Goal-Setting Learning Principles: A Lesson From Practitioner

OpenAIRE

Zainudin bin Abu Bakar; Lee Mei Yun; NG Siew Keow; Tan Hui Li

2014-01-01

One of the prominent theory was the goal-setting theory which was widely been used in educational setting. It is an approach than can enhance the teaching and learning activities in the classroom. This is a report paper about a simple study of the implementation of the goal-setting principle in the classroom. A clinical data of the teaching and learning session was then analysed to address several issues highlighted. It is found that the goal-setting principles if understood clearly by the te...

Keefektifan setting TPS dalam pendekatan discovery learning dan problem-based learning pada pembelajaran materi lingkaran SMP

Directory of Open Access Journals (Sweden)

Rahmi Hidayati

2017-05-01

The purpose of this study was to describe the effectiveness of setting Think Pair Share (TPS in the approach to discovery learning and problem-based learning in terms of student achievement, mathematical communication skills, and interpersonal skills of the student.  This study was a quasi-experimental study using the pretest-posttest nonequivalent group design. The research population comprised all Year VIII students of SMP Negeri 1 Yogyakarta. The research sample was randomly selected from eight classes, two classes were elected. The instrument used in this study is the learning achievement test, a test of mathematical communication skills, and interpersonal skills student questionnaires. To test the effectiveness of setting Think Pair Share (TPS in the approach to discovery learning and problem-based learning, the one sample t-test was carried out. Then, to investigate the difference in effectiveness between the setting Think Pair Share (TPS in the approach to discovery learning and problem-based learning, the Multivariate Analysis of Variance (MANOVA was carried out. The research findings indicate that the setting TPS discovery approach to learning and problem-based approach to learning (PBL is effective in terms of learning achievement, mathematical communication skills, and interpersonal skills of the students. No difference in effectiveness between setting TPS discovery approach to learning and problem-based learning (PBL in terms of learning achievement, mathematical communication skills, and interpersonal skills of the students. Keywords: TPS setting in discovery learning approach, in problem-based learning, academic achievement, mathematical communication skills, and interpersonal skills of the student

How and with What Accuracy Do Children Report Self-Regulated Learning in Contemporary EFL Instructional Settings?

Science.gov (United States)

Ferreira, P. Costa; Simão, A. M. Veiga; da Silva, A. Lopes

2017-01-01

This study aimed to understand how children reflect about learning, report their regulation of learning activity, and develop their performance in contemporary English as a Foreign Language instructional settings. A quasi-experimental design was used with one experimental group working in a self-regulated learning computer-supported instructional…

Performance of a visuomotor walking task in an augmented reality training setting.

Science.gov (United States)

Haarman, Juliet A M; Choi, Julia T; Buurke, Jaap H; Rietman, Johan S; Reenalda, Jasper

2017-12-01

Visual cues can be used to train walking patterns. Here, we studied the performance and learning capacities of healthy subjects executing a high-precision visuomotor walking task, in an augmented reality training set-up. A beamer was used to project visual stepping targets on the walking surface of an instrumented treadmill. Two speeds were used to manipulate task difficulty. All participants (n = 20) had to change their step length to hit visual stepping targets with a specific part of their foot, while walking on a treadmill over seven consecutive training blocks, each block composed of 100 stepping targets. Distance between stepping targets was varied between short, medium and long steps. Training blocks could either be composed of random stepping targets (no fixed sequence was present in the distance between the stepping targets) or sequenced stepping targets (repeating fixed sequence was present). Random training blocks were used to measure non-specific learning and sequenced training blocks were used to measure sequence-specific learning. Primary outcome measures were performance (% of correct hits), and learning effects (increase in performance over the training blocks: both sequence-specific and non-specific). Secondary outcome measures were the performance and stepping-error in relation to the step length (distance between stepping target). Subjects were able to score 76% and 54% at first try for lower speed (2.3 km/h) and higher speed (3.3 km/h) trials, respectively. Performance scores did not increase over the course of the trials, nor did the subjects show the ability to learn a sequenced walking task. Subjects were better able to hit targets while increasing their step length, compared to shortening it. In conclusion, augmented reality training by use of the current set-up was intuitive for the user. Suboptimal feedback presentation might have limited the learning effects of the subjects. Copyright © 2017 Elsevier B.V. All rights reserved.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan

2016-12-29

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Multi-instance dictionary learning via multivariate performance measure optimization

KAUST Repository

Wang, Jim Jing-Yan; Tsang, Ivor Wai-Hung; Cui, Xuefeng; Lu, Zhiwu; Gao, Xin

2016-01-01

The multi-instance dictionary plays a critical role in multi-instance data representation. Meanwhile, different multi-instance learning applications are evaluated by specific multivariate performance measures. For example, multi-instance ranking reports the precision and recall. It is not difficult to see that to obtain different optimal performance measures, different dictionaries are needed. This observation motives us to learn performance-optimal dictionaries for this problem. In this paper, we propose a novel joint framework for learning the multi-instance dictionary and the classifier to optimize a given multivariate performance measure, such as the F1 score and precision at rank k. We propose to represent the bags as bag-level features via the bag-instance similarity, and learn a classifier in the bag-level feature space to optimize the given performance measure. We propose to minimize the upper bound of a multivariate loss corresponding to the performance measure, the complexity of the classifier, and the complexity of the dictionary, simultaneously, with regard to both the dictionary and the classifier parameters. In this way, the dictionary learning is regularized by the performance optimization, and a performance-optimal dictionary is obtained. We develop an iterative algorithm to solve this minimization problem efficiently using a cutting-plane algorithm and a coordinate descent method. Experiments on multi-instance benchmark data sets show its advantage over both traditional multi-instance learning and performance optimization methods.

Structure of Small World Innovation Network and Learning Performance

Directory of Open Access Journals (Sweden)

Shuang Song

2014-01-01

Full Text Available This paper examines the differences of learning performance of 5 MNCs (multinational corporations that filed the largest number of patents in China. We establish the innovation network with the patent coauthorship data by these 5 MNCs and classify the networks by the tail of distribution curve of connections. To make a comparison of the learning performance of these 5 MNCs with differing network structures, we develop an organization learning model by regarding the reality as having m dimensions, which denotes the heterogeneous knowledge about the reality. We further set n innovative individuals that are mutually interactive and own unique knowledge about the reality. A longer (shorter distance between the knowledge of the individual and the reality denotes a lower (higher knowledge level of that individual. Individuals interact with and learn from each other within the small-world network. By making 1,000 numerical simulations and averaging the simulated results, we find that the differing structure of the small-world network leads to the differences of learning performance between these 5 MNCs. The network monopolization negatively impacts and network connectivity positively impacts learning performance. Policy implications in the conclusion section suggest that to improve firm learning performance, it is necessary to establish a flat and connective network.

Surface blemish detection from passive imagery using learned fuzzy set concepts

International Nuclear Information System (INIS)

Gurbuz, S.; Carver, A.; Schalkoff, R.

1997-12-01

An image analysis method for real-time surface blemish detection using passive imagery and fuzzy set concepts is described. The method develops an internal knowledge representation for surface blemish characteristics on the basis of experience, thus facilitating autonomous learning based upon positive and negative exemplars. The method incorporates fuzzy set concepts in the learning subsystem and image segmentation algorithms, thereby mimicking human visual perception. This enables a generic solution for color image segmentation. This method has been applied in the development of ARIES (Autonomous Robotic Inspection Experimental System), designed to inspect DOE warehouse waste storage drums for rust. In this project, the ARIES vision system is used to acquire drum surface images under controlled conditions and subsequently perform visual inspection leading to the classification of the drum as acceptable or suspect

Cooperative learning and algebra performance of eighth grade students in United Arab Emirates.

Science.gov (United States)

Alkhateeb, Haitham M; Jumaa, Mustafa

2002-02-01

This study investigated the effect of cooperative learning on eighth grade students' performance in algebra. 54 boys and 57 girls in four middle-school mathematics classes of Grade 8 in the UAE participated. Over a 3-wk. period, two classes (57 students) were taught using a cooperative learning method, and the other two classes (54 students) were taught using the traditional lecture method. Analysis of covariance using pretest scores as a covariant showed no statistically significant increase in the algebra performance for students in the cooperative learning groups compared with the traditional groups. However, boys in the cooperative setting improved significantly on the performance test compared with boys in the traditional setting.

Management Coaching with Performance Templates to Stimulate Self-Regulated Learning

Science.gov (United States)

Lyons, Paul; Bandura, Randall P.

2017-01-01

Purpose: Much has been written about self-regulated learning (SRL) (including mind-sets) in psychology and education, but little research is found in the HRD or training literature regarding the stimulation of this learning. This paper aims to present a practical training tool, performance templates (P-T), to demonstrate how a line manager may…

Comparative Performance Analysis of Machine Learning Techniques for Software Bug Detection

OpenAIRE

Saiqa Aleem; Luiz Fernando Capretz; Faheem Ahmed

2015-01-01

Machine learning techniques can be used to analyse data from different perspectives and enable developers to retrieve useful information. Machine learning techniques are proven to be useful in terms of software bug prediction. In this paper, a comparative performance analysis of different machine learning techniques is explored f or software bug prediction on public available data sets. Results showed most of the mac ...

Adaptation and learning: characteristic time scales of performance dynamics.

Science.gov (United States)

Newell, Karl M; Mayer-Kress, Gottfried; Hong, S Lee; Liu, Yeou-Teh

2009-12-01

A multiple time scales landscape model is presented that reveals structures of performance dynamics that were not resolved in the traditional power law analysis of motor learning. It shows the co-existence of separate processes during and between practice sessions that evolve in two independent dimensions characterized by time scales that differ by about an order of magnitude. Performance along the slow persistent dimension of learning improves often as much and sometimes more during rest (memory consolidation and/or insight generation processes) than during a practice session itself. In contrast, the process characterized by the fast, transient dimension of adaptation reverses direction between practice sessions, thereby significantly degrading performance at the beginning of the next practice session (warm-up decrement). The theoretical model fits qualitatively and quantitatively the data from Snoddy's [Snoddy, G. S. (1926). Learning and stability. Journal of Applied Psychology, 10, 1-36] classic learning study of mirror tracing and other averaged and individual data sets, and provides a new account of the processes of change in adaptation and learning. 2009 Elsevier B.V. All rights reserved.

Performance of a visuomotor walking task in an augmented reality training setting

NARCIS (Netherlands)

Haarman, Juliet A.M.; Choi, Julia T.; Buurke, Jaap H.; Rietman, Johan S.; Reenalda, Jasper

2017-01-01

Visual cues can be used to train walking patterns. Here, we studied the performance and learning capacities of healthy subjects executing a high-precision visuomotor walking task, in an augmented reality training set-up. A beamer was used to project visual stepping targets on the walking surface of

[Nursing students' perception of the learning process in a hospital setting].

Science.gov (United States)

Alves, Elcilene Andreíne Terra Durgante; Cogo, Ana Luísa Petersen

2014-03-01

The aim of this study was to identijf how nursing students perceive and experience the learning process during curricular practice in a hospital setting. A qualitative, retrospective, documentary study was developed in an undergraduate nursing course. Data were comprised of 162 posts made by 34 students in the online discussion forum of the Learning Management System Moodle, during the first half of 2011. The following themes emergedfrom t he thematic content analysis: "nursing students' understanding about the professional practice," and "the teaching and learning process in the perspective of nursing students." The study demonstrated that the forum was a place for reporting experiences such as the description of the physical area, performing procedures, perception of nursing care activities, conJlicts with peers, coping with death and learning evaluation. The online discussion forum needs to be used by professors as a space of interaction so as to contribute to professional training.

Comparison of Deep Learning With Multiple Machine Learning Methods and Metrics Using Diverse Drug Discovery Data Sets.

Science.gov (United States)

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

Splendidly blended: a machine learning set up for CDU control

Science.gov (United States)

Utzny, Clemens

2017-06-01

As the concepts of machine learning and artificial intelligence continue to grow in importance in the context of internet related applications it is still in its infancy when it comes to process control within the semiconductor industry. Especially the branch of mask manufacturing presents a challenge to the concepts of machine learning since the business process intrinsically induces pronounced product variability on the background of small plate numbers. In this paper we present the architectural set up of a machine learning algorithm which successfully deals with the demands and pitfalls of mask manufacturing. A detailed motivation of this basic set up followed by an analysis of its statistical properties is given. The machine learning set up for mask manufacturing involves two learning steps: an initial step which identifies and classifies the basic global CD patterns of a process. These results form the basis for the extraction of an optimized training set via balanced sampling. A second learning step uses this training set to obtain the local as well as global CD relationships induced by the manufacturing process. Using two production motivated examples we show how this approach is flexible and powerful enough to deal with the exacting demands of mask manufacturing. In one example we show how dedicated covariates can be used in conjunction with increased spatial resolution of the CD map model in order to deal with pathological CD effects at the mask boundary. The other example shows how the model set up enables strategies for dealing tool specific CD signature differences. In this case the balanced sampling enables a process control scheme which allows usage of the full tool park within the specified tight tolerance budget. Overall, this paper shows that the current rapid developments off the machine learning algorithms can be successfully used within the context of semiconductor manufacturing.

Clinical skills-related learning goals of senior medical students after performance feedback.

Science.gov (United States)

Chang, Anna; Chou, Calvin L; Teherani, Arianne; Hauer, Karen E

2011-09-01

Lifelong learning is essential for doctors to maintain competence in clinical skills. With performance feedback, learners should be able to formulate specific and achievable learning goals in areas of need. We aimed to determine: (i) the type and specificity of medical student learning goals after a required clinical performance examination; (ii) differences in goal setting among low, average and high performers, and (iii) whether low performers articulate learning goals that are concordant with their learning needs. We conducted a single-site, multi-year, descriptive comparison study. Senior medical students were given performance benchmarks, individual feedback and guidelines on learning goals; each student was subsequently instructed to write two clinical skills learning goals. Investigators coded the learning goals for specificity, categorised the goals, and performed statistical analyses to determine their concordance with student performance level (low, average or high) in data gathering (history taking and physical examination) or communication skills. All 208 students each wrote two learning goals and most (n=200, 96%) wrote two specific learning goals. Nearly two-thirds of low performers in data gathering wrote at least one learning goal that referred to history taking or physical examination; one-third wrote learning goals pertaining to the organisation of the encounter. High performers in data gathering wrote significantly more patient education goals and significantly fewer history-taking goals than average or low performers. Only 50% of low performers in communication wrote learning goals related to communication skills. Low performers in communication were significantly more likely than average or high performers to identify learning goals related to improving performance in future examinations. The provision of performance benchmarking, individual feedback and brief written guidelines helped most senior medical students in our study to write specific

Designing for expansive science learning and identification across settings

Science.gov (United States)

Stromholt, Shelley; Bell, Philip

2017-10-01

In this study, we present a case for designing expansive science learning environments in relation to neoliberal instantiations of standards-based implementation projects in education. Using ethnographic and design-based research methods, we examine how the design of coordinated learning across settings can engage youth from non-dominant communities in scientific and engineering practices, resulting in learning experiences that are more relevant to youth and their communities. Analyses highlight: (a) transformative moments of identification for one fifth-grade student across school and non-school settings; (b) the disruption of societal, racial stereotypes on the capabilities of and expectations for marginalized youth; and (c) how youth recognized themselves as members of their community and agents of social change by engaging in personally consequential science investigations and learning.

The development of a National set of Physiology learning objectives ...

African Journals Online (AJOL)

International Journal of Medicine and Health Development ... engagement that can be utilized to design a national set of learning objectives towards improving learning ... Key words: Learning objectives, Nigeria, Medical education, curriculum ...

Informal Language Learning Setting: Technology or Social Interaction?

Science.gov (United States)

Bahrani, Taher; Sim, Tam Shu

2012-01-01

Based on the informal language learning theory, language learning can occur outside the classroom setting unconsciously and incidentally through interaction with the native speakers or exposure to authentic language input through technology. However, an EFL context lacks the social interaction which naturally occurs in an ESL context. To explore…

Detecting representative data and generating synthetic samples to improve learning accuracy with imbalanced data sets.

Directory of Open Access Journals (Sweden)

Der-Chiang Li

Full Text Available It is difficult for learning models to achieve high classification performances with imbalanced data sets, because with imbalanced data sets, when one of the classes is much larger than the others, most machine learning and data mining classifiers are overly influenced by the larger classes and ignore the smaller ones. As a result, the classification algorithms often have poor learning performances due to slow convergence in the smaller classes. To balance such data sets, this paper presents a strategy that involves reducing the sizes of the majority data and generating synthetic samples for the minority data. In the reducing operation, we use the box-and-whisker plot approach to exclude outliers and the Mega-Trend-Diffusion method to find representative data from the majority data. To generate the synthetic samples, we propose a counterintuitive hypothesis to find the distributed shape of the minority data, and then produce samples according to this distribution. Four real datasets were used to examine the performance of the proposed approach. We used paired t-tests to compare the Accuracy, G-mean, and F-measure scores of the proposed data pre-processing (PPDP method merging in the D3C method (PPDP+D3C with those of the one-sided selection (OSS, the well-known SMOTEBoost (SB study, and the normal distribution-based oversampling (NDO approach, and the proposed data pre-processing (PPDP method. The results indicate that the classification performance of the proposed approach is better than that of above-mentioned methods.

Managing Learning for Performance.

Science.gov (United States)

Kuchinke, K. Peter

1995-01-01

Presents findings of organizational learning literature that could substantiate claims of learning organization proponents. Examines four learning processes and their contribution to performance-based learning management: knowledge acquisition, information distribution, information interpretation, and organizational memory. (SK)

Competitive Learning Neural Network Ensemble Weighted by Predicted Performance

Science.gov (United States)

Ye, Qiang

2010-01-01

Ensemble approaches have been shown to enhance classification by combining the outputs from a set of voting classifiers. Diversity in error patterns among base classifiers promotes ensemble performance. Multi-task learning is an important characteristic for Neural Network classifiers. Introducing a secondary output unit that receives different…

Peer-Assisted Learning in the Athletic Training Clinical Setting

Science.gov (United States)

Henning, Jolene M; Weidner, Thomas G; Jones, James

2006-01-01

Context: Athletic training educators often anecdotally suggest that athletic training students enhance their learning by teaching their peers. However, peer-assisted learning (PAL) has not been examined within athletic training education in order to provide evidence for its current use or as a pedagogic tool. Objective: To describe the prevalence of PAL in athletic training clinical education and to identify students' perceptions of PAL. Design: Descriptive. Setting: “The Athletic Training Student Seminar” at the National Athletic Trainers' Association 2002 Annual Meeting and Clinical Symposia. Patients or Other Participants: A convenience sample of 138 entry-level male and female athletic training students. Main Outcome Measure(s): Students' perceptions regarding the prevalence and benefits of and preferences for PAL were measured using the Athletic Training Peer-Assisted Learning Assessment Survey. The Survey is a self-report tool with 4 items regarding the prevalence of PAL and 7 items regarding perceived benefits and preferences. Results: A total of 66% of participants practiced a moderate to large amount of their clinical skills with other athletic training students. Sixty percent of students reported feeling less anxious when performing clinical skills on patients in front of other athletic training students than in front of their clinical instructors. Chi-square analysis revealed that 91% of students enrolled in Commission on Accreditation of Allied Health Education Programs–accredited athletic training education programs learned a minimal to small amount of clinical skills from their peers compared with 65% of students in Joint Review Committee on Educational Programs in Athletic Training–candidacy schools (χ2 3 = 14.57, P < .01). Multiple analysis of variance revealed significant interactions between sex and academic level on several items regarding benefits and preferences. Conclusions: According to athletic training students, PAL is occurring in

E-Learning: Students Input for Using Mobile Devices in Science Instructional Settings

Science.gov (United States)

Yilmaz, Ozkan

2016-01-01

A variety of e-learning theories, models, and strategy have been developed to support educational settings. There are many factors for designing good instructional settings. This study set out to determine functionality of mobile devices, students who already have, and the student needs and views in relation to e-learning settings. The study…

Learning with nature and learning from others: nature as setting and resource for early childhood education

OpenAIRE

MacQuarrie, Sarah; Nugent, Clare; Warden, Claire

2015-01-01

Nature-based learning is an increasingly popular type of early childhood education. Despite this, children's experiences-in particular, their form and function within different settings and how they are viewed by practitioners-are relatively unknown. Accordingly, the use of nature as a setting and a resource for learning was researched. A description and an emerging understanding of nature-based learning were obtained through the use of a group discussion and case studies. Practitioners' view...

Bidirectional Active Learning: A Two-Way Exploration Into Unlabeled and Labeled Data Set.

Science.gov (United States)

Zhang, Xiao-Yu; Wang, Shupeng; Yun, Xiaochun

2015-12-01

In practical machine learning applications, human instruction is indispensable for model construction. To utilize the precious labeling effort effectively, active learning queries the user with selective sampling in an interactive way. Traditional active learning techniques merely focus on the unlabeled data set under a unidirectional exploration framework and suffer from model deterioration in the presence of noise. To address this problem, this paper proposes a novel bidirectional active learning algorithm that explores into both unlabeled and labeled data sets simultaneously in a two-way process. For the acquisition of new knowledge, forward learning queries the most informative instances from unlabeled data set. For the introspection of learned knowledge, backward learning detects the most suspiciously unreliable instances within the labeled data set. Under the two-way exploration framework, the generalization ability of the learning model can be greatly improved, which is demonstrated by the encouraging experimental results.

Advantages of Synthetic Noise and Machine Learning for Analyzing Radioecological Data Sets.

Directory of Open Access Journals (Sweden)

Igor Shuryak

Full Text Available The ecological effects of accidental or malicious radioactive contamination are insufficiently understood because of the hazards and difficulties associated with conducting studies in radioactively-polluted areas. Data sets from severely contaminated locations can therefore be small. Moreover, many potentially important factors, such as soil concentrations of toxic chemicals, pH, and temperature, can be correlated with radiation levels and with each other. In such situations, commonly-used statistical techniques like generalized linear models (GLMs may not be able to provide useful information about how radiation and/or these other variables affect the outcome (e.g. abundance of the studied organisms. Ensemble machine learning methods such as random forests offer powerful alternatives. We propose that analysis of small radioecological data sets by GLMs and/or machine learning can be made more informative by using the following techniques: (1 adding synthetic noise variables to provide benchmarks for distinguishing the performances of valuable predictors from irrelevant ones; (2 adding noise directly to the predictors and/or to the outcome to test the robustness of analysis results against random data fluctuations; (3 adding artificial effects to selected predictors to test the sensitivity of the analysis methods in detecting predictor effects; (4 running a selected machine learning method multiple times (with different random-number seeds to test the robustness of the detected "signal"; (5 using several machine learning methods to test the "signal's" sensitivity to differences in analysis techniques. Here, we applied these approaches to simulated data, and to two published examples of small radioecological data sets: (I counts of fungal taxa in samples of soil contaminated by the Chernobyl nuclear power plan accident (Ukraine, and (II bacterial abundance in soil samples under a ruptured nuclear waste storage tank (USA. We show that the proposed

Learning with Nature and Learning from Others: Nature as Setting and Resource for Early Childhood Education

Science.gov (United States)

MacQuarrie, Sarah; Nugent, Clare; Warden, Claire

2015-01-01

Nature-based learning is an increasingly popular type of early childhood education. Despite this, children's experiences--in particular, their form and function within different settings and how they are viewed by practitioners--are relatively unknown. Accordingly, the use of nature as a setting and a resource for learning was researched. A…

The Present and Future State of Blended Learning in Workplace Learning Settings in the United States

Science.gov (United States)

Bonk, Curtis J.; Kim, Kyong-Jee; Oh, Eun Jung; Teng, Ya-Ting; Son, Su Jin

2007-01-01

This paper reports survey findings related to the present and future state of blended learning in workplace learning settings across the U.S. Surveyed in this study are 118 practitioners in corporate training or elearning in various workplace settings. The findings reveal interesting perceptions by respondents regarding the benefits of and…

How clerkship students learn from real patients in practice settings

NARCIS (Netherlands)

Steven, Kathryn; Wenger, Etienne; Boshuizen, Els; Scherpbier, Albert; Dornan, Tim

2018-01-01

Purpose To explore how undergraduate medical students learn from real patients in practice settings, the factors that affect their learning, and how clerkship learning might be enhanced. Method In 2009, 22 medical students in the three clerkship years of an undergraduate medical program in the

Bias-Free Chemically Diverse Test Sets from Machine Learning.

Science.gov (United States)

Swann, Ellen T; Fernandez, Michael; Coote, Michelle L; Barnard, Amanda S

2017-08-14

Current benchmarking methods in quantum chemistry rely on databases that are built using a chemist's intuition. It is not fully understood how diverse or representative these databases truly are. Multivariate statistical techniques like archetypal analysis and K-means clustering have previously been used to summarize large sets of nanoparticles however molecules are more diverse and not as easily characterized by descriptors. In this work, we compare three sets of descriptors based on the one-, two-, and three-dimensional structure of a molecule. Using data from the NIST Computational Chemistry Comparison and Benchmark Database and machine learning techniques, we demonstrate the functional relationship between these structural descriptors and the electronic energy of molecules. Archetypes and prototypes found with topological or Coulomb matrix descriptors can be used to identify smaller, statistically significant test sets that better capture the diversity of chemical space. We apply this same method to find a diverse subset of organic molecules to demonstrate how the methods can easily be reapplied to individual research projects. Finally, we use our bias-free test sets to assess the performance of density functional theory and quantum Monte Carlo methods.

Using Learning Sets to Support UK Delivery of Off-Shore Learning in Africa

Science.gov (United States)

Blackburn, Michelle

2014-01-01

This account of practice focuses on the delivery of Action Learning Sets in Swaziland and Malawi as part of a UK university's remote Master's degree teaching programme. It draws upon the experience of an Academic delivering the programme and the efforts made to refine the approach to action learning given time, understanding and resource…

Learning Performance Enhancement Using Computer-Assisted Language Learning by Collaborative Learning Groups

Directory of Open Access Journals (Sweden)

Ya-huei Wang

2017-08-01

Full Text Available This study attempted to test whether the use of computer-assisted language learning (CALL and innovative collaborative learning could be more effective than the use of traditional collaborative learning in improving students’ English proficiencies. A true experimental design was used in the study. Four randomly-assigned groups participated in the study: a traditional collaborative learning group (TCLG, 34 students, an innovative collaborative learning group (ICLG, 31 students, a CALL traditional collaborative learning group (CALLTCLG, 32 students, and a CALL innovative collaborative learning group (CALLICLG, 31 students. TOEIC (Test of English for International Communication listening, reading, speaking, and writing pre-test and post-test assessments were given to all students at an interval of sixteen weeks. Multivariate analysis of covariance (MANCOVA, multivariate analysis of variance (MANOVA, and analysis of variance (ANOVA were used to analyze the data. The results revealed that students who used CALL had significantly better learning performance than those who did not. Students in innovative collaborative learning had significantly better learning performances than those in traditional collaborative learning. Additionally, students using CALL innovative collaborative learning had better learning performances than those in CALL collaborative learning, those in innovative collaborative learning, and those in traditional collaborative learning.

E-portfolios in university and blended learning settings

DEFF Research Database (Denmark)

Ørngreen, Rikke

2009-01-01

or case work, if the process of and interaction between the students are prioritised. The paper adds to the existing findings within ePortfolio and their application to formal learning settings. It discusses both the planning of and running the process, psychological barriers, students' motivation as well...... as more technological practical aspects of ePortfolio use, that are relevant for people engaged in IT and learning....

A socio-cultural approach to learning in the practice setting.

LENUS (Irish Health Repository)

White, Ciara

2010-11-01

Practice learning is an essential part of the curriculum and accounts for approximately 60% of the current pre-registration nursing programmes in the Republic of Ireland. The nature and quality of the clinical learning environment and the student nurses\\' experience of their practice placements is recognised as being influential in promoting the integration of theory and practice. However, the problem experienced by many learners is how to relate their theoretical knowledge to the situation-at-hand within the practice setting. Socio-cultural or activity theories of learning seek to explain the social nature of learning and propose that knowledge and learning are considered to be contextually situated. Lave and Wenger (1991) argue that learning is integrated with practice and through engagement with a community of practice, by means of sponsorship; students become increasingly competent in their identity as practitioners. This paper examines the changes which have occurred within the pre-registration nursing curriculum in the Republic of Ireland with the transition from the apprenticeship system to the graduate programme, and the resulting reduction in clinical learning hours. It also examines the potential impact on the development of student learning with the implementation of the concepts proposed by Lave and Wenger to learning in the practice setting.

Becoming conscious of learning and nursing in clinical settings

DEFF Research Database (Denmark)

Nielsen, Kirsten; Pedersen, Birthe D.; Helms, Niels Henrik

2015-01-01

Literature shows several benefits of implementing ePortfolio and focusing on learning styles within nursing education. However, there is some ambiguity, so the aim was to investigate learning mediated by the mandatory part of ePortfolio in clinical settings. The design takes a phenomenological......-hermeneutic approach. The setting was a ten-week clinical course in Basic Nursing, and participants were 11 first-year students randomly assigned. Data was generated by participant observations, narrative interviews and portfolio documents. The entire data material was interpreted according to the French philosopher...... Paul Ricoeurs theory of interpretation. This paper reports that the mandatory part promotes consciousness of own learning and competencies in clinical nursing and raises students` consciousness of nurse identity. It gives preceptors the opportunity to differentiate their supervision for individual...

Cooperative learning in the clinical setting.

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Newland, P L

1997-01-01

The modern clinical practice setting presents nurses with challenges about which they must think critically and develop increasingly autonomous problem-solving approaches. It is essential to provide nursing students with opportunities to practice critical thinking so that they can develop this crucial skill. Cooperative learning strategies are interactive teaching methods that stimulate students to think critically, communicate effectively with peers, and accept responsibility for learning through group process activities. Group care planning is one such cooperative strategy that also promotes a positive attitude about care planning and sharpens time management skills. Cooperative assessment and care planning foster the development of critical thinking and effective problem resolution, preparing students for patient care problems they will likely encounter in future positions.

Active Learning Improves Student Performance in a Respiratory Physiology Lab

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Wolf, Alex M.; Liachovitzky, Carlos; Abdullahi, Abass S.

2015-01-01

This study assessed the effectiveness of the introduction of active learning exercises into the anatomy and physiology curriculum in a community college setting. Specifically, the incorporation of a spirometry-based respiratory physiology lab resulted in improved student performance in two concepts (respiratory volumes and the hallmarks of…

Long-term associative learning predicts verbal short-term memory performance.

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Jones, Gary; Macken, Bill

2018-02-01

Studies using tests such as digit span and nonword repetition have implicated short-term memory across a range of developmental domains. Such tests ostensibly assess specialized processes for the short-term manipulation and maintenance of information that are often argued to enable long-term learning. However, there is considerable evidence for an influence of long-term linguistic learning on performance in short-term memory tasks that brings into question the role of a specialized short-term memory system separate from long-term knowledge. Using natural language corpora, we show experimentally and computationally that performance on three widely used measures of short-term memory (digit span, nonword repetition, and sentence recall) can be predicted from simple associative learning operating on the linguistic environment to which a typical child may have been exposed. The findings support the broad view that short-term verbal memory performance reflects the application of long-term language knowledge to the experimental setting.

Does individual learning styles influence the choice to use a web-based ECG learning programme in a blended learning setting?

OpenAIRE

Nilsson, Mikael; ?stergren, Jan; Fors, Uno; Rickenlund, Anette; Jorfeldt, Lennart; Caidahl, Kenneth; Bolinder, Gunilla

2012-01-01

Abstract Background The compressed curriculum in modern knowledge-intensive medicine demands useful tools to achieve approved learning aims in a limited space of time. Web-based learning can be used in different ways to enhance learning. Little is however known regarding its optimal utilisation. Our aim was to investigate if the individual learning styles of medical students influence the choice to use a web-based ECG learning programme in a blended learning setting. Methods The programme, wi...

What's statistical about learning? Insights from modelling statistical learning as a set of memory processes.

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Thiessen, Erik D

2017-01-05

Statistical learning has been studied in a variety of different tasks, including word segmentation, object identification, category learning, artificial grammar learning and serial reaction time tasks (e.g. Saffran et al. 1996 Science 274: , 1926-1928; Orban et al. 2008 Proceedings of the National Academy of Sciences 105: , 2745-2750; Thiessen & Yee 2010 Child Development 81: , 1287-1303; Saffran 2002 Journal of Memory and Language 47: , 172-196; Misyak & Christiansen 2012 Language Learning 62: , 302-331). The difference among these tasks raises questions about whether they all depend on the same kinds of underlying processes and computations, or whether they are tapping into different underlying mechanisms. Prior theoretical approaches to statistical learning have often tried to explain or model learning in a single task. However, in many cases these approaches appear inadequate to explain performance in multiple tasks. For example, explaining word segmentation via the computation of sequential statistics (such as transitional probability) provides little insight into the nature of sensitivity to regularities among simultaneously presented features. In this article, we will present a formal computational approach that we believe is a good candidate to provide a unifying framework to explore and explain learning in a wide variety of statistical learning tasks. This framework suggests that statistical learning arises from a set of processes that are inherent in memory systems, including activation, interference, integration of information and forgetting (e.g. Perruchet & Vinter 1998 Journal of Memory and Language 39: , 246-263; Thiessen et al. 2013 Psychological Bulletin 139: , 792-814). From this perspective, statistical learning does not involve explicit computation of statistics, but rather the extraction of elements of the input into memory traces, and subsequent integration across those memory traces that emphasize consistent information (Thiessen and Pavlik

Can Social Learning Increase Learning Speed, Performance or Both?

NARCIS (Netherlands)

Heinerman, J.V.; Stork, J.; Rebolledo Coy, M.A.; Hubert, J.G.; Eiben, A.E.; Bartz-Beielstein, Thomas; Haasdijk, Evert

2017-01-01

Social learning enables multiple robots to share learned experiences while completing a task. The literature offers contradicting examples of its benefits; robots trained with social learning reach a higher performance, an increased learning speed, or both, compared to their individual learning

Effect of normalization methods on the performance of supervised learning algorithms applied to HTSeq-FPKM-UQ data sets: 7SK RNA expression as a predictor of survival in patients with colon adenocarcinoma.

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Shahriyari, Leili

2017-11-03

One of the main challenges in machine learning (ML) is choosing an appropriate normalization method. Here, we examine the effect of various normalization methods on analyzing FPKM upper quartile (FPKM-UQ) RNA sequencing data sets. We collect the HTSeq-FPKM-UQ files of patients with colon adenocarcinoma from TCGA-COAD project. We compare three most common normalization methods: scaling, standardizing using z-score and vector normalization by visualizing the normalized data set and evaluating the performance of 12 supervised learning algorithms on the normalized data set. Additionally, for each of these normalization methods, we use two different normalization strategies: normalizing samples (files) or normalizing features (genes). Regardless of normalization methods, a support vector machine (SVM) model with the radial basis function kernel had the maximum accuracy (78%) in predicting the vital status of the patients. However, the fitting time of SVM depended on the normalization methods, and it reached its minimum fitting time when files were normalized to the unit length. Furthermore, among all 12 learning algorithms and 6 different normalization techniques, the Bernoulli naive Bayes model after standardizing files had the best performance in terms of maximizing the accuracy as well as minimizing the fitting time. We also investigated the effect of dimensionality reduction methods on the performance of the supervised ML algorithms. Reducing the dimension of the data set did not increase the maximum accuracy of 78%. However, it leaded to discovery of the 7SK RNA gene expression as a predictor of survival in patients with colon adenocarcinoma with accuracy of 78%. © The Author 2017. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com

Performance evaluation of a distance learning program.

OpenAIRE

Dailey, D. J.; Eno, K. R.; Brinkley, J. F.

1994-01-01

This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macint...

Dynamic lighting system for the learning environment: performance of elementary students.

Science.gov (United States)

Choi, Kyungah; Suk, Hyeon-Jeong

2016-05-16

This study aims to investigate the effects of lighting color temperatures on elementary students' performance, and thereby propose a dynamic lighting system for a smart learning environment. Three empirical studies were conducted: First, physiological responses were measured as a potential mediator of performance. Second, cognitive and behavioral responses were observed during academic and recess activities. Lastly, the experiment was carried out in a real-life setting with prolonged exposure. With a comprehensive analysis of the three studies, three lighting presets-3500 K, 5000 K, and 6500 K-are suggested for easy, standard, and intensive activity, respectively. The study is expected to act as a good stepping stone for developing dynamic lighting systems to support students' performance in learning environments.

Performance measures for a dialysis setting.

Science.gov (United States)

Gu, Xiuzhu; Itoh, Kenji

2018-03-01

This study from Japan extracted performance measures for dialysis unit management and investigated their characteristics from professional views. Two surveys were conducted using self-administered questionnaires, in which dialysis managers/staff were asked to rate the usefulness of 44 performance indicators. A total of 255 managers and 2,097 staff responded. Eight performance measures were elicited from dialysis manager and staff responses: these were safety, operational efficiency, quality of working life, financial effectiveness, employee development, mortality, patient/employee satisfaction and patient-centred health care. These performance measures were almost compatible with those extracted in overall healthcare settings in a previous study. Internal reliability, content and construct validity of the performance measures for the dialysis setting were ensured to some extent. As a general trend, both dialysis managers and staff perceived performance measures as highly useful, especially for safety, mortality, operational efficiency and patient/employee satisfaction, but showed relatively low concerns for patient-centred health care and employee development. However, dialysis managers' usefulness perceptions were significantly higher than staff. Important guidelines for designing a holistic hospital/clinic management system were yielded. Performance measures must be balanced for outcomes and performance shaping factors (PSF); a common set of performance measures could be applied to all the healthcare settings, although performance indicators of each measure should be composed based on the application field and setting; in addition, sound causal relationships between PSF and outcome measures/indicators should be explored for further improvement. © 2017 European Dialysis and Transplant Nurses Association/European Renal Care Association.

Learning Agent for a Heat-Pump Thermostat with a Set-Back Strategy Using Model-Free Reinforcement Learning

Directory of Open Access Journals (Sweden)

Frederik Ruelens

2015-08-01

Full Text Available The conventional control paradigm for a heat pump with a less efficient auxiliary heating element is to keep its temperature set point constant during the day. This constant temperature set point ensures that the heat pump operates in its more efficient heat-pump mode and minimizes the risk of activating the less efficient auxiliary heating element. As an alternative to a constant set-point strategy, this paper proposes a learning agent for a thermostat with a set-back strategy. This set-back strategy relaxes the set-point temperature during convenient moments, e.g., when the occupants are not at home. Finding an optimal set-back strategy requires solving a sequential decision-making process under uncertainty, which presents two challenges. The first challenge is that for most residential buildings, a description of the thermal characteristics of the building is unavailable and challenging to obtain. The second challenge is that the relevant information on the state, i.e., the building envelope, cannot be measured by the learning agent. In order to overcome these two challenges, our paper proposes an auto-encoder coupled with a batch reinforcement learning technique. The proposed approach is validated for two building types with different thermal characteristics for heating in the winter and cooling in the summer. The simulation results indicate that the proposed learning agent can reduce the energy consumption by 4%–9% during 100 winter days and by 9%–11% during 80 summer days compared to the conventional constant set-point strategy.

Unifying practice schedules in the timescales of motor learning and performance.

Science.gov (United States)

Verhoeven, F Martijn; Newell, Karl M

2018-06-01

In this article, we elaborate from a multiple time scales model of motor learning to examine the independent and integrated effects of massed and distributed practice schedules within- and between-sessions on the persistent (learning) and transient (warm-up, fatigue) processes of performance change. The timescales framework reveals the influence of practice distribution on four learning-related processes: the persistent processes of learning and forgetting, and the transient processes of warm-up decrement and fatigue. The superposition of the different processes of practice leads to a unified set of effects for massed and distributed practice within- and between-sessions in learning motor tasks. This analysis of the interaction between the duration of the interval of practice trials or sessions and parameters of the introduced time scale model captures the unified influence of the between trial and session scheduling of practice on learning and performance. It provides a starting point for new theoretically based hypotheses, and the scheduling of practice that minimizes the negative effects of warm-up decrement, fatigue and forgetting while exploiting the positive effects of learning and retention. Copyright © 2018 Elsevier B.V. All rights reserved.

Color Modulates Olfactory Learning in Honeybees by an Occasion-Setting Mechanism

Science.gov (United States)

Mota, Theo; Giurfa, Martin; Sandoz, Jean-Christophe

2011-01-01

A sophisticated form of nonelemental learning is provided by occasion setting. In this paradigm, animals learn to disambiguate an uncertain conditioned stimulus using alternative stimuli that do not enter into direct association with the unconditioned stimulus. For instance, animals may learn to discriminate odor rewarded from odor nonrewarded…

Validating YouTube Factors Affecting Learning Performance

Science.gov (United States)

Pratama, Yoga; Hartanto, Rudy; Suning Kusumawardani, Sri

2018-03-01

YouTube is often used as a companion medium or a learning supplement. One of the educational places that often uses is Jogja Audio School (JAS) which focuses on music production education. Music production is a difficult material to learn, especially at the audio mastering. With tutorial contents from YouTube, students find it easier to learn and understand audio mastering and improved their learning performance. This study aims to validate the role of YouTube as a medium of learning in improving student’s learning performance by looking at the factors that affect student learning performance. The sample involves 100 respondents from JAS at audio mastering level. The results showed that student learning performance increases seen from factors that have a significant influence of motivation, instructional content, and YouTube usefulness. Overall findings suggest that YouTube has a important role to student learning performance in music production education and as an innovative and efficient learning medium.

Does personalized goal setting and study planning improve academic performance and perception of learning experience in a developing setting?

Directory of Open Access Journals (Sweden)

Kazeem B. Yusuff, PhD

2018-06-01

�.٢، والاختبارات النصفية ٢١.٩ (الانحراف المعياري = ٣.٧، والاختبارات النهائية ٤٢.٨ (الانحراف المعياري = ٥.٣، وكانت نسبة الإنجاز لأهداف المقرر أ (٧٧٪ و ب (٧٨٪ أعلى بكثير في مجموعة الدراسة. أظهرت التغذية الراجعة لنهاية المقرر اختلافات رئيسة في إدراك تجربة التعلم بين مجموعة الدراسة والمجموعة الضابطة. الاستنتاجات: يبدو أن تحديد الأهداف الشخصية والتخطيط للدراسة يؤدي إلى تحسن كبير في المشاركة المستمرة للتعلم، والتركيز على الأهداف الأكاديمية والأداء الأكاديمي. Abstract: Objective: The learning process for pharmacists must enable the skillful harnessing of metacognition, critical thinking, and effective application of specialized skills. This study assessed the impact of self-developed academic goals and study plans on pharmacy students' academic performance and perception of learning experience in a developing setting. Methods: A prospective cohort study was conducted at the College of Clinical Pharmacy, King Faisal University, KSA, in a compulsory 4th year course (Pharmacy management. The study group was exposed to goal setting and study planning while the control group had only routine teaching and learning activities planned for the course. Academic performance was determined with quizzes, midterm, and final exams, and the percentage achievement for the course objectives. An end-of-course evaluation, with a pre-tested questionnaire, was used to assess the perception of learning experience. Results: The study group constituted 41.4% (29, while 58.6% (41 were in the control group, with a mean ± SD age of 22.9 (SD = 3.2 and 21.6 (SD = 6.1 years, respectively. The mean ± SD scores for quizzes (8.4 (SD = 2

Nursing students' perceptions of their clinical learning environment in placements outside traditional hospital settings.

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Bjørk, Ida T; Berntsen, Karin; Brynildsen, Grethe; Hestetun, Margrete

2014-10-01

To explore students' opinions of the learning environment during clinical placement in settings outside traditional hospital settings. Clinical placement experiences may influence positively on nursing students attitudes towards the clinical setting in question. Most studies exploring the quality of clinical placements have targeted students' experience in hospital settings. The number of studies exploring students' experiences of the learning environment in healthcare settings outside of the hospital venue does not match the growing importance of such settings in the delivery of health care, nor the growing number of nurses needed in these venues. A survey design was used. The Clinical Learning Environment Inventory was administered to two cohorts of undergraduate nursing students (n = 184) after clinical placement in mental health care, home care and nursing home care. Nursing students' overall contentment with the learning environment was quite similar across all three placement areas. Students in mental health care had significantly higher scores on the subscale individualisation, and older students had significantly higher scores on the total scale. Compared with other studies where the Clinical Learning Environment Inventory has been used, the students' total scores in this study are similar or higher than scores in studies including students from hospital settings. Results from this study negate the negative views on clinical placements outside the hospital setting, especially those related to placements in nursing homes and mental healthcare settings. Students' experience of the learning environment during placements in mental health care, home care and nursing homes indicates the relevance of clinical education in settings outside the hospital setting. © 2014 The Authors. Journal of Clinical Nursing published by John Wiley & Sons Ltd.

A learning algorithm for adaptive canonical correlation analysis of several data sets.

Science.gov (United States)

Vía, Javier; Santamaría, Ignacio; Pérez, Jesús

2007-01-01

Canonical correlation analysis (CCA) is a classical tool in statistical analysis to find the projections that maximize the correlation between two data sets. In this work we propose a generalization of CCA to several data sets, which is shown to be equivalent to the classical maximum variance (MAXVAR) generalization proposed by Kettenring. The reformulation of this generalization as a set of coupled least squares regression problems is exploited to develop a neural structure for CCA. In particular, the proposed CCA model is a two layer feedforward neural network with lateral connections in the output layer to achieve the simultaneous extraction of all the CCA eigenvectors through deflation. The CCA neural model is trained using a recursive least squares (RLS) algorithm. Finally, the convergence of the proposed learning rule is proved by means of stochastic approximation techniques and their performance is analyzed through simulations.

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

NARCIS (Netherlands)

Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

2009-01-01

Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. Presentation at the 2nd Workshop Mash-Up Personal Learning

ASSESSMENT OF PERFORMANCES OF VARIOUS MACHINE LEARNING ALGORITHMS DURING AUTOMATED EVALUATION OF DESCRIPTIVE ANSWERS

Directory of Open Access Journals (Sweden)

C. Sunil Kumar

2014-07-01

Full Text Available Automation of descriptive answers evaluation is the need of the hour because of the huge increase in the number of students enrolling each year in educational institutions and the limited staff available to spare their time for evaluations. In this paper, we use a machine learning workbench called LightSIDE to accomplish auto evaluation and scoring of descriptive answers. We attempted to identify the best supervised machine learning algorithm given a limited training set sample size scenario. We evaluated performances of Bayes, SVM, Logistic Regression, Random forests, Decision stump and Decision trees algorithms. We confirmed SVM as best performing algorithm based on quantitative measurements across accuracy, kappa, training speed and prediction accuracy with supplied test set.

Mixed-Effects Modeling of Neurofeedback Self-Regulation Performance: Moderators for Learning in Children with ADHD.

Science.gov (United States)

Zuberer, Agnieszka; Minder, Franziska; Brandeis, Daniel; Drechsler, Renate

2018-01-01

Neurofeedback (NF) has gained increasing popularity as a training method for children and adults with attention deficit hyperactivity disorder (ADHD). However, it is unclear to what extent children learn to regulate their brain activity and in what way NF learning may be affected by subject- and treatment-related factors. In total, 48 subjects with ADHD (age 8.5-16.5 years; 16 subjects on methylphenidate (MPH)) underwent 15 double training sessions of NF in either a clinical or a school setting. Four mixed-effects models were employed to analyze learning: training within-sessions, across-sessions, with continuous feedback, and with transfer in which performance feedback is delayed. Age and MPH affected the NF performance in all models. Cross-session learning in the feedback condition was mainly moderated by age and MPH, whereas NF learning in the transfer condition was mainly boosted by MPH. Apart from IQ and task types, other subject-related or treatment-related effects were unrelated to NF learning. This first study analyzing moderators of NF learning in ADHD with a mixed-effects modeling approach shows that NF performance is moderated differentially by effects of age and MPH depending on the training task and time window. Future studies may benefit from using this approach to analyze NF learning and NF specificity. The trial name Neurofeedback and Computerized Cognitive Training in Different Settings for Children and Adolescents With ADHD is registered with NCT02358941.

Performance of machine-learning scoring functions in structure-based virtual screening.

Science.gov (United States)

Wójcikowski, Maciej; Ballester, Pedro J; Siedlecki, Pawel

2017-04-25

Classical scoring functions have reached a plateau in their performance in virtual screening and binding affinity prediction. Recently, machine-learning scoring functions trained on protein-ligand complexes have shown great promise in small tailored studies. They have also raised controversy, specifically concerning model overfitting and applicability to novel targets. Here we provide a new ready-to-use scoring function (RF-Score-VS) trained on 15 426 active and 893 897 inactive molecules docked to a set of 102 targets. We use the full DUD-E data sets along with three docking tools, five classical and three machine-learning scoring functions for model building and performance assessment. Our results show RF-Score-VS can substantially improve virtual screening performance: RF-Score-VS top 1% provides 55.6% hit rate, whereas that of Vina only 16.2% (for smaller percent the difference is even more encouraging: RF-Score-VS top 0.1% achieves 88.6% hit rate for 27.5% using Vina). In addition, RF-Score-VS provides much better prediction of measured binding affinity than Vina (Pearson correlation of 0.56 and -0.18, respectively). Lastly, we test RF-Score-VS on an independent test set from the DEKOIS benchmark and observed comparable results. We provide full data sets to facilitate further research in this area (http://github.com/oddt/rfscorevs) as well as ready-to-use RF-Score-VS (http://github.com/oddt/rfscorevs_binary).

Blended Learning in Obstetrics and Gynecology Resident Education: Impact on Resident Clinical Performance.

Science.gov (United States)

Ghareeb, Allen; Han, Heeyoung; Delfino, Kristin; Taylor, Funminiyi

2016-01-01

Effects of residents' blended learning on their clinical performance have rarely been reported. A blended learning pilot program was instituted at Southern Illinois University School of Medicine's Obstetrics and Gynecology program. One of the modules was chronic hypertension in pregnancy. We sought to evaluate if the resident blended learning was transferred to their clinical performance six months after the module. A review of patient charts demonstrated inadequate documentation of history, evaluation, and counseling of patients with chronic hypertension at the first prenatal visit by Obstetrics and Gynecology (OB/GYN) residents. A blended learning module on chronic hypertension in pregnancy was then provided to the residents. A retrospective chart review was then performed to assess behavioral changes in the OB/GYN residents. This intervention was carried out at the Department of Obstetrics and Gynecology, Southern Illinois University. All 16 OB/GYN residents were enrolled in this module as part of their educational curriculum. A query of all prenatal patients diagnosed with chronic hypertension presenting to the OB/GYN resident clinics four months prior to the implementation of the blended learning module (March 2015-June 2015) and six months after (July 20, 2015-February 2016) was performed. Data were collected from outpatient charts utilizing the electronic medical record. Data were abstracted from resident documentation at the first prenatal visit. The residents thought that the blended learning module was applicable to performance improvement in the real-world setting. Patients evaluated before ( n = 10) and after ( n = 7) the intervention were compared. After the intervention, there was an increase in assessment of baseline liver enzymes, referral for electrocardiogram, and early assessment for diabetes in the obese patients. More patients were provided a blood pressure cuff after the module (71.4% vs. 20%). Data were provided to the residents in an

Identifying Learning Preferences in Vocational Education and Training Classroom Settings

Science.gov (United States)

Smith, Peter J.

2006-01-01

This research was designed to assess whether teachers and trainers of vocational learners noted and valued differences in individual learning preferences and, if so, how those differences were observed in natural classroom, workshop or other formal learning settings. Data were collected from six vocational education and training (VET) learning…

The effectiveness of flipped classroom learning model in secondary physics classroom setting

Science.gov (United States)

Prasetyo, B. D.; Suprapto, N.; Pudyastomo, R. N.

2018-03-01

The research aimed to describe the effectiveness of flipped classroom learning model on secondary physics classroom setting during Fall semester of 2017. The research object was Secondary 3 Physics group of Singapore School Kelapa Gading. This research was initiated by giving a pre-test, followed by treatment setting of the flipped classroom learning model. By the end of the learning process, the pupils were given a post-test and questionnaire to figure out pupils' response to the flipped classroom learning model. Based on the data analysis, 89% of pupils had passed the minimum criteria of standardization. The increment level in the students' mark was analysed by normalized n-gain formula, obtaining a normalized n-gain score of 0.4 which fulfil medium category range. Obtains from the questionnaire distributed to the students that 93% of students become more motivated to study physics and 89% of students were very happy to carry on hands-on activity based on the flipped classroom learning model. Those three aspects were used to generate a conclusion that applying flipped classroom learning model in Secondary Physics Classroom setting is effectively applicable.

Peer assisted learning in the clinical setting: an activity systems analysis

OpenAIRE

Bennett, Deirdre; O?Flynn, Siun; Kelly, Martina

2014-01-01

Peer assisted learning (PAL) is a common feature of medical education. Understanding of PAL has been based on processes and outcomes in controlled settings, such as clinical skills labs. PAL in the clinical setting, a complex learning environment, requires fresh evaluation. Socio-cultural theory is proposed as a means to understand educational interventions in ways that are practical and meaningful. We describe the evaluation of a PAL intervention, introduced to support students? transition i...

Developing a service improvement initiative for people with learning disabilities in hospice settings.

Science.gov (United States)

Springall, Fiona

2018-03-21

People with learning disabilities are often marginalised in healthcare, including in hospice settings, and as a result may not receive effective end of life care. Research in hospice settings has identified that many staff lack confidence, skills and knowledge in caring for people with learning disabilities, which can have a negative effect on the care these individuals receive. To address these issues, the author has proposed a service improvement initiative, which she developed as part of her learning disability nursing degree programme. This proposed initiative aimed to enhance end of life care for people with learning disabilities through the implementation of a community learning disability link nurse in the hospice setting. ©2018 RCN Publishing Company Ltd. All rights reserved. Not to be copied, transmitted or recorded in any way, in whole or part, without prior permission of the publishers.

Pengaruh Learning Climate Terhadap Job Performance Melalui Career Related Continuous Learning

OpenAIRE

Anggiani, Sarfilianty

2017-01-01

This research objective is to identify and to analyze the relatioship of Learning climatehas an influence on Job Performance through the Career Related Continuous Learning. The result of the study showed that Learning climate influenced Job Performance through the career related continuous learning. Managerial implication and the recommendation for future study are provided.

Collaborative teacher learning in different primary school settings

NARCIS (Netherlands)

Doppenberg, J.J.; Bakx, A.W.E.A.; Brok, den P.J.

2012-01-01

During the last two decades there has been a growing awareness of the potentially strong role teacher collaboration can play in relation to teacher and team learning. Teachers collaborate with their colleagues in different formal and informal settings. Because most studies have focused on teacher

The use of blogging in tertiary healthcare educational settings to enhance reflective learning in nursing leadership.

Science.gov (United States)

Levine, Theodora C

2014-01-01

Web 2.0 technologies such as blogs are increasingly used in academic settings; however, they are not widely used in hospital settings. This project explored the effectiveness of using a blog to enhance reflective learning in a nurse manager leadership development course of a tertiary care hospital setting. Differences in reflective learning between the blog group and traditional learning group were measured post training using a Reflective Learning and Interaction Questionnaire. Although the groups did not differ significantly on any reflective learning dimension (p educators contemplating to incorporate blogs into their learning strategies to enhance reflective learning.

Future goal setting, task motivation and learning of minority and non-minority students in Dutch schools.

Science.gov (United States)

Andriessen, Iris; Phalet, Karen; Lens, Willy

2006-12-01

Cross-cultural research on minority school achievement yields mixed findings on the motivational impact of future goal setting for students from disadvantaged minority groups. Relevant and recent motivational research, integrating Future Time Perspective Theory with Self-Determination Theory, has not yet been validated among minority students. To replicate across cultures the known motivational benefits of perceived instrumentality and internal regulation by distant future goals; to clarify when and how the future motivates minority students' educational performance. Participants in this study were 279 minority students (100 of Turkish and 179 of Moroccan origin) and 229 native Dutch students in Dutch secondary schools. Participants rated the importance of future goals, their perceptions of instrumentality, their task motivation and learning strategies. Dependent measures and their functional relations with future goal setting were simultaneously validated across minority and non-minority students, using structural equation modelling in multiple groups. As expected, Positive Perceived Instrumentality for the future increases task motivation and (indirectly) adaptive learning of both minority and non-minority students. But especially internally regulating future goals are strongly related to more task motivation and indirectly to more adaptive learning strategies. Our findings throw new light on the role of future goal setting in minority school careers: distant future goals enhance minority and non-minority students' motivation and learning, if students perceive positive instrumentality and if their schoolwork is internally regulated by future goals.

Monitoring of Students' Interaction in Online Learning Settings by Structural Network Analysis and Indicators.

Science.gov (United States)

Ammenwerth, Elske; Hackl, Werner O

2017-01-01

Learning as a constructive process works best in interaction with other learners. Support of social interaction processes is a particular challenge within online learning settings due to the spatial and temporal distribution of participants. It should thus be carefully monitored. We present structural network analysis and related indicators to analyse and visualize interaction patterns of participants in online learning settings. We validate this approach in two online courses and show how the visualization helps to monitor interaction and to identify activity profiles of learners. Structural network analysis is a feasible approach for an analysis of the intensity and direction of interaction in online learning settings.

Performance of Blended Learning in University Teaching:

Directory of Open Access Journals (Sweden)

Michael Reiss

2010-07-01

Full Text Available Blended learning as a combination of classroom teaching and e-learning has become a widely represented standard in employee and management development of companies. The exploratory survey “Blended Learning@University” conducted in 2008 investigated the integration of blended learning in higher education. The results of the survey show that the majority of participating academic teachers use blended learning in single courses, but not as a program of study and thus do not exploit the core performance potential of blended learning. According to the study, the main driver of blended learning performance is its embeddedness in higher education. Integrated blended programs of study deliver the best results. In blended learning, learning infrastructure (in terms of software, culture, skills, funding, content providing, etc. does not play the role of a performance driver but serves as an enabler for blended learning.

Influence of course characteristics, student characteristics, and behavior in learning management systems on student performance

OpenAIRE

Conijn, Rianne; Kleingeld, Ad; Matzat, Uwe; Snijders, Chris; van Zaanen, Menno

2016-01-01

The use of learning management systems (LMS) in education make it possible to track students’ online behavior. This data can be used for educational data mining and learning analytics, for example, by predicting student performance. Although LMS data might contain useful predictors, course characteristics and student characteristics have shown to influence student performance as well. However, these different sets of features are rarely combined or compared. Therefore, in the current study we...

Perceived impact on student engagement when learning middle school science in an outdoor setting

Science.gov (United States)

Abbatiello, James

Human beings have an innate need to spend time outside, but in recent years children are spending less time outdoors. It is possible that this decline in time spent outdoors could have a negative impact on child development. Science teachers can combat the decline in the amount of time children spend outside by taking their science classes outdoors for regular classroom instruction. This study identified the potential impacts that learning in an outdoor setting might have on student engagement when learning middle school science. One sixth-grade middle school class participated in this case study, and students participated in outdoor intervention lessons where the instructional environment was a courtyard on the middle school campus. The outdoor lessons consisted of the same objectives and content as lessons delivered in an indoor setting during a middle school astronomy unit. Multiple sources of data were collected including questionnaires after each lesson, a focus group, student work samples, and researcher observations. The data was triangulated, and a vignette was written about the class' experiences learning in an outdoor setting. This study found that the feeling of autonomy and freedom gained by learning in an outdoor setting, and the novelty of the outdoor environment did increase student engagement for learning middle school science. In addition, as a result of this study, more work is needed to identify how peer to peer relationships are impacted by learning outdoors, how teachers could best utilize the outdoor setting for regular science instruction, and how learning in an outdoor setting might impact a feeling of stewardship for the environment in young adults.

Undergraduate teaching in geriatric medicine using computer-aided learning improves student performance in examinations.

Science.gov (United States)

Daunt, Laura A; Umeonusulu, Patience I; Gladman, John R F; Blundell, Adrian G; Conroy, Simon P; Gordon, Adam L

2013-07-01

computer-aided learning (CAL) is increasingly used to deliver teaching, but few studies have evaluated its impact on learning within geriatric medicine. We developed and implemented CAL packages on falls and continence, and evaluated their effect on student performance in two medical schools. traditional ward based and didactic teaching was replaced by blended learning (CAL package combined with traditional teaching methods). Examination scores were compared for cohorts of medical students receiving traditional learning and those receiving blended learning. Control questions were included to provide data on cohort differences. in both medical schools, there was a trend towards improved scores following blended learning, with a smaller number of students achieving low scores (P learning was associated with improvement in student examination performance, regardless of the setting or the methods adopted, and without increasing teaching time. Our findings support the use of CAL in teaching geriatric medicine, and this method has been adopted for teaching other topics in the undergraduate curriculum.

Workplace Learning by Action Learning: A Practical Example.

Science.gov (United States)

Miller, Peter

2003-01-01

An action learning approach to help managers enhance learning capacity involved a performance management seminar, work by action learning sets, implementation of a new performance management instrument with mentoring by action learning facilitators, and evaluation. Survey responses from 392 participants revealed satisfaction with managerial…

Narratives of social justice: learning in innovative clinical settings.

Science.gov (United States)

Reimer Kirkham, Sheryl; Van Hofwegen, Lynn; Hoe Harwood, Catherine

2005-01-01

The nursing profession has renewed its commitment to social and political mandates, resulting in increasing attention to issues pertaining to diversity, vulnerable populations, social determinants of health, advocacy and activism, and social justice in nursing curricula. Narratives from a qualitative study examining undergraduate nursing student learning in five innovative clinical settings (corrections, international, parish, rural, and aboriginal) resonate with these curricular emphases. Data were derived from focus groups and interviews with 65 undergraduate nursing students, clinical instructors, and RN mentors. Findings of this study reveal how students in innovative clinical placements bear witness to poverty, inequities, and marginalization (critical awareness), often resulting in dissonance and soul-searching (critical engagement), and a renewed commitment to social transformation (social change). These findings suggest the potential for transformative learning in these settings.

Do action learning sets facilitate collaborative, deliberative learning?: A focus group evaluation of Graduate Entry Pre-registration Nursing (GEN) students' experience.

Science.gov (United States)

Maddison, Charlotte; Strang, Gus

2018-01-01

The aim of this study was to investigate if by participating in action learning sets, Graduate Entry Pre-registration Nursing (GEN) students were able to engage in collaborative and deliberative learning. A single focus group interview involving eleven participants was used to collect data. Data analysis identified five themes; collaborative learning; reflection; learning through case study and problem-solving; communication, and rejection of codified learning. The themes are discussed and further analysed in the context of collaborative and deliberative learning. The evidence from this small scale study suggests that action learning sets do provide an environment where collaborative and deliberative learning can occur. However, students perceived some of them, particularly during year one, to be too 'teacher lead', which stifled learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Study of Machine-Learning Classifier and Feature Set Selection for Intent Classification of Korean Tweets about Food Safety

Directory of Open Access Journals (Sweden)

Yeom, Ha-Neul

2014-09-01

Full Text Available In recent years, several studies have proposed making use of the Twitter micro-blogging service to track various trends in online media and discussion. In this study, we specifically examine the use of Twitter to track discussions of food safety in the Korean language. Given the irregularity of keyword use in most tweets, we focus on optimistic machine-learning and feature set selection to classify collected tweets. We build the classifier model using Naive Bayes & Naive Bayes Multinomial, Support Vector Machine, and Decision Tree Algorithms, all of which show good performance. To select an optimum feature set, we construct a basic feature set as a standard for performance comparison, so that further test feature sets can be evaluated. Experiments show that precision and F-measure performance are best when using a Naive Bayes Multinomial classifier model with a test feature set defined by extracting Substantive, Predicate, Modifier, and Interjection parts of speech.

Illustrating performance indicators and course characteristics to support students' self-regulated learning in CS1

Science.gov (United States)

Ott, Claudia; Robins, Anthony; Haden, Patricia; Shephard, Kerry

2015-04-01

In higher education, quality feedback for students is regarded as one of the main contributors to improve student learning. Feedback to support students' development into self-regulated learners, who set their own goals, self-monitor their actual performance according to these goals, and adjust learning strategies if necessary, is seen as an important aspect of contemporary feedback practice. However, only those students who are aware of the course demands and the impact of certain study behaviors on their final achievement are in a position to self-regulate their learning on an informed basis. Learning analytics is an emerging field primarily concerned with using predictive models to inform educational instructors or learners about projected study outcomes. In a scoping study, over 200 students of an introductory programming course (CS1) were supplied with information revealing performance indicators for different stages on the course and projecting final performance for various achievement levels. The study was set out to explore the impact of this type of feedback in the confined context of a CS1 course as well as to learn about students' attitudes toward diagnostic course data in general. The results from the study suggest that students valued the information, but, despite high engagement with the information, students' study behavior and learning outcome remained rather unaffected for the aspects investigated. Given these multi-layered results, we suggest further exploration on the provision of feedback based on diagnostic course data - a vital step toward more transparency for students to foster their active role in the learning process.

Performance on a strategy set shifting task during adolescence in a genetic model of attention deficit/hyperactivity disorder: Methylphenidate vs. atomoxetine treatments

Science.gov (United States)

Harvey, Roxann C; Jordan, Chloe J; Tassin, David H; Moody, Kayla R; Dwoskin, Linda P; Kantak, Kathleen M

2013-01-01

Research examining medication effects on set shifting in teens with attention deficit/hyperactivity disorder (ADHD) is lacking. An animal model of ADHD may be useful for exploring this gap. The Spontaneously Hypertensive Rat (SHR) is a commonly used animal model of ADHD. SHR and two comparator strains, Wistar-Kyoto (WKY) and Wistar (WIS), were evaluated during adolescence in a strategy set shifting task under conditions of a 0-sec or 15-sec delay to reinforcer delivery. The task had three phases: initial discrimination, set shift and reversal learning. Under 0-sec delays, SHR performed as well as or better than WKY and WIS. Treatment with 0.3 mg/kg/day atomoxetine had little effect, other than to modestly increase trials to criterion during set shifting in all strains. Under 15-sec delays, SHR had longer lever press reaction times, longer latencies to criterion and more trial omissions than WKY during set shifting and reversal learning. These deficits were not reduced systematically by 1.5 mg/kg/day methylphenidate or 0.3 mg/kg/day atomoxetine. Regarding learning in SHR, methylphenidate improved initial discrimination, whereas atomoxetine improved set shifting but disrupted initial discrimination. During reversal learning, both drugs were ineffective in SHR, and atomoxetine made reaction time and trial omissions greater in WKY. Overall, WIS performance differed from SHR or WKY, depending on phase. Collectively, a genetic model of ADHD in adolescent rats revealed that neither methylphenidate nor atomoxetine mitigated all deficits in SHR during the set shifting task. Thus, methylphenidate or atomoxetine monotherapy may not mitigate all set shift task-related deficits in teens with ADHD. PMID:23376704

A Field Study of a Video Supported Seamless-Learning-Setting with Elementary Learners

Science.gov (United States)

Fößl, Thomas; Ebner, Martin; Schön, Sandra; Holzinger, Andreas

2016-01-01

Seamless Learning shall initiate human learning processes that exceeds lesson and classroom limits. At the same time this approach fosters a self-regulated learning, by means of inspirational, open education settings. Advanced learning materials are easily accessible via mobile digital devices connected to the Internet. In this study it was…

The Impact of Problem Sets on Student Learning

Science.gov (United States)

Kim, Myeong Hwan; Cho, Moon-Heum; Leonard, Karen Moustafa

2012-01-01

The authors examined the role of problem sets on student learning in university microeconomics. A total of 126 students participated in the study in consecutive years. independent samples t test showed that students who were not given answer keys outperformed students who were given answer keys. Multiple regression analysis showed that, along with…

Learning Environment And Pupils Academic Performance ...

African Journals Online (AJOL)

Learning Environment And Pupils Academic Performance: Implications For Counselling. ... facilities as well as learning materials to make teaching and learning easy. In addition, teachers should provide conducive classroom environment to ...

The use of Edmodo in teaching writing in a blended learning setting

OpenAIRE

Pupung Purnawarman; Susilawati Susilawati; Wachyu Sundayana

2016-01-01

The advancement of technology provides education with varioussolutions to create new learning environments. Edmodo as a learning platform is believed to offera solution in the teaching of English, particularly for teaching writing. This research was aimed to investigate how Edmodo as a learning platform,in a blended learning setting, was implemented in teaching writing in its combination with Genre-based Approach, how Edmodo facilitated students’ engagement, and how students perceived the use...

An Integrative Model of Organizational Learning and Social Capital on Effective Knowledge Transfer and Perceived Organizational Performance

Science.gov (United States)

Rhodes, Jo; Lok, Peter; Hung, Richard Yu-Yuan; Fang, Shih-Chieh

2008-01-01

Purpose: The purpose of this paper is to set out to examine the relationships of organizational learning, social capital and the effectiveness of knowledge transfer and perceived organisational performance. Integrating organizational learning capability with social capital networks to shape a holistic knowledge sharing and management enterprise…

Installing and Setting Up Git Software Tool on Windows | High-Performance

Science.gov (United States)

Computing | NREL Git Software Tool on Windows Installing and Setting Up Git Software Tool on Windows Learn how to set up the Git software tool on Windows for use with the Peregrine system. Git is this doc, we'll show you how to get git installed on Windows 7, and how to get things set up on NREL's

Investigating the Relationship between Learning Styles and ESP Reading Strategies in Academic Setting

OpenAIRE

Parviz Ajideh; Mohammad Zohrabi; Kazem Pouralvar

2018-01-01

The present study investigated the relationship between Art and Science students’ learning styles and their ESP reading strategies in academic settings. Learning styles are defined as general orientations learners take toward their learning experiences. This notion has recently obtained attention in the area of language learning. Strategies are also defined as specific behaviours or techniques learners employ towards leaning in order to achieve their learning goals. The strategies chosen are ...

ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings

NARCIS (Netherlands)

Drachsler, Hendrik; Pecceu, Dries; Arts, Tanja; Hutten, Edwin; Rutledge, Lloyd; Van Rosmalen, Peter; Hummel, Hans; Koper, Rob

2009-01-01

Drachsler, H., Peccau, D., Arts, T., Hutten, E., Rutledge, L., Van Rosmalen, P., Hummel, H. G. K., & Koper, R. (2009). ReMashed – Recommendation Approaches for Mash-Up Personal Learning Environments in Formal and Informal Learning Settings. In F. Wild, M. Kalz, M. Palmér & D. Müller (Eds.),

Features of an effective operative dentistry learning environment: students' perceptions and relationship with performance.

Science.gov (United States)

Suksudaj, N; Lekkas, D; Kaidonis, J; Townsend, G C; Winning, T A

2015-02-01

Students' perceptions of their learning environment influence the quality of outcomes they achieve. Learning dental operative techniques in a simulated clinic environment is characterised by reciprocal interactions between skills training, staff- and student-related factors. However, few studies have examined how students perceive their operative learning environments and whether there is a relationship between their perceptions and subsequent performance. Therefore, this study aimed to clarify which learning activities and interactions students perceived as supporting their operative skills learning and to examine relationships with their outcomes. Longitudinal data about examples of operative laboratory sessions that were perceived as effective or ineffective for learning were collected twice a semester, using written critical incidents and interviews. Emergent themes from these data were identified using thematic analysis. Associations between perceptions of learning effectiveness and performance were analysed using chi-square tests. Students indicated that an effective learning environment involved interactions with tutors and peers. This included tutors arranging group discussions to clarify processes and outcomes, providing demonstrations and constructive feedback. Feedback focused on mistakes, and not improvement, was reported as being ineffective for learning. However, there was no significant association between students' perceptions of the effectiveness of their learning experiences and subsequent performance. It was clear that learning in an operative technique setting involved various factors related not only to social interactions and observational aspects of learning but also to cognitive, motivational and affective processes. Consistent with studies that have demonstrated complex interactions between students, their learning environment and outcomes, other factors need investigation. © 2014 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.

Pengaruh Goal Setting terhadap Performance : Tinjauan Teoritis

OpenAIRE

Ginting, Surya Dharma; Ariani, D. Wahyu

2004-01-01

This article is the conceptual view of goal setting theory and effects of goal setting on individual performance. Goal setting is recognized, and is a major theory of work motivation. Difficult goals have consistently been shown to lead to higher levels of performance than easy goals. If there is no commitment, a goal can have no motivational effect. Goals are central to current treatments of work motivation, and goal commitment is a necessary condition for difficult goals to result in higher...

Interactive Role of Organizational Learning and Informal Norms in Accountability and Job Performance in 2014

Directory of Open Access Journals (Sweden)

Abolfazl Ghasemzadeh

2015-09-01

Full Text Available Introduction: Although the contribution of organizational learning to employee organizational performance is well documented, the mechanisms that explain such relationship remain unclear. Accordingly, the purpose of this paper is to investigate the interactional role of organizational learning and informal norms in accountability and job performance of the staff in a medical department. Methods: The research method of the study is descriptive-correlational type. The statistical population of this study included all staff (N=315 of the Medical Department in Oshnavieh Hospital in 2014. For data gathering in this study, a sample comprising of 180 staff was selected using stratified random sampling. The data were collected through standard questionnaires of Neefe for organizational learning, informal norms of Hall, job performance of Paterson, and the questionnaire of individual accountability of Hochwarter. Pearson and moderated multiple regression analysis were used to test hypotheses. Results: Results showed that organizational learning has a positive and significant correlation with job performance and individual accountability. The results, also, showed a positive and significant correlation between informal norms, personal accountability, and job performance. Regression results showed the interactive role of learning structure dimensions, strategy, and shared vision with informal norms, predicting individual accountability of the staff. Also, interactive role of organizational learning and informal norms was confirmed in predicting job performance of the medical staff. Conclusion: The result of this study hold out that organizational learning directly and with interaction of informal norms improves staffs' performance and accountability. As a result of improved informal norms in a medical setting, we will have staff’s strong accountability and performance.

Challenge and Hindrance Stress: Relationships with Exhaustion, Motivation to Learn, and Learning Performance

Science.gov (United States)

LePine, Jeffrey A.; LePine, Marcie A.; Jackson, Christine L.

2004-01-01

In a study of 696 learners, the authors found that stress associated with challenges in the learning environment had a positive relationship with learning performance and that stress associated with hindrances in the learning environment had a negative relationship with learning performance. They also found evidence suggesting that these…

Comparison of combinatorial clustering methods on pharmacological data sets represented by machine learning-selected real molecular descriptors.

Science.gov (United States)

Rivera-Borroto, Oscar Miguel; Marrero-Ponce, Yovani; García-de la Vega, José Manuel; Grau-Ábalo, Ricardo del Corazón

2011-12-27

Cluster algorithms play an important role in diversity related tasks of modern chemoinformatics, with the widest applications being in pharmaceutical industry drug discovery programs. The performance of these grouping strategies depends on various factors such as molecular representation, mathematical method, algorithmical technique, and statistical distribution of data. For this reason, introduction and comparison of new methods are necessary in order to find the model that best fits the problem at hand. Earlier comparative studies report on Ward's algorithm using fingerprints for molecular description as generally superior in this field. However, problems still remain, i.e., other types of numerical descriptions have been little exploited, current descriptors selection strategy is trial and error-driven, and no previous comparative studies considering a broader domain of the combinatorial methods in grouping chemoinformatic data sets have been conducted. In this work, a comparison between combinatorial methods is performed,with five of them being novel in cheminformatics. The experiments are carried out using eight data sets that are well established and validated in the medical chemistry literature. Each drug data set was represented by real molecular descriptors selected by machine learning techniques, which are consistent with the neighborhood principle. Statistical analysis of the results demonstrates that pharmacological activities of the eight data sets can be modeled with a few of families with 2D and 3D molecular descriptors, avoiding classification problems associated with the presence of nonrelevant features. Three out of five of the proposed cluster algorithms show superior performance over most classical algorithms and are similar (or slightly superior in the most optimistic sense) to Ward's algorithm. The usefulness of these algorithms is also assessed in a comparative experiment to potent QSAR and machine learning classifiers, where they perform

Motivation, learning strategies, participation and medical school performance.

Science.gov (United States)

Stegers-Jager, Karen M; Cohen-Schotanus, Janke; Themmen, Axel P N

2012-07-01

Medical schools wish to better understand why some students excel academically and others have difficulty in passing medical courses. Components of self-regulated learning (SRL), such as motivational beliefs and learning strategies, as well as participation in scheduled learning activities, have been found to relate to student performance. Although participation may be a form of SRL, little is known about the relationships among motivational beliefs, learning strategies, participation and medical school performance. This study aimed to test and cross-validate a hypothesised model of relationships among motivational beliefs (value and self-efficacy), learning strategies (deep learning and resource management), participation (lecture attendance, skills training attendance and completion of optional study assignments) and Year 1 performance at medical school. Year 1 medical students in the cohorts of 2008 (n = 303) and 2009 (n = 369) completed a questionnaire on motivational beliefs and learning strategies (sourced from the Motivated Strategies for Learning Questionnaire) and participation. Year 1 performance was operationalised as students' average Year 1 course examination grades. Structural equation modelling was used to analyse the data. Participation and self-efficacy beliefs were positively associated with Year 1 performance (β = 0.78 and β = 0.19, respectively). Deep learning strategies were negatively associated with Year 1 performance (β =- 0.31), but positively related to resource management strategies (β = 0.77), which, in turn, were positively related to participation (β = 0.79). Value beliefs were positively related to deep learning strategies only (β = 0.71). The overall structural model for the 2008 cohort accounted for 47% of the variance in Year 1 grade point average and was cross-validated in the 2009 cohort. This study suggests that participation mediates the relationships between motivation and learning strategies, and medical school

Learning Styles and Student Performance in Introductory Economics

Science.gov (United States)

Brunton, Bruce

2015-01-01

Data from nine introductory microeconomics classes was used to test the effect of student learning style on academic performance. The Kolb Learning Style Inventory was used to assess individual student learning styles. The results indicate that student learning style has no significant effect on performance, undermining the claims of those who…

From performance measurement to learning

DEFF Research Database (Denmark)

Lewis, Jenny; Triantafillou, Peter

2012-01-01

Over the last few decades accountability has accommodated an increasing number of different political, legal and administrative goals. This article focuses on the administrative aspect of accountability and explores the potential perils of a shift from performance measurement to learning. While...... overload. We conclude with some comments on limiting the undesirable consequences of such a move. Points for practitioners Public administrators need to identify and weigh the (human, political and economic) benefits and costs of accountability regimes. While output-focused performance measurement regimes...... to comply with accountability requirements, because of the first point. Third, the costs of compliance are likely to increase because learning requires more participation and dialogue. Fourth, accountability as learning may generate a ‘change for the sake of change’ mentality, creating further government...

Performance evaluation of a distance learning program.

Science.gov (United States)

Dailey, D J; Eno, K R; Brinkley, J F

1994-01-01

This paper presents a performance metric which uses a single number to characterize the response time for a non-deterministic client-server application operating over the Internet. When applied to a Macintosh-based distance learning application called the Digital Anatomist Browser, the metric allowed us to observe that "A typical student doing a typical mix of Browser commands on a typical data set will experience the same delay if they use a slow Macintosh on a local network or a fast Macintosh on the other side of the country accessing the data over the Internet." The methodology presented is applicable to other client-server applications that are rapidly appearing on the Internet.

The Impact of Institutional Settings on Learning Behavior by Venture Capitalists and Start-Ups

DEFF Research Database (Denmark)

Gatti, Anna; Vendelø, Morten Thanning

2005-01-01

differen-ces in local institutional settings affect learning and adaptation by European venture ca-pitalists and start-ups, and thus, affect the processes of field formation. For example, it has been observed that institutional settings can facilitate or discourage learning from direct experience (Herriot...... is to understand if and how US venture capitalism affect the evolvement of venture capitalism in Europe. We study the emergence of a venture capitalist industry in Denmark and Italy, and thus, by selecting two countries with distinctive differences in cultures and institutions, we study learning and adaptation...

Machine Learning for Neuroimaging with Scikit-Learn

Directory of Open Access Journals (Sweden)

Alexandre eAbraham

2014-02-01

Full Text Available Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g. multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g. resting state functional MRI or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Machine learning for neuroimaging with scikit-learn.

Science.gov (United States)

Abraham, Alexandre; Pedregosa, Fabian; Eickenberg, Michael; Gervais, Philippe; Mueller, Andreas; Kossaifi, Jean; Gramfort, Alexandre; Thirion, Bertrand; Varoquaux, Gaël

2014-01-01

Statistical machine learning methods are increasingly used for neuroimaging data analysis. Their main virtue is their ability to model high-dimensional datasets, e.g., multivariate analysis of activation images or resting-state time series. Supervised learning is typically used in decoding or encoding settings to relate brain images to behavioral or clinical observations, while unsupervised learning can uncover hidden structures in sets of images (e.g., resting state functional MRI) or find sub-populations in large cohorts. By considering different functional neuroimaging applications, we illustrate how scikit-learn, a Python machine learning library, can be used to perform some key analysis steps. Scikit-learn contains a very large set of statistical learning algorithms, both supervised and unsupervised, and its application to neuroimaging data provides a versatile tool to study the brain.

Optimizing Distributed Machine Learning for Large Scale EEG Data Set

Directory of Open Access Journals (Sweden)

M Bilal Shaikh

2017-06-01

Full Text Available Distributed Machine Learning (DML has gained its importance more than ever in this era of Big Data. There are a lot of challenges to scale machine learning techniques on distributed platforms. When it comes to scalability, improving the processor technology for high level computation of data is at its limit, however increasing machine nodes and distributing data along with computation looks as a viable solution. Different frameworks   and platforms are available to solve DML problems. These platforms provide automated random data distribution of datasets which miss the power of user defined intelligent data partitioning based on domain knowledge. We have conducted an empirical study which uses an EEG Data Set collected through P300 Speller component of an ERP (Event Related Potential which is widely used in BCI problems; it helps in translating the intention of subject w h i l e performing any cognitive task. EEG data contains noise due to waves generated by other activities in the brain which contaminates true P300Speller. Use of Machine Learning techniques could help in detecting errors made by P300 Speller. We are solving this classification problem by partitioning data into different chunks and preparing distributed models using Elastic CV Classifier. To present a case of optimizing distributed machine learning, we propose an intelligent user defined data partitioning approach that could impact on the accuracy of distributed machine learners on average. Our results show better average AUC as compared to average AUC obtained after applying random data partitioning which gives no control to user over data partitioning. It improves the average accuracy of distributed learner due to the domain specific intelligent partitioning by the user. Our customized approach achieves 0.66 AUC on individual sessions and 0.75 AUC on mixed sessions, whereas random / uncontrolled data distribution records 0.63 AUC.

THE USE OF NUMBERED HEADS TOGETHER (NHT LEARNING MODEL WITH SCIENCE, ENVIRONMENT, TECHNOLOGY, SOCIETY (SETS APPROACH TO IMPROVE STUDENT LEARNING MOTIVATION OF SENIOR HIGH SCHOOL

Directory of Open Access Journals (Sweden)

B. Sutipnyo

2018-01-01

Full Text Available This research was aimed to determine the increasing of students' motivation that has been applied by Numbered Heads Together (NHT learning model with Science, Environment, Technology, Society (SETS approach. The design of this study was quasi experiment with One Group Pretest-Posttest Design. The data of students’ learning motivation obtained through questionnaire administered before and after NHT learning model with SETS approach. In this research, the indicators of learning-motivation were facing tasks diligently, showing interest in variety of problems, prefering to work independently, keeping students’ opinions, and feeling happy to find and solve problems. Increasing of the students’ learning motivation was analyzed by using a gain test. The results showed that applying NHT learning model with SETS approach could increase the students’ learning motivation in medium categories.

Setting Learning Analytics in Context: Overcoming the Barriers to Large-Scale Adoption

Science.gov (United States)

Ferguson, Rebecca; Macfadyen, Leah P.; Clow, Doug; Tynan, Belinda; Alexander, Shirley; Dawson, Shane

2014-01-01

A core goal for most learning analytic projects is to move from small-scale research towards broader institutional implementation, but this introduces a new set of challenges because institutions are stable systems, resistant to change. To avoid failure and maximize success, implementation of learning analytics at scale requires explicit and…

Performance deficits following failure: learned helplessness or self-esteem protection?

Science.gov (United States)

Witkowski, T; Stiensmeier-Pelster, J

1998-03-01

We report two laboratory experiments which compare two competing explanations of performance deficits following failure: one based on Seligman's learned helplessness theory (LHT), and the other, on self-esteem protection theory (SEPT). In both studies, participants (Study 1: N = 40 pupils from secondary schools in Walbrzych, Poland; Study 2: N = 45 students from the University of Bielefeld, Germany) were confronted with either success or failure in a first phase of the experiment. Then, in the second phase of the experiment the participants had to work on a set of mathematical problems (Study 1) or a set of tasks taken from Raven's Progressive Matrices (Study 2) either privately or in public. In both studies failure in the first phase causes performance deficits in the second phase only if the participants had to solve the test tasks in public. These results were interpreted in line with SEPT and as incompatible with LHT.

Improving Job Performance: Workplace Learning Is the First Step

Science.gov (United States)

Daryoush, Younes; Silong, Abu Daud; Omar, Zohara; Othman, Jamilah

2013-01-01

The present study aims to contribute new knowledge to the existing literature on workplace learning and job performance. Particularly, the study analyzes contemporary literature on workplace learning and job performance, specifically formal and informal learning as well as employee task performance and contextual performance. The study…

Fostering Collaborative Learning with Mobile Web 2.0 in Semi-Formal Settings

Science.gov (United States)

Mwanza-Simwami, Daisy

2016-01-01

Mobile Web 2.0 technologies such as: mobile apps, social networking sites and video sharing sites have become essential drivers for shaping daily activities and meeting learning needs in various settings. However, very few studies link mobile Web 2.0 to supporting collaborative learning in real-life problem solving activities in semi-formal…

Focusing on the essentials: learning for performance.

Science.gov (United States)

Murphy, Catherine J

2008-12-10

As The World health report 2006 emphasized, there is increasing consensus that training programmes should focus on "know-how" instead of "know-all." Health workers need to know how to do the job they will be expected to do. IntraHealth International's Learning for performance: a guide and toolkit for health worker training and education programs offers a step-by-step, customizable approach designed to develop the right skills linked to job responsibilities. Using Learning for performance (LFP) yields more efficient training that focuses on what is essential for health workers to do their jobs and on effective learning methods, while addressing the factors that ensure application of new skills on the job. This brief communication describes the Learning for performance approach and initial findings from its application for pre-service education and in-service training in three countries: India, Mali and Bangladesh. Based on IntraHealth's experiences, the author provides thoughts on how LFP's performance-based learning approach can be a useful tool in training scale-up to strengthen human resources for health.

Focusing on the essentials: learning for performance

Directory of Open Access Journals (Sweden)

Murphy Catherine J

2008-12-01

Full Text Available Abstract As The World health report 2006 emphasized, there is increasing consensus that training programmes should focus on "know-how" instead of "know-all." Health workers need to know how to do the job they will be expected to do. IntraHealth International's Learning for performance: a guide and toolkit for health worker training and education programs offers a step-by-step, customizable approach designed to develop the right skills linked to job responsibilities. Using Learning for performance (LFP yields more efficient training that focuses on what is essential for health workers to do their jobs and on effective learning methods, while addressing the factors that ensure application of new skills on the job. This brief communication describes the Learning for performance approach and initial findings from its application for pre-service education and in-service training in three countries: India, Mali and Bangladesh. Based on IntraHealth's experiences, the author provides thoughts on how LFP's performance-based learning approach can be a useful tool in training scale-up to strengthen human resources for health.

Effect of students' learning styles on classroom performance in problem-based learning.

Science.gov (United States)

Alghasham, Abdullah A

2012-01-01

Since problem-based learning (PBL) sessions require a combination of active discussion, group interaction, and inductive and reflective thinking, students with different learning styles can be expected to perform differently in the PBL sessions. Using "Learning Style Inventory Questionnaire," students were divided into separate active and reflective learner groups. Tutors were asked to observe and assess the students' behavioral performance during the PBL sessions for a period of 5 weeks. A questionnaire of 24 items was developed to assess students' behavioral performance in PBL sessions. Active students tended to use multiple activities to obtain the needed information were more adjusted to the group norms and regulation and more skillful in using reasoning and problem-solving skills and in participation in discussion. On the other hand, reflective students used independent study more, listened actively and carefully to others and used previously acquired information in the discussion more frequently. Formative assessment quizzes did not indicate better performance of either group. There were no significant gender differences in PBL behavioral performance or quizzes' scores. Active and reflective learners differ in PBL class behavioral performance but not in the formative assessment. We recommend that students should be informed about their learning style and that they should learn strategies to compensate for any lacks in PBL sessions through self-study. Also, educational planners should ensure an adequate mix of students with different learning styles in the PBL groups to achieve PBL desired objectives.

Upper-Lower Bounds Candidate Sets Searching Algorithm for Bayesian Network Structure Learning

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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.

The effect of negative performance stereotypes on learning.

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Rydell, Robert J; Rydell, Michael T; Boucher, Kathryn L

2010-12-01

Stereotype threat (ST) research has focused exclusively on how negative group stereotypes reduce performance. The present work examines if pejorative stereotypes about women in math inhibit their ability to learn the mathematical rules and operations necessary to solve math problems. In Experiment 1, women experiencing ST had difficulty encoding math-related information into memory and, therefore, learned fewer mathematical rules and showed poorer math performance than did controls. In Experiment 2, women experiencing ST while learning modular arithmetic (MA) performed more poorly than did controls on easy MA problems; this effect was due to reduced learning of the mathematical operations underlying MA. In Experiment 3, ST reduced women's, but not men's, ability to learn abstract mathematical rules and to transfer these rules to a second, isomorphic task. This work provides the first evidence that negative stereotypes about women in math reduce their level of mathematical learning and demonstrates that reduced learning due to stereotype threat can lead to poorer performance in negatively stereotyped domains. PsycINFO Database Record (c) 2010 APA, all rights reserved.

CaPOW! Using Problem Sets in a Capstone Course to Improve Fourth-Year Medical Students' Confidence in Self-Directed Learning.

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Clay, Alison S; Ming, David Y; Knudsen, Nancy W; Engle, Deborah L; Grochowski, Colleen O'Connor; Andolsek, Kathryn M; Chudgar, Saumil M

2017-03-01

Despite the importance of self-directed learning (SDL) in the field of medicine, individuals are rarely taught how to perform SDL or receive feedback on it. Trainee skill in SDL is limited by difficulties with self-assessment and goal setting. Ninety-two graduating fourth-year medical students from Duke University School of Medicine completed an individualized learning plan (ILP) for a transition-to-residency Capstone course in spring 2015 to help foster their skills in SDL. Students completed the ILP after receiving a personalized report from a designated faculty coach detailing strengths and weaknesses on specific topics (e.g., pulmonary medicine) and clinical skills (e.g., generating a differential diagnosis). These were determined by their performance on 12 Capstone Problem Sets of the Week (CaPOWs) compared with their peers. Students used transitional-year milestones to self-assess their confidence in SDL. SDL was successfully implemented in a Capstone course through the development of required clinically oriented problem sets. Coaches provided guided feedback on students' performance to help them identify knowledge deficits. Students' self-assessment of their confidence in SDL increased following course completion. However, students often chose Capstone didactic sessions according to factors other than their CaPOW performance, including perceived relevance to planned specialty and session timing. Future Capstone curriculum changes may further enhance SDL skills of graduating students. Students will receive increased formative feedback on their CaPOW performance and be incentivized to attend sessions in areas of personal weakness.

Making Facilitation Work: The Challenges on an International DBA Action Learning Set

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OFarrell, Jack

2018-01-01

This account relates my experiences as facilitator of an action learning set on a DBA cohort comprising international students and myself. It outlines the reasons for my selection as facilitator and describes my initial expectations and assumptions of action learning. I chart the difficulty in separating the 'what' of my own research from the…

The impact of goal setting and goal orientation on performance during a clerkship surgical skills training program.

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Gardner, Aimee K; Diesen, Diana L; Hogg, Deborah; Huerta, Sergio

2016-02-01

The purpose of this study was to integrate relevant goal-setting theory and to identify if trainees' goal orientations have an impact on the assigned goals-performance relationship. Trainees attended 1 of the 3 goal-training activities (do your best, performance, or learning goals) for knot tying (KT) and camera navigation (CN) during the 3rd-year clerkship rotation. Questionnaires and pretests and/or post-tests were completed. One twenty-seven 3rd-year medical students (age: 25 ± 2.6; 54% women) participated in the training program. Pretraining to post-training performance changes were significant for all groups on both tasks (P goals group (do your best: KTΔ = 2.14, CNΔ = 1.69; performance: KTΔ = 2.49, CNΔ = 2.24; learning: KTΔ = 3.04 CNΔ = 2.76). Correlations between goal orientations and improvement were examined, revealing a unique role of goal orientation for performance improvement. These data indicate that consideration of goal type and trainee goal orientation must be considered during curriculum development to maximize educational value. Copyright © 2016 Elsevier Inc. All rights reserved.

Different Modes of Digital Learning Object Use in School Settings: Do We Design for Individual or Collaborative Learning?

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Akpinar, Yavuz

2014-01-01

The aim of the studies reported in this paper is to gain classroom based empirical evidence on the learning effectiveness of learning objects used in two types of study settings: Collaborative and individual. A total of 127 seventh and ninth grade students participated in the experiments. They were assigned into one of the study modes and worked…

Organisational Learning and Performance--An Empirical Study

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Jyothibabu, C.; Pradhan, Bibhuti Bhusan; Farooq, Ayesha

2011-01-01

This paper explores the important question "how the learning entities--individual, group or organisation--are affecting organisational performance". The answer is important for promoting learning and improving performance. This empirical study in the leading power utility in India found that there is a positive relation between…

Correlation Between Screening Mammography Interpretive Performance on a Test Set and Performance in Clinical Practice.

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Miglioretti, Diana L; Ichikawa, Laura; Smith, Robert A; Buist, Diana S M; Carney, Patricia A; Geller, Berta; Monsees, Barbara; Onega, Tracy; Rosenberg, Robert; Sickles, Edward A; Yankaskas, Bonnie C; Kerlikowske, Karla

2017-10-01

Evidence is inconsistent about whether radiologists' interpretive performance on a screening mammography test set reflects their performance in clinical practice. This study aimed to estimate the correlation between test set and clinical performance and determine if the correlation is influenced by cancer prevalence or lesion difficulty in the test set. This institutional review board-approved study randomized 83 radiologists from six Breast Cancer Surveillance Consortium registries to assess one of four test sets of 109 screening mammograms each; 48 radiologists completed a fifth test set of 110 mammograms 2 years later. Test sets differed in number of cancer cases and difficulty of lesion detection. Test set sensitivity and specificity were estimated using woman-level and breast-level recall with cancer status and expert opinion as gold standards. Clinical performance was estimated using women-level recall with cancer status as the gold standard. Spearman rank correlations between test set and clinical performance with 95% confidence intervals (CI) were estimated. For test sets with fewer cancers (N = 15) that were more difficult to detect, correlations were weak to moderate for sensitivity (woman level = 0.46, 95% CI = 0.16, 0.69; breast level = 0.35, 95% CI = 0.03, 0.61) and weak for specificity (0.24, 95% CI = 0.01, 0.45) relative to expert recall. Correlations for test sets with more cancers (N = 30) were close to 0 and not statistically significant. Correlations between screening performance on a test set and performance in clinical practice are not strong. Test set performance more accurately reflects performance in clinical practice if cancer prevalence is low and lesions are challenging to detect. Copyright © 2017 The Association of University Radiologists. Published by Elsevier Inc. All rights reserved.

Sleep loss, learning capacity and academic performance.

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Curcio, Giuseppe; Ferrara, Michele; De Gennaro, Luigi

2006-10-01

At a time when several studies have highlighted the relationship between sleep, learning and memory processes, an in-depth analysis of the effects of sleep deprivation on student learning ability and academic performance would appear to be essential. Most studies have been naturalistic correlative investigations, where sleep schedules were correlated with school and academic achievement. Nonetheless, some authors were able to actively manipulate sleep in order to observe neurocognitive and behavioral consequences, such as learning, memory capacity and school performance. The findings strongly suggest that: (a) students of different education levels (from school to university) are chronically sleep deprived or suffer from poor sleep quality and consequent daytime sleepiness; (b) sleep quality and quantity are closely related to student learning capacity and academic performance; (c) sleep loss is frequently associated with poor declarative and procedural learning in students; (d) studies in which sleep was actively restricted or optimized showed, respectively, a worsening and an improvement in neurocognitive and academic performance. These results may been related to the specific involvement of the prefrontal cortex (PFC) in vulnerability to sleep loss. Most methodological limitations are discussed and some future research goals are suggested.

Video-task assessment of learning and memory in Macaques (Macaca mulatta) - Effects of stimulus movement on performance

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Washburn, David A.; Hopkins, William D.; Rumbaugh, Duane M.

1989-01-01

Effects of stimulus movement on learning, transfer, matching, and short-term memory performance were assessed with 2 monkeys using a video-task paradigm in which the animals responded to computer-generated images by manipulating a joystick. Performance on tests of learning set, transfer index, matching to sample, and delayed matching to sample in the video-task paradigm was comparable to that obtained in previous investigations using the Wisconsin General Testing Apparatus. Additionally, learning, transfer, and matching were reliably and significantly better when the stimuli or discriminanda moved than when the stimuli were stationary. External manipulations such as stimulus movement may increase attention to the demands of a task, which in turn should increase the efficiency of learning. These findings have implications for the investigation of learning in other populations, as well as for the application of the video-task paradigm to comparative study.

Effects of Collaborative Learning Styles on Performance of Students in a Ubiquitous Collaborative Mobile Learning Environment

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Fakomogbon, Michael Ayodele; Bolaji, Hameed Olalekan

2017-01-01

Collaborative learning is an approach employed by instructors to facilitate learning and improve learner's performance. Mobile learning can accommodate a variety of learning approaches. This study, therefore, investigated the effects of collaborative learning styles on performance of students in a mobile learning environment. The specific purposes…

The difference in learning culture and learning performance between a traditional clinical placement, a dedicated education unit and work-based learning.

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Claeys, Maureen; Deplaecie, Monique; Vanderplancke, Tine; Delbaere, Ilse; Myny, Dries; Beeckman, Dimitri; Verhaeghe, Sofie

2015-09-01

An experiment was carried out on the bachelor's degree course in nursing with two new clinical placement concepts: workplace learning and the dedicated education centre. The aim was to establish a learning culture that creates a sufficiently high learning performance for students. The objectives of this study are threefold: (1) to look for a difference in the "learning culture" and "learning performance" in traditional clinical placement departments and the new clinical placement concepts, the "dedicated education centre" and "workplace learning"; (2) to assess factors influencing the learning culture and learning performance; and (3) to investigate whether there is a link between the learning culture and the learning performance. A non-randomised control study was carried out. The experimental group consisted of 33 final-year nursing undergraduates who were following clinical placements at dedicated education centres and 70 nursing undergraduates who undertook workplace learning. The control group consisted of 106 students who followed a traditional clinical placement. The "learning culture" outcome was measured using the Clinical Learning Environment, Supervision and Nurse Teacher scale. The "learning performance" outcome consisting of three competencies was measured using the Nursing Competence Questionnaire. The traditional clinical placement concept achieved the highest score for learning culture (plearning performance of which the dedicated education centres achieved the highest scores. The 3 clinical placement concepts showed marked differences in learning performance for the "assessment" competency (plearning can be seen as complementary clinical placement concepts. The organisation of clinical placements under the dedicated education centre concept and workplace learning is recommended for final-year undergraduate nursing students. Copyright © 2015 Elsevier Ltd. All rights reserved.

Building up STEM education professional learning community in school setting: Case of Khon Kaen Wittayayon School

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Thana, Aduldej; Siripun, Kulpatsorn; Yuenyong, Chokchai

2018-01-01

The STEM education is new issue of teaching and learning in school setting. Building up STEM education professional learning community may provide some suggestions for further collaborative work of STEM Education from grounded up. This paper aimed to clarify the building up STEM education learning community in Khon Kaen Wittayayon (KKW) School setting. Participants included Khon Kaen University researchers, Khon Kaen Wittayayon School administrators and teachers. Methodology regarded interpretative paradigm. The tools of interpretation included participant observation, interview and document analysis. Data was analyzed to categories of condition for building up STEM education professional learning community. The findings revealed that the actions of developing STEM learning activities and research showed some issues of KKW STEM community of inquiry and improvement. The paper will discuss what and how the community learns about sharing vision of STEM Education, supportive physical and social conditions of KKW, sharing activities of STEM, and good things from some key STEM teachers' ambition. The paper may has implication of supporting STEM education in Thailand school setting.

The Influence of Investment in Workplace Learning on Learning Outcomes and Organizational Performance

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Park, Yoonhee; Jacobs, Ronald L.

2011-01-01

Although the importance of workplace learning has been recognized in research and practice, there is little empirical support that describes how workplace learning, including both formal and informal learning, is linked to organizational performance. This study investigated the influence of investment in workplace learning on learning outcomes and…

Auditory and motor imagery modulate learning in music performance.

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Brown, Rachel M; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of

Auditory and motor imagery modulate learning in music performance

Science.gov (United States)

Brown, Rachel M.; Palmer, Caroline

2013-01-01

Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians' encoding (during Learning, as they practiced novel melodies), and retrieval (during Recall of those melodies). Pianists learned melodies by listening without performing (auditory learning) or performing without sound (motor learning); following Learning, pianists performed the melodies from memory with auditory feedback (Recall). During either Learning (Experiment 1) or Recall (Experiment 2), pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced) and temporal regularity (variability of quarter-note interonset intervals) were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists' pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2). Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1): Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2): Higher auditory imagery skill predicted greater temporal regularity during Recall in the presence of

Training set optimization and classifier performance in a top-down diabetic retinopathy screening system

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Wigdahl, J.; Agurto, C.; Murray, V.; Barriga, S.; Soliz, P.

2013-03-01

Diabetic retinopathy (DR) affects more than 4.4 million Americans age 40 and over. Automatic screening for DR has shown to be an efficient and cost-effective way to lower the burden on the healthcare system, by triaging diabetic patients and ensuring timely care for those presenting with DR. Several supervised algorithms have been developed to detect pathologies related to DR, but little work has been done in determining the size of the training set that optimizes an algorithm's performance. In this paper we analyze the effect of the training sample size on the performance of a top-down DR screening algorithm for different types of statistical classifiers. Results are based on partial least squares (PLS), support vector machines (SVM), k-nearest neighbor (kNN), and Naïve Bayes classifiers. Our dataset consisted of digital retinal images collected from a total of 745 cases (595 controls, 150 with DR). We varied the number of normal controls in the training set, while keeping the number of DR samples constant, and repeated the procedure 10 times using randomized training sets to avoid bias. Results show increasing performance in terms of area under the ROC curve (AUC) when the number of DR subjects in the training set increased, with similar trends for each of the classifiers. Of these, PLS and k-NN had the highest average AUC. Lower standard deviation and a flattening of the AUC curve gives evidence that there is a limit to the learning ability of the classifiers and an optimal number of cases to train on.

Teori Adult Learning, Ekspriental Learning Cycle Dan Perubahan Performance Individu Dalam Pendidikan Dan Pelatihan

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Moh. Dannur

2017-07-01

Full Text Available Teori belajar merupakan hal yang sangat penting dalam Manajmen Pendidikan dan Pelatihan apabila ingin meraih hasil yang maksimal dalam proses transformasi pengetahuan. Adult Learning dan Ekspriental Learning Cycle salah satu teori yang paling masyhur di dalamnya. Dalam upaya meraih hasil yang maksimal juga perlu adanya pengetahuan tentang motivasi dan faktor-faktor dalam pengembangan individu, perubahan performanya, serta dinamika individu kelompok. Sehingga dengan pengetahuan yang dimilikiakan dengan mudah merealisasikan yang diinginkan. Kata kunci: Adult learning, expriental learning cycle, performance.  Learning theory is very important in Management of Education and Training if you want to achieve the maximum results in the transformation process of knowledge. Adult Learning and Expriental Learning Cycle are the most famous theories within it. In the effort to achieve the maximum results also needs the knowledge about motivation, the factors in the development of individuals, the changes of performance, and the dynamics of individual groups. So with this knowledge you will easily realize the thing you desired. Keywords: Adult learning, expriental learning cycle, performance.

KECEMASAN MATEMATIK SISWA KELAS XI SMK BERDASARKAN MAHMOOD DAN KHATOON DALAM SETTING PROBLEM BASED LEARNING

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Desy Kumalasari

2017-03-01

Full Text Available Penelitian ini bertujuan untuk mendeskripsikan kualitas pembelajaran matematika dalam setting problem based learning terhadap kemampuan pemecahan masalah siswa kelas XI SMK, mendeskripsikan tingkat kecemasan matematik siswa dalam mengikuti pelajaran matematika dalam setting problem based learning, dan mendeskripsikan kemampuan pemecahan masalah berdasarkan tingkat kecemasan matematik. Metode penelitian ini adalah mixed methods. Subjek dalam penelitian ini adalah siswa kelas XI TKKB SMKN 10 Semarang. Selanjutnya dipilih 6 siswa dari masing-masing kemampuan pemecahan masalah berdasarkan tingkat kecemasan matematik. Metode pengumpulan data dalam penelitian ini adalah metode observasi, dokumentasi, tes, dan wawancara. Analisis data dalam penelitian ini adalah analisis kualitas pembelajaran, analisis tingkat kecemasan matematik, analisis kemampuan pemecahan masalah, reduksi data, penyajian data, dan menarik kesimpulan dan verifikasi. Hasil penelitian ini diperoleh: kualitas pembelajaran dalam setting problem based learning dalam kategori baik, tingkat kecemasan matematik siswa kelas XI SMKN 10 Semarang sebelum pembelajaran matematika adalah rendah, pada saat kegiatan pembelajaran adalah tinggi, dan setelah kegiatan pembelajaran adalah rendah, untuk tingkat kecemasan sebelum tes kemampuan pemecahan masalah adalah rendah, dan setelah tes kemampuan pemecahan masalah adalah tinggi, dan kemampuan pemecahan masalah matematika siswa yang tingkat kecemasan matematik rendah lebih baik dari pada siswa yang tingkat kecemasan matematiknya tinggi.   This research aimed to describe the quality of  mathematics teaching in the setting of problem based learning to problem­solving ability of class XI student of SMK, the level of mathematics  anxiety  of   students  in  participating  in  the  setting  math  problem  based learning, and the problem­solving abilities by mathematics anxiety levels. This research method is mixed methods. Subjects in this

Auditory and motor imagery modulate learning in music performance

Directory of Open Access Journals (Sweden)

Rachel M. Brown

2013-07-01

Full Text Available Skilled performers such as athletes or musicians can improve their performance by imagining the actions or sensory outcomes associated with their skill. Performers vary widely in their auditory and motor imagery abilities, and these individual differences influence sensorimotor learning. It is unknown whether imagery abilities influence both memory encoding and retrieval. We examined how auditory and motor imagery abilities influence musicians’ encoding (during Learning, as they practiced novel melodies, and retrieval (during Recall of those melodies. Pianists learned melodies by listening without performing (auditory learning or performing without sound (motor learning; following Learning, pianists performed the melodies from memory with auditory feedback (Recall. During either Learning (Experiment 1 or Recall (Experiment 2, pianists experienced either auditory interference, motor interference, or no interference. Pitch accuracy (percentage of correct pitches produced and temporal regularity (variability of quarter-note interonset intervals were measured at Recall. Independent tests measured auditory and motor imagery skills. Pianists’ pitch accuracy was higher following auditory learning than following motor learning and lower in motor interference conditions (Experiments 1 and 2. Both auditory and motor imagery skills improved pitch accuracy overall. Auditory imagery skills modulated pitch accuracy encoding (Experiment 1: Higher auditory imagery skill corresponded to higher pitch accuracy following auditory learning with auditory or motor interference, and following motor learning with motor or no interference. These findings suggest that auditory imagery abilities decrease vulnerability to interference and compensate for missing auditory feedback at encoding. Auditory imagery skills also influenced temporal regularity at retrieval (Experiment 2: Higher auditory imagery skill predicted greater temporal regularity during Recall in the

Learning strategies during clerkships and their effects on clinical performance.

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van Lohuizen, M T; Kuks, J B M; van Hell, E A; Raat, A N; Cohen-Schotanus, J

2009-11-01

Previous research revealed relationships between learning strategies and knowledge acquisition. During clerkships, however, students' focus widens beyond mere knowledge acquisition as they further develop overall competence. This shift in focus can influence learning strategy use. We explored which learning strategies were used during clerkships and their relationship to clinical performance. Participants were 113 (78%) clerks at the university hospital or one of six affiliated hospitals. Learning strategies were assessed using the 'Approaches to Learning at Work Questionnaire' (deep, surface-rational and surface-disorganised learning). Clinical performance was calculated by taking the mean of clinical assessment marks. The relationship between learning strategies and clinical performance was explored using regression analysis. Most students (89%) did not clearly prefer a single learning strategy. No relationship was found between learning strategies and clinical performance. Since overall competence comprises integration of knowledge, skills and professional behaviour, we assume that students without a clear preference use more than one learning strategy. Finding no relationship between learning strategies and clinical performance reflects the complexity of clinical learning. Depending on circumstances it may be important to obtain relevant information quickly (surface-rational) or understand material thoroughly (deep). In future research we will examine when and why students use different learning strategies.

EFL LEARNERS’ READING LEARNING IN WEB BASED INSTRUCTION SETTING

OpenAIRE

Yusup Supriyono

2018-01-01

This research is aimed at exploring reading learning performed by English foreign language learners when Web based instruction is integrated into reading classroom. Teaching learning activity follows the steps:  orientation, discussion, material exploration, action, test, and reflection.  Two data collecting methods—journal and interview are administered to three students of the fourth semester of English Department in University of Siliwangi Tasikmalaya Indonesia after the selected individua...

Mobile learning for HIV/AIDS healthcare worker training in resource-limited settings

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Zolfo Maria

2010-09-01

Full Text Available Abstract Background We present an innovative approach to healthcare worker (HCW training using mobile phones as a personal learning environment. Twenty physicians used individual Smartphones (Nokia N95 and iPhone, each equipped with a portable solar charger. Doctors worked in urban and peri-urban HIV/AIDS clinics in Peru, where almost 70% of the nation's HIV patients in need are on treatment. A set of 3D learning scenarios simulating interactive clinical cases was developed and adapted to the Smartphones for a continuing medical education program lasting 3 months. A mobile educational platform supporting learning events tracked participant learning progress. A discussion forum accessible via mobile connected participants to a group of HIV specialists available for back-up of the medical information. Learning outcomes were verified through mobile quizzes using multiple choice questions at the end of each module. Methods In December 2009, a mid-term evaluation was conducted, targeting both technical feasibility and user satisfaction. It also highlighted user perception of the program and the technical challenges encountered using mobile devices for lifelong learning. Results With a response rate of 90% (18/20 questionnaires returned, the overall satisfaction of using mobile tools was generally greater for the iPhone. Access to Skype and Facebook, screen/keyboard size, and image quality were cited as more troublesome for the Nokia N95 compared to the iPhone. Conclusions Training, supervision and clinical mentoring of health workers are the cornerstone of the scaling up process of HIV/AIDS care in resource-limited settings (RLSs. Educational modules on mobile phones can give flexibility to HCWs for accessing learning content anywhere. However lack of softwares interoperability and the high investment cost for the Smartphones' purchase could represent a limitation to the wide spread use of such kind mLearning programs in RLSs.

Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities

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Yu-Chi Lin

2011-02-01

Full Text Available Due to the implicit characteristics of learning disabilities (LDs, the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN and support vector machine (SVM have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST, which can not only perform as a classifier, but may also produce meaningful explanations or rules, to the LD diagnosis application. Our experiments indicate that the RST approach is competitive as a tool for feature selection, and it performs better in term of prediction accuracy than other rulebased algorithms such as decision tree and ripper algorithms. We also propose to mix samples collected from sources with different LD diagnosis procedure and criteria. By pre-processing these mixed samples with simple and readily available clustering algorithms, we are able to improve the quality and support of rules generated by the RST. Overall, our study shows that the rough set approach, as a classification and knowledge discovery tool, may have great potential in playing an essential role in LD diagnosis.

Automatic Earthquake Detection by Active Learning

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Bergen, K.; Beroza, G. C.

2017-12-01

In recent years, advances in machine learning have transformed fields such as image recognition, natural language processing and recommender systems. Many of these performance gains have relied on the availability of large, labeled data sets to train high-accuracy models; labeled data sets are those for which each sample includes a target class label, such as waveforms tagged as either earthquakes or noise. Earthquake seismologists are increasingly leveraging machine learning and data mining techniques to detect and analyze weak earthquake signals in large seismic data sets. One of the challenges in applying machine learning to seismic data sets is the limited labeled data problem; learning algorithms need to be given examples of earthquake waveforms, but the number of known events, taken from earthquake catalogs, may be insufficient to build an accurate detector. Furthermore, earthquake catalogs are known to be incomplete, resulting in training data that may be biased towards larger events and contain inaccurate labels. This challenge is compounded by the class imbalance problem; the events of interest, earthquakes, are infrequent relative to noise in continuous data sets, and many learning algorithms perform poorly on rare classes. In this work, we investigate the use of active learning for automatic earthquake detection. Active learning is a type of semi-supervised machine learning that uses a human-in-the-loop approach to strategically supplement a small initial training set. The learning algorithm incorporates domain expertise through interaction between a human expert and the algorithm, with the algorithm actively posing queries to the user to improve detection performance. We demonstrate the potential of active machine learning to improve earthquake detection performance with limited available training data.

Drilling Students’ Communication Skill through Science, Environment, Technology, and Society (SETS)-Based Learning

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Al-Farisi, B. L.; Tjandrakirana; Agustini, R.

2018-01-01

Student’s communication skill paid less attention in learning activity at school, even though communication skill is needed by students in the 21st century based on the demands of new curriculum in Indonesia (K13). This study focuses on drilling students’ communication skill through science, environment, technology, and society (SETS)-based learning. The research is a pre-experimental design with a one-shot case study model involving 10 students of ninth-grader of SMPN 2 Manyar, Gresik. The research data were collected through observation method using communication observation sheet. The data were analyzed using the descriptive qualitative method. The result showed that students’ communication skill reached the completeness of skills decided both individually and classically in the curriculum. The fundamental result of this research that SETS-based learning can be used to drill students’ communication skill in K13 context.

Does individual learning styles influence the choice to use a web-based ECG learning programme in a blended learning setting?

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Nilsson, Mikael; Östergren, Jan; Fors, Uno; Rickenlund, Anette; Jorfeldt, Lennart; Caidahl, Kenneth; Bolinder, Gunilla

2012-01-16

The compressed curriculum in modern knowledge-intensive medicine demands useful tools to achieve approved learning aims in a limited space of time. Web-based learning can be used in different ways to enhance learning. Little is however known regarding its optimal utilisation. Our aim was to investigate if the individual learning styles of medical students influence the choice to use a web-based ECG learning programme in a blended learning setting. The programme, with three types of modules (learning content, self-assessment questions and interactive ECG interpretation training), was offered on a voluntary basis during a face to face ECG learning course for undergraduate medical students. The Index of Learning Styles (ILS) and a general questionnaire including questions about computer and Internet usage, preferred future speciality and prior experience of E-learning were used to explore different factors related to the choice of using the programme or not. 93 (76%) out of 123 students answered the ILS instrument and 91 the general questionnaire. 55 students (59%) were defined as users of the web-based ECG-interpretation programme. Cronbach's alpha was analysed with coefficients above 0.7 in all of the four dimensions of ILS. There were no significant differences with regard to learning styles, as assessed by ILS, between the user and non-user groups; Active/Reflective; Visual/Verbal; Sensing/Intuitive; and Sequential/Global (p = 0.56-0.96). Neither did gender, prior experience of E-learning or preference for future speciality differ between groups. Among medical students, neither learning styles according to ILS, nor a number of other characteristics seem to influence the choice to use a web-based ECG programme. This finding was consistent also when the usage of the different modules in the programme were considered. Thus, the findings suggest that web-based learning may attract a broad variety of medical students.

Science and art of setting performance standards and cutoff scores in kinesiology.

Science.gov (United States)

Zhu, Weimo

2013-12-01

Setting standards and cutoff scores is essential to any measurement and evaluation practice. Two evaluation frameworks, norm-referenced (NR) and criterion-referenced (CR), have often been used for setting standards. Although setting fitness standards based on the NR evaluation is relatively easy as long as a nationally representative sample can be obtained and regularly updated, it has several limitations-namely, time dependency, population dependence, discouraging low-level performers, and favoring advantaged or punishing disadvantaged individuals. Fortunately, these limitations can be significantly eliminated by employing the CR evaluation, which was introduced to kinesiology by Safrit and colleagues in the 1980s and has been successfully applied to some practical problems (e.g., set health-related fitness standards for FITNESSGRAM). Yet, the CR evaluation has its own challenges, e.g., selecting an appropriate measure for a criterion behavior, when the expected relationship between the criterion behavior and a predictive measure is not clear, and when standards are not consistent among multiple field measures. Some of these challenges can be addressed by employing the latest statistical methods (e.g., test equating). This article provides a comprehensive review of the science and art of setting standards and cutoff scores in kinesiology. After a brief historical overview of the standard-setting practice in kinesiology is presented, a case analysis of a successful CR evaluation, along with related challenges, is described. Lessons learned from past and current practice as well as how to develop a defendable standard are described. Finally, future research needs and directions are outlined.

Making a Case for E - learning: Experiences in E-learning at ...

African Journals Online (AJOL)

Making a Case for E - learning: Experiences in E-learning at Langston University ... performances can surpass those of students in traditional learning settings. ... The research method was qualitative based mainly on participatory and ...

Optimizing top precision performance measure of content-based image retrieval by learning similarity function

KAUST Repository

Liang, Ru-Ze

2017-04-24

In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

Optimizing top precision performance measure of content-based image retrieval by learning similarity function

KAUST Repository

Liang, Ru-Ze; Shi, Lihui; Wang, Haoxiang; Meng, Jiandong; Wang, Jim Jing-Yan; Sun, Qingquan; Gu, Yi

2017-01-01

In this paper we study the problem of content-based image retrieval. In this problem, the most popular performance measure is the top precision measure, and the most important component of a retrieval system is the similarity function used to compare a query image against a database image. However, up to now, there is no existing similarity learning method proposed to optimize the top precision measure. To fill this gap, in this paper, we propose a novel similarity learning method to maximize the top precision measure. We model this problem as a minimization problem with an objective function as the combination of the losses of the relevant images ranked behind the top-ranked irrelevant image, and the squared Frobenius norm of the similarity function parameter. This minimization problem is solved as a quadratic programming problem. The experiments over two benchmark data sets show the advantages of the proposed method over other similarity learning methods when the top precision is used as the performance measure.

On-campus or online: examining self-regulation and cognitive transfer skills in different learning settings

Directory of Open Access Journals (Sweden)

Miri Barak

2016-11-01

Full Text Available Abstract This study was set to identify self-regulation skills required for online learning and to characterize cognitive transfer of on-campus and online students. The study included two groups of undergraduate students who studied the same course, but in different settings: online and on-campus. Data collected via an online survey and semi-structured interviews indicated that cognitive strategies and regulation of cognition are significant for successful online learning. Findings also indicated that the online students were more aware of mastery learning and information processing strategies than the on-campus peers. The online students specified the importance of planning, controlling, and evaluation skills for meaningful learning; whereas the on-campus students asserted lack of self-discipline and limited communication skills as barriers for distance learning. Near- and far-transfer components were identified, showing a significant positive correlation with self-regulation skills for both groups of learners.

Age-dependent and coordinated shift in performance between implicit and explicit skill learning

Directory of Open Access Journals (Sweden)

Dezso eNemeth

2013-10-01

Full Text Available It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N=288, replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

Age-dependent and coordinated shift in performance between implicit and explicit skill learning.

Science.gov (United States)

Nemeth, Dezso; Janacsek, Karolina; Fiser, József

2013-01-01

It has been reported recently that while general sequence learning across ages conforms to the typical inverted-U shape pattern, with best performance in early adulthood, surprisingly, the basic ability of picking up in an implicit manner triplets that occur with high vs. low probability in the sequence is best before 12 years of age and it significantly weakens afterwards. Based on these findings, it has been hypothesized that the cognitively controlled processes coming online at around 12 are useful for more targeted explicit learning at the cost of becoming relatively less sensitive to raw probabilities of events. To test this hypothesis, we collected data in a sequence learning task using probabilistic sequences in five age groups from 11 to 39 years of age (N = 288), replicating the original implicit learning paradigm in an explicit task setting where subjects were guided to find repeating sequences. We found that in contrast to the implicit results, performance with the high- vs. low-probability triplets was at the same level in all age groups when subjects sought patterns in the sequence explicitly. Importantly, measurements of explicit knowledge about the identity of the sequences revealed a significant increase in ability to explicitly access the true sequences exactly around the age where the earlier study found the significant drop in ability to learn implicitly raw probabilities. These findings support the conjecture that the gradually increasing involvement of more complex internal models optimizes our skill learning abilities by compensating for the performance loss due to down-weighting the raw probabilities of the sensory input, while expanding our ability to acquire more sophisticated skills.

Attitudes of Staff Nurse Preceptors Related to the Education of Nurses with Learning Disabilities in Clinical Settings

Science.gov (United States)

L'Ecuyer, Kristine Marie

2014-01-01

This dissertation presents a quantitative study of the attitudes of staff nurse preceptors toward nursing students with learning disabilities. There are an increased number of nursing students with learning disabilities. These students may have additional challenges in clinical settings, particularly if clinical settings do not understand or…

A cross-level investigation of informal field-based learning and performance improvements.

Science.gov (United States)

Wolfson, Mikhail A; Tannenbaum, Scott I; Mathieu, John E; Maynard, M Travis

2018-01-01

Organizations often operate in complex and dynamic environments which place a premium on employees' ongoing learning and acquisition of new competencies. Additionally, the majority of learning in organizations does not take place in formal training settings, but we know relatively little about how informal field-based learning (IFBL) behaviors relate to changes in job performance. In this study, we first clarified the construct of IFBL as a subset of informal learning. Second, on the basis of this clarified construct definition, we developed a measure of IFBL behaviors and demonstrated its psychometric properties using (a) a sample of subject matter experts who made item content validity judgments and (b) both an Amazon Mechanical Turk sample (N = 400) and a sample of 1,707 healthcare employees. Third, we advanced a grounded theory of IFBL in healthcare, and related it to individuals' regulatory foci and contextual moderators of IFBL behaviors-job performance relationships using a cross-level design and lagged nonmethod bound measures. Specifically, using a sample of 407 healthcare workers from 49 hospital units, our results suggested that promotion-focused individuals, especially in well-staffed units, readily engage in IFBL behaviors. Additionally, we found that the IFBL-changes in job performance relationship was strengthened to the extent that individuals worked in units with relatively nonpunitive climates. Interestingly, staffing levels had a weakening moderating effect on the positive IFBL-performance improvements relationship. Detailed follow-up analyses revealed that the peculiar effect was attributable to differential relationships from IFBL subdimensions. Implications for future theory building, research, and practice are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Interactive Multimodal Molecular Set – Designing Ludic Engaging Science Learning Content

DEFF Research Database (Denmark)

Thorsen, Tine Pinholt; Christiansen, Kasper Holm Bonde; Jakobsen Sillesen, Kristian

2014-01-01

This paper reports on an exploratory study investigating 10 primary school students’ interaction with an interactive multimodal molecular set fostering ludic engaging science learning content in primary schools (8th and 9th grade). The concept of the prototype design was to bridge the physical...... and virtual worlds with electronic tags and, through this, blend the familiarity of the computer and toys, to create a tool that provided a ludic approach to learning about atoms and molecules. The study was inspired by the participatory design and informant design methodologies and included design...

The performance of cleaner wrasse, Labroides dimidiatus, in a reversal learning task varies across experimental paradigms

Directory of Open Access Journals (Sweden)

Simon Gingins

2018-05-01

Full Text Available Testing performance in controlled laboratory experiments is a powerful tool for understanding the extent and evolution of cognitive abilities in non-human animals. However, cognitive testing is prone to a number of potential biases, which, if unnoticed or unaccounted for, may affect the conclusions drawn. We examined whether slight modifications to the experimental procedure and apparatus used in a spatial task and reversal learning task affected performance outcomes in the bluestreak cleaner wrasse, Labroides dimidiatus (hereafter “cleaners”. Using two-alternative forced-choice tests, fish had to learn to associate a food reward with a side (left or right in their holding aquarium. Individuals were tested in one of four experimental treatments that differed slightly in procedure and/or physical set-up. Cleaners from all four treatment groups were equally able to solve the initial spatial task. However, groups differed in their ability to solve the reversal learning task: no individuals solved the reversal task when tested in small tanks with a transparent partition separating the two options, whereas over 50% of individuals solved the task when performed in a larger tank, or with an opaque partition. These results clearly show that seemingly insignificant details to the experimental set-up matter when testing performance in a spatial task and might significantly influence the outcome of experiments. These results echo previous calls for researchers to exercise caution when designing methodologies for cognition tasks to avoid misinterpretations.

The performance of cleaner wrasse, Labroides dimidiatus, in a reversal learning task varies across experimental paradigms.

Science.gov (United States)

Gingins, Simon; Marcadier, Fanny; Wismer, Sharon; Krattinger, Océane; Quattrini, Fausto; Bshary, Redouan; Binning, Sandra A

2018-01-01

Testing performance in controlled laboratory experiments is a powerful tool for understanding the extent and evolution of cognitive abilities in non-human animals. However, cognitive testing is prone to a number of potential biases, which, if unnoticed or unaccounted for, may affect the conclusions drawn. We examined whether slight modifications to the experimental procedure and apparatus used in a spatial task and reversal learning task affected performance outcomes in the bluestreak cleaner wrasse, Labroides dimidiatus (hereafter "cleaners"). Using two-alternative forced-choice tests, fish had to learn to associate a food reward with a side (left or right) in their holding aquarium. Individuals were tested in one of four experimental treatments that differed slightly in procedure and/or physical set-up. Cleaners from all four treatment groups were equally able to solve the initial spatial task. However, groups differed in their ability to solve the reversal learning task: no individuals solved the reversal task when tested in small tanks with a transparent partition separating the two options, whereas over 50% of individuals solved the task when performed in a larger tank, or with an opaque partition. These results clearly show that seemingly insignificant details to the experimental set-up matter when testing performance in a spatial task and might significantly influence the outcome of experiments. These results echo previous calls for researchers to exercise caution when designing methodologies for cognition tasks to avoid misinterpretations.

Accounting Student's Learning Approaches And Impact On Academic Performance

OpenAIRE

Ismail, Suhaiza

2009-01-01

The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student's academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

Use of Web 2.0 Technologies to Enhance Learning Experiences in Alternative School Settings

Science.gov (United States)

Karahan, Engin; Roehrig, Gillian

2016-01-01

As the learning paradigms are shifting to include various forms of digital technologies such as synchronous, asynchronous, and interactive methods, social networking technologies have been introduced to the educational settings in order to increase the quality of learning environments. The literature suggests that effective application of these…

The effect of the use of android-based application in learning together to improve students' academic performance

Science.gov (United States)

Ulfa, Andi Maria; Sugiyarto, Kristian H.; Ikhsan, Jaslin

2017-05-01

Poor achievement of students' performance on Chemistry may result from unfavourable learning processes. Therefore, innovation on learning process must be created. Regarding fast development of mobile technology, learning process cannot ignore the crucial role of the technology. This research and development (R&D) studies was done to develop android based application and to study the effect of its integration in Learning together (LT) into the improvement of students' learning creativity and cognitive achievement. The development of the application was carried out by adapting Borg & Gall and Dick & Carey model. The developed-product was reviewed by chemist, learning media practitioners, peer reviewers, and educators. After the revision based on the reviews, the application was used in the LT model on the topic of Stoichiometry in a senior high school. The instruments were questionnaires to get comments and suggestion from the reviewers about the application, and the another questionnaire was to collect the data of learning creativity. Another instrument used was a set of test by which data of students' achievement was collected. The results showed that the use of the mobile based application on Learning Together can bring about significant improvement of students' performance including creativity and cognitive achievement.

In search of design principles for developing digital learning & performance support for a student design task

NARCIS (Netherlands)

Bollen, Lars; Van der Meij, Hans; Leemkuil, Henny; McKenney, Susan

2016-01-01

A digital learning and performance support environment for university student design tasks was developed. This paper describes on the design rationale, process, and the usage results to arrive at a core set of design principles for the construction of such an environment. We present a collection of

In search of design principles for developing digital learning & performance support for a student design task

NARCIS (Netherlands)

Bollen, Lars; van der Meij, Hans; Leemkuil, Hendrik H.; McKenney, Susan

2015-01-01

A digital learning and performance support environment for university student design tasks was developed. This paper describes on the design rationale, process, and the usage results to arrive at a core set of design principles for the construction of such an environment. We present a collection of

Effects of Situated Mobile Learning Approach on Learning Motivation and Performance of EFL Students

Science.gov (United States)

Huang, Chester S. J.; Yang, Stephen J. H.; Chiang, Tosti H. C.; Su, Addison Y. S.

2016-01-01

This study developed a 5-step vocabulary learning (FSVL) strategy and a mobile learning tool in a situational English vocabulary learning environment and assessed their effects on the learning motivation and performance of English as a foreign language (EFL) students in a situational English vocabulary learning environment. Overall, 80 EFL…

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

Assessing Performance and Learning in Interprofessional Health Care Teams.

Science.gov (United States)

Ekmekci, Ozgur; Sheingold, Brenda; Plack, Margaret; LeLacheur, Susan; Halvaksz, Jennifer; Lewis, Karen; Schlumpf, Karen; Greenberg, Larrie

2015-01-01

Teamwork has become an integral part of health care delivery. Such emphasis on teamwork has generated the need to systematically measure and improve the learning and performance of health care teams. The purpose of this study was to develop a comprehensive assessment instrument, the Interprofessional Education and Practice Inventory (IPEPI), to evaluate learning and performance in interprofessional health care teams. The 12-month study commenced in three 4-month phases: (1) a panel of 25 national and international experts participated in the Delphi process to identify factors influencing team learning and team performance; (2) the research team analyzed the findings from the two Delphi rounds to develop the IPEPI; and (3) a cohort of 27 students at the university engaged in clinical simulations to test and refine the IPEPI. Findings suggest key factors that significantly influence team learning and performance include whether the group is able to foster a climate of mutual respect, adopt effective communication strategies, develop a sense of trust, and invite contributions from others. Additionally, in assessing organizational factors, participants indicated those factors that significantly influence team learning and performance include whether the organization is patient-centered, creates a culture of safety (not blame), and supports individual and team learning. These findings highlight the critical role assessment plays in enhancing not just interprofessional education or interprofessional practice, but in essence advancing interprofessional education and practice--which requires an integrated examination of how health care professionals learn and perform in teams.

Studying learning in the healthcare setting: the potential of quantitative diary methods.

Science.gov (United States)

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.

Atypical performance patterns on Delis-Kaplan Executive Functioning System Color-Word Interference Test: Cognitive switching and learning ability in older adults.

Science.gov (United States)

Berg, Jody-Lynn; Swan, Natasha M; Banks, Sarah J; Miller, Justin B

2016-09-01

Cognitive set shifting requires flexible application of lower level processes. The Delis-Kaplan Executive Functioning System (DKEFS) Color-Word Interference Test (CWIT) is commonly used to clinically assess cognitive set shifting. An atypical pattern of performance has been observed on the CWIT; a subset of individuals perform faster, with equal or fewer errors, on the more difficult inhibition/switching than the inhibition trial. This study seeks to explore the cognitive underpinnings of this atypical pattern. It is hypothesized that atypical patterns on CWIT will be associated with better performance on underlying cognitive measures of attention, working memory, and learning when compared to typical CWIT patterns. Records from 239 clinical referrals (age: M = 68.09 years, SD = 10.62; education: M = 14.87 years, SD = 2.73) seen for a neuropsychological evaluation as part of diagnostic work up in an outpatient dementia and movement disorders clinic were sampled. The standard battery of tests included measures of attention, learning, fluency, executive functioning, and working memory. Analyses of variance (ANOVAs) were conducted to compare the cognitive performance of those with typical versus atypical CWIT patterns. An atypical pattern of performance was confirmed in 23% of our sample. Analyses revealed a significant group difference in acquisition of information on both nonverbal (Brief Visuospatial Memory Test-Revised, BVMT-R total recall), F(1, 213) = 16.61, p < .001, and verbal (Hopkins Verbal Learning Test-Revised, HVLT-R total recall) learning tasks, F(1, 181) = 6.43, p < .01, and semantic fluency (Animal Naming), F(1, 232) = 7.57, p = .006, with the atypical group performing better on each task. Effect sizes were larger for nonverbal (Cohen's d = 0.66) than verbal learning (Cohen's d = 0.47) and semantic fluency (Cohen's d = 0.43). Individuals demonstrating an atypical pattern of performance on the CWIT inhibition/switching trial also demonstrated relative

Does individual learning styles influence the choice to use a web-based ECG learning programme in a blended learning setting?

Directory of Open Access Journals (Sweden)

Nilsson Mikael

2012-01-01

Full Text Available Abstract Background The compressed curriculum in modern knowledge-intensive medicine demands useful tools to achieve approved learning aims in a limited space of time. Web-based learning can be used in different ways to enhance learning. Little is however known regarding its optimal utilisation. Our aim was to investigate if the individual learning styles of medical students influence the choice to use a web-based ECG learning programme in a blended learning setting. Methods The programme, with three types of modules (learning content, self-assessment questions and interactive ECG interpretation training, was offered on a voluntary basis during a face to face ECG learning course for undergraduate medical students. The Index of Learning Styles (ILS and a general questionnaire including questions about computer and Internet usage, preferred future speciality and prior experience of E-learning were used to explore different factors related to the choice of using the programme or not. Results 93 (76% out of 123 students answered the ILS instrument and 91 the general questionnaire. 55 students (59% were defined as users of the web-based ECG-interpretation programme. Cronbach's alpha was analysed with coefficients above 0.7 in all of the four dimensions of ILS. There were no significant differences with regard to learning styles, as assessed by ILS, between the user and non-user groups; Active/Reflective; Visual/Verbal; Sensing/Intuitive; and Sequential/Global (p = 0.56-0.96. Neither did gender, prior experience of E-learning or preference for future speciality differ between groups. Conclusion Among medical students, neither learning styles according to ILS, nor a number of other characteristics seem to influence the choice to use a web-based ECG programme. This finding was consistent also when the usage of the different modules in the programme were considered. Thus, the findings suggest that web-based learning may attract a broad variety of medical

Issues and Considerations regarding Sharable Data Sets for Recommender Systems in Technology Enhanced Learning

DEFF Research Database (Denmark)

Drachsler, Hendrik; Bogers, Toine; Vuorikari, Riina

2010-01-01

This paper raises the issue of missing standardised data sets for recommender systems in Technology Enhanced Learning (TEL) that can be used as benchmarks to compare different recommendation approaches. It discusses how suitable data sets could be created according to some initial suggestions...

Acoustics in Physical Education Settings: The Learning Roadblock

Science.gov (United States)

Ryan, Stu; Mendel, Lisa Lucks

2010-01-01

Background: The audibility of teachers and peers is an essential factor in determining the academic performance of school children. However, acoustic conditions in most classrooms are less than optimal and have been viewed as "hostile listening environments" that undermine the learning of children in school. While research has shown that…

An Integrative Review of In-Class Activities That Enable Active Learning in College Science Classroom Settings

Science.gov (United States)

Arthurs, Leilani A.; Kreager, Bailey Zo

2017-01-01

Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about "active learning" in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are…

The use of an active learning approach in a SCALE-UP learning space improves academic performance in undergraduate General Biology.

Science.gov (United States)

Hacisalihoglu, Gokhan; Stephens, Desmond; Johnson, Lewis; Edington, Maurice

2018-01-01

Active learning is a pedagogical approach that involves students engaging in collaborative learning, which enables them to take more responsibility for their learning and improve their critical thinking skills. While prior research examined student performance at majority universities, this study focuses on specifically Historically Black Colleges and Universities (HBCUs) for the first time. Here we present work that focuses on the impact of active learning interventions at Florida A&M University, where we measured the impact of active learning strategies coupled with a SCALE-UP (Student Centered Active Learning Environment with Upside-down Pedagogies) learning environment on student success in General Biology. In biology sections where active learning techniques were employed, students watched online videos and completed specific activities before class covering information previously presented in a traditional lecture format. In-class activities were then carefully planned to reinforce critical concepts and enhance critical thinking skills through active learning techniques such as the one-minute paper, think-pair-share, and the utilization of clickers. Students in the active learning and control groups covered the same topics, took the same summative examinations and completed identical homework sets. In addition, the same instructor taught all of the sections included in this study. Testing demonstrated that these interventions increased learning gains by as much as 16%, and students reported an increase in their positive perceptions of active learning and biology. Overall, our results suggest that active learning approaches coupled with the SCALE-UP environment may provide an added opportunity for student success when compared with the standard modes of instruction in General Biology.

Effects of Multimodal Information on Learning Performance and Judgment of Learning

Science.gov (United States)

Chen, Gongxiang; Fu, Xiaolan

2003-01-01

Two experiments were conducted to investigate the effects of multimodal information on learning performance and judgment of learning (JOL). Experiment 1 examined the effects of representation type (word-only versus word-plus-picture) and presentation channel (visual-only versus visual-plus-auditory) on recall and immediate-JOL in fixed-rate…

Self-regulated learning and academic performance in medical education.

Science.gov (United States)

Lucieer, Susanna M; Jonker, Laura; Visscher, Chris; Rikers, Remy M J P; Themmen, Axel P N

2016-06-01

Medical schools aim to graduate medical doctors who are able to self-regulate their learning. It is therefore important to investigate whether medical students' self-regulated learning skills change during medical school. In addition, since these skills are expected to be helpful to learn more effectively, it is of interest to investigate whether these skills are related to academic performance. In a cross-sectional design, the Self-Regulation of Learning Self-Report Scale (SRL-SRS) was used to investigate the change in students' self-regulated learning skills. First and third-year students (N = 949, 81.7%) SRL-SRS scores were compared with ANOVA. The relation with academic performance was investigated with multinomial regression analysis. Only one of the six skills, reflection, significantly, but positively, changed during medical school. In addition, a small, but positive relation of monitoring, reflection, and effort with first-year GPA was found, while only effort was related to third-year GPA. The change in self-regulated learning skills is minor as only the level of reflection differs between the first and third year. In addition, the relation between self-regulated learning skills and academic performance is limited. Medical schools are therefore encouraged to re-examine the curriculum and methods they use to enhance their students' self-regulated learning skills. Future research is required to understand the limited impact on performance.

Intuitive Action Set Formation in Learning Classifier Systems with Memory Registers

NARCIS (Netherlands)

Simões, L.F.; Schut, M.C.; Haasdijk, E.W.

2008-01-01

An important design goal in Learning Classifier Systems (LCS) is to equally reinforce those classifiers which cause the level of reward supplied by the environment. In this paper, we propose a new method for action set formation in LCS. When applied to a Zeroth Level Classifier System with Memory

ELT Materials: The Key to Fostering Effective Teaching and Learning Settings

Directory of Open Access Journals (Sweden)

Astrid Núñez Pardo

2009-10-01

Full Text Available Our article aims at providing teachers with an overview for materials development, taking into account the experience gained by two teachers in the English Programme of the School of Education at Universidad Externado de Colombia in Bogotá. This experience has helped us achieve better teaching and learning conditions for our university students in their quest to learn a foreign language. This paper addresses the issue of the role of teachers as textbook developers, and how they can meet materials development demands by integrating a clear conceptualisation and set of principles as well as their essential components.

How Do Social Networks Influence Learning Outcomes? A Case Study in an Industrial Setting

Science.gov (United States)

Maglajlic, Seid; Helic, Denis

2012-01-01

and Purpose: The purpose of this research is to shed light on the impact of implicit social networks to the learning outcome of e-learning participants in an industrial setting. Design/methodology/approach: The paper presents a theoretical framework that allows the authors to measure correlation coefficients between the different affiliations that…

Exploring Daily Physical Activity and Nutrition Patterns in Early Learning Settings: Snapshots of Young Children in Head Start, Primary, and After-School Settings

Science.gov (United States)

Stegelin, Dolores A.; Anderson, Denise; Kemper, Karen; Wagner, Jennifer; Evans, Katharine

2014-01-01

The purpose of this research project was to gain a greater understanding of daily routines of 4-7 year olds regarding physical activity and nutrition practices in typical early learning environments. The settings selected for this observational study included Head Start, primary, and after-school learning environments in a city in the southeast.…

Benchmarking of protein descriptor sets in proteochemometric modeling (part 2): modeling performance of 13 amino acid descriptor sets

Science.gov (United States)

2013-01-01

Background While a large body of work exists on comparing and benchmarking descriptors of molecular structures, a similar comparison of protein descriptor sets is lacking. Hence, in the current work a total of 13 amino acid descriptor sets have been benchmarked with respect to their ability of establishing bioactivity models. The descriptor sets included in the study are Z-scales (3 variants), VHSE, T-scales, ST-scales, MS-WHIM, FASGAI, BLOSUM, a novel protein descriptor set (termed ProtFP (4 variants)), and in addition we created and benchmarked three pairs of descriptor combinations. Prediction performance was evaluated in seven structure-activity benchmarks which comprise Angiotensin Converting Enzyme (ACE) dipeptidic inhibitor data, and three proteochemometric data sets, namely (1) GPCR ligands modeled against a GPCR panel, (2) enzyme inhibitors (NNRTIs) with associated bioactivities against a set of HIV enzyme mutants, and (3) enzyme inhibitors (PIs) with associated bioactivities on a large set of HIV enzyme mutants. Results The amino acid descriptor sets compared here show similar performance (set differences ( > 0.3 log units RMSE difference and >0.7 difference in MCC). Combining different descriptor sets generally leads to better modeling performance than utilizing individual sets. The best performers were Z-scales (3) combined with ProtFP (Feature), or Z-Scales (3) combined with an average Z-Scale value for each target, while ProtFP (PCA8), ST-Scales, and ProtFP (Feature) rank last. Conclusions While amino acid descriptor sets capture different aspects of amino acids their ability to be used for bioactivity modeling is still – on average – surprisingly similar. Still, combining sets describing complementary information consistently leads to small but consistent improvement in modeling performance (average MCC 0.01 better, average RMSE 0.01 log units lower). Finally, performance differences exist between the targets compared thereby underlining that

Standard setting in the teaching and learning process in the Kenya ...

African Journals Online (AJOL)

Standards are set at different levels to govern different requirements that collectively add up to the ingredients of quality education of a child. This study investigated whether or not there are quantitative standards of achievement for guiding teaching and learning in the school system in Kenya. It also investigated teachers' ...

Goal Setting in Principal Evaluation: Goal Quality and Predictors of Achievement

Science.gov (United States)

Sinnema, Claire E. L.; Robinson, Viviane M. J.

2012-01-01

This article draws on goal-setting theory to investigate the goals set by experienced principals during their performance evaluations. While most goals were about teaching and learning, they tended to be vaguely expressed and only partially achieved. Five predictors (commitment, challenge, learning, effort, and support) explained a significant…

Performance management when innovation and learning become critical performance indicators

NARCIS (Netherlands)

Molleman, E.; Timmerman, H.

2003-01-01

If the organization's leading performance indicators shift towards innovation and the creation of knowledge, this will result in more non-routine work and a higher level of interdependency among workers. We argue that a contingent performance management (PM) system has to focus on Learning and group

The Effects of Goal Setting on Rugby Performance

Science.gov (United States)

Mellalieu, Stephen D.; Hanton, Sheldon; O'Brien, Michael

2006-01-01

Goal-setting effects on selected performance behaviors of 5 collegiate rugby players were assessed over an entire competitive season using self-generated targets and goal-attainment scaling. Results suggest that goal setting was effective for enhancing task-specific on-field behavior in rugby union. (Contains 1 figure.)

Predictors of science success: The impact of motivation and learning strategies on college chemistry performance

Science.gov (United States)

Obrentz, Shari B.

As the number of college students studying science continues to grow, it is important to identify variables that predict their success. The literature indicates that motivation and learning strategy use facilitate science success. Research findings show these variables can change throughout a semester and differ by performance level, gender and ethnicity. However, significant predictors of performance vary by research study and by group. The current study looks beyond the traditional predictors of grade point averages, SAT scores and completion of advanced placement (AP) chemistry to consider a comprehensive set of variables not previously investigated within the same study. Research questions address the predictive ability of motivation constructs and learning strategies for success in introductory college chemistry, how these variables change throughout a semester, and how they differ by performance level, gender and ethnicity. Participants were 413 introductory college chemistry students at a highly selective university in the southeast. Participants completed the Chemistry Motivation Questionnaire (CMQ) and Learning Strategies section of the Motivated Strategies for Learning Questionnaire (MSLQ) three times during the semester. Self-efficacy, effort regulation, assessment anxiety and previous achievement were significant predictors of chemistry course success. Levels of motivation changed with significant decreases in self-efficacy and increases in personal relevance and assessment anxiety. Learning strategy use changed with significant increases in elaboration, critical thinking, metacognitive self-regulation skills and peer learning, and significant decreases in time and study management and effort regulation. High course performers reported the highest levels of motivation and learning strategy use. Females reported lower intrinsic motivation, personal relevance, self-efficacy and critical thinking, and higher assessment anxiety, rehearsal and organization

Rapid and Accurate Machine Learning Recognition of High Performing Metal Organic Frameworks for CO2 Capture.

Science.gov (United States)

Fernandez, Michael; Boyd, Peter G; Daff, Thomas D; Aghaji, Mohammad Zein; Woo, Tom K

2014-09-04

In this work, we have developed quantitative structure-property relationship (QSPR) models using advanced machine learning algorithms that can rapidly and accurately recognize high-performing metal organic framework (MOF) materials for CO2 capture. More specifically, QSPR classifiers have been developed that can, in a fraction of a section, identify candidate MOFs with enhanced CO2 adsorption capacity (>1 mmol/g at 0.15 bar and >4 mmol/g at 1 bar). The models were tested on a large set of 292 050 MOFs that were not part of the training set. The QSPR classifier could recover 945 of the top 1000 MOFs in the test set while flagging only 10% of the whole library for compute intensive screening. Thus, using the machine learning classifiers as part of a high-throughput screening protocol would result in an order of magnitude reduction in compute time and allow intractably large structure libraries and search spaces to be screened.

Expansive learning in the university setting: the case for simulated clinical experience.

Science.gov (United States)

Haigh, Jacquelyn

2007-03-01

This paper argues that simulated practice in the university setting is not just a second best to learning in the clinical area but one which offers the potential for deliberation and deep learning [Eraut, M., 2000. Non-formal learning, implicit learning and tacit knowledge in professional work. Journal of Educational Psychology, 70, 113-136]. The context of student learning in an undergraduate midwifery programme is analysed using human activity theory [Engeström, Y., 2001. Expansive learning at work: toward an activity theoretical reconceptualization. Journal of Education and Work, 14, 133-156]. The advantages of this approach to student learning as opposed to situated learning theory and the concept of legitimate peripheral participation [Lave, J., Wenger, E., 1991. Situated Learning: Legitimate Peripheral Participation. Cambridge University Press, New York] are discussed. An activity system changes as a result of contradictions and tensions between what it purports to produce and the views of stakeholders (multi-voicedness) as well as its historical context (Historicity of activity). A focus group with students highlights their expressed need for more simulated practice experience. The views of midwifery lecturers are sought as an alternative voice on this tension in the current programme. Qualitative differences in types of simulated experience are explored and concerns about resources are raised in the analysis. Discussion considers the value of well planned simulations in encouraging the expression of tacit understanding through a group deliberative learning process [Eraut, M., 2000. Non-formal learning, implicit learning and tacit knowledge in professional work. Journal of Educational Psychology, 70, 113-136].

Redefining "Learning" in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?

Science.gov (United States)

Siegelman, Noam; Bogaerts, Louisa; Kronenfeld, Ofer; Frost, Ram

2017-10-07

From a theoretical perspective, most discussions of statistical learning (SL) have focused on the possible "statistical" properties that are the object of learning. Much less attention has been given to defining what "learning" is in the context of "statistical learning." One major difficulty is that SL research has been monitoring participants' performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow a brief visual or auditory familiarization stream. Is that all there is to characterizing SL abilities? Here we adopt a novel perspective for investigating the processing of regularities in the visual modality. By tracking online performance in a self-paced SL paradigm, we focus on the trajectory of learning. In a set of three experiments we show that this paradigm provides a reliable and valid signature of SL performance, and it offers important insights for understanding how statistical regularities are perceived and assimilated in the visual modality. This demonstrates the promise of integrating different operational measures to our theory of SL. © 2017 Cognitive Science Society, Inc.

Training and performance: The mediating role of organizational learning

Directory of Open Access Journals (Sweden)

María Isabel Barba Aragón

2014-07-01

Full Text Available Although there is a general recognition in the literature that training improves a firm's performance, empirical research does not always provide evidence to support this effect. One possible explanation is that training does not have a direct effect on performance but an indirect effect by improving other organizational outcomes. This paper suggests that organizational learning is one of those variables and that it mediates the relationship between training and performance and that the adoption of a learning-oriented training enhances performances through its positive effect on organizational learning. Using a sample of Spanish firms we obtain empirical evidence, which supports the view that this mediating effect is present.

Using Machine Learning to Predict Student Performance

OpenAIRE

Pojon, Murat

2017-01-01

This thesis examines the application of machine learning algorithms to predict whether a student will be successful or not. The specific focus of the thesis is the comparison of machine learning methods and feature engineering techniques in terms of how much they improve the prediction performance. Three different machine learning methods were used in this thesis. They are linear regression, decision trees, and naïve Bayes classification. Feature engineering, the process of modification ...

Progressive learning in endoscopy simulation training improves clinical performance: a blinded randomized trial.

Science.gov (United States)

Grover, Samir C; Scaffidi, Michael A; Khan, Rishad; Garg, Ankit; Al-Mazroui, Ahmed; Alomani, Tareq; Yu, Jeffrey J; Plener, Ian S; Al-Awamy, Mohamed; Yong, Elaine L; Cino, Maria; Ravindran, Nikila C; Zasowski, Mark; Grantcharov, Teodor P; Walsh, Catharine M

2017-11-01

A structured comprehensive curriculum (SCC) that uses simulation-based training (SBT) can improve clinical colonoscopy performance. This curriculum may be enhanced through the application of progressive learning, a training strategy centered on incrementally challenging learners. We aimed to determine whether a progressive learning-based curriculum (PLC) would lead to superior clinical performance compared with an SCC. This was a single-blinded randomized controlled trial conducted at a single academic center. Thirty-seven novice endoscopists were recruited and randomized to either a PLC (n = 18) or to an SCC (n = 19). The PLC comprised 6 hours of SBT, which progressed in complexity and difficulty. The SCC included 6 hours of SBT, with cases of random order of difficulty. Both groups received expert feedback and 4 hours of didactic teaching. Participants were assessed at baseline, immediately after training, and 4 to 6 weeks after training. The primary outcome was participants' performance during their first 2 clinical colonoscopies, as assessed by using the Joint Advisory Group Direct Observation of Procedural Skills assessment tool (JAG DOPS). Secondary outcomes were differences in endoscopic knowledge, technical and communication skills, and global performance in the simulated setting. The PLC group outperformed the SCC group during first and second clinical colonoscopies, measured by JAG DOPS (P PLC group had superior technical and communication skills and global performance in the simulated setting (P  .05). Our findings demonstrate the superiority of a PLC for endoscopic simulation, compared with an SCC. Challenging trainees progressively is a simple, theory-based approach to simulation whereby the performance of clinical colonoscopies can be improved. (Clinical trial registration number: NCT02000180.). Copyright © 2017 American Society for Gastrointestinal Endoscopy. Published by Elsevier Inc. All rights reserved.

ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

Directory of Open Access Journals (Sweden)

Suhaiza Ismail

2009-12-01

Full Text Available The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST was used to assess the approaches to learning adopted by students whilst the students final examination result was considered in examining the performance of the students. The results indicate that majority of the accounting students, both male andfemale groups prefer to use the deep approach in studying Business Finance. The findings also reveal that there were significant relationships between learning approaches and academic performance with positive direction appears for deep and strategic approaches whilst negative relationship reveals for surface approach.

Workplace wellness using online learning tools in a healthcare setting.

Science.gov (United States)

Blake, Holly; Gartshore, Emily

2016-09-01

The aim was to develop and evaluate an online learning tool for use with UK healthcare employees, healthcare educators and healthcare students, to increase knowledge of workplace wellness as an important public health issue. A 'Workplace Wellness' e-learning tool was developed and peer-reviewed by 14 topic experts. This focused on six key areas relating to workplace wellness: work-related stress, musculoskeletal disorders, diet and nutrition, physical activity, smoking and alcohol consumption. Each key area provided current evidence-based information on causes and consequences, access to UK government reports and national statistics, and guidance on actions that could be taken to improve health within a workplace setting. 188 users (93.1% female, age 18-60) completed online knowledge questionnaires before (n = 188) and after (n = 88) exposure to the online learning tool. Baseline knowledge of workplace wellness was poor (n = 188; mean accuracy 47.6%, s.d. 11.94). Knowledge significantly improved from baseline to post-intervention (mean accuracy = 77.5%, s.d. 13.71) (t(75) = -14.801, p online learning, indicating scope for development of further online packages relating to other important health parameters. Copyright © 2016 Elsevier Ltd. All rights reserved.

Optimizing performance through intrinsic motivation and attention for learning: The OPTIMAL theory of motor learning.

Science.gov (United States)

Wulf, Gabriele; Lewthwaite, Rebecca

2016-10-01

Effective motor performance is important for surviving and thriving, and skilled movement is critical in many activities. Much theorizing over the past few decades has focused on how certain practice conditions affect the processing of task-related information to affect learning. Yet, existing theoretical perspectives do not accommodate significant recent lines of evidence demonstrating motivational and attentional effects on performance and learning. These include research on (a) conditions that enhance expectancies for future performance, (b) variables that influence learners' autonomy, and (c) an external focus of attention on the intended movement effect. We propose the OPTIMAL (Optimizing Performance through Intrinsic Motivation and Attention for Learning) theory of motor learning. We suggest that motivational and attentional factors contribute to performance and learning by strengthening the coupling of goals to actions. We provide explanations for the performance and learning advantages of these variables on psychological and neuroscientific grounds. We describe a plausible mechanism for expectancy effects rooted in responses of dopamine to the anticipation of positive experience and temporally associated with skill practice. Learner autonomy acts perhaps largely through an enhanced expectancy pathway. Furthermore, we consider the influence of an external focus for the establishment of efficient functional connections across brain networks that subserve skilled movement. We speculate that enhanced expectancies and an external focus propel performers' cognitive and motor systems in productive "forward" directions and prevent "backsliding" into self- and non-task focused states. Expected success presumably breeds further success and helps consolidate memories. We discuss practical implications and future research directions.

Impact of problem-based learning in a large classroom setting: student perception and problem-solving skills.

Science.gov (United States)

Klegeris, Andis; Hurren, Heather

2011-12-01

Problem-based learning (PBL) can be described as a learning environment where the problem drives the learning. This technique usually involves learning in small groups, which are supervised by tutors. It is becoming evident that PBL in a small-group setting has a robust positive effect on student learning and skills, including better problem-solving skills and an increase in overall motivation. However, very little research has been done on the educational benefits of PBL in a large classroom setting. Here, we describe a PBL approach (using tutorless groups) that was introduced as a supplement to standard didactic lectures in University of British Columbia Okanagan undergraduate biochemistry classes consisting of 45-85 students. PBL was chosen as an effective method to assist students in learning biochemical and physiological processes. By monitoring student attendance and using informal and formal surveys, we demonstrated that PBL has a significant positive impact on student motivation to attend and participate in the course work. Student responses indicated that PBL is superior to traditional lecture format with regard to the understanding of course content and retention of information. We also demonstrated that student problem-solving skills are significantly improved, but additional controlled studies are needed to determine how much PBL exercises contribute to this improvement. These preliminary data indicated several positive outcomes of using PBL in a large classroom setting, although further studies aimed at assessing student learning are needed to further justify implementation of this technique in courses delivered to large undergraduate classes.

The Relationship of Learning and Performance Diagnosis at Different System Levels.

Science.gov (United States)

Lubega, Khalid

2003-01-01

Examines learning and performance diagnosis, separately and in relation to each other, as they function in organization systems; explains the relationship between learning and performance diagnosis at the individual, process, and organizational levels using a three-level performance model; and discusses types of learning, including nonlearning,…

Interests-in-motion in an informal, media-rich learning setting

Directory of Open Access Journals (Sweden)

Ty Hollett

2016-01-01

Full Text Available Much of the literature related to connected learning approaches youth interests as fixed on specific disciplines or activities (e.g. STEM, music production, or game design. As such, mentors design youth-focused programs to serve those interests. Through a micro-ethnographic analysis of two youth’s Minecraft-centered gameplay in a public library, this article makes two primary contributions to research on learning within, and the design of, informal, media-rich settings. First, rather than approach youth interests as fixed on specific disciplines or activities (e.g. STEM, music production, or video games, this article traces youth interests as they spark and emerge among individuals and groups. Then, it follows those interests as they subsequently spread over time, becoming interests-in-motion. Second, recognition of these interests-in-motion can lead mentors to develop program designs that enable learners to work with artifacts (digital and physical that learners can progressively configure and re-configure over time. Mentors, then, design-in-time as they harness the energy surrounding those emergent interests, creating extending learning opportunities in response.

ACCOUNTING STUDENT’S LEARNING APPROACHES AND IMPACT ON ACADEMIC PERFORMANCE

OpenAIRE

Suhaiza Ismail

2009-01-01

The objective of the study is threefold. Firstly, the study explores the learning approaches adopted by students in completing their Business Finance. Secondly, it examines the impact that learning approaches has on the student’s academic performance. Finally, the study considers gender differences in the learning approaches adopted by students and in the relationship between learning approaches and academic performance. The Approaches and Study Skills Inventory for Students (ASSIST) was used...

Scikit-learn: Machine Learning in Python

OpenAIRE

Pedregosa, Fabian; Varoquaux, Gaël; Gramfort, Alexandre; Michel, Vincent; Thirion, Bertrand; Grisel, Olivier; Blondel, Mathieu; Louppe, Gilles; Prettenhofer, Peter; Weiss, Ron; Dubourg, Vincent; Vanderplas, Jake; Passos, Alexandre; Cournapeau, David; Brucher, Matthieu

2012-01-01

Scikit-learn is a Python module integrating a wide range of state-of-the-art machine learning algorithms for medium-scale supervised and unsupervised problems. This package focuses on bringing machine learning to non-specialists using a general-purpose high-level language. Emphasis is put on ease of use, performance, documentation, and API consistency. It has minimal dependencies and is distributed under the simplified BSD license, encouraging its use in both academic and commercial settings....

Job-demand for learning and job-related learning: the mediating effect of job performance improvement initiatives

OpenAIRE

Loon, M; Bartram, T

2007-01-01

This study examined whether job-performance-improvementinitiatives mediate the relationship between individuals’ job-demand for learning and job-related learning. Data were obtained from 115 full-time\\ud employees in a diverse range of occupations. A partial least squares analysis revealed that job-performance-improvement-initiatives mediate partially the effects of job-demand for learning on job-related learning. Several implications\\ud for future research and policy are drawn from the findi...

The Relationship between Learning Organization Dimensions and Library Performance

Science.gov (United States)

Haley, Qing Kong

2010-01-01

The purpose of this research was to examine the relationship between learning organization dimensions and academic library performance. It studied whether differences existed in learning organization dimensions given the predictor variables of performance indicators, library resources, and demographics of the academic library. This research…

Applying Learning Analytics for the Early Prediction of Students' Academic Performance in Blended Learning

Science.gov (United States)

Lu, Owen H. T.; Huang, Anna Y. Q.; Huang, Jeff C. H.; Lin, Albert J. Q.; Ogata, Hiroaki; Yang, Stephen J. H.

2018-01-01

Blended learning combines online digital resources with traditional classroom activities and enables students to attain higher learning performance through well-defined interactive strategies involving online and traditional learning activities. Learning analytics is a conceptual framework and is a part of our Precision education used to analyze…

Effectiveness of simulation-based learning on student nurses' self-efficacy and performance while learning fundamental nursing skills.

Science.gov (United States)

Lin, Hsin-Hsin

2015-01-01

It was noted worldwide while learning fundamental skills and facing skills assessments, nursing students seemed to experience low confidence and high anxiety levels. Could simulation-based learning help to enhance students' self-efficacy and performance? Its effectiveness is mostly unidentified. This study was conducted to provide a shared experience to give nurse educators confidence and an insight into how simulation-based teaching can fit into nursing skills learning. A pilot study was completed with 50 second-year undergraduate nursing students, and the main study included 98 students where a pretest-posttest design was adopted. Data were gathered through four questionnaires and a performance assessment under scrutinized controls such as previous experiences, lecturers' teaching skills, duration of teaching, procedure of skills performance assessment and the inter-rater reliability. The results showed that simulation-based learning significantly improved students' self-efficacy regarding skills learning and the skills performance that nurse educators wish students to acquire. However, technology anxiety, examiners' critical attitudes towards students' performance and their unpredicted verbal and non-verbal expressions, have been found as possible confounding factors. The simulation-based learning proved to have a powerful positive effect on students' achievement outcomes. Nursing skills learning is one area that can benefit greatly from this kind of teaching and learning method.

Supervised learning with restricted training sets: a generating functional analysis

Energy Technology Data Exchange (ETDEWEB)

Heimel, J.A.F.; Coolen, A.C.C. [Department of Mathematics, King' s College London, Strand, London (United Kingdom)

2001-10-26

We study the dynamics of supervised on-line learning of realizable tasks in feed-forward neural networks. We focus on the regime where the number of examples used for training is proportional to the number of input channels N. Using generating functional techniques from spin glass theory, we are able to average over the composition of the training set and transform the problem for N{yields}{infinity} to an effective single pattern system described completely by the student autocovariance, the student-teacher overlap and the student response function with exact closed equations. Our method applies to arbitrary learning rules, i.e., not necessarily of a gradient-descent type. The resulting exact macroscopic dynamical equations can be integrated without finite-size effects up to any degree of accuracy, but their main value is in providing an exact and simple starting point for analytical approximation schemes. Finally, we show how, in the region of absent anomalous response and using the hypothesis that (as in detailed balance systems) the short-time part of the various operators can be transformed away, one can describe the stationary state of the network successfully by a set of coupled equations involving only four scalar order parameters. (author)

Designing and Facilitating Learning in a Cooperative Setting

DEFF Research Database (Denmark)

Poulsen, Søren Bolvig; Rustrup, Louise Lønborg; Mortensen, Helle

2010-01-01

the learning of students. Student involvement in research projects appears to be an increasing trend, which is affecting both the practice of research and education. The Danish research project ‘Innodoors’ investigates, through various initiatives, how User-driven innovation can contribute to innovation...... and affect the culture of innovation in the building sector. One of the research initiatives was originally probing hypothesizes through student projects, where the students not only play a practical and performing role, but also engage in a rather equal partnership with the academic. This was also the case...... for the involved industrial design students, but they found it necessary to redefine the initial, given hypothesis, which surprisingly uncovered knowledge deficiencies for both students and academic; yet, it contributed to a mutual learning situation. Educators are facing new challenges with the responsibility...

Motivating Students through Awareness of the Natural Correlation between College Learning and Corporate Work Settings

Science.gov (United States)

D'Aloisio, Anna

2006-01-01

This article argues that college students can be motivated to be active participants in their own education if made aware of the direct correlation between college learning and corporate work settings. Students can be shown that through the natural course of college learning, they are acquiring valuable core skills or transferable competencies…

Active explorers show low learning performance in a social insect

Institute of Scientific and Technical Information of China (English)

Eve UDINO; Margot PEREZ; Claudio CARERE; Patrizia d'ETTORRE

2017-01-01

An intriguing question in behavioral biology is whether consistent individual differences (called animal personalities) relate to variation in cognitive performance because commonly measured personality traits may be associated with risk-reward trade-offs.Social insects,whose learning abilities have been extensively characterized,show consistent behavioral variability,both at colony and at individual level.We investigated the possible link between personality traits and learning performance in the carpenter ant Camponotus aethiops.Exploratory activity,sociability,and aggression were assessed twice in ant foragers.Behaviors differed among individuals,they were partly repeatable across time and exploratory activity correlated positively with aggression.Learning abilities were quantified by differential conditioning of the maxilla-labium extension response,a task that requires cue perception and information storage.We found that exploratory activity of individual ants significantly predicted learning performance:"active-explorers" were slower in learning the task than "inactive-explorers".The results suggest for the first time a link between a personality trait and cognitive performance in eusocial insects,and that the underlying individual variability could affect colony performance and success.

Collimator settings and performance in 2011 and 2012

International Nuclear Information System (INIS)

Bruce, R.; Assmann, R.W.; Burkart, F.; Cauchi, M.; Deboy, D.; Lari, L.; Redaelli, S; Rossi, A.; Salvachua, B.; Valentino, G.; Wollmann, D.

2012-01-01

Collimator settings and performance are key parameters for deciding the reach in intensity and β* in order to conclude on possible limits for the 2012 run, a summary is first given of the relevant running experience in 2011 and the collimation-related MDs. These include among others tight collimator settings, a quench test, and aperture measurements. Based on the 2011 experience, we conclude on possible running scenarios for 2012 in terms of collimator settings, intensity and β* from the collimation point of view. (authors)

The Influence of Virtual Learning Environments in Students' Performance

Science.gov (United States)

Alves, Paulo; Miranda, Luísa; Morais, Carlos

2017-01-01

This paper focuses mainly on the relation between the use of a virtual learning environment (VLE) and students' performance. Therefore, virtual learning environments are characterised and a study is presented emphasising the frequency of access to a VLE and its relation with the students' performance from a public higher education institution…

A Learning Style-Based Grouping Collaborative Learning Approach to Improve EFL Students' Performance in English Courses

Science.gov (United States)

Kuo, Yu-Chen; Chu, Hui-Chun; Huang, Chi-Hao

2015-01-01

Learning English is an important and challenging task for English as Foreign Language (EFL) students. Educators had indicated that, without proper learning support, most EFL students might feel frustrated while learning English, which could significantly affect their learning performance. In the past research, learning usually utilized grouping,…

Goal Setting and Expectancy Theory Predictions of Effort and Performance.

Science.gov (United States)

Dossett, Dennis L.; Luce, Helen E.

Neither expectancy (VIE) theory nor goal setting alone are effective determinants of individual effort and task performance. To test the combined ability of VIE and goal setting to predict effort and performance, 44 real estate agents and their managers completed questionnaires. Quarterly income goals predicted managers' ratings of agents' effort,…

Assessing the Performance of a Machine Learning Algorithm in Identifying Bubbles in Dust Emission

Science.gov (United States)

Xu, Duo; Offner, Stella S. R.

2017-12-01

Stellar feedback created by radiation and winds from massive stars plays a significant role in both physical and chemical evolution of molecular clouds. This energy and momentum leaves an identifiable signature (“bubbles”) that affects the dynamics and structure of the cloud. Most bubble searches are performed “by eye,” which is usually time-consuming, subjective, and difficult to calibrate. Automatic classifications based on machine learning make it possible to perform systematic, quantifiable, and repeatable searches for bubbles. We employ a previously developed machine learning algorithm, Brut, and quantitatively evaluate its performance in identifying bubbles using synthetic dust observations. We adopt magnetohydrodynamics simulations, which model stellar winds launching within turbulent molecular clouds, as an input to generate synthetic images. We use a publicly available three-dimensional dust continuum Monte Carlo radiative transfer code, HYPERION, to generate synthetic images of bubbles in three Spitzer bands (4.5, 8, and 24 μm). We designate half of our synthetic bubbles as a training set, which we use to train Brut along with citizen-science data from the Milky Way Project (MWP). We then assess Brut’s accuracy using the remaining synthetic observations. We find that Brut’s performance after retraining increases significantly, and it is able to identify yellow bubbles, which are likely associated with B-type stars. Brut continues to perform well on previously identified high-score bubbles, and over 10% of the MWP bubbles are reclassified as high-confidence bubbles, which were previously marginal or ambiguous detections in the MWP data. We also investigate the influence of the size of the training set, dust model, evolutionary stage, and background noise on bubble identification.

The use of Edmodo in teaching writing in a blended learning setting

Directory of Open Access Journals (Sweden)

Pupung Purnawarman

2016-01-01

Full Text Available The advancement of technology provides education with varioussolutions to create new learning environments. Edmodo as a learning platform is believed to offera solution in the teaching of English, particularly for teaching writing. This research was aimed to investigate how Edmodo as a learning platform,in a blended learning setting, was implemented in teaching writing in its combination with Genre-based Approach, how Edmodo facilitated students’ engagement, and how students perceived the use of Edmodo in teaching and learning activities. This research employed a qualitative approach with case study design. The research involved 17 participants from the eleventh grade of a senior high school in Bandung, Indonesia. The data were collected through observations, document analysis, interviews, and questionnaires. The results showed that in teaching writing,it was possible to integrate Edmodo into GBA writing cycles. Edmodo also facilitated students’ engagement cognitively during classroom sessions. The students showed various responses towards the use of Edmodo based on the Uses and Gratification Theory (UGT framework. Some issues on the use of Edmodo identified in this research were bandwidth, confusion in using Edmodo, incompatibility of smartphone applications, and students’ lack responsibilities for learning. The suggestions for the authority and areas of further research are presented.

Stressors, academic performance, and learned resourcefulness in baccalaureate nursing students.

Science.gov (United States)

Goff, Anne-Marie

2011-01-01

High stress levels in nursing students may affect memory, concentration, and problem-solving ability, and may lead to decreased learning, coping, academic performance, and retention. College students with higher levels of learned resourcefulness develop greater self-confidence, motivation, and academic persistence, and are less likely to become anxious, depressed, and frustrated, but no studies specifically involve nursing students. This explanatory correlational study used Gadzella's Student-life Stress Inventory (SSI) and Rosenbaum's Self Control Scale (SCS) to explore learned resourcefulness, stressors, and academic performance in 53 baccalaureate nursing students. High levels of personal and academic stressors were evident, but not significant predictors of academic performance (p = .90). Age was a significant predictor of academic performance (p = learned resourcefulness scores than females and Caucasians. Studies in larger, more diverse samples are necessary to validate these findings.

Learning of pitch and time structures in an artificial grammar setting.

Science.gov (United States)

Prince, Jon B; Stevens, Catherine J; Jones, Mari Riess; Tillmann, Barbara

2018-04-12

Despite the empirical evidence for the power of the cognitive capacity of implicit learning of structures and regularities in several modalities and materials, it remains controversial whether implicit learning extends to the learning of temporal structures and regularities. We investigated whether (a) an artificial grammar can be learned equally well when expressed in duration sequences as when expressed in pitch sequences, (b) learning of the artificial grammar in either duration or pitch (as the primary dimension) sequences can be influenced by the properties of the secondary dimension (invariant vs. randomized), and (c) learning can be boosted when the artificial grammar is expressed in both pitch and duration. After an exposure phase with grammatical sequences, learning in a subsequent test phase was assessed in a grammaticality judgment task. Participants in both the pitch and duration conditions showed incidental (not fully implicit) learning of the artificial grammar when the secondary dimension was invariant, but randomizing the pitch sequence prevented learning of the artificial grammar in duration sequences. Expressing the artificial grammar in both pitch and duration resulted in disproportionately better performance, suggesting an interaction between the learning of pitch and temporal structure. The findings are relevant to research investigating the learning of temporal structures and the learning of structures presented simultaneously in 2 dimensions (e.g., space and time, space and objects). By investigating learning, the findings provide further insight into the potential specificity of pitch and time processing, and their integrated versus independent processing, as previously debated in music cognition research. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Performance Evaluation of Feature Sets of Minutiae Quadruplets ...

African Journals Online (AJOL)

The features proposed in this paper are derived from minutiae quadruplets and are applicable in matching and indexing ngerprint images. In this work nineteen different possibilities of features were explored for indexing and the performances of some of the feature sets were mixed: some giving good performances on ...

Investigating the Relationship between Learning Styles and ESP Reading Strategies in Academic Setting

Directory of Open Access Journals (Sweden)

Parviz Ajideh

2018-05-01

Full Text Available The present study investigated the relationship between Art and Science students’ learning styles and their ESP reading strategies in academic settings. Learning styles are defined as general orientations learners take toward their learning experiences. This notion has recently obtained attention in the area of language learning. Strategies are also defined as specific behaviours or techniques learners employ towards leaning in order to achieve their learning goals. The strategies chosen are often linked to the individual's learning style. The purpose of this study was to identify Art and Science students’ major learning style preferences and their strategies they employ to tackle their reading materials in ESP courses at Tabriz Islamic Art University. To this end, 313 Art and Science students at Tabriz Islamic Art University answered two self-report questionnaires (PLSPQ and SORS to identify their major and minor learning styles as well as their reading strategies in ESP reading. In order to find any relationship between the students’ preferred learning style (s and their reading strategies in ESP, Pearson Product Moment Coefficient r was used to analyze the participants’ answers to the questionnaires. The results showed that Art students favored Kinesthetic, Auditory, Visual and Tactile learning styles as their major learning styles while Science students showed preference to only Kinesthetic Learning style as their major learning style and other learning styles as their minor ones. It was also found that the most dominant reading strategies both Art and Science students apply in reading their ESP texts was cognitive strategies. Correlational analyses of their major learning styles and their reading strategies are discussed.

Using a collaborative Mobile Augmented Reality learning application (CoMARLA) to improve Improve Student Learning

Science.gov (United States)

Hanafi, Hafizul Fahri bin; Soh Said, Che; Hanee Ariffin, Asma; Azlan Zainuddin, Nur; Samsuddin, Khairulanuar

2016-11-01

This study was carried out to improve student learning in ICT course using a collaborative mobile augmented reality learning application (CoMARLA). This learning application was developed based on the constructivist framework that would engender collaborative learning environment, in which students could learn collaboratively using their mobile phones. The research design was based on the pretest posttest control group design. The dependent variable was students’ learning performance after learning, and the independent variables were learning method and gender. Students’ learning performance before learning was treated as the covariate. The sample of the study comprised 120 non-IT (non-technical) undergraduates, with the mean age of 19.5. They were randomized into two groups, namely the experimental and control group. The experimental group used CoMARLA to learn one of the topics of the ICT Literacy course, namely Computer System; whereas the control group learned using the conventional approach. The research instrument used was a set of multiple-choice questions pertaining to the above topic. Pretesting was carried out before the learning sessions, and posttesting was performed after 6 hours of learning. Using the SPSS, Analysis of Covariance (ANCOVA) was performed on the data. The analysis showed that there were main effects attributed to the learning method and gender. The experimental group outperformed the control group by almost 9%, and male students outstripped their opposite counterparts by as much as 3%. Furthermore, an interaction effect was also observed showing differential performances of male students based on the learning methods, which did not occur among female students. Hence, the tool can be used to help undergraduates learn with greater efficacy when contextualized in an appropriate setting.

Academic Performance in Introductory Accounting: Do Learning Styles Matter?

Science.gov (United States)

Tan, Lin Mei; Laswad, Fawzi

2015-01-01

This study examines the impact of learning styles on academic performance using major assessment methods (examinations and assignments including multiple-choice and constructed response questions (CRQs)) in an introductory accounting course. Students' learning styles were assessed using Kolb's Learning Style Inventory Version 3.1. The results…

Learning Apache Solr high performance

CERN Document Server

Mohan, Surendra

2014-01-01

This book is an easy-to-follow guide, full of hands-on, real-world examples. Each topic is explained and demonstrated in a specific and user-friendly flow, from search optimization using Solr to Deployment of Zookeeper applications. This book is ideal for Apache Solr developers and want to learn different techniques to optimize Solr performance with utmost efficiency, along with effectively troubleshooting the problems that usually occur while trying to boost performance. Familiarity with search servers and database querying is expected.

Science learning motivation as correlate of students’ academic performances

Directory of Open Access Journals (Sweden)

Nhorvien Jay P. Libao

2016-09-01

Full Text Available This study was designed to analyze the relationship  of students’ learning motivation and their academic performances in science. The study made use of 21 junior and senior Biological Science students to conclude on the formulated research problems. The respondents had a good to very good motivation in learning science. In general, the extent of their motivation do not vary across their sex, age, and curriculum year. Moreover, the respondents had good academic performances in science. Aptly, extrinsic motivation was found to be related with their academic performances among the indicators of motivations in learning science.

Task-based incidental vocabulary learning in L2 Arabic: The role of proficiency and task performance

Directory of Open Access Journals (Sweden)

Ayman A. Mohamed

2016-03-01

Full Text Available This study tests the claim that word learning in a second language are contingent upon a task’s involvement load (i.e. the amount of need, search, and evaluation it imposes, as proposed by Laufer and Hulstijn (2001. Fifty-three English-speaking learners of Arabic were assigned to one of three vocabulary learning tasks that varied in the degree of involvement: reading comprehension with glosses (low, fill-in-the-gap task (medium, and sentence writing (high. Ten words, selected based on a pretest, were targeted in the tasks. Results showed a main effect of task, with the sentence writing task yielding the highest rates of vocabulary learning, followed by the gap-fill task, and finally the reading comprehension task. A significant correlation was found between accuracy of performance across participants and their subsequent vocabulary acquisition in the immediate posttest. Within groups, only the performance of the writing group correlated significantly with their posttest scores. Results of the present study validate the hypothesis and point to multiple factors at play in incidental vocabulary acquisition. The study provides further arguments to refine the hypothesis and implement pedagogical practices that accommodate incidental learning in foreign language settings.

The influence of the negative-positive ratio and screening database size on the performance of machine learning-based virtual screening.

Science.gov (United States)

Kurczab, Rafał; Bojarski, Andrzej J

2017-01-01

The machine learning-based virtual screening of molecular databases is a commonly used approach to identify hits. However, many aspects associated with training predictive models can influence the final performance and, consequently, the number of hits found. Thus, we performed a systematic study of the simultaneous influence of the proportion of negatives to positives in the testing set, the size of screening databases and the type of molecular representations on the effectiveness of classification. The results obtained for eight protein targets, five machine learning algorithms (SMO, Naïve Bayes, Ibk, J48 and Random Forest), two types of molecular fingerprints (MACCS and CDK FP) and eight screening databases with different numbers of molecules confirmed our previous findings that increases in the ratio of negative to positive training instances greatly influenced most of the investigated parameters of the ML methods in simulated virtual screening experiments. However, the performance of screening was shown to also be highly dependent on the molecular library dimension. Generally, with the increasing size of the screened database, the optimal training ratio also increased, and this ratio can be rationalized using the proposed cost-effectiveness threshold approach. To increase the performance of machine learning-based virtual screening, the training set should be constructed in a way that considers the size of the screening database.

A new intelligent classifier for breast cancer diagnosis based on a rough set and extreme learning machine: RS + ELM

OpenAIRE

KAYA, Yılmaz

2014-01-01

Breast cancer is one of the leading causes of death among women all around the world. Therefore, true and early diagnosis of breast cancer is an important problem. The rough set (RS) and extreme learning machine (ELM) methods were used collectively in this study for the diagnosis of breast cancer. The unnecessary attributes were discarded from the dataset by means of the RS approach. The classification process by means of ELM was performed using the remaining attributes. The Wisconsin B...

Learning Climate and Job Performance among Health Workers. A Pilot Study.

Science.gov (United States)

Cortini, Michela; Pivetti, Monica; Cervai, Sara

2016-01-01

This paper will explore if and how psychological strain plays a mediator role between the learning climate and job performance in a group of health workers. Although the relationship between learning climate and job performance has already been explored in the international literature, the role of psychological strain, which may hamper or deepen this relationship, has yet to be investigated. The research hypothesis is that psychological strain mediates the relationship between the climate toward learning (including also the error avoidance climate) and job performance. Data were gathered in a Public hospital in Italy. Participants ( N = 61) were health professionals (nurses and obstetricians). Considering the relatively small sample size, a mediation analysis with the aid of the SPSS macro PROCESS was performed. The results show that the relationship between the learning climate (specifically its dimension of organizational appreciation toward learning) and job performance is mediated by psychological strain. The future research agenda and practical implications are discussed in the paper.

Academic performance in blended learning in higher education

OpenAIRE

Moreira, J. António; Mendes, Alexandra

2011-01-01

Institutions of Higher Education in Portugal face today unique challenges. Aware of the change, in general, these institutions have presented reform initiatives covering in their strategic plans new frames ofoperation, where e-learning and/or b-learning are recognized. The present study aims mainly to know the impact that b-learning and the implementation of some pedagogical models adapted to these environments may have on academic performance of students in higher education. Data analysis, r...

performance evaluation of feature sets of minutiae quadruplets

African Journals Online (AJOL)

databases. This shows that the evaluation of algorithms on just one or two databases is not sufficient to confirm the performance of tech- niques as they may be database-dependent. Much work was done to find a feature-set that would have a good performance across three. FVC databases of the FVC 2000, 2002 and. 2004 ...

Mobile Learning: Can Students Really Multitask?

Science.gov (United States)

Coens, Joke; Reynvoet, Bert; Clarebout, Geraldine

2011-01-01

The advent of mobile learning offers opportunities for students to do two things at once in an educational context: learning while performing another activity. The main aim of the reported studies is to address the effect of multitasking on learning with a mobile device. Two experiments were set up to examine the effect of performing a secondary…

Beyond Performativity: A Pragmatic Model of Teacher Professional Learning

Science.gov (United States)

Lloyd, Margaret; Davis, James P.

2018-01-01

The intent and content of teacher professional learning has changed in recent times to meet the demands of performativity. In this article, we offer and demonstrate a pragmatic way to map teacher professional learning that both meets current demands and secures a place for teacher-led catalytic learning. To achieve this, we position identified…

"May We Please Have Sex Tonight?"--People with Learning Difficulties Pursuing Privacy in Residential Group Settings

Science.gov (United States)

Hollomotz, Andrea

2009-01-01

Many residential group settings for people with learning difficulties do not provide individuals with the private space in which they can explore their sexual relationships in a safe and dignified manner. Lack of agreed private spaces seriously infringes the individual's human rights. Many people with learning difficulties who lack privacy have no…

Beliefs about and Intention to Learn a Foreign Language in Face-to-Face and Online Settings

Science.gov (United States)

Alhamami, Munassir

2018-01-01

This mixed-methods study investigates language learners' intention to attend a class and learn a foreign language in face-to-face and online settings using Ajzen's theory of planned behavior (TPB). The data were collected using interviews, questionnaires, and treatments with participants in two groups: a face-to-face language learning (FLL) group…

A Correlation Study among Achievement Motivation, Goal-Setting and L2 Learning Strategy in EFL Context

Science.gov (United States)

Han, Jing; Lu, Qingsheng

2018-01-01

Achievement motivation as one of the most important parts in learning motivation indicates a concern with success in competition with some standard of excellence. Learners who are highly motivated to learn a language are likely to use a variety of strategies. Besides achievement motivation, goal setting, a very important cognitive mediator between…

Novel gene sets improve set-level classification of prokaryotic gene expression data.

Science.gov (United States)

Holec, Matěj; Kuželka, Ondřej; Železný, Filip

2015-10-28

Set-level classification of gene expression data has received significant attention recently. In this setting, high-dimensional vectors of features corresponding to genes are converted into lower-dimensional vectors of features corresponding to biologically interpretable gene sets. The dimensionality reduction brings the promise of a decreased risk of overfitting, potentially resulting in improved accuracy of the learned classifiers. However, recent empirical research has not confirmed this expectation. Here we hypothesize that the reported unfavorable classification results in the set-level framework were due to the adoption of unsuitable gene sets defined typically on the basis of the Gene ontology and the KEGG database of metabolic networks. We explore an alternative approach to defining gene sets, based on regulatory interactions, which we expect to collect genes with more correlated expression. We hypothesize that such more correlated gene sets will enable to learn more accurate classifiers. We define two families of gene sets using information on regulatory interactions, and evaluate them on phenotype-classification tasks using public prokaryotic gene expression data sets. From each of the two gene-set families, we first select the best-performing subtype. The two selected subtypes are then evaluated on independent (testing) data sets against state-of-the-art gene sets and against the conventional gene-level approach. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. The novel gene sets are indeed more correlated than the conventional ones, and lead to significantly more accurate classifiers. Novel gene sets defined on the basis of regulatory interactions improve set-level classification of gene expression data. The experimental scripts and other material needed to reproduce the experiments are available at http://ida.felk.cvut.cz/novelgenesets.tar.gz.

Group performance and group learning at dynamic system control tasks

International Nuclear Information System (INIS)

Drewes, Sylvana

2013-01-01

Proper management of dynamic systems (e.g. cooling systems of nuclear power plants or production and warehousing) is important to ensure public safety and economic success. So far, research has provided broad evidence for systematic shortcomings in individuals' control performance of dynamic systems. This research aims to investigate whether groups manifest synergy (Larson, 2010) and outperform individuals and if so, what processes lead to these performance advantages. In three experiments - including simulations of a nuclear power plant and a business setting - I compare the control performance of three-person-groups to the average individual performance and to nominal groups (N = 105 groups per experiment). The nominal group condition captures the statistical advantage of aggregated group judgements not due to social interaction. First, results show a superior performance of groups compared to individuals. Second, a meta-analysis across all three experiments shows interaction-based process gains in dynamic control tasks: Interacting groups outperform the average individual performance as well as the nominal group performance. Third, group interaction leads to stable individual improvements of group members that exceed practice effects. In sum, these results provide the first unequivocal evidence for interaction-based performance gains of groups in dynamic control tasks and imply that employers should rely on groups to provide opportunities for individual learning and to foster dynamic system control at its best.

Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa

Science.gov (United States)

2014-01-01

Neuropsychology, in press     Simulating Category Learning and Set Shifting Deficits in Patients Weight-Restored from Anorexia Nervosa J...University   Objective: To examine set shifting in a group of women previously diagnosed with anorexia nervosa (AN) who are now weight-restored (AN-WR...participant fails to switch to the new rule but rather persists with the previously correct rule. Adult patients with Anorexia Nervosa (AN) are often impaired

Internationalization and Hotel Performance

DEFF Research Database (Denmark)

Assaf, Albert G.; Josiassen, Alexander; Oh, Haemon

2016-01-01

Few industries are as inherently international as the hotel industry. This article sets out to investigate the impact of internationalization on performance in the hotel industry. Building on the theory of organizational learning the authors test several hypotheses regarding the shape of the inte......Few industries are as inherently international as the hotel industry. This article sets out to investigate the impact of internationalization on performance in the hotel industry. Building on the theory of organizational learning the authors test several hypotheses regarding the shape...... of the internationalization–performance relationship as well as the impact of four moderating variables. In line with the research aim and the underlying dynamism of organizational learning theory, these hypotheses are tested using a dynamic Bayesian model. The results indicate that internationalization has a U-shaped impact...

A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

Science.gov (United States)

Giraldo, Sergio I.; Ramirez, Rafael

2016-01-01

Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules

A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music

Directory of Open Access Journals (Sweden)

Sergio Ivan Giraldo

2016-12-01

Full Text Available Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1 quantitatively evaluate the accuracy of the induced models, (2 analyse the relative importance of the considered musical features, (3 discuss some of the learnt expressive performance rules in the context of previous work, and (4 assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules’ performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the

A Machine Learning Approach to Discover Rules for Expressive Performance Actions in Jazz Guitar Music.

Science.gov (United States)

Giraldo, Sergio I; Ramirez, Rafael

2016-01-01

Expert musicians introduce expression in their performances by manipulating sound properties such as timing, energy, pitch, and timbre. Here, we present a data driven computational approach to induce expressive performance rule models for note duration, onset, energy, and ornamentation transformations in jazz guitar music. We extract high-level features from a set of 16 commercial audio recordings (and corresponding music scores) of jazz guitarist Grant Green in order to characterize the expression in the pieces. We apply machine learning techniques to the resulting features to learn expressive performance rule models. We (1) quantitatively evaluate the accuracy of the induced models, (2) analyse the relative importance of the considered musical features, (3) discuss some of the learnt expressive performance rules in the context of previous work, and (4) assess their generailty. The accuracies of the induced predictive models is significantly above base-line levels indicating that the audio performances and the musical features extracted contain sufficient information to automatically learn informative expressive performance patterns. Feature analysis shows that the most important musical features for predicting expressive transformations are note duration, pitch, metrical strength, phrase position, Narmour structure, and tempo and key of the piece. Similarities and differences between the induced expressive rules and the rules reported in the literature were found. Differences may be due to the fact that most previously studied performance data has consisted of classical music recordings. Finally, the rules' performer specificity/generality is assessed by applying the induced rules to performances of the same pieces performed by two other professional jazz guitar players. Results show a consistency in the ornamentation patterns between Grant Green and the other two musicians, which may be interpreted as a good indicator for generality of the ornamentation rules.

How Successful Learners Employ Learning Strategies in an EFL Setting in the Indonesian Context

Science.gov (United States)

Setiyadi, Ag. Bambang; Sukirlan, Muhammad; Mahpul

2016-01-01

Numerous studies have been conducted to correlate the use of language learning strategies and language performance and the studies have contributed to different perspectives of teaching and learning a foreign language. Some studies have also revealed that the students learning a foreign language in Asian contexts have been proved to use different…

Assessing students in community settings: the role of peer evaluation

NARCIS (Netherlands)

H.G. Schmidt (Henk); D.H.J.M. Dolmans (Diana); A.A. Abdel-Hameed (Ahmed); M.E.M. Mohi Eldin (Magzoub)

1998-01-01

textabstractThe assessment of students in community settings faces unique difficulties. Since students are usually posted in small groups in different community settings and since the learning (largely) takes place outside the classroom, assessing student performance becomes an intrinsically complex

Linking public health nursing competencies and service-learning in a global setting.

Science.gov (United States)

Brown, Cynthia L

2017-09-01

Nurse educators in baccalaureate programs are charged with addressing student competence in public health nursing practice. These educators are also responsible for creating nursing student opportunities for civic engagement and development of critical thinking skills. The IOM report (2010) on the Future of Nursing emphasizes the nurse educator's role in promoting collaborative partnerships that incorporate interdisciplinary and intraprofessional efforts to promote health. The purpose of this article is to describe an innovative approach to address public health nursing competencies and to improve the health and well-being of indigenous populations in a global setting through promotion of collaboration and service- learning principles. As part of a hybrid elective course, baccalaureate nursing students from various nursing tracks participated in a 2 week immersion experience in Belize that included preimmersion preparation. These students were to collaborate among themselves and with Belizean communities to address identified health knowledge deficits and health-related needs for school-aged children and adult populations. Students successfully collaborated in order to meet health-related needs and to engage in health promotion activities in the Toledo district of Belize. They also gained practice in developing public health nursing competencies for entry-level nursing practice. Implementation of service-learning principles provided students with opportunities for civic engagement and self-reflection. Some challenges existed from the students', faculty, and global community's perspectives. Lack of culturally appropriate and country specific health education materials was difficult for students and the community. Faculty encountered challenges in communicating and collaborating with the Belizean partners. Commonalities exist between entry-level public health nursing competencies and service-learning principles. Using service-learning principles in the development of

Maximizing lipocalin prediction through balanced and diversified training set and decision fusion.

Science.gov (United States)

Nath, Abhigyan; Subbiah, Karthikeyan

2015-12-01

Lipocalins are short in sequence length and perform several important biological functions. These proteins are having less than 20% sequence similarity among paralogs. Experimentally identifying them is an expensive and time consuming process. The computational methods based on the sequence similarity for allocating putative members to this family are also far elusive due to the low sequence similarity existing among the members of this family. Consequently, the machine learning methods become a viable alternative for their prediction by using the underlying sequence/structurally derived features as the input. Ideally, any machine learning based prediction method must be trained with all possible variations in the input feature vector (all the sub-class input patterns) to achieve perfect learning. A near perfect learning can be achieved by training the model with diverse types of input instances belonging to the different regions of the entire input space. Furthermore, the prediction performance can be improved through balancing the training set as the imbalanced data sets will tend to produce the prediction bias towards majority class and its sub-classes. This paper is aimed to achieve (i) the high generalization ability without any classification bias through the diversified and balanced training sets as well as (ii) enhanced the prediction accuracy by combining the results of individual classifiers with an appropriate fusion scheme. Instead of creating the training set randomly, we have first used the unsupervised Kmeans clustering algorithm to create diversified clusters of input patterns and created the diversified and balanced training set by selecting an equal number of patterns from each of these clusters. Finally, probability based classifier fusion scheme was applied on boosted random forest algorithm (which produced greater sensitivity) and K nearest neighbour algorithm (which produced greater specificity) to achieve the enhanced predictive performance

Does learning style influence academic performance in different forms of assessment?

Science.gov (United States)

Wilkinson, Tracey; Boohan, Mairead; Stevenson, Michael

2014-03-01

Educational research on learning styles has been conducted for some time, initially within the field of psychology. Recent research has widened to include more diverse disciplines, with greater emphasis on application. Although there are numerous instruments available to measure several different dimensions of learning style, it is generally accepted that styles differ, although the qualities of more than one style may be inherent in any one learner. But do these learning styles have a direct effect on student performance in examinations, specifically in different forms of assessment? For this study, hypotheses were formulated suggesting that academic performance is influenced by learning style. Using the Honey and Mumford Learning Style Questionnaire, learning styles of a cohort of first year medical and dental students at Queen's University Belfast were assessed. Pearson correlation was performed between the score for each of the four learning styles and the student examination results in a variety of subject areas (including anatomy) and in different types of assessments - single best answer, short answer questions and Objective Structured Clinical Examinations. In most of the analyses, there was no correlation between learning style and result and in the few cases where the correlations were statistically significant, they generally appeared to be weak. It seems therefore from this study that although the learning styles of students vary, they have little effect on academic performance, including in specific forms of assessment. © 2013 Anatomical Society.

Optimization of thermal performance of a smooth flat-plate solar air heater using teaching–learning-based optimization algorithm

Directory of Open Access Journals (Sweden)

R. Venkata Rao

2015-12-01

Full Text Available This paper presents the performance of teaching–learning-based optimization (TLBO algorithm to obtain the optimum set of design and operating parameters for a smooth flat plate solar air heater (SFPSAH. The TLBO algorithm is a recently proposed population-based algorithm, which simulates the teaching–learning process of the classroom. Maximization of thermal efficiency is considered as an objective function for the thermal performance of SFPSAH. The number of glass plates, irradiance, and the Reynolds number are considered as the design parameters and wind velocity, tilt angle, ambient temperature, and emissivity of the plate are considered as the operating parameters to obtain the thermal performance of the SFPSAH using the TLBO algorithm. The computational results have shown that the TLBO algorithm is better or competitive to other optimization algorithms recently reported in the literature for the considered problem.

Do Dental Students' Personality Types and Group Dynamics Affect Their Performance in Problem-Based Learning?

Science.gov (United States)

Ihm, Jung-Joon; An, So-Youn; Seo, Deog-Gyu

2017-06-01

The aim of this study was to determine whether the personality types of dental students and their group dynamics were linked to their problem-based learning (PBL) performance. The Myers-Briggs Type Indicator (MBTI) instrument was used with 263 dental students enrolled in Seoul National University School of Dentistry from 2011 to 2013; the students had participated in PBL in their first year. A four-session PBL setting was designed to analyze how individual personality types and the diversity of their small groups were associated with PBL performance. Overall, the results showed that the personality type of PBL performance that was the most prominent was Judging. As a group became more diverse with its different constituent personality characteristics, there was a tendency for the group to be higher ranked in terms of PBL performance. In particular, the overperforming group was clustered around three major profiles: Extraverted Intuitive Thinking Judging (ENTJ), Introverted Sensing Thinking Judging (ISTJ), and Extraverted Sensing Thinking Judging (ESTJ). Personality analysis would be beneficial for dental faculty members in order for them to understand the extent to which cooperative learning would work smoothly, especially when considering group personalities.

Assessing the impact of blended learning on student performance

OpenAIRE

Do Won Kwak; Flavio Menezes; Carl Sherwood

2013-01-01

This paper assesses quantitatively the impact on student performance of a blended learning experiment within a large undergraduate first year course in statistics for business and economics students. We employ a differences- in-difference econometric approach, which controls for differences in student characteristics and course delivery method, to evaluate the impact of blended learning on student performance. Although students in the course manifest a preference for live lectures over online...

Development of a grinding-specific performance test set-up.

Science.gov (United States)

Olesen, C G; Larsen, B H; Andresen, E L; de Zee, M

2015-01-01

The aim of this study was to develop a performance test set-up for America's Cup grinders. The test set-up had to mimic the on-boat grinding activity and be capable of collecting data for analysis and evaluation of grinding performance. This study included a literature-based analysis of grinding demands and a test protocol developed to accommodate the necessary physiological loads. This study resulted in a test protocol consisting of 10 intervals of 20 revolutions each interspersed with active resting periods of 50 s. The 20 revolutions are a combination of both forward and backward grinding and an exponentially rising resistance. A custom-made grinding ergometer was developed with computer-controlled resistance and capable of collecting data during the test. The data collected can be used to find measures of grinding performance such as peak power, time to complete and the decline in repeated grinding performance.

Relationship between Academic Performance, Spatial Competence, Learning Styles and Attrition

Directory of Open Access Journals (Sweden)

Marianela Noriega Biggio

2013-04-01

Full Text Available This paper discusses the results of research on factors affecting academic performance and attrition in a sample of 1,500 freshman students majoring in architecture, design and urbanism at the Universidad de Buenos Aires, Argentina [University of Buenos Aires, Argentina] who were enrolled in a drafting course. The hypotheses we tested concern the mediating role of learning styles on the relationship between spatial competence and academic performance, learning-style differences by gender and cohort, and the relationship between attrition, spatial competence level and learning style. Statistical analysis of the data was performed and spatial competence enhanced by motivational profile was found to predict final achievement. Educational implications are identified, highlighting the need to promote in students those academic behaviors that characterize a self-regulated learning style and encourage the use of specific intellectual abilities.

Student Learning Styles and Performance in an Introductory Finance Class

Science.gov (United States)

Seiver, Daniel Alan; Haddad, Kamal; Do, Andrew

2014-01-01

Many academic disciplines have examined the role that variation in Jungian personality types plays in the academic performance of college students. Different personality types tend to have different learning styles, which in turn influence student performance in a variety of college courses. To measure the impact of learning styles on student…

Neural Correlates of High Performance in Foreign Language Vocabulary Learning

Science.gov (United States)

Macedonia, Manuela; Muller, Karsten; Friederici, Angela D.

2010-01-01

Learning vocabulary in a foreign language is a laborious task which people perform with varying levels of success. Here, we investigated the neural underpinning of high performance on this task. In a within-subjects paradigm, participants learned 92 vocabulary items under two multimodal conditions: one condition paired novel words with iconic…

Short-Term Solar Forecasting Performance of Popular Machine Learning Algorithms: Preprint

Energy Technology Data Exchange (ETDEWEB)

Florita, Anthony R [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Elgindy, Tarek [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Hodge, Brian S [National Renewable Energy Laboratory (NREL), Golden, CO (United States); Dobbs, Alex [National Renewable Energy Laboratory (NREL), Golden, CO (United States)

2017-10-03

A framework for assessing the performance of short-term solar forecasting is presented in conjunction with a range of numerical results using global horizontal irradiation (GHI) from the open-source Surface Radiation Budget (SURFRAD) data network. A suite of popular machine learning algorithms is compared according to a set of statistically distinct metrics and benchmarked against the persistence-of-cloudiness forecast and a cloud motion forecast. Results show significant improvement compared to the benchmarks with trade-offs among the machine learning algorithms depending on the desired error metric. Training inputs include time series observations of GHI for a history of years, historical weather and atmospheric measurements, and corresponding date and time stamps such that training sensitivities might be inferred. Prediction outputs are GHI forecasts for 1, 2, 3, and 4 hours ahead of the issue time, and they are made for every month of the year for 7 locations. Photovoltaic power and energy outputs can then be made using the solar forecasts to better understand power system impacts.

Exploring the Political Underbelly of Organizational Learning: Learning during Pay and Performance Management Change

Science.gov (United States)

Field, Laurie

2011-01-01

Purpose: In an effort to better understand the political dimensions of organizational learning, this paper aims to examine learning processes in an organizational context--namely renegotiation of pay and performance management arrangements--where the interests of organizational members are threatened. Design/methodology/approach: Data were derived…

Benchmarking and Learning in Public Healthcare

DEFF Research Database (Denmark)

Buckmaster, Natalie; Mouritsen, Jan

2017-01-01

This research investigates the effects of learning-oriented benchmarking in public healthcare settings. Benchmarking is a widely adopted yet little explored accounting practice that is part of the paradigm of New Public Management. Extant studies are directed towards mandated coercive benchmarking...... applications. The present study analyses voluntary benchmarking in a public setting that is oriented towards learning. The study contributes by showing how benchmarking can be mobilised for learning and offers evidence of the effects of such benchmarking for performance outcomes. It concludes that benchmarking...... can enable learning in public settings but that this requires actors to invest in ensuring that benchmark data are directed towards improvement....

Is Performance in Task-Cuing Experiments Mediated by Task Set Selection or Associative Compound Retrieval?

Science.gov (United States)

Forrest, Charlotte L. D.; Monsell, Stephen; McLaren, Ian P. L.

2014-01-01

Task-cuing experiments are usually intended to explore control of task set. But when small stimulus sets are used, they plausibly afford learning of the response associated with a combination of cue and stimulus, without reference to tasks. In 3 experiments we presented the typical trials of a task-cuing experiment: a cue (colored shape) followed,…

Perceived Frequency of Peer-Assisted Learning in the Laboratory and Collegiate Clinical Settings

Science.gov (United States)

Henning, Jolene M.; Weidner, Thomas G.; Snyder, Melissa; Dudley, William N.

2012-01-01

Context: Peer-assisted learning (PAL) has been recommended as an educational strategy to improve students' skill acquisition and supplement the role of the clinical instructor (CI). How frequently students actually engage in PAL in different settings is unknown. Objective: To determine the perceived frequency of planned and unplanned PAL (peer modeling, peer feedback and assessment, peer mentoring) in different settings. Design: Cross-sectional study. Setting: Laboratory and collegiate clinical settings. Patients or Other Participants: A total of 933 students, 84 administrators, and 208 CIs representing 52 (15%) accredited athletic training education programs. Intervention(s): Three versions (student, CI, administrator) of the Athletic Training Peer Assisted Learning Survey (AT-PALS) were administered. Cronbach α values ranged from .80 to .90. Main Outcome Measure(s): Administrators' and CIs' perceived frequency of 3 PAL categories under 2 conditions (planned, unplanned) and in 2 settings (instructional laboratory, collegiate clinical). Self-reported frequency of students' engagement in 3 categories of PAL in 2 settings. Results: Administrators and CIs perceived that unplanned PAL (0.39 ± 0.22) occurred more frequently than planned PAL (0.29 ± 0.19) regardless of category or setting (F1,282 = 83.48, P < .001). They perceived that PAL occurred more frequently in the collegiate clinical (0.46 ± 0.22) than laboratory (0.21 ± 0.24) setting regardless of condition or category (F1,282 = 217.17, P < .001). Students reported engaging in PAL more frequently in the collegiate clinical (3.31 ± 0.56) than laboratory (3.26 ± 0.62) setting regardless of category (F1,860 = 13.40, P < .001). We found a main effect for category (F2,859 = 1318.02, P < .001), with students reporting they engaged in peer modeling (4.01 ± 0.60) more frequently than peer mentoring (2.99 ± 0.88) (P < .001) and peer assessment and feedback (2.86 ± 0.64) (P < .001). Conclusions: Participants

Motivated strategies for learning and their association with academic performance of a diverse group of 1styear medical students

Directory of Open Access Journals (Sweden)

Shaista Hamid

2016-05-01

Full Text Available Background. Most instruments, including the well-known Motivated Strategies for Learning Questionnaire (MSLQ, have been designed in western homogeneous settings. Use of the MSLQ in health professions education is limited. Objective. To assess the MSLQ and its association with the academic performance of a heterogeneous group of 1st-year medical students. Methods. Eighty-three percent of 1st-year medical students consented to participate in this quantitative study. The MSLQ consisted of a motivation strategies component with six subscales, while the learning strategies component had nine subscales. Demographic and academic achievement information of the students was also collected. Stata version 13 (StataCorp LP, USA was used for the statistical analyses of all data. Results. Female students displayed significantly higher motivational scores. Students with prior educational experience and those who attended peer mentoring sessions had significantly higher learning strategy scores. Significant but moderate relationships were found between academic performance and the motivation strategies subsumed within the categories ‘task value’ and ‘self-efficacy for learning performance’. In terms of the ‘learning strategy component’, ‘critical thinking’, and ‘time and study environment’, the composite score was significantly but poorly correlated to academic performance. Conclusion. Overall, limited correlations were found between the MSLQ scores and academic performance. Further investigation of the use of the MSLQ and its association with academic achievement is recommended, with greater focus on specific learning events than on course outcomes. This study highlights the importance of evaluating an instrument in a specific context before accepting the findings of others with regard to the use of the instrument and its correlation with academic performance.

Performance in physiology evaluation: possible improvement by active learning strategies.

Science.gov (United States)

Montrezor, Luís H

2016-12-01

The evaluation process is complex and extremely important in the teaching/learning process. Evaluations are constantly employed in the classroom to assist students in the learning process and to help teachers improve the teaching process. The use of active methodologies encourages students to participate in the learning process, encourages interaction with their peers, and stimulates thinking about physiological mechanisms. This study examined the performance of medical students on physiology over four semesters with and without active engagement methodologies. Four activities were used: a puzzle, a board game, a debate, and a video. The results show that engaging in activities with active methodologies before a physiology cognitive monitoring test significantly improved student performance compared with not performing the activities. We integrate the use of these methodologies with classic lectures, and this integration appears to improve the teaching/learning process in the discipline of physiology and improves the integration of physiology with cardiology and neurology. In addition, students enjoy the activities and perform better on their evaluations when they use them. Copyright © 2016 The American Physiological Society.

Metric learning

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Bellet, Aurelien; Sebban, Marc

2015-01-01

Similarity between objects plays an important role in both human cognitive processes and artificial systems for recognition and categorization. How to appropriately measure such similarities for a given task is crucial to the performance of many machine learning, pattern recognition and data mining methods. This book is devoted to metric learning, a set of techniques to automatically learn similarity and distance functions from data that has attracted a lot of interest in machine learning and related fields in the past ten years. In this book, we provide a thorough review of the metric learnin

Performance assessment in algebra learning process

Science.gov (United States)

Lestariani, Ida; Sujadi, Imam; Pramudya, Ikrar

2017-12-01

The purpose of research to describe the implementation of performance assessment on algebra learning process. The subject in this research is math educator of SMAN 1 Ngawi class X. This research includes descriptive qualitative research type. Techniques of data collecting are done by observation method, interview, and documentation. Data analysis technique is done by data reduction, data presentation, and conclusion. The results showed any indication that the steps taken by the educator in applying the performance assessment are 1) preparing individual worksheets and group worksheets, 2) preparing rubric assessments for independent worksheets and groups and 3) making performance assessments rubric to learners’ performance results with individual or groups task.

How Good Is Good: Improved Tracking and Managing of Safety Goals, Performance Indicators, Production Targets and Significant Events Using Learning Curves

International Nuclear Information System (INIS)

Duffey, Rommey B.; Saull, John W.

2002-01-01

We show a new way to track and measure safety and performance using learning curves derived on a mathematical basis. When unusual or abnormal events occur in plants and equipment, the regulator and good management practice requires they be reported, investigated, understood and rectified. In addition to reporting so-called 'significant events', both management and the regulator often set targets for individual and collective performance, which are used for both reward and criticism. For almost completely safe systems, like nuclear power plants, commercial aircraft and chemical facilities, many parameters are tracked and measured. Continuous improvement has to be demonstrated, as well as meeting reduced occurrence rates, which are set as management goals or targets. This process usually takes the form of statistics for availability of plant and equipment, forced or unplanned maintenance outage, loss of safety function, safety or procedural violations, etc. These are often rolled up into a set of so-called 'Performance Indicators' as measures of how well safety and operation is being managed at a given facility. The overall operating standards of an industry are also measured. A whole discipline is formed of tracking, measuring, reporting, managing and understanding the plethora of indicators and data. Decreasing occurrence rates and meeting or exceeding goals are seen and rewarded as virtues. Managers and operators need to know how good is their safety management system that has been adopted and used (and paid for), and whether it can itself be improved. We show the importance of accumulated experience in correctly measuring and tracking the decreasing event and error rates speculating a finite minimum rate. We show that the rate of improvement constitutes a measurable 'learning curve', and the attainment of the goals and targets can be affected by the adopted measures. We examine some of the available data on significant events, reportable occurrences, and loss of

Effects of Peer-Assessed Feedback, Goal Setting and a Group Contingency on Performance and Learning by 10-12-Year-Old Academy Soccer Players

Science.gov (United States)

Holt, Josh E.; Kinchin, Gary; Clarke, Gill

2012-01-01

Background: Coaches developing young talent in team sports must maximise practice and learning of essential game skills and accurately and continuously assess the performance and potential of each player. Relative age effects highlight an erroneous process of initial and on-going player assessment, based largely on subjective opinions of game…

Stereoscopy in Astronomical Visualizations to Support Learning at Informal Education Settings

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Price, Aaron; Lee, Hee-Sun

2015-08-01

Stereoscopy has been used in science education for 100 years. Recent innovations in low cost technology as well as trends in the entertainment industry have made stereoscopy popular among educators and audiences alike. However, experimental studies addressing whether stereoscopy actually impacts science learning are limited. Over the last decade, we have conducted a series of quasi-experimental and experimental studies on how children and adult visitors in science museums and planetariums learned about the structure and function of highly spatial scientific objects such as galaxies, supernova, etc. We present a synthesis of the results from these studies and implications for stereoscopic visualization development. The overall finding is that the impact of stereoscopy on perceptions of scientific objects is limited when presented as static imagery. However, when presented as full motion films, a significantly positive impact was detected. To conclude, we present a set of stereoscopic design principles that can help design astronomical stereoscopic films that support deep and effective learning. Our studies cover astronomical content such as the engineering of and imagery from the Mars rovers, artistic stereoscopic imagery of nebulae and a high-resolution stereoscopic film about how astronomers measure and model the structure of our galaxy.

Developing nursing and midwifery students' capacity for coping with bullying and aggression in clinical settings: Students' evaluation of a learning resource.

Science.gov (United States)

Hogan, Rosemarie; Orr, Fiona; Fox, Deborah; Cummins, Allison; Foureur, Maralyn

2018-03-01

An innovative blended learning resource for undergraduate nursing and midwifery students was developed in a large urban Australian university, following a number of concerning reports by students on their experiences of bullying and aggression in clinical settings. The blended learning resource included interactive online learning modules, comprising film clips of realistic clinical scenarios, related readings, and reflective questions, followed by in-class role-play practice of effective responses to bullying and aggression. On completion of the blended learning resource 210 participants completed an anonymous survey (65.2% response rate). Qualitative data was collected and a thematic analysis of the participants' responses revealed the following themes: 'Engaging with the blended learning resource'; 'Responding to bullying' and 'Responding to aggression'. We assert that developing nursing and midwifery students' capacity to effectively respond to aggression and bullying, using a self-paced blended learning resource, provides a solution to managing some of the demands of the clinical setting. The blended learning resource, whereby nursing and midwifery students were introduced to realistic portrayals of bullying and aggression in clinical settings, developed their repertoire of effective responding and coping skills for use in their professional practice. Copyright © 2017 Elsevier Ltd. All rights reserved.

Combining University Student Self-Regulated Learning Indicators and Engagement with Online Learning Events to Predict Academic Performance

Science.gov (United States)

Pardo, Abelardo; Han, Feifei; Ellis, Robert A.

2017-01-01

Self-regulated learning theories are used to understand the reasons for different levels of university student academic performance. Similarly, learning analytics research proposes the combination of detailed data traces derived from technology-mediated tasks with a variety of algorithms to predict student academic performance. The former approach…

Science learning motivation as correlate of students’ academic performances

OpenAIRE

Libao, Nhorvien Jay P.; Sagun, Jessie John B.; Tamangan, Elvira A.; Pattalitan, Agaton P.; Dupa, Maria Elena D.; Bautista, Romiro Gordo

2016-01-01

This study was designed to analyze the relationship of students’ learning motivation and their academic performances in science. The study made use of 21 junior and senior Biological Science students to conclude on the formulated research problems. The respondents had a good to very good motivation in learning science. In general, the extent of their motivation do not vary across their sex, age, and curriculum year. Moreover, the respondents had good academic performances in science. Aptly, e...

Performance of experienced dentists in Switzerland after an e-learning program on ICDAS occlusal caries detection.

Science.gov (United States)

Rodrigues, Jonas Almeida; de Oliveira, Renata Schlesner; Hug, Isabel; Neuhaus, Klaus; Lussi, Adrian

2013-08-01

This study aimed to evaluate the effect of an e-learning program on the validity and reproducibility of the International Caries Detection and Assessment System (ICDAS) in detecting occlusal caries. For the study, 170 permanent molars were selected. Four dentists in Switzerland who had no previous contact with ICDAS examined the teeth before and after the e-learning program and scored the sites according to ICDAS. Teeth were histologically prepared and assessed for caries extension. The significance level was set at 0.05. Sensitivity before and after the e-learning program was 0.80 and 0.77 (D1), 0.72 and 0.63 (D2), and 0.74 and 0.67 (D3,4), respectively. Specificity was 0.64 and 0.69 (D1), 0.70 and 0.81 (D2), and 0.81 and 0.87 (D3,4). A McNemar test did not show any difference between the values of sensitivity, specificity, accuracy, and area under the ROC curve (AUC) before and after the e-learning program. The averages of wK values for interexaminer reproducibility were 0.61 (before) and 0.66 (after). Correlation with histology presented wK values of 0.62 (before) and 0.63 (after). A Wilcoxon test showed a statistically significant difference between before and after the e-learning program. In conclusion, even though ICDAS performed well in detecting occlusal caries, the e-learning program did not have any statistically significant effect on its performance by these experienced dentists.

Games-to-teach or games-to-learn unlocking the power of digital game-based learning through performance

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Chee, Yam San

2016-01-01

The book presents a critical evaluation of current approaches related to the use of digital games in education. The author identifies two competing paradigms: that of games-to-teach and games-to-learn. Arguing in favor of the latter, the author advances the case for approaching game-based learning through the theoretical lens of performance, rooted in play and dialog, to unlock the power of digital games for 21st century learning. Drawing upon the author’s research, three concrete exemplars of game-based learning curricula are described and discussed. The challenge of advancing game-based learning in education is addressed in the context of school reform. Finally, future prospects of and educational opportunities for game-based learning are articulated. Readers of the book will find the explication of performance theory applied to game-based learning especially interesting. This work constitutes the author’s original theorization. Readers will derive four main benefits: (1) an explication of the differenc...

Active learning increases student performance in science, engineering, and mathematics.

Science.gov (United States)

Freeman, Scott; Eddy, Sarah L; McDonough, Miles; Smith, Michelle K; Okoroafor, Nnadozie; Jordt, Hannah; Wenderoth, Mary Pat

2014-06-10

To test the hypothesis that lecturing maximizes learning and course performance, we metaanalyzed 225 studies that reported data on examination scores or failure rates when comparing student performance in undergraduate science, technology, engineering, and mathematics (STEM) courses under traditional lecturing versus active learning. The effect sizes indicate that on average, student performance on examinations and concept inventories increased by 0.47 SDs under active learning (n = 158 studies), and that the odds ratio for failing was 1.95 under traditional lecturing (n = 67 studies). These results indicate that average examination scores improved by about 6% in active learning sections, and that students in classes with traditional lecturing were 1.5 times more likely to fail than were students in classes with active learning. Heterogeneity analyses indicated that both results hold across the STEM disciplines, that active learning increases scores on concept inventories more than on course examinations, and that active learning appears effective across all class sizes--although the greatest effects are in small (n ≤ 50) classes. Trim and fill analyses and fail-safe n calculations suggest that the results are not due to publication bias. The results also appear robust to variation in the methodological rigor of the included studies, based on the quality of controls over student quality and instructor identity. This is the largest and most comprehensive metaanalysis of undergraduate STEM education published to date. The results raise questions about the continued use of traditional lecturing as a control in research studies, and support active learning as the preferred, empirically validated teaching practice in regular classrooms.

Learning Patient Safety in Academic Settings: A Comparative Study of Finnish and British Nursing Students' Perceptions.

Science.gov (United States)

Tella, Susanna; Smith, Nancy-Jane; Partanen, Pirjo; Turunen, Hannele

2015-06-01

Globalization of health care demands nursing education programs that equip students with evidence-based patient safety competences in the global context. Nursing students' entrance into clinical placements requires professional readiness. Thus, evidence-based learning activities about patient safety must be provided in academic settings prior to students' clinical placements. To explore and compare Finnish and British nursing students' perceptions of learning about patient safety in academic settings to inform nursing educators about designing future education curriculum. A purpose-designed instrument, Patient Safety in Nursing Education Questionnaire (PaSNEQ) was used to examine the perceptions of Finnish (n = 195) and British (n = 158) nursing students prior to their final year of registration. Data were collected in two Finnish and two English nursing schools in 2012. Logistic regressions were used to analyze the differences. British students reported more inclusion (p motivation" related to patient safety in their programs. Both student groups considered patient safety education to be more valuable for their own learning than what their programs had provided. Training patient safety skills in the academic settings were the strongest predictors for differences (odds ratio [OR] = 34.69, 95% confidence interval [CI] 7.39-162.83), along with work experience in the healthcare sector (OR = 3.02, 95% CI 1.39-6.58). To prepare nursing students for practical work, training related to clear communication, reporting errors, systems-based approaches, interprofessional teamwork, and use of simulation in academic settings requires comprehensive attention, especially in Finland. Overall, designing patient safety-affirming nursing curricula in collaboration with students may enhance their positive experiences on teaching and learning about patient safety. An international collaboration between educators could help to develop and harmonize patient safety education and to better

Measuring Cognitive Load in Embodied Learning Settings

Directory of Open Access Journals (Sweden)

Alexander Skulmowski

2017-08-01

Full Text Available In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1 Subjective measures must be appropriately phrased to be useful for embodied learning; (2 recent findings indicate potentials as well as problematic aspects of dual-task measures; (3 the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4 meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.

Measuring Cognitive Load in Embodied Learning Settings.

Science.gov (United States)

Skulmowski, Alexander; Rey, Günter Daniel

2017-01-01

In recent years, research on embodied cognition has inspired a number of studies on multimedia learning and instructional psychology. However, in contrast to traditional research on education and multimedia learning, studies on embodied learning (i.e., focusing on bodily action and perception in the context of education) in some cases pose new problems for the measurement of cognitive load. This review provides an overview over recent studies on embodied learning in which cognitive load was measured using surveys, behavioral data, or physiological measures. The different methods are assessed in terms of their success in finding differences of cognitive load in embodied learning scenarios. At the same time, we highlight the most important challenges for researchers aiming to include these measures into their study designs. The main issues we identified are: (1) Subjective measures must be appropriately phrased to be useful for embodied learning; (2) recent findings indicate potentials as well as problematic aspects of dual-task measures; (3) the use of physiological measures offers great potential, but may require mobile equipment in the context of embodied scenarios; (4) meta-cognitive measures can be useful extensions of cognitive load measurement for embodied learning.

Dissimilarity-based multiple instance learning

DEFF Research Database (Denmark)

Sørensen, Lauge; Loog, Marco; Tax, David M. J.

2010-01-01

In this paper, we propose to solve multiple instance learning problems using a dissimilarity representation of the objects. Once the dissimilarity space has been constructed, the problem is turned into a standard supervised learning problem that can be solved with a general purpose supervised cla...... between distributions of within- and between set point distances, thereby taking relations within and between sets into account. Experiments on five publicly available data sets show competitive performance in terms of classification accuracy compared to previously published results....

A Review on the Use and Perceived Effects of Mobile Blogs on Learning in Higher Educational Settings

DEFF Research Database (Denmark)

Norman, Helmi; Din, Rosseni; Nordin, Norazah

2014-01-01

Mobile technology is affecting the way we learn and teach in higher education. An interesting mobile tool for supporting learning and instruction is by using mobile blogs or “moblogs”. This review focuses on existing studies implementing moblogs for learning purposes in higher educational settings...... for moblog usage were identified, namely: (i) moblogs were used for context-sensitive learning; (ii) for collaboration in groups; (iii) as a tool for interaction and communication for learning; (iv) as personal learning diaries; (v) to facilitate learning at students’ own time and pace; (vi) as a tool...... for feedback on instruction; and (vii) for reflections in learning. Meanwhile, three categories were discovered for perceived effects of moblogs, which are: (i) perceived affective effects in terms of satisfaction and attitude; (ii) perceived social effects on students; and (iii) negative perception of moblog...

Active learning for clinical text classification: is it better than random sampling?

Science.gov (United States)

Figueroa, Rosa L; Ngo, Long H; Goryachev, Sergey; Wiechmann, Eduardo P

2012-01-01

Objective This study explores active learning algorithms as a way to reduce the requirements for large training sets in medical text classification tasks. Design Three existing active learning algorithms (distance-based (DIST), diversity-based (DIV), and a combination of both (CMB)) were used to classify text from five datasets. The performance of these algorithms was compared to that of passive learning on the five datasets. We then conducted a novel investigation of the interaction between dataset characteristics and the performance results. Measurements Classification accuracy and area under receiver operating characteristics (ROC) curves for each algorithm at different sample sizes were generated. The performance of active learning algorithms was compared with that of passive learning using a weighted mean of paired differences. To determine why the performance varies on different datasets, we measured the diversity and uncertainty of each dataset using relative entropy and correlated the results with the performance differences. Results The DIST and CMB algorithms performed better than passive learning. With a statistical significance level set at 0.05, DIST outperformed passive learning in all five datasets, while CMB was found to be better than passive learning in four datasets. We found strong correlations between the dataset diversity and the DIV performance, as well as the dataset uncertainty and the performance of the DIST algorithm. Conclusion For medical text classification, appropriate active learning algorithms can yield performance comparable to that of passive learning with considerably smaller training sets. In particular, our results suggest that DIV performs better on data with higher diversity and DIST on data with lower uncertainty. PMID:22707743

Using Game Theory and Competition-Based Learning to Stimulate Student Motivation and Performance

Science.gov (United States)

Burguillo, Juan C.

2010-01-01

This paper introduces a framework for using Game Theory tournaments as a base to implement Competition-based Learning (CnBL), together with other classical learning techniques, to motivate the students and increase their learning performance. The paper also presents a description of the learning activities performed along the past ten years of a…

Action learning in undergraduate engineering thesis supervision

Directory of Open Access Journals (Sweden)

Brad Stappenbelt

2017-03-01

Full Text Available In the present action learning implementation, twelve action learning sets were conducted over eight years. The action learning sets consisted of students involved in undergraduate engineering research thesis work. The concurrent study accompanying this initiative, investigated the influence of the action learning environment on student approaches to learning and any accompanying academic, learning and personal benefits realised. The influence of preferred learning styles on set function and student adoption of the action learning process were also examined. The action learning environment implemented had a measurable significant positive effect on student academic performance, their ability to cope with the stresses associated with conducting a research thesis, the depth of learning, the development of autonomous learners and student perception of the research thesis experience. The present study acts as an addendum to a smaller scale implementation of this action learning approach, applied to supervision of third and fourth year research projects and theses, published in 2010.

Testing the scalar expectancy theory (SET) and the learning-to-time model (LeT) in a double bisection task.

Science.gov (United States)

Machado, Armando; Pata, Paulo

2005-02-01

Two theories of timing, scalar expectancy theory (SET) and learning-to-time (LeT), make substantially different assumptions about what animals learn in temporal tasks. In a test of these assumptions, pigeons learned two temporal discriminations. On Type 1 trials, they learned to choose a red key after a 1-sec signal and a green key after a 4-sec signal; on Type 2 trials, they learned to choose a blue key after a 4-sec signal and a yellow key after either an 8-sec signal (Group 8) or a 16-sec signal (Group 16). Then, the birds were exposed to signals 1 sec, 4 sec, and 16 sec in length and given a choice between novel key combinations (red or green vs. blue or yellow). The choice between the green key and the blue key was of particular significance because both keys were associated with the same 4-sec signal. Whereas SET predicted no effect of the test signal duration on choice, LeT predicted that preference for green would increase monotonically with the length of the signal but would do so faster for Group 8 than for Group 16. The results were consistent with LeT, but not with SET.

Children’s Cultural Learning in Everyday Family Life Exemplified at the Dinner Setting

DEFF Research Database (Denmark)

Hedegaard, Mariane

2017-01-01

through participant observations in their everyday activities in two families (Hedegaard & Fleer. 2013. Play, learning and children’s development. Everyday life in families and transition to school. New York: Cambridge University Press). The family members in the two families got an instant camera...... the setting and directly from parents and siblings. Children’s also put demands on the setting and its participants and how these are met leads to children’s development of new forms of social interaction, new motive orientation, and competences. The argument builds on a research project following children...... and were asked to take photos of what were important for them. In this chapter, the focus is on how demands and motives influence both parents and children at the dinner setting....

Discrimination learning and attentional set formation in a mouse model of Fragile X.

Science.gov (United States)

Casten, Kimberly S; Gray, Annette C; Burwell, Rebecca D

2011-06-01

Fragile X Syndrome is the most prevalent genetic cause of mental retardation. Selective deficits in executive function, including inhibitory control and attention, are core features of the disorder. In humans, Fragile X results from a trinucleotide repeat in the Fmr1 gene that renders it functionally silent and has been modeled in mice by targeted deletion of the Fmr1 gene. Fmr1 knockout (KO) mice recapitulate many features of Fragile X syndrome, but evidence for deficits in executive function is inconsistent. To address this issue, we trained wild-type and Fmr1 KO mice on an experimental paradigm that assesses attentional set-shifting. Mice learned to discriminate between stimuli differing in two of three perceptual dimensions. Successful discrimination required attending only to the relevant dimension, while ignoring irrelevant dimensions. Mice were trained on three discriminations in the same perceptual dimension, each followed by a reversal. This procedure normally results in the formation of an attentional set to the relevant dimension. Mice were then required to shift attention and discriminate based on a previously irrelevant perceptual dimension. Wild-type mice exhibited the increase in trials to criterion expected when shifting attention from one perceptual dimension to another. In contrast, the Fmr1 KO group failed to show the expected increase, suggesting impairment in forming an attentional set. Fmr1 KO mice also exhibited a general impairment in learning discriminations and reversals. This is the first demonstration that Fmr1 KO mice show a deficit in attentional set formation.

Development of a grinding-specific performance test set-up

DEFF Research Database (Denmark)

Olesen, C. G.; Larsen, B. H.; Andresen, E. L.

2015-01-01

The aim of this study was to develop a performance test set-up for America's Cup grinders. The test set-up had to mimic the on-boat grinding activity and be capable of collecting data for analysis and evaluation of grinding performance. This study included a literature-based analysis of grinding...... demands and a test protocol developed to accommodate the necessary physiological loads. This study resulted in a test protocol consisting of 10 intervals of 20 revolutions each interspersed with active resting periods of 50 s. The 20 revolutions are a combination of both forward and backward grinding...... and an exponentially rising resistance. A custom-made grinding ergometer was developed with computer-controlled resistance and capable of collecting data during the test. The data collected can be used to find measures of grinding performance such as peak power, time to complete and the decline in repeated grinding...

Learning Domain-Specific Heuristics for Answer Set Solvers

OpenAIRE

Balduccini, Marcello

2010-01-01

In spite of the recent improvements in the performance of Answer Set Programming (ASP) solvers, when the search space is sufficiently large, it is still possible for the search algorithm to mistakenly focus on areas of the search space that contain no solutions or very few. When that happens, performance degrades substantially, even to the point that the solver may need to be terminated before returning an answer. This prospect is a concern when one is considering using such a solver in an in...

A Performance-Oriented Approach to E-Learning in the Workplace

Science.gov (United States)

Wang, Minhong; Ran, Weijia; Liao, Jian; Yang, Stephen J. H.

2010-01-01

Despite the ever-increasing practice of using e-learning in the workplace, most of the applications perform poorly in motivating employees to learn. Most workplace e-learning applications fail to meet the needs of learners and ultimately fail to serve the organization's quest for success. To solve this problem, we need to examine what workplace…

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

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Ririn Ambarini

2017-12-01

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

Towards a Social Networks Model for Online Learning & Performance

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Chung, Kon Shing Kenneth; Paredes, Walter Christian

2015-01-01

In this study, we develop a theoretical model to investigate the association between social network properties, "content richness" (CR) in academic learning discourse, and performance. CR is the extent to which one contributes content that is meaningful, insightful and constructive to aid learning and by social network properties we…

Blended learning versus traditional teaching-learning-setting: Evaluation of cognitive and affective learning outcomes for the inter-professional field of occupational medicine and prevention / Blended Learning versus traditionelles Lehr-Lernsetting: Evaluierung von kognitiven und affektiven Lernergebnissen für das interprofessionelle Arbeitsfeld Arbeitsmedizin und Prävention

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Eckler Ursula

2017-11-01

Full Text Available Blended learning is characterised as a combination of face-to-face teaching and e-learning in terms of knowledge transfer, students’ learning activities and reduced presence at the teaching facility. The present cohort study investigated long-term effects of blended learning regarding cognitive outcomes as well as self-indicated estimates of immediate learning effects on the affective domain in the inter-professional field of occupational medicine. Physiotherapy students (bachelor degree at FH Campus Wien – University of Applied Sciences completed the course Occupational Medicine/Prevention either in a traditional teaching-learning setting entirely taught face-to-face (control-group, n=94, or with a blended learning model (intervention-group, n=93. Long-term effects (1.5 year follow-up on the cognitive learning outcomes were assessed according to four levels of Bloom’s learning objectives. In addition, students estimated potential benefits resulting from blended learning based on four Krathwohl’s learning objectives for the affective domain by means of a six-option Likert scale (n=282. Concerning cognitive outcomes, significant results favouring both groups were found with effect sizes from small to medium. The traditional teaching-learning setting resulted in significantly better results in the upmost aspired learning objective (analysis at the long-term (p<0,01; r=-0,33. In contrast, the intervention group resulted in significantly better long-term results on learning objective levels 1 (knowledge and 2 (understanding (p=0,01; r=-0,20 and, p=0,02; r=-0,17, respectively. Hence, no general recommendation favouring either the classical setting or blending learning can be drawn regarding the cognitive domain. However, students’ self-indications on the affective domain give preference to blended learning, particularly if inter-professional teamwork is a course objective.

Variable learning performance: the levels of behaviour organization.

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Csányi, V; Altbäcker, V

1990-01-01

Our experiments were focused on some special aspects of learning in the paradise fish. Passive avoidance conditioning method was used with different success depending on the complexity of the learning tasks. In the case of simple behavioural elements various "constrains" on avoidance learning were found. In a small, covered place the fish were ready to perform freezing reaction and mild punishment increased the frequency and duration of the freezing bouts very substantially. However, it was very difficult to enhance the frequency of freezing by punishment in a tank with transparent walls, where the main response to punishment was escape. The most easily learned tasks were the complex ones which had several different solutions. The fish learned to avoid either side of an aquarium very easily because they could use various behavioural elements to solve the problem. These findings could be interpreted within the framework of different organizational levels of behaviour.

Effect of Modifying Intervention Set Size with Acquisition Rate Data among Students Identified with a Learning Disability

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Haegele, Katherine; Burns, Matthew K.

2015-01-01

The amount of information that students can successfully learn and recall at least 1 day later is called an acquisition rate (AR) and is unique to the individual student. The current study extended previous drill rehearsal research with word recognition by (a) using students identified with a learning disability in reading, (b) assessing set sizes…

Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance.

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Carter, Christine E; Grahn, Jessica A

2016-01-01

Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the "contextual interference effect." While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

Optimizing Music Learning: Exploring How Blocked and Interleaved Practice Schedules Affect Advanced Performance

Science.gov (United States)

Carter, Christine E.; Grahn, Jessica A.

2016-01-01

Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the “contextual interference effect.” While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (12 min per piece) and a second concerto exposition and technical excerpt to practice in an interleaved schedule (3 min per piece, alternating until a total of 12 min of practice were completed on each piece). Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated better than those in the blocked schedule

Optimizing music learning: Exploring how blocked and interleaved practice schedules affect advanced performance

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Christine E Carter

2016-08-01

Full Text Available Repetition is the most commonly used practice strategy by musicians. Although blocks of repetition continue to be suggested in the pedagogical literature, work in the field of cognitive psychology suggests that repeated events receive less processing, thereby reducing the potential for long-term learning. Motor skill learning and sport psychology research offer an alternative. Instead of using a blocked practice schedule, with practice completed on one task before moving on to the next task, an interleaved schedule can be used, in which practice is frequently alternated between tasks. This frequent alternation involves more effortful processing, resulting in increased long-term learning. The finding that practicing in an interleaved schedule leads to better retention than practicing in a blocked schedule has been labeled the contextual interference effect. While the effect has been observed across a wide variety of fields, few studies have researched this phenomenon in a music-learning context, despite the broad potential for application to music practice. This study compared the effects of blocked and interleaved practice schedules on advanced clarinet performance in an ecologically valid context. Ten clarinetists were given one concerto exposition and one technical excerpt to practice in a blocked schedule (twelve minutes per piece and a second concerto exposition and technical excerpt to practice in an interleaved schedule (three minutes per piece, alternating until a total of twelve minutes of practice were completed on each piece. Participants sight-read the four pieces prior to practice and performed them at the end of practice and again one day later. The sight-reading and two performance run-throughs of each piece were recorded and given to three professional clarinetists to rate using a percentage scale. Overall, whenever there was a ratings difference between the conditions, pieces practiced in the interleaved schedule were rated

Learning Capability and Business Performance: A Non-Financial and Financial Assessment

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Ma Prieto, Isabel; Revilla, Elena

2006-01-01

Purpose: There has been little research that includes reliable deductions about the positive influence of learning capability on business performance. For this reason, the main objective of the present study is to empirically explore the link between learning capability in organizations and business performance evaluated in both financial and…

Continued usage of e-learning: Expectations and performance

OpenAIRE

Fernando Antonio de Melo Pereira; Anatália Saraiva Martins Ramos; Adrianne Paula Vieira de Andrade; Bruna Miyuki Kasuya de Oliveira

2015-01-01

The present study aims to investigate the determinants of satisfaction and the resulting continuance intention use in e-learning context. The constructs of decomposed expectancy disconfirmation theory (DEDT) are evaluated from the perspective of users of a virtual learning environment (VLE) in relation to expectations and perceived performance. An online survey collected responses from 197 students of a public management course in distance mode. Structural equation modeling was operationalize...

Effectiveness of Student's Note-Taking Activities and Characteristics of Their Learning Performance in Two Types of Online Learning

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Nakayama, Minoru; Mutsuura, Kouichi; Yamamoto, Hiroh

2017-01-01

Aspects of learning behavior during two types of university courses, a blended learning course and a fully online course, were examined using note-taking activity. The contribution of students' characteristics and styles of learning to note-taking activity and learning performance were analyzed, and the relationships between the two types of…

Learning-performance distinction and memory processes for motor skills: a focused review and perspective.

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Kantak, Shailesh S; Winstein, Carolee J

2012-03-01

Behavioral research in cognitive psychology provides evidence for an important distinction between immediate performance that accompanies practice and long-term performance that reflects the relative permanence in the capability for the practiced skill (i.e. learning). This learning-performance distinction is strikingly evident when challenging practice conditions may impair practice performance, but enhance long-term retention of motor skills. A review of motor learning studies with a specific focus on comparing differences in performance between that at the end of practice and at delayed retention suggests that the delayed retention or transfer performance is a better indicator of motor learning than the performance at (or end of) practice. This provides objective evidence for the learning-performance distinction. This behavioral evidence coupled with an understanding of the motor memory processes of encoding, consolidation and retrieval may provide insight into the putative mechanism that implements the learning-performance distinction. Here, we propose a simplistic empirically-based framework--motor behavior-memory framework--that integrates the temporal evolution of motor memory processes with the time course of practice and delayed retention frequently used in behavioral motor learning paradigms. In the context of the proposed framework, recent research has used noninvasive brain stimulation to decipher the role of each motor memory process, and specific cortical brain regions engaged in motor performance and learning. Such findings provide beginning insights into the relationship between the time course of practice-induced performance changes and motor memory processes. This in turn has promising implications for future research and practical applications. Copyright © 2011 Elsevier B.V. All rights reserved.

Using Technology-Enhanced, Cooperative, Group-Project Learning for Student Comprehension and Academic Performance

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Tlhoaele, Malefyane; Suhre, Cor; Hofman, Adriaan

2016-01-01

Cooperative learning may improve students' motivation, understanding of course concepts, and academic performance. This study therefore enhanced a cooperative, group-project learning technique with technology resources to determine whether doing so improved students' deep learning and performance. A sample of 118 engineering students, randomly…

A SEMI-AUTOMATIC RULE SET BUILDING METHOD FOR URBAN LAND COVER CLASSIFICATION BASED ON MACHINE LEARNING AND HUMAN KNOWLEDGE

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H. Y. Gu

2017-09-01

Full Text Available Classification rule set is important for Land Cover classification, which refers to features and decision rules. The selection of features and decision are based on an iterative trial-and-error approach that is often utilized in GEOBIA, however, it is time-consuming and has a poor versatility. This study has put forward a rule set building method for Land cover classification based on human knowledge and machine learning. The use of machine learning is to build rule sets effectively which will overcome the iterative trial-and-error approach. The use of human knowledge is to solve the shortcomings of existing machine learning method on insufficient usage of prior knowledge, and improve the versatility of rule sets. A two-step workflow has been introduced, firstly, an initial rule is built based on Random Forest and CART decision tree. Secondly, the initial rule is analyzed and validated based on human knowledge, where we use statistical confidence interval to determine its threshold. The test site is located in Potsdam City. We utilised the TOP, DSM and ground truth data. The results show that the method could determine rule set for Land Cover classification semi-automatically, and there are static features for different land cover classes.

Ariadne's Thread: Using Social Presence Indices to Distinguish Learning Events in Face-to-Face and ICT-Rich Settings

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Baskin, Colin; Henderson, Michael

2005-01-01

Drawing on ancient Greek mythology, this article traces the learning experiences of 164 pre-service education students as they make the transition from a conventional face-to-face (f-2-f) learning environment to an Information and Communication Technology (ICT) rich setting. Influenced by Social Presence Theory (Short, Williams & Christie,…

Using technology-enhanced, cooperative, group-project learning for student comprehension and academic performance

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Tlhoaele, Malefyane; Suhre, Cor; Hofman, Adriaan

2016-05-01

Cooperative learning may improve students' motivation, understanding of course concepts, and academic performance. This study therefore enhanced a cooperative, group-project learning technique with technology resources to determine whether doing so improved students' deep learning and performance. A sample of 118 engineering students, randomly divided into two groups, participated in this study and provided data through questionnaires issued before and after the experiment. The results, obtained through analyses of variance and structural equation modelling, reveal that technology-enhanced, cooperative, group-project learning improves students' comprehension and academic performance.

A Curriculum Development for the Enhancement of Learning Management Performances Emphasizing Higher Order Thinking Skills for Lower Secondary Science Teachers

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Saksit Seeluangpetch

2016-12-01

conducted in Phase 3 in order to study the effectiveness of the designed curriculum on the teachers and students. The research samples consisted of 12 Science teachers teaching Mattayomsuksa 3 students. The research instruments were included the curriculum for the enhancement of learning management performances emphasizing the higher order thinking skills, the test on knowledge and understanding of the learning management focusing on the higher order thinking skills, the assessment form to assess the capability to design the learning management with the emphasis on the higher order thinking skills, the observation form to assess the ability to manage the learning process that focuses on the higher order thinking skills, and the achievement test to assess the students’ achievement in Science. The results showed as follows. 1. For the knowledge and understanding of the learning management focusing on the higher order thinking skills of the teachers, it exposed that the mean of the score in the pretest was 13.67 and the percentage was 45.56. The mean and the percentage in the post-test were 25.42 and 84.72, respectively. It could be concluded that the teachers teaching Science had knowledge and understanding in the learning management that emphasizes on the higher order thinking skills at higher level after the training. 2. The Science teachers’ capability to design the learning management with the emphasis on the higher order thinking skills was significantly appropriate. 3. The lower secondary Science teachers’ ability to manage the learning process with the emphasis on the higher order thinking skills was at good level. 4. The Mattayomsuksa 3 students learning Science with the trained teachers gained 74.68 percent in post-test which was higher than the set criteria at 70 percent. There were 82 students passing the set criteria accounted for 82 percent. The result indicated that the students achieved their learning and passed the requirement. In Phase 4, the curriculum

The impact of blended learning on student performance in a cardiovascular pharmacotherapy course.

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McLaughlin, Jacqueline E; Gharkholonarehe, Nastaran; Khanova, Julia; Deyo, Zach M; Rodgers, Jo E

2015-03-25

To examine student engagement with, perception of, and performance resulting from blended learning for venous thromboembolism in a required cardiovascular pharmacotherapy course for second-year students. In 2013, key foundational content was packaged into an interactive online module for students to access prior to coming to class; class time was dedicated to active-learning exercises. Students who accessed all online module segments participated in more in class clicker questions (p=0.043) and performed better on the examination (p=0.023). There was no difference in clicker participation or examination performance based on time of module access (prior to or after class). The majority of participants agreed or strongly agreed that foundational content learned prior to class, applied activities during class, and content-related questions in the online module greatly enhanced learning. This study highlights the importance of integrating online modules with classroom learning and the role of blended learning in improving academic performance.

Seeing the Errors You Feel Enhances Locomotor Performance but Not Learning.

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Roemmich, Ryan T; Long, Andrew W; Bastian, Amy J

2016-10-24

In human motor learning, it is thought that the more information we have about our errors, the faster we learn. Here, we show that additional error information can lead to improved motor performance without any concomitant improvement in learning. We studied split-belt treadmill walking that drives people to learn a new gait pattern using sensory prediction errors detected by proprioceptive feedback. When we also provided visual error feedback, participants acquired the new walking pattern far more rapidly and showed accelerated restoration of the normal walking pattern during washout. However, when the visual error feedback was removed during either learning or washout, errors reappeared with performance immediately returning to the level expected based on proprioceptive learning alone. These findings support a model with two mechanisms: a dual-rate adaptation process that learns invariantly from sensory prediction error detected by proprioception and a visual-feedback-dependent process that monitors learning and corrects residual errors but shows no learning itself. We show that our voluntary correction model accurately predicted behavior in multiple situations where visual feedback was used to change acquisition of new walking patterns while the underlying learning was unaffected. The computational and behavioral framework proposed here suggests that parallel learning and error correction systems allow us to rapidly satisfy task demands without necessarily committing to learning, as the relative permanence of learning may be inappropriate or inefficient when facing environments that are liable to change. Copyright © 2016 Elsevier Ltd. All rights reserved.

Science Learning Motivation as Correlate of Students' Academic Performances

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Libao, Nhorvien Jay P.; Sagun, Jessie John B.; Tamangan, Elvira A.; Pattalitan, Agaton P., Jr.; Dupa, Maria Elena D.; Bautista, Romiro G.

2016-01-01

This study was designed to analyze the relationship of students' learning motivation and their academic performances in science. The study made use of 21 junior and senior Biological Science students to conclude on the formulated research problems. The respondents had a good to very good motivation in learning science. In general, the extent of…

A fast-response production-inventory model for deteriorating seasonal products with learning in set-ups

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Ibraheem Abdul

2011-10-01

Full Text Available The classical production-inventory model assumes that both demand and set-up costs are constant. However, in real manufacturing environment, managers usually embark on continuous improvement programmes that often lead to more effective use of tools and machineries and consequently reduction in set-up costs. In fact, constant emphasis on reduction of set-up costs is usually cited as one of the factors responsible for the efficiency of Japanese manufacturing methods. On the other hand, the demand for seasonal product is often characterized by a mixture of time-dependent patterns over the entire season. This paper investigates the effect of learning-based reduction in set-up costs on the optimal schedules and costs of a production-inventory system for deteriorating seasonal products. The demand pattern is a general three-phase ramp-type demand function that represents the various phases of demand commonly observed in many seasonal products in the market. A two-parameter Weibull-distribution function is used for the deterioration of items in order to make the model more generalized and realistic. The study further presents two different multi-period production strategies that can ensure a fast-response to customers’ demand and compare them with the usual single period strategy. The Numerical example and sensitivity analysis shows that learning-based reduction in set-up costs leads to higher production frequency and shorter production runs which are vital aspects of the just-in-time (JIT philosophy.

Investing in organisational culture: nursing students' experience of organisational learning culture in aged care settings following a program of cultural development.

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Grealish, Laurie; Henderson, Amanda

2016-10-01

Concerns around organisational learning culture limit nursing student placements in aged care settings to first year experiences. Determine the impact of an extended staff capacity building program on students' experiences of the organisational learning culture in the aged care setting. Pre and post-test design. A convenience sample of first, second and third year Bachelor of Nursing students attending placements at three residential aged care facilities completed the Clinical Learning Organisational Culture Survey. Responses between the group that attended placement before the program (n = 17/44; RR 38%) and the group that attended following the program (n = 33/72; RR 45%) were compared. Improvements were noted in the areas of recognition, accomplishment, and influence, with decreases in dissatisfaction. Organisational investment in building staff capacity can produce a positive learning culture. The aged care sector offers a rich learning experience for students when staff capacity to support learning is developed.

A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance.

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Skinner, Brian; Guy, Stephen J

2015-01-01

Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player's performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled with a network-style model of the offense that relates players' skills to the team's success at running different plays, can be used to automatically learn players' skills and predict the performance of untested 5-man lineups in a way that accounts for the interaction between players' respective skill sets. After developing a general analysis procedure, we present as an example a specific implementation of our method using a simplified network model. While player tracking data is not yet available in the public domain, we evaluate our model using simulated data and show that player skills can be accurately inferred by a simple statistical inference scheme. Finally, we use the model to analyze games from the 2011 playoff series between the Memphis Grizzlies and the Oklahoma City Thunder and we show that, even with a very limited data set, the model can consistently describe a player's interactions with a given lineup based only on his performance with a different lineup.

Effects of cluster vs. traditional plyometric training sets on maximal-intensity exercise performance.

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Asadi, Abbas; Ramírez-Campillo, Rodrigo

2016-01-01

The aim of this study was to compare the effects of 6-week cluster versus traditional plyometric training sets on jumping ability, sprint and agility performance. Thirteen college students were assigned to a cluster sets group (N=6) or traditional sets group (N=7). Both training groups completed the same training program. The traditional group completed five sets of 20 repetitions with 2min of rest between sets each session, while the cluster group completed five sets of 20 [2×10] repetitions with 30/90-s rest each session. Subjects were evaluated for countermovement jump (CMJ), standing long jump (SLJ), t test, 20-m and 40-m sprint test performance before and after the intervention. Both groups had similar improvements (Psets methods resulted in greater adaptations in sprint performance, while the cluster sets method resulted in greater jump and agility adaptations. Copyright © 2016 The Lithuanian University of Health Sciences. Production and hosting by Elsevier Urban & Partner Sp. z o.o. All rights reserved.

Differential learning and memory performance in OEF/OIF veterans for verbal and visual material.

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Sozda, Christopher N; Muir, James J; Springer, Utaka S; Partovi, Diana; Cole, Michael A

2014-05-01

Memory complaints are particularly salient among veterans who experience combat-related mild traumatic brain injuries and/or trauma exposure, and represent a primary barrier to successful societal reintegration and everyday functioning. Anecdotally within clinical practice, verbal learning and memory performance frequently appears differentially reduced versus visual learning and memory scores. We sought to empirically investigate the robustness of a verbal versus visual learning and memory discrepancy and to explore potential mechanisms for a verbal/visual performance split. Participants consisted of 103 veterans with reported history of mild traumatic brain injuries returning home from U.S. military Operations Enduring Freedom and Iraqi Freedom referred for outpatient neuropsychological evaluation. Findings indicate that visual learning and memory abilities were largely intact while verbal learning and memory performance was significantly reduced in comparison, residing at approximately 1.1 SD below the mean for verbal learning and approximately 1.4 SD below the mean for verbal memory. This difference was not observed in verbal versus visual fluency performance, nor was it associated with estimated premorbid verbal abilities or traumatic brain injury history. In our sample, symptoms of depression, but not posttraumatic stress disorder, were significantly associated with reduced composite verbal learning and memory performance. Verbal learning and memory performance may benefit from targeted treatment of depressive symptomatology. Also, because visual learning and memory functions may remain intact, these might be emphasized when applying neurocognitive rehabilitation interventions to compensate for observed verbal learning and memory difficulties.

Organizational learning and continuous quality improvement: examining the impact on nursing home performance.

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Rondeau, Kent V; Wagar, Terry H

2002-01-01

Interest is growing in learning more about the ability of total quality management and continuous quality improvement (TQM/CQI) initiatives to contribute to the performance of healthcare organizations. A major factor in the successful implementation of TQM/CQI is the seminal contribution of an organization's culture. Many implementation efforts have not succeeded because of a corporate culture that failed to stress broader organizational learning. This may help to explain why some TQM/CQI programs have been unsuccessful in improving healthcare organization performance. Organizational performance variables and organizational learning orientation were assessed in a sample of 181 Canadian long-term care organizations that had implemented a formal TQM/CQI program. Categorical regression analysis shows that, in the absence of a strong corporAte culture that stresses organizational learning and employee development, few performance enhancements are reported. The results of the assessment suggest that a TQM/CQI program without the backing of a strong organizational learning culture may be insufficient to achieve augmented organizational performance.

The Impact of Students' Temporal Perspectives on Time-on-Task and Learning Performance in Game Based Learning

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Romero, Margarida; Usart, Mireia

2013-01-01

The use of games for educational purposes has been considered as a learning methodology that attracts the students' attention and may allow focusing individuals on the learning activity through the [serious games] SG game dynamic. Based on the hypothesis that students' Temporal Perspective has an impact on learning performance and time-on-task,…

Effects of Online College Student's Internet Self-Efficacy on Learning Motivation and Performance

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Chang, Chiung-Sui; Liu, Eric Zhi-Feng; Sung, Hung-Yen; Lin, Chun-Hung; Chen, Nian-Shing; Cheng, Shan-Shan

2014-01-01

This study investigates how Internet self-efficacy helps students to transform motivation into learning action, and its influence on learning performance. In this study, the effects of Internet self-efficacy on motivation and the learning performance of online college students were examined using social cognitive theory. The subjects of this study…

Enhancing Job Performance

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Devlin, Patricia

2011-01-01

The impact of the Self-Determined Career Development Model (hereafter called the Self-Determined Career Model) on the job performance of four adults with moderate intellectual disability employed in competitive work settings was examined. Employees learned to set work-related goals, develop an action plan, implement the plan, and adjust their…

Task complexity, student perceptions of vocabulary learning in EFL, and task performance.

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Wu, Xiaoli; Lowyck, Joost; Sercu, Lies; Elen, Jan

2013-03-01

The study deepened our understanding of how students' self-efficacy beliefs contribute to the context of teaching English as a foreign language in the framework of cognitive mediational paradigm at a fine-tuned task-specific level. The aim was to examine the relationship among task complexity, self-efficacy beliefs, domain-related prior knowledge, learning strategy use, and task performance as they were applied to English vocabulary learning from reading tasks. Participants were 120 second-year university students (mean age 21) from a Chinese university. This experiment had two conditions (simple/complex). A vocabulary level test was first conducted to measure participants' prior knowledge of English vocabulary. Participants were then randomly assigned to one of the learning tasks. Participants were administered task booklets together with the self-efficacy scales, measures of learning strategy use, and post-tests. Data obtained were submitted to multivariate analysis of variance (MANOVA) and path analysis. Results from the MANOVA model showed a significant effect of vocabulary level on self-efficacy beliefs, learning strategy use, and task performance. Task complexity showed no significant effect; however, an interaction effect between vocabulary level and task complexity emerged. Results from the path analysis showed self-efficacy beliefs had an indirect effect on performance. Our results highlighted the mediating role of self-efficacy beliefs and learning strategy use. Our findings indicate that students' prior knowledge plays a crucial role on both self-efficacy beliefs and task performance, and the predictive power of self-efficacy on task performance may lie in its association with learning strategy use. © 2011 The British Psychological Society.

Comparing the performance of meta-classifiers—a case study on selected imbalanced data sets relevant for prediction of liver toxicity

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Jain, Sankalp; Kotsampasakou, Eleni; Ecker, Gerhard F.

2018-04-01

Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class. Here, we present a comparison of the performance of seven different meta-classifiers for their ability to handle imbalanced datasets, whereby Random Forest is used as base-classifier. Four different datasets that are directly (cholestasis) or indirectly (via inhibition of organic anion transporting polypeptide 1B1 and 1B3) related to liver toxicity were chosen for this purpose. The imbalance ratio in these datasets ranges between 4:1 and 20:1 for negative and positive classes, respectively. Three different sets of molecular descriptors for model development were used, and their performance was assessed in 10-fold cross-validation and on an independent validation set. Stratified bagging, MetaCost and CostSensitiveClassifier were found to be the best performing among all the methods. While MetaCost and CostSensitiveClassifier provided better sensitivity values, Stratified Bagging resulted in high balanced accuracies.

Comparing the performance of meta-classifiers—a case study on selected imbalanced data sets relevant for prediction of liver toxicity

Science.gov (United States)

Jain, Sankalp; Kotsampasakou, Eleni; Ecker, Gerhard F.

2018-05-01

Cheminformatics datasets used in classification problems, especially those related to biological or physicochemical properties, are often imbalanced. This presents a major challenge in development of in silico prediction models, as the traditional machine learning algorithms are known to work best on balanced datasets. The class imbalance introduces a bias in the performance of these algorithms due to their preference towards the majority class. Here, we present a comparison of the performance of seven different meta-classifiers for their ability to handle imbalanced datasets, whereby Random Forest is used as base-classifier. Four different datasets that are directly (cholestasis) or indirectly (via inhibition of organic anion transporting polypeptide 1B1 and 1B3) related to liver toxicity were chosen for this purpose. The imbalance ratio in these datasets ranges between 4:1 and 20:1 for negative and positive classes, respectively. Three different sets of molecular descriptors for model development were used, and their performance was assessed in 10-fold cross-validation and on an independent validation set. Stratified bagging, MetaCost and CostSensitiveClassifier were found to be the best performing among all the methods. While MetaCost and CostSensitiveClassifier provided better sensitivity values, Stratified Bagging resulted in high balanced accuracies.

A Study of the Relationships among Learning Styles, Participation Types, and Performance in Programming Language Learning Supported by Online Forums

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Shaw, Ruey-Shiang

2012-01-01

This study is focused on the relationships among learning styles, participation types, and learning performance for programming language learning supported by an online forum. Kolb's learning style inventory was used in this study to determine a learner's learning type: "Diverger", "Assimilator", "Converger", and "Accommodator". Social Learning…

Incremental Learning of Context Free Grammars by Parsing-Based Rule Generation and Rule Set Search

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Nakamura, Katsuhiko; Hoshina, Akemi

This paper discusses recent improvements and extensions in Synapse system for inductive inference of context free grammars (CFGs) from sample strings. Synapse uses incremental learning, rule generation based on bottom-up parsing, and the search for rule sets. The form of production rules in the previous system is extended from Revised Chomsky Normal Form A→βγ to Extended Chomsky Normal Form, which also includes A→B, where each of β and γ is either a terminal or nonterminal symbol. From the result of bottom-up parsing, a rule generation mechanism synthesizes minimum production rules required for parsing positive samples. Instead of inductive CYK algorithm in the previous version of Synapse, the improved version uses a novel rule generation method, called ``bridging,'' which bridges the lacked part of the derivation tree for the positive string. The improved version also employs a novel search strategy, called serial search in addition to minimum rule set search. The synthesis of grammars by the serial search is faster than the minimum set search in most cases. On the other hand, the size of the generated CFGs is generally larger than that by the minimum set search, and the system can find no appropriate grammar for some CFL by the serial search. The paper shows experimental results of incremental learning of several fundamental CFGs and compares the methods of rule generation and search strategies.

Effects of cluster vs. traditional plyometric training sets on maximal-intensity exercise performance

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Abbas Asadi

2016-01-01

Conclusions: Although both plyometric training methods improved lower body maximal-intensity exercise performance, the traditional sets methods resulted in greater adaptations in sprint performance, while the cluster sets method resulted in greater jump and agility adaptations.

How the study of online collaborative learning can guide teachers and predict students' performance in a medical course.

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Saqr, Mohammed; Fors, Uno; Tedre, Matti

2018-02-06

Collaborative learning facilitates reflection, diversifies understanding and stimulates skills of critical and higher-order thinking. Although the benefits of collaborative learning have long been recognized, it is still rarely studied by social network analysis (SNA) in medical education, and the relationship of parameters that can be obtained via SNA with students' performance remains largely unknown. The aim of this work was to assess the potential of SNA for studying online collaborative clinical case discussions in a medical course and to find out which activities correlate with better performance and help predict final grade or explain variance in performance. Interaction data were extracted from the learning management system (LMS) forum module of the Surgery course in Qassim University, College of Medicine. The data were analyzed using social network analysis. The analysis included visual as well as a statistical analysis. Correlation with students' performance was calculated, and automatic linear regression was used to predict students' performance. By using social network analysis, we were able to analyze a large number of interactions in online collaborative discussions and gain an overall insight of the course social structure, track the knowledge flow and the interaction patterns, as well as identify the active participants and the prominent discussion moderators. When augmented with calculated network parameters, SNA offered an accurate view of the course network, each user's position, and level of connectedness. Results from correlation coefficients, linear regression, and logistic regression indicated that a student's position and role in information relay in online case discussions, combined with the strength of that student's network (social capital), can be used as predictors of performance in relevant settings. By using social network analysis, researchers can analyze the social structure of an online course and reveal important information

The Effectiveness of Self-Regulated Learning Scaffolds on Academic Performance in Computer-Based Learning Environments: A Meta-Analysis

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Zheng, Lanqin

2016-01-01

This meta-analysis examined research on the effects of self-regulated learning scaffolds on academic performance in computer-based learning environments from 2004 to 2015. A total of 29 articles met inclusion criteria and were included in the final analysis with a total sample size of 2,648 students. Moderator analyses were performed using a…

The Relationship between Motivation, Learning Approaches, Academic Performance and Time Spent

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Everaert, Patricia; Opdecam, Evelien; Maussen, Sophie

2017-01-01

Previous literature calls for further investigation in terms of precedents and consequences of learning approaches (deep learning and surface learning). Motivation as precedent and time spent and academic performance as consequences are addressed in this paper. The study is administered in a first-year undergraduate course. Results show that the…

Performance Measurement and Target-Setting in California's Safety Net Health Systems.

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Hemmat, Shirin; Schillinger, Dean; Lyles, Courtney; Ackerman, Sara; Gourley, Gato; Vittinghoff, Eric; Handley, Margaret; Sarkar, Urmimala

Health policies encourage implementing quality measurement with performance targets. The 2010-2015 California Medicaid waiver mandated quality measurement and reporting. In 2013, California safety net hospitals participating in the waiver set a voluntary performance target (the 90th percentile for Medicare preferred provider organization plans) for mammography screening and cholesterol control in diabetes. They did not reach the target, and the difference-in-differences analysis suggested that there was no difference for mammography ( P = .39) and low-density lipoprotein control ( P = .11) performance compared to measures for which no statewide quality improvement initiative existed. California's Medicaid waiver was associated with improved performance on a number of metrics, but this performance was not attributable to target setting on specific health conditions. Performance may have improved because of secular trends or systems improvements related to waiver funding. Relying on condition-specific targets to measure performance may underestimate improvements and disadvantage certain health systems. Achieving ambitious targets likely requires sustained fiscal, management, and workforce investments.

Implementation of E-Learning and Corporate Performance: An Empirical Investigation

OpenAIRE

Chang-Yen Lai; Wen-Ching Liou

2010-01-01

Research indicates that successful adoption of information systems (IS) to support business strategy can help the organizations gain superior financial performance. e-Learning can be defined as learning through information and communication technologies and it should include a mechanism for forecasting the actual expected benefits, converted to monetary values, and then comparing the benefits to the projected cost. This study focuses on the relationship between the e-Learning and organization...

Editorial: Technology for higher education, adult learning and human performance

OpenAIRE

Minhong Wang; Chi-Cheng Chang; Feng Wu

2013-01-01

This special issue is dedicated to technology-enabled approaches for improving higher education, adult learning, and human performance. Improvement of learning and human development for sustainable development has been recognized as a key strategy for individuals, institutions, and organizations to strengthen their competitive advantages. It becomes crucial to help adult learners and knowledge workers to improve their self-directed and life-long learning capabilities. Meanwhile, advances in t...

Weakly Supervised Dictionary Learning

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You, Zeyu; Raich, Raviv; Fern, Xiaoli Z.; Kim, Jinsub

2018-05-01

We present a probabilistic modeling and inference framework for discriminative analysis dictionary learning under a weak supervision setting. Dictionary learning approaches have been widely used for tasks such as low-level signal denoising and restoration as well as high-level classification tasks, which can be applied to audio and image analysis. Synthesis dictionary learning aims at jointly learning a dictionary and corresponding sparse coefficients to provide accurate data representation. This approach is useful for denoising and signal restoration, but may lead to sub-optimal classification performance. By contrast, analysis dictionary learning provides a transform that maps data to a sparse discriminative representation suitable for classification. We consider the problem of analysis dictionary learning for time-series data under a weak supervision setting in which signals are assigned with a global label instead of an instantaneous label signal. We propose a discriminative probabilistic model that incorporates both label information and sparsity constraints on the underlying latent instantaneous label signal using cardinality control. We present the expectation maximization (EM) procedure for maximum likelihood estimation (MLE) of the proposed model. To facilitate a computationally efficient E-step, we propose both a chain and a novel tree graph reformulation of the graphical model. The performance of the proposed model is demonstrated on both synthetic and real-world data.

Understanding employee motivation and organizational performance: Arguments for a set-theoretic approach

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Michael T. Lee

2016-09-01

Full Text Available Empirical evidence demonstrates that motivated employees mean better organizational performance. The objective of this conceptual paper is to articulate the progress that has been made in understanding employee motivation and organizational performance, and to suggest how the theory concerning employee motivation and organizational performance may be advanced. We acknowledge the existing limitations of theory development and suggest an alternative research approach. Current motivation theory development is based on conventional quantitative analysis (e.g., multiple regression analysis, structural equation modeling. Since researchers are interested in context and understanding of this social phenomena holistically, they think in terms of combinations and configurations of a set of pertinent variables. We suggest that researchers take a set-theoretic approach to complement existing conventional quantitative analysis. To advance current thinking, we propose a set-theoretic approach to leverage employee motivation for organizational performance.

A model of using social media for collaborative learning to enhance learners’ performance on learning

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Waleed Mugahed Al-Rahmi

2017-10-01

Full Text Available Social media has been always described as the channel through which knowledge is transmitted between communities and learners. This social media has been utilized by colleges in a way to encourage collaborative learning and social interaction. This study explores the use of social media in the process of collaborative learning through learning Quran and Hadith. Through this investigation, different factors enhancing collaborative learning in learning Quran and Hadith in the context of using social media are going to be examined. 340 respondents participated in this study. The structural equation modeling (SEM was used to analyze the data obtained. Upon analysis and structural model validities, the study resulted in a model used for measuring the influences of the different variables. The study reported direct and indirect significant impacts of these variables on collaborative learning through the use of social media which might lead to a better performance by learners.

Learning Needs Analysis of Collaborative E-Classes in Semi-Formal Settings: The REVIT Example

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Anna Mavroudi

2013-12-01

Full Text Available Analysis, the first phase of the typical instructional design process, is often downplayed. This paper focuses on the analysis concerning a series of e-courses for collaborative adult education in semi-formal settings by reporting and generalizing results from the REVIT project. REVIT, an EU-funded research project, offered custom e-courses to learners in several remote European areas and received a ‘best practice’ distinction in social inclusion. These e-courses were designed and developed for the purpose of providing training in aspects of the learners’ professional domains related to the utilization of information and communication technologies. The main challenge was to prove that it is possible and economically feasible to provide meaningful training opportunities via distance education, by utilizing existing infrastructure (“revitalizing schools” and by making use of modern digital technology affordances coupled with suitable distance learning techniques and Web 2.0 tools. ADDIE, the generic instructional systems design model, enhanced with a rapid prototyping phase, was put forth in order to allow stakeholders to interact with a prototypical e-course, which served as an introductory lesson and as a reference point, since its evaluation informed the design choices of all subsequent e-courses. The learning needs approach adopted in REVIT combined learner analysis, context analysis, and needs analysis into a coherent analysis framework in which several methods (observation, estimation, document analysis, survey, and dialogue were exploited. Putting emphasis on the analysis phase and decoupling the design from the delivery of the e-courses facilitated adaptation and localization. Adaptation and localization issues concerning the adoption of the REVIT distance learning framework, taking into account the socio-cultural and pedagogical context, are discussed. A central result reported is that the analysis phase was crucial for the

Using Machine Learning Methods Jointly to Find Better Set of Rules in Data Mining

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SUG Hyontai

2017-01-01

Full Text Available Rough set-based data mining algorithms are one of widely accepted machine learning technologies because of their strong mathematical background and capability of finding optimal rules based on given data sets only without room for prejudiced views to be inserted on the data. But, because the algorithms find rules very precisely, we may confront with the overfitting problem. On the other hand, association rule algorithms find rules of association, where the association resides between sets of items in database. The algorithms find itemsets that occur more than given minimum support, so that they can find the itemsets practically in reasonable time even for very large databases by supplying the minimum support appropriately. In order to overcome the problem of the overfitting problem in rough set-based algorithms, first we find large itemsets, after that we select attributes that cover the large itemsets. By using the selected attributes only, we may find better set of rules based on rough set theory. Results from experiments support our suggested method.

The Effects of Formal Learning and Informal Learning on Job Performance: The Mediating Role of the Value of Learning at Work

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Park, Yoonhee; Choi, Woojae

2016-01-01

Although research has widely recognized the relationships between formal and informal learning and job performance, empirical studies have not paid sufficient attention to these relationships. In addition, there is little understanding how individual perceptions toward learning influence the relationships between the aforementioned two types of…

Effects of a Word-Learning Training on Children With Cochlear Implants

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Lund, Emily

2014-01-01

Preschool children with hearing loss who use cochlear implants demonstrate vocabulary delays when compared to their peers without hearing loss. These delays may be a result of deficient word-learning abilities; children with cochlear implants perform more poorly on rapid word-learning tasks than children with normal hearing. This study explored the malleability of rapid word learning of preschoolers with cochlear implants by evaluating the effects of a word-learning training on rapid word learning. A single-subject, multiple probe design across participants measured the impact of the training on children’s rapid word-learning performance. Participants included 5 preschool children with cochlear implants who had an expressive lexicon of less than 150 words. An investigator guided children to identify, repeat, and learn about unknown sets of words in 2-weekly sessions across 10 weeks. The probe measure, a rapid word-learning task with a different set of words than those taught during training, was collected in the baseline, training, and maintenance conditions. All participants improved their receptive rapid word-learning performance in the training condition. The functional relation indicates that the receptive rapid word-learning performance of children with cochlear implants is malleable. PMID:23981321

Using Importance-Performance Analysis to Guide Instructional Design of Experiential Learning Activities

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Anderson, Sheri; Hsu, Yu-Chang; Kinney, Judy

2016-01-01

Designing experiential learning activities requires an instructor to think about what they want the students to learn. Using importance-performance analysis can assist with the instructional design of the activities. This exploratory study used importance-performance analysis in an online introduction to criminology course. There is limited…

From feedback- to response-based performance monitoring in active and observational learning.

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Bellebaum, Christian; Colosio, Marco

2014-09-01

Humans can adapt their behavior by learning from the consequences of their own actions or by observing others. Gradual active learning of action-outcome contingencies is accompanied by a shift from feedback- to response-based performance monitoring. This shift is reflected by complementary learning-related changes of two ACC-driven ERP components, the feedback-related negativity (FRN) and the error-related negativity (ERN), which have both been suggested to signal events "worse than expected," that is, a negative prediction error. Although recent research has identified comparable components for observed behavior and outcomes (observational ERN and FRN), it is as yet unknown, whether these components are similarly modulated by prediction errors and thus also reflect behavioral adaptation. In this study, two groups of 15 participants learned action-outcome contingencies either actively or by observation. In active learners, FRN amplitude for negative feedback decreased and ERN amplitude in response to erroneous actions increased with learning, whereas observational ERN and FRN in observational learners did not exhibit learning-related changes. Learning performance, assessed in test trials without feedback, was comparable between groups, as was the ERN following actively performed errors during test trials. In summary, the results show that action-outcome associations can be learned similarly well actively and by observation. The mechanisms involved appear to differ, with the FRN in active learning reflecting the integration of information about own actions and the accompanying outcomes.

Enhancing performance expectancies through visual illusions facilitates motor learning in children.

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Bahmani, Moslem; Wulf, Gabriele; Ghadiri, Farhad; Karimi, Saeed; Lewthwaite, Rebecca

2017-10-01

In a recent study by Chauvel, Wulf, and Maquestiaux (2015), golf putting performance was found to be affected by the Ebbinghaus illusion. Specifically, adult participants demonstrated more effective learning when they practiced with a hole that was surrounded by small circles, making it look larger, than when the hole was surrounded by large circles, making it look smaller. The present study examined whether this learning advantage would generalize to children who are assumed to be less sensitive to the visual illusion. Two groups of 10-year olds practiced putting golf balls from a distance of 2m, with perceived larger or smaller holes resulting from the visual illusion. Self-efficacy was increased in the group with the perceived larger hole. The latter group also demonstrated more accurate putting performance during practice. Importantly, learning (i.e., delayed retention performance without the illusion) was enhanced in the group that practiced with the perceived larger hole. The findings replicate previous results with adult learners and are in line with the notion that enhanced performance expectancies are key to optimal motor learning (Wulf & Lewthwaite, 2016). Copyright © 2017 Elsevier B.V. All rights reserved.

The Relationship between the Learning Organization Concept and Firms' Financial Performance: An Empirical Assessment. [and] Invited Reaction: Linking Learning with Financial Performance.

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Ellinger, Andrea D.; Ellinger, Alexander E.; Yang, Baiyin; Howton, Shelly W.

2002-01-01

Reports on a study of 208 manufacturing managers that found a positive correlation between the seven dimensions of learning organizations and four measures of business financial performance. "Invited Reaction" by Timothy T. Baldwin and Camden C. Danielson critiques the use of key respondent perceptions and bottom-line performance.…

Learning Bayesian Dependence Model for Student Modelling

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Adina COCU

2008-12-01

Full Text Available Learning a Bayesian network from a numeric set of data is a challenging task because of dual nature of learning process: initial need to learn network structure, and then to find out the distribution probability tables. In this paper, we propose a machine-learning algorithm based on hill climbing search combined with Tabu list. The aim of learning process is to discover the best network that represents dependences between nodes. Another issue in machine learning procedure is handling numeric attributes. In order to do that, we must perform an attribute discretization pre-processes. This discretization operation can influence the results of learning network structure. Therefore, we make a comparative study to find out the most suitable combination between discretization method and learning algorithm, for a specific data set.

Baseline performance and learning rate of conceptual and perceptual skill-learning tasks: the effect of moderate to severe traumatic brain injury.

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Vakil, Eli; Lev-Ran Galon, Carmit

2014-01-01

Existing literature presents a complex and inconsistent picture of the specific deficiencies involved in skill learning following traumatic brain injury (TBI). In an attempt to address this difficulty, individuals with moderate to severe TBI (n = 29) and a control group (n = 29) were tested with two different skill-learning tasks: conceptual (i.e., Tower of Hanoi Puzzle, TOHP) and perceptual (i.e., mirror reading, MR). Based on previous studies of the effect of divided attention on these tasks and findings regarding the effect of TBI on conceptual and perceptual priming tasks, it was predicted that the group with TBI would show impaired baseline performance compared to controls in the TOHP task though their learning rate would be maintained, while both baseline performance and learning rate on the MR task would be maintained. Consistent with our predictions, overall baseline performance of the group with TBI was impaired in the TOHP test, while the learning rate was not. The learning rate on the MR task was preserved but, contrary to our prediction, response time of the group with TBI was slower than that of controls. The pattern of results observed in the present study was interpreted to possibly reflect an impairment of both the frontal lobes as well as that of diffuse axonal injury, which is well documented as being affected by TBI. The former impairment affects baseline performance of the conceptual learning skill, while the latter affects the overall slower performance of the perceptual learning skill.

Learning Contracts in Undergraduate Courses: Impacts on Student Behaviors and Academic Performance

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Frank, Timothy; Scharf, Lauren F. V

2013-01-01

This project studied the effect of individualized, voluntary learning contracts for 18 students who performed poorly in the first part of the semester. Contracts were hypothesized to increase commitment and motivation, and lead to changes in behaviors and course performance. Self-reported prioritization and learning-related behaviors (completion…

Scene recognition based on integrating active learning with dictionary learning

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Wang, Chengxi; Yin, Xueyan; Yang, Lin; Gong, Chengrong; Zheng, Caixia; Yi, Yugen

2018-04-01

Scene recognition is a significant topic in the field of computer vision. Most of the existing scene recognition models require a large amount of labeled training samples to achieve a good performance. However, labeling image manually is a time consuming task and often unrealistic in practice. In order to gain satisfying recognition results when labeled samples are insufficient, this paper proposed a scene recognition algorithm named Integrating Active Learning and Dictionary Leaning (IALDL). IALDL adopts projective dictionary pair learning (DPL) as classifier and introduces active learning mechanism into DPL for improving its performance. When constructing sampling criterion in active learning, IALDL considers both the uncertainty and representativeness as the sampling criteria to effectively select the useful unlabeled samples from a given sample set for expanding the training dataset. Experiment results on three standard databases demonstrate the feasibility and validity of the proposed IALDL.

Neutronic performance of Indian LLCB TBM set conceptual design in ITER

Energy Technology Data Exchange (ETDEWEB)

Swami, H.L., E-mail: hswami@ipr.res.in; Shaw, A.K.; Mistry, A.N.; Danani, C.

2016-12-15

Highlights: • Neutronic analyses of conceptual design of LLCB test blanket module in ITER have been performed. • The estimated total tritium production rate in the LLCB TBM is 1.66E + 17 tritons/s. • Total heat deposited in the LLCB TBM is 0.46 MW and highest power density at TBM first wall is 5.2 Watt/cc. • The estimation shows the maximum DPA 2.72 at TBM FW. - Abstract: Tritium breeding blanket testing program in ITER is an important milestone towards the development of the fusion reactors. ITER organization is providing an opportunity to the partner countries to test their breeding blanket concepts. A mock-up of Indian Lead Lithium Ceramic Breeder (LLCB) tritium breeding blanket known as LLCB Test Blanket Module (TBM) will be tested in ITER equatorial port no. 2. LLCB blanket consists of lead lithium (PbLi) as a neutron multiplier & tritium breeder, ceramic breeder (Li{sub 2}TiO{sub 3}) as a tritium breeder and India specific Reduced Activation Ferretic Martinic Steel (IN-RAFMS) as a structural material. A stainless steel block which is cooled by water, called as shield block, is attached with TBM to provide neutron shield to ITER TBM port. A comprehensive neutronic performance evaluation is required for the design of the LLCB TBM set (TBM + shield block) and associated ancillary systems in ITER. The neutronic performance of the conceptual design of TBM set in ITER has been carried out and reported here. In order to carry out the neutronic performance evaluation, the neutronic models of the LLCB TBM set along with TBM frame have been constructed and inserted in the equatorial port of ITER reference neutronic model C-lite. Neutronic responses such as tritium production rate, nuclear heating, neutron flux & spectra, gas production & DPA in the LLCB TBM set are calculated considering 500 MW fusion power & fluence level of 0.3 MWa/m{sup 2}. Radiation transport code MCNP6 and FENDL 2.1 nuclear cross-section data library are used to perform the neutronic

Scaling up graph-based semisupervised learning via prototype vector machines.

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Zhang, Kai; Lan, Liang; Kwok, James T; Vucetic, Slobodan; Parvin, Bahram

2015-03-01

When the amount of labeled data are limited, semisupervised learning can improve the learner's performance by also using the often easily available unlabeled data. In particular, a popular approach requires the learned function to be smooth on the underlying data manifold. By approximating this manifold as a weighted graph, such graph-based techniques can often achieve state-of-the-art performance. However, their high time and space complexities make them less attractive on large data sets. In this paper, we propose to scale up graph-based semisupervised learning using a set of sparse prototypes derived from the data. These prototypes serve as a small set of data representatives, which can be used to approximate the graph-based regularizer and to control model complexity. Consequently, both training and testing become much more efficient. Moreover, when the Gaussian kernel is used to define the graph affinity, a simple and principled method to select the prototypes can be obtained. Experiments on a number of real-world data sets demonstrate encouraging performance and scaling properties of the proposed approach. It also compares favorably with models learned via l1 -regularization at the same level of model sparsity. These results demonstrate the efficacy of the proposed approach in producing highly parsimonious and accurate models for semisupervised learning.

Toward Understanding the Role of Web 2.0 Technology in Self-Directed Learning and Job Performance in a Single Organizational Setting: A Qualitative Case Study

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Caruso, Shirley J.

2016-01-01

This single instrumental qualitative case study explores and thickly describes job performance outcomes based upon the manner in which self-directed learning activities of a purposefully selected sample of 3 construction managers are conducted, mediated by the use of Web 2.0 technology. The data collected revealed that construction managers are…

A High-Performance Parallel FDTD Method Enhanced by Using SSE Instruction Set

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Dau-Chyrh Chang

2012-01-01

Full Text Available We introduce a hardware acceleration technique for the parallel finite difference time domain (FDTD method using the SSE (streaming (single instruction multiple data SIMD extensions instruction set. The implementation of SSE instruction set to parallel FDTD method has achieved the significant improvement on the simulation performance. The benchmarks of the SSE acceleration on both the multi-CPU workstation and computer cluster have demonstrated the advantages of (vector arithmetic logic unit VALU acceleration over GPU acceleration. Several engineering applications are employed to demonstrate the performance of parallel FDTD method enhanced by SSE instruction set.

Rough Sets as a Knowledge Discovery and Classification Tool for the Diagnosis of Students with Learning Disabilities

OpenAIRE

Yu-Chi Lin; Tung-Kuang Wu; Shian-Chang Huang; Ying-Ru Meng; Wen-Yau Liang

2011-01-01

Due to the implicit characteristics of learning disabilities (LDs), the diagnosis of students with learning disabilities has long been a difficult issue. Artificial intelligence techniques like artificial neural network (ANN) and support vector machine (SVM) have been applied to the LD diagnosis problem with satisfactory outcomes. However, special education teachers or professionals tend to be skeptical to these kinds of black-box predictors. In this study, we adopt the rough set theory (RST)...

The Semi-opened Infrastructure Model (SopIM): A Frame to Set Up an Organizational Learning Process

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Grundstein, Michel

In this paper, we introduce the "Semi-opened Infrastructure Model (SopIM)" implemented to deploy Artificial Intelligence and Knowledge-based Systems within a large industrial company. This model illustrates what could be two of the operating elements of the Model for General Knowledge Management within the Enterprise (MGKME) that are essential to set up the organizational learning process that leads people to appropriate and use concepts, methods and tools of an innovative technology: the "Ad hoc Infrastructures" element, and the "Organizational Learning Processes" element.

High variability impairs motor learning regardless of whether it affects task performance.

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Cardis, Marco; Casadio, Maura; Ranganathan, Rajiv

2018-01-01

Motor variability plays an important role in motor learning, although the exact mechanisms of how variability affects learning are not well understood. Recent evidence suggests that motor variability may have different effects on learning in redundant tasks, depending on whether it is present in the task space (where it affects task performance) or in the null space (where it has no effect on task performance). We examined the effect of directly introducing null and task space variability using a manipulandum during the learning of a motor task. Participants learned a bimanual shuffleboard task for 2 days, where their goal was to slide a virtual puck as close as possible toward a target. Critically, the distance traveled by the puck was determined by the sum of the left- and right-hand velocities, which meant that there was redundancy in the task. Participants were divided into five groups, based on both the dimension in which the variability was introduced and the amount of variability that was introduced during training. Results showed that although all groups were able to reduce error with practice, learning was affected more by the amount of variability introduced rather than the dimension in which variability was introduced. Specifically, groups with higher movement variability during practice showed larger errors at the end of practice compared with groups that had low variability during learning. These results suggest that although introducing variability can increase exploration of new solutions, this may adversely affect the ability to retain the learned solution. NEW & NOTEWORTHY We examined the role of introducing variability during motor learning in a redundant task. The presence of redundancy allows variability to be introduced in different dimensions: the task space (where it affects task performance) or the null space (where it does not affect task performance). We found that introducing variability affected learning adversely, but the amount of

Impact of E-Learning Strategy on Students' Academic Performance ...

African Journals Online (AJOL)

This study examined the impact of e-learning strategies on students' academic performance at Strathmore University. The purpose of the study was to investigate the methodology, ideologies, output and ecology of ICT strategies and their impact on students' performance. This was done through comparing students' mean ...

The Impact of Organisational Learning on Organisational Performance

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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.

A Method for Using Player Tracking Data in Basketball to Learn Player Skills and Predict Team Performance.

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Brian Skinner

Full Text Available Player tracking data represents a revolutionary new data source for basketball analysis, in which essentially every aspect of a player's performance is tracked and can be analyzed numerically. We suggest a way by which this data set, when coupled with a network-style model of the offense that relates players' skills to the team's success at running different plays, can be used to automatically learn players' skills and predict the performance of untested 5-man lineups in a way that accounts for the interaction between players' respective skill sets. After developing a general analysis procedure, we present as an example a specific implementation of our method using a simplified network model. While player tracking data is not yet available in the public domain, we evaluate our model using simulated data and show that player skills can be accurately inferred by a simple statistical inference scheme. Finally, we use the model to analyze games from the 2011 playoff series between the Memphis Grizzlies and the Oklahoma City Thunder and we show that, even with a very limited data set, the model can consistently describe a player's interactions with a given lineup based only on his performance with a different lineup.

Learning from Top-Performing Managers.

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Brown, Paul L.

2000-01-01

Illustrates five criteria that can be used to identify the "best" managers in any organization: business results, employee attitudes, peer confirmation, upper-level manager appraisal, and customer satisfaction. Examines what top-performing managers say and do, and concludes that their thinking processes and their specific sets of skills…

The Relationship between Learning Capability and Organizational Performance: A Meta-Analytic Examination

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Goh, Swee C.; Elliott, Catherine; Quon, Tony K.

2012-01-01

Purpose: The purpose of this paper is to present a meta-analysis of a subset of published empirical research papers that measure learning capability and link it to organizational performance. It also seeks to examine both financial and non-financial performance. Design/methodology/approach: In a search of published research on learning capability…

Carpet Aids Learning in High Performance Schools

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Hurd, Frank

2009-01-01

The Healthy and High Performance Schools Act of 2002 has set specific federal guidelines for school design, and developed a federal/state partnership program to assist local districts in their school planning. According to the Collaborative for High Performance Schools (CHPS), high-performance schools are, among other things, healthy, comfortable,…

Developing Research Collaborations in an Academic Clinical Setting: Challenges and Lessons Learned.

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Sahs, John A; Nicasio, Andel V; Storey, Joan E; Guarnaccia, Peter J; Lewis-Fernández, Roberto

2017-08-01

Research collaboration in "real world" practice settings may enhance the meaningfulness of the findings and reduce barriers to implementation of novel intervention strategies. This study describes an initiative to integrate research into a hospital-based outpatient psychiatric clinic within an academic medical center, focusing on collaborative processes across three research projects. We report on the varied outcomes of the projects and utilize data from two focus groups to identify the key elements that contributed to the challenges and successes. We identify barriers to practice-research collaborations that emerged even when the initial circumstances of the partnership were favorable. These barriers include the presence of varied agendas across clinicians and investigators, resource constraints, limited staff buy-in, and staff turnover. In highlighting the lessons learned in this collaborative process, we hope to facilitate successful partnerships in other clinical settings.

Learning approaches as predictors of academic performance in first year health and science students.

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Salamonson, Yenna; Weaver, Roslyn; Chang, Sungwon; Koch, Jane; Bhathal, Ragbir; Khoo, Cheang; Wilson, Ian

2013-07-01

To compare health and science students' demographic characteristics and learning approaches across different disciplines, and to examine the relationship between learning approaches and academic performance. While there is increasing recognition of a need to foster learning approaches that improve the quality of student learning, little is known about students' learning approaches across different disciplines, and their relationships with academic performance. Prospective, correlational design. Using a survey design, a total of 919 first year health and science students studying in a university located in the western region of Sydney from the following disciplines were recruited to participate in the study - i) Nursing: n = 476, ii) Engineering: n = 75, iii) Medicine: n = 77, iv) Health Sciences: n = 204, and v) Medicinal Chemistry: n = 87. Although there was no statistically significant difference in the use of surface learning among the five discipline groups, there were wide variations in the use of deep learning approach. Furthermore, older students and those with English as an additional language were more likely to use deep learning approach. Controlling for hours spent in paid work during term-time and English language usage, both surface learning approach (β = -0.13, p = 0.001) and deep learning approach (β = 0.11, p = 0.009) emerged as independent and significant predictors of academic performance. Findings from this study provide further empirical evidence that underscore the importance for faculty to use teaching methods that foster deep instead of surface learning approaches, to improve the quality of student learning and academic performance. Copyright © 2013 Elsevier Ltd. All rights reserved.

Assessment of various supervised learning algorithms using different performance metrics

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Susheel Kumar, S. M.; Laxkar, Deepak; Adhikari, Sourav; Vijayarajan, V.

2017-11-01

Our work brings out comparison based on the performance of supervised machine learning algorithms on a binary classification task. The supervised machine learning algorithms which are taken into consideration in the following work are namely Support Vector Machine(SVM), Decision Tree(DT), K Nearest Neighbour (KNN), Naïve Bayes(NB) and Random Forest(RF). This paper mostly focuses on comparing the performance of above mentioned algorithms on one binary classification task by analysing the Metrics such as Accuracy, F-Measure, G-Measure, Precision, Misclassification Rate, False Positive Rate, True Positive Rate, Specificity, Prevalence.

Learning of Rule Ensembles for Multiple Attribute Ranking Problems

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Dembczyński, Krzysztof; Kotłowski, Wojciech; Słowiński, Roman; Szeląg, Marcin

In this paper, we consider the multiple attribute ranking problem from a Machine Learning perspective. We propose two approaches to statistical learning of an ensemble of decision rules from decision examples provided by the Decision Maker in terms of pairwise comparisons of some objects. The first approach consists in learning a preference function defining a binary preference relation for a pair of objects. The result of application of this function on all pairs of objects to be ranked is then exploited using the Net Flow Score procedure, giving a linear ranking of objects. The second approach consists in learning a utility function for single objects. The utility function also gives a linear ranking of objects. In both approaches, the learning is based on the boosting technique. The presented approaches to Preference Learning share good properties of the decision rule preference model and have good performance in the massive-data learning problems. As Preference Learning and Multiple Attribute Decision Aiding share many concepts and methodological issues, in the introduction, we review some aspects bridging these two fields. To illustrate the two approaches proposed in this paper, we solve with them a toy example concerning the ranking of a set of cars evaluated by multiple attributes. Then, we perform a large data experiment on real data sets. The first data set concerns credit rating. Since recent research in the field of Preference Learning is motivated by the increasing role of modeling preferences in recommender systems and information retrieval, we chose two other massive data sets from this area - one comes from movie recommender system MovieLens, and the other concerns ranking of text documents from 20 Newsgroups data set.

Transforming and Turning around Low-Performing Schools: The Role of Online Learning

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Corry, Michael; Carlson-Bancroft, Angela

2014-01-01

This review of the literature examines online learning as a core strategy for bold, dramatic curricular reform within transformational or turnaround models in improving low-performing K-12 schools. The analysis of the literature in this area found benefits of online learning in transforming and turning around low-performing schools to include: (a)…

Performance of a Deep-Learning Neural Network Model in Assessing Skeletal Maturity on Pediatric Hand Radiographs.

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Larson, David B; Chen, Matthew C; Lungren, Matthew P; Halabi, Safwan S; Stence, Nicholas V; Langlotz, Curtis P

2018-04-01

Purpose To compare the performance of a deep-learning bone age assessment model based on hand radiographs with that of expert radiologists and that of existing automated models. Materials and Methods The institutional review board approved the study. A total of 14 036 clinical hand radiographs and corresponding reports were obtained from two children's hospitals to train and validate the model. For the first test set, composed of 200 examinations, the mean of bone age estimates from the clinical report and three additional human reviewers was used as the reference standard. Overall model performance was assessed by comparing the root mean square (RMS) and mean absolute difference (MAD) between the model estimates and the reference standard bone ages. Ninety-five percent limits of agreement were calculated in a pairwise fashion for all reviewers and the model. The RMS of a second test set composed of 913 examinations from the publicly available Digital Hand Atlas was compared with published reports of an existing automated model. Results The mean difference between bone age estimates of the model and of the reviewers was 0 years, with a mean RMS and MAD of 0.63 and 0.50 years, respectively. The estimates of the model, the clinical report, and the three reviewers were within the 95% limits of agreement. RMS for the Digital Hand Atlas data set was 0.73 years, compared with 0.61 years of a previously reported model. Conclusion A deep-learning convolutional neural network model can estimate skeletal maturity with accuracy similar to that of an expert radiologist and to that of existing automated models. © RSNA, 2017 An earlier incorrect version of this article appeared online. This article was corrected on January 19, 2018.

Deep generative learning for automated EHR diagnosis of traditional Chinese medicine.

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Liang, Zhaohui; Liu, Jun; Ou, Aihua; Zhang, Honglai; Li, Ziping; Huang, Jimmy Xiangji

2018-05-04

Computer-aided medical decision-making (CAMDM) is the method to utilize massive EMR data as both empirical and evidence support for the decision procedure of healthcare activities. Well-developed information infrastructure, such as hospital information systems and disease surveillance systems, provides abundant data for CAMDM. However, the complexity of EMR data with abstract medical knowledge makes the conventional model incompetent for the analysis. Thus a deep belief networks (DBN) based model is proposed to simulate the information analysis and decision-making procedure in medical practice. The purpose of this paper is to evaluate a deep learning architecture as an effective solution for CAMDM. A two-step model is applied in our study. At the first step, an optimized seven-layer deep belief network (DBN) is applied as an unsupervised learning algorithm to perform model training to acquire feature representation. Then a support vector machine model is adopted to DBN at the second step of the supervised learning. There are two data sets used in the experiments. One is a plain text data set indexed by medical experts. The other is a structured dataset on primary hypertension. The data are randomly divided to generate the training set for the unsupervised learning and the testing set for the supervised learning. The model performance is evaluated by the statistics of mean and variance, the average precision and coverage on the data sets. Two conventional shallow models (support vector machine / SVM and decision tree / DT) are applied as the comparisons to show the superiority of our proposed approach. The deep learning (DBN + SVM) model outperforms simple SVM and DT on two data sets in terms of all the evaluation measures, which confirms our motivation that the deep model is good at capturing the key features with less dependence when the index is built up by manpower. Our study shows the two-step deep learning model achieves high performance for medical

Involvement of Working Memory in College Students' Sequential Pattern Learning and Performance

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Kundey, Shannon M. A.; De Los Reyes, Andres; Rowan, James D.; Lee, Bern; Delise, Justin; Molina, Sabrina; Cogdill, Lindsay

2013-01-01

When learning highly organized sequential patterns of information, humans and nonhuman animals learn rules regarding the hierarchical structures of these sequences. In three experiments, we explored the role of working memory in college students' sequential pattern learning and performance in a computerized task involving a sequential…

Digital Game-Based Learning Supports Student Motivation, Cognitive Success, and Performance Outcomes

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Woo, Jeng-Chung

2014-01-01

Traditional multimedia learning is primarily based on the cognitive load concept of information processing theory. Recent digital game-based learning (DGBL) studies have focused on exploring content support for learning motivation and related game characteristics. Motivation, volition, and performance (MVP) theory indicates that cognitive load and…

An integrative review of in-class activities that enable active learning in college science classroom settings

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Arthurs, Leilani A.; Kreager, Bailey Zo

2017-10-01

Engaging students in active learning is linked to positive learning outcomes. This study aims to synthesise the peer-reviewed literature about 'active learning' in college science classroom settings. Using the methodology of an integrative literature review, 337 articles archived in the Educational Resources Information Center (ERIC) are examined. Four categories of in-class activities emerge: (i) individual non-polling activities, (ii) in-class polling activities, (iii) whole-class discussion or activities, and (iv) in-class group activities. Examining the collection of identified in-class activities through the lens of a theoretical framework informed by constructivism and social interdependence theory, we synthesise the reviewed literature to propose the active learning strategies (ALSs) model and the instructional decisions to enable active learning (IDEAL) theory. The ALS model characterises in-class activities in terms of the degrees to which they are designed to promote (i) peer interaction and (ii) social interdependence. The IDEAL theory includes the ALS model and provides a framework for conceptualising different levels of the general concept 'active learning' and how these levels connect to instructional decision-making about using in-class activities. The proposed ALS model and IDEAL theory can be utilised to inform instructional decision-making and future research about active learning in college science courses.

The Effect of Learning Log on the Academic Performance of ...

African Journals Online (AJOL)

The main intent of this study was to identify the impact of using learning log as a learning strategy on the academic performance of university students. Second year psychology students were included as subjects of this study. In the beginning of the study, the students were divided into two: experimental group (N = 60) and ...

How explicit and implicit test instructions in an implicit learning task affect performance.

Directory of Open Access Journals (Sweden)

Arnaud Witt

Full Text Available Typically developing children aged 5 to 8 years were exposed to artificial grammar learning. Following an implicit exposure phase, half of the participants received neutral instructions at test while the other half received instructions making a direct, explicit reference to the training phase. We first aimed to assess whether implicit learning operated in the two test conditions. We then evaluated the differential impact of age on learning performances as a function of test instructions. The results showed that performance did not vary as a function of age in the implicit instructions condition, while age effects emerged when explicit instructions were employed at test. However, performance was affected differently by age and the instructions given at test, depending on whether the implicit learning of short or long units was assessed. These results suggest that the claim that the implicit learning process is independent of age needs to be revised.

The development of automaticity in short-term memory search: Item-response learning and category learning.

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Cao, Rui; Nosofsky, Robert M; Shiffrin, Richard M

2017-05-01

In short-term-memory (STM)-search tasks, observers judge whether a test probe was present in a short list of study items. Here we investigated the long-term learning mechanisms that lead to the highly efficient STM-search performance observed under conditions of consistent-mapping (CM) training, in which targets and foils never switch roles across trials. In item-response learning, subjects learn long-term mappings between individual items and target versus foil responses. In category learning, subjects learn high-level codes corresponding to separate sets of items and learn to attach old versus new responses to these category codes. To distinguish between these 2 forms of learning, we tested subjects in categorized varied mapping (CV) conditions: There were 2 distinct categories of items, but the assignment of categories to target versus foil responses varied across trials. In cases involving arbitrary categories, CV performance closely resembled standard varied-mapping performance without categories and departed dramatically from CM performance, supporting the item-response-learning hypothesis. In cases involving prelearned categories, CV performance resembled CM performance, as long as there was sufficient practice or steps taken to reduce trial-to-trial category-switching costs. This pattern of results supports the category-coding hypothesis for sufficiently well-learned categories. Thus, item-response learning occurs rapidly and is used early in CM training; category learning is much slower but is eventually adopted and is used to increase the efficiency of search beyond that available from item-response learning. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Does academic performance or personal growth share a stronger association with learning environment perception?

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Tackett, Sean; Wright, Scott M.; Shochet, Robert S.

2016-01-01

Objectives This study was conducted to characterize the relative strength of associations of learning environment perception with academic performance and with personal growth. Methods In 2012-2014 second and third year students at Johns Hopkins University School of Medicine completed a learning environment survey and personal growth scale. Hierarchical linear regression analysis was employed to determine if the proportion of variance in learning environment scores accounted for by personal growth was significantly larger than the proportion accounted for by academic performance (course/clerkship grades). Results The proportion of variance in learning environment scores accounted for by personal growth was larger than the proportion accounted for by academic performance in year 2 [R2Δ of 0.09, F(1,175) = 14.99,  p environment scores shared a small amount of variance with academic performance in years 2 and 3.  The amount of variance between learning environment scores and personal growth was small in year 2 and large in year 3. Conclusions Since supportive learning environments are essential for medical education, future work must determine if enhancing personal growth prior to and during the clerkship year will increase learning environment perception. PMID:27570912

Working with Negative Emotions in Sets

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Hillman, Alison

2012-01-01

This account draws upon learning from an incident in an action learning set where an individual challenged a mandatory organisational requirement. As a facilitator I reflect upon my initial defensive reaction to this challenge. The use of critical action learning to inform ourselves as facilitators of the underlying tensions between set members…

Learning better deep features for the prediction of occult invasive disease in ductal carcinoma in situ through transfer learning

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Shi, Bibo; Hou, Rui; Mazurowski, Maciej A.; Grimm, Lars J.; Ren, Yinhao; Marks, Jeffrey R.; King, Lorraine M.; Maley, Carlo C.; Hwang, E. Shelley; Lo, Joseph Y.

2018-02-01

Purpose: To determine whether domain transfer learning can improve the performance of deep features extracted from digital mammograms using a pre-trained deep convolutional neural network (CNN) in the prediction of occult invasive disease for patients with ductal carcinoma in situ (DCIS) on core needle biopsy. Method: In this study, we collected digital mammography magnification views for 140 patients with DCIS at biopsy, 35 of which were subsequently upstaged to invasive cancer. We utilized a deep CNN model that was pre-trained on two natural image data sets (ImageNet and DTD) and one mammographic data set (INbreast) as the feature extractor, hypothesizing that these data sets are increasingly more similar to our target task and will lead to better representations of deep features to describe DCIS lesions. Through a statistical pooling strategy, three sets of deep features were extracted using the CNNs at different levels of convolutional layers from the lesion areas. A logistic regression classifier was then trained to predict which tumors contain occult invasive disease. The generalization performance was assessed and compared using repeated random sub-sampling validation and receiver operating characteristic (ROC) curve analysis. Result: The best performance of deep features was from CNN model pre-trained on INbreast, and the proposed classifier using this set of deep features was able to achieve a median classification performance of ROC-AUC equal to 0.75, which is significantly better (p<=0.05) than the performance of deep features extracted using ImageNet data set (ROCAUC = 0.68). Conclusion: Transfer learning is helpful for learning a better representation of deep features, and improves the prediction of occult invasive disease in DCIS.

E-learning educational process

Directory of Open Access Journals (Sweden)

Leszek Rudak

2012-06-01

Full Text Available The e-learning educational process differs fundamentally from the teaching-learning process in the face-to-face teaching. A reason of differences is the nature of the distance education: the teacher cannot observe the student at work. Thus, the natural process of teaching, based on performing particular actions by teacher and students in relays, is disturbed. So, one has to consider the e-learning educational process as two separate sets of actions. The first, strongly regular, consists of teachers operations. The second, unorganized, contains the student activities. In the article some relations between the both structures are investigated. Moreover, some methods of arranging the set of students’ activities to better fit in with the educational goals are provided.

Process and impact evaluation of the Romp & Chomp obesity prevention intervention in early childhood settings: lessons learned from implementation in preschools and long day care settings.

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de Silva-Sanigorski, Andrea M; Bell, Andrew C; Kremer, Peter; Park, Janet; Demajo, Lisa; Smith, Michael; Sharp, Sharon; Nichols, Melanie; Carpenter, Lauren; Boak, Rachel; Swinburn, Boyd

2012-06-01

The Romp & Chomp controlled trial, which aimed to prevent obesity in preschool Australian children, was recently found to reduce the prevalence of childhood overweight and obesity and improve children's dietary patterns. The intervention focused on capacity building and policy implementation within various early childhood settings. This paper reports on the process and impact evaluation of this trial and the lessons learned from this complex community intervention. Process data was collected throughout and audits capturing nutrition and physical activity-related environments and practices were completed postintervention by directors of Long Day Care (LDC) centers (n = 10) and preschools (n = 41) in intervention and comparison (n = 161 LDC and n = 347 preschool) groups. The environmental audits demonstrated positive impacts in both settings on policy, nutrition, physical activity opportunities, and staff capacity and practices, although results varied across settings and were more substantial in the preschool settings. Important lessons were learned in relation to implementation of such community-based interventions, including the significant barriers to implementing health-promotion interventions in early childhood settings, lack of engagement of for-profit LDC centers in the evaluation, and an inability to attribute direct intervention impacts when the intervention components were delivered as part of a health-promotion package integrated with other programs. These results provide confidence that obesity prevention interventions in children's settings can be effective; however, significant efforts must be directed toward developing context-specific strategies that invest in policies, capacity building, staff support, and parent engagement. Recognition by funders and reviewers of the difficulties involved in implementing and evaluating such complex interventions is also critical to strengthening the evidence base on the effectiveness of such public health

Setting analytical performance specifications based on outcome studies - is it possible?

NARCIS (Netherlands)

Horvath, Andrea Rita; Bossuyt, Patrick M. M.; Sandberg, Sverre; John, Andrew St; Monaghan, Phillip J.; Verhagen-Kamerbeek, Wilma D. J.; Lennartz, Lieselotte; Cobbaert, Christa M.; Ebert, Christoph; Lord, Sarah J.

2015-01-01

The 1st Strategic Conference of the European Federation of Clinical Chemistry and Laboratory Medicine proposed a simplified hierarchy for setting analytical performance specifications (APS). The top two levels of the 1999 Stockholm hierarchy, i.e., evaluation of the effect of analytical performance

Early Childhood Educators' Use of Natural Outdoor Settings as Learning Environments: An Exploratory Study of Beliefs, Practices, and Barriers

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Ernst, Julie

2014-01-01

In efforts to encourage use of natural outdoor settings as learning environments within early childhood education, survey research was conducted with 46 early childhood educators from northern Minnesota (United States) to explore their beliefs and practices regarding natural outdoor settings, as well investigate predictors of and barriers to the…

Setting live coding performance in wider historical contexts