Sample records for learning theoretic method
-
Theoretical Foundations of Active Learning
2009-05-01
I study the informational complexity of active learning in a statistical learning theory framework. Specifically, I derive bounds on the rates of...convergence achievable by active learning , under various noise models and under general conditions on the hypothesis class. I also study the theoretical...advantages of active learning over passive learning, and develop procedures for transforming passive learning algorithms into active learning algorithms
-
An e-Learning Theoretical Framework
Aparicio, Manuela; Bacao, Fernando; Oliveira, Tiago
2016-01-01
E-learning systems have witnessed a usage and research increase in the past decade. This article presents the e-learning concepts ecosystem. It summarizes the various scopes on e-learning studies. Here we propose an e-learning theoretical framework. This theory framework is based upon three principal dimensions: users, technology, and services…
-
Theoretical foundations of learning through simulation.
Zigmont, Jason J; Kappus, Liana J; Sudikoff, Stephanie N
2011-04-01
Health care simulation is a powerful educational tool to help facilitate learning for clinicians and change their practice to improve patient outcomes and safety. To promote effective life-long learning through simulation, the educator needs to consider individuals, their experiences, and their environments. Effective education of adults through simulation requires a sound understanding of both adult learning theory and experiential learning. This review article provides a framework for developing and facilitating simulation courses, founded upon empiric and theoretic research in adult and experiential learning. Specifically, this article provides a theoretic foundation for using simulation to change practice to improve patient outcomes and safety. Copyright © 2011 Elsevier Inc. All rights reserved.
-
Qualitative methods in theoretical physics
Maslov, Dmitrii
2018-01-01
This book comprises a set of tools which allow researchers and students to arrive at a qualitatively correct answer without undertaking lengthy calculations. In general, Qualitative Methods in Theoretical Physics is about combining approximate mathematical methods with fundamental principles of physics: conservation laws and symmetries. Readers will learn how to simplify problems, how to estimate results, and how to apply symmetry arguments and conduct dimensional analysis. A comprehensive problem set is included. The book will appeal to a wide range of students and researchers.
-
Theoretical Foundations of Learning Environments. Second Edition
Jonassen, David, Ed.; Land, Susan, Ed.
2012-01-01
"Theoretical Foundations of Learning Environments" provides students, faculty, and instructional designers with a clear, concise introduction to the major pedagogical and psychological theories and their implications for the design of new learning environments for schools, universities, or corporations. Leading experts describe the most…
-
Machine learning a theoretical approach
Natarajan, Balas K
2014-01-01
This is the first comprehensive introduction to computational learning theory. The author's uniform presentation of fundamental results and their applications offers AI researchers a theoretical perspective on the problems they study. The book presents tools for the analysis of probabilistic models of learning, tools that crisply classify what is and is not efficiently learnable. After a general introduction to Valiant's PAC paradigm and the important notion of the Vapnik-Chervonenkis dimension, the author explores specific topics such as finite automata and neural networks. The presentation
-
Information-theoretic semi-supervised metric learning via entropy regularization.
Niu, Gang; Dai, Bo; Yamada, Makoto; Sugiyama, Masashi
2014-08-01
We propose a general information-theoretic approach to semi-supervised metric learning called SERAPH (SEmi-supervised metRic leArning Paradigm with Hypersparsity) that does not rely on the manifold assumption. Given the probability parameterized by a Mahalanobis distance, we maximize its entropy on labeled data and minimize its entropy on unlabeled data following entropy regularization. For metric learning, entropy regularization improves manifold regularization by considering the dissimilarity information of unlabeled data in the unsupervised part, and hence it allows the supervised and unsupervised parts to be integrated in a natural and meaningful way. Moreover, we regularize SERAPH by trace-norm regularization to encourage low-dimensional projections associated with the distance metric. The nonconvex optimization problem of SERAPH could be solved efficiently and stably by either a gradient projection algorithm or an EM-like iterative algorithm whose M-step is convex. Experiments demonstrate that SERAPH compares favorably with many well-known metric learning methods, and the learned Mahalanobis distance possesses high discriminability even under noisy environments.
-
Information theoretic learning Renyi's entropy and Kernel perspectives
Principe, Jose C
2010-01-01
This book presents the first cohesive treatment of Information Theoretic Learning (ITL) algorithms to adapt linear or nonlinear learning machines both in supervised or unsupervised paradigms. ITL is a framework where the conventional concepts of second order statistics (covariance, L2 distances, correlation functions) are substituted by scalars and functions with information theoretic underpinnings, respectively entropy, mutual information and correntropy. ITL quantifies the stochastic structure of the data beyond second order statistics for improved performance without using full-blown Bayesi
-
Theoretical Perspectives of How Digital Natives Learn
Kivunja, Charles
2014-01-01
Marck Prensky, an authority on teaching and learning especially with the aid of Information and Communication Technologies, has referred to 21st century children born after 1980 as "Digital Natives". This paper reviews literature of leaders in the field to shed some light on theoretical perspectives of how Digital Natives learn and how…
-
Information Theoretic-Learning Auto-Encoder
Santana, Eder; Emigh, Matthew; Principe, Jose C
2016-01-01
We propose Information Theoretic-Learning (ITL) divergence measures for variational regularization of neural networks. We also explore ITL-regularized autoencoders as an alternative to variational autoencoding bayes, adversarial autoencoders and generative adversarial networks for randomly generating sample data without explicitly defining a partition function. This paper also formalizes, generative moment matching networks under the ITL framework.
-
Organisational Learning: Theoretical Shortcomings and Practical Challenges
Directory of Open Access Journals (Sweden)
Jon Aarum Andersen
2014-05-01
Full Text Available This paper addresses two problems related to learning and the use of knowledge at work. The first problem is the theoretical shortcomings stemming from the controversy between three different concepts of ‘organisational learning.’ In order to enhance scholarship in this field the notion that organisations - as organisations - can learn need to be rejected for theoretical and empirical reasons. The metaphorical use of ‘organisational learning’ creates only confusion. Learning is a process and knowledge is the outcome of that process. It is argued that learning and knowledge is only related to individuals. Knowledge is thus the individual capability to draw distinctions, within a domain of action, based on an appreciation of context or theory. Consequently, knowledge becomes organisational when it is created, developed and transmitted to other individuals in the organisation. In a strict sense knowledge becomes organisational when employees use it and act based on generalisations due to the rules and procedures found in their organisation. The gravest problem is practical challenges due to the fact that the emphasis on learning, knowledge and competence of the working force do not materialize in the application of the knowledge acquired. It is evident that employees do not use their increased knowledge. However, we do not know why they do not use it. An enormous waste of money is spent on learning and knowledge in organisations which does not yield what is expected. How can managers act in order to enhance the application of increased knowledge possessed by the workforce?
-
The theoretical base of e-learning and its role in surgical education.
Evgeniou, Evgenios; Loizou, Peter
2012-01-01
The advances in Internet and computer technology offer many solutions that can enhance surgical education and increase the effectiveness of surgical teaching. E-learning plays an important role in surgical education today, with many e-learning projects already available on the Internet. E-learning is based on a mixture of educational theories that derive from behaviorist, cognitivist, and constructivist educational theoretical frameworks. CAN EDUCATIONAL THEORY IMPROVE E-LEARNING?: Conventional educational theory can be applied to improve the quality and effectiveness of e-learning. The theory of "threshold concepts" and educational theories on reflection, motivation, and communities of practice can be applied when designing e-learning material. E-LEARNING IN SURGICAL EDUCATION: E-learning has many advantages but also has weaknesses. Studies have shown that e-learning is an effective teaching method that offers high levels of learner satisfaction. Instead of trying to compare e-learning with traditional methods of teaching, it is better to integrate in e-learning elements of traditional teaching that have been proven to be effective. E-learning can play an important role in surgical education as a blended approach, combined with more traditional methods of teaching, which offer better face-to-interaction with patients and colleagues in different circumstances and hands on practice of practical skills. National provision of e-learning can make evaluation easier. The correct utilization of Internet and computer resources combined with the application of valid conventional educational theory to design e-learning relevant to the various levels of surgical training can be effective in the training of future surgeons. Copyright © 2012 Association of Program Directors in Surgery. Published by Elsevier Inc. All rights reserved.
-
Some New Theoretical Issues in Systems Thinking Relevant for Modelling Corporate Learning
Minati, Gianfranco
2007-01-01
Purpose: The purpose of this paper is to describe fundamental concepts and theoretical challenges with regard to systems, and to build on these in proposing new theoretical frameworks relevant to learning, for example in so-called learning organizations. Design/methodology/approach: The paper focuses on some crucial fundamental aspects introduced…
-
A Comparative Study of Pairwise Learning Methods Based on Kernel Ridge Regression.
Stock, Michiel; Pahikkala, Tapio; Airola, Antti; De Baets, Bernard; Waegeman, Willem
2018-06-12
Many machine learning problems can be formulated as predicting labels for a pair of objects. Problems of that kind are often referred to as pairwise learning, dyadic prediction, or network inference problems. During the past decade, kernel methods have played a dominant role in pairwise learning. They still obtain a state-of-the-art predictive performance, but a theoretical analysis of their behavior has been underexplored in the machine learning literature. In this work we review and unify kernel-based algorithms that are commonly used in different pairwise learning settings, ranging from matrix filtering to zero-shot learning. To this end, we focus on closed-form efficient instantiations of Kronecker kernel ridge regression. We show that independent task kernel ridge regression, two-step kernel ridge regression, and a linear matrix filter arise naturally as a special case of Kronecker kernel ridge regression, implying that all these methods implicitly minimize a squared loss. In addition, we analyze universality, consistency, and spectral filtering properties. Our theoretical results provide valuable insights into assessing the advantages and limitations of existing pairwise learning methods.
-
Unsupervised active learning based on hierarchical graph-theoretic clustering.
Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve
2009-10-01
Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.
-
A Learning Method for Neural Networks Based on a Pseudoinverse Technique
Directory of Open Access Journals (Sweden)
Chinmoy Pal
1996-01-01
Full Text Available A theoretical formulation of a fast learning method based on a pseudoinverse technique is presented. The efficiency and robustness of the method are verified with the help of an Exclusive OR problem and a dynamic system identification of a linear single degree of freedom mass–spring problem. It is observed that, compared with the conventional backpropagation method, the proposed method has a better convergence rate and a higher degree of learning accuracy with a lower equivalent learning coefficient. It is also found that unlike the steepest descent method, the learning capability of which is dependent on the value of the learning coefficient ν, the proposed pseudoinverse based backpropagation algorithm is comparatively robust with respect to its equivalent variable learning coefficient. A combination of the pseudoinverse method and the steepest descent method is proposed for a faster, more accurate learning capability.
-
Robust recognition via information theoretic learning
He, Ran; Yuan, Xiaotong; Wang, Liang
2014-01-01
This Springer Brief represents a comprehensive review of information theoretic methods for robust recognition. A variety of information theoretic methods have been proffered in the past decade, in a large variety of computer vision applications; this work brings them together, attempts to impart the theory, optimization and usage of information entropy.The?authors?resort to a new information theoretic concept, correntropy, as a robust measure and apply it to solve robust face recognition and object recognition problems. For computational efficiency,?the brief?introduces the additive and multip
-
Theoretical frameworks for the learning of geometrical reasoning
Jones, Keith
1998-01-01
With the growth in interest in geometrical ideas it is important to be clear about the nature of geometrical reasoning and how it develops. This paper provides an overview of three theoretical frameworks for the learning of geometrical reasoning: the van Hiele model of thinking in geometry, Fischbein’s theory of figural concepts, and Duval’s cognitive model of geometrical reasoning. Each of these frameworks provides theoretical resources to support research into the development of geometrical...
-
Cognitive culture: theoretical and empirical insights into social learning strategies.
Rendell, Luke; Fogarty, Laurel; Hoppitt, William J E; Morgan, Thomas J H; Webster, Mike M; Laland, Kevin N
2011-02-01
Research into social learning (learning from others) has expanded significantly in recent years, not least because of productive interactions between theoretical and empirical approaches. This has been coupled with a new emphasis on learning strategies, which places social learning within a cognitive decision-making framework. Understanding when, how and why individuals learn from others is a significant challenge, but one that is critical to numerous fields in multiple academic disciplines, including the study of social cognition. Copyright © 2010 Elsevier Ltd. All rights reserved.
-
Theoretical Implementations of Various Mobile Applications Used in English Language Learning
Small, Melissa
2014-01-01
This review of the theoretical framework for Mastery Learning Theory and Sense of Community theories is provided in conjunction with a review of the literature for mobile technology in relation to language learning. Although empirical research is minimal for mobile phone technology as an aid for language learning, the empirical research that…
-
Experts in Teams – An experiential learning method
DEFF Research Database (Denmark)
Johansen, Steffen Kjær
2017-01-01
T becomes a learning method rather than a teaching method. Besides discussing the pedagogical characteristics of EiT, the study also gives a general introduction to EiT as it was taught at SDU fall 2016 as well as a brief review of the basic theory behind experiential learning. As such this study serves...... courses. Most of the practical courses are group work along the lines of project based learning. EiT is in a way both. It is a practical course in as much as our students get hands-on experience with interdisciplinary team work and innovation processes. EiT is a theoretical course in as much as our...... both as an introduction to e.g. new teachers of EiT but also as a starting point for a clarification of the features that makes EiT an experiential learning endeavor....
-
Game-Theoretic Learning in Distributed Control
Marden, Jason R.
2018-01-05
In distributed architecture control problems, there is a collection of interconnected decision-making components that seek to realize desirable collective behaviors through local interactions and by processing local information. Applications range from autonomous vehicles to energy to transportation. One approach to control of such distributed architectures is to view the components as players in a game. In this approach, two design considerations are the components’ incentives and the rules that dictate how components react to the decisions of other components. In game-theoretic language, the incentives are defined through utility functions, and the reaction rules are online learning dynamics. This chapter presents an overview of this approach, covering basic concepts in game theory, special game classes, measures of distributed efficiency, utility design, and online learning rules, all with the interpretation of using game theory as a prescriptive paradigm for distributed control design.
-
PROCESS-BASED LEARNING: TOWARDS THEORETICAL AND LECTURE-BASED COURSEWORK IN STUDIO STYLE
Directory of Open Access Journals (Sweden)
Hatem Ezzat Nabih
2010-07-01
Full Text Available This article presents a process-based learning approach to design education where theoretical coursework is taught in studio-style. Lecture-based coursework is sometimes regarded as lacking in challenge and broadening the gap between theory and practice. Furthermore, lecture-based curricula tend to be detached from the studio and deny students from applying their theoretically gained knowledge. Following the belief that student motivation is increased by establishing a higher level of autonomy in the learning process, I argue for a design education that links theory with applied design work within the studio setting. By synthesizing principles of Constructivist Learning and Problem-Based Learning, PBL students are given greater autonomy by being actively involved in their education. Accordingly, I argue for a studio setting that incorporates learning in studio style by presenting three design applications involving students in investigation and experimentation in order to self-experience the design process.
-
Momida, Hiroyoshi; Oguchi, Tamio
2018-04-01
Longitudinal piezoelectric constant (e 33) values of wurtzite materials, which are listed in a structure database, are calculated and analyzed by using first-principles and statistical learning methods. It is theoretically shown that wurtzite materials with high e 33 generally have small lattice constant ratios (c/a) almost independent of constituent elements, and approximately expressed as e 33 ∝ c/a - (c/a)0 with ideal lattice constant ratio (c/a)0. This relation also holds for highly-piezoelectric ternary materials such as Sc x Al1- x N. We conducted a search for high-piezoelectric wurtzite materials by identifying materials with smaller c/a values. It is proposed that the piezoelectricity of ZnO can be significantly enhanced by substitutions of Zn with Ca.
-
Directory of Open Access Journals (Sweden)
Nkenke Emeka
2012-03-01
Full Text Available Abstract Background Technology-enhanced learning (TEL gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired
-
2012-01-01
Background Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. Methods 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Results Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. Conclusions It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology
-
Theoretical physics 7 quantum mechanics : methods and applications
Nolting, Wolfgang
2017-01-01
This textbook offers a clear and comprehensive introduction to methods and applications in quantum mechanics, one of the core components of undergraduate physics courses. It follows on naturally from the previous volumes in this series, thus developing the understanding of quantized states further on. The first part of the book introduces the quantum theory of angular momentum and approximation methods. More complex themes are covered in the second part of the book, which describes multiple particle systems and scattering theory. Ideally suited to undergraduate students with some grounding in the basics of quantum mechanics, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by numerous worked examples and end of chapter problem sets. About the Theoretical Physics series Translated from the renowned and highly successful German editions, the eight volumes of this seri...
-
Learning Algorithm of Boltzmann Machine Based on Spatial Monte Carlo Integration Method
Directory of Open Access Journals (Sweden)
Muneki Yasuda
2018-04-01
Full Text Available The machine learning techniques for Markov random fields are fundamental in various fields involving pattern recognition, image processing, sparse modeling, and earth science, and a Boltzmann machine is one of the most important models in Markov random fields. However, the inference and learning problems in the Boltzmann machine are NP-hard. The investigation of an effective learning algorithm for the Boltzmann machine is one of the most important challenges in the field of statistical machine learning. In this paper, we study Boltzmann machine learning based on the (first-order spatial Monte Carlo integration method, referred to as the 1-SMCI learning method, which was proposed in the author’s previous paper. In the first part of this paper, we compare the method with the maximum pseudo-likelihood estimation (MPLE method using a theoretical and a numerical approaches, and show the 1-SMCI learning method is more effective than the MPLE. In the latter part, we compare the 1-SMCI learning method with other effective methods, ratio matching and minimum probability flow, using a numerical experiment, and show the 1-SMCI learning method outperforms them.
-
A Theoretical Basis for Adult Learning Facilitation: Review of Selected Articles
Muneja, Mussa S.
2015-01-01
The aim of this paper is to synthesize a theoretical basis for adult learning facilitation in order to provide a valuable systematic resource in the field of adult education. The paper has reviewed 6 journal articles with topics ranging from theory of andragogy; the effect of globalization on adult learning; the contribution of Malcolm Knowles;…
-
Parallelization of the ROOT Machine Learning Methods
Vakilipourtakalou, Pourya
2016-01-01
Today computation is an inseparable part of scientific research. Specially in Particle Physics when there is a classification problem like discrimination of Signals from Backgrounds originating from the collisions of particles. On the other hand, Monte Carlo simulations can be used in order to generate a known data set of Signals and Backgrounds based on theoretical physics. The aim of Machine Learning is to train some algorithms on known data set and then apply these trained algorithms to the unknown data sets. However, the most common framework for data analysis in Particle Physics is ROOT. In order to use Machine Learning methods, a Toolkit for Multivariate Data Analysis (TMVA) has been added to ROOT. The major consideration in this report is the parallelization of some TMVA methods, specially Cross-Validation and BDT.
-
Collaborative Learning: Theoretical Foundations and Applicable Strategies to University
Roselli, Nestor D.
2016-01-01
Collaborative learning is a construct that identifies a current strong field, both in face-to-face and virtual education. Firstly, three converging theoretical sources are analyzed: socio-cognitive conflict theory, intersubjectivity theory and distributed cognition theory. Secondly, a model of strategies that can be implemented by teachers to…
-
Imam, Bita; Jarus, Tal
2014-01-01
Objectives. To identify the virtual reality (VR) interventions used for the lower extremity rehabilitation in stroke population and to explain their underlying training mechanisms using Social Cognitive (SCT) and Motor Learning (MLT) theoretical frameworks. Methods. Medline, Embase, Cinahl, and Cochrane databases were searched up to July 11, 2013. Randomized controlled trials that included a VR intervention for lower extremity rehabilitation in stroke population were included. The Physiotherapy Evidence Database (PEDro) scale was used to assess the quality of the included studies. The underlying training mechanisms involved in each VR intervention were explained according to the principles of SCT (vicarious learning, performance accomplishment, and verbal persuasion) and MLT (focus of attention, order and predictability of practice, augmented feedback, and feedback fading). Results. Eleven studies were included. PEDro scores varied from 3 to 7/10. All studies but one showed significant improvement in outcomes in favour of the VR group (P learning through providing a task-oriented and graduated learning under a variable and unpredictable practice.
-
Decentralized indirect methods for learning automata games.
Tilak, Omkar; Martin, Ryan; Mukhopadhyay, Snehasis
2011-10-01
We discuss the application of indirect learning methods in zero-sum and identical payoff learning automata games. We propose a novel decentralized version of the well-known pursuit learning algorithm. Such a decentralized algorithm has significant computational advantages over its centralized counterpart. The theoretical study of such a decentralized algorithm requires the analysis to be carried out in a nonstationary environment. We use a novel bootstrapping argument to prove the convergence of the algorithm. To our knowledge, this is the first time that such analysis has been carried out for zero-sum and identical payoff games. Extensive simulation studies are reported, which demonstrate the proposed algorithm's fast and accurate convergence in a variety of game scenarios. We also introduce the framework of partial communication in the context of identical payoff games of learning automata. In such games, the automata may not communicate with each other or may communicate selectively. This comprehensive framework has the capability to model both centralized and decentralized games discussed in this paper.
-
A review of theoretical perspectives on language learning and acquisition
Directory of Open Access Journals (Sweden)
Norbahira Mohamad Nor
2018-01-01
Full Text Available This paper reviews three main theoretical perspectives on language learning and acquisition in an attempt to elucidate how people acquire their first language (L1 and learn their second language (L2. Behaviorist, Innatist and Interactionist offer different perspectives on language learning and acquisition which influence the acceptance of how an L2 should be taught and learned. This paper also explicates the relationship between L1 and L2, and elaborates on the similarities and differences between the two. This paper concludes that there is no one solid linguistic theory which can provide the ultimate explanation of L1 acquisition and L2 learning as there are many interrelated factors that influence the success of language acquisition or language learning. The implication is that teachers should base their classroom management practices and pedagogical techniques on several theories rather than a single theory as learners learn and acquire language differently. It is hoped that this paper provides useful insights into the complex process involved in language acquisition and learning, and contributes to the increased awareness of the process among the stakeholders in the field of language education. Keywords: behaviorist, innatist, interactionist, language acquisition, second language learning
-
Examining Asymmetrical Relationships of Organizational Learning Antecedents: A Theoretical Model
Directory of Open Access Journals (Sweden)
Ery Tri Djatmika
2016-02-01
Full Text Available Global era is characterized by highly competitive advantage market demand. Responding to the challenge of rapid environmental changes, organizational learning is becoming a strategic way and solution to empower people themselves within the organization in order to create a novelty as valuable positioning source. For research purposes, determining the influential antecedents that affect organizational learning is vital to understand research-based solutions given for practical implications. Accordingly, identification of variables examined by asymmetrical relationships is critical to establish. Possible antecedent variables come from organizational and personal point of views. It is also possible to include a moderating one. A proposed theoretical model of asymmetrical effects of organizational learning and its antecedents is discussed in this article.
-
Hutchings, Maggie; Scammell, Janet; Quinney, Anne
2013-09-01
While there is growing evidence of theoretical perspectives adopted in interprofessional education, learning theories tend to foreground the individual, focusing on psycho-social aspects of individual differences and professional identity to the detriment of considering social-structural factors at work in social practices. Conversely socially situated practice is criticised for being context-specific, making it difficult to draw generalisable conclusions for improving interprofessional education. This article builds on a theoretical framework derived from earlier research, drawing on the dynamics of Dewey's experiential learning theory and Archer's critical realist social theory, to make a case for a meta-theoretical framework enabling social-constructivist and situated learning theories to be interlinked and integrated through praxis and reflexivity. Our current analysis is grounded in an interprofessional curriculum initiative mediated by a virtual community peopled by health and social care users. Student perceptions, captured through quantitative and qualitative data, suggest three major disruptive themes, creating opportunities for congruence and disjuncture and generating a model of zones of interlinked praxis associated with professional differences and identity, pedagogic strategies and technology-mediated approaches. This model contributes to a framework for understanding the complexity of interprofessional learning and offers bridges between individual and structural factors for engaging with the enablements and constraints at work in communities of practice and networks for interprofessional education.
-
A Theoretical Model for Meaning Construction through Constructivist Concept Learning
DEFF Research Database (Denmark)
Badie, Farshad
The central focus of this Ph.D. research is on ‘Logic and Cognition’ and, more specifically, this research covers the quintuple (Logic and Logical Philosophy, Philosophy of Education, Educational Psychology, Cognitive Science, Computer Science). The most significant contributions of this Ph.D. di...... of ‘learning’, ‘mentoring’, and ‘knowledge’ within learning and knowledge acquisition systems. Constructivism as an epistemology and as a model of knowing and, respectively as a theoretical model of learning builds up the central framework of this research........D. dissertation are conceptual, logical, terminological, and semantic analysis of Constructivist Concept Learning (specifically, in the context of humans’ interactions with their environment and with other agents). This dissertation is concerned with the specification of the conceptualisation of the phenomena...
-
Organizational Learning and Product Design Management: Towards a Theoretical Model.
Chiva-Gomez, Ricardo; Camison-Zornoza, Cesar; Lapiedra-Alcami, Rafael
2003-01-01
Case studies of four Spanish ceramics companies were used to construct a theoretical model of 14 factors essential to organizational learning. One set of factors is related to the conceptual-analytical phase of the product design process and the other to the creative-technical phase. All factors contributed to efficient product design management…
-
Geometrical Modification of Learning Vector Quantization Method for Solving Classification Problems
Directory of Open Access Journals (Sweden)
Korhan GÜNEL
2016-09-01
Full Text Available In this paper, a geometrical scheme is presented to show how to overcome an encountered problem arising from the use of generalized delta learning rule within competitive learning model. It is introduced a theoretical methodology for describing the quantization of data via rotating prototype vectors on hyper-spheres.The proposed learning algorithm is tested and verified on different multidimensional datasets including a binary class dataset and two multiclass datasets from the UCI repository, and a multiclass dataset constructed by us. The proposed method is compared with some baseline learning vector quantization variants in literature for all domains. Large number of experiments verify the performance of our proposed algorithm with acceptable accuracy and macro f1 scores.
-
Llorens, Ariadna; Berbegal-Mirabent, Jasmina; Llinàs-Audet, Xavier
2017-07-01
Engineering education is facing new challenges to effectively provide the appropriate skills to future engineering professionals according to market demands. This study proposes a model based on active learning methods, which is expected to facilitate the acquisition of the professional skills most highly valued in the information and communications technology (ICT) market. The theoretical foundations of the study are based on the specific literature on active learning methodologies. The Delphi method is used to establish the fit between learning methods and generic skills required by the ICT sector. An innovative proposition is therefore presented that groups the required skills in relation to the teaching method that best develops them. The qualitative research suggests that a combination of project-based learning and the learning contract is sufficient to ensure a satisfactory skills level for this profile of engineers.
-
Improved machine learning method for analysis of gas phase chemistry of peptides
Directory of Open Access Journals (Sweden)
Ahn Natalie
2008-12-01
Full Text Available Abstract Background Accurate peptide identification is important to high-throughput proteomics analyses that use mass spectrometry. Search programs compare fragmentation spectra (MS/MS of peptides from complex digests with theoretically derived spectra from a database of protein sequences. Improved discrimination is achieved with theoretical spectra that are based on simulating gas phase chemistry of the peptides, but the limited understanding of those processes affects the accuracy of predictions from theoretical spectra. Results We employed a robust data mining strategy using new feature annotation functions of MAE software, which revealed under-prediction of the frequency of occurrence in fragmentation of the second peptide bond. We applied methods of exploratory data analysis to pre-process the information in the MS/MS spectra, including data normalization and attribute selection, to reduce the attributes to a smaller, less correlated set for machine learning studies. We then compared our rule building machine learning program, DataSqueezer, with commonly used association rules and decision tree algorithms. All used machine learning algorithms produced similar results that were consistent with expected properties for a second gas phase mechanism at the second peptide bond. Conclusion The results provide compelling evidence that we have identified underlying chemical properties in the data that suggest the existence of an additional gas phase mechanism for the second peptide bond. Thus, the methods described in this study provide a valuable approach for analyses of this kind in the future.
-
Directory of Open Access Journals (Sweden)
Viktoriia Kalamazh
2016-06-01
Full Text Available In this research the theoretical principles of psychological analysis of group project activity of students in the process of learning foreign language are defined on the basis of subject-activity, socio-psychological and cognitive paradigms. The approaches of different authors to the understanding of the concept of project and in particular group project activity are considered. The difficulties of the theoretical analysis of this specific notion are indicated due to the considerable variety of subjects, types and forms of the pedagogical activity, academic disciplines regarding which the researches are being carried out. Not disclosed aspects of organizing the group project activity of students are being determined, among them is a project group as an autonomous subject of joint activity for the realization students’ project activity while learning a foreign language; forming psychological readiness of teacher and student to use project method; the role of metacognitive aspect in the surrounding, where the project activity is being carried out; group functioning through the project work as a subject of group examination. It has been indicated that the analysis of project activity as an innovative technology must include its assessment as a condition of student’s developing as a subject of learning activity, his personal, socio-psychological, intellectual and professional self-perfection. Three levels of subjectivity in group project activity are being distinguished: teacher; each particular student; and student project group. Interaction between teacher and student is based on subject-subject relations. An organization of a project activity while learning a foreign language is considered as the one in which the student is moving in order to get the manager position and to master the basis of expert knowledge. Hereby, the main stress is on the group role as a subject of group examination, and also on metacognitive character of the
-
Proverbs as Theoretical Frameworks for Lifelong Learning in Indigenous African Education
Avoseh, Mejai B. M.
2013-01-01
Every aspect of a community's life and values in indigenous Africa provide the theoretical framework for education. The holistic worldview of the traditional system places a strong emphasis on the centrality of the human element and orature in the symmetrical relationship between life and learning. This article focuses on proverbs and the words…
-
Reasons and Methods to Learn the Management
Li, Hongxin; Ding, Mengchun
2010-01-01
Reasons for learning the management include (1) perfecting the knowledge structure, (2) the management is the base of all organizations, (3) one person may be the manager or the managed person, (4) the management is absolutely not simple knowledge, and (5) the learning of the theoretical knowledge of the management can not be replaced by the…
-
Theoretical-methodical Fundamentals of industrial marketing research
Butenko, N.
2009-01-01
The article proves the necessity to research theoretical and methodical fundamentals of industrial marketing and defines main key aspects of relationship management with the customers on industrial market.
-
Machine learning methods for planning
Minton, Steven
1993-01-01
Machine Learning Methods for Planning provides information pertinent to learning methods for planning and scheduling. This book covers a wide variety of learning methods and learning architectures, including analogical, case-based, decision-tree, explanation-based, and reinforcement learning.Organized into 15 chapters, this book begins with an overview of planning and scheduling and describes some representative learning systems that have been developed for these tasks. This text then describes a learning apprentice for calendar management. Other chapters consider the problem of temporal credi
-
Falk, Kristin; Falk, Hanna; Jakobsson Ung, Eva
2016-01-01
A key area for consideration is determining how optimal conditions for learning can be created. Higher education in nursing aims to prepare students to develop their capabilities to become independent professionals. The aim of this study was to evaluate the effects of sequencing clinical practice prior to theoretical studies on student's experiences of self-directed learning readiness and students' approach to learning in the second year of a three-year undergraduate study program in nursing. 123 nursing students was included in the study and divided in two groups. In group A (n = 60) clinical practice preceded theoretical studies. In group (n = 63) theoretical studies preceded clinical practice. Learning readiness was measured using the Directed Learning Readiness Scale for Nursing Education (SDLRSNE), and learning process was measured using the revised two-factor version of the Study Process Questionnaire (R-SPQ-2F). Students were also asked to write down their personal reflections throughout the course. By using a mixed method design, the qualitative component focused on the students' personal experiences in relation to the sequencing of theoretical studies and clinical practice. The quantitative component provided information about learning readiness before and after the intervention. Our findings confirm that students are sensitive and adaptable to their learning contexts, and that the sequencing of courses is subordinate to a pedagogical style enhancing students' deep learning approaches, which needs to be incorporated in the development of undergraduate nursing programs. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Nkenke, Emeka; Vairaktaris, Elefterios; Bauersachs, Anne; Eitner, Stephan; Budach, Alexander; Knipfer, Christoph; Stelzle, Florian
2012-03-30
Technology-enhanced learning (TEL) gives a view to improved education. However, there is a need to clarify how TEL can be used effectively. The study compared students' attitudes and opinions towards a traditional face-to-face course on theoretical radiological science and a TEL course where students could combine face-to-face lectures and e-learning modules at their best convenience. 42 third-year dental students were randomly assigned to the traditional face-to-face group and the TEL group. Both groups completed questionnaires before the beginning and after completion of the course on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning. After completion of the course both groups also filled in the validated German-language TRIL (Trierer Inventar zur Lehrevaluation) questionnaire for the evaluation of courses given at universities. Both groups had a positive attitude towards e-learning that did not change over time. The TEL group attended significantly less face-to-face lectures than the traditional group. However, both groups stated that face-to-face lectures were the basis for education in a theoretical radiological science course. The members of the TEL group rated e-mail reminders significantly more important when they filled in the questionnaire on attitudes and opinions towards a traditional face-to-face lectures and technology-enhanced learning for the second time after completion of the course. The members of the technology-enhanced learning group were significantly less confident in passing the exam compared to the members of the traditional group. However, examination results did not differ significantly for traditional and the TEL group. It seems that technology-enhanced learning in a theoretical radiological science course has the potential to reduce the need for face-to-face lectures. At the same time examination results are not impaired. However, technology-enhanced learning cannot completely replace
-
Subsampled Hessian Newton Methods for Supervised Learning.
Wang, Chien-Chih; Huang, Chun-Heng; Lin, Chih-Jen
2015-08-01
Newton methods can be applied in many supervised learning approaches. However, for large-scale data, the use of the whole Hessian matrix can be time-consuming. Recently, subsampled Newton methods have been proposed to reduce the computational time by using only a subset of data for calculating an approximation of the Hessian matrix. Unfortunately, we find that in some situations, the running speed is worse than the standard Newton method because cheaper but less accurate search directions are used. In this work, we propose some novel techniques to improve the existing subsampled Hessian Newton method. The main idea is to solve a two-dimensional subproblem per iteration to adjust the search direction to better minimize the second-order approximation of the function value. We prove the theoretical convergence of the proposed method. Experiments on logistic regression, linear SVM, maximum entropy, and deep networks indicate that our techniques significantly reduce the running time of the subsampled Hessian Newton method. The resulting algorithm becomes a compelling alternative to the standard Newton method for large-scale data classification.
-
Engineers' Perceptions of Diversity and the Learning Environment at Work: A Mixed Methods Study
Firestone, Brenda L.
2012-01-01
The purpose of this dissertation research study was to investigate engineers' perceptions of diversity and the workplace learning environment surrounding diversity education efforts in engineering occupations. The study made use of a mixed methods methodology and was theoretically framed using a critical feminist adult education lens and…
-
Asiri, Mohammed J. Sherbib; Mahmud, Rosnaini bt; Bakar, Kamariah Abu; Ayub, Ahmad Fauzi bin Mohd
2012-01-01
The purpose of this paper is to present the theoretical framework underlying a research on factors that influence utilization of the Jusur Learning Management System (Jusur LMS) in Saudi Arabian public universities. Development of the theoretical framework was done based on library research approach. Initially, the existing literature relevant to…
-
Directory of Open Access Journals (Sweden)
Bita Imam
2014-01-01
Full Text Available Objectives. To identify the virtual reality (VR interventions used for the lower extremity rehabilitation in stroke population and to explain their underlying training mechanisms using Social Cognitive (SCT and Motor Learning (MLT theoretical frameworks. Methods. Medline, Embase, Cinahl, and Cochrane databases were searched up to July 11, 2013. Randomized controlled trials that included a VR intervention for lower extremity rehabilitation in stroke population were included. The Physiotherapy Evidence Database (PEDro scale was used to assess the quality of the included studies. The underlying training mechanisms involved in each VR intervention were explained according to the principles of SCT (vicarious learning, performance accomplishment, and verbal persuasion and MLT (focus of attention, order and predictability of practice, augmented feedback, and feedback fading. Results. Eleven studies were included. PEDro scores varied from 3 to 7/10. All studies but one showed significant improvement in outcomes in favour of the VR group (P<0.05. Ten VR interventions followed the principle of performance accomplishment. All the eleven VR interventions directed subject’s attention externally, whereas nine provided training in an unpredictable and variable fashion. Conclusions. The results of this review suggest that VR applications used for lower extremity rehabilitation in stroke population predominantly mediate learning through providing a task-oriented and graduated learning under a variable and unpredictable practice.
-
Cooperative Learning in Elementary Schools
Slavin, Robert E.
2015-01-01
Cooperative learning refers to instructional methods in which students work in small groups to help each other learn. Although cooperative learning methods are used for different age groups, they are particularly popular in elementary (primary) schools. This article discusses methods and theoretical perspectives on cooperative learning for the…
-
Cooperative Learning as a Democratic Learning Method
Erbil, Deniz Gökçe; Kocabas, Ayfer
2018-01-01
In this study, the effects of applying the cooperative learning method on the students' attitude toward democracy in an elementary 3rd-grade life studies course was examined. Over the course of 8 weeks, the cooperative learning method was applied with an experimental group, and traditional methods of teaching life studies in 2009, which was still…
-
A Graphical Evolutionary Game Approach to Social Learning
Cao, Xuanyu; Liu, K. J. Ray
2017-06-01
In this work, we study the social learning problem, in which agents of a networked system collaborate to detect the state of the nature based on their private signals. A novel distributed graphical evolutionary game theoretic learning method is proposed. In the proposed game-theoretic method, agents only need to communicate their binary decisions rather than the real-valued beliefs with their neighbors, which endows the method with low communication complexity. Under mean field approximations, we theoretically analyze the steady state equilibria of the game and show that the evolutionarily stable states (ESSs) coincide with the decisions of the benchmark centralized detector. Numerical experiments are implemented to confirm the effectiveness of the proposed game-theoretic learning method.
-
Qualitative methods in workplace learning
Fabritius, Hannele
2015-01-01
Methods of learning in the workplace will be introduced. The methods are connect to competence development and to the process of conducting development discussions in a dialogical way. The tools developed and applied are a fourfold table, a cycle of work identity, a plan of personal development targets, a learning meeting and a learning map. The methods introduced will aim to better learning at work.
-
Surface physics theoretical models and experimental methods
Mamonova, Marina V; Prudnikova, I A
2016-01-01
The demands of production, such as thin films in microelectronics, rely on consideration of factors influencing the interaction of dissimilar materials that make contact with their surfaces. Bond formation between surface layers of dissimilar condensed solids-termed adhesion-depends on the nature of the contacting bodies. Thus, it is necessary to determine the characteristics of adhesion interaction of different materials from both applied and fundamental perspectives of surface phenomena. Given the difficulty in obtaining reliable experimental values of the adhesion strength of coatings, the theoretical approach to determining adhesion characteristics becomes more important. Surface Physics: Theoretical Models and Experimental Methods presents straightforward and efficient approaches and methods developed by the authors that enable the calculation of surface and adhesion characteristics for a wide range of materials: metals, alloys, semiconductors, and complex compounds. The authors compare results from the ...
-
Pennefather, Jane
2016-01-01
This article focuses on a theoretical model that I am developing in order to understand student teacher learning in a rural context and the enabling conditions that can support this learning. The question of whether a supervised teaching practice in a rural context can contribute to the development of student teacher professional learning and…
-
Lessons learned: advantages and disadvantages of mixed method research
DEFF Research Database (Denmark)
Malina, Mary A.; Nørreklit, Hanne; Selto, Frank H.
2011-01-01
on the use and usefulness of a specialized balanced scorecard; and third, to encourage researchers to actually use multiple methods and sources of data to address the very many accounting phenomena that are not fully understood. Design/methodology/approach – This paper is an opinion piece based...... on the authors' experience conducting a series of longitudinal mixed method studies. Findings – The authors suggest that in many studies, using a mixed method approach provides the best opportunity for addressing research questions. Originality/value – This paper provides encouragement to those who may wish......Purpose – The purpose of this paper is first, to discuss the theoretical assumptions, qualities, problems and myopia of the dominating quantitative and qualitative approaches; second, to describe the methodological lessons that the authors learned while conducting a series of longitudinal studies...
-
Nanoscale thermal transport: Theoretical method and application
Zeng, Yu-Jia; Liu, Yue-Yang; Zhou, Wu-Xing; Chen, Ke-Qiu
2018-03-01
With the size reduction of nanoscale electronic devices, the heat generated by the unit area in integrated circuits will be increasing exponentially, and consequently the thermal management in these devices is a very important issue. In addition, the heat generated by the electronic devices mostly diffuses to the air in the form of waste heat, which makes the thermoelectric energy conversion also an important issue for nowadays. In recent years, the thermal transport properties in nanoscale systems have attracted increasing attention in both experiments and theoretical calculations. In this review, we will discuss various theoretical simulation methods for investigating thermal transport properties and take a glance at several interesting thermal transport phenomena in nanoscale systems. Our emphasizes will lie on the advantage and limitation of calculational method, and the application of nanoscale thermal transport and thermoelectric property. Project supported by the Nation Key Research and Development Program of China (Grant No. 2017YFB0701602) and the National Natural Science Foundation of China (Grant No. 11674092).
-
Gurpinar, Erol; Alimoglu, Mustafa Kemal; Mamakli, Sumer; Aktekin, Mehmet
2010-12-01
The curriculum of our medical school has a hybrid structure including both traditional training (lectures) and problem-based learning (PBL) applications. The purpose of this study was to determine the learning styles of our medical students and investigate the relation of learning styles with each of satisfaction with different instruction methods and academic achievement in them. This study was carried out with the participation of 170 first-year medical students (the participation rate was 91.4%). The researchers prepared sociodemographic and satisfaction questionnaires to determine the characteristics of the participants and their satisfaction levels with traditional training and PBL. The Kolb learning styles inventory was used to explore the learning styles of the study group. The participants completed all forms at the end of the first year of medical education. Indicators of academic achievement were scores of five theoretical block exams and five PBL exams performed throughout the academic year of 2008-2009. The majority of the participants took part in the "diverging" (n = 84, 47.7%) and "assimilating" (n = 73, 41.5%) groups. Numbers of students in the "converging" and "accommodating" groups were 11 (6.3%) and 8 (4.5%), respectively. In all learning style groups, PBL satisfaction scores were significantly higher than those of traditional training. Exam scores for "PBL and traditional training" did not differ among the four learning styles. In logistic regression analysis, learning style (assimilating) predicted student satisfaction with traditional training and success in theoretical block exams. Nothing predicted PBL satisfaction and success. This is the first study conducted among medical students evaluating the relation of learning style with student satisfaction and academic achievement. More research with larger groups is needed to generalize our results. Some learning styles may relate to satisfaction with and achievement in some instruction methods.
-
Symbolic interactionism as a theoretical perspective for multiple method research.
Benzies, K M; Allen, M N
2001-02-01
Qualitative and quantitative research rely on different epistemological assumptions about the nature of knowledge. However, the majority of nurse researchers who use multiple method designs do not address the problem of differing theoretical perspectives. Traditionally, symbolic interactionism has been viewed as one perspective underpinning qualitative research, but it is also the basis for quantitative studies. Rooted in social psychology, symbolic interactionism has a rich intellectual heritage that spans more than a century. Underlying symbolic interactionism is the major assumption that individuals act on the basis of the meaning that things have for them. The purpose of this paper is to present symbolic interactionism as a theoretical perspective for multiple method designs with the aim of expanding the dialogue about new methodologies. Symbolic interactionism can serve as a theoretical perspective for conceptually clear and soundly implemented multiple method research that will expand the understanding of human health behaviour.
-
Ensemble Machine Learning Methods and Applications
Ma, Yunqian
2012-01-01
It is common wisdom that gathering a variety of views and inputs improves the process of decision making, and, indeed, underpins a democratic society. Dubbed “ensemble learning” by researchers in computational intelligence and machine learning, it is known to improve a decision system’s robustness and accuracy. Now, fresh developments are allowing researchers to unleash the power of ensemble learning in an increasing range of real-world applications. Ensemble learning algorithms such as “boosting” and “random forest” facilitate solutions to key computational issues such as face detection and are now being applied in areas as diverse as object trackingand bioinformatics. Responding to a shortage of literature dedicated to the topic, this volume offers comprehensive coverage of state-of-the-art ensemble learning techniques, including various contributions from researchers in leading industrial research labs. At once a solid theoretical study and a practical guide, the volume is a windfall for r...
-
Takeda, Kayoko; Takahashi, Kiyoshi; Masukawa, Hiroyuki; Shimamori, Yoshimitsu
2017-01-01
Recently, the practice of active learning has spread, increasingly recognized as an essential component of academic studies. Classes incorporating small group discussion (SGD) are conducted at many universities. At present, assessments of the effectiveness of SGD have mostly involved evaluation by questionnaires conducted by teachers, by peer assessment, and by self-evaluation of students. However, qualitative data, such as open-ended descriptions by students, have not been widely evaluated. As a result, we have been unable to analyze the processes and methods involved in how students acquire knowledge in SGD. In recent years, due to advances in information and communication technology (ICT), text mining has enabled the analysis of qualitative data. We therefore investigated whether the introduction of a learning system comprising the jigsaw method and problem-based learning (PBL) would improve student attitudes toward learning; we did this by text mining analysis of the content of student reports. We found that by applying the jigsaw method before PBL, we were able to improve student attitudes toward learning and increase the depth of their understanding of the area of study as a result of working with others. The use of text mining to analyze qualitative data also allowed us to understand the processes and methods by which students acquired knowledge in SGD and also changes in students' understanding and performance based on improvements to the class. This finding suggests that the use of text mining to analyze qualitative data could enable teachers to evaluate the effectiveness of various methods employed to improve learning.
-
Oussalah, Abderrahim; Fournier, Jean-Paul; Guéant, Jean-Louis; Braun, Marc
2015-01-01
Abstract Data regarding knowledge acquisition during residency training are sparse. Predictors of theoretical learning quality, academic career achievements and evidence-based medical practice during residency are unknown. We performed a cross-sectional study on residents and attending physicians across several residency programs in 2 French faculties of medicine. We comprehensively evaluated the information-seeking behavior (I-SB) during residency using a standardized questionnaire and looked for independent predictors of theoretical learning quality, academic career achievements, and evidence-based medical practice among I-SB components using multivariate logistic regression analysis. Between February 2013 and May 2013, 338 fellows and attending physicians were included in the study. Textbooks and international medical journals were reported to be used on a regular basis by 24% and 57% of the respondents, respectively. Among the respondents, 47% refer systematically (4.4%) or frequently (42.6%) to published guidelines from scientific societies upon their publication. The median self-reported theoretical learning quality score was 5/10 (interquartile range, 3–6; range, 1–10). A high theoretical learning quality score (upper quartile) was independently and strongly associated with the following I-SB components: systematic reading of clinical guidelines upon their publication (odds ratio [OR], 5.55; 95% confidence interval [CI], 1.77–17.44); having access to a library that offers the leading textbooks of the specialty in the medical department (OR, 2.45, 95% CI, 1.33–4.52); knowledge of the specialty leading textbooks (OR, 2.12; 95% CI, 1.09–4.10); and PubMed search skill score ≥5/10 (OR, 1.94; 95% CI, 1.01–3.73). Research Master (M2) and/or PhD thesis enrolment were independently and strongly associated with the following predictors: PubMed search skill score ≥5/10 (OR, 4.10; 95% CI, 1.46–11.53); knowledge of the leading medical journals of the
-
DEFF Research Database (Denmark)
Iwarsson, Jenny
2014-01-01
A typical goal of voice therapy is a behavioral change in the patient’s everyday speech. The SLP’s plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit...... are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3...... change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy...
-
Institute of Scientific and Technical Information of China (English)
Zi-zhen XU; Ye-fei WANG; Yan WANG; Shu CHENG; Yi-qun HU; Lei DING
2015-01-01
Objective To explore the application and the effect of the case based learning(CBL)method in clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.Methods The CBL method was applied to the experimental group,and the traditional approach for the control group.After the lecture,a questionnaire survey was conducted to evaluate the teaching effect in the two groups.Results The CBL method efficiently increased the students’interest in learning and autonomous learning ability,enhanced their ability to solve clinical problems with basic theoretic knowledge and cultivated their clinical thinking ability.Conclusion The CBL method can improve the quality of clinical probation teaching of the integrated curriculum of hematology among eight-year-program medical students.
-
International Nuclear Information System (INIS)
Wigger, Lothar; Buenger, Carsten
2017-01-01
The book on the educational and learning theoretical reflection of nuclear disasters as a consequence of Fukushima includes contributions on the following issues: pedagogical approach: children write on Fukushima, description of the reality as pedagogical challenge; lessons learned on the nuclear technology - perspectives and limits of pedagogical evaluation: moral education - Japanese teaching materials, educational challenges at the universities with respect to nuclear technology and technology impact assessment; education and technology - questions concerning the pedagogical responsibility: considerations on the responsibility of scientists, on the discrepancy between technology and education, disempowerment of the public by structural corruption - nuclear disaster and post-democratic tendencies in Japan.
-
Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn
Directory of Open Access Journals (Sweden)
Dwi Nur Rachmah
2017-12-01
Full Text Available Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas Lambung Mangkurat. The method used in the study is the experimental method using one group pre-test and post-test design. The results of the measurements before and after the use of jigsaw learning method were compared using paired samples t-test. The results showed that there is a difference in students’ self-efficacy and motivation to learn before and after subjected to the treatments; therefore, it can be said that jigsaw learning method had significant effects on self-efficacy and motivation to learn. The application of jigsaw learning model in a classroom with large number of students was the discussion of this study.
-
Set-theoretic methods in control
Blanchini, Franco
2015-01-01
The second edition of this monograph describes the set-theoretic approach for the control and analysis of dynamic systems, both from a theoretical and practical standpoint. This approach is linked to fundamental control problems, such as Lyapunov stability analysis and stabilization, optimal control, control under constraints, persistent disturbance rejection, and uncertain systems analysis and synthesis. Completely self-contained, this book provides a solid foundation of mathematical techniques and applications, extensive references to the relevant literature, and numerous avenues for further theoretical study. All the material from the first edition has been updated to reflect the most recent developments in the field, and a new chapter on switching systems has been added. Each chapter contains examples, case studies, and exercises to allow for a better understanding of theoretical concepts by practical application. The mathematical language is kept to the minimum level necessary for the adequate for...
-
Information-Theoretic Inference of Large Transcriptional Regulatory Networks
Directory of Open Access Journals (Sweden)
Meyer Patrick
2007-01-01
Full Text Available The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy (MRMR, an effective information-theoretic technique for feature selection in supervised learning. The MRMR principle consists in selecting among the least redundant variables the ones that have the highest mutual information with the target. MRNET extends this feature selection principle to networks in order to infer gene-dependence relationships from microarray data. The paper assesses MRNET by benchmarking it against RELNET, CLR, and ARACNE, three state-of-the-art information-theoretic methods for large (up to several thousands of genes network inference. Experimental results on thirty synthetically generated microarray datasets show that MRNET is competitive with these methods.
-
Information-Theoretic Inference of Large Transcriptional Regulatory Networks
Directory of Open Access Journals (Sweden)
Patrick E. Meyer
2007-06-01
Full Text Available The paper presents MRNET, an original method for inferring genetic networks from microarray data. The method is based on maximum relevance/minimum redundancy (MRMR, an effective information-theoretic technique for feature selection in supervised learning. The MRMR principle consists in selecting among the least redundant variables the ones that have the highest mutual information with the target. MRNET extends this feature selection principle to networks in order to infer gene-dependence relationships from microarray data. The paper assesses MRNET by benchmarking it against RELNET, CLR, and ARACNE, three state-of-the-art information-theoretic methods for large (up to several thousands of genes network inference. Experimental results on thirty synthetically generated microarray datasets show that MRNET is competitive with these methods.
-
Iwarsson, Jenny
2015-12-01
A typical goal of voice therapy is a behavioral change in the patient's everyday speech. The SLP's plan for voice therapy should therefore optimally include strategies for automatization. The aim of the present study was to identify and describe factors that promote behavioral learning and habit change in voice behavior and have the potential to affect patient compliance and thus therapy outcome. Research literature from the areas of motor and behavioral learning, habit formation, and habit change was consulted. Also, specific elements from personal experience of clinical voice therapy are described and discussed from a learning theory perspective. Nine factors that seem to be relevant to facilitate behavioral learning and habit change in voice therapy are presented, together with related practical strategies and theoretical underpinnings. These are: 1) Cue-altering; 2) Attention exercises; 3) Repetition; 4) Cognitive activation; 5) Negative practice; 6) Inhibition through interruption; 7) Decomposing complex behavior; 8) The 'each time-every time' principle; and 9) Successive implementation of automaticity.
-
Directory of Open Access Journals (Sweden)
Sergiu Ciprian Catinas
2015-07-01
Full Text Available A detailed theoretical and practical investigation of the reinforced concrete elements is due to recent techniques and method that are implemented in the construction market. More over a theoretical study is a demand for a better and faster approach nowadays due to rapid development of the calculus technique. The paper above will present a study for implementing in a static calculus the direct stiffness matrix method in order capable to address phenomena related to different stages of loading, rapid change of cross section area and physical properties. The method is a demand due to the fact that in our days the FEM (Finite Element Method is the only alternative to such a calculus and FEM are considered as expensive methods from the time and calculus resources point of view. The main goal in such a method is to create the moment-curvature diagram in the cross section that is analyzed. The paper above will express some of the most important techniques and new ideas as well in order to create the moment curvature graphic in the cross sections considered.
-
Hodson, Derek
2014-01-01
This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…
-
Kruppa, Jochen; Liu, Yufeng; Biau, Gérard; Kohler, Michael; König, Inke R; Malley, James D; Ziegler, Andreas
2014-07-01
Probability estimation for binary and multicategory outcome using logistic and multinomial logistic regression has a long-standing tradition in biostatistics. However, biases may occur if the model is misspecified. In contrast, outcome probabilities for individuals can be estimated consistently with machine learning approaches, including k-nearest neighbors (k-NN), bagged nearest neighbors (b-NN), random forests (RF), and support vector machines (SVM). Because machine learning methods are rarely used by applied biostatisticians, the primary goal of this paper is to explain the concept of probability estimation with these methods and to summarize recent theoretical findings. Probability estimation in k-NN, b-NN, and RF can be embedded into the class of nonparametric regression learning machines; therefore, we start with the construction of nonparametric regression estimates and review results on consistency and rates of convergence. In SVMs, outcome probabilities for individuals are estimated consistently by repeatedly solving classification problems. For SVMs we review classification problem and then dichotomous probability estimation. Next we extend the algorithms for estimating probabilities using k-NN, b-NN, and RF to multicategory outcomes and discuss approaches for the multicategory probability estimation problem using SVM. In simulation studies for dichotomous and multicategory dependent variables we demonstrate the general validity of the machine learning methods and compare it with logistic regression. However, each method fails in at least one simulation scenario. We conclude with a discussion of the failures and give recommendations for selecting and tuning the methods. Applications to real data and example code are provided in a companion article (doi:10.1002/bimj.201300077). © 2014 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.
-
Directory of Open Access Journals (Sweden)
maila dinia husni rahim
2016-03-01
Full Text Available As adults, we often believe that children are only interested with games and children’s ‘stuff’. However research has shown that children do indeed show a greater interest in the world around them, including about politics, elections, and democracy. If we need to teach children about democracy, what are the best methods of teaching democracy to young children? Narrative is considered as an effective medium to convey messages to children and discuss hard subjects. This paper is a theoretical exploration that looks at the narrative approach to teaching and learning about democracy with young children. The researchers has used a literature review to look at why narratives should be used, what narratives should be used and how to use narratives.
-
Statistical learning methods: Basics, control and performance
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de
2006-04-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms.
-
Statistical learning methods: Basics, control and performance
International Nuclear Information System (INIS)
Zimmermann, J.
2006-01-01
The basics of statistical learning are reviewed with a special emphasis on general principles and problems for all different types of learning methods. Different aspects of controlling these methods in a physically adequate way will be discussed. All principles and guidelines will be exercised on examples for statistical learning methods in high energy and astrophysics. These examples prove in addition that statistical learning methods very often lead to a remarkable performance gain compared to the competing classical algorithms
-
Effects of Jigsaw Learning Method on Students’ Self-Efficacy and Motivation to Learn
Dwi Nur Rachmah
2017-01-01
Jigsaw learning as a cooperative learning method, according to the results of some studies, can improve academic skills, social competence, behavior in learning, and motivation to learn. However, in some other studies, there are different findings regarding the effect of jigsaw learning method on self-efficacy. The purpose of this study is to examine the effects of jigsaw learning method on self-efficacy and motivation to learn in psychology students at the Faculty of Medicine, Universitas La...
-
[Learning strategies of autonomous medical students].
Márquez U, Carolina; Fasce H, Eduardo; Ortega B, Javiera; Bustamante D, Carolina; Pérez V, Cristhian; Ibáñez G, Pilar; Ortiz M, Liliana; Espinoza P, Camila; Bastías V, Nancy
2015-12-01
Understanding how autonomous students are capable of regulating their own learning process is essential to develop self-directed teaching methods. To understand how self-directed medical students approach learning in medical schools at University of Concepción, Chile. A qualitative and descriptive study, performed according to Grounded Theory guidelines, following Strauss & Corbin was performed. Twenty medical students were selected by the maximum variation sampling method. The data collection technique was carried out by a semi-structured thematic interview. Students were interviewed by researchers after an informed consent procedure. Data were analyzed by the open coding method using Atlas-ti 7.5.2 software. Self-directed learners were characterized by being good planners and managing their time correctly. Students performed a diligent selection of contents to study based on reliable literature sources, theoretical relevance and type of evaluation. They also emphasized the discussion of clinical cases, where theoretical contents can be applied. This modality allows them to gain a global view of theoretical contents, to verbalize knowledge and to obtain a learning feedback. The learning process of autonomous students is intentional and planned.
-
Cooperative learning and academic achievement: why does groupwork work?
Directory of Open Access Journals (Sweden)
Robert E. Slavin
2014-10-01
Full Text Available Cooperative learning refers to instructional methods in which students work in small groups to help each other learn. Four major theoretical perspectives on achievement effects of cooperative learning are reviewed: Motivational, social cohesion, developmental, and cognitive elaboration. Evidence from practical classroom research primarily supports the motivational perspective, which emphasizes the use of group goals and individual accountability for group success. However, there are conditions under which methods derived from all four theoretical perspectives contribute to achievement gain. This chapter reconciles these perspectives in a unified theory of cooperative learning effects.
-
Tao, Ying; Li, Liping; Xu, Qunyan; Jiang, Anli
2015-11-01
This paper demonstrates the establishment of an extra-curricular education program in Chinese context and evaluates its effectiveness on undergraduate nursing students' self-directed learning. Zimmerman's self-directed learning model was used as the theoretical framework for the development of an education program. Mixed-method was applied in this research study. 165 undergraduate students from a nursing college were divided into experimental group (n=32) and control group (n=133). Pre- and post-tests were implemented to evaluate the effectiveness of this education program using the self-directed learning scale of nursing undergraduates. Qualitative interview was undertaken within participants from the experimental group to obtain their insights into the influence of this program. Both quantitative and qualitative analyses showed that the program contributed to nursing students' self-directed learning ability. In the experimental group, the post-test score showed an increase compared with pretest score (plearning activities and influence on learning environment. It can be found in the qualitative analysis that learners benefited from this program. The education program contributes to the improvement of nursing undergraduates' self-directed learning. Various pedagogic methods could be applied for self-directed learning. Copyright © 2015 Elsevier Ltd. All rights reserved.
-
Theoretical concepts of X-ray nanoscale analysis theory and applications
Benediktovitch, Andrei; Ulyanenkov, Alexander
2013-01-01
This book provides a concise survey of modern theoretical concepts of X-ray materials analysis. The principle features of the book are: basics of X-ray scattering, interaction between X-rays and matter and new theoretical concepts of X-ray scattering. The various X-ray techniques are considered in detail: high-resolution X-ray diffraction, X-ray reflectivity, grazing-incidence small-angle X-ray scattering and X-ray residual stress analysis. All the theoretical methods presented use the unified physical approach. This makes the book especially useful for readers learning and performing data ana
-
Geometrical methods in learning theory
International Nuclear Information System (INIS)
Burdet, G.; Combe, Ph.; Nencka, H.
2001-01-01
The methods of information theory provide natural approaches to learning algorithms in the case of stochastic formal neural networks. Most of the classical techniques are based on some extremization principle. A geometrical interpretation of the associated algorithms provides a powerful tool for understanding the learning process and its stability and offers a framework for discussing possible new learning rules. An illustration is given using sequential and parallel learning in the Boltzmann machine
-
Transnational Learning Processes
DEFF Research Database (Denmark)
Nedergaard, Peter
This paper analyses and compares the transnational learning processes in the employment field in the European Union and among the Nordic countries. Based theoretically on a social constructivist model of learning and methodologically on a questionnaire distributed to the relevant participants......, a number of hypotheses concerning transnational learning processes are tested. The paper closes with a number of suggestions regarding an optimal institutional setting for facilitating transnational learning processes.Key words: Transnational learning, Open Method of Coordination, Learning, Employment......, European Employment Strategy, European Union, Nordic countries....
-
Oussalah, Abderrahim; Fournier, Jean-Paul; Guéant, Jean-Louis; Braun, Marc
2015-02-01
Data regarding knowledge acquisition during residency training are sparse. Predictors of theoretical learning quality, academic career achievements and evidence-based medical practice during residency are unknown. We performed a cross-sectional study on residents and attending physicians across several residency programs in 2 French faculties of medicine. We comprehensively evaluated the information-seeking behavior (I-SB) during residency using a standardized questionnaire and looked for independent predictors of theoretical learning quality, academic career achievements, and evidence-based medical practice among I-SB components using multivariate logistic regression analysis. Between February 2013 and May 2013, 338 fellows and attending physicians were included in the study. Textbooks and international medical journals were reported to be used on a regular basis by 24% and 57% of the respondents, respectively. Among the respondents, 47% refer systematically (4.4%) or frequently (42.6%) to published guidelines from scientific societies upon their publication. The median self-reported theoretical learning quality score was 5/10 (interquartile range, 3-6; range, 1-10). A high theoretical learning quality score (upper quartile) was independently and strongly associated with the following I-SB components: systematic reading of clinical guidelines upon their publication (odds ratio [OR], 5.55; 95% confidence interval [CI], 1.77-17.44); having access to a library that offers the leading textbooks of the specialty in the medical department (OR, 2.45, 95% CI, 1.33-4.52); knowledge of the specialty leading textbooks (OR, 2.12; 95% CI, 1.09-4.10); and PubMed search skill score ≥5/10 (OR, 1.94; 95% CI, 1.01-3.73). Research Master (M2) and/or PhD thesis enrolment were independently and strongly associated with the following predictors: PubMed search skill score ≥5/10 (OR, 4.10; 95% CI, 1.46-11.53); knowledge of the leading medical journals of the specialty (OR, 3.33; 95
-
Deep learning versus traditional machine learning methods for aggregated energy demand prediction
Paterakis, N.G.; Mocanu, E.; Gibescu, M.; Stappers, B.; van Alst, W.
2018-01-01
In this paper the more advanced, in comparison with traditional machine learning approaches, deep learning methods are explored with the purpose of accurately predicting the aggregated energy consumption. Despite the fact that a wide range of machine learning methods have been applied to
-
Effect of Methods of Learning and Self Regulated Learning toward Outcomes of Learning Social Studies
Tjalla, Awaluddin; Sofiah, Evi
2015-01-01
This research aims to reveal the influence of learning methods and self-regulated learning on students learning scores for Social Studies object. The research was done in Islamic Junior High School (MTs Manba'ul Ulum), Batuceper City Tangerang using quasi-experimental method. The research employed simple random technique to 28 students. Data were…
-
DEFF Research Database (Denmark)
Nedergaard, Peter
The purpose of this paper is solely to address two interlinked methodological and theoretical questions concerning the Open Method of Coordination (OMC), using the European Employment Strategy as a case: First, what is the most appropriate approach to learning in the analyses of the processes...... of the European Employment Strategy (EES)? Second, how is mutual learning processes diffused among the Member States? In answering these two questions the paper draws on a social constructivist approach to learning thereby contributing to the debate about learning in the political science literature. At the same...... time, based on this concept of learning, it is concluded that the learning effects of the EES are probably somewhat larger than what is normally suggested, but that successful diffusion still depends on a variety of contextual factors....
-
Teaching learning methods of an entrepreneurship curriculum
Directory of Open Access Journals (Sweden)
KERAMAT ESMI
2015-10-01
Full Text Available Introduction: One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners’ needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation Methods: This is a mixed method research of a sequential exploratory kind conducted through two stages: a developing teaching methods of entrepreneurship curriculum, and b validating developed framework. Data were collected through “triangulation” (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts. Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability, and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach’s alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results: Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of
-
The method of global learning in teaching foreign languages
Directory of Open Access Journals (Sweden)
Tatjana Dragovič
2001-12-01
Full Text Available The authors describe the method of global learning of foreign languages, which is based on the principles of neurolinguistic programming (NLP. According to this theory, the educator should use the method of the so-called periphery learning, where students learn relaxation techniques and at the same time they »incidentally « or subconsciously learn a foreign language. The method of global learning imitates successful strategies of learning in early childhood and therefore creates a relaxed attitude towards learning. Global learning is also compared with standard methods.
-
Topal, Kenan; Sarıkaya, Özlem; Basturk, Ramazan; Buke, Akile
2015-01-01
Objectives: The process of development and evaluation of undergraduate medical education programs should include analysis of learners’ characteristics, needs, and perceptions about learning methods. This study aims to evaluate medical students’ perceptions about problem-based learning methods and to compare these results with their individual learning styles.Materials and Methods: The survey was conducted at Marmara University Medical School where problem-based learning was implemented in the...
-
Collaborative Learning: Theoretical Foundations and Applicable Strategies to University Teaching
Directory of Open Access Journals (Sweden)
Nestor D. Roselli
2016-04-01
Full Text Available Collaborative learning is a construct that identifies a current strong field, both in face-to-face and virtual education. Firstly, three converging theoretical sources are analyzed: socio-cognitive conflict theory, intersubjectivity theory and distributed cognition theory. Secondly, a model of strategies that can be implemented by teachers to develop socio-cognitive collaboration is presented. This model integrates and systematizes several academic group animation techniques developed within the collaborative learning field. These integrated techniques, within a coherent and unified didactic intention, allow talking more about strategies than independent and dissociated techniques. Each strategy is specifically described, which refers to six areas: encouragement of dialogue, listening to others and reciprocal assessment; collaboration for negotiation and consensus building; activity organization; study and appropriation of bibliographic information; conceptual development; collective writing. These strategies proposed (designed to stimulate the collaboration between 2, 4 and exceptionally, 6 or 8 students are not the only possible strategies, they can be combined with the ones the teacher might suggest. The strict pattern of each strategy is a characteristic of the proposal. The teacher is also encouraged to benchmark the results obtained using each strategy and those obtained using individual or non-collaborative strategies. Finally, conclusions and recommendations for the implementation of these strategies are discussed.
-
Teaching learning methods of an entrepreneurship curriculum.
Esmi, Keramat; Marzoughi, Rahmatallah; Torkzadeh, Jafar
2015-10-01
One of the most significant elements of entrepreneurship curriculum design is teaching-learning methods, which plays a key role in studies and researches related to such a curriculum. It is the teaching method, and systematic, organized and logical ways of providing lessons that should be consistent with entrepreneurship goals and contents, and should also be developed according to the learners' needs. Therefore, the current study aimed to introduce appropriate, modern, and effective methods of teaching entrepreneurship and their validation. This is a mixed method research of a sequential exploratory kind conducted through two stages: a) developing teaching methods of entrepreneurship curriculum, and b) validating developed framework. Data were collected through "triangulation" (study of documents, investigating theoretical basics and the literature, and semi-structured interviews with key experts). Since the literature on this topic is very rich, and views of the key experts are vast, directed and summative content analysis was used. In the second stage, qualitative credibility of research findings was obtained using qualitative validation criteria (credibility, confirmability, and transferability), and applying various techniques. Moreover, in order to make sure that the qualitative part is reliable, reliability test was used. Moreover, quantitative validation of the developed framework was conducted utilizing exploratory and confirmatory factor analysis methods and Cronbach's alpha. The data were gathered through distributing a three-aspect questionnaire (direct presentation teaching methods, interactive, and practical-operational aspects) with 29 items among 90 curriculum scholars. Target population was selected by means of purposive sampling and representative sample. Results obtained from exploratory factor analysis showed that a three factor structure is an appropriate method for describing elements of teaching-learning methods of entrepreneurship curriculum
-
Directory of Open Access Journals (Sweden)
Susana Correnti
2016-01-01
Full Text Available The «PBL working environment» is a virtual environment developed in the framework of SCENE project (profeSsional development for an effeCtive PBL approach: a practical experiENce through ICT-enabled lEarning solution, co-funded by the European Lifelong Learning Program. The «PBL working environment» is devoted to prepare headmasters and teachers of secondary and vocational schools to use Problem-Based Learning (PBL pedagogy effectively. It is a student-centered pedagogy where learners are «actively» engaged in real world problems to solve or challenges to meet. Students develop problem-solving, self-directed learning and team skills. The «PBL working environment» is an virtual tool including three main elements: e-learning platform, virtual facilitator and PBL repository. Teachers, trainers and headmasters/school managers learn the PBL pedagogy by attending an on-line course (e-learning platform delivered through the «inductive method». It allows learners to experience PBL approach, by practicing it stage by stage, and then learn to turn practice into theory by abstracting their experience to build a theoretical understanding. Since generating the proper scenario is the most critical aspect of PBL, after benefiting from the on-line course, users can benefit from a further support: the Virtual Facilitator. It provides tips and hints on how correctly design a problem scenario and by asking questions to collect data on user's specific needs. The Virtual Facilitator is able to provide a/or more suitable example(s which match as closest as possible the teacher/trainer need. Finally, users can share problem scenarios and projects of different subjects of studies and with different characteristics uploaded and downloaded in the PBL repository.
-
Reflexive Learning through Visual Methods
DEFF Research Database (Denmark)
Frølunde, Lisbeth
2014-01-01
What. This chapter concerns how visual methods and visual materials can support visually oriented, collaborative, and creative learning processes in education. The focus is on facilitation (guiding, teaching) with visual methods in learning processes that are designerly or involve design. Visual...... methods are exemplified through two university classroom cases about collaborative idea generation processes. The visual methods and materials in the cases are photo elicitation using photo cards, and modeling with LEGO Serious Play sets. Why. The goal is to encourage the reader, whether student...... or professional, to facilitate with visual methods in a critical, reflective, and experimental way. The chapter offers recommendations for facilitating with visual methods to support playful, emergent designerly processes. The chapter also has a critical, situated perspective. Where. This chapter offers case...
-
An Innovative Teaching Method To Promote Active Learning: Team-Based Learning
Balasubramanian, R.
2007-12-01
Traditional teaching practice based on the textbook-whiteboard- lecture-homework-test paradigm is not very effective in helping students with diverse academic backgrounds achieve higher-order critical thinking skills such as analysis, synthesis, and evaluation. Consequently, there is a critical need for developing a new pedagogical approach to create a collaborative and interactive learning environment in which students with complementary academic backgrounds and learning skills can work together to enhance their learning outcomes. In this presentation, I will discuss an innovative teaching method ('Team-Based Learning (TBL)") which I recently developed at National University of Singapore to promote active learning among students in the environmental engineering program with learning abilities. I implemented this new educational activity in a graduate course. Student feedback indicates that this pedagogical approach is appealing to most students, and promotes active & interactive learning in class. Data will be presented to show that the innovative teaching method has contributed to improved student learning and achievement.
-
Pamungkas, Bian Dwi
2017-01-01
This study aims to examine the contribution of learning methods on learning output, the contribution of facilities and infrastructure on output learning, the contribution of learning resources on learning output, and the contribution of learning methods, the facilities and infrastructure, and learning resources on learning output. The research design is descriptive causative, using a goal-oriented assessment approach in which the assessment focuses on assessing the achievement of a goal. The ...
-
DEFF Research Database (Denmark)
Nedergaard, Peter
2005-01-01
The purpose of this paper is to address two normative and interlinked methodological and theoretical questions concerning the Open Method of Coordination (OMC): First, what is the most appropriate approach to learning in the analyses of the processes of the European Employment Strategy (EES......)? Second, how should mutual learning processes be diffused among the Member States in order to be efficient? In answering these two questions the paper draws on a social constructivist approach to learning thereby contributing to the debate about learning in the political science literature. At the same...... time, based on the literature and participatory observations, it is concluded that the learning effects of the EES are probably somewhat larger than what is normally suggested, but that successful diffusion still depends on a variety of contextual factors. At the end of the paper a path for empirical...
-
Game-theoretic interference coordination approaches for dynamic spectrum access
Xu, Yuhua
2016-01-01
Written by experts in the field, this book is based on recent research findings in dynamic spectrum access for cognitive radio networks. It establishes a game-theoretic framework and presents cutting-edge technologies for distributed interference coordination. With game-theoretic formulation and the designed distributed learning algorithms, it provides insights into the interactions between multiple decision-makers and the converging stable states. Researchers, scientists and engineers in the field of cognitive radio networks will benefit from the book, which provides valuable information, useful methods and practical algorithms for use in emerging 5G wireless communication.
-
New e-learning method using databases
Directory of Open Access Journals (Sweden)
Andreea IONESCU
2012-10-01
Full Text Available The objective of this paper is to present a new e-learning method that use databases. The solution could pe implemented for any typeof e-learning system in any domain. The article will purpose a solution to improve the learning process for virtual classes.
-
Theoretical Coalescence: A Method to Develop Qualitative Theory: The Example of Enduring.
Morse, Janice M
Qualitative research is frequently context bound, lacks generalizability, and is limited in scope. The purpose of this article was to describe a method, theoretical coalescence, that provides a strategy for analyzing complex, high-level concepts and for developing generalizable theory. Theoretical coalescence is a method of theoretical expansion, inductive inquiry, of theory development, that uses data (rather than themes, categories, and published extracts of data) as the primary source for analysis. Here, using the development of the lay concept of enduring as an example, I explore the scientific development of the concept in multiple settings over many projects and link it within the Praxis Theory of Suffering. As comprehension emerges when conducting theoretical coalescence, it is essential that raw data from various different situations be available for reinterpretation/reanalysis and comparison to identify the essential features of the concept. The concept is then reconstructed, with additional inquiry that builds description, and evidence is conducted and conceptualized to create a more expansive concept and theory. By utilizing apparently diverse data sets from different contexts that are linked by certain characteristics, the essential features of the concept emerge. Such inquiry is divergent and less bound by context yet purposeful, logical, and with significant pragmatic implications for practice in nursing and beyond our discipline. Theoretical coalescence is a means by which qualitative inquiry is broadened to make an impact, to accommodate new theoretical shifts and concepts, and to make qualitative research applied and accessible in new ways.
-
Strongly Correlated Systems Theoretical Methods
Avella, Adolfo
2012-01-01
The volume presents, for the very first time, an exhaustive collection of those modern theoretical methods specifically tailored for the analysis of Strongly Correlated Systems. Many novel materials, with functional properties emerging from macroscopic quantum behaviors at the frontier of modern research in physics, chemistry and materials science, belong to this class of systems. Any technique is presented in great detail by its own inventor or by one of the world-wide recognized main contributors. The exposition has a clear pedagogical cut and fully reports on the most relevant case study where the specific technique showed to be very successful in describing and enlightening the puzzling physics of a particular strongly correlated system. The book is intended for advanced graduate students and post-docs in the field as textbook and/or main reference, but also for other researchers in the field who appreciates consulting a single, but comprehensive, source or wishes to get acquainted, in a as painless as po...
-
Model United Nations and Deep Learning: Theoretical and Professional Learning
Engel, Susan; Pallas, Josh; Lambert, Sarah
2017-01-01
This article demonstrates that the purposeful subject design, incorporating a Model United Nations (MUN), facilitated deep learning and professional skills attainment in the field of International Relations. Deep learning was promoted in subject design by linking learning objectives to Anderson and Krathwohl's (2001) four levels of knowledge or…
-
Creating the learning situation to promote student deep learning: Data analysis and application case
Guo, Yuanyuan; Wu, Shaoyan
2017-05-01
How to lead students to deeper learning and cultivate engineering innovative talents need to be studied for higher engineering education. In this study, through the survey data analysis and theoretical research, we discuss the correlation of teaching methods, learning motivation, and learning methods. In this research, we find that students have different motivation orientation according to the perception of teaching methods in the process of engineering education, and this affects their choice of learning methods. As a result, creating situations is critical to lead students to deeper learning. Finally, we analyze the process of learning situational creation in the teaching process of «bidding and contract management workshops». In this creation process, teachers use the student-centered teaching to lead students to deeper study. Through the study of influence factors of deep learning process, and building the teaching situation for the purpose of promoting deep learning, this thesis provide a meaningful reference for enhancing students' learning quality, teachers' teaching quality and the quality of innovation talent.
-
Active learning methods for interactive image retrieval.
Gosselin, Philippe Henri; Cord, Matthieu
2008-07-01
Active learning methods have been considered with increased interest in the statistical learning community. Initially developed within a classification framework, a lot of extensions are now being proposed to handle multimedia applications. This paper provides algorithms within a statistical framework to extend active learning for online content-based image retrieval (CBIR). The classification framework is presented with experiments to compare several powerful classification techniques in this information retrieval context. Focusing on interactive methods, active learning strategy is then described. The limitations of this approach for CBIR are emphasized before presenting our new active selection process RETIN. First, as any active method is sensitive to the boundary estimation between classes, the RETIN strategy carries out a boundary correction to make the retrieval process more robust. Second, the criterion of generalization error to optimize the active learning selection is modified to better represent the CBIR objective of database ranking. Third, a batch processing of images is proposed. Our strategy leads to a fast and efficient active learning scheme to retrieve sets of online images (query concept). Experiments on large databases show that the RETIN method performs well in comparison to several other active strategies.
-
Assessing a Theoretical Model on EFL College Students
Chang, Yu-Ping
2011-01-01
This study aimed to (1) integrate relevant language learning models and theories, (2) construct a theoretical model of college students' English learning performance, and (3) assess the model fit between empirically observed data and the theoretical model proposed by the researchers of this study. Subjects of this study were 1,129 Taiwanese EFL…
-
Adaptive e-learning methods and IMS Learning Design. An integrated approach
Burgos, Daniel; Specht, Marcus
2006-01-01
Please, cite this publication as: Burgos, D., & Specht, M. (2006). Adaptive e-learning methods and IMS Learning Design. In Kinshuk, R. Koper, P. Kommers, P. Kirschner, D. G. Sampson & W. Didderen (Eds.), Proceedings of the 6th IEEE International Conference on Advanced Learning Technologies (pp.
-
Psychotherapy Integration via Theoretical Unification
Directory of Open Access Journals (Sweden)
Warren W. Tryon
2017-01-01
Full Text Available Meaningful psychotherapy integration requires theoretical unification because psychotherapists can only be expected to treat patients with the same diagnoses similarly if they understand these disorders similarly and if they agree on the mechanisms by which effective treatments work. Tryon (in press has proposed a transtheoretic transdiagnostic psychotherapy based on an Applied Psychological Science (APS clinical orientation, founded on a BioPsychology Network explanatory system that provides sufficient theoretical unification to support meaningful psychotherapy integration. That proposal focused mainly on making a neuroscience argument. This article makes a different argument for theoretical unification and consequently psychotherapy integration. The strength of theories of psychotherapy, like all theory, is to focus on certain topics, goals, and methods. But this strength is also a weakness because it can blind one to alternative perspectives and thereby promote unnecessary competition among therapies. This article provides a broader perspective based on learning and memory that is consistent with the behavioral, cognitive, cognitive-behavioral, psychodynamic, pharmacologic, and Existential/Humanistic/Experiential clinical orientations. It thereby provides a basis for meaningful psychotherapy integration.
-
Gunthorpe, Sydney
2006-01-01
From the assumption that matching a student's learning style with the learning method best suited for the student, it follows that developing courses that correlate learning method with learning style would be more successful for students. Albuquerque Technical Vocational Institute (TVI) in New Mexico has attempted to provide students with more…
-
A Semantic Reasoning Method Towards Ontological Model for Automated Learning Analysis
Okoye, Kingsley; Tawil, Abdel-Rahman; Naeem, Usman; Lamine, Elyes
2015-01-01
Semantic reasoning can help solve the problem of regulating the evolving and static measures of knowledge at theoretical and technological levels. The technique has been proven to enhance the capability of process models by making inferences, retaining and applying what they have learned as well as discovery of new processes. The work in this paper propose a semantic rule-based approach directed towards discovering learners interaction patterns within a learning knowledge base, and then respo...
-
Automatic Detection of Acromegaly From Facial Photographs Using Machine Learning Methods.
Kong, Xiangyi; Gong, Shun; Su, Lijuan; Howard, Newton; Kong, Yanguo
2018-01-01
Automatic early detection of acromegaly is theoretically possible from facial photographs, which can lessen the prevalence and increase the cure probability. In this study, several popular machine learning algorithms were used to train a retrospective development dataset consisting of 527 acromegaly patients and 596 normal subjects. We firstly used OpenCV to detect the face bounding rectangle box, and then cropped and resized it to the same pixel dimensions. From the detected faces, locations of facial landmarks which were the potential clinical indicators were extracted. Frontalization was then adopted to synthesize frontal facing views to improve the performance. Several popular machine learning methods including LM, KNN, SVM, RT, CNN, and EM were used to automatically identify acromegaly from the detected facial photographs, extracted facial landmarks, and synthesized frontal faces. The trained models were evaluated using a separate dataset, of which half were diagnosed as acromegaly by growth hormone suppression test. The best result of our proposed methods showed a PPV of 96%, a NPV of 95%, a sensitivity of 96% and a specificity of 96%. Artificial intelligence can automatically early detect acromegaly with a high sensitivity and specificity. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.
-
Cross analysis of knowledge and learning methods followed by French residents in cardiology.
Menet, Aymeric; Assez, Nathalie; Lacroix, Dominique
2015-01-01
No scientific assessment of the theoretical teaching of cardiology in France is available. To analyse the impact of the available teaching modalities on the theoretical knowledge of French residents in cardiology. Electronic questionnaires were returned by 283 residents. In the first part, an inventory of the teaching/learning methods was taken, using 21 questions (Yes/No format). The second part was a knowledge test, comprising 15 multiple-choice questions, exploring the core curriculum. Of the 21 variables tested, four emerged as independent predictors of the score obtained in the knowledge test: access to self-assessment (P=0.0093); access to teaching methods other than lectures (P=0.036); systematic discussion about clinical decisions (P=0.013); and the opportunity to prepare and give lectures (P=0.039). The fifth variable was seniority in residency (P=0.0003). Each item of the knowledge test was analysed independently: the score was higher when teaching the item was driven by reading guidelines and was lower if the item had not been covered by the programme (Pcardiology by involving students in the training, by using teaching methods other than lectures and by facilitating access to self-assessment. The use of digital tools may be a particularly effective approach. Copyright © 2015 Elsevier Masson SAS. All rights reserved.
-
A Swarm-Based Learning Method Inspired by Social Insects
He, Xiaoxian; Zhu, Yunlong; Hu, Kunyuan; Niu, Ben
Inspired by cooperative transport behaviors of ants, on the basis of Q-learning, a new learning method, Neighbor-Information-Reference (NIR) learning method, is present in the paper. This is a swarm-based learning method, in which principles of swarm intelligence are strictly complied with. In NIR learning, the i-interval neighbor's information, namely its discounted reward, is referenced when an individual selects the next state, so that it can make the best decision in a computable local neighborhood. In application, different policies of NIR learning are recommended by controlling the parameters according to time-relativity of concrete tasks. NIR learning can remarkably improve individual efficiency, and make swarm more "intelligent".
-
Less is more: regularization perspectives on large scale machine learning
CERN. Geneva
2017-01-01
Deep learning based techniques provide a possible solution at the expanse of theoretical guidance and, especially, of computational requirements. It is then a key challenge for large scale machine learning to devise approaches guaranteed to be accurate and yet computationally efficient. In this talk, we will consider a regularization perspectives on machine learning appealing to classical ideas in linear algebra and inverse problems to scale-up dramatically nonparametric methods such as kernel methods, often dismissed because of prohibitive costs. Our analysis derives optimal theoretical guarantees while providing experimental results at par or out-performing state of the art approaches.
-
Methods for control over learning individual trajectory
Mitsel, A. A.; Cherniaeva, N. V.
2015-09-01
The article discusses models, methods and algorithms of determining student's optimal individual educational trajectory. A new method of controlling the learning trajectory has been developed as a dynamic model of learning trajectory control, which uses score assessment to construct a sequence of studied subjects.
-
Alabdulmohsin, Ibrahim Mansour
2017-05-07
Active learning is a subfield of machine learning that has been successfully used in many applications. One of the main branches of active learning is query synthe- sis, where the learning agent constructs artificial queries from scratch in order to reveal sensitive information about the underlying decision boundary. It has found applications in areas, such as adversarial reverse engineering, automated science, and computational chemistry. Nevertheless, the existing literature on membership query synthesis has, generally, focused on finite concept classes or toy problems, with a limited extension to real-world applications. In this thesis, I develop two spectral algorithms for learning halfspaces via query synthesis. The first algorithm is a maximum-determinant convex optimization method while the second algorithm is a Markovian method that relies on Khachiyan’s classical update formulas for solving linear programs. The general theme of these methods is to construct an ellipsoidal approximation of the version space and to synthesize queries, afterward, via spectral decomposition. Moreover, I also describe how these algorithms can be extended to other settings as well, such as pool-based active learning. Having demonstrated that halfspaces can be learned quite efficiently via query synthesis, the second part of this thesis proposes strategies for mitigating the risk of reverse engineering in adversarial environments. One approach that can be used to render query synthesis algorithms ineffective is to implement a randomized response. In this thesis, I propose a semidefinite program (SDP) for learning a distribution of classifiers, subject to the constraint that any individual classifier picked at random from this distributions provides reliable predictions with a high probability. This algorithm is, then, justified both theoretically and empirically. A second approach is to use a non-parametric classification method, such as similarity-based classification. In this
-
In silico machine learning methods in drug development.
Dobchev, Dimitar A; Pillai, Girinath G; Karelson, Mati
2014-01-01
Machine learning (ML) computational methods for predicting compounds with pharmacological activity, specific pharmacodynamic and ADMET (absorption, distribution, metabolism, excretion and toxicity) properties are being increasingly applied in drug discovery and evaluation. Recently, machine learning techniques such as artificial neural networks, support vector machines and genetic programming have been explored for predicting inhibitors, antagonists, blockers, agonists, activators and substrates of proteins related to specific therapeutic targets. These methods are particularly useful for screening compound libraries of diverse chemical structures, "noisy" and high-dimensional data to complement QSAR methods, and in cases of unavailable receptor 3D structure to complement structure-based methods. A variety of studies have demonstrated the potential of machine-learning methods for predicting compounds as potential drug candidates. The present review is intended to give an overview of the strategies and current progress in using machine learning methods for drug design and the potential of the respective model development tools. We also regard a number of applications of the machine learning algorithms based on common classes of diseases.
-
The Guided Autobiography Method: A Learning Experience
Thornton, James E.
2008-01-01
This article discusses the proposition that learning is an unexplored feature of the guided autobiography method and its developmental exchange. Learning, conceptualized and explored as the embedded and embodied processes, is essential in narrative activities of the guided autobiography method leading to psychosocial development and growth in…
-
Learning Methods for Dynamic Topic Modeling in Automated Behavior Analysis.
Isupova, Olga; Kuzin, Danil; Mihaylova, Lyudmila
2017-09-27
Semisupervised and unsupervised systems provide operators with invaluable support and can tremendously reduce the operators' load. In the light of the necessity to process large volumes of video data and provide autonomous decisions, this paper proposes new learning algorithms for activity analysis in video. The activities and behaviors are described by a dynamic topic model. Two novel learning algorithms based on the expectation maximization approach and variational Bayes inference are proposed. Theoretical derivations of the posterior estimates of model parameters are given. The designed learning algorithms are compared with the Gibbs sampling inference scheme introduced earlier in the literature. A detailed comparison of the learning algorithms is presented on real video data. We also propose an anomaly localization procedure, elegantly embedded in the topic modeling framework. It is shown that the developed learning algorithms can achieve 95% success rate. The proposed framework can be applied to a number of areas, including transportation systems, security, and surveillance.
-
Lacedón Montemayor, Marta
2016-01-01
Treball Final de Grau en Administració d'Empreses. Codi: AE1049. Curs: 2015/2016 The objective of this paper is to examine the influence that leadership has on creating a good working environment, on work teams and on organisational learning, through a theoretical revision. For this, concepts are addressed related to leadership such as the leader's profile, the role he represents within an organisation, his functions and skills, which will help us understand the importance of ...
-
Introducing the Collaborative E-Learning Design Method (CoED)
DEFF Research Database (Denmark)
Ryberg, Thomas; Buus, Lillian; Nyvang, Tom
2015-01-01
In this chapter, a specific learning design method is introduced and explained, namely the Collaborative E-learning Design method (CoED), which has been developed through various projects in “e-Learning Lab – Centre for User Driven Innovation, Learning and Design” (Nyvang & Georgsen, 2007). We br...
-
Everly, Marcee C
2013-02-01
To report the transformation from lecture to more active learning methods in a maternity nursing course and to evaluate whether student perception of improved learning through active-learning methods is supported by improved test scores. The process of transforming a course into an active-learning model of teaching is described. A voluntary mid-semester survey for student acceptance of the new teaching method was conducted. Course examination results, from both a standardized exam and a cumulative final exam, among students who received lecture in the classroom and students who had active learning activities in the classroom were compared. Active learning activities were very acceptable to students. The majority of students reported learning more from having active-learning activities in the classroom rather than lecture-only and this belief was supported by improved test scores. Students who had active learning activities in the classroom scored significantly higher on a standardized assessment test than students who received lecture only. The findings support the use of student reflection to evaluate the effectiveness of active-learning methods and help validate the use of student reflection of improved learning in other research projects. Copyright © 2011 Elsevier Ltd. All rights reserved.
-
Theoretical methods and models for mechanical properties of soft biomaterials
Directory of Open Access Journals (Sweden)
Zhonggang Feng
2017-06-01
Full Text Available We review the most commonly used theoretical methods and models for the mechanical properties of soft biomaterials, which include phenomenological hyperelastic and viscoelastic models, structural biphasic and network models, and the structural alteration theory. We emphasize basic concepts and recent developments. In consideration of the current progress and needs of mechanobiology, we introduce methods and models for tackling micromechanical problems and their applications to cell biology. Finally, the challenges and perspectives in this field are discussed.
-
A Scale Development for Teacher Competencies on Cooperative Learning Method
Kocabas, Ayfer; Erbil, Deniz Gokce
2017-01-01
Cooperative learning method is a learning method studied both in Turkey and in the world for long years as an active learning method. Although cooperative learning method takes place in training programs, it cannot be implemented completely in the direction of its principles. The results of the researches point out that teachers have problems with…
-
Perspectives on ontology learning
Lehmann, J
2014-01-01
Perspectives on Ontology Learning brings together researchers and practitioners from different communities − natural language processing, machine learning, and the semantic web − in order to give an interdisciplinary overview of recent advances in ontology learning.Starting with a comprehensive introduction to the theoretical foundations of ontology learning methods, the edited volume presents the state-of-the-start in automated knowledge acquisition and maintenance. It outlines future challenges in this area with a special focus on technologies suitable for pushing the boundaries beyond the c
-
Toward an Instructionally Oriented Theory of Example-Based Learning
Renkl, Alexander
2014-01-01
Learning from examples is a very effective means of initial cognitive skill acquisition. There is an enormous body of research on the specifics of this learning method. This article presents an instructionally oriented theory of example-based learning that integrates theoretical assumptions and findings from three research areas: learning from…
-
Introduction of active learning method in learning physiology by MBBS students.
Gilkar, Suhail Ahmad; Lone, Shabiruddin; Lone, Riyaz Ahmad
2016-01-01
Active learning has received considerable attention over the past several years, often presented or perceived as a radical change from traditional instruction methods. Current research on learning indicates that using a variety of teaching strategies in the classroom increases student participation and learning. To introduce active learning methodology, i.e., "jigsaw technique" in undergraduate medical education and assess the student and faculty response to it. This study was carried out in the Department of Physiology in a Medical College of North India. A topic was chosen and taught using one of the active learning methods (ALMs), i.e., jigsaw technique. An instrument (questionnaire) was developed in English through an extensive review of literature and was properly validated. The students were asked to give their response on a five-point Likert scale. The feedback was kept anonymous. Faculty also provided their feedback in a separately provided feedback proforma. The data were collected, compiled, and analyzed. Of 150 students of MBBS-first year batch 2014, 142 participated in this study along with 14 faculty members of the Physiology Department. The majority of the students (>90%) did welcome the introduction of ALM and strongly recommended the use of such methods in teaching many more topics in future. 100% faculty members were of the opinion that many more topics shall be taken up using ALMs. This study establishes the fact that both the medical students and faculty want a change from the traditional way of passive, teacher-centric learning, to the more active teaching-learning techniques.
-
Implementing Collaborative Learning Methods in the Political Science Classroom
Wolfe, Angela
2012-01-01
Collaborative learning is one, among other, active learning methods, widely acclaimed in higher education. Consequently, instructors in fields that lack pedagogical training often implement new learning methods such as collaborative learning on the basis of trial and error. Moreover, even though the benefits in academic circles are broadly touted,…
-
New Theoretical Approach Integrated Education and Technology
Ding, Gang
2010-01-01
The paper focuses on exploring new theoretical approach in education with development of online learning technology, from e-learning to u-learning and virtual reality technology, and points out possibilities such as constructing a new teaching ecological system, ubiquitous educational awareness with ubiquitous technology, and changing the…
-
A System Theoretical Inspired Approach to Knowledge Construction
DEFF Research Database (Denmark)
Mathiasen, Helle
2008-01-01
student's knowledge construction, in the light of operative constructivism, inspired by the German sociologist N. Luhmann's system theoretical approach to epistemology. Taking observations as operations based on distinction and indication (selection) contingency becomes a fundamental condition in learning...... Abstract The aim of this paper is to discuss the relation between teaching and learning. The point of departure is that teaching environments (communication forums) is a potential facilitator for learning processes and knowledge construction. The paper present a theoretical frame work, to discuss...... processes, and a condition which teaching must address as far as teaching strives to stimulate non-random learning outcomes. Thus learning outcomes understood as the individual learner's knowledge construction cannot be directly predicted from events and characteristics in the environment. This has...
-
Learning styles: The learning methods of air traffic control students
Jackson, Dontae L.
In the world of aviation, air traffic controllers are an integral part in the overall level of safety that is provided. With a number of controllers reaching retirement age, the Air Traffic Collegiate Training Initiative (AT-CTI) was created to provide a stronger candidate pool. However, AT-CTI Instructors have found that a number of AT-CTI students are unable to memorize types of aircraft effectively. This study focused on the basic learning styles (auditory, visual, and kinesthetic) of students and created a teaching method to try to increase memorization in AT-CTI students. The participants were asked to take a questionnaire to determine their learning style. Upon knowing their learning styles, participants attended two classroom sessions. The participants were given a presentation in the first class, and divided into a control and experimental group for the second class. The control group was given the same presentation from the first classroom session while the experimental group had a group discussion and utilized Middle Tennessee State University's Air Traffic Control simulator to learn the aircraft types. Participants took a quiz and filled out a survey, which tested the new teaching method. An appropriate statistical analysis was applied to determine if there was a significant difference between the control and experimental groups. The results showed that even though the participants felt that the method increased their learning, there was no significant difference between the two groups.
-
[Which learning methods are expected for ultrasound training? Blended learning on trial].
Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R
2014-10-01
Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.
-
Decomposition methods for unsupervised learning
DEFF Research Database (Denmark)
Mørup, Morten
2008-01-01
This thesis presents the application and development of decomposition methods for Unsupervised Learning. It covers topics from classical factor analysis based decomposition and its variants such as Independent Component Analysis, Non-negative Matrix Factorization and Sparse Coding...... methods and clustering problems is derived both in terms of classical point clustering but also in terms of community detection in complex networks. A guiding principle throughout this thesis is the principle of parsimony. Hence, the goal of Unsupervised Learning is here posed as striving for simplicity...... in the decompositions. Thus, it is demonstrated how a wide range of decomposition methods explicitly or implicitly strive to attain this goal. Applications of the derived decompositions are given ranging from multi-media analysis of image and sound data, analysis of biomedical data such as electroencephalography...
-
Smith, Sedef Uzuner; Hayes, Suzanne; Shea, Peter
2017-01-01
After presenting a brief overview of the key elements that underpin Etienne Wenger's communities of practice (CoP) theoretical framework, one of the most widely cited and influential conceptions of social learning, this paper reviews extant empirical work grounded in this framework to investigate online/blended learning in higher education and in…
-
Simulation teaching method in Engineering Optics
Lu, Qieni; Wang, Yi; Li, Hongbin
2017-08-01
We here introduce a pedagogical method of theoretical simulation as one major means of the teaching process of "Engineering Optics" in course quality improvement action plan (Qc) in our school. Students, in groups of three to five, complete simulations of interference, diffraction, electromagnetism and polarization of light; each student is evaluated and scored in light of his performance in the interviews between the teacher and the student, and each student can opt to be interviewed many times until he is satisfied with his score and learning. After three years of Qc practice, the remarkable teaching and learning effect is obatined. Such theoretical simulation experiment is a very valuable teaching method worthwhile for physical optics which is highly theoretical and abstruse. This teaching methodology works well in training students as to how to ask questions and how to solve problems, which can also stimulate their interest in research learning and their initiative to develop their self-confidence and sense of innovation.
-
Latisma D, L.; Kurniawan, W.; Seprima, S.; Nirbayani, E. S.; Ellizar, E.; Hardeli, H.
2018-04-01
The purpose of this study was to see which method are well used with the Chemistry Triangle-oriented learning media. This quasi experimental research involves first grade of senior high school students in six schools namely each two SMA N in Solok city, in Pasaman and two SMKN in Pariaman. The sampling technique was done by Cluster Random Sampling. Data were collected by test and analyzed by one-way anova and Kruskall Wallish test. The results showed that the high school students in Solok learning taught by cooperative method is better than the results of student learning taught by conventional and Individual methods, both for students who have high initial ability and low-ability. Research in SMK showed that the overall student learning outcomes taught by conventional method is better than the student learning outcomes taught by cooperative and individual methods. Student learning outcomes that have high initial ability taught by individual method is better than student learning outcomes that are taught by cooperative method and for students who have low initial ability, there is no difference in student learning outcomes taught by cooperative, individual and conventional methods. Learning in high school in Pasaman showed no significant difference in learning outcomes of the three methods undertaken.
-
Efficient model learning methods for actor-critic control.
Grondman, Ivo; Vaandrager, Maarten; Buşoniu, Lucian; Babuska, Robert; Schuitema, Erik
2012-06-01
We propose two new actor-critic algorithms for reinforcement learning. Both algorithms use local linear regression (LLR) to learn approximations of the functions involved. A crucial feature of the algorithms is that they also learn a process model, and this, in combination with LLR, provides an efficient policy update for faster learning. The first algorithm uses a novel model-based update rule for the actor parameters. The second algorithm does not use an explicit actor but learns a reference model which represents a desired behavior, from which desired control actions can be calculated using the inverse of the learned process model. The two novel methods and a standard actor-critic algorithm are applied to the pendulum swing-up problem, in which the novel methods achieve faster learning than the standard algorithm.
-
Lehmann, Janina A. M.; Seufert, Tina
2017-01-01
This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive detai...
-
Statistical learning methods in high-energy and astrophysics analysis
Energy Technology Data Exchange (ETDEWEB)
Zimmermann, J. [Forschungszentrum Juelich GmbH, Zentrallabor fuer Elektronik, 52425 Juelich (Germany) and Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)]. E-mail: zimmerm@mppmu.mpg.de; Kiesling, C. [Max-Planck-Institut fuer Physik, Foehringer Ring 6, 80805 Munich (Germany)
2004-11-21
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application.
-
Statistical learning methods in high-energy and astrophysics analysis
International Nuclear Information System (INIS)
Zimmermann, J.; Kiesling, C.
2004-01-01
We discuss several popular statistical learning methods used in high-energy- and astro-physics analysis. After a short motivation for statistical learning we present the most popular algorithms and discuss several examples from current research in particle- and astro-physics. The statistical learning methods are compared with each other and with standard methods for the respective application
-
Active teaching methods, studying responses and learning
DEFF Research Database (Denmark)
Christensen, Hans Peter; Vigild, Martin Etchells; Thomsen, Erik Vilain
2010-01-01
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed.......Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed....
-
Enriching behavioral ecology with reinforcement learning methods.
Frankenhuis, Willem E; Panchanathan, Karthik; Barto, Andrew G
2018-02-13
This article focuses on the division of labor between evolution and development in solving sequential, state-dependent decision problems. Currently, behavioral ecologists tend to use dynamic programming methods to study such problems. These methods are successful at predicting animal behavior in a variety of contexts. However, they depend on a distinct set of assumptions. Here, we argue that behavioral ecology will benefit from drawing more than it currently does on a complementary collection of tools, called reinforcement learning methods. These methods allow for the study of behavior in highly complex environments, which conventional dynamic programming methods do not feasibly address. In addition, reinforcement learning methods are well-suited to studying how biological mechanisms solve developmental and learning problems. For instance, we can use them to study simple rules that perform well in complex environments. Or to investigate under what conditions natural selection favors fixed, non-plastic traits (which do not vary across individuals), cue-driven-switch plasticity (innate instructions for adaptive behavioral development based on experience), or developmental selection (the incremental acquisition of adaptive behavior based on experience). If natural selection favors developmental selection, which includes learning from environmental feedback, we can also make predictions about the design of reward systems. Our paper is written in an accessible manner and for a broad audience, though we believe some novel insights can be drawn from our discussion. We hope our paper will help advance the emerging bridge connecting the fields of behavioral ecology and reinforcement learning. Copyright © 2018 The Authors. Published by Elsevier B.V. All rights reserved.
-
Kernel learning algorithms for face recognition
Li, Jun-Bao; Pan, Jeng-Shyang
2013-01-01
Kernel Learning Algorithms for Face Recognition covers the framework of kernel based face recognition. This book discusses the advanced kernel learning algorithms and its application on face recognition. This book also focuses on the theoretical deviation, the system framework and experiments involving kernel based face recognition. Included within are algorithms of kernel based face recognition, and also the feasibility of the kernel based face recognition method. This book provides researchers in pattern recognition and machine learning area with advanced face recognition methods and its new
-
Data Science and Optimal Learning for Material Discovery and Design
; Optimal Learning for Material Discovery & Design Data Science and Optimal Learning for Material inference and optimization methods that can constrain predictions using insights and results from theory directions in the application of information theoretic tools to materials problems related to learning from
-
Deep learning methods for protein torsion angle prediction.
Li, Haiou; Hou, Jie; Adhikari, Badri; Lyu, Qiang; Cheng, Jianlin
2017-09-18
Deep learning is one of the most powerful machine learning methods that has achieved the state-of-the-art performance in many domains. Since deep learning was introduced to the field of bioinformatics in 2012, it has achieved success in a number of areas such as protein residue-residue contact prediction, secondary structure prediction, and fold recognition. In this work, we developed deep learning methods to improve the prediction of torsion (dihedral) angles of proteins. We design four different deep learning architectures to predict protein torsion angles. The architectures including deep neural network (DNN) and deep restricted Boltzmann machine (DRBN), deep recurrent neural network (DRNN) and deep recurrent restricted Boltzmann machine (DReRBM) since the protein torsion angle prediction is a sequence related problem. In addition to existing protein features, two new features (predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments) are used as input to each of the four deep learning architectures to predict phi and psi angles of protein backbone. The mean absolute error (MAE) of phi and psi angles predicted by DRNN, DReRBM, DRBM and DNN is about 20-21° and 29-30° on an independent dataset. The MAE of phi angle is comparable to the existing methods, but the MAE of psi angle is 29°, 2° lower than the existing methods. On the latest CASP12 targets, our methods also achieved the performance better than or comparable to a state-of-the art method. Our experiment demonstrates that deep learning is a valuable method for predicting protein torsion angles. The deep recurrent network architecture performs slightly better than deep feed-forward architecture, and the predicted residue contact number and the error distribution of torsion angles extracted from sequence fragments are useful features for improving prediction accuracy.
-
The Ulam Index: Methods of Theoretical Computer Science Help in Identifying Chemical Substances
Beltran, Adriana; Salvador, James
1997-01-01
In this paper, we show how methods developed for solving a theoretical computer problem of graph isomorphism are used in structural chemistry. We also discuss potential applications of these methods to exobiology: the search for life outside Earth.
-
Directory of Open Access Journals (Sweden)
Ni Putu Wulan Purnama Sari
2017-08-01
Full Text Available Background and Purpose: Caring is the essence of nursing profession. Stimulation of caring attitude should start early. Effective teaching methods needed to foster caring attitude and improve learning achievement. This study aimed to explain the effect of applying flipped classroom learning method for improving caring attitude and learning achievement of new student nurses at nursing institutions in Surabaya. Method: This is a pre-experimental study using the one group pretest posttest and posttest only design. Population was all new student nurses on nursing institutions in Surabaya. Inclusion criteria: female, 18-21 years old, majoring in nursing on their own volition and being first choice during students selection process, status were active in the even semester of 2015/2016 academic year. Sample size was 67 selected by total sampling. Variables: 1 independent: application of flipped classroom learning method; 2 dependent: caring attitude, learning achievement. Instruments: teaching plan, assignment descriptions, presence list, assignment assessment rubrics, study materials, questionnaires of caring attitude. Data analysis: paired and one sample t test. Ethical clearance was available. Results: Most respondents were 20 years old (44.8%, graduated from high school in Surabaya (38.8%, living with parents (68.7% in their homes (64.2%. All data were normally distributed. Flipped classroom learning method could improve caring attitude by 4.13%. Flipped classroom learning method was proved to be effective for improving caring attitude (p=0.021 and learning achievement (p=0.000. Conclusion and Recommendation: Flipped classroom was effective for improving caring attitude and learning achievement of new student nurse. It is recommended to use mix-method and larger sample for further study.
-
Bayesian methods for addressing long-standing problems in associative learning: The case of PREE.
Blanco, Fernando; Moris, Joaquín
2017-07-20
Most associative models typically assume that learning can be understood as a gradual change in associative strength that captures the situation into one single parameter, or representational state. We will call this view single-state learning. However, there is ample evidence showing that under many circumstances different relationships that share features can be learned independently, and animals can quickly switch between expressing one or another. We will call this multiple-state learning. Theoretically, it is understudied because it needs a different data analysis approach from those usually employed. In this paper, we present a Bayesian model of the Partial Reinforcement Extinction Effect (PREE) that can test the predictions of the multiple-state view. This implies estimating the moment of change in the responses (from the acquisition to the extinction performance), both at the individual and at the group levels. We used this model to analyze data from a PREE experiment with three levels of reinforcement during acquisition (100%, 75% and 50%). We found differences in the estimated moment of switch between states during extinction, so that it was delayed after leaner partial reinforcement schedules. The finding is compatible with the multiple-state view. It is the first time, to our knowledge, that the predictions from the multiple-state view are tested directly. The paper also aims to show the benefits that Bayesian methods can bring to the associative learning field.
-
Fernández-Peña, Rosario; Fuentes-Pumarola, Concepció; Malagón-Aguilera, M Carme; Bonmatí-Tomàs, Anna; Bosch-Farré, Cristina; Ballester-Ferrando, David
2016-09-01
Adapting university programmes to European Higher Education Area criteria has required substantial changes in curricula and teaching methodologies. Reflective learning (RL) has attracted growing interest and occupies an important place in the scientific literature on theoretical and methodological aspects of university instruction. However, fewer studies have focused on evaluating the RL methodology from the point of view of nursing students. To assess nursing students' perceptions of the usefulness and challenges of RL methodology. Mixed method design, using a cross-sectional questionnaire and focus group discussion. The research was conducted via self-reported reflective learning questionnaire complemented by focus group discussion. Students provided a positive overall evaluation of RL, highlighting the method's capacity to help them better understand themselves, engage in self-reflection about the learning process, optimize their strengths and discover additional training needs, along with searching for continuous improvement. Nonetheless, RL does not help them as much to plan their learning or identify areas of weakness or needed improvement in knowledge, skills and attitudes. Among the difficulties or challenges, students reported low motivation and lack of familiarity with this type of learning, along with concerns about the privacy of their reflective journals and about the grading criteria. In general, students evaluated RL positively. The results suggest areas of needed improvement related to unfamiliarity with the methodology, ethical aspects of developing a reflective journal and the need for clear evaluation criteria. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
SAIL: Summation-bAsed Incremental Learning for Information-Theoretic Text Clustering.
Cao, Jie; Wu, Zhiang; Wu, Junjie; Xiong, Hui
2013-04-01
Information-theoretic clustering aims to exploit information-theoretic measures as the clustering criteria. A common practice on this topic is the so-called Info-Kmeans, which performs K-means clustering with KL-divergence as the proximity function. While expert efforts on Info-Kmeans have shown promising results, a remaining challenge is to deal with high-dimensional sparse data such as text corpora. Indeed, it is possible that the centroids contain many zero-value features for high-dimensional text vectors, which leads to infinite KL-divergence values and creates a dilemma in assigning objects to centroids during the iteration process of Info-Kmeans. To meet this challenge, in this paper, we propose a Summation-bAsed Incremental Learning (SAIL) algorithm for Info-Kmeans clustering. Specifically, by using an equivalent objective function, SAIL replaces the computation of KL-divergence by the incremental computation of Shannon entropy. This can avoid the zero-feature dilemma caused by the use of KL-divergence. To improve the clustering quality, we further introduce the variable neighborhood search scheme and propose the V-SAIL algorithm, which is then accelerated by a multithreaded scheme in PV-SAIL. Our experimental results on various real-world text collections have shown that, with SAIL as a booster, the clustering performance of Info-Kmeans can be significantly improved. Also, V-SAIL and PV-SAIL indeed help improve the clustering quality at a lower cost of computation.
-
Intelligent systems: A semiotic perspective. Volume I: Theoretical semiotics
Energy Technology Data Exchange (ETDEWEB)
Albus, J.; Meystel, A.; Quintero, R.
1996-12-31
This report contains the papers from the Proceedings of the 1996 International Multidisciplinary Conference - Theoretical Semiotics. General topics covered are: semiotic in biology: biologically inspired complex systems; intelligence in constructed complex systems; intelligence of learning and evolution; fuzzy logic and the mechanisms of generalization; information representation for decision making; sematic foundations; syntactics of intelligent systems: the kind of logic available; intelligence of recognition: the semiotic tools; and multiresolutional methods.
-
Lavoie, Patrick; Michaud, Cécile; Bélisle, Marilou; Boyer, Louise; Gosselin, Émilie; Grondin, Myrian; Larue, Caroline; Lavoie, Stéphan; Pepin, Jacinthe
2018-02-01
To identify the theories used to explain learning in simulation and to examine how these theories guided the assessment of learning outcomes related to core competencies in undergraduate nursing students. Nurse educators face the challenge of making explicit the outcomes of competency-based education, especially when competencies are conceptualized as holistic and context dependent. Theoretical review. Research papers (N = 182) published between 1999-2015 describing simulation in nursing education. Two members of the research team extracted data from the papers, including theories used to explain how simulation could engender learning and tools used to assess simulation outcomes. Contingency tables were created to examine the associations between theories, outcomes and tools. Some papers (N = 79) did not provide an explicit theory. The 103 remaining papers identified one or more learning or teaching theories; the most frequent were the National League for Nursing/Jeffries Simulation Framework, Kolb's theory of experiential learning and Bandura's social cognitive theory and concept of self-efficacy. Students' perceptions of simulation, knowledge and self-confidence were the most frequently assessed, mainly via scales designed for the study where they were used. Core competencies were mostly assessed with an observational approach. This review highlighted the fact that few studies examined the use of simulation in nursing education through learning theories and via assessment of core competencies. It also identified observational tools used to assess competencies in action, as holistic and context-dependent constructs. © 2017 John Wiley & Sons Ltd.
-
Learning automata theory and applications
Najim, K
1994-01-01
Learning systems have made a significant impact on all areas of engineering problems. They are attractive methods for solving many problems which are too complex, highly non-linear, uncertain, incomplete or non-stationary, and have subtle and interactive exchanges with the environment where they operate. The main aim of the book is to give a systematic treatment of learning automata and to produce a guide to a wide variety of ideas and methods that can be used in learning systems, including enough theoretical material to enable the user of the relevant techniques and concepts to understand why
-
DEFF Research Database (Denmark)
Lupp, Daniel; Christensen, Niels Johan; Fristrup, Peter
2014-01-01
n this Perspective, we will focus on the use of both experimental and theoretical methods in the exploration of reaction mechanisms in homogeneous transition metal catalysis. We briefly introduce the use of Hammett studies and kinetic isotope effects (KIE). Both of these techniques can be complem......n this Perspective, we will focus on the use of both experimental and theoretical methods in the exploration of reaction mechanisms in homogeneous transition metal catalysis. We briefly introduce the use of Hammett studies and kinetic isotope effects (KIE). Both of these techniques can...... be complemented by computational chemistry – in particular in cases where interpretation of the experimental results is not straightforward. The good correspondence between experiment and theory is only possible due to recent advances within the applied theoretical framework. We therefore also highlight...
-
Game-theoretic methods for functional response and optimal foraging behavior
Czech Academy of Sciences Publication Activity Database
Cressman, R.; Křivan, Vlastimil; Brown, J. S.; Garay, J.
2014-01-01
Roč. 9, č. 2 (2014), e88773 E-ISSN 1932-6203 Grant - others:Hungarian National Research Fund(HU) K62000; Hungarian National Research Fund(HU) K67961 Institutional support: RVO:60077344 Keywords : game-theoretic methods Subject RIV: EH - Ecology, Behaviour Impact factor: 3.234, year: 2014 http://www.plosone.org/article/info%3Adoi%2F10.1371%2Fjournal.pone.0088773
-
Vlčková Kateřina
2014-01-01
The presentation focused on an so called integrated mixed method research design example on a basis of a Czech Science Foundation Project Nr. GAP407/12/0432 "Foreign Language Learning Strategies and Achievement: Analysis of Strategy Clusters and Sequences". All main integrated parts of the mixed methods research design were discussed: the aim, theoretical framework, research question, methods and validity threats. Prezentace se zaměřovala na tzv. integrovaný vícemetodový výzkumný design na...
-
Mohammadjani, Farzad; Tonkaboni, Forouzan
2015-01-01
The aim of the present research is to investigate a comparison between the effect of cooperative learning teaching method and lecture teaching method on students' learning and satisfaction level. The research population consisted of all the fourth grade elementary school students of educational district 4 in Shiraz. The statistical population…
-
A cross-benchmark comparison of 87 learning to rank methods
Tax, N.; Bockting, S.; Hiemstra, D.
2015-01-01
Learning to rank is an increasingly important scientific field that comprises the use of machine learning for the ranking task. New learning to rank methods are generally evaluated on benchmark test collections. However, comparison of learning to rank methods based on evaluation results is hindered
-
Color image definition evaluation method based on deep learning method
Liu, Di; Li, YingChun
2018-01-01
In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.
-
Directory of Open Access Journals (Sweden)
Mohammed Abdallh Otair
2006-06-01
Full Text Available Attempting to deliver a monolithic mobile learning system is too inflexible in view of the heterogeneous mixture of hardware and services available and the desirability of facility blended approaches to learning delivery, and how to build learning materials to run on all platforms[1]. This paper proposes a framework of mobile learning system using an intelligent method (IP-MLI . A fuzzy matching method is used to find suitable learning material design. It will provide a best matching for each specific platform type for each learner. The main contribution of the proposed method is to use software layer to insulate learning materials from device-specific features. Consequently, many versions of learning materials can be designed to work on many platform types.
-
Directory of Open Access Journals (Sweden)
Sonia CASILLAS MARTÍN
2017-12-01
Full Text Available Collaborative learning has been a subject of great interest in the context of educational research, giving rise to many studies emphasizing the potential of the collaboration process in student learning, knowledge building, the development of diverse abilities and improved academic performance. Based on a conceptual review and thorough reflection on this topic, this article presents the results of a case study carried out in different schools in the Autonomous Community of Castile y Leon (Spain in an attempt to identify patterns of common action through the implementation of collaborative learning methods mediated by information and communication technologies (ICT. Among the many outcomes of this study, we conclude by highlighting the need to plan collaborative work very carefully, taking advantage of the opportunities offered by ICT as communicative environments where it is possible to construct joint and shared learning.
-
Theoretical reflections on the connection between environmental assessment methods and conflict
International Nuclear Information System (INIS)
Persson, Jesper
2006-01-01
Today there is a great variety of methods for evaluating the environmental impact of plans, programs and projects. But which of these methods should planners and managers choose? This theoretical article explores the connection between conflicts, communication and rationality in assessment methods. It focuses on the form (rationality) and substance of communication, i.e. what we should communicate about. The outcome supports the view that environmental assessments should be based on value- and interest-focused thinking, following a teleological ethic, when goals, alternatives and compensations are to be developed and impacts evaluated
-
Theoretical assumptions of Maffesoli's sensitivity and Problem-Based Learning in Nursing Education
Directory of Open Access Journals (Sweden)
María-Aurora Rodríguez-Borrego
2014-06-01
Full Text Available OBJECTIVE: understand the everyday and the imaginary of Nursing students in their knowledge socialization process through the Problem-Based Learning (PBL strategy.METHOD: Action Research, involving 86 students from the second year of an undergraduate Nursing program in Spain. A Critical Incident Questionnaire and Group interview were used. Thematic/categorical analysis, triangulation of researchers, subjects and techniques.RESULTS: the students signal the need to have a view from within, reinforcing the criticism against the schematic dualism; PBL allows one to learn how to be with the other, with his mechanical and organic solidarity; the feeling together, with its emphasis on learning to work in group and wanting to be close to the person taking care.CONCLUSIONS: The great contradictions the protagonists of the process, that is, the students experience seem to express that group learning is not a form of gaining knowledge, as it makes them lose time to study. The daily, the execution time and the imaginary of how learning should be do not seem to have an intersection point in the use of Problem-Based Learning. The importance of focusing on the daily and the imaginary should be reinforced when we consider nursing education.
-
Quantum mechanics the theoretical minimum
Susskind, Leonard
2014-01-01
From the bestselling author of The Theoretical Minimum, an accessible introduction to the math and science of quantum mechanicsQuantum Mechanics is a (second) book for anyone who wants to learn how to think like a physicist. In this follow-up to the bestselling The Theoretical Minimum, physicist Leonard Susskind and data engineer Art Friedman offer a first course in the theory and associated mathematics of the strange world of quantum mechanics. Quantum Mechanics presents Susskind and Friedman’s crystal-clear explanations of the principles of quantum states, uncertainty and time dependence, entanglement, and particle and wave states, among other topics. An accessible but rigorous introduction to a famously difficult topic, Quantum Mechanics provides a tool kit for amateur scientists to learn physics at their own pace.
-
Suhariyanto; Hariyati, Rr Tutik Sri; Ungsianik, Titin
2018-02-01
Effective interpersonal skills are essential for head nurses in governing and managing their work units. Therefore, an active learning strategy could be the key to enhance the interpersonal competences of head nurses. This study aimed to investigate the effects of Peplau's theoretical approach of active learning on the improvement of head nurses' interpersonal skills. This study used a pre-experimental design with one group having pretests and posttests, without control group. A total sample of 25 head nurses from inpatient units of a wellknown private hospital in Jakarta was involved in the study. Data were analyzed using the paired t-test. The results showed a significant increase in head nurses' knowledge following the training to strengthen their interpersonal roles (P=.003). The results also revealed significant increases in the head nurses' skills in playing the roles of leader (P=.006), guardian (P=.014), and teacher/speaker (P=.015). Nonetheless, the results showed no significant increases in the head nurses' skills in playing the roles of counselor (P=.092) and stranger (P=.182). Training in strengthening the interpersonal roles of head nurses significantly increased the head nurses' knowledge and skills. The results of the study suggested the continuation of active learning strategies to improve the interpersonal abilities of head nurses. Furthermore, these strategies could be used to build the abilities of head nurses in other managerial fields. Copyright © 2018 Elsevier España, S.L.U. All rights reserved.
-
Pragmatics of Contemporary Teaching and Learning Methods
Directory of Open Access Journals (Sweden)
Ryszard Józef Panfil
2013-09-01
Full Text Available The dynamics of the environment in which educational institutions operate have a significant influence on the basic activity of these institutions, i.e. the process of educating, and particularly teaching and learning methods used during that process: traditional teaching, tutoring, mentoring and coaching. The identity of an educational institution and the appeal of its services depend on how flexible, diverse and adaptable is the educational process it offers as a core element of its services. Such a process is determined by how its pragmatism is displayed in the operational relativism of methods, their applicability, as well as practical dimension of achieved results and values. Based on the above premises, this publication offers a pragmatic-systemic identification of contemporary teaching and learning methods, while taking into account the differences between them and the scope of their compatibility. Secondly, using the case of sport coaches’ education, the author exemplifies the pragmatic theory of perception of contemporary teaching and learning methods.
-
The Method of High School English Word Learning
Institute of Scientific and Technical Information of China (English)
吴博涵
2016-01-01
Most Chinese students are not interested in English learning, especially English words. In this paper, I focus on English vocabulary learning, for example, the study of high school students English word learning method, and also introduce several ways to make vocabulary memory becomes more effective. The purpose is to make high school students grasp more English word learning skills.
-
Evolution of Theoretical Perspectives in My Research
Otero, Valerie K.
2009-11-01
Over the past 10 years I have been using socio-cultural theoretical perspectives to understand how people learn physics in a highly interactive, inquiry-based physics course such as Physics and Everyday Thinking [1]. As a result of using various perspectives (e.g. Distributed Cognition and Vygotsky's Theory of Concept Formation), my understanding of how these perspectives can be useful for investigating students' learning processes has changed. In this paper, I illustrate changes in my thinking about the role of socio-cultural perspectives in understanding physics learning and describe elements of my thinking that have remained fairly stable. Finally, I will discuss pitfalls in the use of certain perspectives and discuss areas that need attention in theoretical development for PER.
-
Lifelong Transfer Learning for Heterogeneous Teams of Agents in Sequential Decision Processes
2016-06-01
computational complexity and exhibits sublinear regret , thus providing strong theoretical guarantees [Bou Ammar et al., 2015b] (see Appendix C for details...transferred knowledge, providing a potential mechanism for predicting the effectiveness of transfer learning (and thereby avoiding negative transfer). One...learning from demonstration. We theoretically and empirically analyze the performance of the proposed method and derive, for the first time, regret
-
Directory of Open Access Journals (Sweden)
Georg Spöttl
2012-04-01
Full Text Available Two problems can be identified which counteract the need for further training: On the one hand the clientele of skilled workers is not necessarily keen on further training. On the other hand the time and cost pressure within the sector does not offer any room for time-consuming further training measures far away from the workplace. This is why the project “Virtual Learning on the building site – (Vila-b” was realized in cooperation with the project partners of the University of Bremen (Working group »Digital Media« of the Centre for Information Technology as well as from the economy (Arbeitskreis ökologischer Holzbau e. V. and Claus Holm, pm|c. The project team has tested a concept which facilitated learning adapted to the occupational reality and supported by the advantages of digital media. The central didactical elements for the development of this further training course are the contextual and methodological orientation to real work processes as well as the use of digital mobile media which facilitate learning directly at the workplace. The present article starts with a description of the theoretical basics for learning within the work process and discusses the didactical elements which are necessary for work process oriented learning with digital and mobile media.
-
Lazem, Shaimaa; Webster, Mary; Holmes, Wayne; Wolf, Motje
2015-09-02
Here we review 18 articles that describe the design and evaluation of 1 or more games for diabetes from technical, methodological, and theoretical perspectives. We undertook searches covering the period 2010 to May 2015 in the ACM, IEEE, Journal of Medical Internet Research, Studies in Health Technology and Informatics, and Google Scholar online databases using the keywords "children," "computer games," "diabetes," "games," "type 1," and "type 2" in various Boolean combinations. The review sets out to establish, for future research, an understanding of the current landscape of digital games designed for children with diabetes. We briefly explored the use and impact of well-established learning theories in such games. The most frequently mentioned theoretical frameworks were social cognitive theory and social constructivism. Due to the limitations of the reported evaluation methodologies, little evidence was found to support the strong promise of games for diabetes. Furthermore, we could not establish a relation between design features and the game outcomes. We argue that an in-depth discussion about the extent to which learning theories could and should be manifested in the design decisions is required. © 2015 Diabetes Technology Society.
-
e-Learning Business Research Methods
Cowie, Jonathan
2004-01-01
This paper outlines the development of a generic Business Research Methods course from a simple name in a box to a full e-Learning web based module. It highlights particular issues surrounding the nature of the discipline and the integration of a large number of cross faculty subject specific research methods courses into a single generic module.…
-
Question presentation methods for paired-associate learning
Engel, F.L.; Geerings, M.P.W.
1988-01-01
Four different methods of question presentation, in interactive computeraided learning of Dutch-English word pairs are evaluated experimentally. These methods are: 1) the 'open-question method', 2) the 'multiple-choice method', 3) the 'sequential method' and 4) the 'true/ false method'. When
-
Think Pair Share (TPS as Method to Improve Student’s Learning Motivation and Learning Achievement
Directory of Open Access Journals (Sweden)
Hetika Hetika
2018-03-01
Full Text Available This research aims to find out the application of Think Pair Share (TPS learning method in improving learning motivation and learning achievement in the subject of Introduction to Accounting I of the Accounting Study Program students of Politeknik Harapan Bersama. The Method of data collection in this study used observation method, test method, and documentation method. The research instruments used observation sheet, questionnaire and test question. This research used Class Action Research Design which is an action implementation oriented research, with the aim of improving quality or problem solving in a group by carefully and observing the success rate due to the action. The method of analysis used descriptive qualitative and quantitative analysis method. The results showed that the application of Think Pair Share Learning (TPS Method can improve the Learning Motivation and Achievement. Before the implementation of the action, the obtained score is 67% then in the first cycle increases to 72%, and in the second cycle increasws to 80%. In addition, based on questionnaires distributed to students, it also increases the score of Accounting Learning Motivation where the score in the first cycle of 76% increases to 79%. In addition, in the first cycle, the score of pre test and post test of the students has increased from 68.86 to 76.71 while in the second cycle the score of pre test and post test of students has increased from 79.86 to 84.86.
-
Theoretical aspects of business role-playing game for senior students
Directory of Open Access Journals (Sweden)
Faychuk Olena Leonidivna
2015-04-01
Full Text Available The article deals with some theoretically grounded features of the business role-playing game determined to improve the learning process of senior students (specialization «Social work». The authors give the classification of business role-playing games, benefits and effective application of the rules of role-plays, and possibilities of using them in the learning process. Business role-playing games provide students’ initiative, emotional saturation of the learning process and help to assimilate the basic theoretical knowledge.
-
Data, Methods, and Theoretical Implications
Hannagan, Rebecca J.; Schneider, Monica C.; Greenlee, Jill S.
2012-01-01
Within the subfields of political psychology and the study of gender, the introduction of new data collection efforts, methodologies, and theoretical approaches are transforming our understandings of these two fields and the places at which they intersect. In this article we present an overview of the research that was presented at a National…
-
Theoretical Commitment and Implicit Knowledge: Why Anomalies do not Trigger Learning
Ohlsson, Stellan
A theory consists of a mental model, laws that specify parameters of the model and one or more explanatory schemas. Models represent by being isomorphic to real systems. To explain an event is to reenact its genesis by executing the relevant model in the mind's eye. Schemas capture recurring structural features of explanations. To subscribe to a theory is to be committed to explaining a particular class of events with that theory (and nothing else). Given theoretical commitment, an anomaly, i.e., an event that cannot be explained, is an occasion for theory change, but in the absence of commitment, the response is instead to exclude the anomalous event from the domain of application of the theory. Lay people and children hold their theories implicitly and hence without commitment. These observations imply that the analogy between scientist's theories and children's knowledge is valid, but that the analogy between theory change and learning is not.
-
Sheikhaboumasoudi, Rouhollah; Bagheri, Maryam; Hosseini, Sayed Abbas; Ashouri, Elaheh; Elahi, Nasrin
2018-01-01
Fundamentals of nursing course are prerequisite to providing comprehensive nursing care. Despite development of technology on nursing education, effectiveness of using e-learning methods in fundamentals of nursing course is unclear in clinical skills laboratory for nursing students. The aim of this study was to compare the effect of blended learning (combining e-learning with traditional learning methods) with traditional learning alone on nursing students' scores. A two-group post-test experimental study was administered from February 2014 to February 2015. Two groups of nursing students who were taking the fundamentals of nursing course in Iran were compared. Sixty nursing students were selected as control group (just traditional learning methods) and experimental group (combining e-learning with traditional learning methods) for two consecutive semesters. Both groups participated in Objective Structured Clinical Examination (OSCE) and were evaluated in the same way using a prepared checklist and questionnaire of satisfaction. Statistical analysis was conducted through SPSS software version 16. Findings of this study reflected that mean of midterm (t = 2.00, p = 0.04) and final score (t = 2.50, p = 0.01) of the intervention group (combining e-learning with traditional learning methods) were significantly higher than the control group (traditional learning methods). The satisfaction of male students in intervention group was higher than in females (t = 2.60, p = 0.01). Based on the findings, this study suggests that the use of combining traditional learning methods with e-learning methods such as applying educational website and interactive online resources for fundamentals of nursing course instruction can be an effective supplement for improving nursing students' clinical skills.
-
Aoki, Kenichi; Feldman, Marcus W
2014-02-01
The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change--coevolutionary, two-timescale, and information decay--are compared and shown to sometimes yield contradictory results. The so-called Rogers' paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers' paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. Copyright © 2013 Elsevier Inc. All rights reserved.
-
Aoki, Kenichi; Feldman, Marcus W.
2013-01-01
The theoretical literature from 1985 to the present on the evolution of learning strategies in variable environments is reviewed, with the focus on deterministic dynamical models that are amenable to local stability analysis, and on deterministic models yielding evolutionarily stable strategies. Individual learning, unbiased and biased social learning, mixed learning, and learning schedules are considered. A rapidly changing environment or frequent migration in a spatially heterogeneous environment favors individual learning over unbiased social learning. However, results are not so straightforward in the context of learning schedules or when biases in social learning are introduced. The three major methods of modeling temporal environmental change – coevolutionary, two-timescale, and information decay – are compared and shown to sometimes yield contradictory results. The so-called Rogers’ paradox is inherent in the two-timescale method as originally applied to the evolution of pure strategies, but is often eliminated when the other methods are used. Moreover, Rogers’ paradox is not observed for the mixed learning strategies and learning schedules that we review. We believe that further theoretical work is necessary on learning schedules and biased social learning, based on models that are logically consistent and empirically pertinent. PMID:24211681
-
Verpoorten, Dominique; Poumay, M; Leclercq, D
2006-01-01
Please, cite this publication as: Verpoorten, D., Poumay, M., & Leclercq, D. (2006). The 8 Learning Events Model: a Pedagogic Conceptual Tool Supporting Diversification of Learning Methods. Proceedings of International Workshop in Learning Networks for Lifelong Competence Development, TENCompetence
-
Characterizing Reinforcement Learning Methods through Parameterized Learning Problems
2011-06-03
extraneous. The agent could potentially adapt these representational aspects by applying methods from feature selection ( Kolter and Ng, 2009; Petrik et al...611–616. AAAI Press. Kolter , J. Z. and Ng, A. Y. (2009). Regularization and feature selection in least-squares temporal difference learning. In A. P
-
Directory of Open Access Journals (Sweden)
Ana Ecilda Lima Ellery
2012-06-01
Full Text Available Objective: Present and discuss the contribution of the concept of Community of Practice (CP, while collective space of learning and development of knowledge and practice in multidisciplinary teams of Family Health Strategy. Methods: Theoretical study through nonsystematic literature reviews the theme of “Communities of Practice” in the work of social researchers Jean Lave and Etienne Wenger, who developed this concept, completed with studies on the same topic from the research in online databases. Results: A CP is characterized by a group of people who forged and got engaged in a common project, sharing a repertoire, which allowed communication between them. Several effects are attributed to the experienceof working together in a CP, such as the socialization of knowledge, the interprofessional collaboration and the development of an environment conducive to reflective practice, which facilitates the conflict mediation. The theory of CP requires a major change in theconception of learning. Unlike theories that consider learning as resulting mainly from the internal process of the person, as the cognitive, the CP’s theory conceives learning through the angle of social participation. The inter-relationship developed by the CP influences the learning process, negotiation of meaning and identity formation, which results from the fact of belonging to the community and from the meaning attributed to the collaborative. Conclusion: The formation of Community of Practice in Family Health Strategy can be adevice to facilitate the construction of interdisciplinary projects, expressed by the integration of knowledge and interprofessional collaboration.
-
DEFF Research Database (Denmark)
Petersen, Karen Bjerg
2006-01-01
Etienne Wenger. The work by Jean Lave from 1988 (Lave, 1988) based on anthropological field studies in Brazil and Liberia as well as later works by Lave & Wenger (Lave and Wenger, 1991; Chaiklin and Lave, 1993; Wenger, 1998; Wenger, McDermott, R. and W. Snyder, 2002) on situated learning and social...... and scaffolded learning (Wood, Bruner & Ross, 1976; Bruner, 1985; Bruner 1996; Kaye, 1992; Meyer, 1993; Sorensen, 1999) and ?learning in communities of practice? have deeply inspired and to a certain degree become a sort of theoretical and practical framework in Denmark with respect to development of web based...
-
Physical Violence between Siblings: A Theoretical and Empirical Analysis
Hoffman, Kristi L.; Kiecolt, K. Jill; Edwards, John N.
2005-01-01
This study develops and tests a theoretical model to explain sibling violence based on the feminist, conflict, and social learning theoretical perspectives and research in psychology and sociology. A multivariate analysis of data from 651 young adults generally supports hypotheses from all three theoretical perspectives. Males with brothers have…
-
Non-Gaussian Methods for Causal Structure Learning.
Shimizu, Shohei
2018-05-22
Causal structure learning is one of the most exciting new topics in the fields of machine learning and statistics. In many empirical sciences including prevention science, the causal mechanisms underlying various phenomena need to be studied. Nevertheless, in many cases, classical methods for causal structure learning are not capable of estimating the causal structure of variables. This is because it explicitly or implicitly assumes Gaussianity of data and typically utilizes only the covariance structure. In many applications, however, non-Gaussian data are often obtained, which means that more information may be contained in the data distribution than the covariance matrix is capable of containing. Thus, many new methods have recently been proposed for using the non-Gaussian structure of data and inferring the causal structure of variables. This paper introduces prevention scientists to such causal structure learning methods, particularly those based on the linear, non-Gaussian, acyclic model known as LiNGAM. These non-Gaussian data analysis tools can fully estimate the underlying causal structures of variables under assumptions even in the presence of unobserved common causes. This feature is in contrast to other approaches. A simulated example is also provided.
-
Problematic Methods in teaching Modern History. An alternative or a necessity?
Directory of Open Access Journals (Sweden)
Yohany Peralta Pérez
2012-06-01
Full Text Available The article presents the results of the analysis from the study of the theoretical research on the use of problematic methods in Teaching Learning Process of Modern H istory course in Rafael Maria de Mendive University of Pinar del Rio. An anal ysis o f the use of problematic methods in the Process of Teaching Modern History course from the definition of method taking into account the theoretical assumptions of scholars of the subject matter and the advantages and disadvantages provided by the use of these methods in the Teaching Learning Process of Modern History course.
-
Deep kernel learning method for SAR image target recognition
Chen, Xiuyuan; Peng, Xiyuan; Duan, Ran; Li, Junbao
2017-10-01
With the development of deep learning, research on image target recognition has made great progress in recent years. Remote sensing detection urgently requires target recognition for military, geographic, and other scientific research. This paper aims to solve the synthetic aperture radar image target recognition problem by combining deep and kernel learning. The model, which has a multilayer multiple kernel structure, is optimized layer by layer with the parameters of Support Vector Machine and a gradient descent algorithm. This new deep kernel learning method improves accuracy and achieves competitive recognition results compared with other learning methods.
-
Advanced Numerical and Theoretical Methods for Photonic Crystals and Metamaterials
Felbacq, Didier
2016-11-01
This book provides a set of theoretical and numerical tools useful for the study of wave propagation in metamaterials and photonic crystals. While concentrating on electromagnetic waves, most of the material can be used for acoustic (or quantum) waves. For each presented numerical method, numerical code written in MATLAB® is presented. The codes are limited to 2D problems and can be easily translated in Python or Scilab, and used directly with Octave as well.
-
The Among System in the Senior High School History Learning
Directory of Open Access Journals (Sweden)
Nugraha Nugraha
2018-05-01
Full Text Available This study describes the theoretical and practical aspect of the Among - system in the modern historical learning. As a preliminary research, this article formulates a conceptual framework of the Among- system in the contemporary learning, especially modern history learning. This research used library research method that conducted in Dewantara Kirti Griya Library Yogyakarta. Data analysis was done by the descriptive method of collecting data, compiling or classifying, and interpreting.
-
Theoretical and methodological grounds of formation of the efficient system of higher education
Directory of Open Access Journals (Sweden)
Raevneva Elena V.
2013-03-01
Full Text Available The goal of the article lies in generalisation of the modern theoretical and methodological, methodical and instrumentation provision of building of efficient system of higher education. Analysis of literature on the problems of building educational systems shows that there is a theoretical and methodological and instrumentation level of study of this issue. The article considers a theoretical and methodological level of the study and specifies theories and philosophic schools, concepts, educational paradigms and scientific approaches used during formation of the educational paradigm. The article considers models of education and models and technologies of learning as instrumental provision. In the result of the analysis the article makes a conclusion that the humanistic paradigm, which is based on the competency building approach and which assumes the use of modern (innovation technologies of learning, should be in the foundation of reformation of the system of higher education. The prospect of further studies in this directions is formation of competences of potential specialists (graduates of higher educational establishments with consideration of requirements of employers and market in general.
-
Theoretical investigations of the new Cokriging method for variable-fidelity surrogate modeling
DEFF Research Database (Denmark)
Zimmermann, Ralf; Bertram, Anna
2018-01-01
Cokriging is a variable-fidelity surrogate modeling technique which emulates a target process based on the spatial correlation of sampled data of different levels of fidelity. In this work, we address two theoretical questions associated with the so-called new Cokriging method for variable fidelity...
-
Choosing Learning Methods Suitable for Teaching and Learning in Computer Science
Taylor, Estelle; Breed, Marnus; Hauman, Ilette; Homann, Armando
2013-01-01
Our aim is to determine which teaching methods students in Computer Science and Information Systems prefer. There are in total 5 different paradigms (behaviorism, cognitivism, constructivism, design-based and humanism) with 32 models between them. Each model is unique and states different learning methods. Recommendations are made on methods that…
-
Teacher Candidate Technology Integration: For Student Learning or Instruction?
Clark, Cynthia; Zhang, Shaoan; Strudler, Neal
2015-01-01
Transfer of instructional technology knowledge for student-centered learning by teacher candidates is investigated in this study. Using the transfer of learning theoretical framework, a mixed methods research design was employed to investigate whether secondary teacher candidates were able to transfer the instructional technology knowledge for…
-
An online supervised learning method based on gradient descent for spiking neurons.
Xu, Yan; Yang, Jing; Zhong, Shuiming
2017-09-01
The purpose of supervised learning with temporal encoding for spiking neurons is to make the neurons emit a specific spike train encoded by precise firing times of spikes. The gradient-descent-based (GDB) learning methods are widely used and verified in the current research. Although the existing GDB multi-spike learning (or spike sequence learning) methods have good performance, they work in an offline manner and still have some limitations. This paper proposes an online GDB spike sequence learning method for spiking neurons that is based on the online adjustment mechanism of real biological neuron synapses. The method constructs error function and calculates the adjustment of synaptic weights as soon as the neurons emit a spike during their running process. We analyze and synthesize desired and actual output spikes to select appropriate input spikes in the calculation of weight adjustment in this paper. The experimental results show that our method obviously improves learning performance compared with the offline learning manner and has certain advantage on learning accuracy compared with other learning methods. Stronger learning ability determines that the method has large pattern storage capacity. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
Cyrino, Eliana Goldfarb; Toralles-Pereira, Maria Lúcia
2004-01-01
Considering the changes in teaching in the health field and the demand for new ways of dealing with knowledge in higher learning, the article discusses two innovative methodological approaches: problem-based learning (PBL) and problematization. Describing the two methods' theoretical roots, the article attempts to identify their main foundations. As distinct proposals, both contribute to a review of the teaching and learning process: problematization, focused on knowledge construction in the context of the formation of a critical awareness; PBL, focused on cognitive aspects in the construction of concepts and appropriation of basic mechanisms in science. Both problematization and PBL lead to breaks with the traditional way of teaching and learning, stimulating participatory management by actors in the experience and reorganization of the relationship between theory and practice. The critique of each proposal's possibilities and limits using the analysis of their theoretical and methodological foundations leads us to conclude that pedagogical experiences based on PBL and/or problematization can represent an innovative trend in the context of health education, fostering breaks and more sweeping changes.
-
Barnett, Janet Heine; Lodder, Jerry; Pengelley, David
2014-01-01
We analyze our method of teaching with primary historical sources within the context of theoretical frameworks for the role of history in teaching mathematics developed by Barbin, Fried, Jahnke, Jankvist, and Kjeldsen and Blomhøj, and more generally from the perspective of Sfard's theory of learning as communication. We present case studies…
-
Studying depression using imaging and machine learning methods.
Patel, Meenal J; Khalaf, Alexander; Aizenstein, Howard J
2016-01-01
Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presents a background on depression, imaging, and machine learning methodologies; (2) reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3) suggests directions for future depression-related studies.
-
Characterizing Engineering Learners' Preferences for Active and Passive Learning Methods
Magana, Alejandra J.; Vieira, Camilo; Boutin, Mireille
2018-01-01
This paper studies electrical engineering learners' preferences for learning methods with various degrees of activity. Less active learning methods such as homework and peer reviews are investigated, as well as a newly introduced very active (constructive) learning method called "slectures," and some others. The results suggest that…
-
Approximation methods for efficient learning of Bayesian networks
Riggelsen, C
2008-01-01
This publication offers and investigates efficient Monte Carlo simulation methods in order to realize a Bayesian approach to approximate learning of Bayesian networks from both complete and incomplete data. For large amounts of incomplete data when Monte Carlo methods are inefficient, approximations are implemented, such that learning remains feasible, albeit non-Bayesian. The topics discussed are: basic concepts about probabilities, graph theory and conditional independence; Bayesian network learning from data; Monte Carlo simulation techniques; and, the concept of incomplete data. In order to provide a coherent treatment of matters, thereby helping the reader to gain a thorough understanding of the whole concept of learning Bayesian networks from (in)complete data, this publication combines in a clarifying way all the issues presented in the papers with previously unpublished work.
-
Unsupervised process monitoring and fault diagnosis with machine learning methods
Aldrich, Chris
2013-01-01
This unique text/reference describes in detail the latest advances in unsupervised process monitoring and fault diagnosis with machine learning methods. Abundant case studies throughout the text demonstrate the efficacy of each method in real-world settings. The broad coverage examines such cutting-edge topics as the use of information theory to enhance unsupervised learning in tree-based methods, the extension of kernel methods to multiple kernel learning for feature extraction from data, and the incremental training of multilayer perceptrons to construct deep architectures for enhanced data
-
Directory of Open Access Journals (Sweden)
Leila Roshangar
2014-05-01
Full Text Available Introduction: The basic medical sciences section requires 2.5 years in the medical education curriculum. Practical courses complement theoretical knowledge in this period to improve their appreciation. Despite spending lots of disbursement and time, this period’s efficacy is not clearly known. Methods: One hundred thirty-three General Practitioner (GP students have been included in this descriptive cross-sectional study and were asked by questionnaire about the positive impact of practical courses on learning theoretical knowledge. Data were analyzed by descriptive statistics. Result: The agreement in “Practical Head and Neck Anatomy” was 40.91% ± 29.45, in “Practical Trunk Anatomy” was 63.62% ± 2.32 and in “Practical Anatomy of Extremities” was 56.16% ± 2.57. In “Practical Histology”, agreement was 69.50%±2.19; “Practical Biophysics” was 45.97%±2.25, “Practical Physiology” 61.75%±2.17; “Practical Biochemistry” 36.28%±2.42; “Practical Pathology” 59.80%±2.53; “Practical Immunology” 56.25%±26.40; “Practical Microbiology and Virology” 60.39%±2.27 and “Practical Mycology and Parasitology” 68.2%± 2.16.Conclusion: GP students in Tabriz University of Medical Sciences are not optimistic about the applicability of practical courses of basic medical sciences lessons.
-
Bressington, Daniel T; Wong, Wai-Kit; Lam, Kar Kei Claire; Chien, Wai Tong
2018-01-01
Student nurses are provided with a great deal of knowledge within university, but they can find it difficult to relate theory to nursing practice. This study aimed to test the appropriateness and feasibility of assessing Novak's concept mapping as an educational strategy to strengthen the theory-practice link, encourage meaningful learning and enhance learning self-efficacy in nursing students. This pilot study utilised a mixed-methods quasi-experimental design. The study was conducted in a University school of Nursing in Hong Kong. A total of 40 third-year pre-registration Asian mental health nursing students completed the study; 12 in the concept mapping (CM) group and 28 in the usual teaching methods (UTM) group. The impact of concept mapping was evaluated thorough analysis of quantitative changes in students' learning self-efficacy, analysis of the structure and contents of the concept maps (CM group), a quantitative measure of students' opinions about their reflective learning activities and content analysis of qualitative data from reflective written accounts (CM group). There were no significant differences in self-reported learning self-efficacy between the two groups (p=0.38). The concept mapping helped students identify their current level of understanding, but the increased awareness may cause an initial drop in learning self-efficacy. The results highlight that most CM students were able to demonstrate meaningful learning and perceived that concept mapping was a useful reflective learning strategy to help them to link theory and practice. The results provide preliminary evidence that the concept mapping approach can be useful to help mental health nursing students visualise their learning progress and encourage the integration of theoretical knowledge with clinical knowledge. Combining concept mapping data with quantitative measures and qualitative reflective journal data appears to be a useful way of assessing and understanding the effectiveness of
-
Theoretical assumptions of Maffesoli's sensitivity and Problem-Based Learning in Nursing Education1
Rodríguez-Borrego, María-Aurora; Nitschke, Rosane Gonçalves; do Prado, Marta Lenise; Martini, Jussara Gue; Guerra-Martín, María-Dolores; González-Galán, Carmen
2014-01-01
Objective understand the everyday and the imaginary of Nursing students in their knowledge socialization process through the Problem-Based Learning (PBL) strategy. Method Action Research, involving 86 students from the second year of an undergraduate Nursing program in Spain. A Critical Incident Questionnaire and Group interview were used. Thematic/categorical analysis, triangulation of researchers, subjects and techniques. Results the students signal the need to have a view from within, reinforcing the criticism against the schematic dualism; PBL allows one to learn how to be with the other, with his mechanical and organic solidarity; the feeling together, with its emphasis on learning to work in group and wanting to be close to the person taking care. Conclusions The great contradictions the protagonists of the process, that is, the students experience seem to express that group learning is not a form of gaining knowledge, as it makes them lose time to study. The daily, the execution time and the imaginary of how learning should be do not seem to have an intersection point in the use of Problem-Based Learning. The importance of focusing on the daily and the imaginary should be reinforced when we consider nursing education. PMID:25029064
-
A Preliminary Survey of the Preferred Learning Methods for Interpretation Students
Heinz, Michael
2013-01-01
There are many different methods that individuals use to learn languages like reading books or writing essays. Not all methods are equally successful for second language learners but nor do all successful learners of a second language show identical preferences for learning methods. Additionally, at the highest level of language learning various…
-
Collaborative Learning at Engineering Universities: Benefits and Challenges
Olga V. Sumtsova; Tatiana Yu. Aikina; Liudmila M. Bolsunovskaya; Chris Phillips; Olga M. Zubkova; Peter J. Mitchell
2018-01-01
This paper concerns the cutting edge educational approaches incorporated into syllabuses of the most progressive Russian higher technical schools. The authors discuss one of the active methods in teaching foreign languages – collaborative learning implemented in e-courses. Theoretical and historical aspects of this approach are addressed, as are its suitability for engineering education and possible ways of introducing collaborative learning into e-courses. Collaborative learning technology o...
-
Studying depression using imaging and machine learning methods
Directory of Open Access Journals (Sweden)
Meenal J. Patel
2016-01-01
Full Text Available Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1 presents a background on depression, imaging, and machine learning methodologies; (2 reviews methodologies of past studies that have used imaging and machine learning to study depression; and (3 suggests directions for future depression-related studies.
-
Exploring the Learning of Language Through Global Dance and Music: a Theoretical Analysis
Banafi, Norah
2014-01-01
This research paper explores theories behind Total Physical Response (T.P.R) methods and psychology by associating them with music in order to examine the role of listening to music and dancing in language learning. This research utilises the five pillars of Zumba (music, dance, the power of now, enjoyment, and relaxing) that may create an environment for motivating language fluency learning and investigates whether these pillars have the potential for making Zumba, a global phenomenon in tea...
-
Comparison of Machine Learning methods for incipient motion in gravel bed rivers
Valyrakis, Manousos
2013-04-01
Soil erosion and sediment transport of natural gravel bed streams are important processes which affect both the morphology as well as the ecology of earth's surface. For gravel bed rivers at near incipient flow conditions, particle entrainment dynamics are highly intermittent. This contribution reviews the use of modern Machine Learning (ML) methods implemented for short term prediction of entrainment instances of individual grains exposed in fully developed near boundary turbulent flows. Results obtained by network architectures of variable complexity based on two different ML methods namely the Artificial Neural Network (ANN) and the Adaptive Neuro-Fuzzy Inference System (ANFIS) are compared in terms of different error and performance indices, computational efficiency and complexity as well as predictive accuracy and forecast ability. Different model architectures are trained and tested with experimental time series obtained from mobile particle flume experiments. The experimental setup consists of a Laser Doppler Velocimeter (LDV) and a laser optics system, which acquire data for the instantaneous flow and particle response respectively, synchronously. The first is used to record the flow velocity components directly upstream of the test particle, while the later tracks the particle's displacements. The lengthy experimental data sets (millions of data points) are split into the training and validation subsets used to perform the corresponding learning and testing of the models. It is demonstrated that the ANFIS hybrid model, which is based on neural learning and fuzzy inference principles, better predicts the critical flow conditions above which sediment transport is initiated. In addition, it is illustrated that empirical knowledge can be extracted, validating the theoretical assumption that particle ejections occur due to energetic turbulent flow events. Such a tool may find application in management and regulation of stream flows downstream of dams for stream
-
Coya, Liliam de Barbosa; Perez-Coffie, Jorge
1982-01-01
"Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…
-
SMALL GROUP LEARNING METHODS AND THEIR EFFECT ON LEARNERS’ RELATIONSHIPS
Directory of Open Access Journals (Sweden)
Radka Borůvková
2016-04-01
Full Text Available Building relationships in the classroom is an essential part of any teacher's career. Having healthy teacher-to-learner and learner-to-learner relationships is an effective way to help prevent pedagogical failure, social conflict and quarrelsome behavior. Many strategies are available that can be used to achieve good long-lasting relationships in the classroom setting. Successful teachers’ pedagogical work in the classroom requires detailed knowledge of learners’ relationships. Good understanding of the relationships is necessary, especially in the case of teenagers’ class. This sensitive period of adolescence demands attention of all teachers who should deal with the problems of their learners. Special care should be focused on children that are out of their classmates’ interest (so called isolated learners or isolates in such class and on possibilities to integrate them into the class. Natural idea how to do it is that of using some modern non-traditional teaching/learning methods, especially the methods based on work in small groups involving learners’ cooperation. Small group education (especially problem-based learning, project-based learning, cooperative learning, collaborative learning or inquire-based learning as one of these methods involves a high degree of interaction. The effectiveness of learning groups is determined by the extent to which the interaction enables members to clarify their own understanding, build upon each other's contributions, sift out meanings, ask and answer questions. An influence of this kind of methods (especially cooperative learning (CL on learners’ relationships was a subject of the further described research. Within the small group education, students work with their classmates to solve complex and authentic problems that help develop content knowledge as well as problem-solving, reasoning, communication, and self-assessment skills. The aim of the research was to answer the question: Can the
-
Sustainability of healthcare improvement: what can we learn from learning theory?
Directory of Open Access Journals (Sweden)
Hovlid Einar
2012-08-01
Full Text Available Abstract Background Changes that improve the quality of health care should be sustained. Falling back to old, unsatisfactory ways of working is a waste of resources and can in the worst case increase resistance to later initiatives to improve care. Quality improvement relies on changing the clinical system yet factors that influence the sustainability of quality improvements are poorly understood. Theoretical frameworks can guide further research on the sustainability of quality improvements. Theories of organizational learning have contributed to a better understanding of organizational change in other contexts. To identify factors contributing to sustainability of improvements, we use learning theory to explore a case that had displayed sustained improvement. Methods Førde Hospital redesigned the pathway for elective surgery and achieved sustained reduction of cancellation rates. We used a qualitative case study design informed by theory to explore factors that contributed to sustain the improvements at Førde Hospital. The model Evidence in the Learning Organization describes how organizational learning contributes to change in healthcare institutions. This model constituted the framework for data collection and analysis. We interviewed a strategic sample of 20 employees. The in-depth interviews covered themes identified through our theoretical framework. Through a process of coding and condensing, we identified common themes that were interpreted in relation to our theoretical framework. Results Clinicians and leaders shared information about their everyday work and related this knowledge to how the entire clinical pathway could be improved. In this way they developed a revised and deeper understanding of their clinical system and its interdependencies. They became increasingly aware of how different elements needed to interact to enhance the performance and how their own efforts could contribute. Conclusions The improved understanding of
-
A theoretical study on a convergence problem of nodal methods
Energy Technology Data Exchange (ETDEWEB)
Shaohong, Z.; Ziyong, L. [Shanghai Jiao Tong Univ., 1954 Hua Shan Road, Shanghai, 200030 (China); Chao, Y. A. [Westinghouse Electric Company, P. O. Box 355, Pittsburgh, PA 15230-0355 (United States)
2006-07-01
The effectiveness of modern nodal methods is largely due to its use of the information from the analytical flux solution inside a homogeneous node. As a result, the nodal coupling coefficients depend explicitly or implicitly on the evolving Eigen-value of a problem during its solution iteration process. This poses an inherently non-linear matrix Eigen-value iteration problem. This paper points out analytically that, whenever the half wave length of an evolving node interior analytic solution becomes smaller than the size of that node, this non-linear iteration problem can become inherently unstable and theoretically can always be non-convergent or converge to higher order harmonics. This phenomenon is confirmed, demonstrated and analyzed via the simplest 1-D problem solved by the simplest analytic nodal method, the Analytic Coarse Mesh Finite Difference (ACMFD, [1]) method. (authors)
-
Developing a Blended Learning-Based Method for Problem-Solving in Capability Learning
Dwiyogo, Wasis D.
2018-01-01
The main objectives of the study were to develop and investigate the implementation of blended learning based method for problem-solving. Three experts were involved in the study and all three had stated that the model was ready to be applied in the classroom. The implementation of the blended learning-based design for problem-solving was…
-
Zayapragassarazan, Z.; Kumar, Santosh
2012-01-01
Present generation students are primarily active learners with varied learning experiences and lecture courses may not suit all their learning needs. Effective learning involves providing students with a sense of progress and control over their own learning. This requires creating a situation where learners have a chance to try out or test their…
-
Learning Method and Its Influence on Nutrition Study Results Throwing the Ball
Samsudin; Nugraha, Bayu
2015-01-01
This study aimed to know the difference between playing and learning methods of exploratory learning methods to learning outcomes throwing the ball. In addition, this study also aimed to determine the effect of nutritional status of these two learning methods mentioned above. This research was conducted at SDN Cipinang Besar Selatan 16 Pagi East…
-
EXPLANATORY METHODS OF MARKETING DATA ANALYSIS – THEORETICAL AND METHODOLOGICAL CONSIDERATIONS
Directory of Open Access Journals (Sweden)
Rozalia GABOR
2010-01-01
Full Text Available Explanatory methods of data analysis – also named by some authors supervised learning methods - enable researchers to identify and analyse configurations of relations between two or several variables, most of them with a high accuracy, as there is possibility of testing statistic significance by calculating the confidence level associated with validation of relation concerned across the entire population and not only the surveyed sample. The paper shows some of these methods, respectively: variance analysis, covariance analysis, segmentation and discriminant analysis with the mention - for every method – of applicability area for marketing research.
-
International Nuclear Information System (INIS)
Xu, Yun-Chao; Chen, Qun
2013-01-01
The vapor-compression refrigeration systems have been one of the essential energy conversion systems for humankind and exhausting huge amounts of energy nowadays. Surrounding the energy efficiency promotion of the systems, there are lots of effectual optimization methods but mainly relied on engineering experience and computer simulations rather than theoretical analysis due to the complex and vague physical essence. We attempt to propose a theoretical global optimization method based on in-depth physical analysis for the involved physical processes, i.e. heat transfer analysis for condenser and evaporator, through introducing the entransy theory and thermodynamic analysis for compressor and expansion valve. The integration of heat transfer and thermodynamic analyses forms the overall physical optimization model for the systems to describe the relation between all the unknown parameters and known conditions, which makes theoretical global optimization possible. With the aid of the mathematical conditional extremum solutions, an optimization equation group and the optimal configuration of all the unknown parameters are analytically obtained. Eventually, via the optimization of a typical vapor-compression refrigeration system with various working conditions to minimize the total heat transfer area of heat exchangers, the validity and superior of the newly proposed optimization method is proved. - Highlights: • A global optimization method for vapor-compression systems is proposed. • Integrating heat transfer and thermodynamic analyses forms the optimization model. • A mathematical relation between design parameters and requirements is derived. • Entransy dissipation is introduced into heat transfer analysis. • The validity of the method is proved via optimization of practical cases
-
The Keyimage Method of Learning Sound-Symbol Correspondences: A Case Study of Learning Written Khmer
Directory of Open Access Journals (Sweden)
Elizabeth Lavolette
2009-01-01
Full Text Available I documented my strategies for learning sound-symbol correspondences during a Khmer course. I used a mnemonic strategy that I call the keyimage method. In this method, a character evokes an image (the keyimage, which evokes the corresponding sound. For example, the keyimage for the character 2 could be a swan with its head tucked in. This evokes the sound "kaw" that a swan makes, which sounds similar to the Khmer sound corresponding to 2. The method has some similarities to the keyword method. Considering the results of keyword studies, I hypothesize that the keyimage method is more effective than rote learning and that peer-generated keyimages are more effective than researcher- or teacher-generated keyimages, which are more effective than learner-generated ones. In Dr. Andrew Cohen's plenary presentation at the Hawaii TESOL 2007 conference, he mentioned that more case studies are needed on learning strategies (LSs. One reason to study LSs is that what learners do with input to produce output is unclear, and knowing what strategies learners use may help us understand that process (Dornyei, 2005, p. 170. Hopefully, we can use that knowledge to improve language learning, perhaps by teaching learners to use the strategies that we find. With that in mind, I have examined the LSs that I used in studying Khmer as a foreign language, focusing on learning the syllabic alphabet.
-
About possibilities using of theoretical calculation methods in radioecology
International Nuclear Information System (INIS)
Demoukhamedova, S.D.; Aliev, D.I.; Alieva, I.N.
2002-01-01
Full text: Increasing the radiation level into environment is accompanied by accumulation of radioactive compounds into organism and/or their migration into biosphere. Radiotoxins are accumulated into irradiated plants and animals in result of violation of exchanging processes. The are play an important role at the pathogenesis of irradiation. To date, there is well known that even small quantity of the pesticides capable intensified the radiation effect. To understand the mechanism of radiation effect on physiologically active compounds and their complexes, the knowledge of such molecules three-dimensional organization and electron structure is essential. This work is devoted to study the pesticides of carbamate range, i.e. 'sevin' and its derivatives the physiological activity of which has been connected with cholinesterase degradation. Spatial organization and conformational possibilities of the pesticides has been studied using a method of the theoretical conformational analysis on the base of computational program worked out in laboratory of Molecular Biophysics at the Baku State University. Quantum-chemical methods CNDO/2, AM1 and PM3 and complex programs 'LEV' were used in studies of electronic structures of 'sevin' and number of its analogues. Charge distribution on the atoms, optimization of geometrical electrooptic parameters, as well as molecular electrostatic potentials, electron density and nuclear forces were calculated. Visual maps and surface of valence electron density distribution in the given plane and surface of electron-nuclear forces distribution projection were constructed. The geometrical and energetic characteristics, charges on the atoms of investigated pesticides, as well as the maps and relief of the valence electron density distribution on the atoms have been received. According to calculation results, the changing of charge distribution in naphthalene ring is observed. The conclusion was made that the carbonyl group is essential for
-
Information-theoretic methods for estimating of complicated probability distributions
Zong, Zhi
2006-01-01
Mixing up various disciplines frequently produces something that are profound and far-reaching. Cybernetics is such an often-quoted example. Mix of information theory, statistics and computing technology proves to be very useful, which leads to the recent development of information-theory based methods for estimating complicated probability distributions. Estimating probability distribution of a random variable is the fundamental task for quite some fields besides statistics, such as reliability, probabilistic risk analysis (PSA), machine learning, pattern recognization, image processing, neur
-
Social Media and Seamless Learning: Lessons Learned
Panke, Stefanie; Kohls, Christian; Gaiser, Birgit
2017-01-01
The paper discusses best practice approaches and metrics for evaluation that support seamless learning with social media. We draw upon the theoretical frameworks of social learning theory, transfer learning (bricolage), and educational design patterns to elaborate upon different ideas for ways in which social media can support seamless learning.…
-
Kroos, Karmo
2012-03-01
This article examines the value of "eclecticism" as the foundation of meta-theoretical, mixed methods and interdisciplinary research in social sciences. On the basis of the analysis of the historical background of the concept, it is first suggested that eclecticism-based theoretical scholarship in social sciences could benefit from the more systematic research method that has been developed for synthesizing theoretical works under the name metatheorizing. Second, it is suggested that the mixed methods community could base its research approach on philosophical eclecticism instead of pragmatism because the basic idea of eclecticism is much more in sync with the nature of the combined research tradition. Finally, the Kuhnian frame is used to support the argument for interdisciplinary research and, hence, eclecticism in social sciences (rather than making an argument against multiple paradigms). More particularly, it is suggested that integrating the different (inter)disciplinary traditions and schools into one is not necessarily desirable at all in social sciences because of the complexity and openness of the research field. If it is nevertheless attempted, experience in economics suggests that paradigmatic unification comes at a high price.
-
Towards a Quality Assessment Method for Learning Preference Profiles in Negotiation
Hindriks, Koen V.; Tykhonov, Dmytro
In automated negotiation, information gained about an opponent's preference profile by means of learning techniques may significantly improve an agent's negotiation performance. It therefore is useful to gain a better understanding of how various negotiation factors influence the quality of learning. The quality of learning techniques in negotiation are typically assessed indirectly by means of comparing the utility levels of agreed outcomes and other more global negotiation parameters. An evaluation of learning based on such general criteria, however, does not provide any insight into the influence of various aspects of negotiation on the quality of the learned model itself. The quality may depend on such aspects as the domain of negotiation, the structure of the preference profiles, the negotiation strategies used by the parties, and others. To gain a better understanding of the performance of proposed learning techniques in the context of negotiation and to be able to assess the potential to improve the performance of such techniques a more systematic assessment method is needed. In this paper we propose such a systematic method to analyse the quality of the information gained about opponent preferences by learning in single-instance negotiations. The method includes measures to assess the quality of a learned preference profile and proposes an experimental setup to analyse the influence of various negotiation aspects on the quality of learning. We apply the method to a Bayesian learning approach for learning an opponent's preference profile and discuss our findings.
-
Preparing Students for Flipped or Team-Based Learning Methods
Balan, Peter; Clark, Michele; Restall, Gregory
2015-01-01
Purpose: Teaching methods such as Flipped Learning and Team-Based Learning require students to pre-learn course materials before a teaching session, because classroom exercises rely on students using self-gained knowledge. This is the reverse to "traditional" teaching when course materials are presented during a lecture, and students are…
-
Different protein-protein interface patterns predicted by different machine learning methods.
Wang, Wei; Yang, Yongxiao; Yin, Jianxin; Gong, Xinqi
2017-11-22
Different types of protein-protein interactions make different protein-protein interface patterns. Different machine learning methods are suitable to deal with different types of data. Then, is it the same situation that different interface patterns are preferred for prediction by different machine learning methods? Here, four different machine learning methods were employed to predict protein-protein interface residue pairs on different interface patterns. The performances of the methods for different types of proteins are different, which suggest that different machine learning methods tend to predict different protein-protein interface patterns. We made use of ANOVA and variable selection to prove our result. Our proposed methods taking advantages of different single methods also got a good prediction result compared to single methods. In addition to the prediction of protein-protein interactions, this idea can be extended to other research areas such as protein structure prediction and design.
-
A Review on Different Virtual Learning Methods in Pharmacy Education
Directory of Open Access Journals (Sweden)
Amin Noori
2015-10-01
Full Text Available Virtual learning is a type of electronic learning system based on the web. It models traditional in- person learning by providing virtual access to classes, tests, homework, feedbacks and etc. Students and teachers can interact through chat rooms or other virtual environments. Web 2.0 services are usually used for this method. Internet audio-visual tools, multimedia systems, a disco CD-ROMs, videotapes, animation, video conferencing, and interactive phones can all be used to deliver data to the students. E-learning can occur in or out of the classroom. It is time saving with lower costs compared to traditional methods. It can be self-paced, it is suitable for distance learning and it is flexible. It is a great learning style for continuing education and students can independently solve their problems but it has its disadvantages too. Thereby, blended learning (combination of conventional and virtual education is being used worldwide and has improved knowledge, skills and confidence of pharmacy students.The aim of this study is to review, discuss and introduce different methods of virtual learning for pharmacy students.Google scholar, Pubmed and Scupus databases were searched for topics related to virtual, electronic and blended learning and different styles like computer simulators, virtual practice environment technology, virtual mentor, virtual patient, 3D simulators, etc. are discussed in this article.Our review on different studies on these areas shows that the students are highly satisfied withvirtual and blended types of learning.
-
A deep learning-based multi-model ensemble method for cancer prediction.
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.
-
Rondon, Silmara; Sassi, Fernanda Chiarion; Furquim de Andrade, Claudia Regina
2013-02-25
Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students' prior knowledge (i.e. before undergoing the learning method), short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method) were assessed with a multiple choice questionnaire. Students' performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students' short and long-term knowledge retention.
-
Directory of Open Access Journals (Sweden)
Davies Bethany S
2012-01-01
Full Text Available Abstract Background Mobile technology is increasingly being used by clinicians to access up-to-date information for patient care. These offer learning opportunities in the clinical setting for medical students but the underlying pedagogic theories are not clear. A conceptual framework is needed to understand these further. Our initial questions were how the medical students used the technology, how it enabled them to learn and what theoretical underpinning supported the learning. Methods 387 medical students were provided with a personal digital assistant (PDA loaded with medical resources for the duration of their clinical studies. Outcomes were assessed by a mixed-methods triangulation approach using qualitative and quantitative analysis of surveys, focus groups and usage tracking data. Results Learning occurred in context with timely access to key facts and through consolidation of knowledge via repetition. The PDA was an important addition to the learning ecology rather than a replacement. Contextual factors impacted on use both positively and negatively. Barriers included concerns of interrupting the clinical interaction and of negative responses from teachers and patients. Students preferred a future involving smartphone platforms. Conclusions This is the first study to describe the learning ecology and pedagogic basis behind the use of mobile learning technologies in a large cohort of undergraduate medical students in the clinical environment. We have developed a model for mobile learning in the clinical setting that shows how different theories contribute to its use taking into account positive and negative contextual factors. The lessons from this study are transferable internationally, to other health care professions and to the development of similar initiatives with newer technology such as smartphones or tablet computers.
-
Directory of Open Access Journals (Sweden)
Rondon Silmara
2013-02-01
Full Text Available Abstract Background Educational computer games are examples of computer-assisted learning objects, representing an educational strategy of growing interest. Given the changes in the digital world over the last decades, students of the current generation expect technology to be used in advancing their learning requiring a need to change traditional passive learning methodologies to an active multisensory experimental learning methodology. The objective of this study was to compare a computer game-based learning method with a traditional learning method, regarding learning gains and knowledge retention, as means of teaching head and neck Anatomy and Physiology to Speech-Language and Hearing pathology undergraduate students. Methods Students were randomized to participate to one of the learning methods and the data analyst was blinded to which method of learning the students had received. Students’ prior knowledge (i.e. before undergoing the learning method, short-term knowledge retention and long-term knowledge retention (i.e. six months after undergoing the learning method were assessed with a multiple choice questionnaire. Students’ performance was compared considering the three moments of assessment for both for the mean total score and for separated mean scores for Anatomy questions and for Physiology questions. Results Students that received the game-based method performed better in the pos-test assessment only when considering the Anatomy questions section. Students that received the traditional lecture performed better in both post-test and long-term post-test when considering the Anatomy and Physiology questions. Conclusions The game-based learning method is comparable to the traditional learning method in general and in short-term gains, while the traditional lecture still seems to be more effective to improve students’ short and long-term knowledge retention.
-
Data mining methods application in reflexive adaptation realization in e-learning systems
Directory of Open Access Journals (Sweden)
A. S. Bozhday
2017-01-01
the principle of reflexive adaptation in software systems applicable to a wide class of applied programs; The development of a universal architectural template of the software system, oriented to restructuring in the process of operation; Algorithm for self-optimization of the user interface of the software system based on methods of data mining.The development of the theoretical basis for the automatic reorganization of e-learning software will increase the flexibility of the virtual educational environment and increase the period of its exploitation. Unlike existing analogues, the methods proposed in the article are universal and applicable to a wide class of applied programs. This is relevant for e-learning systems, because their may have a different types and purposes (for example, virtual simulators and information library software may be components of one system.
-
Two Undergraduate Process Modeling Courses Taught Using Inductive Learning Methods
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…
-
On Combining Elements of Different Ways of Learning, Methods and Knowledge
Directory of Open Access Journals (Sweden)
Dušana Findeisen
2013-12-01
Full Text Available The paper deals with different thinkers' attitude towards methods in adult education. It examines the value of some elements of »trial and error learning« and »non-directive learning«. Like a multifaceted approach based on elements drawn from different methods, the way we learn can also be eclectic. To illustrate this assertion, the author analyses the »anti method« used by Maurice Pialat, a French film director, contrasting it with methods in which the aim is set in advance and the process leading towards it is organised in sequences. This is most often the case in script-based shooting of films, directing a theatre performance or running adult education. Moreover, the author argues that learning about how to do something is combined with learning about how to be. She further emphasises that methods should not be used to impose one’s knowledge and one’s reality on the learner, thus destroying circumstances necessary for gaining or creating knowledge.
-
Directory of Open Access Journals (Sweden)
Rosa Haydeé Zárate Quiñones
2016-06-01
Full Text Available This research was conducted in order to apply the experimental method of learning for Sustainable Development in students of the Faculty of Forestry and Environmental Sciences of the National University of Central Peru. For its development we worked with a sample of 1062 students and a quasi-experimental design was used. Were employed different methods of mathematical theoretical, empirical and statistical level that allowed data collection, analysis and interpretation of results. A test of knowledge in Environmental Education for Sustainable Development to students, a questionnaire of perception and opinion, as well as a questionnaire of teacher training was applied. The experimental method used allowed the development of knowledge, habits and environmental values for sustainable development in students, contributing to the protection and conservation of the environment.
-
Intelligent Learning System using cognitive science theory and artificial intelligence methods
Energy Technology Data Exchange (ETDEWEB)
Cristensen, D.L.
1986-01-01
This dissertation is a presentation of a theoretical model of an intelligent Learning System (ILS). The approach view intelligent computer-based instruction on a curricular-level and educational-theory base, instead of the conventional instructional-only level. The ILS is divided into two components: (1) macro-level, curricular; and (2) micro-level (MAIS), instructional. The primary purpose of the ILS macro level is to establish the initial conditions of learning by considering individual difference variables within specification of the curriculum content domain. Second, the ILS macro-level will iteratively update the conditions of learning as the individual student progresses through the given curriculum. The term dynamic is used to describe the expert tutor that establishes and monitors the conditions of instruction between the ILS macro level and the micro level. As the student progresses through the instruction, appropriate information is sent back continuously to the macro level to constantly improve decision making for succeeding conditions of instruction.
-
Directory of Open Access Journals (Sweden)
Stanislawski Jerzy
2013-01-01
Full Text Available Abstract Background Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. Results We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%. The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile to 0.5 CPU-hours (simplified 3D profile to seconds (machine learning. Conclusions We showed that the simplified profile generation method does not introduce an error with regard to the original method, while
-
Stanislawski, Jerzy; Kotulska, Malgorzata; Unold, Olgierd
2013-01-17
Amyloids are proteins capable of forming fibrils. Many of them underlie serious diseases, like Alzheimer disease. The number of amyloid-associated diseases is constantly increasing. Recent studies indicate that amyloidogenic properties can be associated with short segments of aminoacids, which transform the structure when exposed. A few hundreds of such peptides have been experimentally found. Experimental testing of all possible aminoacid combinations is currently not feasible. Instead, they can be predicted by computational methods. 3D profile is a physicochemical-based method that has generated the most numerous dataset - ZipperDB. However, it is computationally very demanding. Here, we show that dataset generation can be accelerated. Two methods to increase the classification efficiency of amyloidogenic candidates are presented and tested: simplified 3D profile generation and machine learning methods. We generated a new dataset of hexapeptides, using more economical 3D profile algorithm, which showed very good classification overlap with ZipperDB (93.5%). The new part of our dataset contains 1779 segments, with 204 classified as amyloidogenic. The dataset of 6-residue sequences with their binary classification, based on the energy of the segment, was applied for training machine learning methods. A separate set of sequences from ZipperDB was used as a test set. The most effective methods were Alternating Decision Tree and Multilayer Perceptron. Both methods obtained area under ROC curve of 0.96, accuracy 91%, true positive rate ca. 78%, and true negative rate 95%. A few other machine learning methods also achieved a good performance. The computational time was reduced from 18-20 CPU-hours (full 3D profile) to 0.5 CPU-hours (simplified 3D profile) to seconds (machine learning). We showed that the simplified profile generation method does not introduce an error with regard to the original method, while increasing the computational efficiency. Our new dataset
-
Directory of Open Access Journals (Sweden)
Dania Regueira Martínez
2014-03-01
Full Text Available This article presents the learning task considered as the unit of smaller organization level in the teaching-learning process that conditions in its systemic structuring, the learning actions, for the students acquisition of the content, by means of the development of the reflection and the metacognitiv e regulation when they conscious ly or partially plan different types of learning strategies in the ir realization, with the objective to solv e the pedagogic professional problems that are p resented in the disciplines they receive and in its research task during the direction o f the teaching-learning process.
-
Actively Teaching Research Methods with a Process Oriented Guided Inquiry Learning Approach
Mullins, Mary H.
2017-01-01
Active learning approaches have shown to improve student learning outcomes and improve the experience of students in the classroom. This article compares a Process Oriented Guided Inquiry Learning style approach to a more traditional teaching method in an undergraduate research methods course. Moving from a more traditional learning environment to…
-
Rabgay, Tshewang
2018-01-01
The study investigated the effect of using cooperative learning method on tenth grade students' learning achievement in biology and their attitude towards the subject in a Higher Secondary School in Bhutan. The study used a mixed method approach. The quantitative component included an experimental design where cooperative learning was the…
-
Educational Communities of Inquiry: Theoretical Framework, Research and Practice
Akyol, Zehra; Garrison, D. Randy
2013-01-01
Communications technologies have been continuously integrated into learning and training environments which has revealed the need for a clear understanding of the process. The Community of Inquiry (COI) Theoretical Framework has a philosophical foundation which provides planned guidelines and principles to development useful learning environments…
-
Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin
2014-01-01
This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study…
-
Theoretical Methods of Domain Structures in Ultrathin Ferroelectric Films: A Review
Directory of Open Access Journals (Sweden)
Jianyi Liu
2014-09-01
Full Text Available This review covers methods and recent developments of the theoretical study of domain structures in ultrathin ferroelectric films. The review begins with an introduction to some basic concepts and theories (e.g., polarization and its modern theory, ferroelectric phase transition, domain formation, and finite size effects, etc. that are relevant to the study of domain structures in ultrathin ferroelectric films. Basic techniques and recent progress of a variety of important approaches for domain structure simulation, including first-principles calculation, molecular dynamics, Monte Carlo simulation, effective Hamiltonian approach and phase field modeling, as well as multiscale simulation are then elaborated. For each approach, its important features and relative merits over other approaches for modeling domain structures in ultrathin ferroelectric films are discussed. Finally, we review recent theoretical studies on some important issues of domain structures in ultrathin ferroelectric films, with an emphasis on the effects of interfacial electrostatics, boundary conditions and external loads.
-
Theoretical and numerical investigations into the SPRT method for anomaly detection
International Nuclear Information System (INIS)
Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E.
1995-01-01
The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author)
-
Theoretical and numerical investigations into the SPRT method for anomaly detection
Energy Technology Data Exchange (ETDEWEB)
Schoonewelle, H.; Hagen, T.H.J.J. van der; Hoogenboom, J.E. [Interuniversitair Reactor Inst., Delft (Netherlands)
1995-11-01
The sequential probability ratio test developed by Wald is a powerful method of testing an alternative hypothesis against a null hypothesis. This makes the method applicable for anomaly detection. In this paper the method is used to detect a change of the standard deviation of a Gaussian distributed white noise signal. The false alarm probability, the alarm failure probability and the average time to alarm of the method, which are important parameters for anomaly detection, are determined by simulation and compared with theoretical results. Each of the three parameters is presented in dependence of the other two and the ratio of the standard deviation of the anomalous signal and that of the normal signal. Results show that the method is very well suited for anomaly detection. It can detect for example a 50% change in standard deviation within 1 second with a false alarm and alarm failure rate of less than once per month. (author).
-
Learning in Non-Stationary Environments Methods and Applications
Lughofer, Edwin
2012-01-01
Recent decades have seen rapid advances in automatization processes, supported by modern machines and computers. The result is significant increases in system complexity and state changes, information sources, the need for faster data handling and the integration of environmental influences. Intelligent systems, equipped with a taxonomy of data-driven system identification and machine learning algorithms, can handle these problems partially. Conventional learning algorithms in a batch off-line setting fail whenever dynamic changes of the process appear due to non-stationary environments and external influences. Learning in Non-Stationary Environments: Methods and Applications offers a wide-ranging, comprehensive review of recent developments and important methodologies in the field. The coverage focuses on dynamic learning in unsupervised problems, dynamic learning in supervised classification and dynamic learning in supervised regression problems. A later section is dedicated to applications in which dyna...
-
Toward a Social Approach to Learning in Community Service Learning
Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda
2004-01-01
The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…
-
Korotcov, Alexandru; Tkachenko, Valery; Russo, Daniel P; Ekins, Sean
2017-12-04
Machine learning methods have been applied to many data sets in pharmaceutical research for several decades. The relative ease and availability of fingerprint type molecular descriptors paired with Bayesian methods resulted in the widespread use of this approach for a diverse array of end points relevant to drug discovery. Deep learning is the latest machine learning algorithm attracting attention for many of pharmaceutical applications from docking to virtual screening. Deep learning is based on an artificial neural network with multiple hidden layers and has found considerable traction for many artificial intelligence applications. We have previously suggested the need for a comparison of different machine learning methods with deep learning across an array of varying data sets that is applicable to pharmaceutical research. End points relevant to pharmaceutical research include absorption, distribution, metabolism, excretion, and toxicity (ADME/Tox) properties, as well as activity against pathogens and drug discovery data sets. In this study, we have used data sets for solubility, probe-likeness, hERG, KCNQ1, bubonic plague, Chagas, tuberculosis, and malaria to compare different machine learning methods using FCFP6 fingerprints. These data sets represent whole cell screens, individual proteins, physicochemical properties as well as a data set with a complex end point. Our aim was to assess whether deep learning offered any improvement in testing when assessed using an array of metrics including AUC, F1 score, Cohen's kappa, Matthews correlation coefficient and others. Based on ranked normalized scores for the metrics or data sets Deep Neural Networks (DNN) ranked higher than SVM, which in turn was ranked higher than all the other machine learning methods. Visualizing these properties for training and test sets using radar type plots indicates when models are inferior or perhaps over trained. These results also suggest the need for assessing deep learning further
-
Roca, Judith; Reguant, Mercedes; Canet, Olga
2016-11-01
Teaching strategies are essential in order to facilitate meaningful learning and the development of high-level thinking skills in students. To compare three teaching methodologies (problem-based learning, case-based teaching and traditional methods) in terms of the learning outcomes achieved by nursing students. This quasi-experimental research was carried out in the Nursing Degree programme in a group of 74 students who explored the subject of The Oncology Patient through the aforementioned strategies. A performance test was applied based on Bloom's Revised Taxonomy. A significant correlation was found between the intragroup theoretical and theoretical-practical dimensions. Likewise, intergroup differences were related to each teaching methodology. Hence, significant differences were estimated between the traditional methodology (x-=9.13), case-based teaching (x-=12.96) and problem-based learning (x-=14.84). Problem-based learning was shown to be the most successful learning method, followed by case-based teaching and the traditional methodology. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Efficient learning strategy of Chinese characters based on network approach.
Directory of Open Access Journals (Sweden)
Xiaoyong Yan
Full Text Available We develop an efficient learning strategy of Chinese characters based on the network of the hierarchical structural relations between Chinese characters. A more efficient strategy is that of learning the same number of useful Chinese characters in less effort or time. We construct a node-weighted network of Chinese characters, where character usage frequencies are used as node weights. Using this hierarchical node-weighted network, we propose a new learning method, the distributed node weight (DNW strategy, which is based on a new measure of nodes' importance that considers both the weight of the nodes and its location in the network hierarchical structure. Chinese character learning strategies, particularly their learning order, are analyzed as dynamical processes over the network. We compare the efficiency of three theoretical learning methods and two commonly used methods from mainstream Chinese textbooks, one for Chinese elementary school students and the other for students learning Chinese as a second language. We find that the DNW method significantly outperforms the others, implying that the efficiency of current learning methods of major textbooks can be greatly improved.
-
Advanced Steel Microstructural Classification by Deep Learning Methods.
Azimi, Seyed Majid; Britz, Dominik; Engstler, Michael; Fritz, Mario; Mücklich, Frank
2018-02-01
The inner structure of a material is called microstructure. It stores the genesis of a material and determines all its physical and chemical properties. While microstructural characterization is widely spread and well known, the microstructural classification is mostly done manually by human experts, which gives rise to uncertainties due to subjectivity. Since the microstructure could be a combination of different phases or constituents with complex substructures its automatic classification is very challenging and only a few prior studies exist. Prior works focused on designed and engineered features by experts and classified microstructures separately from the feature extraction step. Recently, Deep Learning methods have shown strong performance in vision applications by learning the features from data together with the classification step. In this work, we propose a Deep Learning method for microstructural classification in the examples of certain microstructural constituents of low carbon steel. This novel method employs pixel-wise segmentation via Fully Convolutional Neural Network (FCNN) accompanied by a max-voting scheme. Our system achieves 93.94% classification accuracy, drastically outperforming the state-of-the-art method of 48.89% accuracy. Beyond the strong performance of our method, this line of research offers a more robust and first of all objective way for the difficult task of steel quality appreciation.
-
Institute of Scientific and Technical Information of China (English)
无
2006-01-01
A set of scientific theories and an effective acupuncture therapy for insomnia about "the needling method for tranquillization and calming the mind" are gradually formed through many years' theoretical and clinical studies. In this paper, the theoretical intention about "the needling method for tranquillization and calming the mind" for treatment of insomnia are briefly introduced mainly from the cause of disease,pathogenesis, therapeutic method and characteristics of composition of a prescription, etc. in order to provide a new train of thoughts and a new method for working out scientific and standard prescriptions in the treatment of insomnia.
-
DEFF Research Database (Denmark)
Lauridsen, Karen M.; Lauridsen, Ole
Ole Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Karen M. Lauridsen, Aarhus School of Business and Social Sciences, Aarhus University, Denmark Learning Styles in Higher Education – Learning How to Learn Applying learning styles (LS) in higher education...... by Constructivist learning theory and current basic knowledge of how the brain learns. The LS concept will thus be placed in a broader learning theoretical context as a strong learning and teaching tool. Participants will be offered the opportunity to have their own LS preferences established before...... teaching leads to positive results and enhanced student learning. However, learning styles should not only be considered a didactic matter for the teacher, but also a tool for the individual students to improve their learning capabilities – not least in contexts where information is not necessarily...
-
Implementation of Active Learning Method in Unit Operations II Subject
Ma'mun, Sholeh
2018-01-01
ABSTRACT: Active Learning Method which requires students to take an active role in the process of learning in the classroom has been applied in Department of Chemical Engineering, Faculty of Industrial Technology, Islamic University of Indonesia for Unit Operations II subject in the Even Semester of Academic Year 2015/2016. The purpose of implementation of the learning method is to assist students in achieving competencies associated with the Unit Operations II subject and to help in creating...
-
Researching workplace learning
DEFF Research Database (Denmark)
Jørgensen, Christian Helms; Warring, Niels
2007-01-01
This article presents a theoretical and methodological framework for understanding and researching learning in the workplace. The workplace is viewed in a societal context and the learner is viewed as more than an employee in order to understand the learning process in relation to the learner......'s life history.Moreover we will explain the need to establish a 'double view' by examining learning in the workplace both as an objective and as a subjective reality. The article is mainly theoretical, but can also be of interest to practitioners who wish to understand learning in the workplace both...
-
Social media marketing as an entrepreneurial learning process
Lagrosen, Stefan; Josefsson, Pernilla
2011-01-01
The purpose for this paper is to explore social media marketing fromthe perspective of entrepreneurial learning. The theoretical basis consists ofcontributions from the fields of organisational learning and entrepreneurship.An empirical study involving ten companies has been carried out. Thedata were analysed with methods inspired by grounded theory. Categoriesdescribing the companies’ social media presence from an entrepreneuriallearning perspective are provided. The value of using organisat...
-
TEACHING METHODS IN MBA AND LIFELONG LEARNING PROGRAMMES FOR MANAGERS
Directory of Open Access Journals (Sweden)
Jarošová, Eva
2017-09-01
Full Text Available Teaching methods in MBA and Lifelong Learning Programmes (LLP for managers should be topically relevant in terms of content as well as the teaching methods used. In terms of the content, the integral part of MBA and Lifelong Learning Programmes for managers should be the development of participants’ leadership competencies and their understanding of current leadership concepts. The teaching methods in educational programmes for managers as adult learners should correspond to the strategy of learner-centred teaching that focuses on the participants’ learning process and their active involvement in class. The focus on the participants’ learning process also raises questions about whether the programme’s participants perceive the teaching methods used as useful and relevant for their development as leaders. The paper presents the results of the analysis of the responses to these questions in a sample of 54 Czech participants in the MBA programme and of lifelong learning programmes at the University of Economics, Prague. The data was acquired based on written or electronically submitted questionnaires. The data was analysed in relation to the usefulness of the teaching methods for understanding the concepts of leadership, leadership skills development as well as respondents’ personal growth. The results show that the respondents most valued the methods that enabled them to get feedback, activated them throughout the programme and got them involved in discussions with others in class. Implications for managerial education practices are discussed.
-
Investigating Learning with an Interactive Tutorial: A Mixed-Methods Strategy
de Villiers, M. R.; Becker, Daphne
2017-01-01
From the perspective of parallel mixed-methods research, this paper describes interactivity research that employed usability-testing technology to analyse cognitive learning processes; personal learning styles and times; and errors-and-recovery of learners using an interactive e-learning tutorial called "Relations." "Relations"…
-
E-learning and blended learning in orthodontic education
Directory of Open Access Journals (Sweden)
Avinash Kumar
2017-01-01
Full Text Available The purpose of this article is to evaluate how effective and efficient e-learning and blended learning is when compared with traditional face-to-face learning in orthodontic education. This article also provides a comparison between face-to-face learning, e-learning, and blended learning. An open PubMed literature search was done from 1980 to 2015, and a total of 23 relevant key articles were reviewed. Information emerging from studies in orthodontic education has indicated that e-learning classes are at least as good as and/or better than face-to-face classroom learning. Till date, only one study stated that the face-to-face conventional learning is better than e-learning. Two studies stated that blended approach using both traditional face-to-face learning and e-learning is the best method. In one study, the advantages of e-learning observed in the theoretical fields of orthodontics were not achieved in learning practical procedures for manual skills. Few studies found improvements in the efficiency of learning with e-learning program. Studies performed through questionnaires showed that student's attitude and acceptance toward the use of e-learning was positive and favorable; however, blended learning was always rated high. Future research should be based on experiences of both faculty and student on a large scale for implementation of e-learning and blended learning in academic institutions. There is also need to provide professional development for faculty who will be teaching both in the physical and virtual environments.
-
Directory of Open Access Journals (Sweden)
Gabriele Berkenbusch
2009-01-01
Full Text Available Conversational analysis—situated between pragmatic linguistics and qualitative empirical research—is a complex method, which needs a lot of time and dedication. It is necessary to develop a so-called “analytical mentality”. The aim of the project presented in this paper was to develop the theoretical insights and the practical skills of a group of students for this kind of research. They worked together throughout the duration of the project, especially in the collec¬tion of empiric material: i.e. the recording of conversations between foreign and German stu¬dents, the transcription of the material, a group discussion on the data and finally its analysis. This articles aims at showing what students can learn by doing this kind of work, based on examples of the collected empirical material: (1 they will be introduced to the different levels and stages of the research process and have the chance to develop a methodical and methodological competence; (2 their general communicative competences and their special competences of the foreign language will increase, as well as (3 their knowledge of intercultural learning by working with authentic data of intercultural communication. So, for instance, stereotypes and how they have been constructed during the interaction may be analysed and precisely described on a micro-analytical level. URN: urn:nbn:de:0114-fqs0901335
-
Considerations for Task Analysis Methods and Rapid E-Learning Development Techniques
Directory of Open Access Journals (Sweden)
Dr. Ismail Ipek
2014-02-01
Full Text Available The purpose of this paper is to provide basic dimensions for rapid training development in e-learning courses in education and business. Principally, it starts with defining task analysis and how to select tasks for analysis and task analysis methods for instructional design. To do this, first, learning and instructional technologies as visions of the future were discussed. Second, the importance of task analysis methods in rapid e-learning was considered, with learning technologies as asynchronous and synchronous e-learning development. Finally, rapid instructional design concepts and e-learning design strategies were defined and clarified with examples, that is, all steps for effective task analysis and rapid training development techniques based on learning and instructional design approaches were discussed, such as m-learning and other delivery systems. As a result, the concept of task analysis, rapid e-learning development strategies and the essentials of online course design were discussed, alongside learner interface design features for learners and designers.
-
Kim, Jihun; Kim, Jonghong; Jang, Gil-Jin; Lee, Minho
2017-03-01
Deep learning has received significant attention recently as a promising solution to many problems in the area of artificial intelligence. Among several deep learning architectures, convolutional neural networks (CNNs) demonstrate superior performance when compared to other machine learning methods in the applications of object detection and recognition. We use a CNN for image enhancement and the detection of driving lanes on motorways. In general, the process of lane detection consists of edge extraction and line detection. A CNN can be used to enhance the input images before lane detection by excluding noise and obstacles that are irrelevant to the edge detection result. However, training conventional CNNs requires considerable computation and a big dataset. Therefore, we suggest a new learning algorithm for CNNs using an extreme learning machine (ELM). The ELM is a fast learning method used to calculate network weights between output and hidden layers in a single iteration and thus, can dramatically reduce learning time while producing accurate results with minimal training data. A conventional ELM can be applied to networks with a single hidden layer; as such, we propose a stacked ELM architecture in the CNN framework. Further, we modify the backpropagation algorithm to find the targets of hidden layers and effectively learn network weights while maintaining performance. Experimental results confirm that the proposed method is effective in reducing learning time and improving performance. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Directory of Open Access Journals (Sweden)
Janina A. M. Lehmann
2017-10-01
Full Text Available This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive details such as background music worsen learning. Moreover, as working memory capacity has a crucial influence on learning with seductive details, we also included the learner’s working memory capacity as a factor in our study. We tested 81 college students using a between-subject design with half of the sample listening to two pop songs while learning a visual text and the other half learning in silence. We included working memory capacity in the design as a continuous organism variable. Arousal and mood scores before and after learning were collected as potential mediating variables. To measure learning outcomes we tested recall and comprehension. We did not find a mediation effect between background music and arousal or mood on learning outcomes. In addition, for recall performance there were no main effects of background music or working memory capacity, nor an interaction effect of these factors. However, when considering comprehension we did find an interaction between background music and working memory capacity: the higher the learners’ working memory capacity, the better they learned with background music. This is in line with the seductive detail assumption.
-
Lehmann, Janina A M; Seufert, Tina
2017-01-01
This study investigates how background music influences learning with respect to three different theoretical approaches. Both the Mozart effect as well as the arousal-mood-hypothesis indicate that background music can potentially benefit learning outcomes. While the Mozart effect assumes a direct influence of background music on cognitive abilities, the arousal-mood-hypothesis assumes a mediation effect over arousal and mood. However, the seductive detail effect indicates that seductive details such as background music worsen learning. Moreover, as working memory capacity has a crucial influence on learning with seductive details, we also included the learner's working memory capacity as a factor in our study. We tested 81 college students using a between-subject design with half of the sample listening to two pop songs while learning a visual text and the other half learning in silence. We included working memory capacity in the design as a continuous organism variable. Arousal and mood scores before and after learning were collected as potential mediating variables. To measure learning outcomes we tested recall and comprehension. We did not find a mediation effect between background music and arousal or mood on learning outcomes. In addition, for recall performance there were no main effects of background music or working memory capacity, nor an interaction effect of these factors. However, when considering comprehension we did find an interaction between background music and working memory capacity: the higher the learners' working memory capacity, the better they learned with background music. This is in line with the seductive detail assumption.
-
Directory of Open Access Journals (Sweden)
Ross S Williamson
2015-04-01
Full Text Available Stimulus dimensionality-reduction methods in neuroscience seek to identify a low-dimensional space of stimulus features that affect a neuron's probability of spiking. One popular method, known as maximally informative dimensions (MID, uses an information-theoretic quantity known as "single-spike information" to identify this space. Here we examine MID from a model-based perspective. We show that MID is a maximum-likelihood estimator for the parameters of a linear-nonlinear-Poisson (LNP model, and that the empirical single-spike information corresponds to the normalized log-likelihood under a Poisson model. This equivalence implies that MID does not necessarily find maximally informative stimulus dimensions when spiking is not well described as Poisson. We provide several examples to illustrate this shortcoming, and derive a lower bound on the information lost when spiking is Bernoulli in discrete time bins. To overcome this limitation, we introduce model-based dimensionality reduction methods for neurons with non-Poisson firing statistics, and show that they can be framed equivalently in likelihood-based or information-theoretic terms. Finally, we show how to overcome practical limitations on the number of stimulus dimensions that MID can estimate by constraining the form of the non-parametric nonlinearity in an LNP model. We illustrate these methods with simulations and data from primate visual cortex.
-
Machine Learning Methods for Attack Detection in the Smart Grid.
Ozay, Mete; Esnaola, Inaki; Yarman Vural, Fatos Tunay; Kulkarni, Sanjeev R; Poor, H Vincent
2016-08-01
Attack detection problems in the smart grid are posed as statistical learning problems for different attack scenarios in which the measurements are observed in batch or online settings. In this approach, machine learning algorithms are used to classify measurements as being either secure or attacked. An attack detection framework is provided to exploit any available prior knowledge about the system and surmount constraints arising from the sparse structure of the problem in the proposed approach. Well-known batch and online learning algorithms (supervised and semisupervised) are employed with decision- and feature-level fusion to model the attack detection problem. The relationships between statistical and geometric properties of attack vectors employed in the attack scenarios and learning algorithms are analyzed to detect unobservable attacks using statistical learning methods. The proposed algorithms are examined on various IEEE test systems. Experimental analyses show that machine learning algorithms can detect attacks with performances higher than attack detection algorithms that employ state vector estimation methods in the proposed attack detection framework.
-
Upper-Lower Bounds Candidate Sets Searching Algorithm for Bayesian Network Structure Learning
Directory of Open Access Journals (Sweden)
Guangyi Liu
2014-01-01
Full Text Available Bayesian network is an important theoretical model in artificial intelligence field and also a powerful tool for processing uncertainty issues. Considering the slow convergence speed of current Bayesian network structure learning algorithms, a fast hybrid learning method is proposed in this paper. We start with further analysis of information provided by low-order conditional independence testing, and then two methods are given for constructing graph model of network, which is theoretically proved to be upper and lower bounds of the structure space of target network, so that candidate sets are given as a result; after that a search and scoring algorithm is operated based on the candidate sets to find the final structure of the network. Simulation results show that the algorithm proposed in this paper is more efficient than similar algorithms with the same learning precision.
-
A reward optimization method based on action subrewards in hierarchical reinforcement learning.
Fu, Yuchen; Liu, Quan; Ling, Xionghong; Cui, Zhiming
2014-01-01
Reinforcement learning (RL) is one kind of interactive learning methods. Its main characteristics are "trial and error" and "related reward." A hierarchical reinforcement learning method based on action subrewards is proposed to solve the problem of "curse of dimensionality," which means that the states space will grow exponentially in the number of features and low convergence speed. The method can reduce state spaces greatly and choose actions with favorable purpose and efficiency so as to optimize reward function and enhance convergence speed. Apply it to the online learning in Tetris game, and the experiment result shows that the convergence speed of this algorithm can be enhanced evidently based on the new method which combines hierarchical reinforcement learning algorithm and action subrewards. The "curse of dimensionality" problem is also solved to a certain extent with hierarchical method. All the performance with different parameters is compared and analyzed as well.
-
Research on demand-oriented Business English learning method
Directory of Open Access Journals (Sweden)
Zhou Yuan
2016-01-01
Full Text Available Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher vocational students to learn Business English Visual-audio-oral Course, master Business English knowledge, and improve communicative competence of Business English.
-
Arts-Based Methods in Education
DEFF Research Database (Denmark)
Chemi, Tatiana; Du, Xiangyun
2017-01-01
This chapter introduces the field of arts-based methods in education with a general theoretical perspective, reviewing the journey of learning in connection to the arts, and the contribution of the arts to societies from an educational perspective. Also presented is the rationale and structure...
-
Henderson, Saras
2002-12-01
Since nurse education moved to universities, a reoccurring concern of health consumers, health administrators, and some practising nurses is that nurses are not able to transfer the theoretical knowledge of holistic care into practice. Much has been written about this concern usually under the heading of the theory-practice gap. A common reason that has been highlighted as the cause of this gap is that the theoretical knowledge that nurses learn in academia is predicated on concepts such as humanism and holistic caring. In contrast, the bureaucratic organisation where nurses provide care tends to be based on management concepts where cost containment and outcome measures are more acceptable. Hence nurses' learned values of holistic caring are pitted against the reality of the practice setting. So what is this practice reality? This paper attempts to provide an insider view of why the theoretical knowledge of holistic care may be difficult to enact in the clinical setting. In-depth taped interviews with nurses and participant observation were conducted in acute care hospitals in Western Australia. The interviews were transcribed verbatim and analysed using the constant comparative method. The findings indicated that utilitarian nursing and role models had impacted on the transference of theoretical knowledge of holistic care into practice. The paper outlines some measures that nurses themselves can undertake to ensure the narrowing of the theory-practice gap in this area.
-
How A Flipped Learning Environment Affects Learning In A Course On Theoretical Computer Science
DEFF Research Database (Denmark)
Gnaur, Dorina; Hüttel, Hans
2014-01-01
This paper reports initial experiences with flipping the classroom in an undergraduate computer science course as part of an overall attempt to enhance the pedagogical support for student learning. Our findings indicate that, just as the flipped classroom implies, a shift of focus in the learning...... context influences the way students engage with the course and their learning strategies....
-
Activating teaching methods, studying responses and learning
Christensen, Hans Peter; Vigild, Martin E.; Thomsen, Erik; Szabo, Peter; Horsewell, Andy
2009-01-01
Students’ study strategies when exposed to activating teaching methods are measured, analysed and compared to study strategies in more traditional lecture-based teaching. The resulting learning outcome is discussed. Peer Reviewed
-
Using Graph and Vertex Entropy to Compare Empirical Graphs with Theoretical Graph Models
Directory of Open Access Journals (Sweden)
Tomasz Kajdanowicz
2016-09-01
Full Text Available Over the years, several theoretical graph generation models have been proposed. Among the most prominent are: the Erdős–Renyi random graph model, Watts–Strogatz small world model, Albert–Barabási preferential attachment model, Price citation model, and many more. Often, researchers working with real-world data are interested in understanding the generative phenomena underlying their empirical graphs. They want to know which of the theoretical graph generation models would most probably generate a particular empirical graph. In other words, they expect some similarity assessment between the empirical graph and graphs artificially created from theoretical graph generation models. Usually, in order to assess the similarity of two graphs, centrality measure distributions are compared. For a theoretical graph model this means comparing the empirical graph to a single realization of a theoretical graph model, where the realization is generated from the given model using an arbitrary set of parameters. The similarity between centrality measure distributions can be measured using standard statistical tests, e.g., the Kolmogorov–Smirnov test of distances between cumulative distributions. However, this approach is both error-prone and leads to incorrect conclusions, as we show in our experiments. Therefore, we propose a new method for graph comparison and type classification by comparing the entropies of centrality measure distributions (degree centrality, betweenness centrality, closeness centrality. We demonstrate that our approach can help assign the empirical graph to the most similar theoretical model using a simple unsupervised learning method.
-
Márquez U, Carolina; Fasce H, Eduardo; Pérez V, Cristhian; Ortega B, Javiera; Parra P, Paula; Ortiz M, Liliana; Matus B, Olga; Ibáñez G, Pilar
2014-11-01
Self-directed learning (SDL) skills are particularly important in medical education, considering that physicians should be able to regulate their own learning experiences. To evaluate the relationship between learning styles and strategies and self-directed learning in medical students. One hundred ninety nine first year medical students (120 males) participated in the study. Preparation for Independent Learning (EPAI) scale was used to assess self-direction. Schmeck learning strategies scale and Honey and Alonso (CHAEA) scales were used to evaluate learning styles and strategies. Theoretical learning style and deep processing learning strategy had positive correlations with self-direct learning. Medical students with theoretical styles and low retention of facts are those with greater ability to self-direct their learning. Further studies are required to determine the relationship between learning styles and strategies with SDL in medical students. The acquired knowledge will allow the adjustment of teaching strategies to encourage SDL.
-
Embedding reflection and learning into agile software development
DEFF Research Database (Denmark)
Babb, Jeffry; Hoda, Rashina; Nørbjerg, Jacob
2014-01-01
The theoretical underpinnings of agile methods emphasize regular reflection as a means to sustainable development pace and continuous learning, but in practice, high iteration pressure can diminish reflection opportunities. The Reflective Agile Learning Model (REALM) combines insights and results...... from studies of agile development practices in India, New Zealand, and the US with Schön’s theory of reflective practice to embed reflection in everyday agile practices....
-
Saha, S.; Basak, S.; Safonova, M.; Bora, K.; Agrawal, S.; Sarkar, P.; Murthy, J.
2018-04-01
Seven Earth-sized planets, known as the TRAPPIST-1 system, was discovered with great fanfare in the last week of February 2017. Three of these planets are in the habitable zone of their star, making them potentially habitable planets (PHPs) a mere 40 light years away. The discovery of the closest potentially habitable planet to us just a year before - Proxima b and a realization that Earth-type planets in circumstellar habitable zones are a common occurrence provides the impetus to the existing pursuit for life outside the Solar System. The search for life has two goals essentially: looking for planets with Earth-like conditions (Earth similarity) and looking for the possibility of life in some form (habitability). An index was recently developed, the Cobb-Douglas Habitability Score (CDHS), based on Cobb-Douglas habitability production function (CD-HPF), which computes the habitability score by using measured and estimated planetary parameters. As an initial set, radius, density, escape velocity and surface temperature of a planet were used. The proposed metric, with exponents accounting for metric elasticity, is endowed with analytical properties that ensure global optima and can be scaled to accommodate a finite number of input parameters. We show here that the model is elastic, and the conditions on elasticity to ensure global maxima can scale as the number of predictor parameters increase. K-NN (K-Nearest Neighbor) classification algorithm, embellished with probabilistic herding and thresholding restriction, utilizes CDHS scores and labels exoplanets into appropriate classes via feature-learning methods yielding granular clusters of habitability. The algorithm works on top of a decision-theoretical model using the power of convex optimization and machine learning. The goal is to characterize the recently discovered exoplanets into an "Earth League" and several other classes based on their CDHS values. A second approach, based on a novel feature-learning and
-
Tan, Meng; Hew, Khe Foon
2016-01-01
In this study, we investigated how the use of meaningful gamification affects student learning, engagement, and affective outcomes in a short, 3-day blended learning research methods class using a combination of experimental and qualitative research methods. Twenty-two postgraduates were randomly split into two groups taught by the same…
-
A theoretical design for learning model addressing the networked society
DEFF Research Database (Denmark)
Levinsen, Karin; Nielsen, Janni; Sørensen, Birgitte Holm
2010-01-01
The transition from the industrial to the networked society produces contradictions that challenges the educational system and force it to adapt to new conditions. In a Danish virtual Master in Information and Communication Technologies and Learning (MIL) these contradictions appear as a field of...... which enables students to develop Networked Society competencies and maintain progression in the learning process also during the online periods. Additionally we suggest that our model contributes to the innovation of a networked society's design for learning....... is continuously decreasing. We teach for deep learning but are confronted by students' cost-benefit strategies when they navigate through the study programme under time pressure. To meet these challenges a Design for Learning Model has been developed. The aim is to provide a scaffold that ensures students......' acquisition of the subject matter within a time limit and at a learning quality that support their deep learning process during a subsequent period of on-line study work. In the process of moving from theory to application the model passes through three stages: 1) Conceptual modelling; 2) Orchestration, and 3...
-
Simultaneous anatomical sketching as learning by doing method of teaching human anatomy.
Noorafshan, Ali; Hoseini, Leila; Amini, Mitra; Dehghani, Mohammad-Reza; Kojuri, Javad; Bazrafkan, Leila
2014-01-01
Learning by lecture is a passive experience. Many innovative techniques have been presented to stimulate students to assume a more active attitude toward learning. In this study, simultaneous sketch drawing, as an interactive learning technique was applied to teach anatomy to the medical students. We reconstructed a fun interactive model of teaching anatomy as simultaneous anatomic sketching. To test the model's instruction effectiveness, we conducted a quasi- experimental study and then the students were asked to write their learning experiences in their portfolio, also their view was evaluated by a questionnaire. The results of portfolio evaluation revealed that students believed that this method leads to deep learning and understanding anatomical subjects better. Evaluation of the students' views on this teaching approach was showed that, more than 80% of the students were agreed or completely agreed with this statement that leaning anatomy concepts are easier and the class is less boring with this method. More than 60% of the students were agreed or completely agreed to sketch anatomical figures with professor simultaneously. They also found the sketching make anatomy more attractive and it reduced the time for learning anatomy. These number of students were agree or completely agree that the method help them learning anatomical concept in anatomy laboratory. More than 80% of the students found the simultaneous sketching is a good method for learning anatomy overall. Sketch drawing, as an interactive learning technique, is an attractive for students to learn anatomy.
-
Poell, R.F.; Moorsel, M.A.A.H. van
1996-01-01
This paper discusses the relevance of Van der Krogt's learning network theory (1995) for our understanding of the concepts of work-related learning projects and learning climate in organisations. The main assumptions of the learning network theory are presented and transferred to the level of learning groups in organisations. Four theoretical types of learning projects are distinguished. Four different approaches to the learning climate of work groups are compared to the approach offered by t...
-
Child Language Acquisition: Contrasting Theoretical Approaches
Ambridge, Ben; Lieven, Elena V. M.
2011-01-01
Is children's language acquisition based on innate linguistic structures or built from cognitive and communicative skills? This book summarises the major theoretical debates in all of the core domains of child language acquisition research (phonology, word-learning, inflectional morphology, syntax and binding) and includes a complete introduction…
-
Basic theoretical physics a concise overview
Krey, Uwe
2007-01-01
This concise treatment embraces, in four parts, all the main aspects of theoretical physics (I . Mechanics and Basic Relativity, II. Electrodynamics and Aspects of Optics, III. Non-relativistic Quantum Mechanics, IV. Thermodynamics and Statistical Physics). It summarizes the material that every graduate student, physicist working in industry, or physics teacher should master during his or her degree course. It thus serves both as an excellent revision and preparation tool, and as a convenient reference source, covering the whole of theoretical physics. It may also be successfully employed to deepen its readers' insight and add new dimensions to their understanding of these fundamental concepts. Recent topics such as holography and quantum cryptography are included, thus making this a unique contribution to the learning material for theoretical physics.
-
Kilbrink, Nina; Bjurulf, Veronica; Blomberg, Ingela; Heidkamp, Anja; Hollsten, Ann-Christin
2014-01-01
This article describes the process of a learning study conducted in technology education in a Swedish preschool class. The learning study method used in this study is a collaborative method, where researchers and teachers work together as a team concerning teaching and learning about a specific learning object. The object of learning in this study concerns strong constructions and framed structures. This article describes how this learning study was conducted and discusses reflections made du...
-
Directory of Open Access Journals (Sweden)
Іван Нищак
2015-12-01
Full Text Available The article contains Theoretical Foundations of designing of author’s electronic educational-methodical complex (EEMC «Graphics», intended to implement the engineering-graphic preparation of future teachers of technology in terms of computer-based learning. The process of designing of electronic educational-methodical complex “Graphics” includes the following successive stages: 1 identification of didactic goals and objectives; 2the designing of patterns of EEMC; 3 the selection of contents and systematization of educational material; 4 the program-technical implementation of EEMC; 5 interface design; 6 expert assessment of quality of EEMC; 7 testing of EEMC; 8 adjusting the software; 9 the development of guidelines and instructions for the use of EEMC.
-
Active semi-supervised learning method with hybrid deep belief networks.
Zhou, Shusen; Chen, Qingcai; Wang, Xiaolong
2014-01-01
In this paper, we develop a novel semi-supervised learning algorithm called active hybrid deep belief networks (AHD), to address the semi-supervised sentiment classification problem with deep learning. First, we construct the previous several hidden layers using restricted Boltzmann machines (RBM), which can reduce the dimension and abstract the information of the reviews quickly. Second, we construct the following hidden layers using convolutional restricted Boltzmann machines (CRBM), which can abstract the information of reviews effectively. Third, the constructed deep architecture is fine-tuned by gradient-descent based supervised learning with an exponential loss function. Finally, active learning method is combined based on the proposed deep architecture. We did several experiments on five sentiment classification datasets, and show that AHD is competitive with previous semi-supervised learning algorithm. Experiments are also conducted to verify the effectiveness of our proposed method with different number of labeled reviews and unlabeled reviews respectively.
-
Method to predict process signals to learn for SVM
International Nuclear Information System (INIS)
Minowa, Hirotsugu; Gofuku, Akio
2013-01-01
Study of diagnostic system using machine learning to reduce the incidents of the plant is in advance because an accident causes large damage about human, economic and social loss. There is a problem that 2 performances between a classification performance and generalization performance on the machine diagnostic machine is exclusive. However, multi agent diagnostic system makes it possible to use a diagnostic machine specialized either performance by multi diagnostic machines can be used. We propose method to select optimized variables to improve classification performance. The method can also be used for other supervised learning machine but Support Vector Machine. This paper reports that our method and result of evaluation experiment applied our method to output 40% of Monju. (author)
-
DEFF Research Database (Denmark)
Haller, Michel; Cruickshank, Chynthia; Streicher, Wolfgang
2009-01-01
This paper reviews different methods that have been proposed to characterize thermal stratification in energy storages from a theoretical point of view. Specifically, this paper focuses on the methods that can be used to determine the ability of a storage to promote and maintain stratification...... during charging, storing and discharging, and represent this ability with a single numerical value in terms of a stratification efficiency for a given experiment or under given boundary conditions. Existing methods for calculating stratification efficiencies have been applied to hypothetical storage...
-
International Nuclear Information System (INIS)
Reed, D.L.; Symons, C.R.
1965-01-01
A method of calculation is given which assists the analyses of chopper measurements of spectra from ZENITH and enables complex multigroup theoretical calculations of the spectra to be put into a form which may be compared with experiment. In addition the theory of the cut-off function has been extended to give analytical expressions which take into account the effects of sub-collimators, off centre slits and of a rotor made of a material partially transparent to neutrons. The theoretical cut-off function suggested shows good agreement with experiment. (author)
-
Energy Technology Data Exchange (ETDEWEB)
Reed, D L; Symons, C R [General Reactor Physics Division, Atomic Energy Establishment, Winfrith, Dorchester, Dorset (United Kingdom)
1965-01-15
A method of calculation is given which assists the analyses of chopper measurements of spectra from ZENITH and enables complex multigroup theoretical calculations of the spectra to be put into a form which may be compared with experiment. In addition the theory of the cut-off function has been extended to give analytical expressions which take into account the effects of sub-collimators, off centre slits and of a rotor made of a material partially transparent to neutrons. The theoretical cut-off function suggested shows good agreement with experiment. (author)
-
Students' Ideas on Cooperative Learning Method
Yoruk, Abdulkadir
2016-01-01
Aim of this study is to investigate students' ideas on cooperative learning method. For that purpose students who are studying at elementary science education program are distributed into two groups through an experimental design. Factors threaten the internal validity are either eliminated or reduced to minimum value. Data analysis is done…
-
Challenges of E-learning in medicine: methods and results of a systematical exploration
Directory of Open Access Journals (Sweden)
Spreckelsen, Cord
2006-11-01
Full Text Available E-learning in medicine traditionally concentrates on case oriented or problem oriented learning scenarios, the development of multimedia courseware or the implementation of simulators. This paper aims at a systematic exploration of actual and new challenges for E-learning in the medical domain. The exploration is based on the analysis of the scientific discourse in the field of Medical Education. The analysis starts from text based sources: the concept hierarchy of the Medical Subject Headings, the profiles of the relevant scientific associations, and the scientific program of scientific conferences or annual meetings. These sources are subjected to conceptual analysis, supported by network visualization tools and supplemented by network theoretic indices (Betweeness Centrality. As a result, the main concerns of the Medical Education community and their modifications during the last six years can be identified. The analysis discovers new challenges, which result from central issues of Medical Education, namely from e.g. curricular and faculty development or the sustainable integration of postgraduate education and continuing medial education. The main challenges are: 1 the implementation of integrative conceptions of the application of learning management systems (LMS and 2 the necessity of combining aspects of organizational development, knowledge management and learning management within the scope of a comprehensive learning life cycle management.
-
E-learning as new method of medical education.
Masic, Izet
2008-01-01
NONE DECLARED Distance learning refers to use of technologies based on health care delivered on distance and covers areas such as electronic health, tele-health (e-health), telematics, telemedicine, tele-education, etc. For the need of e-health, telemedicine, tele-education and distance learning there are various technologies and communication systems from standard telephone lines to the system of transmission digitalized signals with modem, optical fiber, satellite links, wireless technologies, etc. Tele-education represents health education on distance, using Information Communication Technologies (ICT), as well as continuous education of a health system beneficiaries and use of electronic libraries, data bases or electronic data with data bases of knowledge. Distance learning (E-learning) as a part of tele-education has gained popularity in the past decade; however, its use is highly variable among medical schools and appears to be more common in basic medical science courses than in clinical education. Distance learning does not preclude traditional learning processes; frequently it is used in conjunction with in-person classroom or professional training procedures and practices. Tele-education has mostly been used in biomedical education as a blended learning method, which combines tele-education technology with traditional instructor-led training, where, for example, a lecture or demonstration is supplemented by an online tutorial. Distance learning is used for self-education, tests, services and for examinations in medicine i.e. in terms of self-education and individual examination services. The possibility of working in the exercise mode with image files and questions is an attractive way of self education. Automated tracking and reporting of learners' activities lessen faculty administrative burden. Moreover, e-learning can be designed to include outcomes assessment to determine whether learning has occurred. This review article evaluates the current
-
Lessons learned applying CASE methods/tools to Ada software development projects
Blumberg, Maurice H.; Randall, Richard L.
1993-01-01
This paper describes the lessons learned from introducing CASE methods/tools into organizations and applying them to actual Ada software development projects. This paper will be useful to any organization planning to introduce a software engineering environment (SEE) or evolving an existing one. It contains management level lessons learned, as well as lessons learned in using specific SEE tools/methods. The experiences presented are from Alpha Test projects established under the STARS (Software Technology for Adaptable and Reliable Systems) project. They reflect the front end efforts by those projects to understand the tools/methods, initial experiences in their introduction and use, and later experiences in the use of specific tools/methods and the introduction of new ones.
-
Constructivist learning theories and complex learning environments
R-J. Simons; Dr. S. Bolhuis
2004-01-01
Learning theories broadly characterised as constructivist, agree on the importance to learning of the environment, but differ on what exactly it is that constitutes this importance. Accordingly, they also differ on the educational consequences to be drawn from the theoretical perspective. Cognitive
-
Hense, Jan; Mandl, Heinz
2012-01-01
This conceptual paper aims to clarify the theoretical underpinnings of game based learning (GBL) and learning with digital learning games (DLGs). To do so, it analyses learning of game related skills and contents, which occurs constantly during playing conventional entertainment games, from three perspectives: learning theory, emotion theory, and…
-
A Doctoral Seminar in Qualitative Research Methods: Lessons Learned
Directory of Open Access Journals (Sweden)
Suzanne Franco
2016-09-01
Full Text Available New qualitative research methods continue to emerge in response to factors such as renewed interest in mixed methods, better understanding of the importance of a researcher’s philosophical stance, as well as the increased use of technology in data collection and analysis, to name a few. As a result, those facilitating research methods courses must revisit content and instructional strategies in order to prepare well-informed researchers. Approaches range from paradigm to pragmatic emphasis. This descriptive case study of a doctoral seminar for novice qualitative researchers describes the intricacies of the syllabus of a pragmatic approach in a constructivist/social constructionist learning environment. The purpose was to document the delivery and faculty/student interactions and reactions. Noteworthy were the contradictions and frustrations in the delivery as well as in student experiences. In the end, student input led to seminal learning experiences. The confirmation of the effectiveness of a constructivist/social constructivist learning environment is applicable to higher education pedagogy in general.
-
A diagram retrieval method with multi-label learning
Fu, Songping; Lu, Xiaoqing; Liu, Lu; Qu, Jingwei; Tang, Zhi
2015-01-01
In recent years, the retrieval of plane geometry figures (PGFs) has attracted increasing attention in the fields of mathematics education and computer science. However, the high cost of matching complex PGF features leads to the low efficiency of most retrieval systems. This paper proposes an indirect classification method based on multi-label learning, which improves retrieval efficiency by reducing the scope of compare operation from the whole database to small candidate groups. Label correlations among PGFs are taken into account for the multi-label classification task. The primitive feature selection for multi-label learning and the feature description of visual geometric elements are conducted individually to match similar PGFs. The experiment results show the competitive performance of the proposed method compared with existing PGF retrieval methods in terms of both time consumption and retrieval quality.
-
Theoretical Foundations for Website Design Courses.
Walker, Kristin
2002-01-01
Considers how theoretical foundations in website design courses can facilitate students learning the genres of Internet communication. Proposes ways that theories can be integrated into website design courses. Focuses on two students' website portfolios and ways they utilize genre theory and activity theory discussed in class to produce websites…
-
Zeng, Irene Sui Lan; Lumley, Thomas
2018-01-01
Integrated omics is becoming a new channel for investigating the complex molecular system in modern biological science and sets a foundation for systematic learning for precision medicine. The statistical/machine learning methods that have emerged in the past decade for integrated omics are not only innovative but also multidisciplinary with integrated knowledge in biology, medicine, statistics, machine learning, and artificial intelligence. Here, we review the nontrivial classes of learning methods from the statistical aspects and streamline these learning methods within the statistical learning framework. The intriguing findings from the review are that the methods used are generalizable to other disciplines with complex systematic structure, and the integrated omics is part of an integrated information science which has collated and integrated different types of information for inferences and decision making. We review the statistical learning methods of exploratory and supervised learning from 42 publications. We also discuss the strengths and limitations of the extended principal component analysis, cluster analysis, network analysis, and regression methods. Statistical techniques such as penalization for sparsity induction when there are fewer observations than the number of features and using Bayesian approach when there are prior knowledge to be integrated are also included in the commentary. For the completeness of the review, a table of currently available software and packages from 23 publications for omics are summarized in the appendix.
-
Andrusyszyn, M A; Cragg, C E; Humbert, J
2001-04-01
The relationships among multiple distance delivery methods, preferred learning style, content, and achievement was sought for primary care nurse practitioner students. A researcher-designed questionnaire was completed by 86 (71%) participants, while 6 engaged in follow-up interviews. The results of the study included: participants preferred learning by "considering the big picture"; "setting own learning plans"; and "focusing on concrete examples." Several positive associations were found: learning on own with learning by reading, and setting own learning plans; small group with learning through discussion; large group with learning new things through hearing and with having learning plans set by others. The most preferred method was print-based material and the least preferred method was audio tape. The most suited method for content included video teleconferencing for counseling, political action, and transcultural issues; and video tape for physical assessment. Convenience, self-direction, and timing of learning were more important than delivery method or learning style. Preferred order of learning was reading, discussing, observing, doing, and reflecting. Recommended considerations when designing distance courses include a mix of delivery methods, specific content, outcomes, learner characteristics, and state of technology.
-
Measuring strategic control in implicit learning: how and why?
Norman, Elisabeth
2015-01-01
Several methods have been developed for measuring the extent to which implicitly learned knowledge can be applied in a strategic, flexible manner. Examples include generation exclusion tasks in Serial Reaction Time (SRT) learning (Goschke, 1998; Destrebecqz and Cleeremans, 2001) and 2-grammar classification tasks in Artificial Grammar Learning (AGL; Dienes et al., 1995; Norman et al., 2011). Strategic control has traditionally been used as a criterion for determining whether acquired knowledge is conscious or unconscious, or which properties of knowledge are consciously available. In this paper I first summarize existing methods that have been developed for measuring strategic control in the SRT and AGL tasks. I then address some methodological and theoretical questions. Methodological questions concern choice of task, whether the measurement reflects inhibitory control or task switching, and whether or not strategic control should be measured on a trial-by-trial basis. Theoretical questions concern the rationale for including measurement of strategic control, what form of knowledge is strategically controlled, and how strategic control can be combined with subjective awareness measures.
-
Exploring Non-Traditional Learning Methods in Virtual and Real-World Environments
Lukman, Rebeka; Krajnc, Majda
2012-01-01
This paper identifies the commonalities and differences within non-traditional learning methods regarding virtual and real-world environments. The non-traditional learning methods in real-world have been introduced within the following courses: Process Balances, Process Calculation, and Process Synthesis, and within the virtual environment through…
-
The Convergent Learning Space:
DEFF Research Database (Denmark)
Kjærgaard, Hanne Wacher; Kjeldsen, Lars Peter; Asmussen, Jørgen Bering
is described as well as the theoretical construct and hypotheses surrounding the emergence of the concept in technology-rich classrooms, where students bring their own devices and involve their personal learning spaces and networks. The need for new ways of approaching concepts like choice, learning resources......This paper describes the concept of “The Convergent Learning Space” as it is being explored in an ongoing action research project carried out at undergraduate level in select bachelor programs at a Danish University College. The background nature, design, and beginning of this work in progress......, trajectories of participation etc. calls for new action and new pedagogies by teachers in order to secure alignment between students’ worlds and expectations and aims and plans of the teacher. Action research methods are being used to define and test the constituents and variables of the convergent learning...
-
Appraising the Qualities of Social Work Students' Theoretical Knowledge: A Qualitative Exploration
van Bommel, Marijke; Boshuizen, Henny P. A.; Kwakman, Kitty
2012-01-01
Higher professional education aims to prepare students for entering practice with an adequate theoretical body of knowledge. In constructivist programmes, authentic learning contexts and self-directed learning are assumed to support knowledge learning and the transition from education to practice. Through an in-depth exploration, this case study…
-
DEFF Research Database (Denmark)
Dirckinck-Holmfeld, Lone; Svendsen, Brian Møller; Ponti, Marisa
The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments.......The report documents and summarises the elements and dimensions that have been identified to describe and analyse the case studies collected in the Kaleidoscope Jointly Executed Integrating Research Project (JEIRP) on Conditions for productive learning in network learning environments....
-
Directory of Open Access Journals (Sweden)
Eimear Fallon
2013-05-01
Full Text Available This paper discusses a research project carried out with 82 final and third year undergraduate students, learning Research Methods prior to undertaking an undergraduate thesis during the academic years 2010 and 2011. The research had two separate, linked objectives, (a to develop a Research Methods module that embraces an activity-based approach to learning in a group environment, (b to improve engagement by all students. The Research Methods module was previously taught through a traditional lecture-based format. Anecdotally, it was felt that student engagement was poor and learning was limited. It was believed that successful completion of the development of this Module would equip students with a deeply-learned battery of research skills to take into their further academic and professional careers. Student learning was achieved through completion of a series of activities based on different research methods. In order to encourage student engagement, a wide variety of activities were used. These activities included workshops, brainstorming, mind-mapping, presentations, written submissions, peer critiquing, lecture/seminar, and ‘speed dating’ with more senior students and self reflection. Student engagement was measured through a survey based on a U.S. National Survey of Student Engagement (2000. A questionnaire was devised to establish whether, and to what degree, students were engaged in the material that they were learning, while they were learning it. The results of the questionnaire were very encouraging with between 63% and 96% of students answering positively to a range of questions concerning engagement. In terms of the two objectives set, these were satisfactorily met. The module was successfully developed and continues to be delivered, based upon this new and significant level of student engagement.
-
31st International Colloquium in Group Theoretical Methods in Physics
Gazeau, Jean-Pierre; Faci, Sofiane; Micklitz, Tobias; Scherer, Ricardo; Toppan, Francesco
2017-01-01
This proceedings records the 31st International Colloquium on Group Theoretical Methods in Physics (“Group 31”). Plenary-invited articles propose new approaches to the moduli spaces in gauge theories (V. Pestun, 2016 Weyl Prize Awardee), the phenomenology of neutrinos in non-commutative space-time, the use of Hardy spaces in quantum physics, contradictions in the use of statistical methods on complex systems, and alternative models of supersymmetry. This volume’s survey articles broaden the colloquia’s scope out into Majorana neutrino behavior, the dynamics of radiating charges, statistical pattern recognition of amino acids, and a variety of applications of gauge theory, among others. This year’s proceedings further honors Bertram Kostant (2016 Wigner Medalist), as well as S.T. Ali and L. Boyle, for their life-long contributions to the math and physics communities. The aim of the ICGTMP is to provide a forum for physicists, mathematicians, and scientists of related disciplines who develop or apply ...
-
Theoretical Perspectives Underlying the Application of Cooperative Learning in Classrooms
Tran, Van Dat
2013-01-01
Cooperative learning has been the centre of worldwide attention because it has been shown to have strong effects on student learning, as well as other positive outcomes. Although the academic, social, affective and psychological outcomes of students taught by cooperative learning are more positive compared with students taught by the traditional…
-
Research on demand-oriented Business English learning method
Zhou Yuan
2016-01-01
Business English is integrated with visual-audio-oral English, which focuses on the application for English listening and speaking skills in common business occasions, and acquire business knowledge and improve skills through English. This paper analyzes the Business English Visual-audio-oral Course, and learning situation of higher vocational students’ learning objectives, interests, vocabulary, listening and speaking, and focuses on the research of effective methods to guide the higher voca...
-
IMPROVEMENT OF RECOGNITION QUALITY IN DEEP LEARNING NETWORKS BY SIMULATED ANNEALING METHOD
Directory of Open Access Journals (Sweden)
A. S. Potapov
2014-09-01
Full Text Available The subject of this research is deep learning methods, in which automatic construction of feature transforms is taken place in tasks of pattern recognition. Multilayer autoencoders have been taken as the considered type of deep learning networks. Autoencoders perform nonlinear feature transform with logistic regression as an upper classification layer. In order to verify the hypothesis of possibility to improve recognition rate by global optimization of parameters for deep learning networks, which are traditionally trained layer-by-layer by gradient descent, a new method has been designed and implemented. The method applies simulated annealing for tuning connection weights of autoencoders while regression layer is simultaneously trained by stochastic gradient descent. Experiments held by means of standard MNIST handwritten digit database have shown the decrease of recognition error rate from 1.1 to 1.5 times in case of the modified method comparing to the traditional method, which is based on local optimization. Thus, overfitting effect doesn’t appear and the possibility to improve learning rate is confirmed in deep learning networks by global optimization methods (in terms of increasing recognition probability. Research results can be applied for improving the probability of pattern recognition in the fields, which require automatic construction of nonlinear feature transforms, in particular, in the image recognition. Keywords: pattern recognition, deep learning, autoencoder, logistic regression, simulated annealing.
-
Directory of Open Access Journals (Sweden)
Mei Lick Cheok
2015-01-01
Full Text Available This paper develops a theoretical model of the determinants of e-learning satisfaction in teaching and learning among secondary school teachers. It is based on reviews of past studies on satisfaction in using information technology systems. Three potential groups of determinants of satisfaction among secondary school teachers were identified; user-related characteristics, organisational-related characteristics and the e-learning-system characteristics. Usage is established as a mediating variable between the three potential groups of determinants and satisfaction towards e-learning. Future research could provide a more definitive theoretical statement of e-learning satisfaction and develop an additional proposition which could be derived from a more refined theory. The research yields a theoretical framework that outlines the predictive potential of the three groups of key factors in explaining e-learning satisfaction among secondary school teachers. The factors can be considered when developing future continuous professional development courses and intervention programmes when proposing a new innovation in the curriculum.
-
Theoretical and Methodological Perspectives on Designing Video Studies of Interaction
Directory of Open Access Journals (Sweden)
Anna-Lena Rostvall
2005-12-01
Full Text Available In this article the authors discuss the theoretical basis for the methodological decisions made during the course of a Swedish research project on interaction and learning. The purpose is to discuss how different theories are applied at separate levels of the study. The study is structured on three levels, with separate sets of research questions and theoretical concepts. The levels reflect a close-up description, a systematic analysis, and an interpretation of how teachers and students act and interact. The data consist of 12 hours of video-recorded and transcribed music lessons from high school and college. Through a multidisciplinary theoretical framework, the general understanding of teaching and learning in terms of interaction can be widened. The authors also present a software tool developed to facilitate the processes of transcription and analysis of the video data.
-
Studying learning in the healthcare setting: the potential of quantitative diary methods.
Ciere, Yvette; Jaarsma, Debbie; Visser, Annemieke; Sanderman, Robbert; Snippe, Evelien; Fleer, Joke
2015-08-01
Quantitative diary methods are longitudinal approaches that involve the repeated measurement of aspects of peoples' experience of daily life. In this article, we outline the main characteristics and applications of quantitative diary methods and discuss how their use may further research in the field of medical education. Quantitative diary methods offer several methodological advantages, such as measuring aspects of learning with great detail, accuracy and authenticity. Moreover, they enable researchers to study how and under which conditions learning in the health care setting occurs and in which way learning can be promoted. Hence, quantitative diary methods may contribute to theory development and the optimization of teaching methods in medical education.
-
Tomasello, Michael
2016-01-01
M. Tomasello, A. Kruger, and H. Ratner (1993) proposed a theory of cultural learning comprising imitative learning, instructed learning, and collaborative learning. Empirical and theoretical advances in the past 20 years suggest modifications to the theory; for example, children do not just imitate but overimitate in order to identify and…
-
Koponen, Jonna; Pyörälä, Eeva; Isotalus, Pekka
2012-01-01
Despite numerous studies exploring medical students' attitudes to communication skills learning (CSL), there are apparently no studies comparing different experiential learning methods and their influence on students' attitudes. We compared medical students' attitudes to learning communication skills before and after a communication course in the data as a whole, by gender and when divided into three groups using different methods. Second-year medical students (n = 129) were randomly assigned to three groups. In group A (n = 42) the theatre in education method, in group B (n = 44) simulated patients and in group C (n = 43) role-play were used. The data were gathered before and after the course using Communication Skills Attitude Scale. Students' positive attitudes to learning communication skills (PAS; positive attitude scale) increased significantly and their negative attitudes (NAS; negative attitude scale) decreased significantly between the beginning and end of the course. Female students had more positive attitudes than the male students. There were no significant differences in the three groups in the mean scores for PAS or NAS measured before or after the course. The use of experiential methods and integrating communication skills training with visits to health centres may help medical students to appreciate the importance of CSL.
-
"Debate" Learning Method and Its Implications for the Formal Education System
Najafi, Mohammad; Motaghi, Zohre; Nasrabadi, Hassanali Bakhtiyar; Heshi, Kamal Nosrati
2016-01-01
Regarding the importance of enhancement in learner's social skills, especially in learning process, this study tries to introduce one of the group learning programs entitled "debate" as a teaching method in Iran religious universities. It also considers the concept and the history of this method by qualitative and descriptive-analytical…
-
Adult Learners' Preferred Methods of Learning Preventative Heart Disease Care
Alavi, Nasim
2016-01-01
The purpose of this study was to investigate the preferred method of learning about heart disease by adult learners. This research study also investigated if there was a statistically significant difference between race/ethnicity, age, and gender of adult learners and their preferred method of learning preventative heart disease care. This…
-
Multi-Role Project (MRP): A New Project-Based Learning Method for STEM
Warin, Bruno; Talbi, Omar; Kolski, Christophe; Hoogstoel, Frédéric
2016-01-01
This paper presents the "Multi-Role Project" method (MRP), a broadly applicable project-based learning method, and describes its implementation and evaluation in the context of a Science, Technology, Engineering, and Mathematics (STEM) course. The MRP method is designed around a meta-principle that considers the project learning activity…
-
Directory of Open Access Journals (Sweden)
Sucheston Lara
2010-09-01
Full Text Available Abstract Background Multifactorial diseases such as cancer and cardiovascular diseases are caused by the complex interplay between genes and environment. The detection of these interactions remains challenging due to computational limitations. Information theoretic approaches use computationally efficient directed search strategies and thus provide a feasible solution to this problem. However, the power of information theoretic methods for interaction analysis has not been systematically evaluated. In this work, we compare power and Type I error of an information-theoretic approach to existing interaction analysis methods. Methods The k-way interaction information (KWII metric for identifying variable combinations involved in gene-gene interactions (GGI was assessed using several simulated data sets under models of genetic heterogeneity driven by susceptibility increasing loci with varying allele frequency, penetrance values and heritability. The power and proportion of false positives of the KWII was compared to multifactor dimensionality reduction (MDR, restricted partitioning method (RPM and logistic regression. Results The power of the KWII was considerably greater than MDR on all six simulation models examined. For a given disease prevalence at high values of heritability, the power of both RPM and KWII was greater than 95%. For models with low heritability and/or genetic heterogeneity, the power of the KWII was consistently greater than RPM; the improvements in power for the KWII over RPM ranged from 4.7% to 14.2% at for α = 0.001 in the three models at the lowest heritability values examined. KWII performed similar to logistic regression. Conclusions Information theoretic models are flexible and have excellent power to detect GGI under a variety of conditions that characterize complex diseases.
-
A parallel ILP algorithm that incorporates incremental batch learning
Nuno Fonseca; Rui Camacho; Fernado Silva
2003-01-01
In this paper we tackle the problems of eciency and scala-bility faced by Inductive Logic Programming (ILP) systems. We proposethe use of parallelism to improve eciency and the use of an incrementalbatch learning to address the scalability problem. We describe a novelparallel algorithm that incorporates into ILP the method of incremen-tal batch learning. The theoretical complexity of the algorithm indicatesthat a linear speedup can be achieved.
-
Computer-enhanced visual learning method: a paradigm to teach and document surgical skills.
Maizels, Max; Mickelson, Jennie; Yerkes, Elizabeth; Maizels, Evelyn; Stork, Rachel; Young, Christine; Corcoran, Julia; Holl, Jane; Kaplan, William E
2009-09-01
Changes in health care are stimulating residency training programs to develop new methods for teaching surgical skills. We developed Computer-Enhanced Visual Learning (CEVL) as an innovative Internet-based learning and assessment tool. The CEVL method uses the educational procedures of deliberate practice and performance to teach and learn surgery in a stylized manner. CEVL is a learning and assessment tool that can provide students and educators with quantitative feedback on learning a specific surgical procedure. Methods involved examine quantitative data of improvement in surgical skills. Herein, we qualitatively describe the method and show how program directors (PDs) may implement this technique in their residencies. CEVL allows an operation to be broken down into teachable components. The process relies on feedback and remediation to improve performance, with a focus on learning that is applicable to the next case being performed. CEVL has been shown to be effective for teaching pediatric orchiopexy and is being adapted to additional adult and pediatric procedures and to office examination skills. The CEVL method is available to other residency training programs.
-
Directory of Open Access Journals (Sweden)
Leyfa A.V.
2009-12-01
Full Text Available The value of theoretical knowledge, methodical, practical studies, skills in forming physical activity of students is rotined. The level of mastering of components of physical activity is closely associate with the basic blocks of professional preparation of students and their future professional activity. Theoretical knowledge on discipline the «Physical culture» assist the certain affecting depth and breadth of mastering of knowledge of professional preparation.
-
Theoretical physics 8 statistical physics
Nolting, Wolfgang
2018-01-01
This textbook offers a clear and comprehensive introduction to statistical physics, one of the core components of advanced undergraduate physics courses. It follows on naturally from the previous volumes in this series, using methods of probability theory and statistics to solve physical problems. The first part of the book gives a detailed overview on classical statistical physics and introduces all mathematical tools needed. The second part of the book covers topics related to quantized states, gives a thorough introduction to quantum statistics, followed by a concise treatment of quantum gases. Ideally suited to undergraduate students with some grounding in quantum mechanics, the book is enhanced throughout with learning features such as boxed inserts and chapter summaries, with key mathematical derivations highlighted to aid understanding. The text is supported by numerous worked examples and end of chapter problem sets. About the Theoretical Physics series Translated from the renowned and highly successf...
-
Directory of Open Access Journals (Sweden)
Hendrik Pratama
2017-12-01
Full Text Available The purpose of this research was determined the effect of application WhatsApp Messenger in the Group Investigation (GI method on learning achievement. The methods used experimental research with control group pretest-postest design. The sampling procedure used the purposive sampling technique that consists of 17 students as a control group and 17 students as an experimental group. The sample in this research is students in Electrical Engineering Education Study Program. The experimental group used the GI method that integrated with WhatsApp Messenger. The control group used lecture method without social media integration. The collecting data used observation, documentation, interview, questionnaire, and test. The researcher used a t-test for compared the control group and the experimental group’s learning outcomes at an alpha level of 0,05. The results showed differences between the experiment group and the control group. The study result of the experimental higher than the control groups. This learning was designed with start, grouping, planning, presenting, organizing, investigating, evaluating, ending’s stage. Integration of WhatsApp with group investigation method could cause the positive communication between student and lecturer. Discussion in this learning was well done, the student’s knowledge could appear in a group and the information could spread evenly and quickly.
-
Hybrid Method for Mobile learning Cooperative: Study of Timor Leste
da Costa Tavares, Ofelia Cizela; Suyoto; Pranowo
2018-02-01
In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process) and SAW (simple additive Weighting) method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.
-
Hybrid Method for Mobile learning Cooperative: Study of Timor Leste
Directory of Open Access Journals (Sweden)
da Costa Tavares Ofelia Cizela
2018-01-01
Full Text Available In the modern world today the decision support system is very useful to help in solving a problem, so this study discusses the learning process of savings and loan cooperatives in Timor Leste. The purpose of the observation is that the people of Timor Leste are still in the process of learning the use DSS for good saving and loan cooperative process. Based on existing research on the Timor Leste community on credit cooperatives, a mobile application will be built that will help the cooperative learning process in East Timorese society. The methods used for decision making are AHP (Analytical Hierarchy Process and SAW (simple additive Weighting method to see the result of each criterion and the weight of the value. The result of this research is mobile leaning cooperative in decision support system by using SAW and AHP method. Originality Value: Changed the two methods of mobile application development using AHP and SAW methods to help the decision support system process of a savings and credit cooperative in Timor Leste.
-
Theoretical and simulation studies of seeding methods
Energy Technology Data Exchange (ETDEWEB)
Pellegrini, Claudio [Univ. of California, Los Angeles, CA (United States)
2017-12-11
We report the theoretical and experimental studies done with the support of DOE-Grant DE-SC0009983 to increase an X-ray FEL peak power from the present level of 20 to 40 GW to one or more TW by seeding, undulator tapering and using the new concept of the Double Bunch FEL.
-
Number theoretic methods in cryptography complexity lower bounds
Shparlinski, Igor
1999-01-01
The book introduces new techniques which imply rigorous lower bounds on the complexity of some number theoretic and cryptographic problems. These methods and techniques are based on bounds of character sums and numbers of solutions of some polynomial equations over finite fields and residue rings. It also contains a number of open problems and proposals for further research. We obtain several lower bounds, exponential in terms of logp, on the de grees and orders of • polynomials; • algebraic functions; • Boolean functions; • linear recurring sequences; coinciding with values of the discrete logarithm modulo a prime p at suf ficiently many points (the number of points can be as small as pI/He). These functions are considered over the residue ring modulo p and over the residue ring modulo an arbitrary divisor d of p - 1. The case of d = 2 is of special interest since it corresponds to the representation of the right most bit of the discrete logarithm and defines whether the argument is a quadratic...
-
Students' perceptions of a blended learning experience in dental education.
Varthis, S; Anderson, O R
2018-02-01
"Flipped" instructional sequencing is a new instructional method where online instruction precedes the group meeting, allowing for more sophisticated learning through discussion and critical thinking during the in-person class session; a novel approach studied in this research. The purpose of this study was to document dental students' perceptions of flipped-based blended learning and to apply a new method of displaying their perceptions based on Likert-scale data analysis using a network diagramming method known as an item correlation network diagram (ICND). In addition, this article aimed to encourage institutions or course directors to consider self-regulated learning and social constructivism as a theoretical framework when blended learning is incorporated in dental curricula. Twenty (second year) dental students at a Northeastern Regional Dental School in the United States participated in this study. A Likert scale was administered before and after the learning experience to obtain evidence of their perceptions of its quality and educational merits. Item correlation network diagrams, based on the intercorrelations amongst the responses to the Likert-scale items, were constructed to display students' changes in perceptions before and after the learning experience. Students reported positive perceptions of the blended learning, and the ICND analysis of their responses before and after the learning experience provided insights into their social (group-based) cognition about the learning experience. The ICNDs are considered evidence of social or group-based cognition, because they are constructed from evidence obtained using intercorrelations of the total group responses to the Likert-scale items. The students positively received blended learning in dental education, and the ICND analyses demonstrated marked changes in their social cognition of the learning experience based on the pre- and post-Likert survey data. Self-regulated learning and social constructivism
-
Learning Practice-Based Research Methods: Capturing the Experiences of MSW Students
Natland, Sidsel; Weissinger, Erika; Graaf, Genevieve; Carnochan, Sarah
2016-01-01
The literature on teaching research methods to social work students identifies many challenges, such as dealing with the tensions related to producing research relevant to practice, access to data to teach practice-based research, and limited student interest in learning research methods. This is an exploratory study of the learning experiences of…
-
Machine Learning Method Applied in Readout System of Superheated Droplet Detector
Liu, Yi; Sullivan, Clair Julia; d'Errico, Francesco
2017-07-01
Direct readability is one advantage of superheated droplet detectors in neutron dosimetry. Utilizing such a distinct characteristic, an imaging readout system analyzes image of the detector for neutron dose readout. To improve the accuracy and precision of algorithms in the imaging readout system, machine learning algorithms were developed. Deep learning neural network and support vector machine algorithms are applied and compared with generally used Hough transform and curvature analysis methods. The machine learning methods showed a much higher accuracy and better precision in recognizing circular gas bubbles.
-
Machine Learning Methods for Identifying Composition of Uranium Deposits in Kazakhstan
Directory of Open Access Journals (Sweden)
Kuchin Yan
2017-12-01
Full Text Available The paper explores geophysical methods of wells survey, as well as their role in the development of Kazakhstan’s uranium deposit mining efforts. An analysis of the existing methods for solving the problem of interpreting geophysical data using machine learning in petroleum geophysics is made. The requirements and possible applications of machine learning methods in regard to uranium deposits of Kazakhstan are formulated in the paper.
-
Information-Theoretic Data Discarding for Dynamic Trees on Data Streams
Directory of Open Access Journals (Sweden)
Christoforos Anagnostopoulos
2013-12-01
Full Text Available Ubiquitous automated data collection at an unprecedented scale is making available streaming, real-time information flows in a wide variety of settings, transforming both science and industry. Learning algorithms deployed in such contexts often rely on single-pass inference, where the data history is never revisited. Learning may also need to be temporally adaptive to remain up-to-date against unforeseen changes in the data generating mechanism. Online Bayesian inference remains challenged by such transient, evolving data streams. Nonparametric modeling techniques can prove particularly ill-suited, as the complexity of the model is allowed to increase with the sample size. In this work, we take steps to overcome these challenges by porting information theoretic heuristics, such as exponential forgetting and active learning, into a fully Bayesian framework. We showcase our methods by augmenting a modern non-parametric modeling framework, dynamic trees, and illustrate its performance on a number of practical examples. The end product is a powerful streaming regression and classification tool, whose performance compares favorably to the state-of-the-art.
-
A Computer-Assisted Learning Model Based on the Digital Game Exponential Reward System
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…
-
Theoretical Physics 1. Theoretical Mechanics
International Nuclear Information System (INIS)
Dreizler, Reiner M.; Luedde, Cora S.
2010-01-01
After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. (orig.)
-
Theoretical Physics 1. Theoretical Mechanics
Energy Technology Data Exchange (ETDEWEB)
Dreizler, Reiner M.; Luedde, Cora S. [Frankfurt Univ. (Germany). Inst. fuer Theoretische Physik
2010-07-01
After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. (orig.)
-
Teaching numerical methods with IPython notebooks and inquiry-based learning
Ketcheson, David I.
2014-01-01
A course in numerical methods should teach both the mathematical theory of numerical analysis and the craft of implementing numerical algorithms. The IPython notebook provides a single medium in which mathematics, explanations, executable code, and visualizations can be combined, and with which the student can interact in order to learn both the theory and the craft of numerical methods. The use of notebooks also lends itself naturally to inquiry-based learning methods. I discuss the motivation and practice of teaching a course based on the use of IPython notebooks and inquiry-based learning, including some specific practical aspects. The discussion is based on my experience teaching a Masters-level course in numerical analysis at King Abdullah University of Science and Technology (KAUST), but is intended to be useful for those who teach at other levels or in industry.
-
Project Oriented Immersion Learning: Method and Results
DEFF Research Database (Denmark)
Icaza, José I.; Heredia, Yolanda; Borch, Ole M.
2005-01-01
A pedagogical approach called “project oriented immersion learning” is presented and tested on a graduate online course. The approach combines the Project Oriented Learning method with immersion learning in a virtual enterprise. Students assumed the role of authors hired by a fictitious publishing...... house that develops digital products including e-books, tutorials, web sites and so on. The students defined the problem that their product was to solve; choose the type of product and the content; and built the product following a strict project methodology. A wiki server was used as a platform to hold...
-
Examining Neuronal Connectivity and Its Role in Learning and Memory
Gala, Rohan
Learning and long-term memory formation are accompanied with changes in the patterns and weights of synaptic connections in the underlying neuronal network. However, the fundamental rules that drive connectivity changes, and the precise structure-function relationships within neuronal networks remain elusive. Technological improvements over the last few decades have enabled the observation of large but specific subsets of neurons and their connections in unprecedented detail. Devising robust and automated computational methods is critical to distill information from ever-increasing volumes of raw experimental data. Moreover, statistical models and theoretical frameworks are required to interpret the data and assemble evidence into understanding of brain function. In this thesis, I first describe computational methods to reconstruct connectivity based on light microscopy imaging experiments. Next, I use these methods to quantify structural changes in connectivity based on in vivo time-lapse imaging experiments. Finally, I present a theoretical model of associative learning that can explain many stereotypical features of experimentally observed connectivity.
-
Empowering and Engaging Students in Learning Research Methods
Liu, Shuang; Breit, Rhonda
2013-01-01
The capacity to conduct research is essential for university graduates to survive and thrive in their future career. However, research methods courses have often been considered by students as "abstract", "uninteresting", and "hard". Thus, motivating students to engage in the process of learning research methods has become a crucial challenge for…
-
A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction.
Lu, Hongyang; Wei, Jingbo; Liu, Qiegen; Wang, Yuhao; Deng, Xiaohua
2016-01-01
Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV) approach and adaptive dictionary learning (DL). In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.
-
An information-theoretic machine learning approach to expression QTL analysis.
Directory of Open Access Journals (Sweden)
Tao Huang
Full Text Available Expression Quantitative Trait Locus (eQTL analysis is a powerful tool to study the biological mechanisms linking the genotype with gene expression. Such analyses can identify genomic locations where genotypic variants influence the expression of genes, both in close proximity to the variant (cis-eQTL, and on other chromosomes (trans-eQTL. Many traditional eQTL methods are based on a linear regression model. In this study, we propose a novel method by which to identify eQTL associations with information theory and machine learning approaches. Mutual Information (MI is used to describe the association between genetic marker and gene expression. MI can detect both linear and non-linear associations. What's more, it can capture the heterogeneity of the population. Advanced feature selection methods, Maximum Relevance Minimum Redundancy (mRMR and Incremental Feature Selection (IFS, were applied to optimize the selection of the affected genes by the genetic marker. When we applied our method to a study of apoE-deficient mice, it was found that the cis-acting eQTLs are stronger than trans-acting eQTLs but there are more trans-acting eQTLs than cis-acting eQTLs. We compared our results (mRMR.eQTL with R/qtl, and MatrixEQTL (modelLINEAR and modelANOVA. In female mice, 67.9% of mRMR.eQTL results can be confirmed by at least two other methods while only 14.4% of R/qtl result can be confirmed by at least two other methods. In male mice, 74.1% of mRMR.eQTL results can be confirmed by at least two other methods while only 18.2% of R/qtl result can be confirmed by at least two other methods. Our methods provide a new way to identify the association between genetic markers and gene expression. Our software is available from supporting information.
-
Theoretical and methodological basis of the comparative historical and legal method development
Directory of Open Access Journals (Sweden)
Д. А. Шигаль
2015-05-01
Full Text Available Problem setting. Development of any scientific method is always both a question of its structural and functional characteristics and place in the system of scientific methods, and a comment as for practicability of such methodological work. This paper attempts to give a detailed response to the major comments and objections arising in respect of the separation as an independent means of special and scientific knowledge of comparative historical and legal method. Recent research and publications analysis. Analyzing research and publications within the theme of the scientific article, it should be noted that attention to methodological issues of both general and legal science at the time was paid by such prominent foreign and domestic scholars as I. D. Andreev, Yu. Ya. Baskin, O. L. Bygych, M. A. Damirli, V. V. Ivanov, I. D. Koval'chenko, V. F. Kolomyitsev, D. V. Lukyanov, L. A. Luts, J. Maida, B. G. Mogilnytsky, N. M. Onishchenko, N. M. Parkhomenko, O. V. Petryshyn, S. P. Pogrebnyak, V. I. Synaisky, V. M. Syryh, O. F. Skakun, A. O. Tille, D. I. Feldman and others. It should be noted that, despite a large number of scientific papers in this field, the interest of research partnership in the methodology of history of state and law science still unfairly remains very low. Paper objective. The purpose of this scientific paper is theoretical and methodological rationale for the need of separation and development of comparative historical and legal method in the form of answers to more common questions and objections that arise in scientific partnership in this regard. Paper main body. Development of comparative historical and legal means of knowledge is quite justified because it meets the requirements of the scientific method efficiency, which criteria are the speed for achieving this goal, ease of use of one or another way of scientific knowledge, universality of research methods, convenience of techniques that are used and so on. Combining the
-
Ariana, Armin; Amin, Moein; Pakneshan, Sahar; Dolan-Evans, Elliot; Lam, Alfred K
2016-09-01
Dental students require a basic ability to explain and apply general principles of pathology to systemic, dental, and oral pathology. Although there have been recent advances in electronic and online resources, the academic effectiveness of using self-directed e-learning tools in pathology courses for dental students is unclear. The aim of this study was to determine if blended learning combining e-learning with traditional learning methods of lectures and tutorials would improve students' scores and satisfaction over those who experienced traditional learning alone. Two consecutive cohorts of Bachelor of Dentistry and Oral Health students taking the general pathology course at Griffith University in Australia were compared. The control cohort experienced traditional methods only, while members of the study cohort were also offered self-directed learning materials including online resources and online microscopy classes. Final assessments for the course were used to compare the differences in effectiveness of the intervention, and students' satisfaction with the teaching format was evaluated using questionnaires. On the final course assessments, students in the study cohort had significantly higher scores than students in the control cohort (plearning tools such as virtual microscopy and interactive online resources for delivering pathology instruction can be an effective supplement for developing dental students' competence, confidence, and satisfaction.
-
The Learners’ Attitudes towards Using Different Learning Methods in E-Learning Portal Environment
Directory of Open Access Journals (Sweden)
Issham Ismail
2011-09-01
Full Text Available This study investigates the learners’ preference of academic, collaborative and social interaction towards interaction methods in e-learning portal. Academic interaction consists of interaction between learners and online learning resources such as online reading, online explanation, online examination and also online question answering. Collaborative interaction occurs when learners interact among themselves using online group discussion. Social interaction happens when learners and instructors participate in the session either via online text chatting or voice chatting. The study employed qualitative methodology where data were collected through questionnaire that was administered to 933 distance education students from Bachelor of Management, Bachelor of Science, Bachelor of Social Science and Bachelor of Art. The survey responses were tabulated in a 5-point Likert scale and analyzed using the Statistical Package for Social Science (SPSS Version 12.0 based on frequency and percentage distribution. The result of the study suggest that among three types of interaction, most of the student prefer academic interaction for their learning supports in e-learning portal compared to collaborative and social interaction. They wish to interact with learning content rather than interact with people. They prefer to read and learn from the resources rather than sharing knowledge among themselves and instructors via collaborative and social interaction.
-
Action methods in the classroom: creative strategies for nursing education.
McLaughlin, Dorcas E; Freed, Patricia E; Tadych, Rita A
2006-01-01
Nursing education recognizes the need for a framework of experiential learning that supports the development of professional roles. Action methods, originated by Jacob L. Moreno (1953), can be readily adapted to any nursing classroom to create the conditions under which students learn and practice professional nursing roles. While nurse faculty can learn to use action methods, they may not fully comprehend their theoretical underpinnings or may believe they are only used in therapy. This article explores Moreno's ideas related to psychodrama and sociodrama applied in classroom settings, and presents many examples and tips for classroom teachers who wish to incorporate action methods into their classes.
-
Directory of Open Access Journals (Sweden)
Vicente D. Estruch
2017-08-01
Full Text Available The concept of random variable is a mathematical construct that presents some theoretical complexity. However, learning this concept can be facilitated if it is presented as the end of a sequential process of modeling of a real event. More specifically, to learn the concept of discrete random variable, the Monte Carlo simulation can provide an extremely useful tool because in the process of modeling / simulation one can approach the theoretical concept of random variable, while the random variable is observed \\in action". This paper presents a Research and Study Course (RSC based on series of activities related to random variables such as training and introduction of simulation elements, then the construction of the model is presented, which is the substantial part of the activity, generating a random variable and its probability function. Starting from a simple situation related to reproduction and survival of the litter of a rodent, with random components, step by step, the model that represents the real raised situation is built obtaining an \\original" random variable. In the intermediate stages of the construction of the model have a fundamental role the uniform discrete and binomial distributions. The trajectory of these stages allows reinforcing the concept of random variable while exploring the possibilities offered by Monte Carlo methods to simulate real cases and the simplicity of implementing these methods by means of the Matlab© programming language.
-
STEM learning activity among home-educating families
Bachman, Jennifer
2011-12-01
Science, technology, engineering, and mathematics (STEM) learning was studied among families in a group of home-educators in the Pacific Northwest. Ethnographic methods recorded learning activity (video, audio, fieldnotes, and artifacts) which was analyzed using a unique combination of Cultural-Historical Activity Theory (CHAT) and Mediated Action (MA), enabling analysis of activity at multiple levels. Findings indicate that STEM learning activity is family-led, guided by parents' values and goals for learning, and negotiated with children to account for learner interests and differences, and available resources. Families' STEM education practice is dynamic, evolves, and influenced by larger societal STEM learning activity. Parents actively seek support and resources for STEM learning within their home-school community, working individually and collectively to share their funds of knowledge. Home-schoolers also access a wide variety of free-choice learning resources: web-based materials, museums, libraries, and community education opportunities (e.g. afterschool, weekend and summer programs, science clubs and classes, etc.). A lesson-heuristic, grounded in Mediated Action, represents and analyzes home STEM learning activity in terms of tensions between parental goals, roles, and lesson structure. One tension observed was between 'academic' goals or school-like activity and 'lifelong' goals or everyday learning activity. Theoretical and experiential learning was found in both activity, though parents with academic goals tended to focus more on theoretical learning and those with lifelong learning goals tended to be more experiential. Examples of the National Research Council's science learning strands (NRC, 2009) were observed in the STEM practices of all these families. Findings contribute to the small but growing body of empirical CHAT research in science education, specifically to the empirical base of family STEM learning practices at home. It also fills a
-
Harman, Tara; Bertrand, Brenda; Greer, Annette; Pettus, Arianna; Jennings, Jill; Wall-Bassett, Elizabeth; Babatunde, Oyinlola Toyin
2015-03-01
The vision of dietetics professions is based on interdependent education, credentialing, and practice. Case-based learning is a method of problem-based learning that is designed to heighten higher-order thinking. Case-based learning can assist students to connect education and specialized practice while developing professional skills for entry-level practice in nutrition and dietetics. This study examined student perspectives of their learning after immersion into case-based learning in nutrition courses. The theoretical frameworks of phenomenology and Bloom's Taxonomy of Educational Objectives triangulated the design of this qualitative study. Data were drawn from 426 written responses and three focus group discussions among 85 students from three upper-level undergraduate nutrition courses. Coding served to deconstruct the essence of respondent meaning given to case-based learning as a learning method. The analysis of the coding was the constructive stage that led to configuration of themes and theoretical practice pathways about student learning. Four leading themes emerged. Story or Scenario represents the ways that students described case-based learning, changes in student thought processes to accommodate case-based learning are illustrated in Method of Learning, higher cognitive learning that was achieved from case-based learning is represented in Problem Solving, and Future Practice details how students explained perceived professional competency gains from case-based learning. The skills that students acquired are consistent with those identified as essential to professional practice. In addition, the common concept of Big Picture was iterated throughout the themes and demonstrated that case-based learning prepares students for multifaceted problems that they are likely to encounter in professional practice. Copyright © 2015 Academy of Nutrition and Dietetics. Published by Elsevier Inc. All rights reserved.
-
An Analytical framework of social learning facilitated by participatory methods
Scholz, G.; Dewulf, A.; Pahl-Wostl, C.
2014-01-01
Social learning among different stakeholders is often a goal in problem solving contexts such as environmental management. Participatory methods (e.g., group model-building and role playing games) are frequently assumed to stimulate social learning. Yet understanding if and why this assumption is
-
Kratochvíl Jiří
2014-01-01
Purpose: The main goal of this paper is to argue E-learning can be a viable alternative teaching method for Information Literacy according to a comparation of librarian’s time spent face-to-face teaching with tutoring the E-learning course, average time spent a week on learning by the students, time flexibility of E-learning, students’ satisfaction with E-learning and students’ ability to gain practical skills and theoretical knowledge through E-learning. Design/methodology/approach: Sati...
-
Blatt, John M
1979-01-01
A classic work by two leading physicists and scientific educators endures as an uncommonly clear and cogent investigation and correlation of key aspects of theoretical nuclear physics. It is probably the most widely adopted book on the subject. The authors approach the subject as ""the theoretical concepts, methods, and considerations which have been devised in order to interpret the experimental material and to advance our ability to predict and control nuclear phenomena.""The present volume does not pretend to cover all aspects of theoretical nuclear physics. Its coverage is restricted to
-
Experimental and Theoretical Methods in Algebra, Geometry and Topology
Veys, Willem; Bridging Algebra, Geometry, and Topology
2014-01-01
Algebra, geometry and topology cover a variety of different, but intimately related research fields in modern mathematics. This book focuses on specific aspects of this interaction. The present volume contains refereed papers which were presented at the International Conference “Experimental and Theoretical Methods in Algebra, Geometry and Topology”, held in Eforie Nord (near Constanta), Romania, during 20-25 June 2013. The conference was devoted to the 60th anniversary of the distinguished Romanian mathematicians Alexandru Dimca and Ştefan Papadima. The selected papers consist of original research work and a survey paper. They are intended for a large audience, including researchers and graduate students interested in algebraic geometry, combinatorics, topology, hyperplane arrangements and commutative algebra. The papers are written by well-known experts from different fields of mathematics, affiliated to universities from all over the word, they cover a broad range of topics and explore the research f...
-
Stochastic sensitivity analysis and Langevin simulation for neural network learning
International Nuclear Information System (INIS)
Koda, Masato
1997-01-01
A comprehensive theoretical framework is proposed for the learning of a class of gradient-type neural networks with an additive Gaussian white noise process. The study is based on stochastic sensitivity analysis techniques, and formal expressions are obtained for stochastic learning laws in terms of functional derivative sensitivity coefficients. The present method, based on Langevin simulation techniques, uses only the internal states of the network and ubiquitous noise to compute the learning information inherent in the stochastic correlation between noise signals and the performance functional. In particular, the method does not require the solution of adjoint equations of the back-propagation type. Thus, the present algorithm has the potential for efficiently learning network weights with significantly fewer computations. Application to an unfolded multi-layered network is described, and the results are compared with those obtained by using a back-propagation method
-
Radical-Local Teaching and Learning
DEFF Research Database (Denmark)
Hedegaard, Mariane; Chaiklin, Seth
Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded in the l......Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded...... radical-local teaching and learning approach. The first half of the book introduces the idea of radical-local teaching and learning and develops the theoretical background for this perspective, drawing on the cultural-historical research tradition, particularly from Vygotsky, El'konin, Davydov......, and Aidarova. The second half of the book addresses the central concern of radical-local teaching and learning - how to relate educational practices to children's specific historical and cultural conditions. The experiment was conducted for an academic year in an afterschool programme in the East Harlem...
-
Theoretical studies of potential energy surfaces and computational methods
Energy Technology Data Exchange (ETDEWEB)
Shepard, R. [Argonne National Laboratory, IL (United States)
1993-12-01
This project involves the development, implementation, and application of theoretical methods for the calculation and characterization of potential energy surfaces involving molecular species that occur in hydrocarbon combustion. These potential energy surfaces require an accurate and balanced treatment of reactants, intermediates, and products. This difficult challenge is met with general multiconfiguration self-consistent-field (MCSCF) and multireference single- and double-excitation configuration interaction (MRSDCI) methods. In contrast to the more common single-reference electronic structure methods, this approach is capable of describing accurately molecular systems that are highly distorted away from their equilibrium geometries, including reactant, fragment, and transition-state geometries, and of describing regions of the potential surface that are associated with electronic wave functions of widely varying nature. The MCSCF reference wave functions are designed to be sufficiently flexible to describe qualitatively the changes in the electronic structure over the broad range of geometries of interest. The necessary mixing of ionic, covalent, and Rydberg contributions, along with the appropriate treatment of the different electron-spin components (e.g. closed shell, high-spin open-shell, low-spin open shell, radical, diradical, etc.) of the wave functions, are treated correctly at this level. Further treatment of electron correlation effects is included using large scale multireference CI wave functions, particularly including the single and double excitations relative to the MCSCF reference space. This leads to the most flexible and accurate large-scale MRSDCI wave functions that have been used to date in global PES studies.
-
Directory of Open Access Journals (Sweden)
Michael Kiener
2008-08-01
Full Text Available Under the principles of the scholarship of teaching and learning and action research this study sought to examine how an instructor created and facilitated engagement in his students. The research was primarily undertaken to further define the middle range theory of mutual engagement. Theoretical sampling was used to analyze approximately 100 pieces of data that included instructor notes, teaching observations, feedback from conference presentations, student assessments, and end of semester student evaluations. Engaging conversationally (EC emerged as the phenomenon that described the instructor’s engagement in the learning process. EC was an ongoing cyclical pattern of inquiry that included preparing, reflecting and modeling. Interconnected in the pattern of inquiry were personality traits, counselor education, and teaching philosophy.
-
A study of active learning methods for named entity recognition in clinical text.
Chen, Yukun; Lasko, Thomas A; Mei, Qiaozhu; Denny, Joshua C; Xu, Hua
2015-12-01
Named entity recognition (NER), a sequential labeling task, is one of the fundamental tasks for building clinical natural language processing (NLP) systems. Machine learning (ML) based approaches can achieve good performance, but they often require large amounts of annotated samples, which are expensive to build due to the requirement of domain experts in annotation. Active learning (AL), a sample selection approach integrated with supervised ML, aims to minimize the annotation cost while maximizing the performance of ML-based models. In this study, our goal was to develop and evaluate both existing and new AL methods for a clinical NER task to identify concepts of medical problems, treatments, and lab tests from the clinical notes. Using the annotated NER corpus from the 2010 i2b2/VA NLP challenge that contained 349 clinical documents with 20,423 unique sentences, we simulated AL experiments using a number of existing and novel algorithms in three different categories including uncertainty-based, diversity-based, and baseline sampling strategies. They were compared with the passive learning that uses random sampling. Learning curves that plot performance of the NER model against the estimated annotation cost (based on number of sentences or words in the training set) were generated to evaluate different active learning and the passive learning methods and the area under the learning curve (ALC) score was computed. Based on the learning curves of F-measure vs. number of sentences, uncertainty sampling algorithms outperformed all other methods in ALC. Most diversity-based methods also performed better than random sampling in ALC. To achieve an F-measure of 0.80, the best method based on uncertainty sampling could save 66% annotations in sentences, as compared to random sampling. For the learning curves of F-measure vs. number of words, uncertainty sampling methods again outperformed all other methods in ALC. To achieve 0.80 in F-measure, in comparison to random
-
Learning Physical Domains: Toward a Theoretical Framework.
1986-12-01
advanced ids o the iaime doinain in containing more information, especially perceptual " ’It. iho lI b1 rwt... tI hat. psychboigists by no means...Acquisitions Dr Kenneth D Forbus 4833 Rugby Avenue University of Illinois Dr Robert Glaser Bethesda, MD 20014 Department of Computer Science Learning
-
Conduct disorders as a result of specific learning disorders
VOKROJOVÁ, Nela
2012-01-01
This thesis focuses on relationship between specific learning disorders and conduct disorders in puberty. The theoretical part explains the basic terms apearing in the thesis such as specific learning disorders, conduct disorders, puberty and prevention of conduct disorder formation. It presents Czech and foreign research which have already been done in this and related areas. The empirical part uses a quantitative method to measure anxiety and occurrence of conduct disorders in second grade ...
-
Maximizing policy learning in international committees
DEFF Research Database (Denmark)
Nedergaard, Peter
2007-01-01
, this article demonstrates that valuable lessons can be learned about policy learning, in practice and theoretically, by analysing the cooperation in the OMC committees. Using the Advocacy Coalition Framework as the starting point of analysis, 15 hypotheses on policy learning are tested. Among other things......In the voluminous literature on the European Union's open method of coordination (OMC), no one has hitherto analysed on the basis of scholarly examination the question of what contributes to the learning processes in the OMC committees. On the basis of a questionnaire sent to all participants......, it is concluded that in order to maximize policy learning in international committees, empirical data should be made available to committees and provided by sources close to the participants (i.e. the Commission). In addition, the work in the committees should be made prestigious in order to attract well...
-
Rock, Adam J; Coventry, William L; Morgan, Methuen I; Loi, Natasha M
2016-01-01
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.
-
Rock, Adam J.; Coventry, William L.; Morgan, Methuen I.; Loi, Natasha M.
2016-01-01
Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal et al., 1997). Given the ubiquitous and distributed nature of eLearning systems (Nof et al., 2015), teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology. PMID:27014147
-
Directory of Open Access Journals (Sweden)
Adam John Rock
2016-03-01
Full Text Available Generally, academic psychologists are mindful of the fact that, for many students, the study of research methods and statistics is anxiety provoking (Gal, Ginsburg, & Schau, 1997. Given the ubiquitous and distributed nature of eLearning systems (Nof, Ceroni, Jeong, & Moghaddam, 2015, teachers of research methods and statistics need to cultivate an understanding of how to effectively use eLearning tools to inspire psychology students to learn. Consequently, the aim of the present paper is to discuss critically how using eLearning systems might engage psychology students in research methods and statistics. First, we critically appraise definitions of eLearning. Second, we examine numerous important pedagogical principles associated with effectively teaching research methods and statistics using eLearning systems. Subsequently, we provide practical examples of our own eLearning-based class activities designed to engage psychology students to learn statistical concepts such as Factor Analysis and Discriminant Function Analysis. Finally, we discuss general trends in eLearning and possible futures that are pertinent to teachers of research methods and statistics in psychology.
-
A Comparison of Machine Learning Methods in a High-Dimensional Classification Problem
Directory of Open Access Journals (Sweden)
Zekić-Sušac Marijana
2014-09-01
Full Text Available Background: Large-dimensional data modelling often relies on variable reduction methods in the pre-processing and in the post-processing stage. However, such a reduction usually provides less information and yields a lower accuracy of the model. Objectives: The aim of this paper is to assess the high-dimensional classification problem of recognizing entrepreneurial intentions of students by machine learning methods. Methods/Approach: Four methods were tested: artificial neural networks, CART classification trees, support vector machines, and k-nearest neighbour on the same dataset in order to compare their efficiency in the sense of classification accuracy. The performance of each method was compared on ten subsamples in a 10-fold cross-validation procedure in order to assess computing sensitivity and specificity of each model. Results: The artificial neural network model based on multilayer perceptron yielded a higher classification rate than the models produced by other methods. The pairwise t-test showed a statistical significance between the artificial neural network and the k-nearest neighbour model, while the difference among other methods was not statistically significant. Conclusions: Tested machine learning methods are able to learn fast and achieve high classification accuracy. However, further advancement can be assured by testing a few additional methodological refinements in machine learning methods.
-
Deep Learning in Open Source Learning Streams
DEFF Research Database (Denmark)
Kjærgaard, Thomas
2016-01-01
This chapter presents research on deep learning in a digital learning environment and raises the question if digital instructional designs can catalyze deeper learning than traditional classroom teaching. As a theoretical point of departure the notion of ‘situated learning’ is utilized...... and contrasted to the notion of functionalistic learning in a digital context. The mechanism that enables deep learning in this context is ‘The Open Source Learning Stream’. ‘The Open Source Learning Stream’ is the notion of sharing ‘learning instances’ in a digital space (discussion board, Facebook group......, unistructural, multistructural or relational learning. The research concludes that ‘The Open Source Learning Stream’ can catalyze deep learning and that there are four types of ‘Open Source Learning streams’; individual/ asynchronous, individual/synchronous, shared/asynchronous and shared...
-
Strategic Management: An Evaluation of the Use of Three Learning Methods.
Jennings, David
2002-01-01
A study of 46 management students compared three methods for learning strategic management: cases, simulation, and action learning through consulting projects. Simulation was superior to action learning on all outcomes and equal or superior to cases on two. Simulation gave students a central role in management and greater control of the learning…
-
Frank Gilbreth and health care delivery method study driven learning.
Towill, Denis R
2009-01-01
The purpose of this article is to look at method study, as devised by the Gilbreths at the beginning of the twentieth century, which found early application in hospital quality assurance and surgical "best practice". It has since become a core activity in all modern methods, as applied to healthcare delivery improvement programmes. The article traces the origin of what is now currently and variously called "business process re-engineering", "business process improvement" and "lean healthcare" etc., by different management gurus back to the century-old pioneering work of Frank Gilbreth. The outcome is a consistent framework involving "width", "length" and "depth" dimensions within which healthcare delivery systems can be analysed, designed and successfully implemented to achieve better and more consistent performance. Healthcare method (saving time plus saving motion) study is best practised as co-joint action learning activity "owned" by all "players" involved in the re-engineering process. However, although process mapping is a key step forward, in itself it is no guarantee of effective re-engineering. It is not even the beginning of the end of the change challenge, although it should be the end of the beginning. What is needed is innovative exploitation of method study within a healthcare organisational learning culture accelerated via the Gilbreth Knowledge Flywheel. It is shown that effective healthcare delivery pipeline improvement is anchored into a team approach involving all "players" in the system especially physicians. A comprehensive process study, constructive dialogue, proper and highly professional re-engineering plus managed implementation are essential components. Experience suggests "learning" is thereby achieved via "natural groups" actively involved in healthcare processes. The article provides a proven method for exploiting Gilbreths' outputs and their many successors in enabling more productive evidence-based healthcare delivery as summarised
-
A Dictionary Learning Method with Total Generalized Variation for MRI Reconstruction
Directory of Open Access Journals (Sweden)
Hongyang Lu
2016-01-01
Full Text Available Reconstructing images from their noisy and incomplete measurements is always a challenge especially for medical MR image with important details and features. This work proposes a novel dictionary learning model that integrates two sparse regularization methods: the total generalized variation (TGV approach and adaptive dictionary learning (DL. In the proposed method, the TGV selectively regularizes different image regions at different levels to avoid oil painting artifacts largely. At the same time, the dictionary learning adaptively represents the image features sparsely and effectively recovers details of images. The proposed model is solved by variable splitting technique and the alternating direction method of multiplier. Extensive simulation experimental results demonstrate that the proposed method consistently recovers MR images efficiently and outperforms the current state-of-the-art approaches in terms of higher PSNR and lower HFEN values.
-
Institute of Scientific and Technical Information of China (English)
Weixin Cheng; Feike A. Dijkstra
2007-01-01
Continuous isotope labeling and tracing is often needed to study the transformation, movement, and allocation of carbon in plant-soil systems. However, existing labeling methods have numerous limitations. The present study introduces a new continuous labeling method using naturally 13C-depleted CO2. We theoretically proved that a stable level of 13C-CO2 abundance In a labeling chamber can be maintained by controlling the rate of CO2-free air injection and the rate of ambient airflow with coupling of automatic control of CO2 concentration using a CO2 analyzer. The theoretical results were tested and confirmed in a 54 day experiment in a plant growth chamber. This new continuous labeling method avoids the use of radioactive 14C or expensive 13C-enriched CO2 required by existing methods and therefore eliminates issues of radiation safety or unaffordable isotope cost, as well as creating new opportunities for short- or long-term labeling experiments under a controlled environment.
-
Future Competencies and Learning Methods in Engineering Education
DEFF Research Database (Denmark)
Kolmos, Anette
2002-01-01
What are the competencies for tommorow´s enginnering education and the implications of these regarding the choice of teaching content and learning methods? The paper analyses two trends: the traditional and the techo-science approach. These two trends are based on technological innovation...... and change processes and impact on educational content and methods....
-
Hartle, R. Todd
2007-12-01
. Understanding how to identify and evaluate constructivist lessons is the first step in promoting and improving constructivism in teaching. Chapter 4 summarizes a theoretically-generated series of practical criteria that define constructivism: (1) Eliciting Prior Knowledge, (2) Creating Cognitive Dissonance, (3) Application of New Knowledge with Feedback, and (4) Reflection on Learning, or Metacognition. These criteria can be used by any practitioner to evaluate the level of constructivism used in a given lesson or activity.
-
Theoretical Mechanics Theoretical Physics 1
Dreizler, Reiner M
2011-01-01
After an introduction to basic concepts of mechanics more advanced topics build the major part of this book. Interspersed is a discussion of selected problems of motion. This is followed by a concise treatment of the Lagrangian and the Hamiltonian formulation of mechanics, as well as a brief excursion on chaotic motion. The last chapter deals with applications of the Lagrangian formulation to specific systems (coupled oscillators, rotating coordinate systems, rigid bodies). The level of this textbook is advanced undergraduate. The authors combine teaching experience of more than 40 years in all fields of Theoretical Physics and related mathematical disciplines and thorough knowledge in creating advanced eLearning content. The text is accompanied by an extensive collection of online material, in which the possibilities of the electronic medium are fully exploited, e.g. in the form of applets, 2D- and 3D-animations. - A collection of 74 problems with detailed step-by-step guidance towards the solutions. - A col...
-
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.
-
Preferred Methods of Learning for Nursing Students in an On-Line Degree Program.
Hampton, Debra; Pearce, Patricia F; Moser, Debra K
Investigators have demonstrated that on-line courses result in effective learning outcomes, but limited information has been published related to preferred teaching strategies. Delivery of on-line courses requires various teaching methods to facilitate interaction between students, content, and technology. The purposes of this study were to understand student teaching/learning preferences in on-line courses to include (a) differences in preferred teaching/learning methods for on-line nursing students across generations and (b) which teaching strategies students found to be most engaging and effective. Participants were recruited from 2 accredited, private school nursing programs (N=944) that admit students from across the United States and deliver courses on-line. Participants provided implied consent, and 217 (23%) students completed the on-line survey. Thirty-two percent of the students were from the Baby Boomer generation (1946-1964), 48% from Generation X (1965-1980), and 20% from the Millennial Generation (born after 1980). The preferred teaching/learning methods for students were videos or narrated PowerPoint presentations, followed by synchronous Adobe Connect educations sessions, assigned journal article reading, and e-mail dialog with the instructor. The top 2 methods identified by participants as the most energizing/engaging and most effective for learning were videos or narrated PowerPoint presentations and case studies. The teaching/learning method least preferred by participants and that was the least energizing/engaging was group collaborative projects with other students; the method that was the least effective for learning was wikis. Baby Boomers and Generation X participants had a significantly greater preference for discussion board (PBaby Boomer and Generation X students and rated on-line games as significantly more energizing/engaging and more effective for learning (PBaby Boomer and Generation X students. In conclusion, the results of this
-
Almost Free Modules Set-Theoretic Methods
Eklof, PC
1990-01-01
This is an extended treatment of the set-theoretic techniques which have transformed the study of abelian group and module theory over the last 15 years. Part of the book is new work which does not appear elsewhere in any form. In addition, a large body of material which has appeared previously (in scattered and sometimes inaccessible journal articles) has been extensively reworked and in many cases given new and improved proofs. The set theory required is carefully developed with algebraists in mind, and the independence results are derived from explicitly stated axioms. The book contains exe
-
Wilson, Penne L.
2007-12-01
This study was conducted as part of the five year evaluation of the Star Schools grant awarded to Oklahoma State University for the development on online teacher professional development in the Hypothesis Based Learning (HbL) method of science instruction. Participants in this research were five teachers who had completed the online workshop, submitted a lesson plan, and who allowed this researcher and other members of the University of New Mexico Evaluation Team into their classrooms to observe and to determine if the learning of the method from the online HbL workshop had translated into practice. These teachers worked in inner city, suburban, metropolitan, and rural communities in the U.S. Southwest. This study was conducted to determine if teachers learned the HbL method from the online HbL workshop, to examine the relationship of satisfaction to learning, and to determine the elements of the online workshop that led to teacher learning. To measure learning of HbL, three different assessment instruments were used: embedded assessments within the online HbL workshop that gave teachers a scenario and asked them to generate questions to facilitate the HbL process; the analysis of a lesson plan provided by teachers using a science concept that they wished to incorporate in their curriculum using an HbL lesson template provided at the HbL website; and, observations of teachers facilitating the HbL process conducted at three different times during the year that they began the HbL online workshop. To determine if teachers were satisfied with the learning environment, the online HbL workshop, and the product, HbL Method for Teaching Science, and to determine if teachers could identify the elements of the online workshop that led to learning, interviews with the participants were conducted. The research findings were presented in two parts: Part I is an analysis of data provided by the assessment instruments and a content analysis of the transcripts of the teacher
-
Davies, Bethany S; Rafique, Jethin; Vincent, Tim R; Fairclough, Jil; Packer, Mark H; Vincent, Richard; Haq, Inam
2012-01-12
Mobile technology is increasingly being used by clinicians to access up-to-date information for patient care. These offer learning opportunities in the clinical setting for medical students but the underlying pedagogic theories are not clear. A conceptual framework is needed to understand these further. Our initial questions were how the medical students used the technology, how it enabled them to learn and what theoretical underpinning supported the learning. 387 medical students were provided with a personal digital assistant (PDA) loaded with medical resources for the duration of their clinical studies. Outcomes were assessed by a mixed-methods triangulation approach using qualitative and quantitative analysis of surveys, focus groups and usage tracking data. Learning occurred in context with timely access to key facts and through consolidation of knowledge via repetition. The PDA was an important addition to the learning ecology rather than a replacement. Contextual factors impacted on use both positively and negatively. Barriers included concerns of interrupting the clinical interaction and of negative responses from teachers and patients. Students preferred a future involving smartphone platforms. This is the first study to describe the learning ecology and pedagogic basis behind the use of mobile learning technologies in a large cohort of undergraduate medical students in the clinical environment. We have developed a model for mobile learning in the clinical setting that shows how different theories contribute to its use taking into account positive and negative contextual factors.The lessons from this study are transferable internationally, to other health care professions and to the development of similar initiatives with newer technology such as smartphones or tablet computers.
-
Energy Technology Data Exchange (ETDEWEB)
Wigger, Lothar; Buenger, Carsten (eds.) [Technische Univ. Dortmund (Germany). Bereich Allgemeine Erziehungswissenschaft; Platzer, Barbara [Technische Univ. Dortmund (Germany)
2017-08-01
The book on the educational and learning theoretical reflection of nuclear disasters as a consequence of Fukushima includes contributions on the following issues: pedagogical approach: children write on Fukushima, description of the reality as pedagogical challenge; lessons learned on the nuclear technology - perspectives and limits of pedagogical evaluation: moral education - Japanese teaching materials, educational challenges at the universities with respect to nuclear technology and technology impact assessment; education and technology - questions concerning the pedagogical responsibility: considerations on the responsibility of scientists, on the discrepancy between technology and education, disempowerment of the public by structural corruption - nuclear disaster and post-democratic tendencies in Japan.
-
Associationism and cognition: human contingency learning at 25.
Shanks, David R
2007-03-01
A major topic within human learning, the field of contingency judgement, began to emerge about 25 years ago following publication of an article on depressive realism by Alloy and Abramson (1979). Subsequently, associationism has been the dominant theoretical framework for understanding contingency learning but this has been challenged in recent years by an alternative cognitive or inferential approach. This article outlines the key conceptual differences between these approaches and summarizes some of the main methods that have been employed to distinguish between them.
-
Directory of Open Access Journals (Sweden)
Alexander eHanuschkin
2013-06-01
Full Text Available Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: Random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, they allow for imitating arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions.Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird’s own song
-
Hanuschkin, A; Ganguli, S; Hahnloser, R H R
2013-01-01
Mirror neurons are neurons whose responses to the observation of a motor act resemble responses measured during production of that act. Computationally, mirror neurons have been viewed as evidence for the existence of internal inverse models. Such models, rooted within control theory, map-desired sensory targets onto the motor commands required to generate those targets. To jointly explore both the formation of mirrored responses and their functional contribution to inverse models, we develop a correlation-based theory of interactions between a sensory and a motor area. We show that a simple eligibility-weighted Hebbian learning rule, operating within a sensorimotor loop during motor explorations and stabilized by heterosynaptic competition, naturally gives rise to mirror neurons as well as control theoretic inverse models encoded in the synaptic weights from sensory to motor neurons. Crucially, we find that the correlational structure or stereotypy of the neural code underlying motor explorations determines the nature of the learned inverse model: random motor codes lead to causal inverses that map sensory activity patterns to their motor causes; such inverses are maximally useful, by allowing the imitation of arbitrary sensory target sequences. By contrast, stereotyped motor codes lead to less useful predictive inverses that map sensory activity to future motor actions. Our theory generalizes previous work on inverse models by showing that such models can be learned in a simple Hebbian framework without the need for error signals or backpropagation, and it makes new conceptual connections between the causal nature of inverse models, the statistical structure of motor variability, and the time-lag between sensory and motor responses of mirror neurons. Applied to bird song learning, our theory can account for puzzling aspects of the song system, including necessity of sensorimotor gating and selectivity of auditory responses to bird's own song (BOS) stimuli.
-
Suggestology as an Effective Language Learning Method.
MaCoy, Katherine W.
The methods used and the results obtained by means of the accelerated language learning techniques developed by Georgi Lozanov, Director of the Institute of Suggestology in Bulgaria, are discussed. The following topics are included: (1) discussion of hypermnesia, "super memory," and the reasons foreign languages were chosen for purposes…
-
The Rebirth of Children's Learning.
Siegler, Robert S.
2000-01-01
Maintains that recent theoretical and methodological advances have sparked renewed interest in studying children's learning. Describes consistent and interesting findings regarding how children learn and intriguing proposals regarding mechanisms underlying learning. Argues that increasing the focus on children's learning promises practical…
-
THE ROLE AND IMPORTANCE OF THEORETICAL PREPARATION ON “PHYSICAL EDUCATION FOR HIGHSCHOOL STUDENTS
Directory of Open Access Journals (Sweden)
DANIEL DOCU AXELERAD
2009-12-01
Full Text Available According to the pre-universitary curriculum, one of the criteria to asses the level of the subject’s acquisition is the quality of the theoretical knowledge. In the basic organizing documents of school physical education, there were and still are stipulated the exact requests regarding the necessary theoretical knowledge ofstudents on various education levels. According to these documents, the theoretical knowledge was general knowledge. To the general knowledge, there are added those pertaining to the basic information of the given subject, information about the means and methods of physical education, information from the domain of prophylactic physical education, etc. Special knowledge is that representing the students’ knowledge form various sports tests provided by the school curriculum, such as the sporting games (volleyball, basketball,football, handball, athletics (running, jumping, throwing and gymnastics (apparatus and floor exercises. It is here that the means and methods applied in acquiring the compartments listed above are attributed. In the special knowledge category there is also the knowledge related to the means, the forms and the methods to develop the basic motor qualities (force, speed, flexibility, resistance, skills, as well as the procedures for evaluating them.Nevertheless, regardless of the fact that in the physical education organizing normative documents, highschool included, it is provided that theoretical knowledge should be acquired, still there is no actual presentation of the specific requirements and the assessment criteria for the level of acquisition. No document specifies the ways to evaluate the volume and quality of acquiring the theoretical knowledge, which is why we are going to present here a detailed analysis of the level of acquisition of theoretical knowledge for the “Physical Education” subject by highschool students after applying the teaching –learning -evaluation technique on the
-
Koo, Ching Lee; Liew, Mei Jing; Mohamad, Mohd Saberi; Salleh, Abdul Hakim Mohamed
2013-01-01
Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs), support vector machine (SVM), and random forests (RFs) in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
-
A Review for Detecting Gene-Gene Interactions Using Machine Learning Methods in Genetic Epidemiology
Directory of Open Access Journals (Sweden)
Ching Lee Koo
2013-01-01
Full Text Available Recently, the greatest statistical computational challenge in genetic epidemiology is to identify and characterize the genes that interact with other genes and environment factors that bring the effect on complex multifactorial disease. These gene-gene interactions are also denoted as epitasis in which this phenomenon cannot be solved by traditional statistical method due to the high dimensionality of the data and the occurrence of multiple polymorphism. Hence, there are several machine learning methods to solve such problems by identifying such susceptibility gene which are neural networks (NNs, support vector machine (SVM, and random forests (RFs in such common and multifactorial disease. This paper gives an overview on machine learning methods, describing the methodology of each machine learning methods and its application in detecting gene-gene and gene-environment interactions. Lastly, this paper discussed each machine learning method and presents the strengths and weaknesses of each machine learning method in detecting gene-gene interactions in complex human disease.
-
A fast learning method for large scale and multi-class samples of SVM
Fan, Yu; Guo, Huiming
2017-06-01
A multi-class classification SVM(Support Vector Machine) fast learning method based on binary tree is presented to solve its low learning efficiency when SVM processing large scale multi-class samples. This paper adopts bottom-up method to set up binary tree hierarchy structure, according to achieved hierarchy structure, sub-classifier learns from corresponding samples of each node. During the learning, several class clusters are generated after the first clustering of the training samples. Firstly, central points are extracted from those class clusters which just have one type of samples. For those which have two types of samples, cluster numbers of their positive and negative samples are set respectively according to their mixture degree, secondary clustering undertaken afterwards, after which, central points are extracted from achieved sub-class clusters. By learning from the reduced samples formed by the integration of extracted central points above, sub-classifiers are obtained. Simulation experiment shows that, this fast learning method, which is based on multi-level clustering, can guarantee higher classification accuracy, greatly reduce sample numbers and effectively improve learning efficiency.
-
Optimality of Poisson Processes Intensity Learning with Gaussian Processes
Kirichenko, A.; van Zanten, H.
2015-01-01
In this paper we provide theoretical support for the so-called "Sigmoidal Gaussian Cox Process" approach to learning the intensity of an inhomogeneous Poisson process on a d-dimensional domain. This method was proposed by Adams, Murray and MacKay (ICML, 2009), who developed a tractable computational
-
Unorthodox theoretical methods
Energy Technology Data Exchange (ETDEWEB)
Nedd, Sean [Iowa State Univ., Ames, IA (United States)
2012-01-01
The use of the ReaxFF force field to correlate with NMR mobilities of amine catalytic substituents on a mesoporous silica nanosphere surface is considered. The interfacing of the ReaxFF force field within the Surface Integrated Molecular Orbital/Molecular Mechanics (SIMOMM) method, in order to replicate earlier SIMOMM published data and to compare with the ReaxFF data, is discussed. The development of a new correlation consistent Composite Approach (ccCA) is presented, which incorporates the completely renormalized coupled cluster method with singles, doubles and non-iterative triples corrections towards the determination of heats of formations and reaction pathways which contain biradical species.
-
D.3.3 PLOT Persuasive Learning Design Framework
DEFF Research Database (Denmark)
Gram-Hansen, Sandra Burri
2012-01-01
In this third and final deliverable of WP3: Persuasive Learning Designs, the theoretical cross field between persuasion and learning and the practical analysis of the technological learning tools and products which are currently related to the PLOT project, namely the GLOMaker and the 3ET tool......, are linked together as persuasive learning designs are defined and exemplified through the four e-PLOT cases. Based on the literary study of D.3.1 as well as the subsequent discussions and reflections regarding the theoretical foundation and practical application of persuasive learning technologies......-PLOT work cases. In conclusion, the report presents a number of suggestions regarding the improvement of the two learning tools, which from a theoretical perspective will enhance the persuasive potential, and which can be taken into consideration in WP4 and 5....
-
Donnenberg, O.; De Loo, I.G.M.
2004-01-01
Action learning programmes are supposed to result in both personal and organizational development. However, organizational development can be negligible because, as the term implies, a connection must be secured between what has been learned by action learning participants and other members of an
-
Implementing Adaptive Educational Methods with IMS Learning Design
Specht, Marcus; Burgos, Daniel
2006-01-01
Please, cite this publication as: Specht, M. & Burgos, D. (2006). Implementing Adaptive Educational Methods with IMS Learning Design. Proceedings of Adaptive Hypermedia. June, Dublin, Ireland. Retrieved June 30th, 2006, from http://dspace.learningnetworks.org
-
Linked-Class Problem-Based Learning in Engineering: Method and Evaluation
Hunt, Emily M.; Lockwood-Cooke, Pamela; Kelley, Judy
2010-01-01
Problem-Based Learning (PBL) is a problem-centered teaching method with exciting potential in engineering education for motivating and enhancing student learning. Implementation of PBL in engineering education has the potential to bridge the gap between theory and practice. Two common problems are encountered when attempting to integrate PBL into…
-
Directory of Open Access Journals (Sweden)
Lina Yang
2014-01-01
Full Text Available To reduce the computation complexity of wavelet transform, this paper presents a novel approach to be implemented. It consists of two key techniques: (1 fast number theoretic transform(FNTT In the FNTT, linear convolution is replaced by the circular one. It can speed up the computation of 2D discrete wavelet transform. (2 In two-dimensional overlap-save method directly calculating the FNTT to the whole input sequence may meet two difficulties; namely, a big modulo obstructs the effective implementation of the FNTT and a long input sequence slows the computation of the FNTT down. To fight with such deficiencies, a new technique which is referred to as 2D overlap-save method is developed. Experiments have been conducted. The fast number theoretic transform and 2D overlap-method have been used to implement the dyadic wavelet transform and applied to contour extraction in pattern recognition.
-
Identity and Power in Organizational Learning
DEFF Research Database (Denmark)
Keller, Hanne Dauer; Jørgensen, Kenneth Mølbjerg
2005-01-01
This paper presents the conceptual framework for analysing learning in a change project on a teacher training college. We address this project through social learning theory with a special emphasis on Wenger’s concepts the negotiation of meaning and identity. These concepts are further developed...... by drawing on discourse theoretical insight – especially an organization theoretical application of Foucault’s conception of power. Thus, we want to discuss the impact of identity and power on the learning within the change project. We regard organizational learning as processes that take place on various...
-
Early Language Learning: Complexity and Mixed Methods
Enever, Janet, Ed.; Lindgren, Eva, Ed.
2017-01-01
This is the first collection of research studies to explore the potential for mixed methods to shed light on foreign or second language learning by young learners in instructed contexts. It brings together recent studies undertaken in Cameroon, China, Croatia, Ethiopia, France, Germany, Italy, Kenya, Mexico, Slovenia, Spain, Sweden, Tanzania and…
-
Directory of Open Access Journals (Sweden)
AA Vaezi
2015-12-01
Full Text Available Introduction: The effect of teaching methods on learning process of students will help teachers to improve the quality of teaching by selecting an appropriate method. This study aimed to compare the team- based learning and lecture teaching method on learning-teaching process of nursing students in surgical and internal diseases courses. Method: This quasi-experimental study was carried on the nursing students in the School of Nursing and Midwifery in Yazd and Meybod cities. Studied sample was all of the students in the sixth term in the Faculty of Nursing in Yazd (48 persons and the Faculty of Nursing in Meybod (28 persons. The rate of students' learning through lecture was measured using MCQ tests and teaching based on team-based learning (TBL method was run using MCQ tests (IRAT, GRAT, Appeals and Task group. Therefore, in order to examine the students' satisfaction about the TBL method, a 5-point Likert scale (translated questionnaire (1=completely disagree, 2= disagree, 3=not effective, 4=agree, and 5=completely agree consisted of 22 items was utilized. The reliability and validity of this translated questionnaire was measured. The collected data were analyzed through SPSS 17.0 using descriptive and analytical statistic. Result: The results showed that the mean scores in team-based learning were meaningful in individual assessment (17±84 and assessment group (17.2±1.17. The mean of overall scores in TBL method (17.84±0.98% was higher compared with the lecture teaching method (16±2.31. Most of the students believed that TBL method has improved their interpersonal and group interaction skills (100%. Among them, 97.7% of students mentioned that this method (TBL helped them to understand the course content better. The lowest levels of the satisfaction have related to the continuous learning during lifelong (51.2%. Conclusion: The results of the present study showed that the TBL method led to improving the communication skills, understanding
-
COOPERATIVE LEARNING IN DISTANCE LEARNING: A MIXED METHODS STUDY
Directory of Open Access Journals (Sweden)
Lori Kupczynski
2012-07-01
Full Text Available Distance learning has facilitated innovative means to include Cooperative Learning (CL in virtual settings. This study, conducted at a Hispanic-Serving Institution, compared the effectiveness of online CL strategies in discussion forums with traditional online forums. Quantitative and qualitative data were collected from 56 graduate student participants. Quantitative results revealed no significant difference on student success between CL and Traditional formats. The qualitative data revealed that students in the cooperative learning groups found more learning benefits than the Traditional group. The study will benefit instructors and students in distance learning to improve teaching and learning practices in a virtual classroom.
-
Using Problem Based Learning Methods from Engineering Education in Company Based Development
DEFF Research Database (Denmark)
Kofoed, Lise B.; Jørgensen, Frances
2007-01-01
This paper discusses how Problem-Based Learning (PBL) methods were used to support a Danish company in its efforts to become more of a 'learning organisation', characterized by sharing of knowledge and experiences. One of the central barriers to organisational learning in this company involved...
-
Examining Hypermedia Learning: The Role of Cognitive Load and Self-Regulated Learning
Moos, Daniel
2013-01-01
Distinct theoretical perspectives, Cognitive Load Theory and Self-Regulated Learning (SRL) theory, have been used to examine individual differences the challenges faced with hypermedia learning. However, research has tended to use these theories independently, resulting in less robust explanations of hypermedia learning. This study examined the…
-
Non-linguistic learning in aphasia: Effects of training method and stimulus characteristics
Vallila-Rohter, Sofia; Kiran, Swathi
2013-01-01
Purpose The purpose of the current study was to explore non-linguistic learning ability in patients with aphasia, examining the impact of stimulus typicality and feedback on success with learning. Method Eighteen patients with aphasia and eight healthy controls participated in this study. All participants completed four computerized, non-linguistic category-learning tasks. We probed learning ability under two methods of instruction: feedback-based (FB) and paired-associate (PA). We also examined the impact of task complexity on learning ability, comparing two stimulus conditions: typical (Typ) and atypical (Atyp). Performance was compared between groups and across conditions. Results Results demonstrated that healthy controls were able to successfully learn categories under all conditions. For our patients with aphasia, two patterns of performance arose. One subgroup of patients was able to maintain learning across task manipulations and conditions. The other subgroup of patients demonstrated a sensitivity to task complexity, learning successfully only in the typical training conditions. Conclusions Results support the hypothesis that impairments of general learning are present in aphasia. Some patients demonstrated the ability to extract category information under complex training conditions, while others learned only under conditions that were simplified and emphasized salient category features. Overall, the typical training condition facilitated learning for all participants. Findings have implications for therapy, which are discussed. PMID:23695914
-
A Robust Cooperated Control Method with Reinforcement Learning and Adaptive H∞ Control
Obayashi, Masanao; Uchiyama, Shogo; Kuremoto, Takashi; Kobayashi, Kunikazu
This study proposes a robust cooperated control method combining reinforcement learning with robust control to control the system. A remarkable characteristic of the reinforcement learning is that it doesn't require model formula, however, it doesn't guarantee the stability of the system. On the other hand, robust control system guarantees stability and robustness, however, it requires model formula. We employ both the actor-critic method which is a kind of reinforcement learning with minimal amount of computation to control continuous valued actions and the traditional robust control, that is, H∞ control. The proposed system was compared method with the conventional control method, that is, the actor-critic only used, through the computer simulation of controlling the angle and the position of a crane system, and the simulation result showed the effectiveness of the proposed method.
-
A Fast Optimization Method for General Binary Code Learning.
Shen, Fumin; Zhou, Xiang; Yang, Yang; Song, Jingkuan; Shen, Heng; Tao, Dacheng
2016-09-22
Hashing or binary code learning has been recognized to accomplish efficient near neighbor search, and has thus attracted broad interests in recent retrieval, vision and learning studies. One main challenge of learning to hash arises from the involvement of discrete variables in binary code optimization. While the widely-used continuous relaxation may achieve high learning efficiency, the pursued codes are typically less effective due to accumulated quantization error. In this work, we propose a novel binary code optimization method, dubbed Discrete Proximal Linearized Minimization (DPLM), which directly handles the discrete constraints during the learning process. Specifically, the discrete (thus nonsmooth nonconvex) problem is reformulated as minimizing the sum of a smooth loss term with a nonsmooth indicator function. The obtained problem is then efficiently solved by an iterative procedure with each iteration admitting an analytical discrete solution, which is thus shown to converge very fast. In addition, the proposed method supports a large family of empirical loss functions, which is particularly instantiated in this work by both a supervised and an unsupervised hashing losses, together with the bits uncorrelation and balance constraints. In particular, the proposed DPLM with a supervised `2 loss encodes the whole NUS-WIDE database into 64-bit binary codes within 10 seconds on a standard desktop computer. The proposed approach is extensively evaluated on several large-scale datasets and the generated binary codes are shown to achieve very promising results on both retrieval and classification tasks.
-
Directory of Open Access Journals (Sweden)
Supriatna Supriatna
2017-10-01
Full Text Available The purpose of this research was to know the influence of cooperative learning method (Jigsaw and TPS and personality type (extrovert and introvert toward students’ ability in scientific writing at the SMA Negeri 2 Ciamis class XII. The research used experimental method with 2 x 2 factorial design. The population was the students of class XII which consisted of 150. The sample was 57 students. The results showed that: (1 The ability to write scientific articles of students learning by cooperative learning method jigsaw model (= 65,88 is higher than students who learn by cooperative technique method of TPS (= 59,88, (2 Ability writing scientific articles of students whose extroverted personality (= 65.69 is higher than introverted students (= 60.06; (3 there is interaction between cooperative learning method and personality type to score of writing ability of scientific article (4 ability to write scientific article of extrovert student and studying with technique of Jigsaw (= 77,75 higher than extrovert student learning with cooperative learning method model of TPS (= 53,63 to score of writing ability of scientific article, (5 ability to write introverted student's scientific article and get treatment of cooperative learning method of jigsaw model (= 54,00 lower than introverted student learning TPS technique = 66,13, (6 the ability to write extroverted students' scientific articles studied with jigsaw techniques, and introverted students who studied Jigsaw techniques (= 77.75 were higher than those with introverted personality types studied by the Jigsaw technique (= 54.00 , (7 Ability to write scientific articles of students learning by cooperative techniques of TPS technique and have extrovert personality type ( = 53.63 lower than introverted students learning TPS techniques (= 66.13.
-
Listening to Our Students: Understanding How They Learn Research Methods in Geography
Keenan, Kevin; Fontaine, Danielle
2012-01-01
How undergraduate students learn research methods in geography has been understudied. Existing work has focused on course description from the instructor's perspective. This study, however, uses a grounded theory approach to allow students' voices to shape a new theory of how they themselves say that they learn research methods. Data from two…
-
Keystone Method: A Learning Paradigm in Mathematics
Siadat, M. Vali; Musial, Paul M.; Sagher, Yoram
2008-01-01
This study reports the effects of an integrated instructional program (the Keystone Method) on the students' performance in mathematics and reading, and tracks students' persistence and retention. The subject of the study was a large group of students in remedial mathematics classes at the college, willing to learn but lacking basic educational…
-
Building Customer Churn Prediction Models in Fitness Industry with Machine Learning Methods
Shan, Min
2017-01-01
With the rapid growth of digital systems, churn management has become a major focus within customer relationship management in many industries. Ample research has been conducted for churn prediction in different industries with various machine learning methods. This thesis aims to combine feature selection and supervised machine learning methods for defining models of churn prediction and apply them on fitness industry. Forward selection is chosen as feature selection methods. Support Vector ...
-
Approximate kernel competitive learning.
Wu, Jian-Sheng; Zheng, Wei-Shi; Lai, Jian-Huang
2015-03-01
Kernel competitive learning has been successfully used to achieve robust clustering. However, kernel competitive learning (KCL) is not scalable for large scale data processing, because (1) it has to calculate and store the full kernel matrix that is too large to be calculated and kept in the memory and (2) it cannot be computed in parallel. In this paper we develop a framework of approximate kernel competitive learning for processing large scale dataset. The proposed framework consists of two parts. First, it derives an approximate kernel competitive learning (AKCL), which learns kernel competitive learning in a subspace via sampling. We provide solid theoretical analysis on why the proposed approximation modelling would work for kernel competitive learning, and furthermore, we show that the computational complexity of AKCL is largely reduced. Second, we propose a pseudo-parallelled approximate kernel competitive learning (PAKCL) based on a set-based kernel competitive learning strategy, which overcomes the obstacle of using parallel programming in kernel competitive learning and significantly accelerates the approximate kernel competitive learning for large scale clustering. The empirical evaluation on publicly available datasets shows that the proposed AKCL and PAKCL can perform comparably as KCL, with a large reduction on computational cost. Also, the proposed methods achieve more effective clustering performance in terms of clustering precision against related approximate clustering approaches. Copyright © 2014 Elsevier Ltd. All rights reserved.
-
Perception of mathematics teachers on cooperative learning method in the 21st century
Taufik, Nurshahira Alwani Mohd; Maat, Siti Mistima
2017-05-01
Mathematics education is one of the branches to be mastered by students to help them compete with the upcoming challenges that are very challenging. As such, all parties should work together to help increase student achievement in Mathematics education in line with the Malaysian Education Blueprint (MEB) 2010-2025. Teaching methods play a very important role in attracting and fostering student understanding and interested in learning Mathematics. Therefore, this study was conducted to identify the perceptions of teachers in carrying out cooperative methods in the teaching and learning of mathematics. Participants of this study involving 4 teachers who teach Mathematics in primary schools around the state of Negeri Sembilan. Interviews are used as a method for gathering data. The findings indicate that cooperative methods help increasing interest and understanding in the teaching and learning of mathematics. In conclusion, the teaching methods affect the interest and understanding of students in the learning of Mathematics in the classroom.
-
Teaching of anatomical sciences: A blended learning approach.
Khalil, Mohammed K; Abdel Meguid, Eiman M; Elkhider, Ihsan A
2018-04-01
Blended learning is the integration of different learning approaches, new technologies, and activities that combine traditional face-to-face teaching methods with authentic online methodologies. Although advances in educational technology have helped to expand the selection of different pedagogies, the teaching of anatomical sciences has been challenged by implementation difficulties and other limitations. These challenges are reported to include lack of time, costs, and lack of qualified teachers. Easy access to online information and advances in technology make it possible to resolve these limitations by adopting blended learning approaches. Blended learning strategies have been shown to improve students' academic performance, motivation, attitude, and satisfaction, and to provide convenient and flexible learning. Implementation of blended learning strategies has also proved cost effective. This article provides a theoretical foundation for blended learning and proposes a validated framework for the design of blended learning activities in the teaching and learning of anatomical sciences. Clin. Anat. 31:323-329, 2018. © 2018 Wiley Periodicals, Inc. © 2018 Wiley Periodicals, Inc.
-
Optimal robustness of supervised learning from a noniterative point of view
Hu, Chia-Lun J.
1995-08-01
In most artificial neural network applications, (e.g. pattern recognition) if the dimension of the input vectors is much larger than the number of patterns to be recognized, generally, a one- layered, hard-limited perceptron is sufficient to do the recognition job. As long as the training input-output mapping set is numerically given, and as long as this given set satisfies a special linear-independency relation, the connection matrix to meet the supervised learning requirements can be solved by a noniterative, one-step, algebra method. The learning of this noniterative scheme is very fast (close to real-time learning) because the learning is one-step and noniterative. The recognition of the untrained patterns is very robust because a universal geometrical optimization process of selecting the solution can be applied to the learning process. This paper reports the theoretical foundation of this noniterative learning scheme and focuses the result at the optimal robustness analysis. A real-time character recognition scheme is then designed along this line. This character recognition scheme will be used (in a movie presentation) to demonstrate the experimental results of some theoretical parts reported in this paper.
-
Group-theoretical method in the many-beam theory of electron diffraction
International Nuclear Information System (INIS)
Kogiso, Motokazu; Takahashi, Hidewo.
1977-01-01
A group-theoretical method is developed for the many-beam dynamical theory of the symmetric Laue case. When the incident wave is directed so that the Laue point lies on a symmetric position in the reciprocal lattice, the dispersion matrix in the fundamental equation can be reduced to a block diagonal form. The transformation matrix is composed of column vectors belonging to irreducible representations of the group of the incident wave vector. Without performing reduction, the reduced form of the dispersion matrix is determined from characters of representations. Practical application is made to the case of symmorphic crystals, where general reduced forms and all solvable examples are given in terms of some geometrical factors of reciprocal lattice arrangements. (auth.)
-
Mathematics Education as a Practice: A Theoretical Position
Grootenboer, Peter; Edwards-Groves, Christine
2013-01-01
In this paper we will examine mathematics education using practice theory. We outline the theoretical and philosophical ideas that have been developed, and in particular, we discuss the "sayings," "doings," and "relatings" inherent in the teaching and learning practices of mathematics education. This theorising is…
-
Python for probability, statistics, and machine learning
Unpingco, José
2016-01-01
This book covers the key ideas that link probability, statistics, and machine learning illustrated using Python modules in these areas. The entire text, including all the figures and numerical results, is reproducible using the Python codes and their associated Jupyter/IPython notebooks, which are provided as supplementary downloads. The author develops key intuitions in machine learning by working meaningful examples using multiple analytical methods and Python codes, thereby connecting theoretical concepts to concrete implementations. Modern Python modules like Pandas, Sympy, and Scikit-learn are applied to simulate and visualize important machine learning concepts like the bias/variance trade-off, cross-validation, and regularization. Many abstract mathematical ideas, such as convergence in probability theory, are developed and illustrated with numerical examples. This book is suitable for anyone with an undergraduate-level exposure to probability, statistics, or machine learning and with rudimentary knowl...
-
Reframing Photovoice to Boost Its Potential for Learning Research
Directory of Open Access Journals (Sweden)
Lucian Ciolan
2017-04-01
Full Text Available Visual methods are not new within education research field, but they are certainly an innovative approach, especially in higher education where students’ voice is understood as a central need. In this positional article, the authors intend to accomplish two key objectives. First, the article aims to emphasize that visual method, especially photovoice, can be enriching for studying the ways students engage in learning activities and support authentic conversations about how learning takes place and what students are thinking about this process (metacognition. The second objective is to set theoretical and methodological grounds to apply visually based methods such as photovoice and bubble dialogue in education research, particularly in learning research area. The considerations regarding specific methodological aspects are based on the discussion of a study conducted by using photovoice methodology. The authors suggest that participatory analysis and particularly interpretative phenomenological analysis are appropriate to complete the process of data analysis. The article, therefore, contributes to expanding knowledge about specific visual methods and set the ground for methodological innovation in learning research.
-
dr. Donald Ropes
2014-01-01
Purpose – To illustrate the possibilities of implementing intergenerational learning as a strategy for promoting older worker learning and development. Design/methodology/approach – Review of literature. Findings – Intergenerational learning is theoretically a natural and effective way for
-
Mobile Learning for Higher Education in Problem-Based Learning Environments
DEFF Research Database (Denmark)
Rongbutsri, Nikorn
2011-01-01
This paper describes the PhD project on Mobile Learning for Higher Education in Problem-Based Learning Environment which aims to understand how students gain benefit from using mobile devices in the aspect of project work collaboration. It demonstrates research questions, theoretical perspective...
-
Sultan, A. Z.; Hamzah, N.; Rusdi, M.
2018-01-01
The implementation of concept attainment method based on simulation was used to increase student’s interest in the subjects Engineering of Mechanics in second semester of academic year 2016/2017 in Manufacturing Engineering Program, Department of Mechanical PNUP. The result of the implementation of this learning method shows that there is an increase in the students’ learning interest towards the lecture material which is summarized in the form of interactive simulation CDs and teaching materials in the form of printed books and electronic books. From the implementation of achievement method of this simulation based concept, it is noted that the increase of student participation in the presentation and discussion as well as the deposit of individual assignment of significant student. With the implementation of this method of learning the average student participation reached 89%, which before the application of this learning method only reaches an average of 76%. And also with previous learning method, for exam achievement of A-grade under 5% and D-grade above 8%. After the implementation of the new learning method (simulation based-concept attainment method) the achievement of Agrade has reached more than 30% and D-grade below 1%.
-
Theoretical Foundations for Enhancing Social Connectedness in Online Learning Environments
Slagter van Tryon, Patricia J.; Bishop, M. J.
2009-01-01
Group social structure provides a comfortable and predictable context for interaction in learning environments. Students in face-to-face learning environments process social information about others in order to assess traits, predict behaviors, and determine qualifications for assuming particular responsibilities within a group. In online learning…
-
A Pharmacy Preregistration Course Using Online Teaching and Learning Methods
McDowell, Jenny; Marriott, Jennifer L.; Calandra, Angela; Duncan, Gregory
2009-01-01
Objective To design and evaluate a preregistration course utilizing asynchronous online learning as the primary distance education delivery method. Design Online course components including tutorials, quizzes, and moderated small-group asynchronous case-based discussions were implemented. Online delivery was supplemented with self-directed and face-to-face learning. Assessment Pharmacy graduates who had completed the course in 2004 and 2005 were surveyed. The majority felt they had benefited from all components of the course, and that online delivery provided benefits including increased peer support, shared learning, and immediate feedback on performance. A majority of the first cohort reported that the workload associated with asynchronous online discussions was too great. The course was altered in 2005 to reduce the online component. Participant satisfaction improved, and most felt that the balance of online to face-to-face delivery was appropriate. Conclusion A new pharmacy preregistration course was successfully implemented. Online teaching and learning was well accepted and appeared to deliver benefits over traditional distance education methods once workload issues were addressed. PMID:19777092
-
Verhoeven, Thibault; Schmid, Konstantin; Müller, Klaus-Robert; Tangermann, Michael; Kindermans, Pieter-Jan
2017-01-01
Objective Using traditional approaches, a brain-computer interface (BCI) requires the collection of calibration data for new subjects prior to online use. Calibration time can be reduced or eliminated e.g., by subject-to-subject transfer of a pre-trained classifier or unsupervised adaptive classification methods which learn from scratch and adapt over time. While such heuristics work well in practice, none of them can provide theoretical guarantees. Our objective is to modify an event-related potential (ERP) paradigm to work in unison with the machine learning decoder, and thus to achieve a reliable unsupervised calibrationless decoding with a guarantee to recover the true class means. Method We introduce learning from label proportions (LLP) to the BCI community as a new unsupervised, and easy-to-implement classification approach for ERP-based BCIs. The LLP estimates the mean target and non-target responses based on known proportions of these two classes in different groups of the data. We present a visual ERP speller to meet the requirements of LLP. For evaluation, we ran simulations on artificially created data sets and conducted an online BCI study with 13 subjects performing a copy-spelling task. Results Theoretical considerations show that LLP is guaranteed to minimize the loss function similar to a corresponding supervised classifier. LLP performed well in simulations and in the online application, where 84.5% of characters were spelled correctly on average without prior calibration. Significance The continuously adapting LLP classifier is the first unsupervised decoder for ERP BCIs guaranteed to find the optimal decoder. This makes it an ideal solution to avoid tedious calibration sessions. Additionally, LLP works on complementary principles compared to existing unsupervised methods, opening the door for their further enhancement when combined with LLP. PMID:28407016
-
Information-Theoretic Properties of Auditory Sequences Dynamically Influence Expectation and Memory.
Agres, Kat; Abdallah, Samer; Pearce, Marcus
2018-01-01
A basic function of cognition is to detect regularities in sensory input to facilitate the prediction and recognition of future events. It has been proposed that these implicit expectations arise from an internal predictive coding model, based on knowledge acquired through processes such as statistical learning, but it is unclear how different types of statistical information affect listeners' memory for auditory stimuli. We used a combination of behavioral and computational methods to investigate memory for non-linguistic auditory sequences. Participants repeatedly heard tone sequences varying systematically in their information-theoretic properties. Expectedness ratings of tones were collected during three listening sessions, and a recognition memory test was given after each session. Information-theoretic measures of sequential predictability significantly influenced listeners' expectedness ratings, and variations in these properties had a significant impact on memory performance. Predictable sequences yielded increasingly better memory performance with increasing exposure. Computational simulations using a probabilistic model of auditory expectation suggest that listeners dynamically formed a new, and increasingly accurate, implicit cognitive model of the information-theoretic structure of the sequences throughout the experimental session. Copyright © 2017 Cognitive Science Society, Inc.
-
A Photometric Machine-Learning Method to Infer Stellar Metallicity
Miller, Adam A.
2015-01-01
Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..
-
DL-ReSuMe: A Delay Learning-Based Remote Supervised Method for Spiking Neurons.
Taherkhani, Aboozar; Belatreche, Ammar; Li, Yuhua; Maguire, Liam P
2015-12-01
Recent research has shown the potential capability of spiking neural networks (SNNs) to model complex information processing in the brain. There is biological evidence to prove the use of the precise timing of spikes for information coding. However, the exact learning mechanism in which the neuron is trained to fire at precise times remains an open problem. The majority of the existing learning methods for SNNs are based on weight adjustment. However, there is also biological evidence that the synaptic delay is not constant. In this paper, a learning method for spiking neurons, called delay learning remote supervised method (DL-ReSuMe), is proposed to merge the delay shift approach and ReSuMe-based weight adjustment to enhance the learning performance. DL-ReSuMe uses more biologically plausible properties, such as delay learning, and needs less weight adjustment than ReSuMe. Simulation results have shown that the proposed DL-ReSuMe approach achieves learning accuracy and learning speed improvements compared with ReSuMe.
-
Arabic Supervised Learning Method Using N-Gram
Sanan, Majed; Rammal, Mahmoud; Zreik, Khaldoun
2008-01-01
Purpose: Recently, classification of Arabic documents is a real problem for juridical centers. In this case, some of the Lebanese official journal documents are classified, and the center has to classify new documents based on these documents. This paper aims to study and explain the useful application of supervised learning method on Arabic texts…
-
Directory of Open Access Journals (Sweden)
Vladislav V. Bulgakov
2018-03-01
Full Text Available Features of training in higher educational institutions of system of EMERCOM of Russia demand introduction of the new educational techniques and the technical means directed on intensification of educational process, providing an opportunity of preparation of cadets at any time in the independent mode and improving quality of their theoretical knowledge. The authors have developed a structural and methodological model of increasing the level of theoretical training of cadets using information and communication technologies. The proposed structural and methodological model that includes elements to stimulate and enhance cognitive activity, allows you to generate the trajectory of theoretical training of cadets for the entire period of study at the University, to organize a systematic independent work, objective, current and final control of theoretical knowledge. The structural and methodological model for improving the level of theoretical training consists of three main elements: the base of theoretical questions, functional modules "teacher" and "cadet". The basis of the structural and methodological model of increasing the level of theoretical training of cadets is the base of theoretical issues, developed in all disciplines specialty 20.05.01 – fire safety. The functional module "teacher" allows you to create theoretical questions of various kinds, edit questions and delete them from the database if necessary, as well as create tests and monitor their implementation. The functional module "cadet" provides ample opportunities for theoretical training through independent work, testing for current and final control, the implementation of the game form of training in the form of a duel, as well as for the formation of the results of the cadets in the form of statistics and rankings. Structural and methodical model of increasing the level of theoretical training of cadets is implemented in practice in the form of a multi-level automated system
-
Group theoretical methods in physics. [Tuebingen, July 18-22, 1977
Energy Technology Data Exchange (ETDEWEB)
Kramer, P; Rieckers, A
1978-01-01
This volume comprises the proceedings of the 6th International Colloquium on Group Theoretical Methods in Physics, held at Tuebingen in July 1977. Invited papers were presented on the following topics: supersymmetry and graded Lie algebras; concepts of order and disorder arising from molecular physics; symplectic structures and many-body physics; symmetry breaking in statistical mechanics and field theory; automata and systems as examples of applied (semi-) group theory; renormalization group; and gauge theories. Summaries are given of the contributed papers, which can be grouped as follows: supersymmetry, symmetry in particles and relativistic physics; symmetry in molecular and solid state physics; broken symmetry and phase transitions; structure of groups and dynamical systems; representations of groups and Lie algebras; and general symmetries, quantization. Those individual papers in scope for the TIC data base are being entered from ATOMINDEX tapes. (RWR)
-
Evaluation Methods on Usability of M-Learning Environments
Directory of Open Access Journals (Sweden)
Teresa Magal-Royo
2007-10-01
Full Text Available Nowadays there are different evaluation methods focused in the assessment of the usability of telematic methods. The assessment of 3rd generation web environments evaluates the effectiveness and usability of application with regard to the user needs. Wireless usability and, specifically in mobile phones, is concentrated in the validation of the features and tools management using conventional interactive environments. There is not a specific and suitable criterion to evaluate created environments and m-learning platforms, where the restricted and sequential representation is a fundamental aspect to be considered.The present paper exposes the importance of the conventional usability methods to verify both: the employed contents in wireless formats, and the possible interfaces from the conception phases, to the validations of the platform with such characteristics.The development of usability adapted inspection could be complemented with the Remote’s techniques of usability testing, which are being carried out these days in the mobile devices field and which pointed out the need to apply common criteria in the validation of non-located learning scenarios.
-
Williams van Rooij, Shahron
2007-01-01
This study examined the impact of two Problem-Based Learning (PBL) approaches on knowledge transfer, problem-solving self-efficacy, and perceived learning gains among four intact classes of adult learners engaged in a group project in an online undergraduate business research methods course. With two of the classes using a text-only PBL workbook…
-
A Survey of Quantum Learning Theory
Arunachalam, Srinivasan; de Wolf, Ronald
2017-01-01
This paper surveys quantum learning theory: the theoretical aspects of machine learning using quantum computers. We describe the main results known for three models of learning: exact learning from membership queries, and Probably Approximately Correct (PAC) and agnostic learning from classical or quantum examples.
-
Research progress in machine learning methods for gene-gene interaction detection.
Peng, Zhe-Ye; Tang, Zi-Jun; Xie, Min-Zhu
2018-03-20
Complex diseases are results of gene-gene and gene-environment interactions. However, the detection of high-dimensional gene-gene interactions is computationally challenging. In the last two decades, machine-learning approaches have been developed to detect gene-gene interactions with some successes. In this review, we summarize the progress in research on machine learning methods, as applied to gene-gene interaction detection. It systematically examines the principles and limitations of the current machine learning methods used in genome wide association studies (GWAS) to detect gene-gene interactions, such as neural networks (NN), random forest (RF), support vector machines (SVM) and multifactor dimensionality reduction (MDR), and provides some insights on the future research directions in the field.
-
Hommes, J.; Van den Bossche, P.; de Grave, W.; Bos, G.; Schuwirth, L.; Scherpbier, A.
2014-01-01
Little is known how time influences collaborative learning groups in medical education. Therefore a thorough exploration of the development of learning processes over time was undertaken in an undergraduate PBL curriculum over 18 months. A mixed-methods triangulation design was used. First, the quantitative study measured how various learning…
-
Distributed learning process: principles of design and implementation
Directory of Open Access Journals (Sweden)
G. N. Boychenko
2016-01-01
Full Text Available At the present stage, broad information and communication technologies (ICT usage in educational practices is one of the leading trends of global education system development. This trend has led to the instructional interaction models transformation. Scientists have developed the theory of distributed cognition (Salomon, G., Hutchins, E., and distributed education and training (Fiore, S. M., Salas, E., Oblinger, D. G., Barone, C. A., Hawkins, B. L.. Educational process is based on two separated in time and space sub-processes of learning and teaching which are aimed at the organization of fl exible interactions between learners, teachers and educational content located in different non-centralized places.The purpose of this design research is to fi nd a solution for the problem of formalizing distributed learning process design and realization that is signifi cant in instructional design. The solution to this problem should take into account specifi cs of distributed interactions between team members, which becomes collective subject of distributed cognition in distributed learning process. This makes it necessary to design roles and functions of the individual team members performing distributed educational activities. Personal educational objectives should be determined by decomposition of team objectives into functional roles of its members with considering personal and learning needs and interests of students.Theoretical and empirical methods used in the study: theoretical analysis of philosophical, psychological, and pedagogical literature on the issue, analysis of international standards in the e-learning domain; exploration on practical usage of distributed learning in academic and corporate sectors; generalization, abstraction, cognitive modelling, ontology engineering methods.Result of the research is methodology for design and implementation of distributed learning process based on the competency approach. Methodology proposed by
-
Interest in Currency Trading Learning – Preferred Methods and Motivational Factors
Directory of Open Access Journals (Sweden)
Pintar Rok
2016-02-01
Full Text Available Background and purpose: This paper analyzes the interest of potential users for learning in the field of currency trading or foreign exchange (forex, FX. The purpose of our article is a to present currency trading, b to present different options, methods and learning approaches to educating in forex, c to present the research results discovering the interest of potential users for learning in the field of currency trading.
-
The Impact of Organisational Learning on Organisational Performance
Directory of Open Access Journals (Sweden)
Anna Zgrzywa-Ziemak
2015-12-01
Full Text Available Purpose: The aim of this article is to analyse the theoretical views and results of empirical research concerning the relation between organisational learning (OL and organisational performance (OP. Methodology: The study was carried out through extensive literature research, including relevant literature review from databases such as ProQuest, Elsevier, Emerald and EBSCO (the phrases: “organisational learning”, “learning organisation” and “organisational performance” were searched in the keywords, titles or abstracts. Findings: From a theoretical point of view, the relation between OL and OP is neither obvious nor clear, but the analysis of the empirical studies allows one to assume that OL has an essential impact on OP. However, differences in the strength of the relation were shown and some contradictions related to the presence of the relation between OL and selected (mostly financial performance aspects identified. Furthermore, the article discusses the significant differences and inconsistencies in the methods of measuring OL, measuring OP, selecting contextual factors and adopted methods of data analysis. Implications: Inconsistencies and gaps found in the studies of the relationship between OL and OP made it possible to designate the direction for promising further research. Value: The article presents valuable insight through its in-depth, critical analysis of the organisational learning and organisational outcomes. First and foremost, this indicates that the formula of the previous empirical studies does not allow for the development of precise solutions pertaining to organisational learning management for the benefit of OP improvement.
-
Energy Technology Data Exchange (ETDEWEB)
Constantin, A., E-mail: adrian.constantin@kcl.ac.uk [Department of Mathematics, King' s College London, Strand, London WC2R 2LS (United Kingdom); Faculty of Mathematics, University of Vienna, Oskar-Morgenstern-Platz 1, 1090 Vienna (Austria); Johnson, R.S., E-mail: r.s.johnson@ncl.ac.uk [School of Mathematics & Statistics, Newcastle University, Newcastle upon Tyne NE1 7RU (United Kingdom)
2016-09-07
Highlights: • Systematic theoretical methods in studies of equatorial ocean dynamics. • Linear wave-current interactions in stratified flows. • Exact solutions – Kelvin waves, azimuthal non-uniform currents. • Three-dimensional nonlinear currents. • Hamiltonian formulation for the governing equations and for structure-preserving/enhancing approximations. - Abstract: This essay is a commentary on the pivotal role of systematic theoretical methods in physical oceanography. At some level, there will always be a conflict between theory and experiment/data collection: Which is pre-eminent? Which should come first? This issue appears to be particularly marked in physical oceanography, to the extreme detriment of the development of the subject. It is our contention that the classical theory of fluids, coupled with methods from the theory of differential equations, can play a significant role in carrying the subject, and our understanding, forward. We outline the philosophy behind a systematic theoretical approach, highlighting some aspects of equatorial ocean dynamics where these methods have already been successful, paving the way for much more in the future and leading, we expect, to the better understanding of this and many other types of ocean flow. We believe that the ideas described here promise to reveal a rich and beautiful dynamical structure.
-
Spatial Visualization Learning in Engineering: Traditional Methods vs. a Web-Based Tool
Pedrosa, Carlos Melgosa; Barbero, Basilio Ramos; Miguel, Arturo Román
2014-01-01
This study compares an interactive learning manager for graphic engineering to develop spatial vision (ILMAGE_SV) to traditional methods. ILMAGE_SV is an asynchronous web-based learning tool that allows the manipulation of objects with a 3D viewer, self-evaluation, and continuous assessment. In addition, student learning may be monitored, which…
-
Collaborations in Open Learning Environments
Spoelstra, Howard
2015-01-01
This thesis researches automated services for professionals aiming at starting collaborative learning projects in open learning environments, such as MOOCs. It investigates the theoretical backgrounds of team formation for collaborative learning. Based on the outcomes, a model is developed
-
Learning by Designing Interview Methods in Special Education
DEFF Research Database (Denmark)
Jönsson, Lise Høgh
2017-01-01
, and people with learning disabilities worked together to develop five new visual and digital methods for interviewing in special education. Thereby not only enhancing the students’ competences, knowledge and proficiency in innovation and research, but also proposing a new teaching paradigm for university...
-
Studying depression using imaging and machine learning methods
Patel, Meenal J.; Khalaf, Alexander; Aizenstein, Howard J.
2015-01-01
Depression is a complex clinical entity that can pose challenges for clinicians regarding both accurate diagnosis and effective timely treatment. These challenges have prompted the development of multiple machine learning methods to help improve the management of this disease. These methods utilize anatomical and physiological data acquired from neuroimaging to create models that can identify depressed patients vs. non-depressed patients and predict treatment outcomes. This article (1) presen...
-
Directory of Open Access Journals (Sweden)
Hao Li
2016-01-01
Full Text Available 1,1,1,2,3,3,3-Heptafluoropropane (R227ea is a good refrigerant that reduces greenhouse effects and ozone depletion. In practical applications, we usually have to know the compressed liquid densities at different temperatures and pressures. However, the measurement requires a series of complex apparatus and operations, wasting too much manpower and resources. To solve these problems, here, Song and Mason equation, support vector machine (SVM, and artificial neural networks (ANNs were used to develop theoretical and machine learning models, respectively, in order to predict the compressed liquid densities of R227ea with only the inputs of temperatures and pressures. Results show that compared with the Song and Mason equation, appropriate machine learning models trained with precise experimental samples have better predicted results, with lower root mean square errors (RMSEs (e.g., the RMSE of the SVM trained with data provided by Fedele et al. [1] is 0.11, while the RMSE of the Song and Mason equation is 196.26. Compared to advanced conventional measurements, knowledge-based machine learning models are proved to be more time-saving and user-friendly.
-
Fast Low-Rank Shared Dictionary Learning for Image Classification.
Tiep Huu Vu; Monga, Vishal
2017-11-01
Despite the fact that different objects possess distinct class-specific features, they also usually share common patterns. This observation has been exploited partially in a recently proposed dictionary learning framework by separating the particularity and the commonality (COPAR). Inspired by this, we propose a novel method to explicitly and simultaneously learn a set of common patterns as well as class-specific features for classification with more intuitive constraints. Our dictionary learning framework is hence characterized by both a shared dictionary and particular (class-specific) dictionaries. For the shared dictionary, we enforce a low-rank constraint, i.e., claim that its spanning subspace should have low dimension and the coefficients corresponding to this dictionary should be similar. For the particular dictionaries, we impose on them the well-known constraints stated in the Fisher discrimination dictionary learning (FDDL). Furthermore, we develop new fast and accurate algorithms to solve the subproblems in the learning step, accelerating its convergence. The said algorithms could also be applied to FDDL and its extensions. The efficiencies of these algorithms are theoretically and experimentally verified by comparing their complexities and running time with those of other well-known dictionary learning methods. Experimental results on widely used image data sets establish the advantages of our method over the state-of-the-art dictionary learning methods.
-
Minimax bounds for active learning
Castro, R.M.; Nowak, R.
2008-01-01
This paper analyzes the potential advantages and theoretical challenges of "active learning" algorithms. Active learning involves sequential sampling procedures that use information gleaned from previous samples in order to focus the sampling and accelerate the learning process relative to "passive
-
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 ...
-
Comparative Analysis of Kernel Methods for Statistical Shape Learning
National Research Council Canada - National Science Library
Rathi, Yogesh; Dambreville, Samuel; Tannenbaum, Allen
2006-01-01
.... In this work, we perform a comparative analysis of shape learning techniques such as linear PCA, kernel PCA, locally linear embedding and propose a new method, kernelized locally linear embedding...
-
Sunspot drawings handwritten character recognition method based on deep learning
Zheng, Sheng; Zeng, Xiangyun; Lin, Ganghua; Zhao, Cui; Feng, Yongli; Tao, Jinping; Zhu, Daoyuan; Xiong, Li
2016-05-01
High accuracy scanned sunspot drawings handwritten characters recognition is an issue of critical importance to analyze sunspots movement and store them in the database. This paper presents a robust deep learning method for scanned sunspot drawings handwritten characters recognition. The convolution neural network (CNN) is one algorithm of deep learning which is truly successful in training of multi-layer network structure. CNN is used to train recognition model of handwritten character images which are extracted from the original sunspot drawings. We demonstrate the advantages of the proposed method on sunspot drawings provided by Chinese Academy Yunnan Observatory and obtain the daily full-disc sunspot numbers and sunspot areas from the sunspot drawings. The experimental results show that the proposed method achieves a high recognition accurate rate.
-
APA's Learning Objectives for Research Methods and Statistics in Practice: A Multimethod Analysis
Tomcho, Thomas J.; Rice, Diana; Foels, Rob; Folmsbee, Leah; Vladescu, Jason; Lissman, Rachel; Matulewicz, Ryan; Bopp, Kara
2009-01-01
Research methods and statistics courses constitute a core undergraduate psychology requirement. We analyzed course syllabi and faculty self-reported coverage of both research methods and statistics course learning objectives to assess the concordance with APA's learning objectives (American Psychological Association, 2007). We obtained a sample of…
-
Learn Quantum Mechanics with Haskell
Directory of Open Access Journals (Sweden)
Scott N. Walck
2016-11-01
Full Text Available To learn quantum mechanics, one must become adept in the use of various mathematical structures that make up the theory; one must also become familiar with some basic laboratory experiments that the theory is designed to explain. The laboratory ideas are naturally expressed in one language, and the theoretical ideas in another. We present a method for learning quantum mechanics that begins with a laboratory language for the description and simulation of simple but essential laboratory experiments, so that students can gain some intuition about the phenomena that a theory of quantum mechanics needs to explain. Then, in parallel with the introduction of the mathematical framework on which quantum mechanics is based, we introduce a calculational language for describing important mathematical objects and operations, allowing students to do calculations in quantum mechanics, including calculations that cannot be done by hand. Finally, we ask students to use the calculational language to implement a simplified version of the laboratory language, bringing together the theoretical and laboratory ideas.
-
A Photometric Machine-Learning Method to Infer Stellar Metallicity
Miller, Adam A.
2015-01-01
Following its formation, a star's metal content is one of the few factors that can significantly alter its evolution. Measurements of stellar metallicity ([Fe/H]) typically require a spectrum, but spectroscopic surveys are limited to a few x 10(exp 6) targets; photometric surveys, on the other hand, have detected > 10(exp 9) stars. I present a new machine-learning method to predict [Fe/H] from photometric colors measured by the Sloan Digital Sky Survey (SDSS). The training set consists of approx. 120,000 stars with SDSS photometry and reliable [Fe/H] measurements from the SEGUE Stellar Parameters Pipeline (SSPP). For bright stars (g' machine-learning method is similar to the scatter in [Fe/H] measurements from low-resolution spectra..
-
Abbaszadeh, Abbas; Sabeghi, Hakimeh; Borhani, Fariba; Heydari, Abbas
2011-01-01
Accurate recording of the nursing care indicates the care performance and its quality, so that, any failure in documentation can be a reason for inadequate patient care. Therefore, improving nurses' skills in this field using effective educational methods is of high importance. Since traditional teaching methods are not suitable for communities with rapid knowledge expansion and constant changes, e-learning methods can be a viable alternative. To show the importance of e-learning methods on nurses' care reporting skills, this study was performed to compare the e-learning methods with the traditional instructor-led methods. This was a quasi-experimental study aimed to compare the effect of two teaching methods (e-learning and lecture) on nursing documentation and examine the differences in acquiring competency on documentation between nurses who participated in the e-learning (n = 30) and nurses in a lecture group (n = 31). The results of the present study indicated that statistically there was no significant difference between the two groups. The findings also revealed that statistically there was no significant correlation between the two groups toward demographic variables. However, we believe that due to benefits of e-learning against traditional instructor-led method, and according to their equal effect on nurses' documentation competency, it can be a qualified substitute for traditional instructor-led method. E-learning as a student-centered method as well as lecture method equally promote competency of the nurses on documentation. Therefore, e-learning can be used to facilitate the implementation of nursing educational programs.
-
Teaching-learning: stereoscopic 3D versus Traditional methods in Mexico City.
Mendoza Oropeza, Laura; Ortiz Sánchez, Ricardo; Ojeda Villagómez, Raúl
2015-01-01
In the UNAM Faculty of Odontology, we use a stereoscopic 3D teaching method that has grown more common in the last year, which makes it important to know whether students can learn better with this strategy. The objective of the study is to know, if the 4th year students of the bachelor's degree in dentistry learn more effectively with the use of stereoscopic 3D than the traditional method in Orthodontics. first, we selected the course topics, to be used for both methods; the traditional method using projection of slides and for the stereoscopic third dimension, with the use of videos in digital stereo projection (seen through "passive" polarized 3D glasses). The main topic was supernumerary teeth, including and diverted from their guide eruption. Afterwards we performed an exam on students, containing 24 items, validated by expert judgment in Orthodontics teaching. The results of the data were compared between the two educational methods for determined effectiveness using the model before and after measurement with the statistical package SPSS 20 version. The results presented for the 9 groups of undergraduates in dentistry, were collected with a total of 218 students for 3D and traditional methods, we found in a traditional method a mean 4.91, SD 1.4752 in the pretest and X=6.96, SD 1.26622, St Error 0.12318 for the posttest. The 3D method had a mean 5.21, SD 1.996779 St Error 0.193036 for the pretest X= 7.82, SD =0.963963, St Error 0.09319 posttest; the analysis of Variance between groups F= 5.60 Prob > 0.0000 and Bartlett's test for equal variances 21.0640 Prob > chi2 = 0.007. These results show that the student's learning in 3D means a significant improvement as compared to the traditional teaching method and having a strong association between the two methods. The findings suggest that the stereoscopic 3D method lead to improved student learning compared to traditional teaching.
-
Metric Learning Method Aided Data-Driven Design of Fault Detection Systems
Directory of Open Access Journals (Sweden)
Guoyang Yan
2014-01-01
Full Text Available Fault detection is fundamental to many industrial applications. With the development of system complexity, the number of sensors is increasing, which makes traditional fault detection methods lose efficiency. Metric learning is an efficient way to build the relationship between feature vectors with the categories of instances. In this paper, we firstly propose a metric learning-based fault detection framework in fault detection. Meanwhile, a novel feature extraction method based on wavelet transform is used to obtain the feature vector from detection signals. Experiments on Tennessee Eastman (TE chemical process datasets demonstrate that the proposed method has a better performance when comparing with existing methods, for example, principal component analysis (PCA and fisher discriminate analysis (FDA.
-
Directory of Open Access Journals (Sweden)
Philippe Burlina
Full Text Available To evaluate the use of ultrasound coupled with machine learning (ML and deep learning (DL techniques for automated or semi-automated classification of myositis.Eighty subjects comprised of 19 with inclusion body myositis (IBM, 14 with polymyositis (PM, 14 with dermatomyositis (DM, and 33 normal (N subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally were acquired. We considered three problems of classification including (A normal vs. affected (DM, PM, IBM; (B normal vs. IBM patients; and (C IBM vs. other types of myositis (DM or PM. We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification.The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A, 86.6% ± 2.4% for (B and 74.8% ± 3.9% for (C, while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A, 84.3% ± 2.3% for (B and 68.9% ± 2.5% for (C.This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.
-
Burlina, Philippe; Billings, Seth; Joshi, Neil; Albayda, Jemima
2017-01-01
To evaluate the use of ultrasound coupled with machine learning (ML) and deep learning (DL) techniques for automated or semi-automated classification of myositis. Eighty subjects comprised of 19 with inclusion body myositis (IBM), 14 with polymyositis (PM), 14 with dermatomyositis (DM), and 33 normal (N) subjects were included in this study, where 3214 muscle ultrasound images of 7 muscles (observed bilaterally) were acquired. We considered three problems of classification including (A) normal vs. affected (DM, PM, IBM); (B) normal vs. IBM patients; and (C) IBM vs. other types of myositis (DM or PM). We studied the use of an automated DL method using deep convolutional neural networks (DL-DCNNs) for diagnostic classification and compared it with a semi-automated conventional ML method based on random forests (ML-RF) and "engineered" features. We used the known clinical diagnosis as the gold standard for evaluating performance of muscle classification. The performance of the DL-DCNN method resulted in accuracies ± standard deviation of 76.2% ± 3.1% for problem (A), 86.6% ± 2.4% for (B) and 74.8% ± 3.9% for (C), while the ML-RF method led to accuracies of 72.3% ± 3.3% for problem (A), 84.3% ± 2.3% for (B) and 68.9% ± 2.5% for (C). This study demonstrates the application of machine learning methods for automatically or semi-automatically classifying inflammatory muscle disease using muscle ultrasound. Compared to the conventional random forest machine learning method used here, which has the drawback of requiring manual delineation of muscle/fat boundaries, DCNN-based classification by and large improved the accuracies in all classification problems while providing a fully automated approach to classification.
-
To have or to learn? The effects of materialism on British and Chinese children's learning
Ku, L.; Dittmar, H.; Banerjee, R.
2014-01-01
The file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link. This article presents a systematic attempt to examine the associations of materialism with learning in 9- to 11-year-old children in 2 countries of similar economic development but different cultural heritage. Using cross-sectional, longitudinal, and experimental methods, we test a theoretically driven model of associations among materialism, l...
-
A deep learning method for lincRNA detection using auto-encoder algorithm.
Yu, Ning; Yu, Zeng; Pan, Yi
2017-12-06
RNA sequencing technique (RNA-seq) enables scientists to develop novel data-driven methods for discovering more unidentified lincRNAs. Meantime, knowledge-based technologies are experiencing a potential revolution ignited by the new deep learning methods. By scanning the newly found data set from RNA-seq, scientists have found that: (1) the expression of lincRNAs appears to be regulated, that is, the relevance exists along the DNA sequences; (2) lincRNAs contain some conversed patterns/motifs tethered together by non-conserved regions. The two evidences give the reasoning for adopting knowledge-based deep learning methods in lincRNA detection. Similar to coding region transcription, non-coding regions are split at transcriptional sites. However, regulatory RNAs rather than message RNAs are generated. That is, the transcribed RNAs participate the biological process as regulatory units instead of generating proteins. Identifying these transcriptional regions from non-coding regions is the first step towards lincRNA recognition. The auto-encoder method achieves 100% and 92.4% prediction accuracy on transcription sites over the putative data sets. The experimental results also show the excellent performance of predictive deep neural network on the lincRNA data sets compared with support vector machine and traditional neural network. In addition, it is validated through the newly discovered lincRNA data set and one unreported transcription site is found by feeding the whole annotated sequences through the deep learning machine, which indicates that deep learning method has the extensive ability for lincRNA prediction. The transcriptional sequences of lincRNAs are collected from the annotated human DNA genome data. Subsequently, a two-layer deep neural network is developed for the lincRNA detection, which adopts the auto-encoder algorithm and utilizes different encoding schemes to obtain the best performance over intergenic DNA sequence data. Driven by those newly
-
The socio-materiality of learning practices and implications for the field of learning technology
Directory of Open Access Journals (Sweden)
Aditya Johri
2011-12-01
Full Text Available Although the use of digital information technologies in education has becomecommonplace, there are few, if any, central guiding frameworks or theories thatexplicate the relationship between technology and learning practices. In thispaper, I argue that such a theoretical framework can assist scholars and practitionersalike by working as a conduit to study and design learning technologies.Towards this goal, I propose socio-materiality as a key theoretical construct withvaluable insights and implications for the field of learning technology. Sociomaterialityhelps balance the disproportionate attention given to either the socialimplications of technology use or the material aspects of technology design.Furthermore, I forward ‘socio-material bricolage' as a useful analytical frameworkto examine and design technology-infused learning environments. I illustratethe value of the framework by applying it to three case studies of formaland informal technology-based learning.
-
Cameron, Leanne
2017-01-01
This paper reports on the learning designs, teaching methods and activities most commonly employed within the disciplines in six universities in Australia. The study sought to establish if there were significant differences between the disciplines in learning designs, teaching methods and teaching activities in the current Australian context, as…
-
Slussareff, Michaela; Braad, Eelco; Wilkinson, Philip; Strååt, Björn; Dörner, Ralf; Göbel, Stefan; Kickmeier-Rust, Michael; Masuch, Maic; Zweig, Katharina
This chapter discusses educational aspects and possibilities of serious games. For researchers as well as game designers we describe key learning theories to ground their work in theoretical framework. We draw on recent metareviews to offer an exhaustive inventory of known learning and affective
-
Conditions for Productive Learning in Network Learning Environments
DEFF Research Database (Denmark)
Ponti, M.; Dirckinck-Holmfeld, Lone; Lindström, B.
2004-01-01
are designed without a deep understanding of the pedagogical, communicative and collaborative conditions embedded in networked learning. Despite the existence of good theoretical views pointing to a social understanding of learning, rather than a traditional individualistic and information processing approach......The Kaleidoscope1 Jointly Executed Integrating Research Project (JEIRP) on Conditions for Productive Networked Learning Environments is developing and elaborating conceptual understandings of Computer Supported Collaborative Learning (CSCL) emphasizing the use of cross-cultural comparative......: Pedagogical design and the dialectics of the digital artefacts, the concept of collaboration, ethics/trust, identity and the role of scaffolding of networked learning environments. The JEIRP is motivated by the fact that many networked learning environments in various European educational settings...
-
Learning Unknown Structure in CRFs via Adaptive Gradient Projection Method
Directory of Open Access Journals (Sweden)
Wei Xue
2016-08-01
Full Text Available We study the problem of fitting probabilistic graphical models to the given data when the structure is not known. More specifically, we focus on learning unknown structure in conditional random fields, especially learning both the structure and parameters of a conditional random field model simultaneously. To do this, we first formulate the learning problem as a convex minimization problem by adding an l_2-regularization to the node parameters and a group l_1-regularization to the edge parameters, and then a gradient-based projection method is proposed to solve it which combines an adaptive stepsize selection strategy with a nonmonotone line search. Extensive simulation experiments are presented to show the performance of our approach in solving unknown structure learning problems.
-
Stirling, Bridget V
2017-08-01
Learning style preference impacts how well groups of students respond to their curricula. Faculty have many choices in the methods for delivering nursing content, as well as assessing students. The purpose was to develop knowledge around how faculty delivered curricula content, and then considering these findings in the context of the students learning style preference. Following an in-service on teaching and learning styles, faculty completed surveys on their methods of teaching and the proportion of time teaching, using each learning style (visual, aural, read/write and kinesthetic). This study took place at the College of Nursing a large all-female university in Saudi Arabia. 24 female nursing faculty volunteered to participate in the project. A cross-sectional design was used. Faculty reported teaching using mostly methods that were kinesthetic and visual, although lecture was also popular (aural). Students preferred kinesthetic and aural learning methods. Read/write was the least preferred by students and the least used method of teaching by faculty. Faculty used visual methods about one third of the time, although they were not preferred by the students. Students' preferred learning style (kinesthetic) was the method most used by faculty. Copyright © 2017 Elsevier Ltd. All rights reserved.
-
DEFF Research Database (Denmark)
Helms, Niels Henrik; Larsen, Lasse Juel
2009-01-01
, it is not a specific place where you can access scarce information. Pervasive or ubiquitous communication opens up for taking the organizing and design of learning landscapes a step further. Furthermore it calls for theoretical developments, which can open up for a deeper understanding of the relationship between...... emerging contexts, design of contexts and learning....
-
Electronic learning and constructivism: a model for nursing education.
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.
-
Trivette, Carol M.; Dunst, Carl J.; Hamby, Deborah W.; O'Herin, Chainey E.
2009-01-01
The effectiveness of four adult learning methods (accelerated learning, coaching, guided design, and just-in-time training) constituted the focus of this research synthesis. Findings reported in "How People Learn" (Bransford et al., 2000) were used to operationally define six adult learning method characteristics, and to code and analyze…
-
Ma, Xiao H; Jia, Jia; Zhu, Feng; Xue, Ying; Li, Ze R; Chen, Yu Z
2009-05-01
Machine learning methods have been explored as ligand-based virtual screening tools for facilitating drug lead discovery. These methods predict compounds of specific pharmacodynamic, pharmacokinetic or toxicological properties based on their structure-derived structural and physicochemical properties. Increasing attention has been directed at these methods because of their capability in predicting compounds of diverse structures and complex structure-activity relationships without requiring the knowledge of target 3D structure. This article reviews current progresses in using machine learning methods for virtual screening of pharmacodynamically active compounds from large compound libraries, and analyzes and compares the reported performances of machine learning tools with those of structure-based and other ligand-based (such as pharmacophore and clustering) virtual screening methods. The feasibility to improve the performance of machine learning methods in screening large libraries is discussed.
-
Cooperative Learning in Virtual Environments: The Jigsaw Method in Statistical Courses
Vargas-Vargas, Manuel; Mondejar-Jimenez, Jose; Santamaria, Maria-Letica Meseguer; Alfaro-Navarro, Jose-Luis; Fernandez-Aviles, Gema
2011-01-01
This document sets out a novel teaching methodology as used in subjects with statistical content, traditionally regarded by students as "difficult". In a virtual learning environment, instructional techniques little used in mathematical courses were employed, such as the Jigsaw cooperative learning method, which had to be adapted to the…
-
Enhancing the Pronunciation of English Suprasegmental Features through Reflective Learning Method
Suwartono
2014-01-01
Suprasegmental features are of paramount importance in spoken English. Yet, these pronunciation features are marginalised in EFL/ESL teaching-learning. This article reported a study that was aimed at improving the students' mastery of English suprasegmental features through the use of reflective learning method. The study adopted Kemmis and…
-
Foundations of Game-Based Learning
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…
-
Guo, Yujie; Shen, Jie; Ye, Xuchun; Chen, Huali; Jiang, Anli
2013-08-01
This paper aims to report the design and test the effectiveness of an innovative caring teaching model based on the theoretical framework of caring in the Chinese context. Since the 1970's, caring has been a core value in nursing education. In a previous study, a theoretical framework of caring in the Chinese context is explored employing a grounded theory study, considered beneficial for caring education. A caring teaching model was designed theoretically and a one group pre- and post-test quasi-experimental study was administered to test its effectiveness. From Oct, 2009 to Jul, 2010, a cohort of grade-2 undergraduate nursing students (n=64) in a Chinese medical school was recruited to participate in the study. Data were gathered through quantitative and qualitative methods to evaluate the effectiveness of the caring teaching model. The caring teaching model created an esthetic situation and experiential learning style for teaching caring that was integrated within the curricula. Quantitative data from the quasi-experimental study showed that the post-test scores of each item were higher than those on the pre-test (p<0.01). Thematic analysis of 1220 narratives from students' caring journals and reports of participant class observation revealed two main thematic categories, which reflected, from the students' points of view, the development of student caring character and the impact that the caring teaching model had on this regard. The model could be used as an integrated approach to teach caring in nursing curricula. It would also be beneficial for nursing administrators in cultivating caring nurse practitioners. Copyright © 2012 Elsevier Ltd. All rights reserved.
-
Case study teaching method improves student performance and perceptions of learning gains.
Bonney, Kevin M
2015-05-01
Following years of widespread use in business and medical education, the case study teaching method is becoming an increasingly common teaching strategy in science education. However, the current body of research provides limited evidence that the use of published case studies effectively promotes the fulfillment of specific learning objectives integral to many biology courses. This study tested the hypothesis that case studies are more effective than classroom discussions and textbook reading at promoting learning of key biological concepts, development of written and oral communication skills, and comprehension of the relevance of biological concepts to everyday life. This study also tested the hypothesis that case studies produced by the instructor of a course are more effective at promoting learning than those produced by unaffiliated instructors. Additionally, performance on quantitative learning assessments and student perceptions of learning gains were analyzed to determine whether reported perceptions of learning gains accurately reflect academic performance. The results reported here suggest that case studies, regardless of the source, are significantly more effective than other methods of content delivery at increasing performance on examination questions related to chemical bonds, osmosis and diffusion, mitosis and meiosis, and DNA structure and replication. This finding was positively correlated to increased student perceptions of learning gains associated with oral and written communication skills and the ability to recognize connections between biological concepts and other aspects of life. Based on these findings, case studies should be considered as a preferred method for teaching about a variety of concepts in science courses.
-
Case Study Teaching Method Improves Student Performance and Perceptions of Learning Gains
Directory of Open Access Journals (Sweden)
Kevin M. Bonney
2015-02-01
Full Text Available Following years of widespread use in business and medical education, the case study teaching method is becoming an increasingly common teaching strategy in science education. However, the current body of research provides limited evidence that the use of published case studies effectively promotes the fulfillment of specific learning objectives integral to many biology courses. This study tested the hypothesis that case studies are more effective than classroom discussions and textbook reading at promoting learning of key biological concepts, development of written and oral communication skills, and comprehension of the relevance of biological concepts to everyday life. This study also tested the hypothesis that case studies produced by the instructor of a course are more effective at promoting learning than those produced by unaffiliated instructors. Additionally, performance on quantitative learning assessments and student perceptions of learning gains were analyzed to determine whether reported perceptions of learning gains accurately reflect academic performance. The results reported here suggest that case studies, regardless of the source, are significantly more effective than other methods of content delivery at increasing performance on examination questions related to chemical bonds, osmosis and diffusion, mitosis and meiosis, and DNA structure and replication. This finding was positively correlated to increased student perceptions of learning gains associated with oral and written communication skills and the ability to recognize connections between biological concepts and other aspects of life. Based on these findings, case studies should be considered as a preferred method for teaching about a variety of concepts in science courses.
-
The role of problem solving method on the improvement of mathematical learning
Directory of Open Access Journals (Sweden)
Saeed Mokhtari-Hassanabad
2012-10-01
Full Text Available In history of education, problem solving is one of the important educational goals and teachers or parents have intended that their students have capacity of problem solving. In present research, it is tried that study the problem solving method for mathematical learning. This research is implemented via quasi-experimental method on 49 boy students at high school. The results of Leven test and T-test indicated that problem solving method has more effective on the improvement of mathematical learning than traditional instruction method. Therefore it seems that teachers of mathematics must apply the problem solving method in educational systems till students became self-efficiency in mathematical problem solving.
-
Advanced methods in NDE using machine learning approaches
Wunderlich, Christian; Tschöpe, Constanze; Duckhorn, Frank
2018-04-01
Machine learning (ML) methods and algorithms have been applied recently with great success in quality control and predictive maintenance. Its goal to build new and/or leverage existing algorithms to learn from training data and give accurate predictions, or to find patterns, particularly with new and unseen similar data, fits perfectly to Non-Destructive Evaluation. The advantages of ML in NDE are obvious in such tasks as pattern recognition in acoustic signals or automated processing of images from X-ray, Ultrasonics or optical methods. Fraunhofer IKTS is using machine learning algorithms in acoustic signal analysis. The approach had been applied to such a variety of tasks in quality assessment. The principal approach is based on acoustic signal processing with a primary and secondary analysis step followed by a cognitive system to create model data. Already in the second analysis steps unsupervised learning algorithms as principal component analysis are used to simplify data structures. In the cognitive part of the software further unsupervised and supervised learning algorithms will be trained. Later the sensor signals from unknown samples can be recognized and classified automatically by the algorithms trained before. Recently the IKTS team was able to transfer the software for signal processing and pattern recognition to a small printed circuit board (PCB). Still, algorithms will be trained on an ordinary PC; however, trained algorithms run on the Digital Signal Processor and the FPGA chip. The identical approach will be used for pattern recognition in image analysis of OCT pictures. Some key requirements have to be fulfilled, however. A sufficiently large set of training data, a high signal-to-noise ratio, and an optimized and exact fixation of components are required. The automated testing can be done subsequently by the machine. By integrating the test data of many components along the value chain further optimization including lifetime and durability
-
An exploration of learning to link with Wikipedia: features, methods and training collection
He, J.; de Rijke, M.
2010-01-01
We describe our participation in the Link-the-Wiki track at INEX 2009. We apply machine learning methods to the anchor-to-best-entry-point task and explore the impact of the following aspects of our approaches: features, learning methods as well as the collection used for training the models. We
-
The Effect of Integrated Learning-Teaching Approach on Reading Comprehension and Narration Skills
Directory of Open Access Journals (Sweden)
Ergün Hamzadayı
2010-12-01
Full Text Available This study investigated the effects of integrated learning-teaching approach on reading comprehension and narration skills. Considerations regarding how to overcome difficulties in the teaching of Turkish language through multi-theoretical perspectives have resulted in this approach to come into the existence. For the purpose of forming theoretical foundations of the research, behaviourist, cognitive and constructivist learning theories with their philosophical foundations were introduced, their principals and assumptions with regard to instructional design were compared, and their strengths and weakness were delineated. These considerations were then associated with the components of Turkish language program (content, objectives, teaching strategies and methods, assessment and that paved way for “integrative learning and teaching approach” to come into being. This study aimed to investigate whether there is a significant difference between the performance of the experimental group students who were exposed to integrative learning and teaching approach and that of control group students who were not exposed to integrative learning and teaching approach in terms of reading comprehension and written expression skills in Turkish language
-
Kernel methods for interpretable machine learning of order parameters
Ponte, Pedro; Melko, Roger G.
2017-11-01
Machine learning is capable of discriminating phases of matter, and finding associated phase transitions, directly from large data sets of raw state configurations. In the context of condensed matter physics, most progress in the field of supervised learning has come from employing neural networks as classifiers. Although very powerful, such algorithms suffer from a lack of interpretability, which is usually desired in scientific applications in order to associate learned features with physical phenomena. In this paper, we explore support vector machines (SVMs), which are a class of supervised kernel methods that provide interpretable decision functions. We find that SVMs can learn the mathematical form of physical discriminators, such as order parameters and Hamiltonian constraints, for a set of two-dimensional spin models: the ferromagnetic Ising model, a conserved-order-parameter Ising model, and the Ising gauge theory. The ability of SVMs to provide interpretable classification highlights their potential for automating feature detection in both synthetic and experimental data sets for condensed matter and other many-body systems.
-
Social Structures for Learning
I.M. Bogenrieder (Irma); B. Nooteboom (Bart)
2001-01-01
textabstractThis article investigates what learning groups there are in organizations, other than the familiar 'communities of practice'. It first develops an interdisciplinary theoretical framework for identifying, categorizing and understanding learning groups. For this, it employs a
-
Mikhchi, Abbas; Honarvar, Mahmood; Kashan, Nasser Emam Jomeh; Aminafshar, Mehdi
2016-06-21
Genotype imputation is an important tool for prediction of unknown genotypes for both unrelated individuals and parent-offspring trios. Several imputation methods are available and can either employ universal machine learning methods, or deploy algorithms dedicated to infer missing genotypes. In this research the performance of eight machine learning methods: Support Vector Machine, K-Nearest Neighbors, Extreme Learning Machine, Radial Basis Function, Random Forest, AdaBoost, LogitBoost, and TotalBoost compared in terms of the imputation accuracy, computation time and the factors affecting imputation accuracy. The methods employed using real and simulated datasets to impute the un-typed SNPs in parent-offspring trios. The tested methods show that imputation of parent-offspring trios can be accurate. The Random Forest and Support Vector Machine were more accurate than the other machine learning methods. The TotalBoost performed slightly worse than the other methods.The running times were different between methods. The ELM was always most fast algorithm. In case of increasing the sample size, the RBF requires long imputation time.The tested methods in this research can be an alternative for imputation of un-typed SNPs in low missing rate of data. However, it is recommended that other machine learning methods to be used for imputation. Copyright © 2016 Elsevier Ltd. All rights reserved.
-
Attentional Focus in Motor Learning, the Feldenkrais Method, and Mindful Movement.
Mattes, Josef
2016-08-01
The present paper discusses attentional focus in motor learning and performance from the point of view of mindful movement practices, taking as a starting point the Feldenkrais method. It is argued that earlier criticism of the Feldenkrais method (and thereby implicitly of mindful movement practices more generally) because of allegedly inappropriate attentional focus turns out to be unfounded in light of recent developments in the study of motor learning and performance. Conversely, the examples of the Feldenkrais method and Ki-Aikido are used to illustrate how both Western and Eastern (martial arts derived) mindful movement practices might benefit sports psychology. © The Author(s) 2016.
-
Directory of Open Access Journals (Sweden)
F. Kiani
2017-07-01
Full Text Available Analytical measurement of materials requires exact knowledge of their acid dissociation constant (pKa values. In recent years, quantum mechanical calculations have been extensively used to study of acidities in the aqueous solutions and the results were compared with the experimental values. In this study, a theoretical study was carried out on xylenol orange (in water solution by ab initio method. We calculated the pKa values of xylenol orange in water, using high-level ab initio (PM3, DFT (HF, B3LYP/6-31+G(d and SCRF methods. The experimental determination of these values (pKa,s is a challenge because xylenol orange has a low solubility in water. We considered several ionization reactions and equilibriums in water that constitute the indispensable theoretical basis to calculate the pKa values of xylenol orange. The results show that the calculated pKa values have a comparable agreement with the experimentally determined pKa values. Therefore, this method can be used to predict such properties for indicators, drugs and other important molecules.
-
Social Structures for Learning
Bogenrieder, I.M.; Nooteboom, B.
2001-01-01
textabstractThis article investigates what learning groups there are in organizations, other than the familiar 'communities of practice'. It first develops an interdisciplinary theoretical framework for identifying, categorizing and understanding learning groups. For this, it employs a constructivist, interactionist theory of knowledge and learning. It employs elements of transaction cost theory and of social theory of trust. Transaction cost economics neglects learning and trust, but element...
-
[Learning styles in medical residents and their professors of a pediatric hospital.
Juárez-Muñoz, Irina Elizabeth; Gómez-Negrete, Alonso; Varela-Ruiz, Margarita; Mejía-Aranguré, Juan Manuel; Mercado-Arellano, José Agustín; Sciandra-Rico, Martha Minerva; Matute-González, Mario Manuel
2013-01-01
Background: the learning styles are cognitive, emotional, and psychological characteristics, which function as relatively stable indicators of how teachers and students perceive, interact, and respond to their learning environments. Knowing students' styles allows teachers to have tools to improve medical education. Our objective was to identify learning styles in pediatric residents and professors from a pediatric hospital. Methods: a learning styles questionnaire was applied to residents and theirs professors; data was analyzed in SPSS 12 software. Results: the dominant learning style in pediatric residents was reflexive and for professors was theoretical. There wasn't any difference between sexes or between medical or surgical specialities. There was more correlation between professors and residents when there was an increase in training time. Conclusions: the learning styles between professors and residents are different, especially at the beginning of the medical specialty courses; that's why it is necessary to realize a confrontation between the students' learning styles and teaching methods used by professors to improve significant learning. To know learning styles gives residents an important alternative to find a better study strategy.
-
Creating an Innovative Learning Organization
Salisbury, Mark
2010-01-01
This article describes how to create an innovative learning (iLearning) organization. It begins by discussing the life cycle of knowledge in an organization, followed by a description of the theoretical foundation for iLearning. Next, the article presents an example of iLearning, followed by a description of the distributed nature of work, the…
-
Maximum entropy methods for extracting the learned features of deep neural networks.
Finnegan, Alex; Song, Jun S
2017-10-01
New architectures of multilayer artificial neural networks and new methods for training them are rapidly revolutionizing the application of machine learning in diverse fields, including business, social science, physical sciences, and biology. Interpreting deep neural networks, however, currently remains elusive, and a critical challenge lies in understanding which meaningful features a network is actually learning. We present a general method for interpreting deep neural networks and extracting network-learned features from input data. We describe our algorithm in the context of biological sequence analysis. Our approach, based on ideas from statistical physics, samples from the maximum entropy distribution over possible sequences, anchored at an input sequence and subject to constraints implied by the empirical function learned by a network. Using our framework, we demonstrate that local transcription factor binding motifs can be identified from a network trained on ChIP-seq data and that nucleosome positioning signals are indeed learned by a network trained on chemical cleavage nucleosome maps. Imposing a further constraint on the maximum entropy distribution also allows us to probe whether a network is learning global sequence features, such as the high GC content in nucleosome-rich regions. This work thus provides valuable mathematical tools for interpreting and extracting learned features from feed-forward neural networks.
-
Nissim, Nir; Shahar, Yuval; Boland, Mary Regina; Tatonetti, Nicholas P; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert
2018-01-01
Background and Objectives Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers’ learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. Methods We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by
-
Measuring strategic control in implicit learning: How and why?
Directory of Open Access Journals (Sweden)
Elisabeth eNorman
2015-09-01
Full Text Available Several methods have been developed for measuring the extent to which implicitly learned knowledge can be applied in a strategic, flexible manner. Examples include generation exclusion tasks in SRT learning (Destrebecqz & Cleeremans, 2001; Goschke, 1998 and 2-grammar classification tasks in AGL (Dienes, Altmann, Kwan, & Goode, 1995; Norman, Price, & Jones, 2011. Strategic control has traditionally been used as a criterion for determining whether acquired knowledge is conscious or unconscious, or which properties of knowledge is consciously available. In this paper I first summarize existing methods that have been developed for measuring strategic control in the SRT and AGL tasks. I then address some methodologial and theoretical questions. Methodological questions concern choice of task, whether the measurement reflects inhibitory control or task switching, and whether or not strategic control should be measured on a trial-by-trial basis. Theoretical questions concern the rationale for including measurement of strategic control, what form of knowledge is strategically controlled, and how strategic control can be combined with subjective awareness measures.
-
Zhang, Wen; Zhu, Xiaopeng; Fu, Yu; Tsuji, Junko; Weng, Zhiping
2017-12-01
Alternative splicing is the critical process in a single gene coding, which removes introns and joins exons, and splicing branchpoints are indicators for the alternative splicing. Wet experiments have identified a great number of human splicing branchpoints, but many branchpoints are still unknown. In order to guide wet experiments, we develop computational methods to predict human splicing branchpoints. Considering the fact that an intron may have multiple branchpoints, we transform the branchpoint prediction as the multi-label learning problem, and attempt to predict branchpoint sites from intron sequences. First, we investigate a variety of intron sequence-derived features, such as sparse profile, dinucleotide profile, position weight matrix profile, Markov motif profile and polypyrimidine tract profile. Second, we consider several multi-label learning methods: partial least squares regression, canonical correlation analysis and regularized canonical correlation analysis, and use them as the basic classification engines. Third, we propose two ensemble learning schemes which integrate different features and different classifiers to build ensemble learning systems for the branchpoint prediction. One is the genetic algorithm-based weighted average ensemble method; the other is the logistic regression-based ensemble method. In the computational experiments, two ensemble learning methods outperform benchmark branchpoint prediction methods, and can produce high-accuracy results on the benchmark dataset.
-
An improved segmentation-based HMM learning method for Condition-based Maintenance
International Nuclear Information System (INIS)
Liu, T; Lemeire, J; Cartella, F; Meganck, S
2012-01-01
In the domain of condition-based maintenance (CBM), persistence of machine states is a valid assumption. Based on this assumption, we present an improved Hidden Markov Model (HMM) learning algorithm for the assessment of equipment states. By a good estimation of initial parameters, more accurate learning can be achieved than by regular HMM learning methods which start with randomly chosen initial parameters. It is also better in avoiding getting trapped in local maxima. The data is segmented with a change-point analysis method which uses a combination of cumulative sum charts (CUSUM) and bootstrapping techniques. The method determines a confidence level that a state change happens. After the data is segmented, in order to label and combine the segments corresponding to the same states, a clustering technique is used based on a low-pass filter or root mean square (RMS) values of the features. The segments with their labelled hidden state are taken as 'evidence' to estimate the parameters of an HMM. Then, the estimated parameters are served as initial parameters for the traditional Baum-Welch (BW) learning algorithms, which are used to improve the parameters and train the model. Experiments on simulated and real data demonstrate that both performance and convergence speed is improved.
-
Kruger, Tina M; Pearl, Andrew J
2016-01-01
Service-learning is a useful pedagogical tool and high-impact practice, providing multiple benefits. Gerontology (and other) courses frequently include service-learning activities but lack theory-based, intentional research on outcomes. Here, the authors define service-learning and contextualize it in higher education, provide an overview of research and assessment in service-learning and gerontology courses, demonstrate the shortcomings of program evaluations, and offer suggestions for future research to advance and generate theory.
-
Learning design: reflections upon the current landscape
Directory of Open Access Journals (Sweden)
Brock Craft
2012-08-01
Full Text Available The mounting wealth of open and readily available information and the accelerated evolution of social, mobile and creative technologies call for a re-conceptualisation of the role of educators: from providers of knowledge to designers of learning. This call is reverberated by the rising trend of research in learning design (LD. Addressing this, the Art and Science of Learning Design workshop brought together leading voices in the field, and provided a forum for discussing its key issues. It focused on three major themes: (1 practices, methods and methodologies, (2 tools and resources and (3 theoretical frameworks. This paper proposes a definition of LD, reviews the main contributions from the workshop, and suggests some challenges for future research.
-
Radical-Local Teaching and Learning
DEFF Research Database (Denmark)
Hedegaard, Mariane; Chaiklin, Seth
radical-local teaching and learning approach. The first half of the book introduces the idea of radical-local teaching and learning and develops the theoretical background for this perspective, drawing on the cultural-historical research tradition, particularly from Vygotsky, El'konin, Davydov......, and Aidarova. The second half of the book addresses the central concern of radical-local teaching and learning - how to relate educational practices to children's specific historical and cultural conditions. The experiment was conducted for an academic year in an afterschool programme in the East Harlem......Radical-Local Teaching and Learning presents a theoretical perspective for analyzing and planning educational programmes for schoolchildren. To realize both general societal interests and worthwhile personal development, the content of educational programmes for children must be grounded...
-
Application of a Novel Collaboration Engineering Method for Learning Design: A Case Study
Cheng, Xusen; Li, Yuanyuan; Sun, Jianshan; Huang, Jianqing
2016-01-01
Collaborative case studies and computer-supported collaborative learning (CSCL) play an important role in the modern education environment. A number of researchers have given significant attention to learning design in order to improve the satisfaction of collaborative learning. Although collaboration engineering (CE) is a mature method widely…
-
Nissim, Nir; Shahar, Yuval; Elovici, Yuval; Hripcsak, George; Moskovitch, Robert
2017-09-01
Labeling instances by domain experts for classification is often time consuming and expensive. To reduce such labeling efforts, we had proposed the application of active learning (AL) methods, introduced our CAESAR-ALE framework for classifying the severity of clinical conditions, and shown its significant reduction of labeling efforts. The use of any of three AL methods (one well known [SVM-Margin], and two that we introduced [Exploitation and Combination_XA]) significantly reduced (by 48% to 64%) condition labeling efforts, compared to standard passive (random instance-selection) SVM learning. Furthermore, our new AL methods achieved maximal accuracy using 12% fewer labeled cases than the SVM-Margin AL method. However, because labelers have varying levels of expertise, a major issue associated with learning methods, and AL methods in particular, is how to best to use the labeling provided by a committee of labelers. First, we wanted to know, based on the labelers' learning curves, whether using AL methods (versus standard passive learning methods) has an effect on the Intra-labeler variability (within the learning curve of each labeler) and inter-labeler variability (among the learning curves of different labelers). Then, we wanted to examine the effect of learning (either passively or actively) from the labels created by the majority consensus of a group of labelers. We used our CAESAR-ALE framework for classifying the severity of clinical conditions, the three AL methods and the passive learning method, as mentioned above, to induce the classifications models. We used a dataset of 516 clinical conditions and their severity labeling, represented by features aggregated from the medical records of 1.9 million patients treated at Columbia University Medical Center. We analyzed the variance of the classification performance within (intra-labeler), and especially among (inter-labeler) the classification models that were induced by using the labels provided by seven
-
Nisbet, Gillian; Lincoln, Michelle; Dunn, Stewart
2013-11-01
In this paper, we explore the educational and workplace learning literature to identify the potential and significance for informal interprofessional learning within the workplace. We also examine theoretical perspectives informing informal workplace interprofessional learning. Despite numerous studies focusing on formal interprofessional education programs, we suggest that informal interprofessional learning opportunities are currently unrealized. We highlight reasons for a focus on learning within the workplace and the potential benefits within an interprofessional context.