementation of best practices. © 2015 K. Quillin and S. Thomas. CBE—Life Sciences Education © 2015 The American Society for Cell Biology. This article is distributed by The American Society for Cell Biology under license from the author(s). It is available to the public under an Attribution–Noncommercial–Share Alike 3.0 Unported Creative Commons License (http://creativecommons.org/licenses/by-nc-sa/3.0).

  19. Reliability assessment of a manual-based procedure towards learning curve modeling and fmea analysis

    Directory of Open Access Journals (Sweden)

    Gustavo Rech

    2013-03-01

    Full Text Available Separation procedures in drug Distribution Centers (DC are manual-based activities prone to failures such as shipping exchanged, expired or broken drugs to the customer. Two interventions seem as promising in improving the reliability in the separation procedure: (i selection and allocation of appropriate operators to the procedure, and (ii analysis of potential failure modes incurred by selected operators. This article integrates Learning Curves (LC and FMEA (Failure Mode and Effect Analysis aimed at reducing the occurrence of failures in the manual separation of a drug DC. LCs parameters enable generating an index to identify the recommended operators to perform the procedures. The FMEA is then applied to the separation procedure carried out by the selected operators in order to identify failure modes. It also deployed the traditional FMEA severity index into two sub-indexes related to financial issues and damage to company´s image in order to characterize failures severity. When applied to a drug DC, the proposed method significantly reduced the frequency and severity of failures in the separation procedure.

  20. E-learning optimization: the relative and combined effects of mental practice and modeling on enhanced podcast-based learning-a randomized controlled trial.

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P; LeBlanc, Vicki R

    2016-10-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced podcasts. Sixty-three medical students were randomised to one of four versions of an airway management enhanced podcast: (1) control: narrated presentation; (2) modeling: narration with video demonstration of skills; (3) mental practice: narrated presentation with guided mental practice; (4) combined: modeling and mental practice. One week later, students managed a manikin-based simulated airway crisis. Knowledge acquisition was assessed by baseline and retention multiple-choice quizzes. Two blinded raters assessed all videos obtained from simulated crises to measure the students' skills using a key-elements scale, critical error checklist, and the Ottawa global rating scale (GRS). Baseline knowledge was not different between all four groups (p = 0.65). One week later, knowledge retention was significantly higher for (1) both the mental practice and modeling group than the control group (p = 0.01; p = 0.01, respectively) and (2) the combined mental practice and modeling group compared to all other groups (all ps = 0.01). Regarding skills acquisition, the control group significantly under-performed in comparison to all other groups on the key-events scale (all ps ≤ 0.05), the critical error checklist (all ps ≤ 0.05), and the Ottawa GRS (all ps ≤ 0.05). The combination of mental practice and modeling led to greater improvement on the key events checklist (p = 0.01) compared to either strategy alone. However, the combination of the two strategies did not result in any further learning gains on the two other measures of clinical performance (all ps > 0.05). The effectiveness of enhanced podcasts for

  1. Translation of an Action Learning Collaborative Model Into a Community-Based Intervention to Promote Physical Activity and Healthy Eating.

    Science.gov (United States)

    Schifferdecker, Karen E; Adachi-Mejia, Anna M; Butcher, Rebecca L; O'Connor, Sharon; Li, Zhigang; Bazos, Dorothy A

    2016-01-01

    Action Learning Collaboratives (ALCs), whereby teams apply quality improvement (QI) tools and methods, have successfully improved patient care delivery and outcomes. We adapted and tested the ALC model as a community-based obesity prevention intervention focused on physical activity and healthy eating. The intervention used QI tools (e.g., progress monitoring) and team-based activities and was implemented in three communities through nine monthly meetings. To assess process and outcomes, we used a longitudinal repeated-measures and mixed-methods triangulation approach with a quasi-experimental design including objective measures at three time points. Most of the 97 participants were female (85.4%), White (93.8%), and non-Hispanic/Latino (95.9%). Average age was 52 years; 28.0% had annual household income of $20,000 or less; and mean body mass index was 35. Through mixed-effects models, we found some physical activity outcomes improved. Other outcomes did not significantly change. Although participants favorably viewed the QI tools, components of the QI process such as sharing goals and data on progress in teams and during meetings were limited. Participants' requests for more education or activities around physical activity and healthy eating, rather than progress monitoring and data sharing required for QI activities, challenged ALC model implementation. An ALC model for community-based obesity prevention may be more effective when applied to preexisting teams in community-based organizations. © 2015 Society for Public Health Education.

  2. Perspective: Web-based machine learning models for real-time screening of thermoelectric materials properties

    Science.gov (United States)

    Gaultois, Michael W.; Oliynyk, Anton O.; Mar, Arthur; Sparks, Taylor D.; Mulholland, Gregory J.; Meredig, Bryce

    2016-05-01

    The experimental search for new thermoelectric materials remains largely confined to a limited set of successful chemical and structural families, such as chalcogenides, skutterudites, and Zintl phases. In principle, computational tools such as density functional theory (DFT) offer the possibility of rationally guiding experimental synthesis efforts toward very different chemistries. However, in practice, predicting thermoelectric properties from first principles remains a challenging endeavor [J. Carrete et al., Phys. Rev. X 4, 011019 (2014)], and experimental researchers generally do not directly use computation to drive their own synthesis efforts. To bridge this practical gap between experimental needs and computational tools, we report an open machine learning-based recommendation engine (http://thermoelectrics.citrination.com) for materials researchers that suggests promising new thermoelectric compositions based on pre-screening about 25 000 known materials and also evaluates the feasibility of user-designed compounds. We show this engine can identify interesting chemistries very different from known thermoelectrics. Specifically, we describe the experimental characterization of one example set of compounds derived from our engine, RE12Co5Bi (RE = Gd, Er), which exhibits surprising thermoelectric performance given its unprecedentedly high loading with metallic d and f block elements and warrants further investigation as a new thermoelectric material platform. We show that our engine predicts this family of materials to have low thermal and high electrical conductivities, but modest Seebeck coefficient, all of which are confirmed experimentally. We note that the engine also predicts materials that may simultaneously optimize all three properties entering into zT; we selected RE12Co5Bi for this study due to its interesting chemical composition and known facile synthesis.

  3. E-Learning Optimization: The Relative and Combined Effects of Mental Practice and Modeling on Enhanced Podcast-Based Learning--A Randomized Controlled Trial

    Science.gov (United States)

    Alam, Fahad; Boet, Sylvain; Piquette, Dominique; Lai, Anita; Perkes, Christopher P.; LeBlanc, Vicki R.

    2016-01-01

    Enhanced podcasts increase learning, but evidence is lacking on how they should be designed to optimize their effectiveness. This study assessed the impact two learning instructional design methods (mental practice and modeling), either on their own or in combination, for teaching complex cognitive medical content when incorporated into enhanced…

  4. Modelling and Optimizing Mathematics Learning in Children

    Science.gov (United States)

    Käser, Tanja; Busetto, Alberto Giovanni; Solenthaler, Barbara; Baschera, Gian-Marco; Kohn, Juliane; Kucian, Karin; von Aster, Michael; Gross, Markus

    2013-01-01

    This study introduces a student model and control algorithm, optimizing mathematics learning in children. The adaptive system is integrated into a computer-based training system for enhancing numerical cognition aimed at children with developmental dyscalculia or difficulties in learning mathematics. The student model consists of a dynamic…

  5. A Trial and Perceptions Assessment of APP-Based Flipped Classroom Teaching Model for Medical Students in Learning Immunology in China

    Directory of Open Access Journals (Sweden)

    Xingming Ma

    2018-04-01

    Full Text Available The application-based flipped classroom (APP-FC is an innovative teaching-learning model that has not been applied and assessed in basic medical curricula teaching in China. The aim of this investigation is to assess students’ perceptions to the APP-based flipped classroom (APP-FC teaching model in an immunology course. The data of this study were collected from second-year medical students (n = 92 at Lanzhou University. One class (n = 50, as a control group, was offered lecture-based learning (LBL, while the other class (n = 42, as the APP-FC group, was given lecture-based instruction and the APP-FC teaching model during September–November 2017. Afterward, the perceptions of students on APP-FC teaching model were evaluated using questionnaires. Students responded that APP-FC improves their motivation (83% and interest in learning immunology (81%, as well as their self-directed learning skills (81%. Compared to the traditional lecture-based instruction, the APP-FC noticeably improved students’ motivation in learning (P = 0.011, self-directed learn skills (P = 0.001, memory abilities (P = 0.009, and problem-solving abilities (P = 0.010. Most medical students’ scores (60% in the final examination were more than 80 points after implementing an APP-FC model as compared to the control group (40%. The majority of students (70% preferred the APP-FC teaching approach over traditional lecture-based pedagogy. The implementation of the APP-FC teaching model could improve students’ learning motivation, self-directed learn skills, and problem-solving abilities, which is a preferable teaching model for medical immunology courses in China.

  6. AN EXTENDED REINFORCEMENT LEARNING MODEL OF BASAL GANGLIA TO UNDERSTAND THE CONTRIBUTIONS OF SEROTONIN AND DOPAMINE IN RISK-BASED DECISION MAKING, REWARD PREDICTION, AND PUNISHMENT LEARNING

    Directory of Open Access Journals (Sweden)

    Pragathi Priyadharsini Balasubramani

    2014-04-01

    Full Text Available Although empirical and neural studies show that serotonin (5HT plays many functional roles in the brain, prior computational models mostly focus on its role in behavioral inhibition. In this study, we present a model of risk based decision making in a modified Reinforcement Learning (RL-framework. The model depicts the roles of dopamine (DA and serotonin (5HT in Basal Ganglia (BG. In this model, the DA signal is represented by the temporal difference error (δ, while the 5HT signal is represented by a parameter (α that controls risk prediction error. This formulation that accommodates both 5HT and DA reconciles some of the diverse roles of 5HT particularly in connection with the BG system. We apply the model to different experimental paradigms used to study the role of 5HT: 1 Risk-sensitive decision making, where 5HT controls risk assessment, 2 Temporal reward prediction, where 5HT controls time-scale of reward prediction, and 3 Reward/Punishment sensitivity, in which the punishment prediction error depends on 5HT levels. Thus the proposed integrated RL model reconciles several existing theories of 5HT and DA in the BG.

  7. Development and assessment of a lysophospholipid-based deep learning model to discriminate geographical origins of white rice.

    Science.gov (United States)

    Long, Nguyen Phuoc; Lim, Dong Kyu; Mo, Changyeun; Kim, Giyoung; Kwon, Sung Won

    2017-08-17

    Geographical origin determination of white rice has become the major issue of food industry. However, there is still lack of a high-throughput method for rapidly and reproducibly differentiating the geographical origins of commercial white rice. In this study, we developed a method that employed lipidomics and deep learning to discriminate white rice from Korea to China. A total of 126 white rice of 30 cultivars from different regions were utilized for the method development and validation. By using direct infusion-mass spectrometry-based targeted lipidomics, 17 lysoglycerophospholipids were simultaneously characterized within minutes per sample. Unsupervised data exploration showed a noticeable overlap of white rice between two countries. In addition, lysophosphatidylcholines (lysoPCs) were prominent in white rice from Korea while lysophosphatidylethanolamines (lysoPEs) were enriched in white rice from China. A deep learning prediction model was built using 2014 white rice and validated using two different batches of 2015 white rice. The model accurately discriminated white rice from two countries. Among 10 selected predictors, lysoPC(18:2), lysoPC(14:0), and lysoPE(16:0) were the three most important features. Random forest and gradient boosting machine models also worked well in this circumstance. In conclusion, this study provides an architecture for high-throughput classification of white rice from different geographical origins.

  8. Student Modeling and Machine Learning

    OpenAIRE

    Sison , Raymund; Shimura , Masamichi

    1998-01-01

    After identifying essential student modeling issues and machine learning approaches, this paper examines how machine learning techniques have been used to automate the construction of student models as well as the background knowledge necessary for student modeling. In the process, the paper sheds light on the difficulty, suitability and potential of using machine learning for student modeling processes, and, to a lesser extent, the potential of using student modeling techniques in machine le...

  9. Error modeling for surrogates of dynamical systems using machine learning: Machine-learning-based error model for surrogates of dynamical systems

    International Nuclear Information System (INIS)

    Trehan, Sumeet; Carlberg, Kevin T.; Durlofsky, Louis J.

    2017-01-01

    A machine learning–based framework for modeling the error introduced by surrogate models of parameterized dynamical systems is proposed. The framework entails the use of high-dimensional regression techniques (eg, random forests, and LASSO) to map a large set of inexpensively computed “error indicators” (ie, features) produced by the surrogate model at a given time instance to a prediction of the surrogate-model error in a quantity of interest (QoI). This eliminates the need for the user to hand-select a small number of informative features. The methodology requires a training set of parameter instances at which the time-dependent surrogate-model error is computed by simulating both the high-fidelity and surrogate models. Using these training data, the method first determines regression-model locality (via classification or clustering) and subsequently constructs a “local” regression model to predict the time-instantaneous error within each identified region of feature space. We consider 2 uses for the resulting error model: (1) as a correction to the surrogate-model QoI prediction at each time instance and (2) as a way to statistically model arbitrary functions of the time-dependent surrogate-model error (eg, time-integrated errors). We then apply the proposed framework to model errors in reduced-order models of nonlinear oil-water subsurface flow simulations, with time-varying well-control (bottom-hole pressure) parameters. The reduced-order models used in this work entail application of trajectory piecewise linearization in conjunction with proper orthogonal decomposition. Moreover, when the first use of the method is considered, numerical experiments demonstrate consistent improvement in accuracy in the time-instantaneous QoI prediction relative to the original surrogate model, across a large number of test cases. When the second use is considered, results show that the proposed method provides accurate statistical predictions of the time- and well

  10. The (kinetic) theory of active particles applied to learning dynamics. Comment on "Collective learning modeling based on the kinetic theory of active particles" by D. Burini et al.

    Science.gov (United States)

    Nieto, J.

    2016-03-01

    The learning phenomena, their complexity, concepts, structure, suitable theories and models, have been extensively treated in the mathematical literature in the last century, and [4] contains a very good introduction to the literature describing the many approaches and lines of research developed about them. Two main schools have to be pointed out [5] in order to understand the two -not exclusive- kinds of existing models: the stimulus sampling models and the stochastic learning models. Also [6] should be mentioned as a survey where two methods of learning are pointed out, the cognitive and the social, and where the knowledge looks like a mathematical unknown. Finally, as the authors do, we refer to the works [9,10], where the concept of population thinking was introduced and which motivate the game theory rules as a tool (both included in [4] to develop their theory) and [7], where the ideas of developing a mathematical kinetic theory of perception and learning were proposed.

  11. Learning Markov Decision Processes for Model Checking

    DEFF Research Database (Denmark)

    Mao, Hua; Chen, Yingke; Jaeger, Manfred

    2012-01-01

    . The proposed learning algorithm is adapted from algorithms for learning deterministic probabilistic finite automata, and extended to include both probabilistic and nondeterministic transitions. The algorithm is empirically analyzed and evaluated by learning system models of slot machines. The evaluation......Constructing an accurate system model for formal model verification can be both resource demanding and time-consuming. To alleviate this shortcoming, algorithms have been proposed for automatically learning system models based on observed system behaviors. In this paper we extend the algorithm...... on learning probabilistic automata to reactive systems, where the observed system behavior is in the form of alternating sequences of inputs and outputs. We propose an algorithm for automatically learning a deterministic labeled Markov decision process model from the observed behavior of a reactive system...

  12. Distance learning, problem based learning and dynamic knowledge networks.

    Science.gov (United States)

    Giani, U; Martone, P

    1998-06-01

    This paper is an attempt to develop a distance learning model grounded upon a strict integration of problem based learning (PBL), dynamic knowledge networks (DKN) and web tools, such as hypermedia documents, synchronous and asynchronous communication facilities, etc. The main objective is to develop a theory of distance learning based upon the idea that learning is a highly dynamic cognitive process aimed at connecting different concepts in a network of mutually supporting concepts. Moreover, this process is supposed to be the result of a social interaction that has to be facilitated by the web. The model was tested by creating a virtual classroom of medical and nursing students and activating a learning session on the concept of knowledge representation in health sciences.

  13. Model-based online optimisation. Pt. 1: active learning; Modellbasierte Online-Optimierung moderner Verbrennungsmotoren. T. 1: Aktives Lernen

    Energy Technology Data Exchange (ETDEWEB)

    Poland, J.; Knoedler, K.; Zell, A. [Tuebingen Univ. (Germany). Lehrstuhl fuer Rechnerarchitektur; Fleischhauer, T.; Mitterer, A.; Ullmann, S. [BMW Group (Germany)

    2003-05-01

    This two-part article presents the model-based optimisation algorithm ''mbminimize''. It was developed in a corporate project of the University Tuebingen and the BMW Group for the purpose of optimising internal combustion engines online on the engine test bed. The first part concentrates on the basic algorithmic design, as well as on modelling, experimental design and active learning. The second part will discuss strategies for dealing with limits such as knocking. (orig.) [German] Dieser zweiteilige Beitrag stellt den modellbasierten Optimierungsalgorithmus ''mbminimize'' vor, der in Kooperation von der Universitaet Tuebingen und der BMW Group fuer die Online-Optimierung von Verbrennungsmotoren entwickelt wurde. Der vorliegende erste Teil konzentriert sich auf das grundlegende algorithmische Design, auf Modellierung, Versuchsplanung und aktives Lernen. Der zweite Teil diskutiert Strategien zur Behandlung von Limits wie Motorklopfen.

  14. Quantitative Outline-based Shape Analysis and Classification of Planetary Craterforms using Supervised Learning Models

    Science.gov (United States)

    Slezak, Thomas Joseph; Radebaugh, Jani; Christiansen, Eric

    2017-10-01

    The shapes of craterform morphology on planetary surfaces provides rich information about their origins and evolution. While morphologic information provides rich visual clues to geologic processes and properties, the ability to quantitatively communicate this information is less easily accomplished. This study examines the morphology of craterforms using the quantitative outline-based shape methods of geometric morphometrics, commonly used in biology and paleontology. We examine and compare landforms on planetary surfaces using shape, a property of morphology that is invariant to translation, rotation, and size. We quantify the shapes of paterae on Io, martian calderas, terrestrial basaltic shield calderas, terrestrial ash-flow calderas, and lunar impact craters using elliptic Fourier analysis (EFA) and the Zahn and Roskies (Z-R) shape function, or tangent angle approach to produce multivariate shape descriptors. These shape descriptors are subjected to multivariate statistical analysis including canonical variate analysis (CVA), a multiple-comparison variant of discriminant analysis, to investigate the link between craterform shape and classification. Paterae on Io are most similar in shape to terrestrial ash-flow calderas and the shapes of terrestrial basaltic shield volcanoes are most similar to martian calderas. The shapes of lunar impact craters, including simple, transitional, and complex morphology, are classified with a 100% rate of success in all models. Multiple CVA models effectively predict and classify different craterforms using shape-based identification and demonstrate significant potential for use in the analysis of planetary surfaces.

  15. Soft object deformation monitoring and learning for model-based robotic hand manipulation.

    Science.gov (United States)

    Cretu, Ana-Maria; Payeur, Pierre; Petriu, Emil M

    2012-06-01

    This paper discusses the design and implementation of a framework that automatically extracts and monitors the shape deformations of soft objects from a video sequence and maps them with force measurements with the goal of providing the necessary information to the controller of a robotic hand to ensure safe model-based deformable object manipulation. Measurements corresponding to the interaction force at the level of the fingertips and to the position of the fingertips of a three-finger robotic hand are associated with the contours of a deformed object tracked in a series of images using neural-network approaches. The resulting model captures the behavior of the object and is able to predict its behavior for previously unseen interactions without any assumption on the object's material. The availability of such models can contribute to the improvement of a robotic hand controller, therefore allowing more accurate and stable grasp while providing more elaborate manipulation capabilities for deformable objects. Experiments performed for different objects, made of various materials, reveal that the method accurately captures and predicts the object's shape deformation while the object is submitted to external forces applied by the robot fingers. The proposed method is also fast and insensitive to severe contour deformations, as well as to smooth changes in lighting, contrast, and background.

  16. Case study method and problem-based learning: utilizing the pedagogical model of progressive complexity in nursing education.

    Science.gov (United States)

    McMahon, Michelle A; Christopher, Kimberly A

    2011-08-19

    As the complexity of health care delivery continues to increase, educators are challenged to determine educational best practices to prepare BSN students for the ambiguous clinical practice setting. Integrative, active, and student-centered curricular methods are encouraged to foster student ability to use clinical judgment for problem solving and informed clinical decision making. The proposed pedagogical model of progressive complexity in nursing education suggests gradually introducing students to complex and multi-contextual clinical scenarios through the utilization of case studies and problem-based learning activities, with the intention to transition nursing students into autonomous learners and well-prepared practitioners at the culmination of a nursing program. Exemplar curricular activities are suggested to potentiate student development of a transferable problem solving skill set and a flexible knowledge base to better prepare students for practice in future novel clinical experiences, which is a mutual goal for both educators and students.

  17. Motion Learning Based on Bayesian Program Learning

    Directory of Open Access Journals (Sweden)

    Cheng Meng-Zhen

    2017-01-01

    Full Text Available The concept of virtual human has been highly anticipated since the 1980s. By using computer technology, Human motion simulation could generate authentic visual effect, which could cheat human eyes visually. Bayesian Program Learning train one or few motion data, generate new motion data by decomposing and combining. And the generated motion will be more realistic and natural than the traditional one.In this paper, Motion learning based on Bayesian program learning allows us to quickly generate new motion data, reduce workload, improve work efficiency, reduce the cost of motion capture, and improve the reusability of data.

  18. Development Instrument’s Learning of Physics Through Scientific Inquiry Model Based Batak Culture to Improve Science Process Skill and Student’s Curiosity

    Science.gov (United States)

    Nasution, Derlina; Syahreni Harahap, Putri; Harahap, Marabangun

    2018-03-01

    This research aims to: (1) developed a instrument’s learning (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) of physics learning through scientific inquiry learning model based Batak culture to achieve skills improvement process of science students and the students’ curiosity; (2) describe the quality of the result of develop instrument’s learning in high school using scientific inquiry learning model based Batak culture (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) to achieve the science process skill improvement of students and the student curiosity. This research is research development. This research developed a instrument’s learning of physics by using a development model that is adapted from the development model Thiagarajan, Semmel, and Semmel. The stages are traversed until retrieved a valid physics instrument’s learning, practical, and effective includes :(1) definition phase, (2) the planning phase, and (3) stages of development. Test performed include expert test/validation testing experts, small groups, and test classes is limited. Test classes are limited to do in SMAN 1 Padang Bolak alternating on a class X MIA. This research resulted in: 1) the learning of physics static fluid material specially for high school grade 10th consisted of (lesson plan, worksheet, student’s book, teacher’s guide book, and instrument test) and quality worthy of use in the learning process; 2) each component of the instrument’s learning meet the criteria have valid learning, practical, and effective way to reach the science process skill improvement and curiosity in students.

  19. Andragogical Modeling and the Success of the "EMPACTS" project-based learning model in the STEM disciplines: A decade of growth and learner success in the 2Y College Learning Environment.

    Science.gov (United States)

    Phillips, C. D.; Thomason, R.; Galloway, M.; Sorey, N.; Stidham, L.; Torgerson, M.

    2014-12-01

    EMPACTS (Educationally Managed Projects Advancing Curriculum, Technology/Teamwork and Service) is a project-based, adult learning modelthat is designed to enhance learning of course content through real-world application and problem solving self directed and collaborative learning use of technology service to the community EMPACTS students are self-directed in their learning, often working in teams to develop, implement, report and present final project results. EMPACTS faculty use community based projects to increase deeper learning of course content through "real-world" service experiences. Learners develop personal and interpersonal work and communication skills as they plan, execute and complete project goals together. Technology is used as a tool to solve problems and to publish the products of their learning experiences. Courses across a broad STEM curriculum integrate the EMPACTS project experience into the overall learning outcomes as part of the learning college mission of preparing 2Y graduates for future academic and/or workforce success. Since the program began in 2005, there have been over 200 completed projects/year. Student driven successes have led to the establishment of an EMPACTS Technology Corp, which is funded through scholarship and allows EMPACTS learners the opportunity to serve and learn from one another as "peer instructors." Engineering and 3D graphic design teams have written technology proposals and received funding for 3D printing replication projects, which have benefited the college as a whole through grant opportunities tied to these small scale successes. EMPACTS students engage in a variety of outreachprojects with area schools as they share the successes and joys of self directed, inquiry, project based learning. The EMPACTS Program has successfully trained faculty and students in the implementation of the model and conduct semester to semester and once a year workshops for college and K-12 faculty, who are interested in

  20. Visual Perceptual Learning and Models.

    Science.gov (United States)

    Dosher, Barbara; Lu, Zhong-Lin

    2017-09-15

    Visual perceptual learning through practice or training can significantly improve performance on visual tasks. Originally seen as a manifestation of plasticity in the primary visual cortex, perceptual learning is more readily understood as improvements in the function of brain networks that integrate processes, including sensory representations, decision, attention, and reward, and balance plasticity with system stability. This review considers the primary phenomena of perceptual learning, theories of perceptual learning, and perceptual learning's effect on signal and noise in visual processing and decision. Models, especially computational models, play a key role in behavioral and physiological investigations of the mechanisms of perceptual learning and for understanding, predicting, and optimizing human perceptual processes, learning, and performance. Performance improvements resulting from reweighting or readout of sensory inputs to decision provide a strong theoretical framework for interpreting perceptual learning and transfer that may prove useful in optimizing learning in real-world applications.

  1. A multiplicative reinforcement learning model capturing learning dynamics and interindividual variability in mice

    OpenAIRE

    Bathellier, Brice; Tee, Sui Poh; Hrovat, Christina; Rumpel, Simon

    2013-01-01

    Learning speed can strongly differ across individuals. This is seen in humans and animals. Here, we measured learning speed in mice performing a discrimination task and developed a theoretical model based on the reinforcement learning framework to account for differences between individual mice. We found that, when using a multiplicative learning rule, the starting connectivity values of the model strongly determine the shape of learning curves. This is in contrast to current learning models ...

  2. A machine learning model to determine the accuracy of variant calls in capture-based next generation sequencing.

    Science.gov (United States)

    van den Akker, Jeroen; Mishne, Gilad; Zimmer, Anjali D; Zhou, Alicia Y

    2018-04-17

    Next generation sequencing (NGS) has become a common technology for clinical genetic tests. The quality of NGS calls varies widely and is influenced by features like reference sequence characteristics, read depth, and mapping accuracy. With recent advances in NGS technology and software tools, the majority of variants called using NGS alone are in fact accurate and reliable. However, a small subset of difficult-to-call variants that still do require orthogonal confirmation exist. For this reason, many clinical laboratories confirm NGS results using orthogonal technologies such as Sanger sequencing. Here, we report the development of a deterministic machine-learning-based model to differentiate between these two types of variant calls: those that do not require confirmation using an orthogonal technology (high confidence), and those that require additional quality testing (low confidence). This approach allows reliable NGS-based calling in a clinical setting by identifying the few important variant calls that require orthogonal confirmation. We developed and tested the model using a set of 7179 variants identified by a targeted NGS panel and re-tested by Sanger sequencing. The model incorporated several signals of sequence characteristics and call quality to determine if a variant was identified at high or low confidence. The model was tuned to eliminate false positives, defined as variants that were called by NGS but not confirmed by Sanger sequencing. The model achieved very high accuracy: 99.4% (95% confidence interval: +/- 0.03%). It categorized 92.2% (6622/7179) of the variants as high confidence, and 100% of these were confirmed to be present by Sanger sequencing. Among the variants that were categorized as low confidence, defined as NGS calls of low quality that are likely to be artifacts, 92.1% (513/557) were found to be not present by Sanger sequencing. This work shows that NGS data contains sufficient characteristics for a machine-learning-based model to

  3. Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods

    Science.gov (United States)

    Soroush, Masoud; Weinberger, Charles B.

    2010-01-01

    This manuscript presents a successful application of inductive learning in process modeling. It describes two process modeling courses that use inductive learning methods such as inquiry learning and problem-based learning, among others. The courses include a novel collection of multi-disciplinary complementary process modeling examples. They were…

  4. Development of a Model for Whole Brain Learning of Physiology

    Science.gov (United States)

    Eagleton, Saramarie; Muller, Anton

    2011-01-01

    In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed…

  5. Extended Worksheet Developed According to 5E Model Based on Constructivist Learning Approach

    Science.gov (United States)

    Töman, Ufuk; Akdeniz, Ali Riza; Odabasi Çimer, Sabiha; Gürbüz, Fatih

    2013-01-01

    In order to achieve the targeted objectives desired level of education and modern learning theories for learner centered methods are recommended. In this context the use of worksheets developed and that student participation is considered to be one of the methods. This research is one of the ethyl alcohol fermentation biology issues and prepare…

  6. Cloud-Based E-Learning: A Proposed Model and Benefits by Using E-Learning Based on Cloud Computing for Educational Institution

    OpenAIRE

    Selviandro , Nungki; Hasibuan , Zainal ,

    2013-01-01

    Part 1: Information and Communication Technology- Eurasia Conference (ICT-EurAsia); International audience; The increasing research in the areas of information technology have a positive impact in the world of education. The implementation of e-learning is one of contribution from information technology to the world of education. The implementation of e-learning has been implemented by several educational institutions in Indonesia. E-Learning provides many benefits such as flexibility, divers...

  7. Developing Critical Thinking of Middle School Students using Problem Based Learning 4 Core Areas (PBL4C) Model

    Science.gov (United States)

    Haridza, R.; E Irving, K.

    2017-02-01

    Traditional methods such as rote learning and memorization in teaching science create passive students in science classrooms. The impact of this continuous action for many decades is inactive learners who cannot develop higher order thinking skills. Based on the performance test, students’ critical thinking skill in Public Middle School 3 Pontianak was in low level although their achievement score were higher than school standards. The purpose of this study is to develop critical thinking skills of middle school students using Problem Based Learning 4 Core Areas (PBL4C). The design of this research is classroom action research with two cycles. Data has been collected using observation checklist, rating scale, self and peer assessment. Research findings reveal that students experience development from 11.11% to 88.45% in identifying the problem correctly, 37.03% to 76.92% for sub skills distinguish knowledge and opinion, 18.51% to 65.38% for sub skills providing possible solution, 22.22% to 69.23% for sub skills making decision, and 11.11% to 69.23% for sub skills identifying the impact of the implementation of their solution. In conclusion, the findings indicate that development of students’ critical thinking skills occurs when PBL4C model applied in science classroom. These findings suggest that teachers should act as facilitator in a classroom as well as should provide meaningful learning resources that can benefit students’ critical thinking skills. On the other hand, students should practice constantly to offer a sharp, accurate and appropriate solution.

  8. An explanatory model of academic achievement based on aptitudes, goal orientations, self-concept and learning strategies.

    Science.gov (United States)

    Miñano Pérez, Pablo; Castejón Costa, Juan-Luis; Gilar Corbí, Raquel

    2012-03-01

    As a result of studies examining factors involved in the learning process, various structural models have been developed to explain the direct and indirect effects that occur between the variables in these models. The objective was to evaluate a structural model of cognitive and motivational variables predicting academic achievement, including general intelligence, academic self-concept, goal orientations, effort and learning strategies. The sample comprised of 341 Spanish students in the first year of compulsory secondary education. Different tests and questionnaires were used to evaluate each variable, and Structural Equation Modelling (SEM) was applied to contrast the relationships of the initial model. The model proposed had a satisfactory fit, and all the hypothesised relationships were significant. General intelligence was the variable most able to explain academic achievement. Also important was the direct influence of academic self-concept on achievement, goal orientations and effort, as well as the mediating ability of effort and learning strategies between academic goals and final achievement.

  9. Teaching Problem Based Learning as Blended Learning

    DEFF Research Database (Denmark)

    Kolbæk, Ditte; Nortvig, Anne-Mette

    2018-01-01

    Problem-based and project organized learning (PBL) was originally developed for collaboration between physically present students, but political decisions at many universities require that collaboration, dialogues, and other PBL activities take place online as well. With a theoretical point...... of departure in Dewey and a methodological point of departure in netnography, this study focuses on an online module at Aalborg University where teaching is based on PBL. With the research question ‘How can teachers design for PBL online,’ this study explores the teacher’s role in a six weeks’ blended learning...... program, and we present suggestions for designs for blended learning PBL based on case studies from two PBL courses...

  10. Online Learning of Industrial Manipulators' Dynamics Models

    DEFF Research Database (Denmark)

    Polydoros, Athanasios

    2017-01-01

    , it was compared with multiple other state-of-the-art machine learning algorithms. Moreover, the thesis presents the application of the proposed learning method on robot control for achieving trajectory execution while learning the inverse dynamics models  on-the-fly . Also it is presented the application...... of the dynamics models. Those mainly derive from physics-based methods and thus they are based on physical properties which are hard to be calculated.  In this thesis, is presented, a novel online machine learning approach  which is able to model both inverse and forward dynamics models of industrial manipulators....... The proposed method belongs to the class of deep learning and exploits the concepts of self-organization, recurrent neural networks and iterative multivariate Bayesian regression. It has been evaluated on multiple datasets captured from industrial robots while they were performing various tasks. Also...

  11. A Study on Online Education Model using Location Based Adaptive Mobile Learning

    OpenAIRE

    K. Krishna Prasad; P. S. Aithal

    2017-01-01

    Online educations are gaining more scope due to the busy schedule of working groups and their interest to acquire knowledge in new fields. Working group people find difficult to get admission in top institutions for their interested course due to competition and lack of time flexibility. Regular full-time university affiliated courses become lack of interest for the working group due to outdated curriculum, lack of innovation in teaching, unchanged learning and evaluation environment and lack...

  12. Java problem-based learning

    Directory of Open Access Journals (Sweden)

    Goran P, Šimić

    2012-01-01

    Full Text Available The paper describes the self-directed problem-based learning system (PBL named Java PBL. The expert module is the kernel of Java PBL. It involves a specific domain model, a problem generator and a solution generator. The overall system architecture is represented in the paper. Java PBL can act as the stand-alone system, but it is also designed to provide support to learning management systems (LMSs. This is provided by a modular design of the system. An LMS can offer the declarative knowledge only. Java PBL offers the procedural knowledge and the progress of the learner programming skills. The free navigation, unlimited numbers of problems and recommendations represent the main pedagogical strategies and tactics implemented into the system.

  13. Combining Metabolite-Based Pharmacophores with Bayesian Machine Learning Models for Mycobacterium tuberculosis Drug Discovery.

    Science.gov (United States)

    Ekins, Sean; Madrid, Peter B; Sarker, Malabika; Li, Shao-Gang; Mittal, Nisha; Kumar, Pradeep; Wang, Xin; Stratton, Thomas P; Zimmerman, Matthew; Talcott, Carolyn; Bourbon, Pauline; Travers, Mike; Yadav, Maneesh; Freundlich, Joel S

    2015-01-01

    Integrated computational approaches for Mycobacterium tuberculosis (Mtb) are useful to identify new molecules that could lead to future tuberculosis (TB) drugs. Our approach uses information derived from the TBCyc pathway and genome database, the Collaborative Drug Discovery TB database combined with 3D pharmacophores and dual event Bayesian models of whole-cell activity and lack of cytotoxicity. We have prioritized a large number of molecules that may act as mimics of substrates and metabolites in the TB metabolome. We computationally searched over 200,000 commercial molecules using 66 pharmacophores based on substrates and metabolites from Mtb and further filtering with Bayesian models. We ultimately tested 110 compounds in vitro that resulted in two compounds of interest, BAS 04912643 and BAS 00623753 (MIC of 2.5 and 5 μg/mL, respectively). These molecules were used as a starting point for hit-to-lead optimization. The most promising class proved to be the quinoxaline di-N-oxides, evidenced by transcriptional profiling to induce mRNA level perturbations most closely resembling known protonophores. One of these, SRI58 exhibited an MIC = 1.25 μg/mL versus Mtb and a CC50 in Vero cells of >40 μg/mL, while featuring fair Caco-2 A-B permeability (2.3 x 10-6 cm/s), kinetic solubility (125 μM at pH 7.4 in PBS) and mouse metabolic stability (63.6% remaining after 1 h incubation with mouse liver microsomes). Despite demonstration of how a combined bioinformatics/cheminformatics approach afforded a small molecule with promising in vitro profiles, we found that SRI58 did not exhibit quantifiable blood levels in mice.

  14. The effect of discovery learning and problem-based learning on middle school students’ self-regulated learning

    Science.gov (United States)

    Miatun, A.; Muntazhimah

    2018-01-01

    The aim of this research was to determine the effect of learning models on mathematics achievement viewed from student’s self-regulated learning. The learning model compared were discovery learning and problem-based learning. The population was all students at the grade VIII of Junior High School in Boyolali regency. The samples were students of SMPN 4 Boyolali, SMPN 6 Boyolali, and SMPN 4 Mojosongo. The instruments used were mathematics achievement tests and self-regulated learning questionnaire. The data were analyzed using unbalanced two-ways Anova. The conclusion was as follows: (1) discovery learning gives better achievement than problem-based learning. (2) Achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. (3) For discovery learning, achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. For problem-based learning, students who have high and medium self-regulated learning have the same achievement. (4) For students who have high self-regulated learning, discovery learning gives better achievement than problem-based learning. Students who have medium and low self-regulated learning, both learning models give the same achievement.

  15. Structural Damage Detection using Frequency Response Function Index and Surrogate Model Based on Optimized Extreme Learning Machine Algorithm

    Directory of Open Access Journals (Sweden)

    R. Ghiasi

    2017-09-01

    Full Text Available Utilizing surrogate models based on artificial intelligence methods for detecting structural damages has attracted the attention of many researchers in recent decades. In this study, a new kernel based on Littlewood-Paley Wavelet (LPW is proposed for Extreme Learning Machine (ELM algorithm to improve the accuracy of detecting multiple damages in structural systems.  ELM is used as metamodel (surrogate model of exact finite element analysis of structures in order to efficiently reduce the computational cost through updating process. In the proposed two-step method, first a damage index, based on Frequency Response Function (FRF of the structure, is used to identify the location of damages. In the second step, the severity of damages in identified elements is detected using ELM. In order to evaluate the efficacy of ELM, the results obtained from the proposed kernel were compared with other kernels proposed for ELM as well as Least Square Support Vector Machine algorithm. The solved numerical problems indicated that ELM algorithm accuracy in detecting structural damages is increased drastically in case of using LPW kernel.

  16. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis

    Directory of Open Access Journals (Sweden)

    Muhammad Sohaib

    2017-12-01

    Full Text Available Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE-based deep neural networks (DNNs to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs and backpropagation neural networks (BPNNs.

  17. A Hybrid Feature Model and Deep-Learning-Based Bearing Fault Diagnosis.

    Science.gov (United States)

    Sohaib, Muhammad; Kim, Cheol-Hong; Kim, Jong-Myon

    2017-12-11

    Bearing fault diagnosis is imperative for the maintenance, reliability, and durability of rotary machines. It can reduce economical losses by eliminating unexpected downtime in industry due to failure of rotary machines. Though widely investigated in the past couple of decades, continued advancement is still desirable to improve upon existing fault diagnosis techniques. Vibration acceleration signals collected from machine bearings exhibit nonstationary behavior due to variable working conditions and multiple fault severities. In the current work, a two-layered bearing fault diagnosis scheme is proposed for the identification of fault pattern and crack size for a given fault type. A hybrid feature pool is used in combination with sparse stacked autoencoder (SAE)-based deep neural networks (DNNs) to perform effective diagnosis of bearing faults of multiple severities. The hybrid feature pool can extract more discriminating information from the raw vibration signals, to overcome the nonstationary behavior of the signals caused by multiple crack sizes. More discriminating information helps the subsequent classifier to effectively classify data into the respective classes. The results indicate that the proposed scheme provides satisfactory performance in diagnosing bearing defects of multiple severities. Moreover, the results also demonstrate that the proposed model outperforms other state-of-the-art algorithms, i.e., support vector machines (SVMs) and backpropagation neural networks (BPNNs).

  18. Active Learning with Statistical Models.

    Science.gov (United States)

    1995-01-01

    Active Learning with Statistical Models ASC-9217041, NSF CDA-9309300 6. AUTHOR(S) David A. Cohn, Zoubin Ghahramani, and Michael I. Jordan 7. PERFORMING...TERMS 15. NUMBER OF PAGES Al, MIT, Artificial Intelligence, active learning , queries, locally weighted 6 regression, LOESS, mixtures of gaussians...COMPUTATIONAL LEARNING DEPARTMENT OF BRAIN AND COGNITIVE SCIENCES A.I. Memo No. 1522 January 9. 1995 C.B.C.L. Paper No. 110 Active Learning with

  19. Evaluating the Generalization Value of Process-based Models in a Deep-in-time Machine Learning framework

    Science.gov (United States)

    Shen, C.; Fang, K.

    2017-12-01

    Deep Learning (DL) methods have made revolutionary strides in recent years. A core value proposition of DL is that abstract notions and patterns can be extracted purely from data, without the need for domain expertise. Process-based models (PBM), on the other hand, can be regarded as repositories of human knowledge or hypotheses about how systems function. Here, through computational examples, we argue that there is merit in integrating PBMs with DL due to the imbalance and lack of data in many situations, especially in hydrology. We trained a deep-in-time neural network, the Long Short-Term Memory (LSTM), to learn soil moisture dynamics from Soil Moisture Active Passive (SMAP) Level 3 product. We show that when PBM solutions are integrated into LSTM, the network is able to better generalize across regions. LSTM is able to better utilize PBM solutions than simpler statistical methods. Our results suggest PBMs have generalization value which should be carefully assessed and utilized. We also emphasize that when properly regularized, the deep network is robust and is of superior testing performance compared to simpler methods.

  20. Caka E-Learning Model

    Science.gov (United States)

    Gorsev, Gonca; Turkmen, Ugur; Askin, Cihat

    2017-01-01

    In today's world, in order to obtain the information in education, various approaches, methods and devices have been developed. Like many developing countries, e-learning and distance learning (internet based learning) are used today in many areas of education in Turkey. This research aims to contribute to education systems and develop a…

  1. Pengembangan Paket Nekamedia Matematika Kurikulum 2013 Menggunakan Model Problem Based Learning (Pbl) pada Materi Bangun Ruang Sisi Datar Kelas VIII SMP di Kota Surakarta

    OpenAIRE

    Anggraini, Putri Nurika; Budiyono, Budiyono; Slamet, Isnandar

    2016-01-01

    This study was aimed to obtain 2013 Curriculum of mathematics mutlimedia kit using Problem Based Learning (PBL) model in plane geometry lesson of eighth grade junior high school in Surakarta which is considered as a valid, practical, and effective to be applied for learning. Furthermore, the goal was to discover whether the student's achievement of plane geometry lesson using the developed mutlimedia kit is better than using the prior product. The study type was Research and Development (R &a...

  2. A model reference and sensitivity model-based self-learning fuzzy logic controller as a solution for control of nonlinear servo systems

    NARCIS (Netherlands)

    Kovacic, Z.; Bogdan, S.; Balenovic, M.

    1999-01-01

    In this paper, the design, simulation and experimental verification of a self-learning fuzzy logic controller (SLFLC) suitable for the control of nonlinear servo systems are described. The SLFLC contains a learning algorithm that utilizes a second-order reference model and a sensitivity model

  3. Development of innovative problem based learning model with PMRI-scientific approach using ICT to increase mathematics literacy and independence-character of junior high school students

    Science.gov (United States)

    Wardono; Waluya, B.; Kartono; Mulyono; Mariani, S.

    2018-03-01

    This research is very urgent in relation to the national issue of human development and the nation's competitiveness because of the ability of Indonesian Junior High School students' mathematics literacy results of the Programme for International Student Assessment (PISA) by OECD field of Mathematics is still very low compared to other countries. Curriculum 2013 launched one of them reflect the results of PISA which is still far from the expectations of the Indonesian nation and to produce a better quality of education, PISA ratings that reflect the nation's better competitiveness need to be developed innovative, interactive learning models such as innovative interactive learning Problem Based Learning (PBL) based on the approach of Indonesian Realistic Mathematics Education (PMRI) and the Scientific approach using Information and Communication Technology (ICT).The research was designed using Research and Development (R&D), research that followed up the development and dissemination of a product/model. The result of the research shows the innovative interactive learning PBL model based on PMRI-Scientific using ICT that developed valid, practical and effective and can improve the ability of mathematics literacy and independence-character of junior high school students. While the quality of innovative interactive learning PBL model based on PMRI-Scientific using ICT meet the good category.

  4. Constructivism Based Learning: Design and Practice

    Directory of Open Access Journals (Sweden)

    Lia Kurniawati

    2016-06-01

    Full Text Available Abstract One of many problems in the madrasahs is that learning processes less-involve students actively (teacher-centered, thus, it affects to the improvement of learning outcomes and quality of the graduates. The purposes of this study are , firstly, to analyze what type of constructivism learning models, which can be developed to overcome madrasahs’ problems. Secondly, how to design and implement a learning plan based on the developed constructivism models. This research was conducted at Private Islamic Elementary School  (Madrasah Ad-Diyanah Ciputat, South Tangerang. Research method used in this study is descriptive-qualitative research. The results showed that the active learning models based on constructivism are suitable to be developed in the Madarasah, which were the models of Problem Based Learning (PBM, Realistic Learning, Inquiry Learning and Thematic Learning and also how the development of the learning processes from the lesson plans to the learning implementation showed a paradigm shifting from teacher-centered to student-centered. Abstrak Salah satu permasalahan di madrasah-madrasah adalah proses pembelajaran yang kurang melibatkan siswa secara aktif (berpusat pada guru, sehingga hal ini mengakibatkan pada peningkatan hasil belajar dan kualitas lulusan. Tujuan dari penelitian ini adalah, pertama, untuk menganalisis jenis model pembelajaran konstruktivisme apa yang dapat dikembangkan untuk mengatasi permasalahan di madrasah. Ke dua, bagaimana merancang dan melaksanakan rencana pembelajaran berdasarkan model konstruktivisme yang dikembangkan. Penelitian ini dilaksanakan di Sekolah Dasar Swasta (madrasah Ad-Diayanah Ciputat, Tangerang Selatan. Metode penelitian yang digunakan adalah metode deskriptif-kualitatif. Hasil penelitian menunjukkan bahwa model pembelajaran aktif yang berbasis konstruktivisme sesuai untuk dikembangkan di madrasah, yakni model pembelajaran Problem Based Learning (PBL, Pembelajaran Realistis, Pembelajaran

  5. Inquiry Based Learning and Meaning Generation through Modelling on Geometrical Optics in a Constructionist Environment

    Science.gov (United States)

    Kotsari, Constantina; Smyrnaiou, Zacharoula

    2017-01-01

    The central roles that modelling plays in the processes of scientific enquiry and that models play as the outcomes of that enquiry are well established (Gilbert & Boulter, 1998). Besides, there are considerable similarities between the processes and outcomes of science and technology (Cinar, 2016). In this study, we discuss how the use of…

  6. Comparison of E-learning and the Classroom Lecture in Microbiology Course Based on Gagne's Instructional Model

    Directory of Open Access Journals (Sweden)

    Mojgan Mohammadimehr

    2016-06-01

    Full Text Available Background: This study aims to design and produce electronic content of a microbiology course for students in AJA (Islamic Republic of Iran Army University of Medical Sciences based on Gagne's instructional design model and determine its effectiveness. Methods: This is a quasi-experimental study. All medical students studying in the 2014-2015 academic year in AJA University of Medical Sciences who had taken the microbiology course were entered in the study. Students were divided randomly into two groups, control and trial (16 subjects in each. After designing and producing the educational multimedia, the trial group was trained in concepts of the microbiology course using multimedia educational software during 6 sessions over 6 continuous weeks. Finally, they were given post-test questions to determine the educational progress level among the students. Results: The mean ± standard deviation for pre-test and post-test in the trial group were 4.44 ± 1.99 and 12.75 ± 1.06, respectively, and in the control group they were 3.75 ± 2.32 and 9.31 ± 1.25, respectively. The results of the analysis of covariance between adjusted means of both groups for variable of learning show a significant difference between the two groups (F(29,1= 65.69; P=0.001. The effect size was 0.69. Conclusion: The multimedia software produced in AJA University of Medical Sciences can be used as a proper educational instrument for teaching the microbiology courses. So, it is better to incorporate the multimedia method as a part of education into curriculum of universities, especially medical sciences universities. Keywords: e-learning, Gagne's instructional design, model, Education, Army, microbiology course

  7. Problem Based Learning Online

    DEFF Research Database (Denmark)

    Kolbæk, Ditte

    2018-01-01

    “How do two online learning designs affect student engagement in the PBL online modules?” The empirical data were collected and analyzed using a netnographic approach. The study finds that concepts such as self-directed learning and active involvement may be perceived very differently from the students...

  8. Carotid wall volume quantification from magnetic resonance images using deformable model fitting and learning-based correction of systematic errors

    International Nuclear Information System (INIS)

    Hameeteman, K; Niessen, W J; Klein, S; Van 't Klooster, R; Selwaness, M; Van der Lugt, A; Witteman, J C M

    2013-01-01

    We present a method for carotid vessel wall volume quantification from magnetic resonance imaging (MRI). The method combines lumen and outer wall segmentation based on deformable model fitting with a learning-based segmentation correction step. After selecting two initialization points, the vessel wall volume in a region around the bifurcation is automatically determined. The method was trained on eight datasets (16 carotids) from a population-based study in the elderly for which one observer manually annotated both the lumen and outer wall. An evaluation was carried out on a separate set of 19 datasets (38 carotids) from the same study for which two observers made annotations. Wall volume and normalized wall index measurements resulting from the manual annotations were compared to the automatic measurements. Our experiments show that the automatic method performs comparably to the manual measurements. All image data and annotations used in this study together with the measurements are made available through the website http://ergocar.bigr.nl. (paper)

  9. Proposed Models of Appropriate Website and Courseware for E-Learning in Higher Education: Research Based Design Models

    Science.gov (United States)

    Khlaisang, Jintavee

    2010-01-01

    The purpose of this study was to investigate proper website and courseware for e-learning in higher education. Methods used in this study included the data collection, the analysis surveys, the experts' in-depth interview, and the experts' focus group. Results indicated that there were 16 components for website, as well as 16 components for…

  10. The Development of Cooperative Learning Model Based on Local Wisdom of Bali for Physical Education, Sport and Health Subject in Junior High School

    Science.gov (United States)

    Yoda, I. K.

    2017-03-01

    The purpose of this research is to develop a cooperative learning model based on local wisdom (PKBKL) of Bali (Tri Pramana’s concept), for physical education, sport, and health learning in VII grade of Junior High School in Singaraja-Buleleng Bali. This research is the development research of the development design chosen refers to the development proposed by Dick and Carey. The development of model and learning devices was conducted through four stages, namely: (1) identification and needs analysis stage (2) the development of design and draft of PKBKL and RPP models, (3) testing stage (expert review, try out, and implementation). Small group try out was conducted on VII-3 grade of Undiksha Laboratory Junior High School in the academic year 2013/2014, large group try out was conducted on VIIb of Santo Paulus Junior High School Singaraja in the academic year 2014/2015, and the implementation of the model was conducted on three (3) schools namely SMPN 2 Singaraja, SMPN 3 Singaraja, and Undiksha laboratory Junior High School in the academic year 2014/2015. Data were collected using documentation, testing, non-testing, questionnaire, and observation. The data were analyzed descriptively. The findings of this research indicate that: (1) PKBKL model has met the criteria of the operation of a learning model namely: syntax, social system, principles of reaction, support system, as well as instructional and nurturing effects, (2) PKBKL model is a valid, practical, and effective model, (3) the practicality of the learning devices (RPP), is at the high category. Based on the research results, there are two things recommended: (1) in order that learning stages (syntax) of PKBKL model can be performed well, then teachers need to have an understanding of the cooperative learning model of Student Team Achievement Division (STAD) type and the concepts of scientifically approach well, (2) PKBKL model can be performed well on physical education, sport and health learning, if the

  11. Dimensions of problem based learning

    DEFF Research Database (Denmark)

    Nielsen, Jørgen Lerche; Andreasen, Lars Birch

    2013-01-01

    The article contributes to the literature on problem based learning and problem-oriented project work, building on and reflecting the experiences of the authors through decades of work with problem-oriented project pedagogy. The article explores different dimensions of problem based learning such...... and Learning (MIL). We discuss changes in the roles of the teachers as supervisors within this learning environment, and we explore the involvement of students as active participants and co-designers of how course and project activities unfold....

  12. Modeling human learning involved in car driving

    NARCIS (Netherlands)

    Wewerinke, P.H.

    1994-01-01

    In this paper, car driving is considered at the level of human tracking and maneuvering in the context of other traffic. A model analysis revealed the most salient features determining driving performance and safety. Learning car driving is modelled based on a system theoretical approach and based

  13. Learning Bayesian Dependence Model for Student Modelling

    Directory of Open Access Journals (Sweden)

    Adina COCU

    2008-12-01

    Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.

  14. Analysis of critical thinking ability of VII grade students based on the mathematical anxiety level through learning cycle 7E model

    Science.gov (United States)

    Widyaningsih, E.; Waluya, S. B.; Kurniasih, A. W.

    2018-03-01

    This study aims to know mastery learning of students’ critical thinking ability with learning cycle 7E, determine whether the critical thinking ability of the students with learning cycle 7E is better than students’ critical thinking ability with expository model, and describe the students’ critical thinking phases based on the mathematical anxiety level. The method is mixed method with concurrent embedded. The population is VII grade students of SMP Negeri 3 Kebumen academic year 2016/2017. Subjects are determined by purposive sampling, selected two students from each level of mathematical anxiety. Data collection techniques include test, questionnaire, interview, and documentation. Quantitative data analysis techniques include mean test, proportion test, difference test of two means, difference test of two proportions and for qualitative data used Miles and Huberman model. The results show that: (1) students’ critical thinking ability with learning cycle 7E achieve mastery learning; (2) students’ critical thinking ability with learning cycle 7E is better than students’ critical thinking ability with expository model; (3) description of students’ critical thinking phases based on the mathematical anxiety level that is the lower the mathematical anxiety level, the subjects have been able to fulfil all of the indicators of clarification, assessment, inference, and strategies phases.

  15. The Effect of CTL Approach Based on NHT Learning Model toward Students’ motivation, Science Achievement, and Retention

    Directory of Open Access Journals (Sweden)

    Muhammad Mifta Fausan

    2017-07-01

    Full Text Available The learning is an interaction process between students and their environment in order to improve good behavior. The results of observation which has been done in grade V SDN No. 4 Tanjung Batu showed that the students’ motivation and science achievement were low. This was becaused by the learning process which was still product oriented (based on material content, consequently, this lead to limit the learning is merely on memorizing concept activities. One of the learning approach that can be used to solve this problem is the Contextual Teaching and Learning (CTL based on Numbered Head Together (NHT. This research aims to determine the effect of CTL based on NHT toward student’s motivation, science achievement, and retention. Subjects in this research were the students of grade V SDN No. 4 Tanjung Batu. This research is a quasi-experimental using post-test only control design. The data obtained were analyzed by using descriptive and inferential statistical analysis. The research instruments were observation sheets and written test. The results showed that there was significant effect of CTL based on NHT toward students’ motivation, science achievement, and retention. It can be seen from the independent sample t-test results which showed significant value less than 0.05.

  16. Combining Correlation-Based and Reward-Based Learning in Neural Control for Policy Improvement

    DEFF Research Database (Denmark)

    Manoonpong, Poramate; Kolodziejski, Christoph; Wörgötter, Florentin

    2013-01-01

    Classical conditioning (conventionally modeled as correlation-based learning) and operant conditioning (conventionally modeled as reinforcement learning or reward-based learning) have been found in biological systems. Evidence shows that these two mechanisms strongly involve learning about...... associations. Based on these biological findings, we propose a new learning model to achieve successful control policies for artificial systems. This model combines correlation-based learning using input correlation learning (ICO learning) and reward-based learning using continuous actor–critic reinforcement...... learning (RL), thereby working as a dual learner system. The model performance is evaluated by simulations of a cart-pole system as a dynamic motion control problem and a mobile robot system as a goal-directed behavior control problem. Results show that the model can strongly improve pole balancing control...

  17. Design for game based learning platforms

    DEFF Research Database (Denmark)

    Sørensen, Birgitte Holm; Meyer, Bente

    2010-01-01

    This paper focuses on the challenges related to the design of game based learning platforms for formal learning contexts that are inspired by the pupil's leisure time related use of web 2.0. The paper is based on the project Serious Games on a Global Market Place (2007-2011) founded by the Danish...... of web 2.0 and integrates theories of learning, didactics, games, play, communication, multimodality and different pedagogical approaches. In relation to the introduced model the teacher role is discussed.......This paper focuses on the challenges related to the design of game based learning platforms for formal learning contexts that are inspired by the pupil's leisure time related use of web 2.0. The paper is based on the project Serious Games on a Global Market Place (2007-2011) founded by the Danish...... Council for Strategic Research, in which an online game-based platform for English as a foreign language in primary school is studied. The paper presents a model for designing for game based learning platforms. This design is based on cultural and ethnographic based research on children's leisure time use...

  18. Implementing Project Based Learning Approach to Graphic Design Course

    Science.gov (United States)

    Riyanti, Menul Teguh; Erwin, Tuti Nuriah; Suriani, S. H.

    2017-01-01

    The purpose of this study was to develop a learning model based Commercial Graphic Design Drafting project-based learning approach, was chosen as a strategy in the learning product development research. University students as the target audience of this model are the students of the fifth semester Visual Communications Design Studies Program…

  19. The 5E Instructional Model: A Learning Cycle Approach for Inquiry-Based Science Teaching

    Science.gov (United States)

    Duran, Lena Ballone; Duran, Emilio

    2004-01-01

    The implementation of inquiry-based teaching is a major theme in national science education reform documents such as "Project 2061: Science for All Americans" (Rutherford & Alhgren, 1990) and the "National Science Education Standards" (NRC, 1996). These reports argue that inquiry needs to be a central strategy of all…

  20. Communicative task modeling and its practice on academic English learning in a web-based environment

    NARCIS (Netherlands)

    Chen, Jin; Cristea, A.I.; Okamoto, T.

    2003-01-01

    A web-based course for scholarly communicative language competence development via a distance tutoring system is presented. Particular focus is given to the description of the representation and organization of communicative tasks representing the subject matter knowledge in terms of

  1. Integrating critical thinking and evidence-based dentistry across a four-year dental curriculum: a model for independent learning.

    Science.gov (United States)

    Marshall, Teresa A; Straub-Morarend, Cheryl L; Handoo, Nidhi; Solow, Catherine M; Cunningham-Ford, Marsha A; Finkelstein, Michael W

    2014-03-01

    Introducing critical thinking and evidence-based dentistry (EBD) content into an established dental curriculum can be a difficult and challenging process. Over the past three years, the University of Iowa College of Dentistry has developed and implemented a progressive four-year integrated critical thinking and EBD curriculum. The objective of this article is to describe the development and implementation process to make it available as a model for other dental schools contemplating introduction of critical thinking and EBD into their curricula. The newly designed curriculum built upon an existing problem-based learning foundation, which introduces critical thinking and the scientific literature in the D1 year, in order to expose students to the rationale and resources for practicing EBD in the D2 and D3 years and provide opportunities to practice critical thinking and apply the EBD five-step process in the D2, D3, and D4 years. All curricular content is online, and D3 and D4 EBD activities are integrated within existing clinical responsibilities. The curricular content, student resources, and student activities are described.

  2. PENINGKATAN KUALITAS PEMBELAJARAN IPA MELALUI MODEL PROBLEM BASED LEARNING (PBL MENGGUNAKAN AUDIOVISUAL

    Directory of Open Access Journals (Sweden)

    Endang Eka Wulandari, Sri Hartati

    2016-11-01

    Full Text Available Tujuan Penelitian ini untuk meningkatkan kualitas pembelajaran IPA pada siswa kelas IV melalui model PBL menggunakan audiovisual. Penelitian ini menggunakan desain penelitian tindakan kelas yang berlangsung dalam tiga siklus. Data dianalisis dengan menggunakan teknik analisis deskriptif kuantitatif dan kualitatif. Hasil penelitian menunjukan bahwa (1 Keterampilan guru pada siklus I mendapat skor 18, siklus II skor 22, meningkat pada siklus III skor 25.(2 Aktivitas siswa pada siklus I skor 16,8, pada siklus II skor 22, meningkat menjadi 24,4 pada siklus III. (3 Respon siswa pada siklus I dengan persentase 71% siklus II dengan persentase 78%, meningkat 92% pada siklus III (4 Hasil belajar siswa pada siklus I mengalami ketuntasan klasikal sebesar 60%, siklus II sebesar 73%, dan mengalami peningkatan pada siklus III menjadi 94%. Kesimpulan penelitian ini menunjukan model PBL menggunakan audiovisual dapat meningkatkan kualitas pembelajaran IPA yang ditandai dengan meningkatnya keterampilan guru, aktivitas siswa, respon siswa dan hasil belajar siswa.

  3. Testing the Community-Based Learning Collaborative (CBLC) implementation model: a study protocol

    OpenAIRE

    Hanson, Rochelle F.; Schoenwald, Sonja; Saunders, Benjamin E.; Chapman, Jason; Palinkas, Lawrence A.; Moreland, Angela D.; Dopp, Alex

    2016-01-01

    Background High rates of youth exposure to violence, either through direct victimization or witnessing, result in significant health/mental health consequences and high associated lifetime costs. Evidence-based treatments (EBTs), such as Trauma-Focused Cognitive Behavioral Therapy (TF-CBT), can prevent and/or reduce these negative effects, yet these treatments are not standard practice for therapists working with children identified by child welfare or mental health systems as needing service...

  4. System modeling based on machine learning for anomaly detection and predictive maintenance in industrial plants

    OpenAIRE

    Kroll, Björn; Schaffranek, David; Schriegel, Sebastian; Niggemann, Oliver

    2014-01-01

    Electricity, water or air are some Industrial energy carriers which are struggling under the prices of primary energy carriers. The European Union for example used more 20.000.000 GWh electricity in 2011 based on the IEA Report [1]. Cyber Physical Production Systems (CPPS) are able to reduce this amount, but they also help to increase the efficiency of machines above expectations which results in a more cost efficient production. Especially in the field of improving industrial plants, one of ...

  5. How Much Do You Trust Me? Learning a Case-Based Model of Inverse Trust

    Science.gov (United States)

    2014-10-01

    metric does not take into account factors of the robot’s behavior that increase trust. The inverse trust metric we use is based on the number of times the...sets contain identical behav- iors. To account for this, the similarity function looks at the overlap between the two sets and ignores behaviors that...155–156 5. Jian, J.Y., Bisantz, A.M., Drury , C.G.: Foundations for an empirically determined scale of trust in automated systems. International

  6. The effectiveness of clinical problem-based learning model of medico-jurisprudence education on general law knowledge for Obstetrics/Gynecological interns.

    Science.gov (United States)

    Chang, Hui-Chin; Wang, Ning-Yen; Ko, Wen-Ru; Yu, You-Tsz; Lin, Long-Yau; Tsai, Hui-Fang

    2017-06-01

    The effective education method of medico-jurisprudence for medical students is unclear. The study was designed to evaluate the effectiveness of problem-based learning (PBL) model teaching medico-jurisprudence in clinical setting on General Law Knowledge (GLK) for medical students. Senior medical students attending either campus-based law curriculum or Obstetrics/Gynecology (Ob/Gyn) clinical setting morning meeting from February to July in 2015 were enrolled. A validated questionnaire comprising 45 questions were completed before and after the law education. The interns attending clinical setting small group improvisation medico-jurisprudence problem-based learning education had significantly better GLK scores than the GLK of students attending campus-based medical law education course after the period studied. PBL teaching model of medico-jurisprudence is an ideal alternative pedagogy model in medical law education curriculum. Copyright © 2017. Published by Elsevier B.V.

  7. The effect of application of contextual teaching and learning (CTL model-based on lesson study with mind mapping media to assess student learning outcomes on chemistry on colloid systems

    Directory of Open Access Journals (Sweden)

    Annisa Fadillah

    2017-08-01

    Full Text Available The research was conducted to determine the effect of the application of CTL learning model based on lesson study with mind mapping media to the learning outcomes of students on colloid systems. The population of this research was all students of grade XI of SMA N 1 Sunggal. The sample was taken using on the purposive random sampling. The Experiment class was taught with Contextual Teaching and Learning (CTL model based on Lesson Study with Mind Mapping media and the control class taught with conventional learning model. The data was collected using an objective test was consisting of 20 questions which validity, reliability, level of difficulty and power of difference had been tested. T test results showed that tcalculate = 2.1 and ttable = 1.6697 thus tcalculate> ttable which means that Ha is accepted and Ho is rejected. The enhancement of the student learning outcomes showed that the results of experiment class are g = 72.88%, while the control class is 68.97%. From the percentage, it can be seen that learning outcomes of the experiment class are greater than the control class. The analysis of developing cognitive aspects pointed out that C1 = 70.02%, C2 = 73.58%, C3 = 68.63%, Thus the domain of cognitive level are on the cognitive aspects of C2. The result of Lesson Study Analysis showed the results of 71.09% at the first lesson and 88.28% at the second lesson. It means that there is increasing adherence to the indicators after two lessons. Based on the above results, it can be concluded that the result of studying chemistry of the students of class XI of SMA Negeri I Sunggal TA 2014/2015 taught by a CTL model based  on Lesson Study with Mind Mapping media was higher (72.88% than those taught by conventional learning models (68.97% in the subject matter of colloids System.

  8. The Development Model of Knowledge Management via Web-Based Learning to Enhance Pre-Service Teacher's Competency

    Science.gov (United States)

    Rampai, Nattaphon; Sopeerak, Saroch

    2011-01-01

    This research explores that the model of knowledge management and web technology for teachers' professional development as well as its impact in the classroom on learning and teaching, especially in pre-service teacher's competency and practices that refer to knowledge creating, analyzing, nurturing, disseminating, and optimizing process as part…

  9. Pedagogical Catalysts of Civic Competence: The Development of a Critical Epistemological Model for Community-Based Learning

    Science.gov (United States)

    Stokamer, Stephanie

    2013-01-01

    Democratic problem-solving necessitates an active and informed citizenry, but existing research on service-learning has shed little light on the relationship between pedagogical practices and civic competence outcomes. This study developed and tested a model to represent that relationship and identified pedagogical catalysts of civic competence…

  10. PENINGKATAN KEMAMPUAN ANALISIS MASALAH EKONOMI DENGAN MODEL PEMBELAJARAN PROBLEM BASED LEARNING (STUDI PADA SISWA KELAS X IIS 3 SMA 1 BAE KUDUS TAHUN AJARAN 2014/2015

    Directory of Open Access Journals (Sweden)

    Kurnia Norma Handayani

    2015-02-01

    Full Text Available atar belakang penelitian ini adalah karena kurangnya kemampuan analisis masalah ekonomi sehingga menyebabkan kurangnya pemahaman siswa akan materi dan berpengaruh terhadap hasil belajar siswa kurang optimal, selain itu karena metode pembelajaran yang digunakan tidak tepat yaitu menggunakan ceramah tanpa variasi sedangkan karakter materinya adalah teoritis dan membutuhkan analisis. Penelitian ini bertujuan untuk mengetahui peningkatan kemampuan analisis masalah ekonomi dengan model pembelajaran Problem Based Learning dan mengetahui penerapan model pembelajaran Problem Based Learning untuk meningkatkan kemampuan analisis masalah ekonomi. Subyek penelitian ini adalah siswa kelas X IIS 3 SMA 1 Bae Kudus. Penelitian ini merupakan penelitian tindakan kelas yang dilakukan dalam 2 siklus. Hasil penelitian ini diperoleh data kemampuan analisis siswa siklus I nilai rata-rata 73,94 dengan ketuntasan klasikal sebesar 52,94%, pada siklus II nilai rata-rata meningkat menjadi 82,29 dengan ketuntasan klasikal sebesar 82,35%, aktivitas siswa pada pembelajaran siklus I cukup dan pada siklus II meningkat menjadi sangat baik. The background of this research is the lack of knowledge in economic problems so students learning outcomes less optimal, moreover because the learning method that is used is not appropriate to use the oral speech without variation while the character is doctrinaire and needing analysis. This research aims to know improving the analysis ability on the subject economic problems with problem based learning model and how the use problem based learning can improving the analysis ability on the subject economic problems. The subject of this research is the class X IIS 3 SMA 1 Bae Kudus. This study is an action research conducted in two cycles. The research finding showed that analysis ability in learning cycle I average grade is 73,94 with percentage of classical completeness is 52,94%, in cycle II average grade increase to 82,29 with percentage of

  11. Examining Prediction Models of Giving up within a Resource-Based Framework of Coping in Primary School Students with and without Learning Disabilities

    Science.gov (United States)

    Skues, Jason L.; Cunningham, Everarda G.; Theiler, Stephen S.

    2016-01-01

    This study tests a proposed model of coping outcomes for 290 primary school students in Years 5 and 6 (mean age = 11.50 years) with and without learning disabilities (LDs) within a resource-based framework of coping. Group-administered educational and intelligence tests were used to screen students for LDs. Students also completed a questionnaire…

  12. Potential Teachers' Appropriate and Inappropriate Application of Pedagogical Resources in a Model-Based Physics Course: A "Knowledge in Pieces" Perspective on Teacher Learning

    Science.gov (United States)

    Harlow, Danielle B.; Bianchini, Julie A.; Swanson, Lauren H.; Dwyer, Hilary A.

    2013-01-01

    We used a "knowledge in pieces" perspective on teacher learning to document undergraduates' pedagogical resources in a model-based physics course for potential teachers. We defined pedagogical resources as small, discrete ideas about teaching science that are applied appropriately or inappropriately in specific contexts. Neither…

  13. An Instructional Design Model with the Cultivating Research-Based Learning Strategies for Fostering Teacher Students' Creative Thinking Abilities

    Science.gov (United States)

    Khuana, Khwanchai; Khuana, Tanthip; Santiboon, Toansakul

    2017-01-01

    Designing the instructional model with the innovative the "Research-Based Learning Strategy Lesson Plans" of the effectiveness of the processing performance and the resulting performance (E1/E2) with the IOC value determining standardized criteria of 80/80 were developed. Students' perceptions were assessed with the 30-item…

  14. Cancer survival analysis using semi-supervised learning method based on Cox and AFT models with L1/2 regularization.

    Science.gov (United States)

    Liang, Yong; Chai, Hua; Liu, Xiao-Ying; Xu, Zong-Ben; Zhang, Hai; Leung, Kwong-Sak

    2016-03-01

    One of the most important objectives of the clinical cancer research is to diagnose cancer more accurately based on the patients' gene expression profiles. Both Cox proportional hazards model (Cox) and accelerated failure time model (AFT) have been widely adopted to the high risk and low risk classification or survival time prediction for the patients' clinical treatment. Nevertheless, two main dilemmas limit the accuracy of these prediction methods. One is that the small sample size and censored data remain a bottleneck for training robust and accurate Cox classification model. In addition to that, similar phenotype tumours and prognoses are actually completely different diseases at the genotype and molecular level. Thus, the utility of the AFT model for the survival time prediction is limited when such biological differences of the diseases have not been previously identified. To try to overcome these two main dilemmas, we proposed a novel semi-supervised learning method based on the Cox and AFT models to accurately predict the treatment risk and the survival time of the patients. Moreover, we adopted the efficient L1/2 regularization approach in the semi-supervised learning method to select the relevant genes, which are significantly associated with the disease. The results of the simulation experiments show that the semi-supervised learning model can significant improve the predictive performance of Cox and AFT models in survival analysis. The proposed procedures have been successfully applied to four real microarray gene expression and artificial evaluation datasets. The advantages of our proposed semi-supervised learning method include: 1) significantly increase the available training samples from censored data; 2) high capability for identifying the survival risk classes of patient in Cox model; 3) high predictive accuracy for patients' survival time in AFT model; 4) strong capability of the relevant biomarker selection. Consequently, our proposed semi

  15. How Model Can Help Inquiry--A Qualitative Study of Model Based Inquiry Learning (Mobile) in Engineering Education

    Science.gov (United States)

    Gong, Yu

    2017-01-01

    This study investigates how students can use "interactive example models" in inquiry activities to develop their conceptual knowledge about an engineering phenomenon like electromagnetic fields and waves. An interactive model, for example a computational model, could be used to develop and teach principles of dynamic complex systems, and…

  16. Learning Radiology in an Integrated Problem-Based Learning (PBL ...

    African Journals Online (AJOL)

    Background: The Faculty of Medicine (FoM) has been training health professions in Uganda since 1924. Five years ago, it decided to change the undergraduate curriculum from traditional to Problem Based Learning (PBL) and adopted the SPICES model. Radiology was integrated into the different courses throughout the 5 ...

  17. Learning to Model in Engineering

    Science.gov (United States)

    Gainsburg, Julie

    2013-01-01

    Policymakers and education scholars recommend incorporating mathematical modeling into mathematics education. Limited implementation of modeling instruction in schools, however, has constrained research on how students learn to model, leaving unresolved debates about whether modeling should be reified and explicitly taught as a competence, whether…

  18. A Predictive Model for Guillain-Barré Syndrome Based on Single Learning Algorithms

    Directory of Open Access Journals (Sweden)

    Juana Canul-Reich

    2017-01-01

    Full Text Available Background. Guillain-Barré Syndrome (GBS is a potentially fatal autoimmune neurological disorder. The severity varies among the four main subtypes, named as Acute Inflammatory Demyelinating Polyneuropathy (AIDP, Acute Motor Axonal Neuropathy (AMAN, Acute Motor Sensory Axonal Neuropathy (AMSAN, and Miller-Fisher Syndrome (MF. A proper subtype identification may help to promptly carry out adequate treatment in patients. Method. We perform experiments with 15 single classifiers in two scenarios: four subtypes’ classification and One versus All (OvA classification. We used a dataset with the 16 relevant features identified in a previous phase. Performance evaluation is made by 10-fold cross validation (10-FCV. Typical classification performance measures are used. A statistical test is conducted in order to identify the top five classifiers for each case. Results. In four GBS subtypes’ classification, half of the classifiers investigated in this study obtained an average accuracy above 0.90. In OvA classification, the two subtypes with the largest number of instances resulted in the best classification results. Conclusions. This study represents a comprehensive effort on creating a predictive model for Guillain-Barré Syndrome subtypes. Also, the analysis performed in this work provides insight about the best single classifiers for each classification case.

  19. Mosaic model for sensorimotor learning and control.

    Science.gov (United States)

    Haruno, M; Wolpert, D M; Kawato, M

    2001-10-01

    Humans demonstrate a remarkable ability to generate accurate and appropriate motor behavior under many different and often uncertain environmental conditions. We previously proposed a new modular architecture, the modular selection and identification for control (MOSAIC) model, for motor learning and control based on multiple pairs of forward (predictor) and inverse (controller) models. The architecture simultaneously learns the multiple inverse models necessary for control as well as how to select the set of inverse models appropriate for a given environment. It combines both feedforward and feedback sensorimotor information so that the controllers can be selected both prior to movement and subsequently during movement. This article extends and evaluates the MOSAIC architecture in the following respects. The learning in the architecture was implemented by both the original gradient-descent method and the expectation-maximization (EM) algorithm. Unlike gradient descent, the newly derived EM algorithm is robust to the initial starting conditions and learning parameters. Second, simulations of an object manipulation task prove that the architecture can learn to manipulate multiple objects and switch between them appropriately. Moreover, after learning, the model shows generalization to novel objects whose dynamics lie within the polyhedra of already learned dynamics. Finally, when each of the dynamics is associated with a particular object shape, the model is able to select the appropriate controller before movement execution. When presented with a novel shape-dynamic pairing, inappropriate activation of modules is observed followed by on-line correction.

  20. The Effects of Using Jigsaw Method Based on Cooperative Learning Model in the Undergraduate Science Laboratory Practices

    Science.gov (United States)

    Karacop, Ataman

    2017-01-01

    The main aim of the present study is to determine the influence of a Jigsaw method based on cooperative learning and a confirmatory laboratory method on prospective science teachers' achievements of physics in science teaching laboratory practice courses. The sample of this study consisted of 33 female and 15 male third-grade prospective science…

  1. Community Based Learning and Civic Engagement: Informal Learning among Adult Volunteers in Community Organizations

    Science.gov (United States)

    Mundel, Karsten; Schugurensky, Daniel

    2008-01-01

    Many iterations of community based learning employ models, such as consciousness raising groups, cultural circles, and participatory action research. In all of them, learning is a deliberate part of an explicit educational activity. This article explores another realm of community learning: the informal learning that results from volunteering in…

  2. Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

    Science.gov (United States)

    Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

    2010-04-01

    Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

  3. Performance evaluation in competence-based learning model in higher education scenarios using social network: a case study

    Directory of Open Access Journals (Sweden)

    Katherina Edith GALLARDO CÓRDOVA

    2017-12-01

    Full Text Available A research about performance evaluation was conducted in a graduate online course designed in the Based-Competency Model. Facebook was used as a social and interactive tool that would permit sharing information to illustrate various aspects of diverse educational contexts as well as the impacts of the implementation of improvement projects seen from the beneficiaries’ perspective. Case Study was the methodology selected. Postgraduate students got the task to work on certain improvements on learning assessment matters. The educational scenarios were located in Mexico and Colombia. 7 units of analysis were chosen among 34 possible. The findings pointed out that students worked on their contexts in alignment with the stipulated academic competencies. The use of video materials posted and shared using Facebook allowed get a deeper understanding of the way the benefits influenced in each of the educational communities. Besides, these products evidenced students’ appropriate performance. In conclusion, the use of social networks for fortifying performance assessment is highly recommended. Moreover, it is expected that these benefits also influence some of the curricular and instructional design aspects.

  4. Design of learner-centred constructivism based learning process

    OpenAIRE

    Schreurs, Jeanne; Al-Huneidi, Ahmad

    2012-01-01

    A Learner-centered learning is constructivism based and Competence directed. We define general competencies, domain competencies and specific course competencies. Constructivism based learning activities are based on constructivism theory. For each course module the intended learning level will be defined. A model is built for the design of a learner centered constructivism based and competency directed learning process. The application of it in two courses are presented. Constructivism ba...

  5. Proposing a Holistic Model for Formulating the Security Requirements of e-learning based on Stakeholders’ Point of Veiw

    Directory of Open Access Journals (Sweden)

    Abouzar Arabsorkhi Mishabi

    2016-03-01

    Full Text Available Development of e-learning applications and services in the context of information and communication networks –beside qualitative and quantitative improvement in the scope and range of services they provide – has increased veriety of threats which are emerged from these networks and telecommunications infrastructure. This kind of issue have mad the effective and accurate analysing of security issues nessesary to managers and decision makers. Accordingly, in this study, using findings of other studies in the field of e-learning security, using methasyntesis, attempted to define a holistic model for classification and organization of security requirements. A structure that defines the origin of security requirements of e-learning and rolplays as a reference for formulating security requirements for this area.

  6. How people learn about causal influence when there are many possible causes: A model based on informative transitions.

    Science.gov (United States)

    Derringer, Cory; Rottman, Benjamin Margolin

    2018-05-01

    Four experiments tested how people learn cause-effect relations when there are many possible causes of an effect. When there are many cues, even if all the cues together strongly predict the effect, the bivariate relation between each individual cue and the effect can be weak, which can make it difficult to detect the influence of each cue. We hypothesized that when detecting the influence of a cue, in addition to learning from the states of the cues and effect (e.g., a cue is present and the effect is present), which is hypothesized by multiple existing theories of learning, participants would also learn from transitions - how the cues and effect change over time (e.g., a cue turns on and the effect turns on). We found that participants were better able to identify positive and negative cues in an environment in which only one cue changed from one trial to the next, compared to multiple cues changing (Experiments 1A, 1B). Within a single learning sequence, participants were also more likely to update their beliefs about causal strength when one cue changed at a time ('one-change transitions') than when multiple cues changed simultaneously (Experiment 2). Furthermore, learning was impaired when the trials were grouped by the state of the effect (Experiment 3) or when the trials were grouped by the state of a cue (Experiment 4), both of which reduce the number of one-change transitions. We developed a modification of the Rescorla-Wagner algorithm to model this 'Informative Transitions' learning processes. Copyright © 2018 Elsevier Inc. All rights reserved.

  7. E-learning: Web-based education.

    Science.gov (United States)

    Sajeva, Marco

    2006-12-01

    This review introduces state-of-the-art Web-based education and shows how the e-learning model can be applied to an anaesthesia department using Open Source solutions, as well as lifelong learning programs, which is happening in several European research projects. The definition of the term e-learning is still a work in progress due to the fact that technologies are evolving every day and it is difficult to improve teaching methodologies or to adapt traditional methods to a new or already existing educational model. The European Community is funding several research projects to define the new common market place for tomorrow's educational system; this is leading to new frontiers like virtual Erasmus inter-exchange programs based on e-learning. The first step when adapting a course to e-learning is to re-define the educational/learning model adopted: cooperative learning and tutoring are the two key concepts. This means that traditional lecture notes, books and exercises are no longer effective; teaching files must use rich multimedia content and have to be developed using the new media. This can lead to several pitfalls that can be avoided with an accurate design phase.

  8. Analysis of mathematical literacy ability based on goal orientation in model eliciting activities learning with murder strategy

    Science.gov (United States)

    Wijayanti, R.; Waluya, S. B.; Masrukan

    2018-03-01

    The purpose of this research are (1) to analyze the learning quality of MEAs with MURDER strategy, (2) to analyze students’ mathematical literacy ability based on goal orientation in MEAs learning with MURDER strategy. This research is a mixed method research of concurrent embedded type where qualitative method as the primary method. The data were obtained using the methods of scale, observation, test and interviews. The results showed that (1) MEAs Learning with MURDER strategy on students' mathematical literacy ability is qualified, (2) Students who have mastery goal characteristics are able to master the seven components of mathematical literacy process although there are still two components that the solution is less than the maximum. Students who have performance goal characteristics have not mastered the components of mathematical literacy process with the maximum, they are only able to master the ability of using mathematics tool and the other components of mathematical literacy process is quite good.

  9. Applying the technology acceptance model to explore public health nurses' intentions towards web-based learning: a cross-sectional questionnaire survey.

    Science.gov (United States)

    Chen, I Ju; Yang, Kuei-Feng; Tang, Fu-In; Huang, Chun-Hsia; Yu, Shu

    2008-06-01

    In the era of the knowledge economy, public health nurses (PHNs) need to update their knowledge to ensure quality of care. In pre-implementation stage, policy makers and educators should understand PHNs' behavioural intentions (BI) toward web-based learning because it is the most important determinant of actual behaviour. To understand PHNs' BI toward web-based learning and further to identify the factors influencing PHNs' BI based on the technology acceptance model (TAM) in pre-implementation stage. A nationwide-based cross-sectional research design was used in this study. Three hundred and sixty-nine health centres in Taiwan. A randomly selected sample, 202 PHNs participated in this study. Data were collected by mailing in a questionnaire. The majority of PHNs (91.6%, n=185) showed an affirmative BI toward web-based learning. PHNs rated moderate values of perceived usefulness (U), perceived ease of use (EOU) and attitude toward web-based learning (A). Multiple regression analyses indicated that only U revealed a significantly direct influence on BI. U and EOU had significantly direct relationships with A; however, no significant relationship existed between A and BI. Additionally, EOU and an individual's computer competence revealed significant relationships with U; Internet access at the workplace revealed a significant relationship with EOU. In the pre-implementation stage, PHNs perceived a high likelihood of adopting web-based learning as their way of continuing education. In pre-implementation stage, perceived usefulness is the most important factor for BI instead of the attitude. Perceived EOU, an individual's computer competency, and Internet access at workplaces revealed indirect effects on BI. Therefore, increasing U, EOU, computer competence, and Internet access at workplace will be helpful in increasing PHNs' BI. Moreover, we suggest that future studies should focus on clarifying problems in different stages of implementation to build a more complete

  10. Correlation Between Blended Learning Model With The Perspective Of Learning Effectiveness For Nursing Student

    Directory of Open Access Journals (Sweden)

    Susila Sumartiningsih

    2015-06-01

    Full Text Available ABSTRACT The learning model is one of the enabling factors that influence the achievement of students. That students have a good learning outcomes the lecturer must choose appropriate learning models. But in fact not all lecturers choose the most appropriate learning model with the demands of learning outcomes and student characteristics.The study design was descriptive quantitative correlation. Total population of 785 the number of samples are 202 were taken by purposive sampling. Techniques of data collection is done by cross-sectional and then processed through the Spearman test. The results showed no significant relationship between classroom lecture method in the context of blended learning models to study the effectiveness perspective the p value of 0.001. There is a significant relationship between e-learning methods in the context of blended learning models with perspective of activities study of nursing students the p value of 0.028. There is a significant relationship between learning model of blended learning with the perspective of nursing students learning effectiveness p value 0.167. Researchers recommend to future researchers conduct more research on the comparison between the effectiveness of the learning model based on student learning centers with the e-learning models and its impact on student achievement of learning competencies as well as to the implications for other dimensions of learning outcomes and others.

  11. Planning Model of Physics Learning In Senior High School To Develop Problem Solving Creativity Based On National Standard Of Education

    Science.gov (United States)

    Putra, A.; Masril, M.; Yurnetti, Y.

    2018-04-01

    One of the causes of low achievement of student’s competence in physics learning in high school is the process which they have not been able to develop student’s creativity in problem solving. This is shown that the teacher’s learning plan is not accordance with the National Eduction Standard. This study aims to produce a reconstruction model of physics learning that fullfil the competency standards, content standards, and assessment standards in accordance with applicable curriculum standards. The development process follows: Needs analysis, product design, product development, implementation, and product evaluation. The research process involves 2 peers judgment, 4 experts judgment and two study groups of high school students in Padang. The data obtained, in the form of qualitative and quantitative data that collected through documentation, observation, questionnaires, and tests. The result of this research up to the product development stage that obtained the physics learning plan model that meets the validity of the content and the validity of the construction in terms of the fulfillment of Basic Competence, Content Standards, Process Standards and Assessment Standards.

  12. Evaluation of a Digital Game-Based Learning Program for Enhancing Youth Mental Health: A Structural Equation Modeling of the Program Effectiveness.

    Science.gov (United States)

    Huen, Jenny My; Lai, Eliza Sy; Shum, Angie Ky; So, Sam Wk; Chan, Melissa Ky; Wong, Paul Wc; Law, Y W; Yip, Paul Sf

    2016-10-07

    Digital game-based learning (DGBL) makes use of the entertaining power of digital games for educational purposes. Effectiveness assessment of DGBL programs has been underexplored and no attempt has been made to simultaneously model both important components of DGBL: learning attainment (ie, educational purposes of DGBL) and engagement of users (ie, entertaining power of DGBL) in evaluating program effectiveness. This study aimed to describe and evaluate an Internet-based DGBL program, Professor Gooley and the Flame of Mind, which promotes mental health to adolescents in a positive youth development approach. In particular, we investigated whether user engagement in the DGBL program could enhance their attainment on each of the learning constructs per DGBL module and subsequently enhance their mental health as measured by psychological well-being. Users were assessed on their attainment on each learning construct, psychological well-being, and engagement in each of the modules. One structural equation model was constructed for each DGBL module to model the effect of users' engagement and attainment on the learning construct on their psychological well-being. Of the 498 secondary school students that registered and participated from the first module of the DGBL program, 192 completed all 8 modules of the program. Results from structural equation modeling suggested that a higher extent of engagement in the program activities facilitated users' attainment on the learning constructs on most of the modules and in turn enhanced their psychological well-being after controlling for users' initial psychological well-being and initial attainment on the constructs. This study provided evidence that Internet intervention for mental health, implemented with the technologies and digital innovations of DGBL, could enhance youth mental health. Structural equation modeling is a promising approach in evaluating the effectiveness of DGBL programs.

  13. Investigating the experience: A case study of a science professional development program based on Kolb's experiential learning model

    Science.gov (United States)

    Davis, Brian L.

    Professional development for educators has been defined as the process or processes by which teachers achieve higher levels of professional competence and expand their understanding of self, role, context and career (Duke and Stiggins, 1990). Currently, there is limited research literature that examines the effect a professional development course, which uses David Kolb's experiential learning model, has on the professional growth and teaching practice of middle school science teachers. The purpose of this interpretive case study is to investigate how three science teachers who participated in the Rivers to Reef professional development course interpreted the learning experience and integrated the experience into their teaching practice. The questions guiding this research are (1) What is the relationship between a professional development course that uses an experiential learning model and science teaching practice? (2) How do the Rivers to Reef participants reflect on and describe the course as a professional growth experience? The creation of the professional development course and the framework for the study were established using David Kolb's (1975) experiential learning theory and the reflection process model designed by David Boud (1985). The participants in the study are three middle school science teachers from schools representing varied settings and socioeconomic levels in the southeastern United States. Data collected used the three-interview series interview format designed by Dolbere and Schuman (Seidman, 1998). Data was analyzed for the identification of common categories related to impact on science teaching practice and professional growth. The major finding of this study indicates the years of teaching experience of middle school science teachers significantly influences how they approach professional development, what and how they learn from the experience, and the ways in which the experience influences their teaching practices.

  14. [Mathematical models of decision making and learning].

    Science.gov (United States)

    Ito, Makoto; Doya, Kenji

    2008-07-01

    Computational models of reinforcement learning have recently been applied to analysis of brain imaging and neural recording data to identity neural correlates of specific processes of decision making, such as valuation of action candidates and parameters of value learning. However, for such model-based analysis paradigms, selecting an appropriate model is crucial. In this study we analyze the process of choice learning in rats using stochastic rewards. We show that "Q-learning," which is a standard reinforcement learning algorithm, does not adequately reflect the features of choice behaviors. Thus, we propose a generalized reinforcement learning (GRL) algorithm that incorporates the negative reward effect of reward loss and forgetting of values of actions not chosen. Using the Bayesian estimation method for time-varying parameters, we demonstrated that the GRL algorithm can predict an animal's choice behaviors as efficiently as the best Markov model. The results suggest the usefulness of the GRL for the model-based analysis of neural processes involved in decision making.

  15. Virtual Learning Environments and Learning Forms -experiments in ICT-based learning

    DEFF Research Database (Denmark)

    Helbo, Jan; Knudsen, Morten

    2004-01-01

    This paper report the main results of a three year experiment in ICT-based distance learning. The results are based on a full scale experiment in the education, Master of Industrial Information Technology (MII) and is one of many projects deeply rooted in the project Virtual Learning Environments...... didactic model has until now been a positive experience........ The main problem is that we do not find the same self regulatoring learning effect in the group work among the off-campus students as is the case for on-campus students. Based on feedback from evaluation questionnaires and discussions with the students didactic adjustments have been made. The revised...

  16. SIMPLIFIED PREDICTIVE MODELS FOR CO₂ SEQUESTRATION PERFORMANCE ASSESSMENT RESEARCH TOPICAL REPORT ON TASK #3 STATISTICAL LEARNING BASED MODELS

    Energy Technology Data Exchange (ETDEWEB)

    Mishra, Srikanta; Schuetter, Jared

    2014-11-01

    We compare two approaches for building a statistical proxy model (metamodel) for CO₂ geologic sequestration from the results of full-physics compositional simulations. The first approach involves a classical Box-Behnken or Augmented Pairs experimental design with a quadratic polynomial response surface. The second approach used a space-filling maxmin Latin Hypercube sampling or maximum entropy design with the choice of five different meta-modeling techniques: quadratic polynomial, kriging with constant and quadratic trend terms, multivariate adaptive regression spline (MARS) and additivity and variance stabilization (AVAS). Simulations results for CO₂ injection into a reservoir-caprock system with 9 design variables (and 97 samples) were used to generate the data for developing the proxy models. The fitted models were validated with using an independent data set and a cross-validation approach for three different performance metrics: total storage efficiency, CO₂ plume radius and average reservoir pressure. The Box-Behnken–quadratic polynomial metamodel performed the best, followed closely by the maximin LHS–kriging metamodel.

  17. Learning model of eye movement system based on anatomical structure; Kaibogakuteki kozo ni motozuita gakushu kino wo motsu gankyu undo system to sono tokusei

    Energy Technology Data Exchange (ETDEWEB)

    Zhang, X.; Wakamatsu, H. [Tokyo Medical and Dental University, Tokyo (Japan)

    1998-07-01

    A learning system is proposed to explain the adaptive function of an eye movement consisting of compensatory and optokinetic reflex, and pursuit movements based on the brain anatomy and physiology. Thereby, the learning system is synthesized as an artificial neural network based on the structure and function of the biological neural network of flocculus. The role of neural paths into flocculus from stretch receptors of ocular muscles are discussed in detail from the viewpoint of system control engineering. The mathematical learning process is also shown taking into account the adaptive mechanism and the anatomical structure of vestibular nuclei. The experimental results through simulation confirm the validity of the hypothesis and the appropriateness of the inference process in connection with the proposed mathematical model. 18 refs., 11 figs.

  18. Supplier's optimal bidding strategy in electricity pay-as-bid auction: Comparison of the Q-learning and a model-based approach

    International Nuclear Information System (INIS)

    Rahimiyan, Morteza; Rajabi Mashhadi, Habib

    2008-01-01

    In this paper, the bidding decision making problem in electricity pay-as-bid auction is studied from a supplier's point of view. The bidding problem is a complicated task, because of suppliers' uncertain behaviors and demand fluctuation. In a specific case, in which, the market clearing price (MCP) is considered as a continuous random variable with a known probability distribution function (PDF), an analytic solution is proposed. The suggested solution is generalized to consider the effect of supplier market power due to transmission congestion. As a result, an algebraic equation is developed to compute optimal offering price. The basic assumption in this approach is to take the known probabilistic model for the MCP. The above-mentioned method, called model-based approach, is not more applicable in a realistic situation. In order to overcome the drawback of this method, which needs information about the MCP and its PDF, the supplier learns from past experiences using the Q-learning algorithm to find out the optimal bid price. The simulation results of the model-based and Q-learning methods are compared on a studied system. It is shown that a supplier using the Q-learning algorithm is able to find the optimal bidding strategy similar to one obtained by the model-based approach. Furthermore, to analyze a more realistic situation, the suppliers' behaviors are modeled using a multi-agent system. Simulation results illustrate that the studied supplier finds the optimal bidding strategy in power market using the Q-learning algorithm. (author)

  19. Problem Solving Model for Science Learning

    Science.gov (United States)

    Alberida, H.; Lufri; Festiyed; Barlian, E.

    2018-04-01

    This research aims to develop problem solving model for science learning in junior high school. The learning model was developed using the ADDIE model. An analysis phase includes curriculum analysis, analysis of students of SMP Kota Padang, analysis of SMP science teachers, learning analysis, as well as the literature review. The design phase includes product planning a science-learning problem-solving model, which consists of syntax, reaction principle, social system, support system, instructional impact and support. Implementation of problem-solving model in science learning to improve students' science process skills. The development stage consists of three steps: a) designing a prototype, b) performing a formative evaluation and c) a prototype revision. Implementation stage is done through a limited trial. A limited trial was conducted on 24 and 26 August 2015 in Class VII 2 SMPN 12 Padang. The evaluation phase was conducted in the form of experiments at SMPN 1 Padang, SMPN 12 Padang and SMP National Padang. Based on the development research done, the syntax model problem solving for science learning at junior high school consists of the introduction, observation, initial problems, data collection, data organization, data analysis/generalization, and communicating.

  20. Learning Probabilistic Logic Models from Probabilistic Examples.

    Science.gov (United States)

    Chen, Jianzhong; Muggleton, Stephen; Santos, José

    2008-10-01

    We revisit an application developed originally using abductive Inductive Logic Programming (ILP) for modeling inhibition in metabolic networks. The example data was derived from studies of the effects of toxins on rats using Nuclear Magnetic Resonance (NMR) time-trace analysis of their biofluids together with background knowledge representing a subset of the Kyoto Encyclopedia of Genes and Genomes (KEGG). We now apply two Probabilistic ILP (PILP) approaches - abductive Stochastic Logic Programs (SLPs) and PRogramming In Statistical modeling (PRISM) to the application. Both approaches support abductive learning and probability predictions. Abductive SLPs are a PILP framework that provides possible worlds semantics to SLPs through abduction. Instead of learning logic models from non-probabilistic examples as done in ILP, the PILP approach applied in this paper is based on a general technique for introducing probability labels within a standard scientific experimental setting involving control and treated data. Our results demonstrate that the PILP approach provides a way of learning probabilistic logic models from probabilistic examples, and the PILP models learned from probabilistic examples lead to a significant decrease in error accompanied by improved insight from the learned results compared with the PILP models learned from non-probabilistic examples.

  1. A Multiobjective Sparse Feature Learning Model for Deep Neural Networks.

    Science.gov (United States)

    Gong, Maoguo; Liu, Jia; Li, Hao; Cai, Qing; Su, Linzhi

    2015-12-01

    Hierarchical deep neural networks are currently popular learning models for imitating the hierarchical architecture of human brain. Single-layer feature extractors are the bricks to build deep networks. Sparse feature learning models are popular models that can learn useful representations. But most of those models need a user-defined constant to control the sparsity of representations. In this paper, we propose a multiobjective sparse feature learning model based on the autoencoder. The parameters of the model are learnt by optimizing two objectives, reconstruction error and the sparsity of hidden units simultaneously to find a reasonable compromise between them automatically. We design a multiobjective induced learning procedure for this model based on a multiobjective evolutionary algorithm. In the experiments, we demonstrate that the learning procedure is effective, and the proposed multiobjective model can learn useful sparse features.

  2. A Novel Hybrid Model Based on Extreme Learning Machine, k-Nearest Neighbor Regression and Wavelet Denoising Applied to Short-Term Electric Load Forecasting

    Directory of Open Access Journals (Sweden)

    Weide Li

    2017-05-01

    Full Text Available Electric load forecasting plays an important role in electricity markets and power systems. Because electric load time series are complicated and nonlinear, it is very difficult to achieve a satisfactory forecasting accuracy. In this paper, a hybrid model, Wavelet Denoising-Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EWKM, which combines k-Nearest Neighbor (KNN and Extreme Learning Machine (ELM based on a wavelet denoising technique is proposed for short-term load forecasting. The proposed hybrid model decomposes the time series into a low frequency-associated main signal and some detailed signals associated with high frequencies at first, then uses KNN to determine the independent and dependent variables from the low-frequency signal. Finally, the ELM is used to get the non-linear relationship between these variables to get the final prediction result for the electric load. Compared with three other models, Extreme Learning Machine optimized by k-Nearest Neighbor Regression (EKM, Wavelet Denoising-Extreme Learning Machine (WKM and Wavelet Denoising-Back Propagation Neural Network optimized by k-Nearest Neighbor Regression (WNNM, the model proposed in this paper can improve the accuracy efficiently. New South Wales is the economic powerhouse of Australia, so we use the proposed model to predict electric demand for that region. The accurate prediction has a significant meaning.

  3. Scaffolding in geometry based on self regulated learning

    Science.gov (United States)

    Bayuningsih, A. S.; Usodo, B.; Subanti, S.

    2017-12-01

    This research aim to know the influence of problem based learning model by scaffolding technique on junior high school student’s learning achievement. This research took location on the junior high school in Banyumas. The research data obtained through mathematic learning achievement test and self-regulated learning (SRL) questioner. Then, the data analysis used two ways ANOVA. The results showed that scaffolding has positive effect to the mathematic learning achievement. The mathematic learning achievement use PBL-Scaffolding model is better than use PBL. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

  4. MEMECAHKAN MASALAH GEOGRAFI MELALUI PROBLEM BASED LEARNING

    Directory of Open Access Journals (Sweden)

    Sujiono Sujiono

    2018-01-01

    Full Text Available This study aims to determine the effect of Problem Based Learning model on geography problem-solving sklills. This research model is quasi experiment with non-equivalent control group design. The subjects of the study were the students of XI IPS SMA Negeri 1 Pulau Laut Timur, academic year 2016/2017. The assessment instrument is an essay test based on an indicator of problem solving skills, ie (1 identifying problems; (2 formulate the problem; (3 finding alternative solutions; (4 choose alternative solutions; and (5 make conclusions. Data analysis using independent sample t-test model with 5% significance level. The results showed that there is an influence of PBL model on geography problem-solving sklills. The geography problem-solving skills of experimental class with PBL model is higher than control class with conventional model. Suggestion given, that is to make a plan of learning well and doing learning PBL on outdoor study.   Keywords Problem Based Learning, problem-solving skills, geography   http://dx.doi.org/10.17977/um022v2i22017p072

  5. Active Learning for Player Modeling

    DEFF Research Database (Denmark)

    Shaker, Noor; Abou-Zleikha, Mohamed; Shaker, Mohammad

    2015-01-01

    Learning models of player behavior has been the focus of several studies. This work is motivated by better understanding of player behavior, a knowledge that can ultimately be employed to provide player-adapted or personalized content. In this paper, we propose the use of active learning for player...... experience modeling. We use a dataset from hundreds of players playing Infinite Mario Bros. as a case study and we employ the random forest method to learn mod- els of player experience through the active learning approach. The results obtained suggest that only part of the dataset (up to half the size...... that the method can be used online during the content generation process where the mod- els can improve and better content can be presented as the game is being played....

  6. How to Enhance Interdisciplinary Competence--Interdisciplinary Problem-Based Learning versus Interdisciplinary Project-Based Learning

    Science.gov (United States)

    Brassler, Mirjam; Dettmers, Jan

    2017-01-01

    Interdisciplinary competence is important in academia for both employability and sustainable development. However, to date, there are no specific interdisciplinary education models and, naturally, no empirical studies to assess them. Since problem-based learning (PBL) and project-based learning (PjBL) are learning approaches that emphasize…

  7. Unsupervised learning of mixture models based on swarm intelligence and neural networks with optimal completion using incomplete data

    Directory of Open Access Journals (Sweden)

    Ahmed R. Abas

    2012-07-01

    Full Text Available In this paper, a new algorithm is presented for unsupervised learning of finite mixture models (FMMs using data set with missing values. This algorithm overcomes the local optima problem of the Expectation-Maximization (EM algorithm via integrating the EM algorithm with Particle Swarm Optimization (PSO. In addition, the proposed algorithm overcomes the problem of biased estimation due to overlapping clusters in estimating missing values in the input data set by integrating locally-tuned general regression neural networks with Optimal Completion Strategy (OCS. A comparison study shows the superiority of the proposed algorithm over other algorithms commonly used in the literature in unsupervised learning of FMM parameters that result in minimum mis-classification errors when used in clustering incomplete data set that is generated from overlapping clusters and these clusters are largely different in their sizes.

  8. A Visual Detection Learning Model

    Science.gov (United States)

    Beard, Bettina L.; Ahumada, Albert J., Jr.; Trejo, Leonard (Technical Monitor)

    1998-01-01

    Our learning model has memory templates representing the target-plus-noise and noise-alone stimulus sets. The best correlating template determines the response. The correlations and the feedback participate in the additive template updating rule. The model can predict the relative thresholds for detection in random, fixed and twin noise.

  9. The island model for parallel implementation of evolutionary algorithm of Population-Based Incremental Learning (PBIL) optimization

    International Nuclear Information System (INIS)

    Lima, Alan M.M. de; Schirru, Roberto

    2000-01-01

    Genetic algorithms are biologically motivated adaptive systems which have been used, with good results, for function optimization. The purpose of this work is to introduce a new parallelization method to be applied to the Population-Based Incremental Learning (PBIL) algorithm. PBIL combines standard genetic algorithm mechanisms with simple competitive learning and has ben successfully used in combinatorial optimization problems. The development of this algorithm aims its application to the reload optimization of PWR nuclear reactors. Tests have been performed with combinatorial optimization problems similar to the reload problem. Results are compared to the serial PBIL ones, showing the new method's superiority and its viability as a tool for the nuclear core reload problem solution. (author)

  10. The Answering Process for Multiple-Choice Questions in Collaborative Learning: A Mathematical Learning Model Analysis

    Science.gov (United States)

    Nakamura, Yasuyuki; Nishi, Shinnosuke; Muramatsu, Yuta; Yasutake, Koichi; Yamakawa, Osamu; Tagawa, Takahiro

    2014-01-01

    In this paper, we introduce a mathematical model for collaborative learning and the answering process for multiple-choice questions. The collaborative learning model is inspired by the Ising spin model and the model for answering multiple-choice questions is based on their difficulty level. An intensive simulation study predicts the possibility of…

  11. Developing models to predict 8th grade students' achievement levels on timss science based on opportunity-to-learn variables

    Science.gov (United States)

    Whitford, Melinda M.

    Science educational reforms have placed major emphasis on improving science classroom instruction and it is therefore vital to study opportunity-to-learn (OTL) variables related to student science learning experiences and teacher teaching practices. This study will identify relationships between OTL and student science achievement and will identify OTL predictors of students' attainment at various distinct achievement levels (low/intermediate/high/advanced). Specifically, the study (a) address limitations of previous studies by examining a large number of independent and control variables that may impact students' science achievement and (b) it will test hypotheses of structural relations to how the identified predictors and mediating factors impact on student achievement levels. The study will follow a multi-stage and integrated bottom-up and top-down approach to identify predictors of students' achievement levels on standardized tests using TIMSS 2011 dataset. Data mining or pattern recognition, a bottom-up approach will identify the most prevalent association patterns between different student achievement levels and variables related to student science learning experiences, teacher teaching practices and home and school environments. The second stage is a top-down approach, testing structural equation models of relations between the significant predictors and students' achievement levels according.

  12. Study and Application of Reinforcement Learning in Cooperative Strategy of the Robot Soccer Based on BDI Model

    Directory of Open Access Journals (Sweden)

    Wu Bo-ying

    2009-11-01

    Full Text Available The dynamic cooperation model of multi-Agent is formed by combining reinforcement learning with BDI model. In this model, the concept of the individual optimization loses its meaning, because the repayment of each Agent dose not only depend on itsself but also on the choice of other Agents. All Agents can pursue a common optimum solution and try to realize the united intention as a whole to a maximum limit. The robot moves to its goal, depending on the present positions of the other robots that cooperate with it and the present position of the ball. One of these robots cooperating with it is controlled to move by man with a joystick. In this way, Agent can be ensured to search for each state-action as frequently as possible when it carries on choosing movements, so as to shorten the time of searching for the movement space so that the convergence speed of reinforcement learning can be improved. The validity of the proposed cooperative strategy for the robot soccer has been proved by combining theoretical analysis with simulation robot soccer match (11vs11 .

  13. Effect of Face-to-face Education, Problem-based Learning, and Goldstein Systematic Training Model on Quality of Life and Fatigue among Caregivers of Patients with Diabetes.

    Science.gov (United States)

    Masoudi, Reza; Soleimani, Mohammad Ali; Yaghoobzadeh, Ameneh; Baraz, Shahram; Hakim, Ashrafalsadat; Chan, Yiong H

    2017-01-01

    Education is a fundamental component for patients with diabetes to achieve good glycemic control. In addition, selecting the appropriate method of education is one of the most effective factors in the quality of life. The present study aimed to evaluate the effect of face-to-face education, problem-based learning, and Goldstein systematic training model on the quality of life (QOL) and fatigue among caregivers of patients with diabetes. This randomized clinical trial was conducted in Hajar Hospital (Shahrekord, Iran) in 2012. The study subjects consisted of 105 family caregivers of patients with diabetes. The participants were randomly assigned to three intervention groups (35 caregivers in each group). For each group, 5-h training sessions were held separately. QOL and fatigue were evaluated immediately before and after the intervention, and after 1, 2, 3, and 4 months of intervention. There was a significant increase in QOL for all the three groups. Both the problem-based learning and the Goldstein method showed desirable QOL improvement over time. The desired educational intervention for fatigue reduction during the 4-month post-intervention period was the Goldstein method. A significant reduction was observed in fatigue in all three groups after the intervention ( P problem-based learning and Goldstein systematic training model improve the QOL of caregivers of patients with diabetes. In addition, the Goldstein systematic training model had the greatest effect on the reduction of fatigue within 4 months of the intervention.

  14. Computational modeling of epiphany learning.

    Science.gov (United States)

    Chen, Wei James; Krajbich, Ian

    2017-05-02

    Models of reinforcement learning (RL) are prevalent in the decision-making literature, but not all behavior seems to conform to the gradual convergence that is a central feature of RL. In some cases learning seems to happen all at once. Limited prior research on these "epiphanies" has shown evidence of sudden changes in behavior, but it remains unclear how such epiphanies occur. We propose a sequential-sampling model of epiphany learning (EL) and test it using an eye-tracking experiment. In the experiment, subjects repeatedly play a strategic game that has an optimal strategy. Subjects can learn over time from feedback but are also allowed to commit to a strategy at any time, eliminating all other options and opportunities to learn. We find that the EL model is consistent with the choices, eye movements, and pupillary responses of subjects who commit to the optimal strategy (correct epiphany) but not always of those who commit to a suboptimal strategy or who do not commit at all. Our findings suggest that EL is driven by a latent evidence accumulation process that can be revealed with eye-tracking data.

  15. Learning Analytics for Networked Learning Models

    Science.gov (United States)

    Joksimovic, Srecko; Hatala, Marek; Gaševic, Dragan

    2014-01-01

    Teaching and learning in networked settings has attracted significant attention recently. The central topic of networked learning research is human-human and human-information interactions occurring within a networked learning environment. The nature of these interactions is highly complex and usually requires a multi-dimensional approach to…

  16. Enhancing students' learning in problem based learning: validation of a self-assessment scale for active learning and critical thinking

    NARCIS (Netherlands)

    Khoiriyah, U.; Roberts, C.; Jorm, C.; Vleuten, C.P. van der

    2015-01-01

    BACKGROUND: Problem based learning (PBL) is a powerful learning activity but fidelity to intended models may slip and student engagement wane, negatively impacting learning processes, and outcomes. One potential solution to solve this degradation is by encouraging self-assessment in the PBL

  17. PROJECT BASED LEARNING BERMUATAN ETNOMATEMATIKA DALAM PEMBELAJAR MATEMATIKA

    Directory of Open Access Journals (Sweden)

    I Wayan Eka Mahendra

    2017-03-01

    Full Text Available This study aims to determine differences simultaneously in motivation and mathematics learning outcomes between students taking project based learningmodel charged ethnomathematics and students who followed the conventional learning modelon the class VIII SMP Negeri 3 Abiansemalyear 2016/2017. It was a quasi experiment with a sample of 71 student obtain by using simple random sampling. The data were analyzed by one-way multivariate analysis (Manova.The results of this study indicate that there are differences in simultaneously in learning motivation and learning outcomes between students taking mathematics model project based learning charged ethnomathematics and students who followed the conventional learning model on the class VIII SMP Negeri 3 Abiansemal year 2016/2017. Besed on the research findings, junior high school teachers are suggested to improve their student learning outcome for mathematics. Teachers also need to use a learning models accurately and correctly.

  18. Science Teacher Efficacy and Extrinsic Factors Toward Professional Development Using Video Games in a Design-Based Research Model: The Next Generation of STEM Learning

    Science.gov (United States)

    Annetta, Leonard A.; Frazier, Wendy M.; Folta, Elizabeth; Holmes, Shawn; Lamb, Richard; Cheng, Meng-Tzu

    2013-02-01

    Designed-based research principles guided the study of 51 secondary-science teachers in the second year of a 3-year professional development project. The project entailed the creation of student-centered, inquiry-based, science, video games. A professional development model appropriate for infusing innovative technologies into standards-based curricula was employed to determine how science teacher's attitudes and efficacy where impacted while designing science-based video games. The study's mixed-method design ascertained teacher efficacy on five factors (General computer use, Science Learning, Inquiry Teaching and Learning, Synchronous chat/text, and Playing Video Games) related to technology and gaming using a web-based survey). Qualitative data in the form of online blog posts was gathered during the project to assist in the triangulation and assessment of teacher efficacy. Data analyses consisted of an Analysis of Variance and serial coding of teacher reflective responses. Results indicated participants who used computers daily have higher efficacy while using inquiry-based teaching methods and science teaching and learning. Additional emergent findings revealed possible motivating factors for efficacy. This professional development project was focused on inquiry as a pedagogical strategy, standard-based science learning as means to develop content knowledge, and creating video games as technological knowledge. The project was consistent with the Technological Pedagogical Content Knowledge (TPCK) framework where overlapping circles of the three components indicates development of an integrated understanding of the suggested relationships. Findings provide suggestions for development of standards-based science education software, its integration into the curriculum and, strategies for implementing technology into teaching practices.

  19. Collaborative Inquiry-based Learning

    NARCIS (Netherlands)

    Suarez, Angel

    2017-01-01

    This thesis presents the results of the conducted research and development of applications to support collaborative inquiry-based learning, with a special focus on leveraging learners’ agency. The reported results are structured into three parts: the theoretical foundations, the design and

  20. Learning in AN Oscillatory Cortical Model

    Science.gov (United States)

    Scarpetta, Silvia; Li, Zhaoping; Hertz, John

    We study a model of generalized-Hebbian learning in asymmetric oscillatory neural networks modeling cortical areas such as hippocampus and olfactory cortex. The learning rule is based on the synaptic plasticity observed experimentally, in particular long-term potentiation and long-term depression of the synaptic efficacies depending on the relative timing of the pre- and postsynaptic activities during learning. The learned memory or representational states can be encoded by both the amplitude and the phase patterns of the oscillating neural populations, enabling more efficient and robust information coding than in conventional models of associative memory or input representation. Depending on the class of nonlinearity of the activation function, the model can function as an associative memory for oscillatory patterns (nonlinearity of class II) or can generalize from or interpolate between the learned states, appropriate for the function of input representation (nonlinearity of class I). In the former case, simulations of the model exhibits a first order transition between the "disordered state" and the "ordered" memory state.

  1. A New Mobile Learning Adaptation Model

    OpenAIRE

    Mohamd Hassan Hassan; Jehad Al-Sadi

    2009-01-01

    This paper introduces a new model for m- Learning context adaptation due to the need of utilizing mobile technology in education. Mobile learning; m-Learning for short; in considered to be one of the hottest topics in the educational community, many researches had been done to conceptualize this new form of learning. We are presenting a promising design for a model to adapt the learning content in mobile learning applications in order to match the learner context, preferences and the educatio...

  2. Architectural and Functional Design and Evaluation of E-Learning VUIS Based on the Proposed IEEE LTSA Reference Model.

    Science.gov (United States)

    O'Droma, Mairtin S.; Ganchev, Ivan; McDonnell, Fergal

    2003-01-01

    Presents a comparative analysis from the Institute of Electrical and Electronics Engineers (IEEE) Learning Technology Standards Committee's (LTSC) of the architectural and functional design of e-learning delivery platforms and applications, e-learning course authoring tools, and learning management systems (LMSs), with a view of assessing how…

  3. What else are psychotherapy trainees learning? A qualitative model of students' personal experiences based on two populations.

    Science.gov (United States)

    Pascual-Leone, Antonio; Rodriguez-Rubio, Beatriz; Metler, Samantha

    2013-01-01

    After an introductory course in experiential-integrative psychotherapy, 21 graduate students provided personal narratives of their experiences, which were analyzed using the grounded theory method. Results produced 37 hierarchically organized experiences, revealing that students perceived multiple changes in both professional (i.e., skill acquisition and learning related to the therapeutic process) and personal (i.e., self growth in a more private sphere) domains. Analysis also highlighted key areas of difficulties in training. By adding the personal accounts of graduate trainees, this study enriches and extends Pascual-Leone et al.'s (2012) findings on undergraduates' experiences, raising the number of cases represented in the model to 45. Findings confirm the model of novice trainee experiences while highlighting the unique experiences of undergraduate vs. graduate trainees.

  4. New Realities and the Implications for Problem Based Learning

    DEFF Research Database (Denmark)

    Sørensen, Olav Jull

    2004-01-01

    -based learning model with the new realities of today. Three new realities are discussed, the new global realities, the new business realities, and the new realities at the individual level. The new realities challenge the problem-based learning model. Adjustments are needed in terms of closer co...

  5. Learning-based identification and iterative learning control of direct-drive robots

    NARCIS (Netherlands)

    Bukkems, B.H.M.; Kostic, D.; Jager, de A.G.; Steinbuch, M.

    2005-01-01

    A combination of model-based and Iterative Learning Control is proposed as a method to achieve high-quality motion control of direct-drive robots in repetitive motion tasks. We include both model-based and learning components in the total control law, as their individual properties influence the

  6. Web-Based Instruction, Learning Effectiveness and Learning Behavior: The Impact of Relatedness

    Science.gov (United States)

    Shieh, Chich-Jen; Liao, Ying; Hu, Ridong

    2013-01-01

    This study aims to discuss the effects of Web-based Instruction and Learning Behavior on Learning Effectiveness. Web-based Instruction contains the dimensions of Active Learning, Simulation-based Learning, Interactive Learning, and Accumulative Learning; and, Learning Behavior covers Learning Approach, Learning Habit, and Learning Attitude. The…

  7. Estimating Students’ Satisfaction with Web Based Learning System in Blended Learning Environment

    Directory of Open Access Journals (Sweden)

    Sanja Bauk

    2014-01-01

    Full Text Available Blended learning became the most popular educational model that universities apply for teaching and learning. This model combines online and face-to-face learning environments, in order to enhance learning with implementation of new web technologies and tools in learning process. In this paper principles of DeLone and Mclean success model for information system are applied to Kano two-dimensional model, for categorizing quality attributes related to satisfaction of students with web based learning system used in blended learning model. Survey results are obtained among the students at “Mediterranean” University in Montenegro. The (dysfunctional dimensions of Kano model, including Kano basic matrix for assessment of the degree of students’ satisfaction level, have been considered in some more detail through corresponding numerical, graphical, and statistical analysis.

  8. Individual Learning Accounts and Other Models of Financing Lifelong Learning

    Science.gov (United States)

    Schuetze, Hans G.

    2007-01-01

    To answer the question "Financing what?" this article distinguishes several models of lifelong learning as well as a variety of lifelong learning activities. Several financing methods are briefly reviewed, however the principal focus is on Individual Learning Accounts (ILAs) which were seen by some analysts as a promising model for…

  9. Urban Studies: A Learning Model.

    Science.gov (United States)

    Cooper, Terry L.; Sundeen, Richard

    1979-01-01

    The urban studies learning model described in this article was found to increase students' self-esteem, imbue a more flexible and open perspective, contribute to the capacity for self-direction, produce increases on the feeling reactivity, spontaneity, and acceptance of aggression scales, and expand interpersonal competence. (Author/WI)

  10. promoting self directed learning in simulation based discovery learning environments through intelligent support.

    NARCIS (Netherlands)

    Veermans, K.H.; de Jong, Anthonius J.M.; van Joolingen, Wouter

    2000-01-01

    Providing learners with computer-generated feedback on their learning process in simulationbased discovery environments cannot be based on a detailed model of the learning process due to the “open” character of discovery learning. This paper describes a method for generating adaptive feedback for

  11. Learning Object Retrieval and Aggregation Based on Learning Styles

    Science.gov (United States)

    Ramirez-Arellano, Aldo; Bory-Reyes, Juan; Hernández-Simón, Luis Manuel

    2017-01-01

    The main goal of this article is to develop a Management System for Merging Learning Objects (msMLO), which offers an approach that retrieves learning objects (LOs) based on students' learning styles and term-based queries, which produces a new outcome with a better score. The msMLO faces the task of retrieving LOs via two steps: The first step…

  12. Project-based Collaborative learning in distance education in "The Aalborg PBL Model – Progress, Diversity and Challenges" (Eds.: Anette Kolmos, Flemming K. Fink and Lone Krogh)

    DEFF Research Database (Denmark)

    Knudsen, Morten; Bajard, C.; Helbo, Jan

    This article describes the experiences drawn from an experiment in transferring positive experience with a project-organised on-campus engineering programme to a technology supported distance education programme. Three years of experience with the Master of Industrial Information Technology (MII)......, didactic adjustments have been made based on feedback, in particular from evaluation questionnaires. This process has been very constructive in approaching the goal: a successful model for project organized learning in distance education.......) programme indicates, however, that adjustments are required in transforming the on-campus model to distance education. The main problem is that while project work is an excellent regulator of the learning process for on-campus students, this does not seem to be the case for off-campus students. Consequently...

  13. Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON's programming language hoc.

    Science.gov (United States)

    Hernández, Oscar E; Zurek, Eduardo E

    2013-05-15

    We present a software tool called SENB, which allows the geometric and biophysical neuronal properties in a simple computational model of a Hodgkin-Huxley (HH) axon to be changed. The aim of this work is to develop a didactic and easy-to-use computational tool in the NEURON simulation environment, which allows graphical visualization of both the passive and active conduction parameters and the geometric characteristics of a cylindrical axon with HH properties. The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and potassium equilibrium potentials, and propagation velocity of the action potentials. Furthermore, it allows the user to see all this information immediately in the main window. Finally, with just one click SENB can save an image of the main window as evidence. The SENB software is didactic and versatile, and can be used to improve and facilitate the teaching and learning of the underlying mechanisms in the electrical activity of an axon using the biophysical properties of the squid giant axon.

  14. Teaching and learning the Hodgkin-Huxley model based on software developed in NEURON’s programming language hoc

    Science.gov (United States)

    2013-01-01

    Background We present a software tool called SENB, which allows the geometric and biophysical neuronal properties in a simple computational model of a Hodgkin-Huxley (HH) axon to be changed. The aim of this work is to develop a didactic and easy-to-use computational tool in the NEURON simulation environment, which allows graphical visualization of both the passive and active conduction parameters and the geometric characteristics of a cylindrical axon with HH properties. Results The SENB software offers several advantages for teaching and learning electrophysiology. First, SENB offers ease and flexibility in determining the number of stimuli. Second, SENB allows immediate and simultaneous visualization, in the same window and time frame, of the evolution of the electrophysiological variables. Third, SENB calculates parameters such as time and space constants, stimuli frequency, cellular area and volume, sodium and potassium equilibrium potentials, and propagation velocity of the action potentials. Furthermore, it allows the user to see all this information immediately in the main window. Finally, with just one click SENB can save an image of the main window as evidence. Conclusions The SENB software is didactic and versatile, and can be used to improve and facilitate the teaching and learning of the underlying mechanisms in the electrical activity of an axon using the biophysical properties of the squid giant axon. PMID:23675833

  15. E-Model for Online Learning Communities.

    Science.gov (United States)

    Rogo, Ellen J; Portillo, Karen M

    2015-10-01

    The purpose of this study was to explore the students' perspectives on the phenomenon of online learning communities while enrolled in a graduate dental hygiene program. A qualitative case study method was designed to investigate the learners' experiences with communities in an online environment. A cross-sectional purposive sampling method was used. Interviews were the data collection method. As the original data were being analyzed, the researchers noted a pattern evolved indicating the phenomenon developed in stages. The data were re-analyzed and validated by 2 member checks. The participants' experiences revealed an e-model consisting of 3 stages of formal learning community development as core courses in the curriculum were completed and 1 stage related to transmuting the community to an informal entity as students experienced the independent coursework in the program. The development of the formal learning communities followed 3 stages: Building a Foundation for the Learning Community, Building a Supportive Network within the Learning Community and Investing in the Community to Enhance Learning. The last stage, Transforming the Learning Community, signaled a transition to an informal network of learners. The e-model was represented by 3 key elements: metamorphosis of relationships, metamorphosis through the affective domain and metamorphosis through the cognitive domain, with the most influential element being the affective development. The e-model describes a 4 stage process through which learners experience a metamorphosis in their affective, relationship and cognitive development. Synergistic learning was possible based on the interaction between synergistic relationships and affective actions. Copyright © 2015 The American Dental Hygienists’ Association.

  16. Research on Model of Student Engagement in Online Learning

    Science.gov (United States)

    Peng, Wang

    2017-01-01

    In this study, online learning refers students under the guidance of teachers through the online learning platform for organized learning. Based on the analysis of related research results, considering the existing problems, the main contents of this paper include the following aspects: (1) Analyze and study the current student engagement model.…

  17. PENGEMBANGAN CASE BASE LEARNING PADA MATA KULIAH PEREKONOMIAN INDONESIA

    Directory of Open Access Journals (Sweden)

    Hastarini Dwi Atmani

    2011-05-01

    Full Text Available In this time, teacher centered learning is a methods in part of higher education in Indonsia. This method, students passively receive information.Case base learning is an instructional design model that is a variant of project oriented learning. Cases are factually-based, complex problems written to stimulate classroom discussion and collaborative analysis. This one, students construct knowledge through gathering and synthesizing information and integrating it with the general skills of inquiry, communication, critical thinking, and problem solving. Key words : active learning, case base learning.

  18. Learning topic models by belief propagation.

    Science.gov (United States)

    Zeng, Jia; Cheung, William K; Liu, Jiming

    2013-05-01

    Latent Dirichlet allocation (LDA) is an important hierarchical Bayesian model for probabilistic topic modeling, which attracts worldwide interest and touches on many important applications in text mining, computer vision and computational biology. This paper represents the collapsed LDA as a factor graph, which enables the classic loopy belief propagation (BP) algorithm for approximate inference and parameter estimation. Although two commonly used approximate inference methods, such as variational Bayes (VB) and collapsed Gibbs sampling (GS), have gained great success in learning LDA, the proposed BP is competitive in both speed and accuracy, as validated by encouraging experimental results on four large-scale document datasets. Furthermore, the BP algorithm has the potential to become a generic scheme for learning variants of LDA-based topic models in the collapsed space. To this end, we show how to learn two typical variants of LDA-based topic models, such as author-topic models (ATM) and relational topic models (RTM), using BP based on the factor graph representations.

  19. Computer-based learning in neuroanatomy: A longitudinal study of learning, transfer, and retention

    Science.gov (United States)

    Chariker, Julia H.

    A longitudinal experiment was conducted to explore computer-based learning of neuroanatomy. Using a realistic 3D graphical model of neuroanatomy, and sections derived from the model, exploratory graphical tools were integrated into interactive computer programs so as to allow adaptive exploration. 72 participants learned either sectional anatomy alone or learned whole anatomy followed by sectional anatomy. Sectional anatomy was explored either in perceptually continuous animation or discretely, as in the use of an anatomical atlas. Learning was measured longitudinally to a high performance criterion. After learning, transfer to biomedical images and long-term retention was tested. Learning whole anatomy prior to learning sectional anatomy led to a more efficient learning experience. Learners demonstrated high levels of transfer from whole anatomy to sectional anatomy and from sectional anatomy to complex biomedical images. All learning groups demonstrated high levels of retention at 2--3 weeks.

  20. From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

    Science.gov (United States)

    Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan

    2015-01-01

    This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…

  1. Learner Open Modeling in Adaptive Mobile Learning System for Supporting Student to Learn English

    Directory of Open Access Journals (Sweden)

    Van Cong Pham

    2011-10-01

    Full Text Available This paper represents a personalized context-aware mobile learning architecture for supporting student to learn English as foreign language in order to prepare for TOEFL test. We consider how to apply open learner modeling techniques to adapt contents for different learners based on context, which includes location, amount of time to learn, the manner as well as learner's knowledge in learning progress. Through negotiation with system, the editable learner model will be updated to support adaptive engine to select adaptive contents meeting learner's demands. Empirical testing results for students who used application prototype indicate that interaction user modeling is helpful in supporting learner to learn adaptive materials.

  2. A Coterminous Collaborative Learning Model: Interconnectivity of Leadership and Learning

    Directory of Open Access Journals (Sweden)

    Ilana Margolin

    2012-05-01

    Full Text Available This qualitative ethnographic study examines a collaborative leadership model focused on learning and socially just practices within a change context of a wide educational partnership. The study analyzes a range of perspectives of novice teachers, mentor teachers, teacher educators and district superintendents on leadership and learning. The findings reveal the emergence of a coalition of leaders crossing borders at all levels of the educational system: local school level, district level and teacher education level who were involved in coterminous collaborative learning. Four categories of learning were identified as critical to leading a change in the educational system: learning in professional communities, learning from practice, learning through theory and research and learning from and with leaders. The implications of the study for policy makers as well as for practitioners are to adopt a holistic approach to the educational environment and plan a collaborative learning continuum from initial pre-service programs through professional development learning at all levels.

  3. Constructivism Based Blended Learning in Higher Education

    OpenAIRE

    Al-Huneidi, Ahmad

    2011-01-01

    Blended Learning, which is a mix of online and face-to-face learning, can combine the benefits of both, traditional classroom learning and e-learning environments.3 The aim of this thesis is to explore how to design and implement Blended Learning environment based on Constructivism theory, which focuses on students’ experience to construct the knowledge, in order to increase learning outcomes, performance, and quality in academic institutions. An affective and successful learni...

  4. [Verification of Learning Effects by Team-based Learning].

    Science.gov (United States)

    Ono, Shin-Ichi; Ito, Yoshihisa; Ishige, Kumiko; Inokuchi, Norio; Kosuge, Yasuhiro; Asami, Satoru; Izumisawa, Megumi; Kobayashi, Hiroko; Hayashi, Hiroyuki; Suzuki, Takashi; Kishikawa, Yukinaga; Hata, Harumi; Kose, Eiji; Tabata, Kei-Ichi

    2017-11-01

     It has been recommended that active learning methods, such as team-based learning (TBL) and problem-based learning (PBL), be introduced into university classes by the Central Council for Education. As such, for the past 3 years, we have implemented TBL in a medical therapeutics course for 4-year students. Based upon our experience, TBL is characterized as follows: TBL needs fewer teachers than PBL to conduct a TBL module. TBL enables both students and teachers to recognize and confirm the learning results from preparation and reviewing. TBL grows students' responsibility for themselves and their teams, and likely facilitates learning activities through peer assessment.

  5. Observing and Understanding an On-Line Learning Activity: A Model-Based Approach for Activity Indicator Engineering

    Science.gov (United States)

    Djouad, Tarek; Mille, Alain

    2018-01-01

    Although learning indicators are now properly studied and published, it is still very difficult to manage them freely within most distance learning platforms. As all activity indicators need to collect and analyze properly traces of the learning activity, we propose to use these traces as a starting point for a platform independent Trace…

  6. Covariance-based synaptic plasticity in an attractor network model accounts for fast adaptation in free operant learning.

    Science.gov (United States)

    Neiman, Tal; Loewenstein, Yonatan

    2013-01-23

    In free operant experiments, subjects alternate at will between targets that yield rewards stochastically. Behavior in these experiments is typically characterized by (1) an exponential distribution of stay durations, (2) matching of the relative time spent at a target to its relative share of the total number of rewards, and (3) adaptation after a change in the reward rates that can be very fast. The neural mechanism underlying these regularities is largely unknown. Moreover, current decision-making neural network models typically aim at explaining behavior in discrete-time experiments in which a single decision is made once in every trial, making these models hard to extend to the more natural case of free operant decisions. Here we show that a model based on attractor dynamics, in which transitions are induced by noise and preference is formed via covariance-based synaptic plasticity, can account for the characteristics of behavior in free operant experiments. We compare a specific instance of such a model, in which two recurrently excited populations of neurons compete for higher activity, to the behavior of rats responding on two levers for rewarding brain stimulation on a concurrent variable interval reward schedule (Gallistel et al., 2001). We show that the model is consistent with the rats' behavior, and in particular, with the observed fast adaptation to matching behavior. Further, we show that the neural model can be reduced to a behavioral model, and we use this model to deduce a novel "conservation law," which is consistent with the behavior of the rats.

  7. IoT Security Techniques Based on Machine Learning

    OpenAIRE

    Xiao, Liang; Wan, Xiaoyue; Lu, Xiaozhen; Zhang, Yanyong; Wu, Di

    2018-01-01

    Internet of things (IoT) that integrate a variety of devices into networks to provide advanced and intelligent services have to protect user privacy and address attacks such as spoofing attacks, denial of service attacks, jamming and eavesdropping. In this article, we investigate the attack model for IoT systems, and review the IoT security solutions based on machine learning techniques including supervised learning, unsupervised learning and reinforcement learning. We focus on the machine le...

  8. BEBP: An Poisoning Method Against Machine Learning Based IDSs

    OpenAIRE

    Li, Pan; Liu, Qiang; Zhao, Wentao; Wang, Dongxu; Wang, Siqi

    2018-01-01

    In big data era, machine learning is one of fundamental techniques in intrusion detection systems (IDSs). However, practical IDSs generally update their decision module by feeding new data then retraining learning models in a periodical way. Hence, some attacks that comprise the data for training or testing classifiers significantly challenge the detecting capability of machine learning-based IDSs. Poisoning attack, which is one of the most recognized security threats towards machine learning...

  9. E-learning to supplement and synergise practice-based learning in the emergency department

    Institute of Scientific and Technical Information of China (English)

    Fatimah Lateef

    2012-01-01

    Practice-based learning involves on- the-job learning as well as learning ‘of-the job’ in its realistic setting. It gives trainees and interns the exposure to a diversity of encounters as well as an understanding of the different workplace models, strategies and capabilities. It is now very commonly utilized in teaching and training in medical disciplines. The whole process emphasizes active learning, with collaboration between learners and supervisors, for the eventual delivery of best clinical care to patients.

  10. Personalization and Contextualization of Learning Experiences based on Semantics

    Directory of Open Access Journals (Sweden)

    Nicola Capuano

    2014-04-01

    Full Text Available Context-aware e-learning is an educational model that foresees the selection of learning resources to make the e-learning content more relevant and suitable for the learner in his/her situation. The purpose of this paper is to demonstrate that an ontological approach can be used to define leaning contexts and to allow contextualizing learning experiences finding out relevant topics for each context. To do that, we defined a context model able to formally describe a learning context, an ontology-based model enabling the representation of a teaching domain (including context information and a methodology to generate personalized and context-aware learning experiences starting from them. Based on these theoretical components we improved an existing system for personalized e-learning with contextualisation features and experimented it with real users in two University courses. The results obtained from this experimentation have been compared with those achieved by similar systems.

  11. Web-based Cooperative Learning in College Chemistry Teaching

    Directory of Open Access Journals (Sweden)

    Bin Jiang

    2014-03-01

    Full Text Available With the coming of information era, information process depend on internet and multi-media technology in education becomes the new approach of present teaching model reform. Web-based cooperative learning is becoming a popular learning approach with the rapid development of web technology. The paper aims to how to carry out the teaching strategy of web-based cooperative learning and applied in the foundation chemistry teaching.It was shown that with the support of modern web-based teaching environment, students' cooperative learning capacity and overall competence can be better improved and the problems of interaction in large foundation chemistry classes can be solved. Web-based cooperative learning can improve learning performance of students, what's more Web-based cooperative learning provides students with cooperative skills, communication skills, creativity, critical thinking skills and skills in information technology application.

  12. Electronic learning and constructivism: a model for nursing education.

    Science.gov (United States)

    Kala, Sasikarn; Isaramalai, Sang-Arun; Pohthong, Amnart

    2010-01-01

    Nurse educators are challenged to teach nursing students to become competent professionals, who have both in-depth knowledge and decision-making skills. The use of electronic learning methods has been found to facilitate the teaching-learning process in nursing education. Although learning theories are acknowledged as useful guides to design strategies and activities of learning, integration of these theories into technology-based courses appears limited. Constructivism is a theoretical paradigm that could prove to be effective in guiding the design of electronic learning experiences for the purpose of providing positive outcomes, such as the acquisition of knowledge and decision-making skills. Therefore, the purposes of this paper are to: describe electronic learning, present a brief overview of what is known about the outcomes of electronic learning, discuss constructivism theory, present a model for electronic learning using constructivism, and describe educators' roles emphasizing the utilization of the model in developing electronic learning experiences in nursing education.

  13. Designing for Learning and Play - The Smiley Model as Framework

    DEFF Research Database (Denmark)

    Weitze, Charlotte Lærke

    2016-01-01

    digital games. The Smiley Model inspired and provided a scaffold or a heuristic for the overall gamified learning design –- as well as for the students’ learning game design processes when creating small games turning the learning situation into an engaging experience. The audience for the experiments......This paper presents a framework for designing engaging learning experiences in games – the Smiley Model. In this Design-Based Research project, student-game-designers were learning inside a gamified learning design - while designing and implementing learning goals from curriculum into the small...... was adult upper secondary general students as well as 7th grade primary school students. The intention with this article is to inspire future learning designers that would like to experiment with integrating learning and play....

  14. Qualitative and quantitative analysis of the students’ perceptions to the use of 3D electronic models in problem-based learning

    Directory of Open Access Journals (Sweden)

    Hai Ming Wong

    2017-06-01

    Full Text Available Faculty of Dentistry of the University of Hong Kong has introduced innovative blended problem-based learning (PBL with the aid of 3D electronic models (e-models to Bachelor of Dental Surgery (BDS curriculum. Statistical results of pre- and post-semester questionnaire surveys illustrated compatibility of e-models in PBL settings. The students’ importance ratings of two objectives “Complete assigned tasks on time” and “Active listener”, and twenty-two facilitator evaluation items including critical thinking and group problem-solving skills had increased significantly. The students’ PBL preparation behavior, attentions to problem understanding, problem analysis, and learning resource quality were also found to be related to online support of e-models and its software. Qualitative analysis of open-ended questions with visual text analytic software “Leximancer” improved validity of statistical results. Using e-model functions in treatment planning, problem analysis and giving instructions provided a method of informative communication. Therefore, it is critical for the faculty to continuously provide facilitator training and quality online e-model resources to the students.

  15. From primary care to public health: using Problem-based Learning and the ecological model to teach public health to first year medical students.

    Science.gov (United States)

    Hoover, Cora R; Wong, Candice C; Azzam, Amin

    2012-06-01

    We investigated whether a public health-oriented Problem-Based Learning case presented to first-year medical students conveyed 12 "Population Health Competencies for Medical Students," as recommended by the Association of American Medical Colleges and the Regional Medicine-Public Health Education Centers. A public health-oriented Problem-Based Learning case guided by the ecological model paradigm was developed and implemented among two groups of 8 students at the University of California, Berkeley-UCSF Joint Medical Program, in the Fall of 2010. Using directed content analysis, student-generated written reports were coded for the presence of the 12 population health content areas. Students generated a total of 29 reports, of which 20 (69%) contained information relevant to at least one of the 12 population health competencies. Each of the 12 content areas was addressed by at least one report. As physicians-in-training prepare to confront the challenges of integrating prevention and population health with clinical practice, Problem-Based Learning is a promising tool to enhance medical students' engagement with public health.

  16. N-grams Based Supervised Machine Learning Model for Mobile Agent Platform Protection against Unknown Malicious Mobile Agents

    Directory of Open Access Journals (Sweden)

    Pallavi Bagga

    2017-12-01

    Full Text Available From many past years, the detection of unknown malicious mobile agents before they invade the Mobile Agent Platform has been the subject of much challenging activity. The ever-growing threat of malicious agents calls for techniques for automated malicious agent detection. In this context, the machine learning (ML methods are acknowledged more effective than the Signature-based and Behavior-based detection methods. Therefore, in this paper, the prime contribution has been made to detect the unknown malicious mobile agents based on n-gram features and supervised ML approach, which has not been done so far in the sphere of the Mobile Agents System (MAS security. To carry out the study, the n-grams ranging from 3 to 9 are extracted from a dataset containing 40 malicious and 40 non-malicious mobile agents. Subsequently, the classification is performed using different classifiers. A nested 5-fold cross validation scheme is employed in order to avoid the biasing in the selection of optimal parameters of classifier. The observations of extensive experiments demonstrate that the work done in this paper is suitable for the task of unknown malicious mobile agent detection in a Mobile Agent Environment, and also adds the ML in the interest list of researchers dealing with MAS security.

  17. Vicarious Learning from Human Models in Monkeys

    OpenAIRE

    Falcone, Rossella; Brunamonti, Emiliano; Genovesio, Aldo

    2012-01-01

    We examined whether monkeys can learn by observing a human model, through vicarious learning. Two monkeys observed a human model demonstrating an object-reward association and consuming food found underneath an object. The monkeys observed human models as they solved more than 30 learning problems. For each problem, the human models made a choice between two objects, one of which concealed a piece of apple. In the test phase afterwards, the monkeys made a choice of their own. Learning was app...

  18. Saul: Towards Declarative Learning Based Programming.

    Science.gov (United States)

    Kordjamshidi, Parisa; Roth, Dan; Wu, Hao

    2015-07-01

    We present Saul , a new probabilistic programming language designed to address some of the shortcomings of programming languages that aim at advancing and simplifying the development of AI systems. Such languages need to interact with messy, naturally occurring data, to allow a programmer to specify what needs to be done at an appropriate level of abstraction rather than at the data level, to be developed on a solid theory that supports moving to and reasoning at this level of abstraction and, finally, to support flexible integration of these learning and inference models within an application program. Saul is an object-functional programming language written in Scala that facilitates these by (1) allowing a programmer to learn, name and manipulate named abstractions over relational data; (2) supporting seamless incorporation of trainable (probabilistic or discriminative) components into the program, and (3) providing a level of inference over trainable models to support composition and make decisions that respect domain and application constraints. Saul is developed over a declaratively defined relational data model, can use piecewise learned factor graphs with declaratively specified learning and inference objectives, and it supports inference over probabilistic models augmented with declarative knowledge-based constraints. We describe the key constructs of Saul and exemplify its use in developing applications that require relational feature engineering and structured output prediction.

  19. Contextual Approach with Guided Discovery Learning and Brain Based Learning in Geometry Learning

    Science.gov (United States)

    Kartikaningtyas, V.; Kusmayadi, T. A.; Riyadi

    2017-09-01

    The aim of this study was to combine the contextual approach with Guided Discovery Learning (GDL) and Brain Based Learning (BBL) in geometry learning of junior high school. Furthermore, this study analysed the effect of contextual approach with GDL and BBL in geometry learning. GDL-contextual and BBL-contextual was built from the steps of GDL and BBL that combined with the principles of contextual approach. To validate the models, it uses quasi experiment which used two experiment groups. The sample had been chosen by stratified cluster random sampling. The sample was 150 students of grade 8th in junior high school. The data were collected through the student’s mathematics achievement test that given after the treatment of each group. The data analysed by using one way ANOVA with different cell. The result shows that GDL-contextual has not different effect than BBL-contextual on mathematics achievement in geometry learning. It means both the two models could be used in mathematics learning as the innovative way in geometry learning.

  20. An Evaluation of Effective Factors in Learning Transfer of Nursing On-the-Job Training Courses in Work-Environment Based on Holton’s Transfer Model

    Directory of Open Access Journals (Sweden)

    mehdi mohammadi

    2017-06-01

    Full Text Available Background of Objective: Nursing is one of the health care jobs. In addition to health care, they need to continue education for individual development and be aware of the latest medical science achievements. The main purpose of this study was an evaluation of effective factors in learning transfer of nursing on the job training courses in work environment based on Holton’s transfer model. Materials and Methods: This was a descriptive, cross-sectional study in which the population was all of Jahrom University of Medical Sciences nurses. Passing on-the-job training courses in 2015 was inclusion criterion. Using random sampling method and Cocran formula, 95 nurses were selected. Research instrument was learning transfer system inventory that was distributed after its validity and reliability were calculated. Data was analyzed by inferential statistical methods and SPSS21. Results: The results showed that effective individual, organizational and educational factors in learning transfer of on-the-job training courses in work environment are important. Also, they showed that individual was the most dominant effective factor (P< 0.05. Conclusion: With special attention to the nurse's on- the -job training courses, it is possible to transfer learning to work environment.