Unsupervised Discovery of Demixed, Low-Dimensional Neural Dynamics across Multiple Timescales through Tensor Component Analysis.

PubMed

Williams, Alex H; Kim, Tony Hyun; Wang, Forea; Vyas, Saurabh; Ryu, Stephen I; Shenoy, Krishna V; Schnitzer, Mark; Kolda, Tamara G; Ganguli, Surya

2018-06-27

Perceptions, thoughts, and actions unfold over millisecond timescales, while learned behaviors can require many days to mature. While recent experimental advances enable large-scale and long-term neural recordings with high temporal fidelity, it remains a formidable challenge to extract unbiased and interpretable descriptions of how rapid single-trial circuit dynamics change slowly over many trials to mediate learning. We demonstrate a simple tensor component analysis (TCA) can meet this challenge by extracting three interconnected, low-dimensional descriptions of neural data: neuron factors, reflecting cell assemblies; temporal factors, reflecting rapid circuit dynamics mediating perceptions, thoughts, and actions within each trial; and trial factors, describing both long-term learning and trial-to-trial changes in cognitive state. We demonstrate the broad applicability of TCA by revealing insights into diverse datasets derived from artificial neural networks, large-scale calcium imaging of rodent prefrontal cortex during maze navigation, and multielectrode recordings of macaque motor cortex during brain machine interface learning. Copyright © 2018 Elsevier Inc. All rights reserved.

Adaptive social learning strategies in temporally and spatially varying environments : how temporal vs. spatial variation, number of cultural traits, and costs of learning influence the evolution of conformist-biased transmission, payoff-biased transmission, and individual learning.

PubMed

Nakahashi, Wataru; Wakano, Joe Yuichiro; Henrich, Joseph

2012-12-01

Long before the origins of agriculture human ancestors had expanded across the globe into an immense variety of environments, from Australian deserts to Siberian tundra. Survival in these environments did not principally depend on genetic adaptations, but instead on evolved learning strategies that permitted the assembly of locally adaptive behavioral repertoires. To develop hypotheses about these learning strategies, we have modeled the evolution of learning strategies to assess what conditions and constraints favor which kinds of strategies. To build on prior work, we focus on clarifying how spatial variability, temporal variability, and the number of cultural traits influence the evolution of four types of strategies: (1) individual learning, (2) unbiased social learning, (3) payoff-biased social learning, and (4) conformist transmission. Using a combination of analytic and simulation methods, we show that spatial-but not temporal-variation strongly favors the emergence of conformist transmission. This effect intensifies when migration rates are relatively high and individual learning is costly. We also show that increasing the number of cultural traits above two favors the evolution of conformist transmission, which suggests that the assumption of only two traits in many models has been conservative. We close by discussing how (1) spatial variability represents only one way of introducing the low-level, nonadaptive phenotypic trait variation that so favors conformist transmission, the other obvious way being learning errors, and (2) our findings apply to the evolution of conformist transmission in social interactions. Throughout we emphasize how our models generate empirical predictions suitable for laboratory testing.

Informatics and machine learning to define the phenotype.

PubMed

Basile, Anna Okula; Ritchie, Marylyn DeRiggi

2018-03-01

For the past decade, the focus of complex disease research has been the genotype. From technological advancements to the development of analysis methods, great progress has been made. However, advances in our definition of the phenotype have remained stagnant. Phenotype characterization has recently emerged as an exciting area of informatics and machine learning. The copious amounts of diverse biomedical data that have been collected may be leveraged with data-driven approaches to elucidate trait-related features and patterns. Areas covered: In this review, the authors discuss the phenotype in traditional genetic associations and the challenges this has imposed.Approaches for phenotype refinement that can aid in more accurate characterization of traits are also discussed. Further, the authors highlight promising machine learning approaches for establishing a phenotype and the challenges of electronic health record (EHR)-derived data. Expert commentary: The authors hypothesize that through unsupervised machine learning, data-driven approaches can be used to define phenotypes rather than relying on expert clinician knowledge. Through the use of machine learning and an unbiased set of features extracted from clinical repositories, researchers will have the potential to further understand complex traits and identify patient subgroups. This knowledge may lead to more preventative and precise clinical care.

When Unbiased Probabilistic Learning Is Not Enough: Acquiring a Parametric System of Metrical Phonology

ERIC Educational Resources Information Center

Pearl, Lisa S.

2011-01-01

Parametric systems have been proposed as models of how humans represent knowledge about language, motivated in part as a way to explain children's rapid acquisition of linguistic knowledge. Given this, it seems reasonable to examine if children with knowledge of parameters could in fact acquire the adult system from the data available to them.…

Virtual screening by a new Clustering-based Weighted Similarity Extreme Learning Machine approach

PubMed Central

Kudisthalert, Wasu

2018-01-01

Machine learning techniques are becoming popular in virtual screening tasks. One of the powerful machine learning algorithms is Extreme Learning Machine (ELM) which has been applied to many applications and has recently been applied to virtual screening. We propose the Weighted Similarity ELM (WS-ELM) which is based on a single layer feed-forward neural network in a conjunction of 16 different similarity coefficients as activation function in the hidden layer. It is known that the performance of conventional ELM is not robust due to random weight selection in the hidden layer. Thus, we propose a Clustering-based WS-ELM (CWS-ELM) that deterministically assigns weights by utilising clustering algorithms i.e. k-means clustering and support vector clustering. The experiments were conducted on one of the most challenging datasets–Maximum Unbiased Validation Dataset–which contains 17 activity classes carefully selected from PubChem. The proposed algorithms were then compared with other machine learning techniques such as support vector machine, random forest, and similarity searching. The results show that CWS-ELM in conjunction with support vector clustering yields the best performance when utilised together with Sokal/Sneath(1) coefficient. Furthermore, ECFP_6 fingerprint presents the best results in our framework compared to the other types of fingerprints, namely ECFP_4, FCFP_4, and FCFP_6. PMID:29652912

Magnetic resonance image restoration via dictionary learning under spatially adaptive constraints.

PubMed

Wang, Shanshan; Xia, Yong; Dong, Pei; Feng, David Dagan; Luo, Jianhua; Huang, Qiu

2013-01-01

This paper proposes a spatially adaptive constrained dictionary learning (SAC-DL) algorithm for Rician noise removal in magnitude magnetic resonance (MR) images. This algorithm explores both the strength of dictionary learning to preserve image structures and the robustness of local variance estimation to remove signal-dependent Rician noise. The magnitude image is first separated into a number of partly overlapping image patches. The statistics of each patch are collected and analyzed to obtain a local noise variance. To better adapt to Rician noise, a correction factor is formulated with the local signal-to-noise ratio (SNR). Finally, the trained dictionary is used to denoise each image patch under spatially adaptive constraints. The proposed algorithm has been compared to the popular nonlocal means (NLM) filtering and unbiased NLM (UNLM) algorithm on simulated T1-weighted, T2-weighted and PD-weighted MR images. Our results suggest that the SAC-DL algorithm preserves more image structures while effectively removing the noise than NLM and it is also superior to UNLM at low noise levels.

Valence-Dependent Belief Updating: Computational Validation

PubMed Central

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments. PMID:28706499

Valence-Dependent Belief Updating: Computational Validation.

PubMed

Kuzmanovic, Bojana; Rigoux, Lionel

2017-01-01

People tend to update beliefs about their future outcomes in a valence-dependent way: they are likely to incorporate good news and to neglect bad news. However, belief formation is a complex process which depends not only on motivational factors such as the desire for favorable conclusions, but also on multiple cognitive variables such as prior beliefs, knowledge about personal vulnerabilities and resources, and the size of the probabilities and estimation errors. Thus, we applied computational modeling in order to test for valence-induced biases in updating while formally controlling for relevant cognitive factors. We compared biased and unbiased Bayesian models of belief updating, and specified alternative models based on reinforcement learning. The experiment consisted of 80 trials with 80 different adverse future life events. In each trial, participants estimated the base rate of one of these events and estimated their own risk of experiencing the event before and after being confronted with the actual base rate. Belief updates corresponded to the difference between the two self-risk estimates. Valence-dependent updating was assessed by comparing trials with good news (better-than-expected base rates) with trials with bad news (worse-than-expected base rates). After receiving bad relative to good news, participants' updates were smaller and deviated more strongly from rational Bayesian predictions, indicating a valence-induced bias. Model comparison revealed that the biased (i.e., optimistic) Bayesian model of belief updating better accounted for data than the unbiased (i.e., rational) Bayesian model, confirming that the valence of the new information influenced the amount of updating. Moreover, alternative computational modeling based on reinforcement learning demonstrated higher learning rates for good than for bad news, as well as a moderating role of personal knowledge. Finally, in this specific experimental context, the approach based on reinforcement learning was superior to the Bayesian approach. The computational validation of valence-dependent belief updating represents a novel support for a genuine optimism bias in human belief formation. Moreover, the precise control of relevant cognitive variables justifies the conclusion that the motivation to adopt the most favorable self-referential conclusions biases human judgments.

A New Model for the Estimation of Cell Proliferation Dynamics Using CFSE Data

DTIC Science & Technology

2011-08-20

cells, and hence into the resulting division and death rates . Alternatively, we propose that there is information to be learned not only from...meaningful estimation of population proliferation and death rates in a manner which is unbiased and mechanistically sound. Significantly, this new model is...change in permitting the dependence of the proliferation and death rates (α and β) and the label loss rate (v) on both time t and measured FI x. This

Machine Learning methods for Quantitative Radiomic Biomarkers.

PubMed

Parmar, Chintan; Grossmann, Patrick; Bussink, Johan; Lambin, Philippe; Aerts, Hugo J W L

2015-08-17

Radiomics extracts and mines large number of medical imaging features quantifying tumor phenotypic characteristics. Highly accurate and reliable machine-learning approaches can drive the success of radiomic applications in clinical care. In this radiomic study, fourteen feature selection methods and twelve classification methods were examined in terms of their performance and stability for predicting overall survival. A total of 440 radiomic features were extracted from pre-treatment computed tomography (CT) images of 464 lung cancer patients. To ensure the unbiased evaluation of different machine-learning methods, publicly available implementations along with reported parameter configurations were used. Furthermore, we used two independent radiomic cohorts for training (n = 310 patients) and validation (n = 154 patients). We identified that Wilcoxon test based feature selection method WLCX (stability = 0.84 ± 0.05, AUC = 0.65 ± 0.02) and a classification method random forest RF (RSD = 3.52%, AUC = 0.66 ± 0.03) had highest prognostic performance with high stability against data perturbation. Our variability analysis indicated that the choice of classification method is the most dominant source of performance variation (34.21% of total variance). Identification of optimal machine-learning methods for radiomic applications is a crucial step towards stable and clinically relevant radiomic biomarkers, providing a non-invasive way of quantifying and monitoring tumor-phenotypic characteristics in clinical practice.

Exploring Genome-Wide Expression Profiles Using Machine Learning Techniques.

PubMed

Kebschull, Moritz; Papapanou, Panos N

2017-01-01

Although contemporary high-throughput -omics methods produce high-dimensional data, the resulting wealth of information is difficult to assess using traditional statistical procedures. Machine learning methods facilitate the detection of additional patterns, beyond the mere identification of lists of features that differ between groups.Here, we demonstrate the utility of (1) supervised classification algorithms in class validation, and (2) unsupervised clustering in class discovery. We use data from our previous work that described the transcriptional profiles of gingival tissue samples obtained from subjects suffering from chronic or aggressive periodontitis (1) to test whether the two diagnostic entities were also characterized by differences on the molecular level, and (2) to search for a novel, alternative classification of periodontitis based on the tissue transcriptomes.Using machine learning technology, we provide evidence for diagnostic imprecision in the currently accepted classification of periodontitis, and demonstrate that a novel, alternative classification based on differences in gingival tissue transcriptomes is feasible. The outlined procedures allow for the unbiased interrogation of high-dimensional datasets for characteristic underlying classes, and are applicable to a broad range of -omics data.

A robust classic.

PubMed

Kutzner, Florian; Vogel, Tobias; Freytag, Peter; Fiedler, Klaus

2011-01-01

In the present research, we argue for the robustness of illusory correlations (ICs, Hamilton & Gifford, 1976) regarding two boundary conditions suggested in previous research. First, we argue that ICs are maintained under extended experience. Using simulations, we derive conflicting predictions. Whereas noise-based accounts predict ICs to be maintained (Fielder, 2000; Smith, 1991), a prominent account based on discrepancy-reducing feedback learning predicts ICs to disappear (Van Rooy et al., 2003). An experiment involving 320 observations with majority and minority members supports the claim that ICs are maintained. Second, we show that actively using the stereotype to make predictions that are met with reward and punishment does not eliminate the bias. In addition, participants' operant reactions afford a novel online measure of ICs. In sum, our findings highlight the robustness of ICs that can be explained as a result of unbiased but noisy learning.

Learning the Relationship between Galaxy Spectra and Star Formation Histories

NASA Astrophysics Data System (ADS)

Lovell, Christopher; Acquaviva, Viviana; Iyer, Kartheik; Gawiser, Eric

2018-01-01

We explore novel approaches to the problem of predicting a galaxy’s star formation history (SFH) from its Spectral Energy Distribution (SED). Traditional approaches to SED template fitting use constant or exponentially declining SFHs, and are known to incur significant bias in the inferred SFHs, which are typically skewed toward younger stellar populations. Machine learning approaches, including tree ensemble methods and convolutional neural networks, would not be affected by the same bias, and may work well in recovering unbiased and multi-episodic star formation histories. We use a supervised approach whereby models are trained using synthetic spectra, generated from three state of the art hydrodynamical simulations, including nebular emission. We explore how SED feature maps can be used to highlight areas of the spectrum with the highest predictive power and discuss the limitations of the approach when applied to real data.

Fault Tolerant Characteristics of Artificial Neural Network Electronic Hardware

NASA Technical Reports Server (NTRS)

Zee, Frank

1995-01-01

The fault tolerant characteristics of analog-VLSI artificial neural network (with 32 neurons and 532 synapses) chips are studied by exposing them to high energy electrons, high energy protons, and gamma ionizing radiations under biased and unbiased conditions. The biased chips became nonfunctional after receiving a cumulative dose of less than 20 krads, while the unbiased chips only started to show degradation with a cumulative dose of over 100 krads. As the total radiation dose increased, all the components demonstrated graceful degradation. The analog sigmoidal function of the neuron became steeper (increase in gain), current leakage from the synapses progressively shifted the sigmoidal curve, and the digital memory of the synapses and the memory addressing circuits began to gradually fail. From these radiation experiments, we can learn how to modify certain designs of the neural network electronic hardware without using radiation-hardening techniques to increase its reliability and fault tolerance.

Prioritizing causal disease genes using unbiased genomic features.

PubMed

Deo, Rahul C; Musso, Gabriel; Tasan, Murat; Tang, Paul; Poon, Annie; Yuan, Christiana; Felix, Janine F; Vasan, Ramachandran S; Beroukhim, Rameen; De Marco, Teresa; Kwok, Pui-Yan; MacRae, Calum A; Roth, Frederick P

2014-12-03

Cardiovascular disease (CVD) is the leading cause of death in the developed world. Human genetic studies, including genome-wide sequencing and SNP-array approaches, promise to reveal disease genes and mechanisms representing new therapeutic targets. In practice, however, identification of the actual genes contributing to disease pathogenesis has lagged behind identification of associated loci, thus limiting the clinical benefits. To aid in localizing causal genes, we develop a machine learning approach, Objective Prioritization for Enhanced Novelty (OPEN), which quantitatively prioritizes gene-disease associations based on a diverse group of genomic features. This approach uses only unbiased predictive features and thus is not hampered by a preference towards previously well-characterized genes. We demonstrate success in identifying genetic determinants for CVD-related traits, including cholesterol levels, blood pressure, and conduction system and cardiomyopathy phenotypes. Using OPEN, we prioritize genes, including FLNC, for association with increased left ventricular diameter, which is a defining feature of a prevalent cardiovascular disorder, dilated cardiomyopathy or DCM. Using a zebrafish model, we experimentally validate FLNC and identify a novel FLNC splice-site mutation in a patient with severe DCM. Our approach stands to assist interpretation of large-scale genetic studies without compromising their fundamentally unbiased nature.

Some simple guides to finding useful information in exploration geochemical data

USGS Publications Warehouse

Singer, D.A.; Kouda, R.

2001-01-01

Most regional geochemistry data reflect processes that can produce superfluous bits of noise and, perhaps, information about the mineralization process of interest. There are two end-member approaches to finding patterns in geochemical data-unsupervised learning and supervised learning. In unsupervised learning, data are processed and the geochemist is given the task of interpreting and identifying possible sources of any patterns. In supervised learning, data from known subgroups such as rock type, mineralized and nonmineralized, and types of mineralization are used to train the system which then is given unknown samples to classify into these subgroups. To locate patterns of interest, it is helpful to transform the data and to remove unwanted masking patterns. With trace elements use of a logarithmic transformation is recommended. In many situations, missing censored data can be estimated using multiple regression of other uncensored variables on the variable with censored values. In unsupervised learning, transformed values can be standardized, or normalized, to a Z-score by subtracting the subset's mean and dividing by its standard deviation. Subsets include any source of differences that might be related to processes unrelated to the target sought such as different laboratories, regional alteration, analytical procedures, or rock types. Normalization removes effects of different means and measurement scales as well as facilitates comparison of spatial patterns of elements. These adjustments remove effects of different subgroups and hopefully leave on the map the simple and uncluttered pattern(s) related to the mineralization only. Supervised learning methods, such as discriminant analysis and neural networks, offer the promise of consistent and, in certain situations, unbiased estimates of where mineralization might exist. These methods critically rely on being trained with data that encompasses all populations fairly and that can possibly fall into only the identified populations. ?? 2001 International Association for Mathematical Geology.

Discover mouse gene coexpression landscapes using dictionary learning and sparse coding.

PubMed

Li, Yujie; Chen, Hanbo; Jiang, Xi; Li, Xiang; Lv, Jinglei; Peng, Hanchuan; Tsien, Joe Z; Liu, Tianming

2017-12-01

Gene coexpression patterns carry rich information regarding enormously complex brain structures and functions. Characterization of these patterns in an unbiased, integrated, and anatomically comprehensive manner will illuminate the higher-order transcriptome organization and offer genetic foundations of functional circuitry. Here using dictionary learning and sparse coding, we derived coexpression networks from the space-resolved anatomical comprehensive in situ hybridization data from Allen Mouse Brain Atlas dataset. The key idea is that if two genes use the same dictionary to represent their original signals, then their gene expressions must share similar patterns, thereby considering them as "coexpressed." For each network, we have simultaneous knowledge of spatial distributions, the genes in the network and the extent a particular gene conforms to the coexpression pattern. Gene ontologies and the comparisons with published gene lists reveal biologically identified coexpression networks, some of which correspond to major cell types, biological pathways, and/or anatomical regions.

Machine Learning and Computer Vision System for Phenotype Data Acquisition and Analysis in Plants.

PubMed

Navarro, Pedro J; Pérez, Fernando; Weiss, Julia; Egea-Cortines, Marcos

2016-05-05

Phenomics is a technology-driven approach with promising future to obtain unbiased data of biological systems. Image acquisition is relatively simple. However data handling and analysis are not as developed compared to the sampling capacities. We present a system based on machine learning (ML) algorithms and computer vision intended to solve the automatic phenotype data analysis in plant material. We developed a growth-chamber able to accommodate species of various sizes. Night image acquisition requires near infrared lightning. For the ML process, we tested three different algorithms: k-nearest neighbour (kNN), Naive Bayes Classifier (NBC), and Support Vector Machine. Each ML algorithm was executed with different kernel functions and they were trained with raw data and two types of data normalisation. Different metrics were computed to determine the optimal configuration of the machine learning algorithms. We obtained a performance of 99.31% in kNN for RGB images and a 99.34% in SVM for NIR. Our results show that ML techniques can speed up phenomic data analysis. Furthermore, both RGB and NIR images can be segmented successfully but may require different ML algorithms for segmentation.

Transfer of location-specific control to untrained locations.

PubMed

Weidler, Blaire J; Bugg, Julie M

2016-11-01

Recent research highlights a seemingly flexible and automatic form of cognitive control that is triggered by potent contextual cues, as exemplified by the location-specific proportion congruence effect--reduced compatibility effects in locations associated with a high as compared to low likelihood of conflict. We investigated just how flexible location-specific control is by examining whether novel locations effectively cue control for congruency-unbiased stimuli. In two experiments, biased (mostly compatible or mostly incompatible) training stimuli appeared in distinct locations. During a final block, unbiased (50% compatible) stimuli appeared in novel untrained locations spatially linked to biased locations. The flanker compatibly effect was reduced for unbiased stimuli in novel locations linked to a mostly incompatible compared to a mostly compatible location, indicating transfer. Transfer was observed when stimuli appeared along a linear function (Experiment 1) or in rings of a bullseye (Experiment 2). The novel transfer effects imply that location-specific control is more flexible than previously reported and further counter the complex stimulus-response learning account of location-specific proportion congruence effects. We propose that the representation and retrieval of control settings in untrained locations may depend on environmental support and the presentation of stimuli in novel locations that fall within the same categories of space as trained locations.

Reinforcement Learning Models and Their Neural Correlates: An Activation Likelihood Estimation Meta-Analysis

PubMed Central

Kumar, Poornima; Eickhoff, Simon B.; Dombrovski, Alexandre Y.

2015-01-01

Reinforcement learning describes motivated behavior in terms of two abstract signals. The representation of discrepancies between expected and actual rewards/punishments – prediction error – is thought to update the expected value of actions and predictive stimuli. Electrophysiological and lesion studies suggest that mesostriatal prediction error signals control behavior through synaptic modification of cortico-striato-thalamic networks. Signals in the ventromedial prefrontal and orbitofrontal cortex are implicated in representing expected value. To obtain unbiased maps of these representations in the human brain, we performed a meta-analysis of functional magnetic resonance imaging studies that employed algorithmic reinforcement learning models, across a variety of experimental paradigms. We found that the ventral striatum (medial and lateral) and midbrain/thalamus represented reward prediction errors, consistent with animal studies. Prediction error signals were also seen in the frontal operculum/insula, particularly for social rewards. In Pavlovian studies, striatal prediction error signals extended into the amygdala, while instrumental tasks engaged the caudate. Prediction error maps were sensitive to the model-fitting procedure (fixed or individually-estimated) and to the extent of spatial smoothing. A correlate of expected value was found in a posterior region of the ventromedial prefrontal cortex, caudal and medial to the orbitofrontal regions identified in animal studies. These findings highlight a reproducible motif of reinforcement learning in the cortico-striatal loops and identify methodological dimensions that may influence the reproducibility of activation patterns across studies. PMID:25665667

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers.

PubMed

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-12-12

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice.

Systematic assessment of cervical cancer initiation and progression uncovers genetic panels for deep learning-based early diagnosis and proposes novel diagnostic and prognostic biomarkers

PubMed Central

Long, Nguyen Phuoc; Jung, Kyung Hee; Yoon, Sang Jun; Anh, Nguyen Hoang; Nghi, Tran Diem; Kang, Yun Pyo; Yan, Hong Hua; Min, Jung Eun; Hong, Soon-Sun; Kwon, Sung Won

2017-01-01

Although many outstanding achievements in the management of cervical cancer (CxCa) have obtained, it still imposes a major burden which has prompted scientists to discover and validate new CxCa biomarkers to improve the diagnostic and prognostic assessment of CxCa. In this study, eight different gene expression data sets containing 202 cancer, 115 cervical intraepithelial neoplasia (CIN), and 105 normal samples were utilized for an integrative systems biology assessment in a multi-stage carcinogenesis manner. Deep learning-based diagnostic models were established based on the genetic panels of intrinsic genes of cervical carcinogenesis as well as on the unbiased variable selection approach. Survival analysis was also conducted to explore the potential biomarker candidates for prognostic assessment. Our results showed that cell cycle, RNA transport, mRNA surveillance, and one carbon pool by folate were the key regulatory mechanisms involved in the initiation, progression, and metastasis of CxCa. Various genetic panels combined with machine learning algorithms successfully differentiated CxCa from CIN and normalcy in cross-study normalized data sets. In particular, the 168-gene deep learning model for the differentiation of cancer from normalcy achieved an externally validated accuracy of 97.96% (99.01% sensitivity and 95.65% specificity). Survival analysis revealed that ZNF281 and EPHB6 were the two most promising prognostic genetic markers for CxCa among others. Our findings open new opportunities to enhance current understanding of the characteristics of CxCa pathobiology. In addition, the combination of transcriptomics-based signatures and deep learning classification may become an important approach to improve CxCa diagnosis and management in clinical practice. PMID:29312619

Implementation of a Comprehensive Curriculum in Personal Finance for Medical Fellows

PubMed Central

Bar-Or, Yuval D; Fessler, Henry E; Desai, Dipan A

2018-01-01

Introduction: Many residents and fellows complete graduate medical education having received minimal unbiased financial planning guidance. This places them at risk of making ill-informed financial decisions, which may lead to significant harm to them and their families. Therefore, we sought to provide fellows with comprehensive unbiased financial education and empower them to make timely, constructive financial decisions. Methods: A self-selected cohort of cardiovascular disease, pulmonary and critical care, and infectious disease fellows (n = 18) at a single institution attended a live, eight-hour interactive course on personal finance. The course consisted of four two-hour sessions delivered over four weeks, facilitated by an unbiased business school faculty member with expertise in personal finance. Prior to the course, all participants completed a demographic survey. After course completion, participants were offered an exit survey evaluating the course, which also asked respondents for any tangible financial decisions made as a result of the course learning.  Results: Participants included 12 women and six men, with a mean age of 33 and varying amounts of debt and financial assets. Twelve respondents completed the exit survey, and all “Strongly Agreed” that courses on financial literacy are important for trainees. In addition, 11 reported that the course helped them make important financial decisions, providing 21 examples. Conclusions: Fellows derive a significant benefit from objective financial literacy education. Graduate medical education programs should offer comprehensive financial literacy education to all graduating trainees, and that education should be provided by an unbiased expert who has no incentive to sell financial products and services. PMID:29515942

Implementation of a Comprehensive Curriculum in Personal Finance for Medical Fellows.

PubMed

Bar-Or, Yuval D; Fessler, Henry E; Desai, Dipan A; Zakaria, Sammy

2018-01-01

Many residents and fellows complete graduate medical education having received minimal unbiased financial planning guidance. This places them at risk of making ill-informed financial decisions, which may lead to significant harm to them and their families. Therefore, we sought to provide fellows with comprehensive unbiased financial education and empower them to make timely, constructive financial decisions. A self-selected cohort of cardiovascular disease, pulmonary and critical care, and infectious disease fellows (n = 18) at a single institution attended a live, eight-hour interactive course on personal finance. The course consisted of four two-hour sessions delivered over four weeks, facilitated by an unbiased business school faculty member with expertise in personal finance. Prior to the course, all participants completed a demographic survey. After course completion, participants were offered an exit survey evaluating the course, which also asked respondents for any tangible financial decisions made as a result of the course learning.  Results: Participants included 12 women and six men, with a mean age of 33 and varying amounts of debt and financial assets. Twelve respondents completed the exit survey, and all "Strongly Agreed" that courses on financial literacy are important for trainees. In addition, 11 reported that the course helped them make important financial decisions, providing 21 examples. Fellows derive a significant benefit from objective financial literacy education. Graduate medical education programs should offer comprehensive financial literacy education to all graduating trainees, and that education should be provided by an unbiased expert who has no incentive to sell financial products and services.

The spacing effect in immediate and delayed free recall.

PubMed

Godbole, Namrata R; Delaney, Peter F; Verkoeijen, Peter P J L

2014-01-01

Spacing repetitions improves learning relative to massing repetitions (the spacing effect). While most studies have examined the spacing effect at short retention intervals, there are contradictory claims about its fate at a delay. Certain empirical findings suggest that the spacing effect persists at a delay. However, a recent theoretical account proposes that in free recall the spacing effect should disappear at a delay. The few studies that have examined the spacing effect at a delay are sub-optimally designed, preventing an unbiased conclusion. The current study used incidental learning and controlled recency and encoding strategy in order to examine the effect of delay on the recall of spaced items within a free recall paradigm. The results demonstrated that the spacing effect persists after a delay. The results point to an important dissociation between intentional forgetting and context-change designs (which produce more forgetting of spaced than massed items) and the passage of time (which produces similar forgetting of spaced and massed items).

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis.

PubMed

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one.

Dual Systems for Spatial Updating in Immediate and Retrieved Environments: Evidence from Bias Analysis

PubMed Central

Liu, Chuanjun; Xiao, Chengli

2018-01-01

The spatial updating and memory systems are employed during updating in both the immediate and retrieved environments. However, these dual systems seem to work differently, as the difference of pointing latency and absolute error between the two systems vary across environments. To verify this issue, the present study employed the bias analysis of signed errors based on the hypothesis that the transformed representation will bias toward the original one. Participants learned a spatial layout and then either stayed in the learning location or were transferred to a neighboring room directly or after being disoriented. After that, they performed spatial judgments from perspectives aligned with the learning direction, aligned with the direction they faced during the test, or a novel direction misaligned with the two above-mentioned directions. The patterns of signed error bias were consistent across environments. Responses for memory aligned perspectives were unbiased, whereas responses for sensorimotor aligned perspectives were biased away from the memory aligned perspective, and responses for misaligned perspectives were biased toward sensorimotor aligned perspectives. These findings indicate that the spatial updating system is consistently independent of the spatial memory system regardless of the environments, but the updating system becomes less accessible as the environment changes from immediate to a retrieved one. PMID:29467698

Familial Sotos syndrome (cerebral gigantism): craniofacial and psychological characteristics.

PubMed

Bale, A E; Drum, M A; Parry, D M; Mulvihill, J J

1985-04-01

Most reported cases of Sotos syndrome are sporadic, but autosomal dominant and recessive inheritance patterns have been suggested. Ascertainment of a two-generation family through a 7-year-old proposita with a learning disability allowed the relatively unbiased study of two affected relatives. Developmental delay was not pronounced in the patient's mother or sister; craniofacial characteristics at variance with the characteristic description included acrocephaly and maxillary prominence. Steepness of the anterior cranial base angle and protrusion of the middle and lower face, shown in all three patients by cephalometric radiographs, deserve further evaluation as diagnostic criteria.

Interpreting linear support vector machine models with heat map molecule coloring

PubMed Central

2011-01-01

Background Model-based virtual screening plays an important role in the early drug discovery stage. The outcomes of high-throughput screenings are a valuable source for machine learning algorithms to infer such models. Besides a strong performance, the interpretability of a machine learning model is a desired property to guide the optimization of a compound in later drug discovery stages. Linear support vector machines showed to have a convincing performance on large-scale data sets. The goal of this study is to present a heat map molecule coloring technique to interpret linear support vector machine models. Based on the weights of a linear model, the visualization approach colors each atom and bond of a compound according to its importance for activity. Results We evaluated our approach on a toxicity data set, a chromosome aberration data set, and the maximum unbiased validation data sets. The experiments show that our method sensibly visualizes structure-property and structure-activity relationships of a linear support vector machine model. The coloring of ligands in the binding pocket of several crystal structures of a maximum unbiased validation data set target indicates that our approach assists to determine the correct ligand orientation in the binding pocket. Additionally, the heat map coloring enables the identification of substructures important for the binding of an inhibitor. Conclusions In combination with heat map coloring, linear support vector machine models can help to guide the modification of a compound in later stages of drug discovery. Particularly substructures identified as important by our method might be a starting point for optimization of a lead compound. The heat map coloring should be considered as complementary to structure based modeling approaches. As such, it helps to get a better understanding of the binding mode of an inhibitor. PMID:21439031

Objective assessment of gynecologic laparoscopic skills using the LapSimGyn virtual reality simulator.

PubMed

Larsen, C R; Grantcharov, T; Aggarwal, R; Tully, A; Sørensen, J L; Dalsgaard, T; Ottesen, B

2006-09-01

Safe realistic training and unbiased quantitative assessment of technical skills are required for laparoscopy. Virtual reality (VR) simulators may be useful tools for training and assessing basic and advanced surgical skills and procedures. This study aimed to investigate the construct validity of the LapSimGyn VR simulator, and to determine the learning curves of gynecologists with different levels of experience. For this study, 32 gynecologic trainees and consultants (juniors or seniors) were allocated into three groups: novices (0 advanced laparoscopic procedures), intermediate level (>20 and <60 procedures), and experts (>100 procedures). All performed 10 sets of simulations consisting of three basic skill tasks and an ectopic pregnancy program. The simulations were carried out on 3 days within a maximum period of 2 weeks. Assessment of skills was based on time, economy of movement, and error parameters measured by the simulator. The data showed that expert gynecologists performed significantly and consistently better than intermediate and novice gynecologists. The learning curves differed significantly between the groups, showing that experts start at a higher level and more rapidly reach the plateau of their learning curve than do intermediate and novice groups of surgeons. The LapSimGyn VR simulator package demonstrates construct validity on both the basic skills module and the procedural gynecologic module for ectopic pregnancy. Learning curves can be obtained, but to reach the maximum performance for the more complex tasks, 10 repetitions do not seem sufficient at the given task level and settings. LapSimGyn also seems to be flexible and widely accepted by the users.

Statistical and Machine Learning forecasting methods: Concerns and ways forward

PubMed Central

Makridakis, Spyros; Assimakopoulos, Vassilios

2018-01-01

Machine Learning (ML) methods have been proposed in the academic literature as alternatives to statistical ones for time series forecasting. Yet, scant evidence is available about their relative performance in terms of accuracy and computational requirements. The purpose of this paper is to evaluate such performance across multiple forecasting horizons using a large subset of 1045 monthly time series used in the M3 Competition. After comparing the post-sample accuracy of popular ML methods with that of eight traditional statistical ones, we found that the former are dominated across both accuracy measures used and for all forecasting horizons examined. Moreover, we observed that their computational requirements are considerably greater than those of statistical methods. The paper discusses the results, explains why the accuracy of ML models is below that of statistical ones and proposes some possible ways forward. The empirical results found in our research stress the need for objective and unbiased ways to test the performance of forecasting methods that can be achieved through sizable and open competitions allowing meaningful comparisons and definite conclusions. PMID:29584784

Evaluation and construction of diagnostic criteria for inclusion body myositis

PubMed Central

Mammen, Andrew L.; Amato, Anthony A.; Weiss, Michael D.; Needham, Merrilee

2014-01-01

Objective: To use patient data to evaluate and construct diagnostic criteria for inclusion body myositis (IBM), a progressive disease of skeletal muscle. Methods: The literature was reviewed to identify all previously proposed IBM diagnostic criteria. These criteria were applied through medical records review to 200 patients diagnosed as having IBM and 171 patients diagnosed as having a muscle disease other than IBM by neuromuscular specialists at 2 institutions, and to a validating set of 66 additional patients with IBM from 2 other institutions. Machine learning techniques were used for unbiased construction of diagnostic criteria. Results: Twenty-four previously proposed IBM diagnostic categories were identified. Twelve categories all performed with high (≥97%) specificity but varied substantially in their sensitivities (11%–84%). The best performing category was European Neuromuscular Centre 2013 probable (sensitivity of 84%). Specialized pathologic features and newly introduced strength criteria (comparative knee extension/hip flexion strength) performed poorly. Unbiased data-directed analysis of 20 features in 371 patients resulted in construction of higher-performing data-derived diagnostic criteria (90% sensitivity and 96% specificity). Conclusions: Published expert consensus–derived IBM diagnostic categories have uniformly high specificity but wide-ranging sensitivities. High-performing IBM diagnostic category criteria can be developed directly from principled unbiased analysis of patient data. Classification of evidence: This study provides Class II evidence that published expert consensus–derived IBM diagnostic categories accurately distinguish IBM from other muscle disease with high specificity but wide-ranging sensitivities. PMID:24975859

Deep neural networks for modeling visual perceptual learning.

PubMed

Wenliang, Li; Seitz, Aaron R

2018-05-23

Understanding visual perceptual learning (VPL) has become increasingly more challenging as new phenomena are discovered with novel stimuli and training paradigms. While existing models aid our knowledge of critical aspects of VPL, the connections shown by these models between behavioral learning and plasticity across different brain areas are typically superficial. Most models explain VPL as readout from simple perceptual representations to decision areas and are not easily adaptable to explain new findings. Here, we show that a well-known instance of deep neural network (DNN), while not designed specifically for VPL, provides a computational model of VPL with enough complexity to be studied at many levels of analyses. After learning a Gabor orientation discrimination task, the DNN model reproduced key behavioral results, including increasing specificity with higher task precision, and also suggested that learning precise discriminations could asymmetrically transfer to coarse discriminations when the stimulus conditions varied. In line with the behavioral findings, the distribution of plasticity moved towards lower layers when task precision increased, and this distribution was also modulated by tasks with different stimulus types. Furthermore, learning in the network units demonstrated close resemblance to extant electrophysiological recordings in monkey visual areas. Altogether, the DNN fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. Although the comparisons were mostly qualitative, the DNN provides a new method of studying VPL and can serve as a testbed for theories and assist in generating predictions for physiological investigations. SIGNIFICANCE STATEMENT Visual perceptual learning (VPL) has been found to cause changes at multiple stages of the visual hierarchy. We found that training a deep neural network (DNN) on an orientation discrimination task produced similar behavioral and physiological patterns found in human and monkey experiments. Unlike existing VPL models, the DNN was pre-trained on natural images to reach high performance in object recognition but was not designed specifically for VPL, and yet it fulfilled predictions of existing theories regarding specificity and plasticity, and reproduced findings of tuning changes in neurons of the primate visual areas. When used with care, this unbiased and deep-hierarchical model can provide new ways of studying VPL from behavior to physiology. Copyright © 2018 the authors.

The Decay of Motor Memories Is Independent of Context Change Detection

PubMed Central

Brennan, Andrew E.; Smith, Maurice A.

2015-01-01

When the error signals that guide human motor learning are withheld following training, recently-learned motor memories systematically regress toward untrained performance. It has previously been hypothesized that this regression results from an intrinsic volatility in these memories, resulting in an inevitable decay in the absence of ongoing error signals. However, a recently-proposed alternative posits that even recently-acquired motor memories are intrinsically stable, decaying only if a change in context is detected. This new theory, the context-dependent decay hypothesis, makes two key predictions: (1) after error signals are withheld, decay onset should be systematically delayed until the context change is detected; and (2) manipulations that impair detection by masking context changes should result in prolonged delays in decay onset and reduced decay amplitude at any given time. Here we examine the decay of motor adaptation following the learning of novel environmental dynamics in order to carefully evaluate this hypothesis. To account for potential issues in previous work that supported the context-dependent decay hypothesis, we measured decay using a balanced and baseline-referenced experimental design that allowed for direct comparisons between analogous masked and unmasked context changes. Using both an unbiased variant of the previous decay onset analysis and a novel highly-powered group-level version of this analysis, we found no evidence for systematically delayed decay onset nor for the masked context change affecting decay amplitude or its onset time. We further show how previous estimates of decay onset latency can be substantially biased in the presence of noise, and even more so with correlated noise, explaining the discrepancy between the previous results and our findings. Our results suggest that the decay of motor memories is an intrinsic feature of error-based learning that does not depend on context change detection. PMID:26111244

Learning Probabilities From Random Observables in High Dimensions: The Maximum Entropy Distribution and Others

NASA Astrophysics Data System (ADS)

Obuchi, Tomoyuki; Cocco, Simona; Monasson, Rémi

2015-11-01

We consider the problem of learning a target probability distribution over a set of N binary variables from the knowledge of the expectation values (with this target distribution) of M observables, drawn uniformly at random. The space of all probability distributions compatible with these M expectation values within some fixed accuracy, called version space, is studied. We introduce a biased measure over the version space, which gives a boost increasing exponentially with the entropy of the distributions and with an arbitrary inverse `temperature' Γ . The choice of Γ allows us to interpolate smoothly between the unbiased measure over all distributions in the version space (Γ =0) and the pointwise measure concentrated at the maximum entropy distribution (Γ → ∞ ). Using the replica method we compute the volume of the version space and other quantities of interest, such as the distance R between the target distribution and the center-of-mass distribution over the version space, as functions of α =(log M)/N and Γ for large N. Phase transitions at critical values of α are found, corresponding to qualitative improvements in the learning of the target distribution and to the decrease of the distance R. However, for fixed α the distance R does not vary with Γ which means that the maximum entropy distribution is not closer to the target distribution than any other distribution compatible with the observable values. Our results are confirmed by Monte Carlo sampling of the version space for small system sizes (N≤ 10).

A Deep Learning Framework for Robust and Accurate Prediction of ncRNA-Protein Interactions Using Evolutionary Information.

PubMed

Yi, Hai-Cheng; You, Zhu-Hong; Huang, De-Shuang; Li, Xiao; Jiang, Tong-Hai; Li, Li-Ping

2018-06-01

The interactions between non-coding RNAs (ncRNAs) and proteins play an important role in many biological processes, and their biological functions are primarily achieved by binding with a variety of proteins. High-throughput biological techniques are used to identify protein molecules bound with specific ncRNA, but they are usually expensive and time consuming. Deep learning provides a powerful solution to computationally predict RNA-protein interactions. In this work, we propose the RPI-SAN model by using the deep-learning stacked auto-encoder network to mine the hidden high-level features from RNA and protein sequences and feed them into a random forest (RF) model to predict ncRNA binding proteins. Stacked assembling is further used to improve the accuracy of the proposed method. Four benchmark datasets, including RPI2241, RPI488, RPI1807, and NPInter v2.0, were employed for the unbiased evaluation of five established prediction tools: RPI-Pred, IPMiner, RPISeq-RF, lncPro, and RPI-SAN. The experimental results show that our RPI-SAN model achieves much better performance than other methods, with accuracies of 90.77%, 89.7%, 96.1%, and 99.33%, respectively. It is anticipated that RPI-SAN can be used as an effective computational tool for future biomedical researches and can accurately predict the potential ncRNA-protein interacted pairs, which provides reliable guidance for biological research. Copyright © 2018 The Author(s). Published by Elsevier Inc. All rights reserved.

Assessing predation risk: optimal behaviour and rules of thumb.

PubMed

Welton, Nicky J; McNamara, John M; Houston, Alasdair I

2003-12-01

We look at a simple model in which an animal makes behavioural decisions over time in an environment in which all parameters are known to the animal except predation risk. In the model there is a trade-off between gaining information about predation risk and anti-predator behaviour. All predator attacks lead to death for the prey, so that the prey learns about predation risk by virtue of the fact that it is still alive. We show that it is not usually optimal to behave as if the current unbiased estimate of the predation risk is its true value. We consider two different ways to model reproduction; in the first scenario the animal reproduces throughout its life until it dies, and in the second scenario expected reproductive success depends on the level of energy reserves the animal has gained by some point in time. For both of these scenarios we find results on the form of the optimal strategy and give numerical examples which compare optimal behaviour with behaviour under simple rules of thumb. The numerical examples suggest that the value of the optimal strategy over the rules of thumb is greatest when there is little current information about predation risk, learning is not too costly in terms of predation, and it is energetically advantageous to learn about predation. We find that for the model and parameters investigated, a very simple rule of thumb such as 'use the best constant control' performs well.

Melioration as rational choice: sequential decision making in uncertain environments.

PubMed

Sims, Chris R; Neth, Hansjörg; Jacobs, Robert A; Gray, Wayne D

2013-01-01

Melioration-defined as choosing a lesser, local gain over a greater longer term gain-is a behavioral tendency that people and pigeons share. As such, the empirical occurrence of meliorating behavior has frequently been interpreted as evidence that the mechanisms of human choice violate the norms of economic rationality. In some environments, the relationship between actions and outcomes is known. In this case, the rationality of choice behavior can be evaluated in terms of how successfully it maximizes utility given knowledge of the environmental contingencies. In most complex environments, however, the relationship between actions and future outcomes is uncertain and must be learned from experience. When the difficulty of this learning challenge is taken into account, it is not evident that melioration represents suboptimal choice behavior. In the present article, we examine human performance in a sequential decision-making experiment that is known to induce meliorating behavior. In keeping with previous results using this paradigm, we find that the majority of participants in the experiment fail to adopt the optimal decision strategy and instead demonstrate a significant bias toward melioration. To explore the origins of this behavior, we develop a rational analysis (Anderson, 1990) of the learning problem facing individuals in uncertain decision environments. Our analysis demonstrates that an unbiased learner would adopt melioration as the optimal response strategy for maximizing long-term gain. We suggest that many documented cases of melioration can be reinterpreted not as irrational choice but rather as globally optimal choice under uncertainty.

Short-arc measurement and fitting based on the bidirectional prediction of observed data

NASA Astrophysics Data System (ADS)

Fei, Zhigen; Xu, Xiaojie; Georgiadis, Anthimos

2016-02-01

To measure a short arc is a notoriously difficult problem. In this study, the bidirectional prediction method based on the Radial Basis Function Neural Network (RBFNN) to the observed data distributed along a short arc is proposed to increase the corresponding arc length, and thus improve its fitting accuracy. Firstly, the rationality of regarding observed data as a time series is discussed in accordance with the definition of a time series. Secondly, the RBFNN is constructed to predict the observed data where the interpolation method is used for enlarging the size of training examples in order to improve the learning accuracy of the RBFNN’s parameters. Finally, in the numerical simulation section, we focus on simulating how the size of the training sample and noise level influence the learning error and prediction error of the built RBFNN. Typically, the observed data coming from a 5{}^\\circ short arc are used to evaluate the performance of the Hyper method known as the ‘unbiased fitting method of circle’ with a different noise level before and after prediction. A number of simulation experiments reveal that the fitting stability and accuracy of the Hyper method after prediction are far superior to the ones before prediction.

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

PubMed

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

2016-01-01

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

Tongue Images Classification Based on Constrained High Dispersal Network.

PubMed

Meng, Dan; Cao, Guitao; Duan, Ye; Zhu, Minghua; Tu, Liping; Xu, Dong; Xu, Jiatuo

2017-01-01

Computer aided tongue diagnosis has a great potential to play important roles in traditional Chinese medicine (TCM). However, the majority of the existing tongue image analyses and classification methods are based on the low-level features, which may not provide a holistic view of the tongue. Inspired by deep convolutional neural network (CNN), we propose a novel feature extraction framework called constrained high dispersal neural networks (CHDNet) to extract unbiased features and reduce human labor for tongue diagnosis in TCM. Previous CNN models have mostly focused on learning convolutional filters and adapting weights between them, but these models have two major issues: redundancy and insufficient capability in handling unbalanced sample distribution. We introduce high dispersal and local response normalization operation to address the issue of redundancy. We also add multiscale feature analysis to avoid the problem of sensitivity to deformation. Our proposed CHDNet learns high-level features and provides more classification information during training time, which may result in higher accuracy when predicting testing samples. We tested the proposed method on a set of 267 gastritis patients and a control group of 48 healthy volunteers. Test results show that CHDNet is a promising method in tongue image classification for the TCM study.

Quantum Inference on Bayesian Networks

NASA Astrophysics Data System (ADS)

Yoder, Theodore; Low, Guang Hao; Chuang, Isaac

2014-03-01

Because quantum physics is naturally probabilistic, it seems reasonable to expect physical systems to describe probabilities and their evolution in a natural fashion. Here, we use quantum computation to speedup sampling from a graphical probability model, the Bayesian network. A specialization of this sampling problem is approximate Bayesian inference, where the distribution on query variables is sampled given the values e of evidence variables. Inference is a key part of modern machine learning and artificial intelligence tasks, but is known to be NP-hard. Classically, a single unbiased sample is obtained from a Bayesian network on n variables with at most m parents per node in time (nmP(e) - 1 / 2) , depending critically on P(e) , the probability the evidence might occur in the first place. However, by implementing a quantum version of rejection sampling, we obtain a square-root speedup, taking (n2m P(e) -1/2) time per sample. The speedup is the result of amplitude amplification, which is proving to be broadly applicable in sampling and machine learning tasks. In particular, we provide an explicit and efficient circuit construction that implements the algorithm without the need for oracle access.

Supervised and Unsupervised Learning Technology in the Study of Rodent Behavior

PubMed Central

Gris, Katsiaryna V.; Coutu, Jean-Philippe; Gris, Denis

2017-01-01

Quantifying behavior is a challenge for scientists studying neuroscience, ethology, psychology, pathology, etc. Until now, behavior was mostly considered as qualitative descriptions of postures or labor intensive counting of bouts of individual movements. Many prominent behavioral scientists conducted studies describing postures of mice and rats, depicting step by step eating, grooming, courting, and other behaviors. Automated video assessment technologies permit scientists to quantify daily behavioral patterns/routines, social interactions, and postural changes in an unbiased manner. Here, we extensively reviewed published research on the topic of the structural blocks of behavior and proposed a structure of behavior based on the latest publications. We discuss the importance of defining a clear structure of behavior to allow professionals to write viable algorithms. We presented a discussion of technologies that are used in automated video assessment of behavior in mice and rats. We considered advantages and limitations of supervised and unsupervised learning. We presented the latest scientific discoveries that were made using automated video assessment. In conclusion, we proposed that the automated quantitative approach to evaluating animal behavior is the future of understanding the effect of brain signaling, pathologies, genetic content, and environment on behavior. PMID:28804452

Deciphering Neural Codes of Memory during Sleep

PubMed Central

Chen, Zhe; Wilson, Matthew A.

2017-01-01

Memories of experiences are stored in the cerebral cortex. Sleep is critical for consolidating hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms on memory consolidation, and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here, we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches for analyzing sleep-associated neural codes (SANC). We focus on two analysis paradigms for sleep-associated memory, and propose a new unsupervised learning framework (“memory first, meaning later”) for unbiased assessment of SANC. PMID:28390699

Online probabilistic learning with an ensemble of forecasts

NASA Astrophysics Data System (ADS)

Thorey, Jean; Mallet, Vivien; Chaussin, Christophe

2016-04-01

Our objective is to produce a calibrated weighted ensemble to forecast a univariate time series. In addition to a meteorological ensemble of forecasts, we rely on observations or analyses of the target variable. The celebrated Continuous Ranked Probability Score (CRPS) is used to evaluate the probabilistic forecasts. However applying the CRPS on weighted empirical distribution functions (deriving from the weighted ensemble) may introduce a bias because of which minimizing the CRPS does not produce the optimal weights. Thus we propose an unbiased version of the CRPS which relies on clusters of members and is strictly proper. We adapt online learning methods for the minimization of the CRPS. These methods generate the weights associated to the members in the forecasted empirical distribution function. The weights are updated before each forecast step using only past observations and forecasts. Our learning algorithms provide the theoretical guarantee that, in the long run, the CRPS of the weighted forecasts is at least as good as the CRPS of any weighted ensemble with weights constant in time. In particular, the performance of our forecast is better than that of any subset ensemble with uniform weights. A noteworthy advantage of our algorithm is that it does not require any assumption on the distributions of the observations and forecasts, both for the application and for the theoretical guarantee to hold. As application example on meteorological forecasts for photovoltaic production integration, we show that our algorithm generates a calibrated probabilistic forecast, with significant performance improvements on probabilistic diagnostic tools (the CRPS, the reliability diagram and the rank histogram).

Targeted estimation of nuisance parameters to obtain valid statistical inference.

PubMed

van der Laan, Mark J

2014-01-01

In order to obtain concrete results, we focus on estimation of the treatment specific mean, controlling for all measured baseline covariates, based on observing independent and identically distributed copies of a random variable consisting of baseline covariates, a subsequently assigned binary treatment, and a final outcome. The statistical model only assumes possible restrictions on the conditional distribution of treatment, given the covariates, the so-called propensity score. Estimators of the treatment specific mean involve estimation of the propensity score and/or estimation of the conditional mean of the outcome, given the treatment and covariates. In order to make these estimators asymptotically unbiased at any data distribution in the statistical model, it is essential to use data-adaptive estimators of these nuisance parameters such as ensemble learning, and specifically super-learning. Because such estimators involve optimal trade-off of bias and variance w.r.t. the infinite dimensional nuisance parameter itself, they result in a sub-optimal bias/variance trade-off for the resulting real-valued estimator of the estimand. We demonstrate that additional targeting of the estimators of these nuisance parameters guarantees that this bias for the estimand is second order and thereby allows us to prove theorems that establish asymptotic linearity of the estimator of the treatment specific mean under regularity conditions. These insights result in novel targeted minimum loss-based estimators (TMLEs) that use ensemble learning with additional targeted bias reduction to construct estimators of the nuisance parameters. In particular, we construct collaborative TMLEs (C-TMLEs) with known influence curve allowing for statistical inference, even though these C-TMLEs involve variable selection for the propensity score based on a criterion that measures how effective the resulting fit of the propensity score is in removing bias for the estimand. As a particular special case, we also demonstrate the required targeting of the propensity score for the inverse probability of treatment weighted estimator using super-learning to fit the propensity score.

Fortune Favours the Bold: An Agent-Based Model Reveals Adaptive Advantages of Overconfidence in War

PubMed Central

Johnson, Dominic D. P.; Weidmann, Nils B.; Cederman, Lars-Erik

2011-01-01

Overconfidence has long been considered a cause of war. Like other decision-making biases, overconfidence seems detrimental because it increases the frequency and costs of fighting. However, evolutionary biologists have proposed that overconfidence may also confer adaptive advantages: increasing ambition, resolve, persistence, bluffing opponents, and winning net payoffs from risky opportunities despite occasional failures. We report the results of an agent-based model of inter-state conflict, which allows us to evaluate the performance of different strategies in competition with each other. Counter-intuitively, we find that overconfident states predominate in the population at the expense of unbiased or underconfident states. Overconfident states win because: (1) they are more likely to accumulate resources from frequent attempts at conquest; (2) they are more likely to gang up on weak states, forcing victims to split their defences; and (3) when the decision threshold for attacking requires an overwhelming asymmetry of power, unbiased and underconfident states shirk many conflicts they are actually likely to win. These “adaptive advantages” of overconfidence may, via selection effects, learning, or evolved psychology, have spread and become entrenched among modern states, organizations and decision-makers. This would help to explain the frequent association of overconfidence and war, even if it no longer brings benefits today. PMID:21731627

Observations on the State of NASA's GN&C Engineering Discipline: Results of an Independent Non-Advocate Study

NASA Technical Reports Server (NTRS)

Pawlikowski, Gerald J.; Dennehy, Cornelius J.

2010-01-01

The NASA Technical Fellows periodically conduct State-of-the-Discipline assessments. The GN&C Technical Fellow contracted Harlan Brown & Company in 2007 and 2009 to conduct independent, third party studies to gain unbiased insight and understanding into the attitudes and beliefs of NASA's GN&C Community of Practice (CoP). The paper first outlines the background, objectives and methodology of the studies. The paper then summarizes key study results of the 2007 baseline study, as well as the 2009 update. The update was then used to track and monitor perceptions, identify performance trends, identify areas where further improvement needs to be made in NASA's GN&C discipline. It also generated feedback on the recently developed GN&C CoP online knowledge capture and learning site.

U-BIOPRED: evaluation of the value of a public-private partnership to industry.

PubMed

Riley, John H; Erpenbeck, Veit J; Matthews, J G; Holweg, C T J; Compton, C; Seibold, W; Higenbottam, T; Wagers, S S; Rowe, A; Myles, D

2018-06-21

Unbiased Biomarkers for the Prediction of Respiratory Disease Outcomes (U-BIOPRED) was initiated in the first year of the Innovative Medicines Initiative (IMI). It was an ambitious plan to tackle the understanding of asthma through an integration of clinical and multi-'omics approaches that necessitated the bringing together of industry, academic, and patient representatives because it was too large to be managed by any one of the partners in isolation. It was a novel experience for all concerned. In this review, we describe the main features of the U-BIOPRED experience from the industry perspective. We list some of the key advantages and learnings from the perspective of the authors, and also improvements that we feel could be made in future projects. Copyright © 2018 Elsevier Ltd. All rights reserved.

Prediction of Breeding Values for Dairy Cattle Using Artificial Neural Networks and Neuro-Fuzzy Systems

PubMed Central

Shahinfar, Saleh; Mehrabani-Yeganeh, Hassan; Lucas, Caro; Kalhor, Ahmad; Kazemian, Majid; Weigel, Kent A.

2012-01-01

Developing machine learning and soft computing techniques has provided many opportunities for researchers to establish new analytical methods in different areas of science. The objective of this study is to investigate the potential of two types of intelligent learning methods, artificial neural networks and neuro-fuzzy systems, in order to estimate breeding values (EBV) of Iranian dairy cattle. Initially, the breeding values of lactating Holstein cows for milk and fat yield were estimated using conventional best linear unbiased prediction (BLUP) with an animal model. Once that was established, a multilayer perceptron was used to build ANN to predict breeding values from the performance data of selection candidates. Subsequently, fuzzy logic was used to form an NFS, a hybrid intelligent system that was implemented via a local linear model tree algorithm. For milk yield the correlations between EBV and EBV predicted by the ANN and NFS were 0.92 and 0.93, respectively. Corresponding correlations for fat yield were 0.93 and 0.93, respectively. Correlations between multitrait predictions of EBVs for milk and fat yield when predicted simultaneously by ANN were 0.93 and 0.93, respectively, whereas corresponding correlations with reference EBV for multitrait NFS were 0.94 and 0.95, respectively, for milk and fat production. PMID:22991575

Cost-sensitive AdaBoost algorithm for ordinal regression based on extreme learning machine.

PubMed

Riccardi, Annalisa; Fernández-Navarro, Francisco; Carloni, Sante

2014-10-01

In this paper, the well known stagewise additive modeling using a multiclass exponential (SAMME) boosting algorithm is extended to address problems where there exists a natural order in the targets using a cost-sensitive approach. The proposed ensemble model uses an extreme learning machine (ELM) model as a base classifier (with the Gaussian kernel and the additional regularization parameter). The closed form of the derived weighted least squares problem is provided, and it is employed to estimate analytically the parameters connecting the hidden layer to the output layer at each iteration of the boosting algorithm. Compared to the state-of-the-art boosting algorithms, in particular those using ELM as base classifier, the suggested technique does not require the generation of a new training dataset at each iteration. The adoption of the weighted least squares formulation of the problem has been presented as an unbiased and alternative approach to the already existing ELM boosting techniques. Moreover, the addition of a cost model for weighting the patterns, according to the order of the targets, enables the classifier to tackle ordinal regression problems further. The proposed method has been validated by an experimental study by comparing it with already existing ensemble methods and ELM techniques for ordinal regression, showing competitive results.

Recognizing molecular patterns by machine learning: An agnostic structural definition of the hydrogen bond

DOE Office of Scientific and Technical Information (OSTI.GOV)

Gasparotto, Piero; Ceriotti, Michele, E-mail: michele.ceriotti@epfl.ch

The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding – a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogenmore » bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.« less

Recognizing molecular patterns by machine learning: an agnostic structural definition of the hydrogen bond.

PubMed

Gasparotto, Piero; Ceriotti, Michele

2014-11-07

The concept of chemical bonding can ultimately be seen as a rationalization of the recurring structural patterns observed in molecules and solids. Chemical intuition is nothing but the ability to recognize and predict such patterns, and how they transform into one another. Here, we discuss how to use a computer to identify atomic patterns automatically, so as to provide an algorithmic definition of a bond based solely on structural information. We concentrate in particular on hydrogen bonding--a central concept to our understanding of the physical chemistry of water, biological systems, and many technologically important materials. Since the hydrogen bond is a somewhat fuzzy entity that covers a broad range of energies and distances, many different criteria have been proposed and used over the years, based either on sophisticate electronic structure calculations followed by an energy decomposition analysis, or on somewhat arbitrary choices of a range of structural parameters that is deemed to correspond to a hydrogen-bonded configuration. We introduce here a definition that is univocal, unbiased, and adaptive, based on our machine-learning analysis of an atomistic simulation. The strategy we propose could be easily adapted to similar scenarios, where one has to recognize or classify structural patterns in a material or chemical compound.

Gene repressive mechanisms in the mouse brain involved in memory formation

PubMed Central

Yu, Nam-Kyung; Kaang, Bong-Kiun

2016-01-01

Gene regulation in the brain is essential for long-term plasticity and memory formation. Despite this established notion, the quantitative translational map in the brain during memory formation has not been reported. To systematically probe the changes in protein synthesis during memory formation, our recent study exploited ribosome profiling using the mouse hippocampal tissues at multiple time points after a learning event. Analysis of the resulting database revealed novel types of gene regulation after learning. First, the translation of a group of genes was rapidly suppressed without change in mRNA levels. At later time points, the expression of another group of genes was downregulated through reduction in mRNA levels. This reduction was predicted to be downstream of inhibition of ESR1 (Estrogen Receptor 1) signaling. Overexpressing Nrsn1, one of the genes whose translation was suppressed, or activating ESR1 by injecting an agonist interfered with memory formation, suggesting the functional importance of these findings. Moreover, the translation of genes encoding the translational machineries was found to be suppressed, among other genes in the mouse hippocampus. Together, this unbiased approach has revealed previously unidentified characteristics of gene regulation in the brain and highlighted the importance of repressive controls. [BMB Reports 2016; 49(4): 199-200] PMID:26949020

Gene repressive mechanisms in the mouse brain involved in memory formation.

PubMed

Yu, Nam-Kyung; Kaang, Bong-Kiun

2016-04-01

Gene regulation in the brain is essential for long-term plasticity and memory formation. Despite this established notion, the quantitative translational map in the brain during memory formation has not been reported. To systematically probe the changes in protein synthesis during memory formation, our recent study exploited ribosome profiling using the mouse hippocampal tissues at multiple time points after a learning event. Analysis of the resulting database revealed novel types of gene regulation after learning. First, the translation of a group of genes was rapidly suppressed without change in mRNA levels. At later time points, the expression of another group of genes was downregulated through reduction in mRNA levels. This reduction was predicted to be downstream of inhibition of ESR1 (Estrogen Receptor 1) signaling. Overexpressing Nrsn1, one of the genes whose translation was suppressed, or activating ESR1 by injecting an agonist interfered with memory formation, suggesting the functional importance of these findings. Moreover, the translation of genes encoding the translational machineries was found to be suppressed, among other genes in the mouse hippocampus. Together, this unbiased approach has revealed previously unidentified characteristics of gene regulation in the brain and highlighted the importance of repressive controls. [BMB Reports 2016; 49(4): 199-200].

A Comparison Study for DNA Motif Modeling on Protein Binding Microarray.

PubMed

Wong, Ka-Chun; Li, Yue; Peng, Chengbin; Wong, Hau-San

2016-01-01

Transcription factor binding sites (TFBSs) are relatively short (5-15 bp) and degenerate. Identifying them is a computationally challenging task. In particular, protein binding microarray (PBM) is a high-throughput platform that can measure the DNA binding preference of a protein in a comprehensive and unbiased manner; for instance, a typical PBM experiment can measure binding signal intensities of a protein to all possible DNA k-mers (k = 8∼10). Since proteins can often bind to DNA with different binding intensities, one of the major challenges is to build TFBS (also known as DNA motif) models which can fully capture the quantitative binding affinity data. To learn DNA motif models from the non-convex objective function landscape, several optimization methods are compared and applied to the PBM motif model building problem. In particular, representative methods from different optimization paradigms have been chosen for modeling performance comparison on hundreds of PBM datasets. The results suggest that the multimodal optimization methods are very effective for capturing the binding preference information from PBM data. In particular, we observe a general performance improvement if choosing di-nucleotide modeling over mono-nucleotide modeling. In addition, the models learned by the best-performing method are applied to two independent applications: PBM probe rotation testing and ChIP-Seq peak sequence prediction, demonstrating its biological applicability.

HUMAN DECISIONS AND MACHINE PREDICTIONS.

PubMed

Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

2018-02-01

Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior).

HUMAN DECISIONS AND MACHINE PREDICTIONS*

PubMed Central

Kleinberg, Jon; Lakkaraju, Himabindu; Leskovec, Jure; Ludwig, Jens; Mullainathan, Sendhil

2018-01-01

Can machine learning improve human decision making? Bail decisions provide a good test case. Millions of times each year, judges make jail-or-release decisions that hinge on a prediction of what a defendant would do if released. The concreteness of the prediction task combined with the volume of data available makes this a promising machine-learning application. Yet comparing the algorithm to judges proves complicated. First, the available data are generated by prior judge decisions. We only observe crime outcomes for released defendants, not for those judges detained. This makes it hard to evaluate counterfactual decision rules based on algorithmic predictions. Second, judges may have a broader set of preferences than the variable the algorithm predicts; for instance, judges may care specifically about violent crimes or about racial inequities. We deal with these problems using different econometric strategies, such as quasi-random assignment of cases to judges. Even accounting for these concerns, our results suggest potentially large welfare gains: one policy simulation shows crime reductions up to 24.7% with no change in jailing rates, or jailing rate reductions up to 41.9% with no increase in crime rates. Moreover, all categories of crime, including violent crimes, show reductions; and these gains can be achieved while simultaneously reducing racial disparities. These results suggest that while machine learning can be valuable, realizing this value requires integrating these tools into an economic framework: being clear about the link between predictions and decisions; specifying the scope of payoff functions; and constructing unbiased decision counterfactuals. JEL Codes: C10 (Econometric and statistical methods and methodology), C55 (Large datasets: Modeling and analysis), K40 (Legal procedure, the legal system, and illegal behavior) PMID:29755141

EMQIT: a machine learning approach for energy based PWM matrix quality improvement.

PubMed

Smolinska, Karolina; Pacholczyk, Marcin

2017-08-01

Transcription factor binding affinities to DNA play a key role for the gene regulation. Learning the specificity of the mechanisms of binding TFs to DNA is important both to experimentalists and theoreticians. With the development of high-throughput methods such as, e.g., ChiP-seq the need to provide unbiased models of binding events has been made apparent. We present EMQIT a modification to the approach introduced by Alamanova et al. and later implemented as 3DTF server. We observed that tuning of Boltzmann factor weights, used for conversion of calculated energies to nucleotide probabilities, has a significant impact on the quality of the associated PWM matrix. Consequently, we proposed to use receiver operator characteristics curves and the 10-fold cross-validation to learn best weights using experimentally verified data from TRANSFAC database. We applied our method to data available for various TFs. We verified the efficiency of detecting TF binding sites by the 3DTF matrices improved with our technique using experimental data from the TRANSFAC database. The comparison showed a significant similarity and comparable performance between the improved and the experimental matrices (TRANSFAC). Improved 3DTF matrices achieved significantly higher AUC values than the original 3DTF matrices (at least by 0.1) and, at the same time, detected notably more experimentally verified TFBSs. The resulting new improved PWM matrices for analyzed factors show similarity to TRANSFAC matrices. Matrices had comparable predictive capabilities. Moreover, improved PWMs achieve better results than matrices downloaded from 3DTF server. Presented approach is general and applicable to any energy-based matrices. EMQIT is available online at http://biosolvers.polsl.pl:3838/emqit . This article was reviewed by Oliviero Carugo, Marek Kimmel and István Simon.

Cannabinoid transmission in the prelimbic cortex bidirectionally controls opiate reward and aversion signaling through dissociable kappa versus μ-opiate receptor dependent mechanisms.

PubMed

Ahmad, Tasha; Lauzon, Nicole M; de Jaeger, Xavier; Laviolette, Steven R

2013-09-25

Cannabinoid, dopamine (DA), and opiate receptor pathways play integrative roles in emotional learning, associative memory, and sensory perception. Modulation of cannabinoid CB1 receptor transmission within the medial prefrontal cortex (mPFC) regulates the emotional valence of both rewarding and aversive experiences. Furthermore, CB1 receptor substrates functionally interact with opiate-related motivational processing circuits, particularly in the context of reward-related learning and memory. Considerable evidence demonstrates functional interactions between CB1 and DA signaling pathways during the processing of motivationally salient information. However, the role of mPFC CB1 receptor transmission in the modulation of behavioral opiate-reward processing is not currently known. Using an unbiased conditioned place preference paradigm with rats, we examined the role of intra-mPFC CB1 transmission during opiate reward learning. We report that activation or inhibition of CB1 transmission within the prelimbic cortical (PLC) division of the mPFC bidirectionally regulates the motivational valence of opiates; whereas CB1 activation switched morphine reward signaling into an aversive stimulus, blockade of CB1 transmission potentiated the rewarding properties of normally sub-reward threshold conditioning doses of morphine. Both of these effects were dependent upon DA transmission as systemic blockade of DAergic transmission prevented CB1-dependent modulation of morphine reward and aversion behaviors. We further report that CB1-mediated intra-PLC opiate motivational signaling is mediated through a μ-opiate receptor-dependent reward pathway, or a κ-opiate receptor-dependent aversion pathway, directly within the ventral tegmental area. Our results provide evidence for a novel CB1-mediated motivational valence switching mechanism within the PLC, controlling dissociable subcortical reward and aversion pathways.

Machine Learning-Based Classification of 38 Years of Spine-Related Literature Into 100 Research Topics.

PubMed

Sing, David C; Metz, Lionel N; Dudli, Stefan

2017-06-01

Retrospective review. To identify the top 100 spine research topics. Recent advances in "machine learning," or computers learning without explicit instructions, have yielded broad technological advances. Topic modeling algorithms can be applied to large volumes of text to discover quantifiable themes and trends. Abstracts were extracted from the National Library of Medicine PubMed database from five prominent peer-reviewed spine journals (European Spine Journal [ESJ], The Spine Journal [SpineJ], Spine, Journal of Spinal Disorders and Techniques [JSDT], Journal of Neurosurgery: Spine [JNS]). Each abstract was entered into a latent Dirichlet allocation model specified to discover 100 topics, resulting in each abstract being assigned a probability of belonging in a topic. Topics were named using the five most frequently appearing terms within that topic. Significance of increasing ("hot") or decreasing ("cold") topic popularity over time was evaluated with simple linear regression. From 1978 to 2015, 25,805 spine-related research articles were extracted and classified into 100 topics. Top two most published topics included "clinical, surgeons, guidelines, information, care" (n = 496 articles) and "pain, back, low, treatment, chronic" (424). Top two hot trends included "disc, cervical, replacement, level, arthroplasty" (+0.05%/yr, P < 0.001), and "minimally, invasive, approach, technique" (+0.05%/yr, P < 0.001). By journal, the most published topics were ESJ-"operative, surgery, postoperative, underwent, preoperative"; SpineJ-"clinical, surgeons, guidelines, information, care"; Spine-"pain, back, low, treatment, chronic"; JNS- "tumor, lesions, rare, present, diagnosis"; JSDT-"cervical, anterior, plate, fusion, ACDF." Topics discovered through latent Dirichlet allocation modeling represent unbiased meaningful themes relevant to spine care. Topic dynamics can provide historical context and direction for future research for aspiring investigators and trainees interested in spine careers. Please explore https://singdc.shinyapps.io/spinetopics. N A.

Academic consortium for the evaluation of computer-aided diagnosis (CADx) in mammography

NASA Astrophysics Data System (ADS)

Mun, Seong K.; Freedman, Matthew T.; Wu, Chris Y.; Lo, Shih-Chung B.; Floyd, Carey E., Jr.; Lo, Joseph Y.; Chan, Heang-Ping; Helvie, Mark A.; Petrick, Nicholas; Sahiner, Berkman; Wei, Datong; Chakraborty, Dev P.; Clarke, Laurence P.; Kallergi, Maria; Clark, Bob; Kim, Yongmin

1995-04-01

Computer aided diagnosis (CADx) is a promising technology for the detection of breast cancer in screening mammography. A number of different approaches have been developed for CADx research that have achieved significant levels of performance. Research teams now recognize the need for a careful and detailed evaluation study of approaches to accelerate the development of CADx, to make CADx more clinically relevant and to optimize the CADx algorithms based on unbiased evaluations. The results of such a comparative study may provide each of the participating teams with new insights into the optimization of their individual CADx algorithms. This consortium of experienced CADx researchers is working as a group to compare results of the algorithms and to optimize the performance of CADx algorithms by learning from each other. Each institution will be contributing an equal number of cases that will be collected under a standard protocol for case selection, truth determination, and data acquisition to establish a common and unbiased database for the evaluation study. An evaluation procedure for the comparison studies are being developed to analyze the results of individual algorithms for each of the test cases in the common database. Optimization of individual CADx algorithms can be made based on the comparison studies. The consortium effort is expected to accelerate the eventual clinical implementation of CADx algorithms at participating institutions.

From Molecules to Cells to Organisms: Understanding Health and Disease with Multidimensional Single-Cell Methods

NASA Astrophysics Data System (ADS)

Candia, Julián

2013-03-01

The multidimensional nature of many single-cell measurements (e.g. multiple markers measured simultaneously using Fluorescence-Activated Cell Sorting (FACS) technologies) offers unprecedented opportunities to unravel emergent phenomena that are governed by the cooperative action of multiple elements across different scales, from molecules and proteins to cells and organisms. We will discuss an integrated analysis framework to investigate multicolor FACS data from different perspectives: Singular Value Decomposition to achieve an effective dimensional reduction in the data representation, machine learning techniques to separate different patient classes and improve diagnosis, as well as a novel cell-similarity network analysis method to identify cell subpopulations in an unbiased manner. Besides FACS data, this framework is versatile: in this vein, we will demonstrate an application to the multidimensional single-cell shape analysis of healthy and prematurely aged cells.

Deciphering Neural Codes of Memory during Sleep.

PubMed

Chen, Zhe; Wilson, Matthew A

2017-05-01

Memories of experiences are stored in the cerebral cortex. Sleep is critical for the consolidation of hippocampal memory of wake experiences into the neocortex. Understanding representations of neural codes of hippocampal-neocortical networks during sleep would reveal important circuit mechanisms in memory consolidation and provide novel insights into memory and dreams. Although sleep-associated ensemble spike activity has been investigated, identifying the content of memory in sleep remains challenging. Here we revisit important experimental findings on sleep-associated memory (i.e., neural activity patterns in sleep that reflect memory processing) and review computational approaches to the analysis of sleep-associated neural codes (SANCs). We focus on two analysis paradigms for sleep-associated memory and propose a new unsupervised learning framework ('memory first, meaning later') for unbiased assessment of SANCs. Copyright © 2017 Elsevier Ltd. All rights reserved.

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli

PubMed Central

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

ABSTRACT A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells. PMID:26962703

Loss of the integral nuclear envelope protein SUN1 induces alteration of nucleoli.

PubMed

Matsumoto, Ayaka; Sakamoto, Chiyomi; Matsumori, Haruka; Katahira, Jun; Yasuda, Yoko; Yoshidome, Katsuhide; Tsujimoto, Masahiko; Goldberg, Ilya G; Matsuura, Nariaki; Nakao, Mitsuyoshi; Saitoh, Noriko; Hieda, Miki

2016-01-01

A supervised machine learning algorithm, which is qualified for image classification and analyzing similarities, is based on multiple discriminative morphological features that are automatically assembled during the learning processes. The algorithm is suitable for population-based analysis of images of biological materials that are generally complex and heterogeneous. Here we used the algorithm wndchrm to quantify the effects on nucleolar morphology of the loss of the components of nuclear envelope in a human mammary epithelial cell line. The linker of nucleoskeleton and cytoskeleton (LINC) complex, an assembly of nuclear envelope proteins comprising mainly members of the SUN and nesprin families, connects the nuclear lamina and cytoskeletal filaments. The components of the LINC complex are markedly deficient in breast cancer tissues. We found that a reduction in the levels of SUN1, SUN2, and lamin A/C led to significant changes in morphologies that were computationally classified using wndchrm with approximately 100% accuracy. In particular, depletion of SUN1 caused nucleolar hypertrophy and reduced rRNA synthesis. Further, wndchrm revealed a consistent negative correlation between SUN1 expression and the size of nucleoli in human breast cancer tissues. Our unbiased morphological quantitation strategies using wndchrm revealed an unexpected link between the components of the LINC complex and the morphologies of nucleoli that serves as an indicator of the malignant phenotype of breast cancer cells.

Utah Science Activities, Update 2010

USGS Publications Warehouse

,

2010-01-01

The U.S. Geological Survey (USGS), a bureau of the U.S. Department of the Interior, serves the Nation by providing reliable scientific information to describe and understand the Earth; minimize loss of life and property from natural disasters; manage water, biological, energy, and mineral resources; and enhance and protect our quality of life. The USGS has become a world leader in the natural sciences thanks to our scientific excellence and responsiveness to society's needs. This newsletter describes some of the current and recently completed USGS earth-science activities in Utah. As an unbiased, multi-disciplinary science organization that focuses on biology, geography, geology, and water, we are dedicated to the timely, relevant, and impartial study of the landscape, our natural resources, and the natural hazards that threaten us. Learn more about our goals and priorities for the coming decade in the USGS Science Strategy at http://www.usgs.gov/science_strategy/ .

A SVM-based method for sentiment analysis in Persian language

NASA Astrophysics Data System (ADS)

Hajmohammadi, Mohammad Sadegh; Ibrahim, Roliana

2013-03-01

Persian language is the official language of Iran, Tajikistan and Afghanistan. Local online users often represent their opinions and experiences on the web with written Persian. Although the information in those reviews is valuable to potential consumers and sellers, the huge amount of web reviews make it difficult to give an unbiased evaluation to a product. In this paper, standard machine learning techniques SVM and naive Bayes are incorporated into the domain of online Persian Movie reviews to automatically classify user reviews as positive or negative and performance of these two classifiers is compared with each other in this language. The effects of feature presentations on classification performance are discussed. We find that accuracy is influenced by interaction between the classification models and the feature options. The SVM classifier achieves as well as or better accuracy than naive Bayes in Persian movie. Unigrams are proved better features than bigrams and trigrams in capturing Persian sentiment orientation.

Neuroprotective Drug for Nerve Trauma Revealed Using Artificial Intelligence.

PubMed

Romeo-Guitart, David; Forés, Joaquim; Herrando-Grabulosa, Mireia; Valls, Raquel; Leiva-Rodríguez, Tatiana; Galea, Elena; González-Pérez, Francisco; Navarro, Xavier; Petegnief, Valerie; Bosch, Assumpció; Coma, Mireia; Mas, José Manuel; Casas, Caty

2018-01-30

Here we used a systems biology approach and artificial intelligence to identify a neuroprotective agent for the treatment of peripheral nerve root avulsion. Based on accumulated knowledge of the neurodegenerative and neuroprotective processes that occur in motoneurons after root avulsion, we built up protein networks and converted them into mathematical models. Unbiased proteomic data from our preclinical models were used for machine learning algorithms and for restrictions to be imposed on mathematical solutions. Solutions allowed us to identify combinations of repurposed drugs as potential neuroprotective agents and we validated them in our preclinical models. The best one, NeuroHeal, neuroprotected motoneurons, exerted anti-inflammatory properties and promoted functional locomotor recovery. NeuroHeal endorsed the activation of Sirtuin 1, which was essential for its neuroprotective effect. These results support the value of network-centric approaches for drug discovery and demonstrate the efficacy of NeuroHeal as adjuvant treatment with surgical repair for nervous system trauma.

Predicting consumer behavior: using novel mind-reading approaches.

PubMed

Calvert, Gemma A; Brammer, Michael J

2012-01-01

Advances in machine learning as applied to functional magnetic resonance imaging (fMRI) data offer the possibility of pretesting and classifying marketing communications using unbiased pattern recognition algorithms. By using these algorithms to analyze brain responses to brands, products, or existing marketing communications that either failed or succeeded in the marketplace and identifying the patterns of brain activity that characterize success or failure, future planned campaigns or new products can now be pretested to determine how well the resulting brain responses match the desired (successful) pattern of brain activity without the need for verbal feedback. This major advance in signal processing is poised to revolutionize the application of these brain-imaging techniques in the marketing sector by offering greater accuracy of prediction in terms of consumer acceptance of new brands, products, and campaigns at a speed that makes them accessible as routine pretesting tools that will clearly demonstrate return on investment.

Astronomy in the Digital Universe

NASA Astrophysics Data System (ADS)

Haisch, Bernard M.; Lindblom, J.; Terzian, Y.

2006-12-01

The Digital Universe is an Internet project whose mission is to provide free, accurate, unbiased information covering all aspects of human knowledge, and to inspire humans to learn, make use of, and expand this knowledge. It is planned to be a decades long effort, inspired by the Encyclopedia Galactica concept popularized by Carl Sagan, and is being developed by the non-profit Digital Universe Foundation. A worldwide network of experts is responsible for selecting content featured within the Digital Universe. The first publicly available content is the Encyclopedia of Earth, a Boston University project headed by Prof. Cutler Cleveland, which will be part of the Earth Portal. The second major content area will be an analogous Encyclopedia of the Cosmos to be part of the Cosmos Portal. It is anticipated that this will evolve into a major resource for astronomy education. Authors and topic editors are now being recruited for the Encyclopedia of the Cosmos.

Information Theory and Voting Based Consensus Clustering for Combining Multiple Clusterings of Chemical Structures.

PubMed

Saeed, Faisal; Salim, Naomie; Abdo, Ammar

2013-07-01

Many consensus clustering methods have been applied in different areas such as pattern recognition, machine learning, information theory and bioinformatics. However, few methods have been used for chemical compounds clustering. In this paper, an information theory and voting based algorithm (Adaptive Cumulative Voting-based Aggregation Algorithm A-CVAA) was examined for combining multiple clusterings of chemical structures. The effectiveness of clusterings was evaluated based on the ability of the clustering method to separate active from inactive molecules in each cluster, and the results were compared with Ward's method. The chemical dataset MDL Drug Data Report (MDDR) and the Maximum Unbiased Validation (MUV) dataset were used. Experiments suggest that the adaptive cumulative voting-based consensus method can improve the effectiveness of combining multiple clusterings of chemical structures. Copyright © 2013 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

Correcting evaluation bias of relational classifiers with network cross validation

DOE PAGES

Neville, Jennifer; Gallagher, Brian; Eliassi-Rad, Tina; ...

2011-01-04

Recently, a number of modeling techniques have been developed for data mining and machine learning in relational and network domains where the instances are not independent and identically distributed (i.i.d.). These methods specifically exploit the statistical dependencies among instances in order to improve classification accuracy. However, there has been little focus on how these same dependencies affect our ability to draw accurate conclusions about the performance of the models. More specifically, the complex link structure and attribute dependencies in relational data violate the assumptions of many conventional statistical tests and make it difficult to use these tests to assess themore » models in an unbiased manner. In this work, we examine the task of within-network classification and the question of whether two algorithms will learn models that will result in significantly different levels of performance. We show that the commonly used form of evaluation (paired t-test on overlapping network samples) can result in an unacceptable level of Type I error. Furthermore, we show that Type I error increases as (1) the correlation among instances increases and (2) the size of the evaluation set increases (i.e., the proportion of labeled nodes in the network decreases). Lastly, we propose a method for network cross-validation that combined with paired t-tests produces more acceptable levels of Type I error while still providing reasonable levels of statistical power (i.e., 1–Type II error).« less

Cerebellar Structure and Function in Male Wistar-Kyoto Hyperactive Rats

PubMed Central

Thanellou, Alexandra; Green, John T.

2014-01-01

Previous research has suggested that the Wistar-Kyoto Hyperactive (WKHA) rat strain may model some of the behavioral features associated with attention-deficit/hyperactivity disorder (ADHD). We have shown that, in cerebellar-dependent eyeblink conditioning, WKHA emit eyeblink CRs with shortened onset latencies. To further characterize the shortened CR onset latencies seen in WKHA rats, we examined 750-ms delay conditioning with either a tone CS or a light CS, we extended acquisition training, and we included Wistar rats as an additional, outbred control strain. Our results indicated that WKHAs learned more quickly and showed a shortened CR onset latency to a tone CS compared to both Wistar-Kyoto Hypertensive (WKHT) and Wistars. WKHAs and Wistars show a lengthening of CR onset latency over conditioning with a tone CS and an increasing confinement of CRs to the later part of the tone CS (inhibition of delay). WKHAs learned more quickly to a light CS only in comparison to WKHTs and showed a shortened CR onset latency only in comparison to Wistars. Wistars showed an increasing confinement of CRs to the late part of the light CS over conditioning. We used unbiased stereology to estimate the number of Purkinje and granule cells in the cerebellar cortex of the three strains. Our results indicated that WKHAs have more granule cells than Wistars and WKHTs and more Purkinje cells than Wistars. Results are discussed in terms of CS processing and cerebellar cortical contributions to EBC. PMID:23398437

A machine learning methodology for the selection and classification of spontaneous spinal cord dorsum potentials allows disclosure of structured (non-random) changes in neuronal connectivity induced by nociceptive stimulation

PubMed Central

Martin, Mario; Contreras-Hernández, Enrique; Béjar, Javier; Esposito, Gennaro; Chávez, Diógenes; Glusman, Silvio; Cortés, Ulises; Rudomin, Pablo

2015-01-01

Previous studies aimed to disclose the functional organization of the neuronal networks involved in the generation of the spontaneous cord dorsum potentials (CDPs) generated in the lumbosacral spinal segments used predetermined templates to select specific classes of spontaneous CDPs. Since this procedure was time consuming and required continuous supervision, it was limited to the analysis of two specific types of CDPs (negative CDPs and negative positive CDPs), thus excluding potentials that may reflect activation of other neuronal networks of presumed functional relevance. We now present a novel procedure based in machine learning that allows the efficient and unbiased selection of a variety of spontaneous CDPs with different shapes and amplitudes. The reliability and performance of the present method is evaluated by analyzing the effects on the probabilities of generation of different classes of spontaneous CDPs induced by the intradermic injection of small amounts of capsaicin in the anesthetized cat, a procedure known to induce a state of central sensitization leading to allodynia and hyperalgesia. The results obtained with the selection method presently described allowed detection of spontaneous CDPs with specific shapes and amplitudes that are assumed to represent the activation of functionally coupled sets of dorsal horn neurones that acquire different, structured configurations in response to nociceptive stimuli. These changes are considered as responses tending to adequate transmission of sensory information to specific functional requirements as part of homeostatic adjustments. PMID:26379540

On making laboratory report work more meaningful through criterion-based evaluation.

PubMed

Naeraa, N

1987-05-01

The purpose of this work was to encourage students to base their laboratory report work on guidelines reflecting a quality criterion set, previously derived from the functional role of the various sections in scientific papers. The materials were developed by a trial-and-error approach and comprise learning objectives, a parallel structure of manual and reports, general and specific report guidelines and a new common starting experiment. The principal contents are presented, followed by an account of the author's experience with them. Most of the author's students now follow the guidelines. Their conclusions are affected by difficulties in adjusting expected results with due regard to the specific conditions of the experimental subject or to their own deviations from the experimental or analytical procedures prescribed in the manual. Also, problems in interpreting data unbiased by explicit expectations are evident, although a clear distinction between expected and actual results has been helpful for them in seeing the relationship between experiments and textbook contents more clearly, and thus in understanding the hypothetico-deductive approach.

Locating binding poses in protein-ligand systems using reconnaissance metadynamics

PubMed Central

Söderhjelm, Pär; Tribello, Gareth A.; Parrinello, Michele

2012-01-01

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin–benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations. PMID:22440749

The online community based decision making support system for mitigating biased decision making

NASA Astrophysics Data System (ADS)

Kang, Sunghyun; Seo, Jiwan; Choi, Seungjin; Kim, Junho; Han, Sangyong

2016-10-01

As the Internet technology and social media advance, various information and opinions are shared and distributed through the online communities. However, the existence of implicit and explicit bias of opinions may have a potential influence on the outcomes. Compared to the importance of mitigating biased information, the study in this field is relatively young and does not address many important issues. In this paper we propose the noble approach to mitigate the biased opinions using conventional machine learning methods. The proposed method extracts the useful features such as inclination and sentiment of the community members. They are classified based on their previous behavior, and the propensity of the members is understood. This information on each community and its members is very useful and improve the ability to make an unbiased decision. The proposed method presented in this paper is shown to have the ability to assist optimal, fair and good decision making while also reducing the influence of implicit bias.

A quantitative framework to evaluate modeling of cortical development by neural stem cells

PubMed Central

Stein, Jason L.; de la Torre-Ubieta, Luis; Tian, Yuan; Parikshak, Neelroop N.; Hernandez, Israel A.; Marchetto, Maria C.; Baker, Dylan K.; Lu, Daning; Hinman, Cassidy R.; Lowe, Jennifer K.; Wexler, Eric M.; Muotri, Alysson R.; Gage, Fred H.; Kosik, Kenneth S.; Geschwind, Daniel H.

2014-01-01

Summary Neural stem cells have been adopted to model a wide range of neuropsychiatric conditions in vitro. However, how well such models correspond to in vivo brain has not been evaluated in an unbiased, comprehensive manner. We used transcriptomic analyses to compare in vitro systems to developing human fetal brain and observed strong conservation of in vivo gene expression and network architecture in differentiating primary human neural progenitor cells (phNPCs). Conserved modules are enriched in genes associated with ASD, supporting the utility of phNPCs for studying neuropsychiatric disease. We also developed and validated a machine learning approach called CoNTExT that identifies the developmental maturity and regional identity of in vitro models. We observed strong differences between in vitro models, including hiPSC-derived neural progenitors from multiple laboratories. This work provides a systems biology framework for evaluating in vitro systems and supports their value in studying the molecular mechanisms of human neurodevelopmental disease. PMID:24991955

AUTONOMOUS GAUSSIAN DECOMPOSITION

DOE Office of Scientific and Technical Information (OSTI.GOV)

Lindner, Robert R.; Vera-Ciro, Carlos; Murray, Claire E.

2015-04-15

We present a new algorithm, named Autonomous Gaussian Decomposition (AGD), for automatically decomposing spectra into Gaussian components. AGD uses derivative spectroscopy and machine learning to provide optimized guesses for the number of Gaussian components in the data, and also their locations, widths, and amplitudes. We test AGD and find that it produces results comparable to human-derived solutions on 21 cm absorption spectra from the 21 cm SPectral line Observations of Neutral Gas with the EVLA (21-SPONGE) survey. We use AGD with Monte Carlo methods to derive the H i line completeness as a function of peak optical depth and velocitymore » width for the 21-SPONGE data, and also show that the results of AGD are stable against varying observational noise intensity. The autonomy and computational efficiency of the method over traditional manual Gaussian fits allow for truly unbiased comparisons between observations and simulations, and for the ability to scale up and interpret the very large data volumes from the upcoming Square Kilometer Array and pathfinder telescopes.« less

Locating binding poses in protein-ligand systems using reconnaissance metadynamics.

PubMed

Söderhjelm, Pär; Tribello, Gareth A; Parrinello, Michele

2012-04-03

A molecular dynamics-based protocol is proposed for finding and scoring protein-ligand binding poses. This protocol uses the recently developed reconnaissance metadynamics method, which employs a self-learning algorithm to construct a bias that pushes the system away from the kinetic traps where it would otherwise remain. The exploration of phase space with this algorithm is shown to be roughly six to eight times faster than unbiased molecular dynamics and is only limited by the time taken to diffuse about the surface of the protein. We apply this method to the well-studied trypsin-benzamidine system and show that we are able to refind all the poses obtained from a reference EADock blind docking calculation. These poses can be scored based on the length of time the system remains trapped in the pose. Alternatively, one can perform dimensionality reduction on the output trajectory and obtain a map of phase space that can be used in more expensive free-energy calculations.

Influences on choice of surgery as a career: a study of consecutive cohorts in a medical school.

PubMed

Sobral, Dejano T

2006-06-01

To examine the differential impact of person-based and programme-related features on graduates' dichotomous choice between surgical or non-surgical field specialties for first-year residency. A 10-year cohort study was conducted, following 578 students (55.4% male) who graduated from a university medical school during 1994-2003. Data were collected as follows: at the beginning of medical studies, on career preference and learning frame; during medical studies, on academic achievement, cross-year peer tutoring and selective clinical traineeship, and at graduation, on the first-year residency selected. Contingency and logistic regression analyses were performed, with graduates grouped by the dichotomous choice of surgery or not. Overall, 23% of graduates selected a first-year residency in surgery. Seven time-steady features related to this choice: male sex, high self-confidence, option of surgery at admission, active learning style, preference for surgery after Year 1, peer tutoring on clinical surgery, and selective training in clinical surgery. Logistic regression analysis, including all features, predicted 87.1% of the graduates' choices. Male sex, updated preference, peer tutoring and selective training were the most significant predictors in the pathway to choice. The relative roles of person-based and programme-related factors in the choice process are discussed. The findings suggest that for most students the choice of surgery derives from a temporal summation of influences that encompass entry and post-entry factors blended in variable patterns. It is likely that sex-unbiased peer tutoring and selective training supported the students' search process for personal compatibility with specialty-related domains of content and process.

Illustration of Step-Wise Latent Class Modeling With Covariates and Taxometric Analysis in Research Probing Children's Mental Models in Learning Sciences

PubMed Central

Stamovlasis, Dimitrios; Papageorgiou, George; Tsitsipis, Georgios; Tsikalas, Themistoklis; Vaiopoulou, Julie

2018-01-01

This paper illustrates two psychometric methods, latent class analysis (LCA) and taxometric analysis (TA) using empirical data from research probing children's mental representation in science learning. LCA is used to obtain a typology based on observed variables and to further investigate how the encountered classes might be related to external variables, where the effectiveness of classification process and the unbiased estimations of parameters become the main concern. In the step-wise LCA, the class membership is assigned and subsequently its relationship with covariates is established. This leading-edge modeling approach suffers from severe downward-biased estimations. The illustration of LCA is focused on alternative bias correction approaches and demonstrates the effect of modal and proportional class-membership assignment along with BCH and ML correction procedures. The illustration of LCA is presented with three covariates, which are psychometric variables operationalizing formal reasoning, divergent thinking and field dependence-independence, respectively. Moreover, taxometric analysis, a method designed to detect the type of the latent structural model, categorical or dimensional, is introduced, along with the relevant basic concepts and tools. TA was applied complementarily in the same data sets to answer the fundamental hypothesis about children's naïve knowledge on the matters under study and it comprises an additional asset in building theory which is fundamental for educational practices. Taxometric analysis provided results that were ambiguous as far as the type of the latent structure. This finding initiates further discussion and sets a problematization within this framework rethinking fundamental assumptions and epistemological issues. PMID:29713300

Introductory Statistics Students' Conceptual Understanding of Study Design and Conclusions

NASA Astrophysics Data System (ADS)

Fry, Elizabeth Brondos

Recommended learning goals for students in introductory statistics courses include the ability to recognize and explain the key role of randomness in designing studies and in drawing conclusions from those studies involving generalizations to a population or causal claims (GAISE College Report ASA Revision Committee, 2016). The purpose of this study was to explore introductory statistics students' understanding of the distinct roles that random sampling and random assignment play in study design and the conclusions that can be made from each. A study design unit lasting two and a half weeks was designed and implemented in four sections of an undergraduate introductory statistics course based on modeling and simulation. The research question that this study attempted to answer is: How does introductory statistics students' conceptual understanding of study design and conclusions (in particular, unbiased estimation and establishing causation) change after participating in a learning intervention designed to promote conceptual change in these areas? In order to answer this research question, a forced-choice assessment called the Inferences from Design Assessment (IDEA) was developed as a pretest and posttest, along with two open-ended assignments, a group quiz and a lab assignment. Quantitative analysis of IDEA results and qualitative analysis of the group quiz and lab assignment revealed that overall, students' mastery of study design concepts significantly increased after the unit, and the great majority of students successfully made the appropriate connections between random sampling and generalization, and between random assignment and causal claims. However, a small, but noticeable portion of students continued to demonstrate misunderstandings, such as confusion between random sampling and random assignment.

TargetSpy: a supervised machine learning approach for microRNA target prediction.

PubMed

Sturm, Martin; Hackenberg, Michael; Langenberger, David; Frishman, Dmitrij

2010-05-28

Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences.In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org.

TargetSpy: a supervised machine learning approach for microRNA target prediction

PubMed Central

2010-01-01

Background Virtually all currently available microRNA target site prediction algorithms require the presence of a (conserved) seed match to the 5' end of the microRNA. Recently however, it has been shown that this requirement might be too stringent, leading to a substantial number of missed target sites. Results We developed TargetSpy, a novel computational approach for predicting target sites regardless of the presence of a seed match. It is based on machine learning and automatic feature selection using a wide spectrum of compositional, structural, and base pairing features covering current biological knowledge. Our model does not rely on evolutionary conservation, which allows the detection of species-specific interactions and makes TargetSpy suitable for analyzing unconserved genomic sequences. In order to allow for an unbiased comparison of TargetSpy to other methods, we classified all algorithms into three groups: I) no seed match requirement, II) seed match requirement, and III) conserved seed match requirement. TargetSpy predictions for classes II and III are generated by appropriate postfiltering. On a human dataset revealing fold-change in protein production for five selected microRNAs our method shows superior performance in all classes. In Drosophila melanogaster not only our class II and III predictions are on par with other algorithms, but notably the class I (no-seed) predictions are just marginally less accurate. We estimate that TargetSpy predicts between 26 and 112 functional target sites without a seed match per microRNA that are missed by all other currently available algorithms. Conclusion Only a few algorithms can predict target sites without demanding a seed match and TargetSpy demonstrates a substantial improvement in prediction accuracy in that class. Furthermore, when conservation and the presence of a seed match are required, the performance is comparable with state-of-the-art algorithms. TargetSpy was trained on mouse and performs well in human and drosophila, suggesting that it may be applicable to a broad range of species. Moreover, we have demonstrated that the application of machine learning techniques in combination with upcoming deep sequencing data results in a powerful microRNA target site prediction tool http://www.targetspy.org. PMID:20509939

RNA-Sequencing Reveals Unique Transcriptional Signatures of Running and Running-Independent Environmental Enrichment in the Adult Mouse Dentate Gyrus.

PubMed

Grégoire, Catherine-Alexandra; Tobin, Stephanie; Goldenstein, Brianna L; Samarut, Éric; Leclerc, Andréanne; Aumont, Anne; Drapeau, Pierre; Fulton, Stephanie; Fernandes, Karl J L

2018-01-01

Environmental enrichment (EE) is a powerful stimulus of brain plasticity and is among the most accessible treatment options for brain disease. In rodents, EE is modeled using multi-factorial environments that include running, social interactions, and/or complex surroundings. Here, we show that running and running-independent EE differentially affect the hippocampal dentate gyrus (DG), a brain region critical for learning and memory. Outbred male CD1 mice housed individually with a voluntary running disk showed improved spatial memory in the radial arm maze compared to individually- or socially-housed mice with a locked disk. We therefore used RNA sequencing to perform an unbiased interrogation of DG gene expression in mice exposed to either a voluntary running disk (RUN), a locked disk (LD), or a locked disk plus social enrichment and tunnels [i.e., a running-independent complex environment (CE)]. RNA sequencing revealed that RUN and CE mice showed distinct, non-overlapping patterns of transcriptomic changes versus the LD control. Bio-informatics uncovered that the RUN and CE environments modulate separate transcriptional networks, biological processes, cellular compartments and molecular pathways, with RUN preferentially regulating synaptic and growth-related pathways and CE altering extracellular matrix-related functions. Within the RUN group, high-distance runners also showed selective stress pathway alterations that correlated with a drastic decline in overall transcriptional changes, suggesting that excess running causes a stress-induced suppression of running's genetic effects. Our findings reveal stimulus-dependent transcriptional signatures of EE on the DG, and provide a resource for generating unbiased, data-driven hypotheses for novel mediators of EE-induced cognitive changes.

Using machine learning to disentangle homonyms in large text corpora.

PubMed

Roll, Uri; Correia, Ricardo A; Berger-Tal, Oded

2018-06-01

Systematic reviews are an increasingly popular decision-making tool that provides an unbiased summary of evidence to support conservation action. These reviews bridge the gap between researchers and managers by presenting a comprehensive overview of all studies relating to a particular topic and identify specifically where and under which conditions an effect is present. However, several technical challenges can severely hinder the feasibility and applicability of systematic reviews, for example, homonyms (terms that share spelling but differ in meaning). Homonyms add noise to search results and cannot be easily identified or removed. We developed a semiautomated approach that can aid in the classification of homonyms among narratives. We used a combination of automated content analysis and artificial neural networks to quickly and accurately sift through large corpora of academic texts and classify them to distinct topics. As an example, we explored the use of the word reintroduction in academic texts. Reintroduction is used within the conservation context to indicate the release of organisms to their former native habitat; however, a Web of Science search for this word returned thousands of publications in which the term has other meanings and contexts. Using our method, we automatically classified a sample of 3000 of these publications with over 99% accuracy, relative to a manual classification. Our approach can be used easily with other homonyms and can greatly facilitate systematic reviews or similar work in which homonyms hinder the harnessing of large text corpora. Beyond homonyms we see great promise in combining automated content analysis and machine-learning methods to handle and screen big data for relevant information in conservation science. © 2017 Society for Conservation Biology.

Machine learning shows association between genetic variability in PPARG and cerebral connectivity in preterm infants

PubMed Central

Krishnan, Michelle L.; Wang, Zi; Aljabar, Paul; Ball, Gareth; Mirza, Ghazala; Saxena, Alka; Counsell, Serena J.; Hajnal, Joseph V.; Montana, Giovanni

2017-01-01

Preterm infants show abnormal structural and functional brain development, and have a high risk of long-term neurocognitive problems. The molecular and cellular mechanisms involved are poorly understood, but novel methods now make it possible to address them by examining the relationship between common genetic variability and brain endophenotype. We addressed the hypothesis that variability in the Peroxisome Proliferator Activated Receptor (PPAR) pathway would be related to brain development. We employed machine learning in an unsupervised, unbiased, combined analysis of whole-brain diffusion tractography together with genomewide, single-nucleotide polymorphism (SNP)-based genotypes from a cohort of 272 preterm infants, using Sparse Reduced Rank Regression (sRRR) and correcting for ethnicity and age at birth and imaging. Empirical selection frequencies for SNPs associated with cerebral connectivity ranged from 0.663 to zero, with multiple highly selected SNPs mapping to genes for PPARG (six SNPs), ITGA6 (four SNPs), and FXR1 (two SNPs). SNPs in PPARG were significantly overrepresented (ranked 7–11 and 67 of 556,000 SNPs; P < 2.2 × 10−7), and were mostly in introns or regulatory regions with predicted effects including protein coding and nonsense-mediated decay. Edge-centric graph-theoretic analysis showed that highly selected white-matter tracts were consistent across the group and important for information transfer (P < 2.2 × 10−17); they most often connected to the insula (P < 6 × 10−17). These results suggest that the inhibited brain development seen in humans exposed to the stress of a premature extrauterine environment is modulated by genetic factors, and that PPARG signaling has a previously unrecognized role in cerebral development. PMID:29229843

Influence of schooling and age on cognitive performance in healthy older adults

PubMed Central

Bento-Torres, N.V.O.; Bento-Torres, J.; Tomás, A.M.; Costa, V.O.; Corrêa, P.G.R.; Costa, C.N.M.; Jardim, N.Y.V.; Picanço-Diniz, C.W.

2017-01-01

Few studies have examined the influence of a low level of schooling on age-related cognitive decline in countries with wide social and economic inequalities by using the Cambridge Automated Neuropsychological Test Battery (CANTAB). The aim of the present study was to assess the influence of schooling on age-related cognitive decline using unbiased cognitive tests. CANTAB allows cognitive assessment across cultures and education levels with reduced interference of the examiner during data acquisition. Using two-way ANOVA, we assessed the influences of age and education on test scores of old adults (61–84 years of age). CANTAB tests included: Visual Sustained Attention, Reaction Time, Spatial Working Memory, Learning and Episodic Memory. All subjects had a minimum visual acuity of 20/30 (Snellen Test), no previous or current history of traumatic brain/head trauma, stroke, language impairment, chronic alcoholism, neurological diseases, memory problems or depressive symptoms, and normal scores on the Mini Mental State Examination (MMSE). Subjects were grouped according to education level (1 to 7 and ≥8 years of schooling) and age (60–69 and ≥70 years). Low schooling level was associated with significantly lower performance on visual sustained attention, learning and episodic memory, reaction time, and spatial working memory. Although reaction time was influenced by age, no significant results on post hoc analysis were detected. Our findings showed a significantly worse cognitive performance in volunteers with lower levels of schooling and suggested that formal education in early life must be included in the preventive public health agenda. In addition, we suggest that CANTAB may be useful to detect subtle cognitive changes in healthy aging. PMID:28355353

Devoloping an integrated analysis approach to exoplanetary spectroscopy

NASA Astrophysics Data System (ADS)

Waldmann, Ingo

2015-07-01

Analysing the atmospheres of Earth and SuperEarth type planets for possible biomarkers will push us to the limits of current and future instrumentation. As the field matures, we must also upgrade our data analysis and interpretation techniques from their "ad-hoc" beginnings to a solid statistical foundation. This is particularly important for the optimal exploitation of future instruments, such as JWST and E-ELT. At the limits of low signal-to-noise, we are prone to two sources of biases: 1) Prior selection in the data reduction; 2) Prior constraints on the spectral retrieval. A unified set of tools addressing both points is required. To de-trend low S/N, correlated data, we demonstrated blind-source-separation (BSS) machine learning techniques to be a significant step forward. Both in photometry and spectroscopy. BSS finds applications in fields as diverse as medical imaging to cosmology. Applied to exoplanets, it allows us to resolve de-trending biases and demonstrate consistency between data sets that were previously found to be highly discrepant and subject to much debate. For the interpretation of the data, we developed a novel atmospheric retrieval suite, Tau-REx. Tau-REx implements an unbiased prior selections via a custom built pattern recognition software. A full subsequent mapping of the likelihood space (using cluster computing) allows us, for the first time, to fully study degeneracies and biases in emission and transmission spectroscopy. The development of a coherent end-to-end infrastructure is paramount to the characterisation of ever smaller and fainter foreign worlds. In this conference, I will discuss what we have learned for current observations and the need for unified statistical frameworks in the era of JWST, E-ELT.

Habenula and interpeduncular nucleus differentially modulate predator odor-induced innate fear behavior in rats.

PubMed

Vincenz, Daniel; Wernecke, Kerstin E A; Fendt, Markus; Goldschmidt, Jürgen

2017-08-14

Fear is an important behavioral system helping humans and animals to survive potentially dangerous situations. Fear can be innate or learned. Whereas the neural circuits underlying learned fear are already well investigated, the knowledge about the circuits mediating innate fear is still limited. We here used a novel, unbiased approach to image in vivo the spatial patterns of neural activity in odor-induced innate fear behavior in rats. We intravenously injected awake unrestrained rats with a 99m-technetium labeled blood flow tracer (99mTc-HMPAO) during ongoing exposure to fox urine or water as control, and mapped the brain distribution of the trapped tracer using single-photon emission computed tomography (SPECT). Upon fox urine exposure blood flow increased in a number of brain regions previously associated with odor-induced innate fear such as the amygdala, ventromedial hypothalamus and dorsolateral periaqueductal grey, but, unexpectedly, decreased at higher significance levels in the interpeduncular nucleus (IPN). Significant flow changes were found in regions monosynaptically connected to the IPN. Flow decreased in the dorsal tegmentum and entorhinal cortex. Flow increased in the habenula (Hb) and correlated with odor effects on behavioral defensive strategy. Hb lesions reduced avoidance of but increased approach to the fox urine while IPN lesions only reduced avoidance behavior without approach behavior. Our study identifies a new component, the IPN, of the neural circuit mediating odor-induced innate fear behavior in mammals and suggests that the evolutionarily conserved Hb-IPN system, which has recently been implicated in cued fear, also forms an integral part of the innate fear circuitry. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

On the perpetuation of ignorance: system dependence, system justification, and the motivated avoidance of sociopolitical information.

PubMed

Shepherd, Steven; Kay, Aaron C

2012-02-01

How do people cope when they feel uninformed or unable to understand important social issues, such as the environment, energy concerns, or the economy? Do they seek out information, or do they simply ignore the threatening issue at hand? One would intuitively expect that a lack of knowledge would motivate an increased, unbiased search for information, thereby facilitating participation and engagement in these issues-especially when they are consequential, pressing, and self-relevant. However, there appears to be a discrepancy between the importance/self-relevance of social issues and people's willingness to engage with and learn about them. Leveraging the literature on system justification theory (Jost & Banaji, 1994), the authors hypothesized that, rather than motivating an increased search for information, a lack of knowledge about a specific sociopolitical issue will (a) foster feelings of dependence on the government, which will (b) increase system justification and government trust, which will (c) increase desires to avoid learning about the relevant issue when information is negative or when information valence is unknown. In other words, the authors suggest that ignorance-as a function of the system justifying tendencies it may activate-may, ironically, breed more ignorance. In the contexts of energy, environmental, and economic issues, the authors present 5 studies that (a) provide evidence for this specific psychological chain (i.e., ignorance about an issue → dependence → government trust → avoidance of information about that issue); (b) shed light on the role of threat and motivation in driving the second and third links in this chain; and (c) illustrate the unfortunate consequences of this process for individual action in those contexts that may need it most.

Web-Based Instruction, Learning Effectiveness and Learning Behavior: The Impact of Relatedness

ERIC Educational Resources Information Center

Shieh, Chich-Jen; Liao, Ying; Hu, Ridong

2013-01-01

This study aims to discuss the effects of Web-based Instruction and Learning Behavior on Learning Effectiveness. Web-based Instruction contains the dimensions of Active Learning, Simulation-based Learning, Interactive Learning, and Accumulative Learning; and, Learning Behavior covers Learning Approach, Learning Habit, and Learning Attitude. The…

Prediction of maize phenotype based on whole-genome single nucleotide polymorphisms using deep belief networks

NASA Astrophysics Data System (ADS)

Rachmatia, H.; Kusuma, W. A.; Hasibuan, L. S.

2017-05-01

Selection in plant breeding could be more effective and more efficient if it is based on genomic data. Genomic selection (GS) is a new approach for plant-breeding selection that exploits genomic data through a mechanism called genomic prediction (GP). Most of GP models used linear methods that ignore effects of interaction among genes and effects of higher order nonlinearities. Deep belief network (DBN), one of the architectural in deep learning methods, is able to model data in high level of abstraction that involves nonlinearities effects of the data. This study implemented DBN for developing a GP model utilizing whole-genome Single Nucleotide Polymorphisms (SNPs) as data for training and testing. The case study was a set of traits in maize. The maize dataset was acquisitioned from CIMMYT’s (International Maize and Wheat Improvement Center) Global Maize program. Based on Pearson correlation, DBN is outperformed than other methods, kernel Hilbert space (RKHS) regression, Bayesian LASSO (BL), best linear unbiased predictor (BLUP), in case allegedly non-additive traits. DBN achieves correlation of 0.579 within -1 to 1 range.

The clinical application of mobile technology to disaster medicine.

PubMed

Case, Timothy; Morrison, Cecily; Vuylsteke, Alain

2012-10-01

Mobile health care technology (mHealth) has the potential to improve communication and clinical information management in disasters. This study reviews the literature on health care and computing published in the past five years to determine the types and efficacy of mobile applications available to disaster medicine, along with lessons learned. Five types of applications are identified: (1) disaster scene management; (2) remote monitoring of casualties; (3) medical image transmission (teleradiology); (4) decision support applications; and (5) field hospital information technology (IT) systems. Most projects have not yet reached the deployment stage, but evaluation exercises show that mHealth should allow faster processing and transport of patients, improved accuracy of triage and better monitoring of unattended patients at a disaster scene. Deployments of teleradiology and field hospital IT systems to disaster zones suggest that mHealth can improve resource allocation and patient care. The key problems include suitability of equipment for use in disaster zones and providing sufficient training to ensure staff familiarity with complex equipment. Future research should focus on providing unbiased observations of the use of mHealth in disaster medicine.

The effect of discovery learning and problem-based learning on middle school students’ self-regulated learning

NASA Astrophysics Data System (ADS)

Miatun, A.; Muntazhimah

2018-01-01

The aim of this research was to determine the effect of learning models on mathematics achievement viewed from student’s self-regulated learning. The learning model compared were discovery learning and problem-based learning. The population was all students at the grade VIII of Junior High School in Boyolali regency. The samples were students of SMPN 4 Boyolali, SMPN 6 Boyolali, and SMPN 4 Mojosongo. The instruments used were mathematics achievement tests and self-regulated learning questionnaire. The data were analyzed using unbalanced two-ways Anova. The conclusion was as follows: (1) discovery learning gives better achievement than problem-based learning. (2) Achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. (3) For discovery learning, achievement of students who have high self-regulated learning was better than students who have medium and low self-regulated learning. For problem-based learning, students who have high and medium self-regulated learning have the same achievement. (4) For students who have high self-regulated learning, discovery learning gives better achievement than problem-based learning. Students who have medium and low self-regulated learning, both learning models give the same achievement.

Technology, Learning, and Individual Differences

ERIC Educational Resources Information Center

Bear, Anne A. Ghost

2012-01-01

The learning needs for adults that result from the constant increase in technology are rooted in the adult learning concepts of (a) andragogy, (b) self-directed learning, (c) learning-how-to-learn, (d) real-life learning, and (e) learning strategies. This study described the learning strategies that adults use in learning to engage in an online…

The Relationship of Learning Traits, Motivation and Performance-Learning Response Dynamics

ERIC Educational Resources Information Center

Hwang, Wu-Yuin; Chang, Chen-Bin; Chen, Gan-Jung

2004-01-01

This paper proposes a model of learning dynamics and learning energy, one that analyzes learning systems scientifically. This model makes response to the learner action by means of some equations relating to learning dynamics, learning energy, learning speed, learning force, and learning acceleration, which is analogous to the notion of Newtonian…

Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

ERIC Educational Resources Information Center

Choi, Woojae; Jacobs, Ronald L.

2011-01-01

While workplace learning includes formal and informal learning, the relationship between the two has been overlooked, because they have been viewed as separate entities. This study investigated the effects of formal learning, personal learning orientation, and supportive learning environment on informal learning among 203 middle managers in Korean…

Learning Careers/Learning Trajectories. Trends and Issues Alert.

ERIC Educational Resources Information Center

Kerka, Sandra

"Learning autobiography,""learning career," and "learning trajectory" are related descriptors for the process of developing attitudes toward learning and the origins of interests, learning styles, and learning processes. The learning career is composed of events, activities, and interpretations that develop individual…

Metacognitive components in smart learning environment

NASA Astrophysics Data System (ADS)

Sumadyo, M.; Santoso, H. B.; Sensuse, D. I.

2018-03-01

Metacognitive ability in digital-based learning process helps students in achieving learning goals. So that digital-based learning environment should make the metacognitive component as a facility that must be equipped. Smart Learning Environment is the concept of a learning environment that certainly has more advanced components than just a digital learning environment. This study examines the metacognitive component of the smart learning environment to support the learning process. A review of the metacognitive literature was conducted to examine the components involved in metacognitive learning strategies. Review is also conducted on the results of study smart learning environment, ranging from design to context in building smart learning. Metacognitive learning strategies certainly require the support of adaptable, responsive and personalize learning environments in accordance with the principles of smart learning. The current study proposed the role of metacognitive component in smart learning environment, which is useful as the basis of research in building environment in smart learning.

Mutually unbiased product bases for multiple qudits

DOE Office of Scientific and Technical Information (OSTI.GOV)

McNulty, Daniel; Pammer, Bogdan; Weigert, Stefan

We investigate the interplay between mutual unbiasedness and product bases for multiple qudits of possibly different dimensions. A product state of such a system is shown to be mutually unbiased to a product basis only if each of its factors is mutually unbiased to all the states which occur in the corresponding factors of the product basis. This result implies both a tight limit on the number of mutually unbiased product bases which the system can support and a complete classification of mutually unbiased product bases for multiple qubits or qutrits. In addition, only maximally entangled states can be mutuallymore » unbiased to a maximal set of mutually unbiased product bases.« less

Recurrent Themes in E-Learning: A Narrative Analysis of Major E-Learning Reports

ERIC Educational Resources Information Center

Waight, Consuelo L.; Willging, Pedro; Wentling, Tim

2004-01-01

E-learning, sometimes referred to as online learning, Web-based learning, distance learning, and technology-based learning, among other names, is a concept that has garnered significant global attention. This broad attention to e-learning has resulted in numerous e-learning reports. In doing extensive Web searches for e-learning reports, the…

Context Aware Ubiquitous Learning Environments for Peer-to-Peer Collaborative Learning

ERIC Educational Resources Information Center

Yang, Stephen J. H.

2006-01-01

A ubiquitous learning environment provides an interoperable, pervasive, and seamless learning architecture to connect, integrate, and share three major dimensions of learning resources: learning collaborators, learning contents, and learning services. Ubiquitous learning is characterized by providing intuitive ways for identifying right learning…

Blended Learning: An Innovative Approach

ERIC Educational Resources Information Center

Lalima; Dangwal, Kiran Lata

2017-01-01

Blended learning is an innovative concept that embraces the advantages of both traditional teaching in the classroom and ICT supported learning including both offline learning and online learning. It has scope for collaborative learning; constructive learning and computer assisted learning (CAI). Blended learning needs rigorous efforts, right…

Brain Research: Implications for Learning.

ERIC Educational Resources Information Center

Soares, Louise M.; Soares, Anthony T.

Brain research has illuminated several areas of the learning process: (1) learning as association; (2) learning as reinforcement; (3) learning as perception; (4) learning as imitation; (5) learning as organization; (6) learning as individual style; and (7) learning as brain activity. The classic conditioning model developed by Pavlov advanced…

Acquisition of neural learning in cerebellum and cerebral cortex for smooth pursuit eye movements

PubMed Central

Li, Jennifer X.; Medina, Javier F.; Frank, Loren M.; Lisberger, Stephen G.

2011-01-01

We have evaluated the emergence of neural learning in the frontal eye fields (FEFSEM) and the floccular complex of the cerebellum while monkeys learned a precisely-timed change in the direction of pursuit eye movement. For each neuron, we measured the time course of changes in neural response across a learning session that comprised at least 100 repetitions of an instructive change in target direction. In both areas, the average population learning curves tracked the behavioral changes with high fidelity, consistent with possible roles in driving learning. However, the learning curves of individual neurons sometimes bore little relation to the smooth, monotonic progression of behavioral learning. In the FEFSEM, neural learning was episodic. For individual neurons, learning appeared at different times during the learning session and sometimes disappeared by the end of the session. Different FEFSEM neurons expressed maximal learning at different times relative to the acquisition of behavioral learning. In the floccular complex, many Purkinje cells acquired learned simple-spike responses according to the same time course as behavioral learning and retained their learned responses throughout the learning session. A minority of Purkinje cells acquired learned responses late in the learning session, after behavioral learning had reached an asymptote. We conclude that learning in single neurons can follow a very different time course from behavioral learning. Both the FEFSEM and the floccular complex contain representations of multiple temporal components of learning, with different neurons contributing to learning at different times during the acquisition of a learned movement. PMID:21900551

How People Learn in an Asynchronous Online Learning Environment: The Relationships between Graduate Students' Learning Strategies and Learning Satisfaction

ERIC Educational Resources Information Center

Choi, Beomkyu

2016-01-01

The purpose of this study was to examine the relationships between learners' learning strategies and learning satisfaction in an asynchronous online learning environment. In an attempt to shed some light on how people learn in an online learning environment, one hundred and sixteen graduate students who were taking online learning courses…

[Anaesthetists learn--do institutions also learn? Importance of institutional learning and corporate culture in clinics].

PubMed

Schüpfer, G; Gfrörer, R; Schleppers, A

2007-10-01

In only a few contexts is the need for substantial learning more pronounced than in health care. For a health care provider, the ability to learn is essential in a changing environment. Although individual humans are programmed to learn naturally, organisations are not. Learning that is limited to individual professions and traditional approaches to continuing medical education is not sufficient to bring about substantial changes in the learning capacity of an institution. Also, organisational learning is an important issue for anaesthesia departments. Future success of an organisation often depends on new capabilities and competencies. Organisational learning is the capacity or processes within an organisation to maintain or improve performance based on experience. Learning is seen as a system-level phenomenon as it stays in the organisation regardless of the players involved. Experience from other industries shows that learning strategies tend to focus on single loop learning, with relatively little double loop learning and virtually no meta-learning or non-learning. The emphasis on team delivery of health care reinforces the need for team learning. Learning organisations make learning an intrinsic part of their organisations and are a place where people continually learn how to learn together. Organisational learning practice can help to improve existing skills and competencies and to change outdated assumptions, procedures and structures. So far, learning theory has been ignored in medicine, due to a wide variety of complex political, economic, social, organisational culture and medical factors that prevent innovation and resist change. The organisational culture is central to every stage of the learning process. Learning organisations move beyond simple employee training into organisational problem solving, innovation and learning. Therefore, teamwork and leadership are necessary. Successful organisations change the competencies of individuals, the systems, the organisation, the strategy and the culture.

Is It Time to Take Learning Design to Task?

ERIC Educational Resources Information Center

Griffiths, David; Inman, Maggie

2017-01-01

Context drives learning design, but too often context is not considered within learning design literature. Reported skill gaps lead to considerations around learning design and the security, completeness and depth of learning developed by learning designers in adult learning. Frequently learning is linked to context, where learning environments…

A blended learning program on undergraduate nursing students' learning of electrocardiography.

PubMed

Jang, Keum-Seong; Kim, Yun-Min; Park, Soon-Joo

2006-01-01

This study sought to evaluate the feasibility of applying the blended learning program that combines the advantages of face-to-face(FTF) learning and e-learning. The blended learning program was developed by the authors and implemented for 4 weeks. 56 senior nursing students were recruited at a university in Korea. Significant improvement was noted in learning achievement. No significant differences were noted between FTF and web-based learning in learning motivation. Learning satisfaction and students' experience in taking this course revealed some positive effects of blended learning. The use of blended learning program for undergraduate nursing students will provide an effective learning model.

Learning Analytics for Supporting Seamless Language Learning Using E-Book with Ubiquitous Learning System

ERIC Educational Resources Information Center

Mouri, Kousuke; Uosaki, Noriko; Ogata, Hiroaki

2018-01-01

Seamless learning has been recognized as an effective learning approach across various dimensions including formal and informal learning contexts, individual and social learning, and physical world and cyberspace. With the emergence of seamless learning, the majority of the current research focuses on realizing a seamless learning environment at…

Neural Correlates of Motor Learning, Transfer of Learning, and Learning to Learn

PubMed Central

Seidler, Rachael D.

2009-01-01

Recent studies on the neural bases of sensorimotor adaptation demonstrate that the cerebellar and striatal thalamocortical pathways contribute to early learning. Transfer of learning involves a reduction in the contribution of early learning networks, and increased reliance on the cerebellum. The neural correlates of learning to learn remain to be determined, but likely involve enhanced functioning of general aspects of early learning. PMID:20016293

Evolutionarily stable learning schedules and cumulative culture in discrete generation models.

PubMed

Aoki, Kenichi; Wakano, Joe Yuichiro; Lehmann, Laurent

2012-06-01

Individual learning (e.g., trial-and-error) and social learning (e.g., imitation) are alternative ways of acquiring and expressing the appropriate phenotype in an environment. The optimal choice between using individual learning and/or social learning may be dictated by the life-stage or age of an organism. Of special interest is a learning schedule in which social learning precedes individual learning, because such a schedule is apparently a necessary condition for cumulative culture. Assuming two obligatory learning stages per discrete generation, we obtain the evolutionarily stable learning schedules for the three situations where the environment is constant, fluctuates between generations, or fluctuates within generations. During each learning stage, we assume that an organism may target the optimal phenotype in the current environment by individual learning, and/or the mature phenotype of the previous generation by oblique social learning. In the absence of exogenous costs to learning, the evolutionarily stable learning schedules are predicted to be either pure social learning followed by pure individual learning ("bang-bang" control) or pure individual learning at both stages ("flat" control). Moreover, we find for each situation that the evolutionarily stable learning schedule is also the one that optimizes the learned phenotype at equilibrium. Copyright © 2012 Elsevier Inc. All rights reserved.

Serious games experiment toward agent-based simulation

USGS Publications Warehouse

Wein, Anne; Labiosa, William

2013-01-01

We evaluate the potential for serious games to be used as a scientifically based decision-support product that supports the United States Geological Survey’s (USGS) mission--to provide integrated, unbiased scientific information that can make a substantial contribution to societal well-being for a wide variety of complex environmental challenges. Serious or pedagogical games are an engaging way to educate decisionmakers and stakeholders about environmental challenges that are usefully informed by natural and social scientific information and knowledge and can be designed to promote interactive learning and exploration in the face of large uncertainties, divergent values, and complex situations. We developed two serious games that use challenging environmental-planning issues to demonstrate and investigate the potential contributions of serious games to inform regional-planning decisions. Delta Skelta is a game emulating long-term integrated environmental planning in the Sacramento-San Joaquin Delta, California, that incorporates natural hazards (flooding and earthquakes) and consequences for California water supplies amidst conflicting water interests. Age of Ecology is a game that simulates interactions between economic and ecologic processes, as well as natural hazards while implementing agent-based modeling. The content of these games spans the USGS science mission areas related to water, ecosystems, natural hazards, land use, and climate change. We describe the games, reflect on design and informational aspects, and comment on their potential usefulness. During the process of developing these games, we identified various design trade-offs involving factual information, strategic thinking, game-winning criteria, elements of fun, number and type of players, time horizon, and uncertainty. We evaluate the two games in terms of accomplishments and limitations. Overall, we demonstrated the potential for these games to usefully represent scientific information within challenging environmental and ecosystem-management contexts and to provide an interactive way of learning about the complexity of interactions between people and natural systems. Further progress on the use of pedagogical games to fulfill the USGS mission will require collaboration among scientists, game developers, educators, and stakeholders. We conclude that as the USGS positions itself to communicate and convey the results of multiple science strategies, including natural-resource security and sustainability, pedagogical game development and agent-based modeling offer a means to (1) establish interdisciplinary and collaborative teams with a focused integrated outcome; (2) contribute to the modeling of interaction, feedback, and adaptation of ecosystems; and (3) enable social learning through a broadly appealing and increasingly sophisticated medium.

A User-Centric Adaptive Learning System for E-Learning 2.0

ERIC Educational Resources Information Center

Huang, Shiu-Li; Shiu, Jung-Hung

2012-01-01

The success of Web 2.0 inspires e-learning to evolve into e-learning 2.0, which exploits collective intelligence to achieve user-centric learning. However, searching for suitable learning paths and content for achieving a learning goal is time consuming and troublesome on e-learning 2.0 platforms. Therefore, introducing formal learning in these…

Leveraging Experiential Learning Techniques for Transfer

ERIC Educational Resources Information Center

Furman, Nate; Sibthorp, Jim

2013-01-01

Experiential learning techniques can be helpful in fostering learning transfer. Techniques such as project-based learning, reflective learning, and cooperative learning provide authentic platforms for developing rich learning experiences. In contrast to more didactic forms of instruction, experiential learning techniques foster a depth of learning…

The impact of E-learning in medical education.

PubMed

Ruiz, Jorge G; Mintzer, Michael J; Leipzig, Rosanne M

2006-03-01

The authors provide an introduction to e-learning and its role in medical education by outlining key terms, the components of e-learning, the evidence for its effectiveness, faculty development needs for implementation, evaluation strategies for e-learning and its technology, and how e-learning might be considered evidence of academic scholarship. E-learning is the use of Internet technologies to enhance knowledge and performance. E-learning technologies offer learners control over content, learning sequence, pace of learning, time, and often media, allowing them to tailor their experiences to meet their personal learning objectives. In diverse medical education contexts, e-learning appears to be at least as effective as traditional instructor-led methods such as lectures. Students do not see e-learning as replacing traditional instructor-led training but as a complement to it, forming part of a blended-learning strategy. A developing infrastructure to support e-learning within medical education includes repositories, or digital libraries, to manage access to e-learning materials, consensus on technical standardization, and methods for peer review of these resources. E-learning presents numerous research opportunities for faculty, along with continuing challenges for documenting scholarship. Innovations in e-learning technologies point toward a revolution in education, allowing learning to be individualized (adaptive learning), enhancing learners' interactions with others (collaborative learning), and transforming the role of the teacher. The integration of e-learning into medical education can catalyze the shift toward applying adult learning theory, where educators will no longer serve mainly as the distributors of content, but will become more involved as facilitators of learning and assessors of competency.

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

PubMed

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

2013-12-01

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

Comparative Study of Learning Using E-Learning and Printed Materials on Independent Learning and Creativity

NASA Astrophysics Data System (ADS)

Wahyu Utami, Niken; Aziz Saefudin, Abdul

2018-01-01

This study aims to determine: 1) differences in students taking independent learning by using e-learning and the students who attend the learning by using the print instructional materials ; 2) differences in the creativity of students who follow learning with e-learning and the students who attend the learning by using the print instructional materials ; 3) differences in learning independence and creativity of students attend learning with e-learning and the students who attend lessons using printed teaching materials in the subject of Mathematics Instructional Media Development. This study was a quasi-experimental research design using only posttest control design. The study population was all students who take courses in Learning Mathematics Media Development, Academic Year 2014/2015 100 students and used a random sample (random sampling) is 60 students. To test the hypothesis used multivariate analysis of variance or multivariable analysis of variance (MANOVA) of the track. The results of this study indicate that 1) There is a difference in student learning independence following study using the e-learning and the students who attend lessons using printed teaching materials in the lecture PMPM ( F = 4.177, p = 0.046 < 0.05 ) ; 2 ) There is no difference in the creativity of the students who complete the learning by using e -learning and students to follow the learning using printed teaching materials in the lecture PMPM ( F = 0.470, p = 0.496 > 0.05) ; No difference learning independence and creativity of students attend learning by using e-learning and the students who attend the learning using printed teaching materials in the lecture PMPM (F = 2.452, p = 0.095 > 0.05). Based on these studies suggested that the learning using e -learning can be used to develop student creativity, while learning to use e -learning and teaching materials can be printed to use to develop students’ independence.

Effects of Cooperative E-Learning on Learning Outcomes

ERIC Educational Resources Information Center

Yeh, Shang-Pao; Fu, Hsin-Wei

2014-01-01

This study aims to discuss the effects of E-Learning and cooperative learning on learning outcomes. E-Learning covers the dimensions of Interpersonal communication, abundant resources, Dynamic instruction, and Learning community; and, cooperative learning contains three dimensions of Cooperative motive, Social interaction, and Cognition…

Discovery learning with SAVI approach in geometry learning

NASA Astrophysics Data System (ADS)

Sahara, R.; Mardiyana; Saputro, D. R. S.

2018-05-01

Geometry is one branch of mathematics that an important role in learning mathematics in the schools. This research aims to find out about Discovery Learning with SAVI approach to achievement of learning geometry. This research was conducted at Junior High School in Surakarta city. Research data were obtained through test and questionnaire. Furthermore, the data was analyzed by using two-way Anova. The results showed that Discovery Learning with SAVI approach gives a positive influence on mathematics learning achievement. Discovery Learning with SAVI approach provides better mathematics learning outcomes than direct learning. In addition, students with high self-efficacy categories have better mathematics learning achievement than those with moderate and low self-efficacy categories, while student with moderate self-efficacy categories are better mathematics learning achievers than students with low self-efficacy categories. There is an interaction between Discovery Learning with SAVI approach and self-efficacy toward student's mathematics learning achievement. Therefore, Discovery Learning with SAVI approach can improve mathematics learning achievement.

Development of an e-learning package on Service-Learning for university teachers: experience from Hong Kong.

PubMed

Shek, Daniel T L; Chan, Stephen C F

2013-01-01

To help university teachers to understand Service-Learning and develop Service-Learning subjects, a 3-h+ e-learning package was developed at The Hong Kong Polytechnic University (PolyU). There are seven units in this e-learning package: introduction session (Unit 1), what is Service-Learning? (Unit 2), impact and benefits of Service-Learning (Unit 3), myths and positive attitudes toward Service-Learning (Unit 4), developing a Service-Learning subject at PolyU (Unit 5), self-reflection about Service-Learning (Unit 6), and concluding session (Unit 7). To understand the views of the users on the e-learning package, the package was offered before formal launching. For the first offering, three focus group sessions were held. Results showed that the users were satisfied with the structural arrangement of the e-learning package and agreed that the e-learning package was useful for them to understand more about Service-Learning. For the second offering, colleagues were generally satisfied with the e-learning package and demonstrated gain in knowledge on Service-Learning. Suggestions for improvement were noted.

Digital case-based learning system in school.

PubMed

Gu, Peipei; Guo, Jiayang

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework.

Learning during processing Word learning doesn’t wait for word recognition to finish

PubMed Central

Apfelbaum, Keith S.; McMurray, Bob

2017-01-01

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed when, during the course of these dynamic recognition processes, learned representations are formed and updated. If learned representations are formed and updated while recognition is ongoing, the result of learning may incorporate spurious, partial information. For example, during word recognition, words take time to be identified, and competing words are often active in parallel. If learning proceeds before this competition resolves, representations may be influenced by the preliminary activations present at the time of learning. In three experiments using word learning as a model domain, we provide evidence that learning reflects the ongoing dynamics of auditory and visual processing during a learning event. These results show that learning can occur before stimulus recognition processes are complete; learning does not wait for ongoing perceptual processing to complete. PMID:27471082

Digital case-based learning system in school

PubMed Central

Gu, Peipei

2017-01-01

With the continuing growth of multi-media learning resources, it is important to offer methods helping learners to explore and acquire relevant learning information effectively. As services that organize multi-media learning materials together to support programming learning, the digital case-based learning system is needed. In order to create a case-oriented e-learning system, this paper concentrates on the digital case study of multi-media resources and learning processes with an integrated framework. An integration of multi-media resources, testing and learning strategies recommendation as the learning unit is proposed in the digital case-based learning framework. The learning mechanism of learning guidance, multi-media materials learning and testing feedback is supported in our project. An improved personalized genetic algorithm which incorporates preference information and usage degree into the crossover and mutation process is proposed to assemble the personalized test sheet for each learner. A learning strategies recommendation solution is proposed to recommend learning strategies for learners to help them to learn. The experiments are conducted to prove that the proposed approaches are capable of constructing personalized sheets and the effectiveness of the framework. PMID:29107965

The Effect of Animation in Multimedia Computer-Based Learning and Learning Style to the Learning Results

ERIC Educational Resources Information Center

Rusli, Muhammad; Negara, I. Komang Rinartha Yasa

2017-01-01

The effectiveness of a learning depends on four main elements, they are content, desired learning outcome, instructional method and the delivery media. The integration of those four elements can be manifested into a learning module which is called multimedia learning or learning by using multimedia. In learning context by using computer-based…

Learning Science, Learning about Science, Doing Science: Different goals demand different learning methods

NASA Astrophysics Data System (ADS)

Hodson, Derek

2014-10-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that recognize key differences in learning goals and criticizes the common assertion that 'current wisdom advocates that students best learn science through an inquiry-oriented teaching approach' on the grounds that conflating the distinction between learning by inquiry and engaging in scientific inquiry is unhelpful in selecting appropriate teaching/learning approaches.

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed Central

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F.

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students. PMID:28559866

How Do B-Learning and Learning Patterns Influence Learning Outcomes?

PubMed

Sáiz Manzanares, María Consuelo; Marticorena Sánchez, Raúl; García Osorio, César Ignacio; Díez-Pastor, José F

2017-01-01

Learning Management System (LMS) platforms provide a wealth of information on the learning patterns of students. Learning Analytics (LA) techniques permit the analysis of the logs or records of the activities of both students and teachers on the on-line platform. The learning patterns differ depending on the type of Blended Learning (B-Learning). In this study, we analyse: (1) whether significant differences exist between the learning outcomes of students and their learning patterns on the platform, depending on the type of B-Learning [Replacement blend (RB) vs. Supplemental blend (SB)]; (2) whether a relation exists between the metacognitive and the motivational strategies (MS) of students, their learning outcomes and their learning patterns on the platform. The 87,065 log records of 129 students (69 in RB and 60 in SB) in the Moodle 3.1 platform were analyzed. The results revealed different learning patterns between students depending on the type of B-Learning (RB vs. SB). We have found that the degree of blend, RB vs. SB, seems to condition student behavior on the platform. Learning patterns in RB environments can predict student learning outcomes. Additionally, in RB environments there is a relationship between the learning patterns and the metacognitive and (MS) of the students.

Informal learning from error in hospitals: what do we learn, how do we learn and how can informal learning be enhanced? A narrative review.

PubMed

de Feijter, Jeantine M; de Grave, Willem S; Koopmans, Richard P; Scherpbier, Albert J J A

2013-10-01

Learning from error is not just an individual endeavour. Organisations also learn from error. Hospitals provide many learning opportunities, which can be formal or informal. Informal learning from error in hospitals has not been researched in much depth so this narrative review focuses on five learning opportunities: morbidity and mortality conferences, incident reporting systems, patient claims and complaints, chart review and prospective risk analysis. For each of them we describe: (1) what can be learnt, categorised according to the seven CanMEDS competencies; (2) how it is possible to learn from them, analysed against a model of informal and incidental learning; and (3) how this learning can be enhanced. All CanMEDS competencies could be enhanced, but there was a particular focus on the roles of medical expert and manager. Informal learning occurred mostly through reflection and action and was often linked to the learning of others. Most important to enhance informal learning from these learning opportunities was the realisation of a climate of collaboration and trust. Possible new directions for future research on informal learning from error in hospitals might focus on ways to measure informal learning and the balance between formal and informal learning. Finally, 12 recommendations about how hospitals could enhance informal learning within their organisation are given.

A comparison of the weights-of-evidence method and probabilistic neural networks

USGS Publications Warehouse

Singer, Donald A.; Kouda, Ryoichi

1999-01-01

The need to integrate large quantities of digital geoscience information to classify locations as mineral deposits or nondeposits has been met by the weights-of-evidence method in many situations. Widespread selection of this method may be more the result of its ease of use and interpretation rather than comparisons with alternative methods. A comparison of the weights-of-evidence method to probabilistic neural networks is performed here with data from Chisel Lake-Andeson Lake, Manitoba, Canada. Each method is designed to estimate the probability of belonging to learned classes where the estimated probabilities are used to classify the unknowns. Using these data, significantly lower classification error rates were observed for the neural network, not only when test and training data were the same (0.02 versus 23%), but also when validation data, not used in any training, were used to test the efficiency of classification (0.7 versus 17%). Despite these data containing too few deposits, these tests of this set of data demonstrate the neural network's ability at making unbiased probability estimates and lower error rates when measured by number of polygons or by the area of land misclassified. For both methods, independent validation tests are required to ensure that estimates are representative of real-world results. Results from the weights-of-evidence method demonstrate a strong bias where most errors are barren areas misclassified as deposits. The weights-of-evidence method is based on Bayes rule, which requires independent variables in order to make unbiased estimates. The chi-square test for independence indicates no significant correlations among the variables in the Chisel Lake–Andeson Lake data. However, the expected number of deposits test clearly demonstrates that these data violate the independence assumption. Other, independent simulations with three variables show that using variables with correlations of 1.0 can double the expected number of deposits as can correlations of −1.0. Studies done in the 1970s on methods that use Bayes rule show that moderate correlations among attributes seriously affect estimates and even small correlations lead to increases in misclassifications. Adverse effects have been observed with small to moderate correlations when only six to eight variables were used. Consistent evidence of upward biased probability estimates from multivariate methods founded on Bayes rule must be of considerable concern to institutions and governmental agencies where unbiased estimates are required. In addition to increasing the misclassification rate, biased probability estimates make classification into deposit and nondeposit classes an arbitrary subjective decision. The probabilistic neural network has no problem dealing with correlated variables—its performance depends strongly on having a thoroughly representative training set. Probabilistic neural networks or logistic regression should receive serious consideration where unbiased estimates are required. The weights-of-evidence method would serve to estimate thresholds between anomalies and background and for exploratory data analysis.

Intelligent Web-Based Learning System with Personalized Learning Path Guidance

ERIC Educational Resources Information Center

Chen, C. M.

2008-01-01

Personalized curriculum sequencing is an important research issue for web-based learning systems because no fixed learning paths will be appropriate for all learners. Therefore, many researchers focused on developing e-learning systems with personalized learning mechanisms to assist on-line web-based learning and adaptively provide learning paths…

Is There a Relationship between Individual Learning, Team Learning, and Organizational Learning?

ERIC Educational Resources Information Center

Tanyaovalaksna, Sumeth; Li, Xiaobin

2013-01-01

Scholars suggest that there is a need for more research, particularly quantitative designs, that aim to examine the relationship between individual learning, team learning, and organizational learning. The purpose of this study is to investigate whether there is a relationship between perceived individual learning, team learning, and…

Approach to Learning of Sub-Degree Students in Hong Kong

ERIC Educational Resources Information Center

Chan, Yiu Man; Chan, Christine Mei Sheung

2010-01-01

The learning approaches and learning experiences of 404 sub-degree students were assessed by using a Study Process Questionnaire and a Learning Experience Questionnaire. While the learning approaches in this study meant whether students used a deep learning or surface learning approach, the learning experiences referred to students' perceptions…

Effects of Learning Support in Simulation-Based Physics Learning

ERIC Educational Resources Information Center

Chang, Kuo-En; Chen, Yu-Lung; Lin, He-Yan; Sung, Yao-Ting

2008-01-01

This paper describes the effects of learning support on simulation-based learning in three learning models: experiment prompting, a hypothesis menu, and step guidance. A simulation learning system was implemented based on these three models, and the differences between simulation-based learning and traditional laboratory learning were explored in…

A Framework for Mobile Learning for Enhancing Learning in Higher Education

ERIC Educational Resources Information Center

Barreh, Kadar Abdillahi; Abas, Zoraini Wati

2015-01-01

As mobile learning becomes increasingly pervasive, many higher education institutions have initiated a number of mobile learning initiatives to support their traditional learning modes. This study proposes a framework for mobile learning for enhancing learning in higher education. This framework for mobile learning is based on research conducted…

Peer Apprenticeship Learning in Networked Learning Communities: The Diffusion of Epistemic Learning

ERIC Educational Resources Information Center

Jamaludin, Azilawati; Shaari, Imran

2016-01-01

This article discusses peer apprenticeship learning (PAL) as situated within networked learning communities (NLCs). The context revolves around the diffusion of technologically-mediated learning in Singapore schools, where teachers begin to implement inquiry-oriented learning, consistent with 21st century learning, among students. As these schools…

Learning Science and the Science of Learning. Science Educators' Essay Collection.

ERIC Educational Resources Information Center

Bybee, Rodger W., Ed.

This yearbook addresses critical issues in science learning and teaching. Contents are divided into four sections: (1) "How Do Students Learn Science?"; (2) "Designing Curriculum for Student Learning"; (3) "Teaching That Enhances Student Learning"; and (4) "Assessing Student Learning." Papers include: (1) "How Students Learn and How Teachers…

Changing Students' Approaches to Study through Classroom Exercises.

ERIC Educational Resources Information Center

Gibbs, Graham

1983-01-01

Differentiates among learning to study, teaching study skills, and helping people learn how to learn. Concentrates on learning to learn--a developmental process in which people's conceptions of learning evolve--and describes strategies for helping students learn how to learn to change their approaches to study tasks. (JOW)

Learning preferences and learning styles: a study of Wessex general practice registrars.

PubMed Central

Lesmes-Anel, J; Robinson, G; Moody, S

2001-01-01

BACKGROUND: Experienced trainers know that individual registrars react very differently to identical learning experiences generated during the year in practice. This divergence reflects differences in registrars' learning styles. Only one study of United Kingdom (UK) general practitioners' learning styles has been undertaken. Learning style theory predicts that matching learning preference with learning style will enhance learning. This paper researches for the first time the evidence in the setting of UK general practice. AIM: To determine, for the general practice registrars within the Wessex Region, the nature of their learning preferences and learning styles and correlations between them. DESIGN OF STUDY: A descriptive confidential postal questionnaire survey. SETTING: Fifty-seven registrars identified in the Wessex Region with a minimum experience of six months in general practice. METHOD: The questionnaire gathered demographic data (sex, age, experience in general practice, years post-registration, and postgraduate qualifications). Learning preferences were elicited using a six-point Likert scale for learning experiences. The Honey and Mumford Learning Style Questionnaire (LSQ) elicited the registrars' learning styles. A second questionnaire was sent to non-responders. RESULTS: The response rate was 74%. Registrars report that interactive learning with feedback is preferred, but more passive learning formats remain valued. A wide range of learning style scores was found. The Honey and Mumford LSQ mean scores fell within the reflector-theorist quadrant. Evidence for correlations between learning preferences and learning styles was also found, in particular for the multiple choice question and audit components of summative assessment. CONCLUSION: A wide range of registrar learning styles exists in Wessex, and initial correlations are described between learning preferences and learning styles as predicted by style theory. This work sets the stage for a shared understanding and use of learning style theory to enhance professional learning throughout a GP's career. More research is needed in this domain. PMID:11462316

The Effect of Cooperative Learning Model and Kolb Learning Styles on Learning Result of the Basics of Politics

ERIC Educational Resources Information Center

Sugiharto

2015-01-01

The aims of this research were to determine the effect of cooperative learning model and learning styles on learning result. This quasi-experimental study employed a 2x2 treatment by level, involved independent variables, i.e. cooperative learning model and learning styles, and learning result as the dependent variable. Findings signify that: (1)…

Informal Learning from Error in Hospitals: What Do We Learn, How Do We Learn and How Can Informal Learning Be Enhanced? A Narrative Review

ERIC Educational Resources Information Center

de Feijter, Jeantine M.; de Grave, Willem S.; Koopmans, Richard P.; Scherpbier, Albert J. J. A.

2013-01-01

Learning from error is not just an individual endeavour. Organisations also learn from error. Hospitals provide many learning opportunities, which can be formal or informal. Informal learning from error in hospitals has not been researched in much depth so this narrative review focuses on five learning opportunities: morbidity and mortality…

Myths and legends in learning classification rules

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

A discussion is presented of machine learning theory on empirically learning classification rules. Six myths are proposed in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, universal learning algorithms, and interactive learning. Some of the problems raised are also addressed from a Bayesian perspective. Questions are suggested that machine learning researchers should be addressing both theoretically and experimentally.

[Relationship between self-directed learning with learning styles and strategies in medical students].

PubMed

Márquez U, Carolina; Fasce H, Eduardo; Pérez V, Cristhian; Ortega B, Javiera; Parra P, Paula; Ortiz M, Liliana; Matus B, Olga; Ibáñez G, Pilar

2014-11-01

Self-directed learning (SDL) skills are particularly important in medical education, considering that physicians should be able to regulate their own learning experiences. To evaluate the relationship between learning styles and strategies and self-directed learning in medical students. One hundred ninety nine first year medical students (120 males) participated in the study. Preparation for Independent Learning (EPAI) scale was used to assess self-direction. Schmeck learning strategies scale and Honey and Alonso (CHAEA) scales were used to evaluate learning styles and strategies. Theoretical learning style and deep processing learning strategy had positive correlations with self-direct learning. Medical students with theoretical styles and low retention of facts are those with greater ability to self-direct their learning. Further studies are required to determine the relationship between learning styles and strategies with SDL in medical students. The acquired knowledge will allow the adjustment of teaching strategies to encourage SDL.

Arts-Based Learning: A New Approach to Nursing Education Using Andragogy.

PubMed

Nguyen, Megan; Miranda, Joyal; Lapum, Jennifer; Donald, Faith

2016-07-01

Learner-oriented strategies focusing on learning processes are needed to prepare nursing students for complex practice situations. An arts-based learning approach uses art to nurture cognitive and emotional learning. Knowles' theory of andragogy aims to develop the skill of learning and can inform the process of implementing arts-based learning. This article explores the use and evaluation of andragogy-informed arts-based learning for teaching nursing theory at the undergraduate level. Arts-based learning activities were implemented and then evaluated by students and instructors using anonymous questionnaires. Most students reported that the activities promoted learning. All instructors indicated an interest in integrating arts-based learning into the curricula. Facilitators and barriers to mainstreaming arts-based learning were highlighted. Findings stimulate implications for prospective research and education. Findings suggest that arts-based learning approaches enhance learning by supporting deep inquiry and different learning styles. Further exploration of andragogy-informed arts-based learning in nursing and other disciplines is warranted. [J Nurs Educ. 2016;55(7):407-410.]. Copyright 2016, SLACK Incorporated.

The Relationship among Self-Regulated Learning, Procrastination, and Learning Behaviors in Blended Learning Environment

ERIC Educational Resources Information Center

Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Kato, Hiroshi; Miyagawa, Hiroyuki

2015-01-01

This research aims to investigate the relationship among the awareness of self-regulated learning (SRL), procrastination, and learning behaviors in blended learning environment. One hundred seventy nine freshmen participated in this research, conducted in the blended learning style class using learning management system. Data collection was…

Behavioral Feature Extraction to Determine Learning Styles in e-Learning Environments

ERIC Educational Resources Information Center

Fatahi, Somayeh; Moradi, Hadi; Farmad, Elaheh

2015-01-01

Learning Style (LS) is an important parameter in the learning process. Therefore, learning styles should be considered in the design, development, and implementation of e-learning environments. Consequently, an important capability of an e-learning system could be the automatic determination of a student's learning style. In this paper, a set of…

Pervasive Knowledge, Social Networks, and Cloud Computing: E-Learning 2.0

ERIC Educational Resources Information Center

Anshari, Muhammad; Alas, Yabit; Guan, Lim Sei

2015-01-01

Embedding Web 2.0 in learning processes has extended learning from traditional based learning-centred to a collaborative based learning-centred institution that emphasises learning anywhere and anytime. While deploying Semantic Web into e-learning offers a broader spectrum of pervasive knowledge acquisition to enrich users' experience in learning.…

A Mobile Gamification Learning System for Improving the Learning Motivation and Achievements

ERIC Educational Resources Information Center

Su, C-H.; Cheng, C-H.

2015-01-01

This paper aims to investigate how a gamified learning approach influences science learning, achievement and motivation, through a context-aware mobile learning environment, and explains the effects on motivation and student learning. A series of gamified learning activities, based on MGLS (Mobile Gamification Learning System), was developed and…

E-Learning Readiness in Public Secondary Schools in Kenya

ERIC Educational Resources Information Center

Ouma, Gordon O.; Awuor, Fredrick M.; Kyambo, Benjamin

2013-01-01

As e-learning becomes useful to learning institutions worldwide, an assessment of e-learning readiness is essential for the successful implementation of e-learning as a platform for learning. Success in e-learning can be achieved by understanding the level of readiness of e-learning environments. To facilitate schools in Kenya to implement…

Blended Learning in a Teacher Training Course: Integrated Interactive E-Learning and Contact Learning

ERIC Educational Resources Information Center

Kupetz, Rita; Ziegenmeyer, Brigit

2005-01-01

The paper discusses a blended learning concept for a university teacher training course for prospective teachers of English. The concept aims at purposeful learning using different methods and activities, various traditional and electronic media, learning spaces covering contact and distance learning, and task-based learning modules that begin…

Learning from Success: A Leverage for Transforming Schools Into Learning Communities

ERIC Educational Resources Information Center

Schechter, Chen; Sykes, Israel; Rosenfeld, Jona

2004-01-01

Teachers must learn to learn, and thereby develop their abilities to engage in ongoing learning so as to survive and thrive in turbulent and uncertain learning environments. Here, Schechterl discuss the importance of collective retrospective learning as an inbuilt vehicle in the ongoing pursuit toward learning schools. They also explore on the…

Learning Science, Learning about Science, Doing Science: Different Goals Demand Different Learning Methods

ERIC Educational Resources Information Center

Hodson, Derek

2014-01-01

This opinion piece paper urges teachers and teacher educators to draw careful distinctions among four basic learning goals: learning science, learning about science, doing science and learning to address socio-scientific issues. In elaboration, the author urges that careful attention is paid to the selection of teaching/learning methods that…

Prior Learning Assessment: U.S. Experience Facilitating Lifelong Learning.

ERIC Educational Resources Information Center

Mann, Carolyn M.

This paper focuses on the role of prior learning assessment in the life long learning of adults in the United States. The introduction stresses the increasing importance of life long learning in American society. The second section reviews prior learning and its assessment. Prior learning is formally defined as learning which has been acquired…

Can Cooperative Learning Achieve the Four Learning Outcomes of Physical Education? A Review of Literature

ERIC Educational Resources Information Center

Casey, Ashley; Goodyear, Victoria A.

2015-01-01

Physical learning, cognitive learning, social learning, and affective learning are positioned as the legitimate learning outcomes of physical education. It has been argued that these four learning outcomes go toward facilitating students' engagement with the physically active life (Bailey et al., 2009; Kirk, 2013). With Cooperative Learning…

Effects of Teaching and Learning Styles on Students' Reflection Levels for Ubiquitous Learning

ERIC Educational Resources Information Center

Hsieh, Sheng-Wen; Jang, Yu-Ruei; Hwang, Gwo-Jen; Chen, Nian-Shing

2011-01-01

Ubiquitous learning (u-learning), in conjunction with supports from the digital world, is recognized as an effective approach for situating students in real-world learning environments. Earlier studies concerning u-learning have mainly focused on investigating the learning attitudes and learning achievements of students, while the causations such…

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

ERIC Educational Resources Information Center

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…

Learning to Learn in the European Reference Framework for Lifelong Learning

ERIC Educational Resources Information Center

Pirrie, Anne; Thoutenhoofd, Ernst D.

2013-01-01

This article explores the construction of learning to learn that is implicit in the document "Key Competences for Lifelong Learning--European Reference Framework" and related education policy from the European Commission. The authors argue that the hallmark of learning to learn is the development of a fluid sociality rather than the…

Teachers' Everyday Professional Development: Mapping Informal Learning Activities, Antecedents, and Learning Outcomes

ERIC Educational Resources Information Center

Kyndt, Eva; Gijbels, David; Grosemans, Ilke; Donche, Vincent

2016-01-01

Although a lot is known about teacher development by means of formal learning activities, research on teachers' everyday learning is limited. In the current systematic review, we analyzed 74 studies focusing on teachers' informal learning to identify teachers' learning activities, antecedents for informal learning, and learning outcomes. In…

Mobile Formative Assessment Tool Based on Data Mining Techniques for Supporting Web-Based Learning

ERIC Educational Resources Information Center

Chen, Chih-Ming; Chen, Ming-Chuan

2009-01-01

Current trends clearly indicate that online learning has become an important learning mode. However, no effective assessment mechanism for learning performance yet exists for e-learning systems. Learning performance assessment aims to evaluate what learners learned during the learning process. Traditional summative evaluation only considers final…

Preference Learning Style in Engineering Mathematics: Students' Perception of E-Learning

ERIC Educational Resources Information Center

Tawil, Norngainy Mohd; Ismail, Nur Arzilah; Asshaari, Izamarlina; Othman, Haliza; Zaharim, Azami; Bahaludin, Hafizah

2013-01-01

Nowadays, traditional learning styles are assisted with e-learning components to ensure the effectiveness of the teaching and learning process, especially for the students. This approach is known as blended learning. Objective of this paper is to investigate and clarify the students' preferences in learning style, either traditional or e-learning.…

A Joyful Classroom Learning System with Robot Learning Companion for Children to Learn Mathematics Multiplication

ERIC Educational Resources Information Center

Wei, Chun-Wang; Hung, I-Chun; Lee, Ling; Chen, Nian-Shing

2011-01-01

This research demonstrates the design of a Joyful Classroom Learning System (JCLS) with flexible, mobile and joyful features. The theoretical foundations of this research include the experiential learning theory, constructivist learning theory and joyful learning. The developed JCLS consists of the robot learning companion (RLC), sensing input…

A Service Oriented Architecture to Integrate Mobile Assessment in Learning Management Systems

ERIC Educational Resources Information Center

Riad, A. M.; El-Ghareeb, H. A.

2008-01-01

Mobile Learning (M-Learning) is an approach to E-Learning that utilizes mobile devices. Learning Management System (LMS) should enable M-Learning. Unfortunately, M-Learning is not the same at each educational institution. Assessment is one of the learning activities that can be achieved electronically and via mobile device. Mobile assessment…

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

NASA Astrophysics Data System (ADS)

Kim, Dong Won; Yao, Jingtao

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

Improving the quality of learning in science through optimization of lesson study for learning community

NASA Astrophysics Data System (ADS)

Setyaningsih, S.

2018-03-01

Lesson Study for Learning Community is one of lecturer profession building system through collaborative and continuous learning study based on the principles of openness, collegiality, and mutual learning to build learning community in order to form professional learning community. To achieve the above, we need a strategy and learning method with specific subscription technique. This paper provides a description of how the quality of learning in the field of science can be improved by implementing strategies and methods accordingly, namely by applying lesson study for learning community optimally. Initially this research was focused on the study of instructional techniques. Learning method used is learning model Contextual teaching and Learning (CTL) and model of Problem Based Learning (PBL). The results showed that there was a significant increase in competence, attitudes, and psychomotor in the four study programs that were modelled. Therefore, it can be concluded that the implementation of learning strategies in Lesson study for Learning Community is needed to be used to improve the competence, attitude and psychomotor of science students.

Active Learning Not Associated with Student Learning in a Random Sample of College Biology Courses

PubMed Central

Andrews, T. M.; Leonard, M. J.; Colgrove, C. A.; Kalinowski, S. T.

2011-01-01

Previous research has suggested that adding active learning to traditional college science lectures substantially improves student learning. However, this research predominantly studied courses taught by science education researchers, who are likely to have exceptional teaching expertise. The present study investigated introductory biology courses randomly selected from a list of prominent colleges and universities to include instructors representing a broader population. We examined the relationship between active learning and student learning in the subject area of natural selection. We found no association between student learning gains and the use of active-learning instruction. Although active learning has the potential to substantially improve student learning, this research suggests that active learning, as used by typical college biology instructors, is not associated with greater learning gains. We contend that most instructors lack the rich and nuanced understanding of teaching and learning that science education researchers have developed. Therefore, active learning as designed and implemented by typical college biology instructors may superficially resemble active learning used by education researchers, but lacks the constructivist elements necessary for improving learning. PMID:22135373

Social learning across psychological distance.

PubMed

Kalkstein, David A; Kleiman, Tali; Wakslak, Cheryl J; Liberman, Nira; Trope, Yaacov

2016-01-01

While those we learn from are often close to us, more and more our learning environments are shifting to include more distant and dissimilar others. The question we examine in 5 studies is how whom we learn from influences what we learn and how what we learn influences from whom we choose to learn it. In Study 1, we show that social learning, in and of itself, promotes higher level (more abstract) learning than does learning based on one's own direct experience. In Studies 2 and 3, we show that when people learn from and emulate others, they tend to do so at a higher level when learning from a distant model than from a near model. Studies 4 and 5 show that thinking about learning at a higher (compared to a lower) level leads individuals to expand the range of others that they will consider learning from. Study 6 shows that when given an actual choice, people prefer to learn low-level information from near sources and high-level information from distant sources. These results demonstrate a basic link between level of learning and psychological distance in social learning processes. (c) 2016 APA, all rights reserved).

The involvement of model-based but not model-free learning signals during observational reward learning in the absence of choice.

PubMed

Dunne, Simon; D'Souza, Arun; O'Doherty, John P

2016-06-01

A major open question is whether computational strategies thought to be used during experiential learning, specifically model-based and model-free reinforcement learning, also support observational learning. Furthermore, the question of how observational learning occurs when observers must learn about the value of options from observing outcomes in the absence of choice has not been addressed. In the present study we used a multi-armed bandit task that encouraged human participants to employ both experiential and observational learning while they underwent functional magnetic resonance imaging (fMRI). We found evidence for the presence of model-based learning signals during both observational and experiential learning in the intraparietal sulcus. However, unlike during experiential learning, model-free learning signals in the ventral striatum were not detectable during this form of observational learning. These results provide insight into the flexibility of the model-based learning system, implicating this system in learning during observation as well as from direct experience, and further suggest that the model-free reinforcement learning system may be less flexible with regard to its involvement in observational learning. Copyright © 2016 the American Physiological Society.

The ergonomics of learning: educational design and learning performance.

PubMed

Smith, T J

2007-10-01

The application of ergonomics/human factors (E/HF) principles and practices, and the implementation of ergonomics programmes, have achieved proven success in improving performance, productivity, competitiveness, and safety and health in most occupational sectors. However, the benefits that the application of E/HF science might bring to promoting student learning have yet to be widely recognized. This paper deals with the fundamental purpose of education - student learning - and with the question of how the ergonomic design of the learning environment influences learning performance. The underlying premise, embodied in the quote below, is that student learning performance to a substantial degree is context specific - influenced and specialized in relation to specific design factors in the learning environment. The basic scientific question confronting learning ergonomics is which design characteristics in the learning environment have the greatest influence on variability in learning performance. Practically, the basic challenge is to apply this scientific understanding to ergonomic interventions directed at design improvements of learning environments to benefit learning. This paper expands upon these themes by addressing the origins and scope of learning ergonomics, differing perspectives on the nature of learning, evidence for context specificity in learning and conclusions and research implications regarding an ergonomics perspective on learning.

Myths and legends in learning classification rules

NASA Technical Reports Server (NTRS)

Buntine, Wray

1990-01-01

This paper is a discussion of machine learning theory on empirically learning classification rules. The paper proposes six myths in the machine learning community that address issues of bias, learning as search, computational learning theory, Occam's razor, 'universal' learning algorithms, and interactive learnings. Some of the problems raised are also addressed from a Bayesian perspective. The paper concludes by suggesting questions that machine learning researchers should be addressing both theoretically and experimentally.

An exploration of the relationship between academic and experiential learning approaches in vocational education.

PubMed

de Jong, Jan A Stavenga; Wierstra, Ronny F A; Hermanussen, José

2006-03-01

Research on individual learning approaches (or learning styles) is split in two traditions, one of which is biased towards academic learning, and the other towards learning from direct experience. In the reported study, the two traditions are linked by investigating the relationships between school-based (academic) and work-based (experiential) learning approaches of students in vocational education programs. Participants were 899 students of a Dutch school for secondary vocational education; 758 provided data on school-based learning, and 407 provided data on work-based learning, resulting in an overlap of 266 students from whom data were obtained on learning in both settings. Learning approaches in school and work settings were measured with questionnaires. Using factor analysis and cluster analysis, items and students were grouped, both with respect to school- and work-based learning. The study identified two academic learning dimensions (constructive learning and reproductive learning), and three experiential learning dimensions (analysis, initiative, and immersion). Construction and analysis were correlated positively, and reproduction and initiative negatively. Cluster analysis resulted in the identification of three school-based learning orientations and three work-based learning orientations. The relation between the two types of learning orientations, expressed in Cramér's V, appeared to be weak. It is concluded that learning approaches are relatively context specific, which implies that neither theoretical tradition can claim general applicability.

Effectiveness of E-Learning for Students Vocational High School Building Engineering Program

NASA Astrophysics Data System (ADS)

Soeparno; Muslim, Supari

2018-04-01

Implementation of vocational learning in accordance with the 2013 curriculum must meet the criteria, one of which is learning to be consistent with advances in technology and information. Technology-based learning in vocational commonly referred to as E-Learning, online (in the network) and WBL (Web-Based Learning). Facts on the ground indicate that based learning technology and information on Vocational High School of Building Engineering is still not going well. The purpose of this research is to know: advantages and disadvantages of learning with E-Learning, conformity of learning with E-Learning with characteristics of students on Vocational High School of Building Engineering and effective learning method based on E-Learning for students on Vocational High School of Building Engineering. Research done by literature method, get the following conclusion as follow: the advantages of E-Learning is learning can be done anywhere and anytime, efficient in accessing materials and tasks, ease of communication and discussion; while the shortage is the need for additional costs for good internet access and lack of social interaction between teachers and students. E-learning is appropriate to basic knowledge competencies, and not appropriate at the level of advanced competencies and skills. Effective E-Learning Based Learning Method on Vocational High School of Building Engineering is a Blended method that is a mix between conventional method and e-learning.

Deep imitation learning for 3D navigation tasks.

PubMed

Hussein, Ahmed; Elyan, Eyad; Gaber, Mohamed Medhat; Jayne, Chrisina

2018-01-01

Deep learning techniques have shown success in learning from raw high-dimensional data in various applications. While deep reinforcement learning is recently gaining popularity as a method to train intelligent agents, utilizing deep learning in imitation learning has been scarcely explored. Imitation learning can be an efficient method to teach intelligent agents by providing a set of demonstrations to learn from. However, generalizing to situations that are not represented in the demonstrations can be challenging, especially in 3D environments. In this paper, we propose a deep imitation learning method to learn navigation tasks from demonstrations in a 3D environment. The supervised policy is refined using active learning in order to generalize to unseen situations. This approach is compared to two popular deep reinforcement learning techniques: deep-Q-networks and Asynchronous actor-critic (A3C). The proposed method as well as the reinforcement learning methods employ deep convolutional neural networks and learn directly from raw visual input. Methods for combining learning from demonstrations and experience are also investigated. This combination aims to join the generalization ability of learning by experience with the efficiency of learning by imitation. The proposed methods are evaluated on 4 navigation tasks in a 3D simulated environment. Navigation tasks are a typical problem that is relevant to many real applications. They pose the challenge of requiring demonstrations of long trajectories to reach the target and only providing delayed rewards (usually terminal) to the agent. The experiments show that the proposed method can successfully learn navigation tasks from raw visual input while learning from experience methods fail to learn an effective policy. Moreover, it is shown that active learning can significantly improve the performance of the initially learned policy using a small number of active samples.

Medical student use of digital learning resources.

PubMed

Scott, Karen; Morris, Anne; Marais, Ben

2018-02-01

University students expect to use technology as part of their studies, yet health professional teachers can struggle with the change in student learning habits fuelled by technology. Our research aimed to document the learning habits of contemporary medical students during a clinical rotation by exploring the use of locally and externally developed digital and print self-directed learning resources, and study groups. We investigated the learning habits of final-stage medical students during their clinical paediatric rotation using mixed methods, involving learning analytics and a student questionnaire. Learning analytics tracked aggregate student usage statistics of locally produced e-learning resources on two learning management systems and mobile learning resources. The questionnaire recorded student-reported use of digital and print learning resources and study groups. The students made extensive use of digital self-directed learning resources, especially in the 2 weeks before the examination, which peaked the day before the written examination. All students used locally produced digital formative assessment, and most (74/98; 76%) also used digital resources developed by other institutions. Most reported finding locally produced e-learning resources beneficial for learning. In terms of traditional forms of self-directed learning, one-third (28/94; 30%) indicated that they never read the course textbook, and few students used face-to-face 39/98 (40%) or online 6/98 (6%) study groups. Learning analytics and student questionnaire data confirmed the extensive use of digital resources for self-directed learning. Through clarification of learning habits and experiences, we think teachers can help students to optimise effective learning strategies; however, the impact of contemporary learning habits on learning efficacy requires further evaluation. Health professional teachers can struggle with the change in student learning habits fuelled by technology. © 2017 John Wiley & Sons Ltd and The Association for the Study of Medical Education.

Linking Learning, Teaching, and Development.

ERIC Educational Resources Information Center

Fiddler, Morris; Marienau, Catherine

1995-01-01

Learning-centered teaching links learning and development by creating a climate of exchange; using assessment to increase awareness of learning needs; promoting learning to learn; holding learners accountable; using multiple strategies for different learning styles; and involving learners in realistic and challenging goals. (SK)

Building a Global Learning Organization: Lessons from the World's Top Corporations.

ERIC Educational Resources Information Center

Marquardt, Michael J.

1995-01-01

Research on 50 organizations elicited 19 attributes of learning organizations: individual learning, group learning, streamlined structure, corporate learning culture, empowerment, environmental scanning, knowledge creation/transfer, learning technology, quality, learning strategy, supportive atmosphere, teamwork/networking, vision, acculturation,…

The Effect of Learning Type and Avatar Similarity on Learning Outcomes in Educational Video Games

ERIC Educational Resources Information Center

Lewis, Melissa L.

2009-01-01

Two theories guide two very different ideas about learning. Social cognitive theory (Bandura, 1977, 1989) places the greater emphasis on observational learning, or learning by watching a model produce a behavior before doing it oneself. Other researchers purport that experiential learning, or learning by doing, results in stronger learning (Kolb,…

The Effects of Learning Styles and Meaningful Learning on the Learning Achievement of Gamification Health Education Curriculum

ERIC Educational Resources Information Center

Fan, Kuo-Kuang; Xiao, Peng-wei; Su, Chung-Ho

2015-01-01

This study aims to discuss the correlations among learning styles, meaningful learning, and learning achievement. Directed at the rather difficult to comprehend human blood circulation unit in the biology materials for junior high school students, a Mobile Meaningful Blood Circulation Learning System, called MMBCLS gamification learning, was…

Towards a Model for M-Learning in Africa

ERIC Educational Resources Information Center

Brown, Tom H.

2005-01-01

Mobile learning (m-learning) is a natural extension of electronic learning (e-learning) and has the potential to make learning even more widely available and accessible than we are used to in existing e-learning environments. The role that communication and interaction plays in the learning process is a critical success factor. It is within this…

Empirical Validation of the Importance of Employees' Learning Motivation for Workplace E-Learning in Taiwanese Organisations

ERIC Educational Resources Information Center

Chen, Hsiu-Ju; Kao, Chia-Hung

2012-01-01

E-learning systems, adopted by organisations for employee training to enhance employees' performance, are characterised by self-directed, autonomous learning. Learning motivation is then of importance in the design of e-learning practices in workplace. However, empirical study of the alignment of e-learning with individual learning needs and…

An Examination through Conjoint Analysis of the Preferences of Students Concerning Online Learning Environments According to Their Learning Styles

ERIC Educational Resources Information Center

Daghan, Gökhan; Akkoyunlu, Buket

2012-01-01

This study examines learning styles of students receiving education via online learning environments, and their preferences concerning the online learning environment. Maggie McVay Lynch Learning Style Inventory was used to determine learning styles of the students. The preferences of students concerning online learning environments were detected…

Yet Another Adaptive Learning Management System Based on Felder and Silverman's Learning Styles and Mashup

ERIC Educational Resources Information Center

Chang, Yi-Hsing; Chen, Yen-Yi; Chen, Nian-Shing; Lu, You-Te; Fang, Rong-Jyue

2016-01-01

This study designs and implements an adaptive learning management system based on Felder and Silverman's Learning Style Model and the Mashup technology. In this system, Felder and Silverman's Learning Style model is used to assess students' learning styles, in order to provide adaptive learning to leverage learners' learning preferences.…

What Is Learned when Concept Learning Fails?--A Theory of Restricted-Domain Relational Learning

ERIC Educational Resources Information Center

Wright, Anthony A.; Lickteig, Mark T.

2010-01-01

Two matching-to-sample (MTS) and four same/different (S/D) experiments employed tests to distinguish between item-specific learning and relational learning. One MTS experiment showed item-specific learning when concept learning failed (i.e., no novel-stimulus transfer). Another MTS experiment showed item-specific learning when pigeons'…

Learning Environments Designed According to Learning Styles and Its Effects on Mathematics Achievement

ERIC Educational Resources Information Center

Özerem, Aysen; Akkoyunlu, Buket

2015-01-01

Problem Statement: While designing a learning environment it is vital to think about learner characteristics (learning styles, approaches, motivation, interests… etc.) in order to promote effective learning. The learning environment and learning process should be designed not to enable students to learn in the same manner and at the same level,…

The Future of Learning: From eLearning to mLearning.

ERIC Educational Resources Information Center

Keegan, Desmond

The future of electronic learning was explored in an analysis that viewed the provision of learning at a distance as a continuum and traced the evolution from distance learning to electronic learning to mobile learning in Europe and elsewhere. Special attention was paid to the following topics: (1) the impact of the industrial revolution, the…

A Comparison of Learning Outcomes for Adult Students in On-Site and Online Service-Learning

ERIC Educational Resources Information Center

Schwehm, Jeremy S.; Lasker-Scott, Tennille; Elufiede, Oluwakemi

2017-01-01

As noted by Kolb's (1984) experiential learning theory, adults learn best through experiences. Typically delivered in a traditional, face-to-face classroom setting, service-learning integrates the knowledge learned in the classroom with real-world experience and community service. E-service-learning, service-learning delivered in part or entirely…

From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

ERIC Educational Resources Information Center

Yu, Shengquan; Yang, Xianmin; Cheng, Gang; Wang, Minjuan

2015-01-01

This paper presents a new model for organizing learning resources: Learning Cell. This model is open, evolving, cohesive, social, and context-aware. By introducing a time dimension into the organization of learning resources, Learning Cell supports the dynamic evolution of learning resources while they are being used. In addition, by introducing a…

Organizational Learning as an Analogy to Individual Learning? A Case of Augmented Interaction Intensity

ERIC Educational Resources Information Center

Döös, Marianne; Johansson, Peter; Wilhelmson, Lena

2015-01-01

This paper attempts to explore an analogy between individual and organizational learning within experiential learning theory (ELT). The focus is on both the possibility of identifying a learning subject that learns in action, and on the genesis process behind the learning of a suggested learning subject at organizational level. The exploration…

Design and Implementation of C-iLearning: A Cloud-Based Intelligent Learning System

ERIC Educational Resources Information Center

Xiao, Jun; Wang, Minjuan; Wang, Lamei; Zhu, Xiaoxiao

2013-01-01

The gradual development of intelligent learning (iLearning) systems has prompted the changes of teaching and learning. This paper presents the architecture of an intelligent learning (iLearning) system built upon the recursive iLearning model and the key technologies associated with this model. Based on this model and the technical structure of a…

Distance Learning: A Way of Life-Long Learning

DTIC Science & Technology

2005-09-01

promise of future benefits. 15. SUBJECT TERMS training, educational technology , distributed learning , distance learning , collaboration, online instruction...knowledge." - Aristotle Introduction Modern learning technology assumes various names: distance learning , distributed training, computer-based...training, web-based learning , or advanced distributed learning . No matter the name, the basic concept is using computer technology for instruction with no

Developing the OBTL Curriculum with Blended Learning to Enhance Student Learning Effectiveness in the Undergraduate ECE Program

ERIC Educational Resources Information Center

Leung, Chi-hung

2012-01-01

Background: The project included continuous assessment, group presentation, self-learning, and individual assignment to assess students' learning outcomes. A self-learning system was set up as e-learning for students to monitor their learning progress during the semester, including two online exercises and a checklist of learning outcomes. The…

Learning Rationales and Virtual Reality Technology in Education.

ERIC Educational Resources Information Center

Chiou, Guey-Fa

1995-01-01

Defines and describes virtual reality technology and differentiates between virtual learning environment, learning material, and learning tools. Links learning rationales to virtual reality technology to pave conceptual foundations for application of virtual reality technology education. Constructivism, case-based learning, problem-based learning,…

A theory of local learning, the learning channel, and the optimality of backpropagation.

PubMed

Baldi, Pierre; Sadowski, Peter

2016-11-01

In a physical neural system, where storage and processing are intimately intertwined, the rules for adjusting the synaptic weights can only depend on variables that are available locally, such as the activity of the pre- and post-synaptic neurons, resulting in local learning rules. A systematic framework for studying the space of local learning rules is obtained by first specifying the nature of the local variables, and then the functional form that ties them together into each learning rule. Such a framework enables also the systematic discovery of new learning rules and exploration of relationships between learning rules and group symmetries. We study polynomial local learning rules stratified by their degree and analyze their behavior and capabilities in both linear and non-linear units and networks. Stacking local learning rules in deep feedforward networks leads to deep local learning. While deep local learning can learn interesting representations, it cannot learn complex input-output functions, even when targets are available for the top layer. Learning complex input-output functions requires local deep learning where target information is communicated to the deep layers through a backward learning channel. The nature of the communicated information about the targets and the structure of the learning channel partition the space of learning algorithms. For any learning algorithm, the capacity of the learning channel can be defined as the number of bits provided about the error gradient per weight, divided by the number of required operations per weight. We estimate the capacity associated with several learning algorithms and show that backpropagation outperforms them by simultaneously maximizing the information rate and minimizing the computational cost. This result is also shown to be true for recurrent networks, by unfolding them in time. The theory clarifies the concept of Hebbian learning, establishes the power and limitations of local learning rules, introduces the learning channel which enables a formal analysis of the optimality of backpropagation, and explains the sparsity of the space of learning rules discovered so far. Copyright © 2016 Elsevier Ltd. All rights reserved.

The New School-Based Learning (SBL) to Work-Based Learning (WBL) Transition Module: A Practical Implementation in the Technical and Vocational Education (TVE) System in Bahrain

NASA Astrophysics Data System (ADS)

Alseddiqi, M.; Mishra, R.; Pislaru, C.

2012-05-01

This paper diagnoses the implementation of a new engineering course entitled 'school-based learning (SBL) to work-based learning (WBL) transition module' in the Bahrain Technical and Vocational Education (TVE) learning environment. The module was designed to incorporate an innovative education and training approach with a variety of learning activities that are included in various learning case studies. Each case study was based on with learning objectives coupled with desired learning outcomes. The TVE students should meet the desired outcomes after the completion of the learning activities and assessments. To help with the implementation phase of the new module, the authors developed guidelines for each case study. The guidelines incorporated learning activities to be delivered in an integrated learning environment. The skills to be transferred were related to cognitive, affective, and technical proficiencies. The guidelines included structured instructions to help students during the learning process. In addition, technology was introduced to improve learning effectiveness and flexibility. The guidelines include learning indicators for each learning activity and were based on their interrelation with competencies to be achieved with respect to modern industrial requirements. Each learning indicator was then correlated against the type of learning environment, teaching and learning styles, examples of mode of delivery, and assessment strategy. Also, the learning activities were supported by technological features such as discussion forums for social perception and engagement and immediate feedback exercises for self-motivation. Through the developed module, TVE teachers can effectively manage the teaching and learning process as well as the assessment strategy to satisfy students' individual requirements and enable them to meet workplace requirements.

Magic Learning Pill: Ontological and Instrumental Learning in Order to Speed Up Education.

PubMed

Matusov, Eugene; Baker, Daniella; Fan, Yueyue; Choi, Hye Jung; L Hampel, Robert

2017-09-01

The purpose of this research is to investigate the phenomenology of learning - people"s attitudes toward their learning experiences that have inherent worth in themselves (i.e., ontological learning) or have value outside of the learning itself (i.e., instrumental learning). In order to explore this topic, 58 participants from the U.S., Russia, and Brazil were interviewed with a central question derived from the science fiction writer Isaac Asimov's short story "Profession": whether participants would take a "Magic Learning Pill" (MLP) to avoid the process of learning, and instead magically acquire the knowledge. The MLP would guarantee the immediate learning by skipping the process of learning while achieving the same effect of gaining skills and knowledge. Almost all participants could think of some learning experiences for which they would take MLP and others for which they would not. Many participants would not take MLP for ontological learning, which is learning experiences that have inherent value for the people, while they would take MLP for instrumental learning, which is learning that mainly serves some other non-educational purposes. The main finding suggests that both instrumental and ontological types of learning are recognized by a wide range of people from diverse cultures as present and valued in their lives. This is especially significant in light of the overwhelmingly instrumental tone of public discourse about education. In the context of formal education, ontological learning was mentioned 35 times (28.0%) while instrumental learning was mentioned 74 times (60.2%). Although ontological learning was often mentioned as taking place outside of school, incorporating pedagogy supporting ontological learning at school deserves consideration.

Merging Problem-Based Learning with Simulation-Based Learning in the Medical Undergraduate Curriculum: The PAIRED Framework for Enhancing Lifelong Learning

PubMed Central

Koh, Jansen

2016-01-01

Lifelong learning is an essential trait that is expected of every physician. The CanMeds 2005 Physician Competency Framework emphasizes lifelong learning as a key competency that physicians must achieve in becoming better physicians. However, many physicians are not competent at engaging in lifelong learning. The current medical education system is deficient in preparing medical students to develop and carry out their own lifelong learning curriculum upon graduation. Despite understanding how physicians learn at work, medical students are not trained to learn while working. Similarly, although barriers to lifelong learning are known, medical students are not adequately skilled in overcoming these barriers. Learning to learn is just as important, if not more, as acquiring the skills and knowledge required of a physician. The medical undergraduate curriculum lacks a specific learning strategy to prepare medical students in becoming an adept lifelong learner. In this article, we propose a learning strategy for lifelong learning at the undergraduate level. In developing this novel strategy, we paid particular attention to two parameters. First, this strategy should be grounded on literature describing a physician’s lifelong learning process. Second, the framework for implementing this strategy must be based on existing undergraduate learning strategies to obviate the need for additional resources, learner burden, and faculty time. In this paper, we propose a Problem, Analysis, Independent Research Reporting, Experimentation Debriefing (PAIRED) framework that follows the learning process of a physician and serves to synergize the components of problem-based learning and simulation-based learning in specifically targeting the barriers to lifelong learning. PMID:27446767

A phenomenological research study: Perspectives of student learning through small group work between undergraduate nursing students and educators.

PubMed

Wong, Florence Mei Fung

2018-06-18

Small group work is an effective teaching-learning approach in nursing education to enhance students' learning in theoretical knowledge and skill development. Despite its potential advantageous effects on learning, little is known about its actual effects on students' learning from students' and educators' perspectives. To understand students' learning through small group work from the perspectives of students and educators. A qualitative study with focus group interviews was carried out. Semi-structured interviews with open-ended questions were performed with 13 undergraduate nursing students and 10 educators. Four main themes, "initiative learning", "empowerment of interactive group dynamics", "factors for creating effective learning environment", and "barriers influencing students' learning", were derived regarding students' learning in small group work based on the perspectives of the participants. The results showed the importance of learning attitudes of students in individual and group learning. Factors for creating an effective learning environment, including preference for forming groups, effective group size, and adequacy of discussion, facilitate students' learning with the enhancement of learning engagement in small group work. The identified barriers, such as "excessive group work", "conflicts", and "passive team members" can reduce students' motivation and enjoyment of learning. Small group work is recognized as an effective teaching method for knowledge enhancement and skill development in nursing education. All identified themes are important to understand the initiatives of students and group learning, factors influencing an effective learning environment, and barriers hindering students' learning. Nurse educators should pay more attention to the factors that influence an effective learning environment and reduce students' commitment and group dynamics. Moreover, students may need further support to reduce barriers that impede students' learning motivation and enjoyment. Copyright © 2018 Elsevier Ltd. All rights reserved.

Attention Cueing and Activity Equally Reduce False Alarm Rate in Visual-Auditory Associative Learning through Improving Memory.

PubMed

Nikouei Mahani, Mohammad-Ali; Haghgoo, Hojjat Allah; Azizi, Solmaz; Nili Ahmadabadi, Majid

2016-01-01

In our daily life, we continually exploit already learned multisensory associations and form new ones when facing novel situations. Improving our associative learning results in higher cognitive capabilities. We experimentally and computationally studied the learning performance of healthy subjects in a visual-auditory sensory associative learning task across active learning, attention cueing learning, and passive learning modes. According to our results, the learning mode had no significant effect on learning association of congruent pairs. In addition, subjects' performance in learning congruent samples was not correlated with their vigilance score. Nevertheless, vigilance score was significantly correlated with the learning performance of the non-congruent pairs. Moreover, in the last block of the passive learning mode, subjects significantly made more mistakes in taking non-congruent pairs as associated and consciously reported lower confidence. These results indicate that attention and activity equally enhanced visual-auditory associative learning for non-congruent pairs, while false alarm rate in the passive learning mode did not decrease after the second block. We investigated the cause of higher false alarm rate in the passive learning mode by using a computational model, composed of a reinforcement learning module and a memory-decay module. The results suggest that the higher rate of memory decay is the source of making more mistakes and reporting lower confidence in non-congruent pairs in the passive learning mode.

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept.

PubMed

Cooper, Katelyn M; Ashley, Michael; Brownell, Sara E

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning.

Using Expectancy Value Theory as a Framework to Reduce Student Resistance to Active Learning: A Proof of Concept

PubMed Central

Cooper, Katelyn M.; Ashley, Michael; Brownell, Sara E.

2017-01-01

There has been a national movement to transition college science courses from passive lectures to active learning environments. Active learning has been shown to be a more effective way for students to learn, yet there is concern that some students are resistant to active learning approaches. Although there is much discussion about student resistance to active learning, few studies have explored this topic. Furthermore, a limited number of studies have applied theoretical frameworks to student engagement in active learning. We propose using a theoretical lens of expectancy value theory to understand student resistance to active learning. In this study, we examined student perceptions of active learning after participating in 40 hours of active learning. We used the principal components of expectancy value theory to probe student experience in active learning: student perceived self-efficacy in active learning, value of active learning, and potential cost of participating in active learning. We found that students showed positive changes in the components of expectancy value theory and reported high levels of engagement in active learning, which provide proof of concept that expectancy value theory can be used to boost student perceptions of active learning and their engagement in active learning classrooms. From these findings, we have built a theoretical framework of expectancy value theory applied to active learning. PMID:28861130

Learning To Serve, Serving To Learn: A View from Higher Education. Integrating Service-Learning into Curriculum: Lessons Learned. Teacher Education Consortium in Service-Learning.

ERIC Educational Resources Information Center

2003

This collection of papers includes lessons learned from a 3-year collaboration among faculty who had pursued a scholarly inquiry of service-learning, integrated service-learning into their curricula, altered their teaching, forged partnerships with community based organizations, and developed measures and methodologies for assessing results. The…

Learning about Learning: A Conundrum and a Possible Resolution

ERIC Educational Resources Information Center

Barnett, Ronald

2011-01-01

What is it to learn in the modern world? We can identify four "learning epochs" through which our understanding of learning has passed: a metaphysical view; an empirical view; an experiential view; and, currently, a "learning-amid-contestation" view. In this last and current view, learning has its place in a world in which, the more one learns,…

Learning "in" or "with" Games? Quality Criteria for Digital Learning Games from the Perspectives of Learning, Emotion, and Motivation Theory

ERIC Educational Resources Information Center

Hense, Jan; Mandl, Heinz

2012-01-01

This conceptual paper aims to clarify the theoretical underpinnings of game based learning (GBL) and learning with digital learning games (DLGs). To do so, it analyses learning of game related skills and contents, which occurs constantly during playing conventional entertainment games, from three perspectives: learning theory, emotion theory, and…

Comparing Learning Outcomes of Blended Learning and Traditional Face-to-Face Learning of University Students in ESL Courses

ERIC Educational Resources Information Center

Zhang, Wei; Zhu, Chang

2018-01-01

Combining elements of online and face-to-face education, blended learning is emerging as an important teaching and learning model in higher education. In order to examine the effectiveness of blended learning, as compared to the traditional face-to-face learning mode, this research investigated the learning outcomes of students following English…

The Importance of Learning Styles: Understanding the Implications for Learning, Course Design, and Education. Contributions to the Study of Education, No. 64.

ERIC Educational Resources Information Center

Sims, Ronald R., Ed.; Sims, Serbrenia J., Ed.

This volume contains 12 papers on models of different learning styles, instruments to evaluate learning styles, and techniques for assessing individual learning characteristics as well as the future of learning style research and its implications for enhancing learning in higher education institutions. The papers are: "Learning Enhancement in…

Strategies for active learning in online continuing education.

PubMed

Phillips, Janet M

2005-01-01

Online continuing education and staff development is on the rise as the benefits of access, convenience, and quality learning are continuing to take shape. Strategies to enhance learning call for learner participation that is self-directed and independent, thus changing the educator's role from expert to coach and facilitator. Good planning of active learning strategies promotes optimal learning whether the learning content is presented in a course or a just-in-time short module. Active learning strategies can be used to enhance online learning during all phases of the teaching-learning process and can accommodate a variety of learning styles. Feedback from peers, educators, and technology greatly influences learner satisfaction and must be harnessed to provide effective learning experiences. Outcomes of active learning can be assessed online and implemented conveniently and successfully from the initiation of the course or module planning to the end of the evaluation process. Online learning has become accessible and convenient and allows the educator to track learner participation. The future of online education will continue to grow, and using active learning strategies will ensure that quality learning will occur, appealing to a wide variety of learning needs.

An Analysis of the Relationship between the Learning Process and Learning Motivation Profiles of Japanese Pharmacy Students Using Structural Equation Modeling.

PubMed

Yamamura, Shigeo; Takehira, Rieko

2018-04-23

Pharmacy students in Japan have to maintain strong motivation to learn for six years during their education. The authors explored the students’ learning structure. All pharmacy students in their 4th through to 6th year at Josai International University participated in the survey. The revised two factor study process questionnaire and science motivation questionnaire II were used to assess their learning process and learning motivation profiles, respectively. Structural equation modeling (SEM) was used to examine a causal relationship between the latent variables in the learning process and those in the learning motivation profile. The learning structure was modeled on the idea that the learning process affects the learning motivation profile of respondents. In the multi-group SEM, the estimated mean of the deep learning to learning motivation profile increased just after their clinical clerkship for 6th year students. This indicated that the clinical experience benefited students’ deep learning, which is probably because the experience of meeting with real patients encourages meaningful learning in pharmacy studies.

Auditory-motor learning influences auditory memory for music.

PubMed

Brown, Rachel M; Palmer, Caroline

2012-05-01

In two experiments, we investigated how auditory-motor learning influences performers' memory for music. Skilled pianists learned novel melodies in four conditions: auditory only (listening), motor only (performing without sound), strongly coupled auditory-motor (normal performance), and weakly coupled auditory-motor (performing along with auditory recordings). Pianists' recognition of the learned melodies was better following auditory-only or auditory-motor (weakly coupled and strongly coupled) learning than following motor-only learning, and better following strongly coupled auditory-motor learning than following auditory-only learning. Auditory and motor imagery abilities modulated the learning effects: Pianists with high auditory imagery scores had better recognition following motor-only learning, suggesting that auditory imagery compensated for missing auditory feedback at the learning stage. Experiment 2 replicated the findings of Experiment 1 with melodies that contained greater variation in acoustic features. Melodies that were slower and less variable in tempo and intensity were remembered better following weakly coupled auditory-motor learning. These findings suggest that motor learning can aid performers' auditory recognition of music beyond auditory learning alone, and that motor learning is influenced by individual abilities in mental imagery and by variation in acoustic features.

The Relationship between Learning Approaches of Prospective Teachers and Their Academic Achievement

ERIC Educational Resources Information Center

Gurlen, Eda; Turan, Sevgi; Senemoglu, Nuray

2013-01-01

To prepare for future professional challenges, prospective teachers should acquire the capabilities for independent learning. Prospective teachers should know how to learn effectively. In this article, prospective teachers' learning approaches, learning preference and the relationship between learning preference, learning approaches with…

Spiraling into Transformative Learning

ERIC Educational Resources Information Center

Cranton, Patricia

2010-01-01

This article explores how technical and vocational learning may spiral into transformative learning. Transformative learning theory is reviewed and the learning tasks of critical theory are used to integrate various approaches to transformative learning. With this as a foundation, the article explores how transformative learning can be fostered in…

Reinforcement Learning Deficits in People with Schizophrenia Persist after Extended Trials

PubMed Central

Cicero, David C.; Martin, Elizabeth A.; Becker, Theresa M.; Kerns, John G.

2014-01-01

Previous research suggests that people with schizophrenia have difficulty learning from positive feedback and when learning needs to occur rapidly. However, they seem to have relatively intact learning from negative feedback when learning occurs gradually. Participants are typically given a limited amount of acquisition trials to learn the reward contingencies and then tested about what they learned. The current study examined whether participants with schizophrenia continue to display these deficits when given extra time to learn the contingences. Participants with schizophrenia and matched healthy controls completed the Probabilistic Selection Task, which measures positive and negative feedback learning separately. Participants with schizophrenia showed a deficit in learning from both positive and negative feedback. These reward learning deficits persisted even if people with schizophrenia are given extra time (up to 10 blocks of 60 trials) to learn the reward contingencies. These results suggest that the observed deficits cannot be attributed solely to slower learning and instead reflect a specific deficit in reinforcement learning. PMID:25172610

Reinforcement learning deficits in people with schizophrenia persist after extended trials.

PubMed

Cicero, David C; Martin, Elizabeth A; Becker, Theresa M; Kerns, John G

2014-12-30

Previous research suggests that people with schizophrenia have difficulty learning from positive feedback and when learning needs to occur rapidly. However, they seem to have relatively intact learning from negative feedback when learning occurs gradually. Participants are typically given a limited amount of acquisition trials to learn the reward contingencies and then tested about what they learned. The current study examined whether participants with schizophrenia continue to display these deficits when given extra time to learn the contingences. Participants with schizophrenia and matched healthy controls completed the Probabilistic Selection Task, which measures positive and negative feedback learning separately. Participants with schizophrenia showed a deficit in learning from both positive feedback and negative feedback. These reward learning deficits persisted even if people with schizophrenia are given extra time (up to 10 blocks of 60 trials) to learn the reward contingencies. These results suggest that the observed deficits cannot be attributed solely to slower learning and instead reflect a specific deficit in reinforcement learning. Copyright © 2014 Elsevier Ireland Ltd. All rights reserved.

Childhood fever management program for Korean pediatric nurses: A comparison between blended and face-to-face learning method.

PubMed

Jeong, Yong Sun; Kim, Jin Sun

2014-01-01

A blended learning can be a useful learning strategy to improve the quality of fever and fever management education for pediatric nurses. This study compared the effects of a blended and face-to-face learning program on pediatric nurses' childhood fever management, using theory of planned behavior. A nonequivalent control group pretest-posttest design was used. A fever management education program using blended learning (combining face-to-face and online learning components) was offered to 30 pediatric nurses, and 29 pediatric nurses received face-to-face education. Learning outcomes did not significantly differ between the two groups. However, learners' satisfaction was higher for the blended learning program than the face-to-face learning program. A blended learning pediatric fever management program was as effective as a traditional face-to-face learning program. Therefore, a blended learning pediatric fever management-learning program could be a useful and flexible learning method for pediatric nurses.

Machine learning, social learning and the governance of self-driving cars.

PubMed

Stilgoe, Jack

2018-02-01

Self-driving cars, a quintessentially 'smart' technology, are not born smart. The algorithms that control their movements are learning as the technology emerges. Self-driving cars represent a high-stakes test of the powers of machine learning, as well as a test case for social learning in technology governance. Society is learning about the technology while the technology learns about society. Understanding and governing the politics of this technology means asking 'Who is learning, what are they learning and how are they learning?' Focusing on the successes and failures of social learning around the much-publicized crash of a Tesla Model S in 2016, I argue that trajectories and rhetorics of machine learning in transport pose a substantial governance challenge. 'Self-driving' or 'autonomous' cars are misnamed. As with other technologies, they are shaped by assumptions about social needs, solvable problems, and economic opportunities. Governing these technologies in the public interest means improving social learning by constructively engaging with the contingencies of machine learning.

E-service learning: A pedagogic innovation for healthcare management education.

PubMed

Malvey, Donna M; Hamby, Eileen F; Fottler, Myron D

2006-01-01

This paper proposes an innovation in service learning that we identify as e-service learning. By adding the "e" to service learning, we create a service learning model that is dynamic, mediated by technology, and delivered online. This paper begins by examining service learning, which is a distinct learning concept. Service learning furnishes students with opportunities for applied learning through participation in projects and activities in community organizations. The authors then define and conceptualize e-service learning, including the anticipated outcomes of implementation such as enhanced access, quality, and cost effectiveness of healthcare management education. Because e-service learning is mediated by technology, we identify state of the art technologies that support e-service learning activities. In addition, possible e-service learning projects and activities that may be included in healthcare management courses such as finance, human resources, quality, service management/marketing and strategy are identified. Finally, opportunities for future research are suggested.

Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach.

PubMed

McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

2018-01-01

Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction.

Tracking Active Learning in the Medical School Curriculum: A Learning-Centered Approach

PubMed Central

McCoy, Lise; Pettit, Robin K; Kellar, Charlyn; Morgan, Christine

2018-01-01

Background: Medical education is moving toward active learning during large group lecture sessions. This study investigated the saturation and breadth of active learning techniques implemented in first year medical school large group sessions. Methods: Data collection involved retrospective curriculum review and semistructured interviews with 20 faculty. The authors piloted a taxonomy of active learning techniques and mapped learning techniques to attributes of learning-centered instruction. Results: Faculty implemented 25 different active learning techniques over the course of 9 first year courses. Of 646 hours of large group instruction, 476 (74%) involved at least 1 active learning component. Conclusions: The frequency and variety of active learning components integrated throughout the year 1 curriculum reflect faculty familiarity with active learning methods and their support of an active learning culture. This project has sparked reflection on teaching practices and facilitated an evolution from teacher-centered to learning-centered instruction. PMID:29707649

Transferring learning to practice with e-learning--experiences in continuing education in the field of ambient assisted living.

PubMed

Illiger, Kristin; Egbert, Nicole; Krückeberg, Jörn; Stiller, Gerald; Kupka, Thomas; Hübner, Ursula; Behrends, Marianne

2014-01-01

The article describes an analysis of the use of e-learning to improve the learning transfer to practice in continuing education. Therefore an e-learning offer has been developed as a part between two attendance periods of a training course in the field of Ambient Assisted Living (AAL). All participants of the course were free to use the e-learning offer. After the end of the e-learning part we compared the e-learning users to the other participants. Using an online questionnaire we explored if there are differences in the activities in the field AAL after the training course. The results show that e-learning is beneficial especially for communication processes. Due to the fact that the possibility to talk about the learning content is an essential factor for the learning transfer, e-learning can improve the learning success.

Learning second language vocabulary: neural dissociation of situation-based learning and text-based learning.

PubMed

Jeong, Hyeonjeong; Sugiura, Motoaki; Sassa, Yuko; Wakusawa, Keisuke; Horie, Kaoru; Sato, Shigeru; Kawashima, Ryuta

2010-04-01

Second language (L2) acquisition necessitates learning and retrieving new words in different modes. In this study, we attempted to investigate the cortical representation of an L2 vocabulary acquired in different learning modes and in cross-modal transfer between learning and retrieval. Healthy participants learned new L2 words either by written translations (text-based learning) or in real-life situations (situation-based learning). Brain activity was then measured during subsequent retrieval of these words. The right supramarginal gyrus and left middle frontal gyrus were involved in situation-based learning and text-based learning, respectively, whereas the left inferior frontal gyrus was activated when learners used L2 knowledge in a mode different from the learning mode. Our findings indicate that the brain regions that mediate L2 memory differ according to how L2 words are learned and used. Copyright 2009 Elsevier Inc. All rights reserved.

Circuit mechanisms of sensorimotor learning

PubMed Central

Makino, Hiroshi; Hwang, Eun Jung; Hedrick, Nathan G.; Komiyama, Takaki

2016-01-01

SUMMARY The relationship between the brain and the environment is flexible, forming the foundation for our ability to learn. Here we review the current state of our understanding of the modifications in the sensorimotor pathway related to sensorimotor learning. We divide the process in three hierarchical levels with distinct goals: 1) sensory perceptual learning, 2) sensorimotor associative learning, and 3) motor skill learning. Perceptual learning optimizes the representations of important sensory stimuli. Associative learning and the initial phase of motor skill learning are ensured by feedback-based mechanisms that permit trial-and-error learning. The later phase of motor skill learning may primarily involve feedback-independent mechanisms operating under the classic Hebbian rule. With these changes under distinct constraints and mechanisms, sensorimotor learning establishes dedicated circuitry for the reproduction of stereotyped neural activity patterns and behavior. PMID:27883902

Guided discovery learning in geometry learning

NASA Astrophysics Data System (ADS)

Khasanah, V. N.; Usodo, B.; Subanti, S.

2018-03-01

Geometry is a part of the mathematics that must be learned in school. The purpose of this research was to determine the effect of Guided Discovery Learning (GDL) toward geometry learning achievement. This research had conducted at junior high school in Sukoharjo on academic years 2016/2017. Data collection was done based on student’s work test and documentation. Hypothesis testing used two ways analysis of variance (ANOVA) with unequal cells. The results of this research that GDL gave positive effect towards mathematics learning achievement. GDL gave better mathematics learning achievement than direct learning. There was no difference of mathematics learning achievement between male and female. There was no an interaction between sex differences and learning models toward student’s mathematics learning achievement. GDL can be used to improve students’ mathematics learning achievement in geometry.

Grouping students for instruction: effects of learning style on achievement and attitudes.

PubMed

Dunn, R; Giannitti, M C; Murray, J B; Rossi, I; Geisert, G; Quinn, P

1990-08-01

The present study examined the effects of matching and mismatching American middle-school students with a preference for learning alone or learning with peers with selected instructional treatments in order to determine the impact upon their attitudes and achievement in social studies. Analysis revealed that the learning-alone preference performed significantly better in the learning-alone condition and that the learning-with-peers preference performed significantly better in the learning-with-peers condition. However, no-preference students also performed significantly better in the learning-alone condition than with peers. In addition, data revealed that the learning-alone and the learning-with-peers students had significantly more positive attitudes when matched with their preferred learning style; the nopreference students had more positive attitudes in the learning-alone condition.

Trend of E-Learning: The Service Mashup

ERIC Educational Resources Information Center

Yen, Neil Y.; Shih, Timothy K.; Jin, Qun; Hsu, Hui-Huang; Chao, Louis R.

2010-01-01

With the improvement of internet technologies and multimedia resources, traditional learning has been replaced by distance learning, web-based learning or others' e-learning learning styles. According to distance learning, there are many research organizations and companies who make efforts in developing the relevant systems. But they lack…

Transformational Learning: Reflections of an Adult Learning Story

ERIC Educational Resources Information Center

Foote, Laura S.

2015-01-01

Transformational learning, narrative learning, and spiritual learning frame adult experiences in new and exciting ways. These types of learning can involve a simple transformation of belief or opinion or a radical transformation involving one's total perspective; learning may occur abruptly or incrementally. Education should liberate students from…

From Learning Organization to Learning Community: Sustainability through Lifelong Learning

ERIC Educational Resources Information Center

Kearney, Judith; Zuber-Skerritt, Ortrun

2012-01-01

Purpose: This paper aims to: extend the concept of "The learning organization" to "The learning community," especially disadvantaged communities; demonstrate how leaders in a migrant community can achieve positive change at the personal, professional, team and community learning levels through participatory action learning and…

Developing an Experiential Learning Program: Milestones and Challenges

ERIC Educational Resources Information Center

Austin, M. Jill; Rust, Dianna Zeh

2015-01-01

College and University faculty members have increasingly adopted experiential learning teaching methods that are designed to engage students in the learning process. Experiential learning is simply defined as "hands-on" learning and may involve any of the following activities: service learning, applied learning in the discipline,…

Smart Learning: Are We Ready for It?

ERIC Educational Resources Information Center

Poulova, Petra; Klimova, Blanka

2015-01-01

Nowadays learning, particularly the university learning, is supported with modern information and communication technologies. These technologies also enable electronic learning, known as eLearning, which is now firmly established at almost all institutions of higher learning in developed and developing countries. Moreover, at present eLearning is…

Learning Disorders

MedlinePlus

... more of a challenge. What causes learning disorders? Learning disabilities don't have anything to do with intelligence. ... for learning disorders? The most common treatment for learning disabilities is special education. A teacher or other learning ...

From Self-Regulation to Learning to Learn: Observations on the Construction of Self and Learning

ERIC Educational Resources Information Center

Thoutenhoofd, Ernst D.; Pirrie, Anne

2015-01-01

The purpose of this article is to clarify the epistemological basis of self-regulated learning. The authors note that learning to learn, a term that has pervaded education policy at EU and national levels in recent years is often conflated with self-regulated learning. As a result, there has been insufficient attention paid to learning as social…

The Study of Student Motivation on English Learning in Junior Middle School--A Case Study of No. 5 Middle School in Gejiu

ERIC Educational Resources Information Center

Long, Chunmei; Ming, Zhu; Chen, Liping

2013-01-01

Motivation plays an important role in foreign language learning. Learning motivation is to promote and guide and maintain learning activities which have been conducted an internal strength or internal mechanism. Learning motivation once formed, the student will use an active learning attitude to learn, and express a keen interest in learning, and…

Effects of Integrating an Active Learning-Promoting Mechanism into Location-Based Real-World Learning Environments on Students' Learning Performances and Behaviors

ERIC Educational Resources Information Center

Hwang, Gwo-Jen; Chang, Shao-Chen; Chen, Pei-Ying; Chen, Xiang-Ya

2018-01-01

Engaging students in real-world learning contexts has been identified by educators as being an important way of helping them learn to apply what they have learned from textbooks to practical problems. The advancements in mobile and image-processing technologies have enabled students to access learning resources and receive learning guidance in…

The Effects of Students' Learning Anxiety and Motivation on the Learning Achievement in the Activity Theory Based Gamified Learning Environment

ERIC Educational Resources Information Center

Su, Chung-Ho

2017-01-01

The advancement of mobile game-based learning has encouraged many related studies, which has enabled students to learn more and faster. To enhance the clinical path of cardiac catheterization learning, this paper has developed a mobile 3D-CCGBLS (3D Cardiac Catheterization Game-Based Learning System) with a learning assessment for cardiac…

Self-Regulation, Cooperative Learning, and Academic Self-Efficacy: Interactions to Prevent School Failure

PubMed Central

Fernandez-Rio, Javier; Cecchini, Jose A.; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A.

2017-01-01

Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12–17 years old (M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ-means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students’ academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and shared. Educators should be aware of these interactions, symmetrical or asymmetrical, because they determine the quality and quantity of the students’ participation and achievements, and they are key elements to prevent school failure. PMID:28154544

Exam Success at Undergraduate and Graduate-Entry Medical Schools: Is Learning Style or Learning Approach More Important? A Critical Review Exploring Links Between Academic Success, Learning Styles, and Learning Approaches Among School-Leaver Entry ("Traditional") and Graduate-Entry ("Nontraditional") Medical Students.

PubMed

Feeley, Anne-Marie; Biggerstaff, Deborah L

2015-01-01

PHENOMENON: The literature on learning styles over many years has been replete with debate and disagreement. Researchers have yet to elucidate exactly which underlying constructs are measured by the many learning styles questionnaires available. Some academics question whether learning styles exist at all. When it comes to establishing the value of learning styles for medical students, a further issue emerges. The demographics of medical students in the United Kingdom have changed in recent years, so past studies may not be applicable to students today. We wanted to answer a very simple, practical question: what can the literature on learning styles tell us that we can use to help today's medical students succeed academically at medical school? We conducted a literature review to synthesise the available evidence on how two different aspects of learning-the way in which students like to receive information in a learning environment (termed learning "styles") and the motivations that drive their learning (termed learning "approaches")-can impact on medical students' academic achievement. Our review confirms that although learning "styles" do not correlate with exam performance, learning "approaches" do: those with "strategic" and "deep" approaches to learning (i.e., motivated to do well and motivated to learn deeply respectively) perform consistently better in medical school examinations. Changes in medical school entrant demographics in the past decade have not altered these correlations. Optimistically, our review reveals that students' learning approaches can change and more adaptive approaches may be learned. Insights: For educators wishing to help medical students succeed academically, current evidence demonstrates that helping students develop their own positive learning approach using "growth mind-set" is a more effective (and more feasible) than attempting to alter students' learning styles. This conclusion holds true for both "traditional" and graduate-entry medical students.

Self-Regulation, Cooperative Learning, and Academic Self-Efficacy: Interactions to Prevent School Failure.

PubMed

Fernandez-Rio, Javier; Cecchini, Jose A; Méndez-Gimenez, Antonio; Mendez-Alonso, David; Prieto, Jose A

2017-01-01

Learning to learn and learning to cooperate are two important goals for individuals. Moreover, self regulation has been identified as fundamental to prevent school failure. The goal of the present study was to assess the interactions between self-regulated learning, cooperative learning and academic self-efficacy in secondary education students experiencing cooperative learning as the main pedagogical approach for at least one school year. 2.513 secondary education students (1.308 males, 1.205 females), 12-17 years old ( M = 13.85, SD = 1.29), enrolled in 17 different schools belonging to the National Network of Schools on Cooperative Learning in Spain agreed to participate. They all had experienced this pedagogical approach a minimum of one school year. Participants were asked to complete the cooperative learning questionnaire, the strategies to control the study questionnaire and the global academic self-efficacy questionnaire. Participants were grouped based on their perceptions on cooperative learning and self-regulated learning in their classes. A combination of hierarchical and κ -means cluster analyses was used. Results revealed a four-cluster solution: cluster one included students with low levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster two included students with high levels of cooperative learning, self-regulated learning and academic self-efficacy, cluster three included students with high levels of cooperative learning, low levels of self-regulated learning and intermediate-low levels of academic self-efficacy, and, finally, cluster four included students with high levels of self-regulated learning, low levels of cooperative learning, and intermediate-high levels of academic self-efficacy. Self-regulated learning was found more influential than cooperative learning on students' academic self-efficacy. In cooperative learning contexts students interact through different types of regulations: self, co, and shared. Educators should be aware of these interactions, symmetrical or asymmetrical, because they determine the quality and quantity of the students' participation and achievements, and they are key elements to prevent school failure.

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

PubMed

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 (p<0.001). The new concepts scored higher for learning 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 (p<0.05) and for the "interventions" competency (p<0.05). Traditional clinical placement, a dedicated education centre and workplace learning 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.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning

PubMed Central

Raza, Meher; Ivry, Richard B.

2016-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. NEW & NOTEWORTHY We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning. PMID:27832611

Smart Learning Adoption in Employees and HRD Managers

ERIC Educational Resources Information Center

Lee, Junghwan; Zo, Hangjung; Lee, Hwansoo

2014-01-01

The innovation of online technologies and the rapid diffusion of smart devices are changing workplace learning environment. Smart learning, as emerging learning paradigm, enables employees' learning to take place anywhere and anytime. Workplace learning studies, however, have focused on traditional e-learning environment, and they have failed…

How Does Self-Regulated Learning Relate to Active Procrastination and Other Learning Behaviors?

ERIC Educational Resources Information Center

Yamada, Masanori; Goda, Yoshiko; Matsuda, Takeshi; Saito, Yutaka; Kato, Hiroshi; Miyagawa, Hiroyuki

2016-01-01

This research investigates the relationship between self-regulated learning awareness, procrastination, and learning behaviors in a blended learning environment. Participants included 179 first-grade university students attending a blended learning-style class that used a learning management system. Data were collected using questionnaires on…

Learning Spaces Framework: Learning in an Online World

ERIC Educational Resources Information Center

Ministerial Council on Education, Employment, Training and Youth Affairs (NJ1), 2008

2008-01-01

"Contemporary learning--learning in an online world" describes the integrated nature of the highly technological world in which young people live and learn. A key priority is to design learning spaces that integrate technologies: engaging students in ways not previously possible; creating new learning and teaching possibilities;…

Service-Learning and Learning Communities: Tools for Integration and Assessment.

ERIC Educational Resources Information Center

Oates, Karen K.; Leavitt, Lynn H.

This publication attempts to provide fundamental theory about service-learning and learning communities, along with descriptions of best practices, lessons learned, and assessment strategies. The text is designed to provide resources to help readers offer service-learning experiences for their students. Learning communities are now commonly…

Does Artificial Tutoring Foster Inquiry Based Learning?

ERIC Educational Resources Information Center

Schmoelz, Alexander; Swertz, Christian; Forstner, Alexandra; Barberi, Alessandro

2014-01-01

This contribution looks at the Intelligent Tutoring Interface for Technology Enhanced Learning, which integrates multistage-learning and inquiry-based learning in an adaptive e-learning system. Based on a common pedagogical ontology, adaptive e-learning systems can be enabled to recommend learning objects and activities, which follow inquiry-based…

Hybrid E-Learning Tool TransLearning: Video Storytelling to Foster Vicarious Learning within Multi-Stakeholder Collaboration Networks

ERIC Educational Resources Information Center

van der Meij, Marjoleine G.; Kupper, Frank; Beers, Pieter J.; Broerse, Jacqueline E. W.

2016-01-01

E-learning and storytelling approaches can support informal vicarious learning within geographically widely distributed multi-stakeholder collaboration networks. This case study evaluates hybrid e-learning and video-storytelling approach "TransLearning" by investigation into how its storytelling e-tool supported informal vicarious…

Learner Performance in Multimedia Learning Arrangements: An Analysis across Instructional Approaches

ERIC Educational Resources Information Center

Eysink, Tessa H. S.; de Jong, Ton; Berthold, Kirsten; Kolloffel, Bas; Opfermann, Maria; Wouters, Pieter

2009-01-01

In this study, the authors compared four multimedia learning arrangements differing in instructional approach on effectiveness and efficiency for learning: (a) hypermedia learning, (b) observational learning, (c) self-explanation-based learning, and (d) inquiry learning. The approaches all advocate learners' active attitude toward the learning…

Personalised Context-Aware Ubiquitous Learning System for Supporting Effective English Vocabulary Learning

ERIC Educational Resources Information Center

Chen, Chih-Ming; Li, Yi-Lun

2010-01-01

Because learning English is extremely popular in non-native English speaking countries, developing modern assisted-learning schemes that facilitate effective English learning is a critical issue in English-language education. Vocabulary learning is vital within English learning because vocabulary comprises the basic building blocks of English…

Learning Outcomes Assessment: Extrapolating from Study Abroad to International Service-Learning

ERIC Educational Resources Information Center

Rubin, Donald L.; Matthews, Paul H.

2013-01-01

For international service-learning to thrive, it must document student learning outcomes that accrue to participants. The approaches to international service-learning assessment must be compelling to a variety of stakeholders. Recent large-scale projects in study abroad learning outcomes assessment--including the Georgia Learning Outcomes of…

Organizational Learning Culture, Learning Transfer Climate and Perceived Innovation in Jordanian Organizations

ERIC Educational Resources Information Center

Bates, Reid; Khasawneh, Samer

2005-01-01

This paper examines the relationship between organizational learning culture, learning transfer climate, and organizational innovation. The objective was to test the ability of learning organization culture to account for variance in learning transfer climate and subsequent organizational innovation, and to examine the role of learning transfer…

B-Learning under Examination: Advantages, Disadvantages and Opinions

ERIC Educational Resources Information Center

Bemposta-Rosende, Sergio; García-García, María José; Escribano-Otero, Juan José

2011-01-01

In recent years, learning management systems (LMS) have become very popular in almost all traditional universities, generating a new learning strategy approach, mixing elements from both traditional and online learning: the blended learning or b-learning. How these new environments influence teaching activities and learning processes are the main…

Ideal versus School Learning: Analyzing Israeli Secondary School Students' Conceptions of Learning

ERIC Educational Resources Information Center

Hadar, Linor

2009-01-01

This study explored 130 secondary school students' conceptions of learning using an open-ended task, analyzed both qualitatively and quantitatively. Students' reality of learning comprised two separate spheres, ideal learning and school learning, which rarely interacted. Generally, students commented more about school than ideal learning. Factor…

Seamless Language Learning: Second Language Learning with Social Media

ERIC Educational Resources Information Center

Wong, Lung-Hsiang; Chai, Ching Sing; Aw, Guat Poh

2017-01-01

This conceptual paper describes a language learning model that applies social media to foster contextualized and connected language learning in communities. The model emphasizes weaving together different forms of language learning activities that take place in different learning contexts to achieve seamless language learning. it promotes social…

Moving and Learning: Expanding Style and Increasing Flexibility

ERIC Educational Resources Information Center

Peterson, Kay; DeCato, Lisa; Kolb, David A.

2015-01-01

This article introduces ways in which movement can enhance one's understanding of how to learn using Experiential Learning Theory (ELT) concepts of the Learning Cycle, Learning Styles, and Learning Flexibility. The theoretical correspondence between the dialectic dimensions of the Learning Cycle and the dimensions of the Laban Movement Analysis…

New Learning - The IPP Programme: Improvements in Learning and Self Esteem by Changing the Organization of Learning

NASA Astrophysics Data System (ADS)

Garber, Klaus; Ausserer, Oskar; Giacomuzzi, Salvatore

"New learning" is basically an individualized learning style. "New learning" starts by the individual itself. The individual is the basis for conditions, learning contents, rhythm, duration and intensity of the teaching. The appropriate slogan is: fetch the individual at his personal conditions.

The Effects of Organizational Learning Environment Factors on E-Learning Acceptance

ERIC Educational Resources Information Center

Cheng, Bo; Wang, Minhong; Moormann, Jurgen; Olaniran, Bolanle A.; Chen, Nian-Shing

2012-01-01

Workplace learning is an important means of employees' continuous learning and professional development. E-learning is being recognized as an important supportive practice for learning at work. Current research on the success factors of e-learning in the workplace has emphasized on employees' characteristics, technological attributes, and training…

Learning Companion Systems, Social Learning Systems, and the Global Social Learning Club.

ERIC Educational Resources Information Center

Chan, Tak-Wai

1996-01-01

Describes the development of learning companion systems and their contributions to the class of social learning systems that integrate artificial intelligence agents and use machine learning to tutor and interact with students. Outlines initial social learning projects, their programming languages, and weakness. Future improvements will include…

Blended Learning: The Perceptions of First-Year Geography Students

ERIC Educational Resources Information Center

Mitchell, Phillipa; Forer, Pip

2010-01-01

Focusing on "Digital Worlds", a first-year geography blended learning course at the University of Auckland, this paper gives voice to the students, examining how they perceived e-learning versus traditional learning mechanisms; how e-learning mechanisms have affected their learning behaviour; and why certain e-learning mechanisms offered…

The 3 R's of Learning Time: Rethink, Reshape, Reclaim

ERIC Educational Resources Information Center

Sackey, Shera Carter

2012-01-01

The Learning School Alliance is a network of schools collaborating about professional practice. The network embodies Learning Forward's purpose to advance effective job-embedded professional learning that leads to student outcomes. A key component of Learning Forward's Standards for Professional Learning is a focus on collaborative learning,…

Development and Evaluation of a Context-Aware Ubiquitous Learning Environment for Astronomy Education

ERIC Educational Resources Information Center

Chen, Chia-Chen; Lin, Pei-Hsuan

2016-01-01

In recent years information technology has been integrated into education to produce a series of trends, beginning with "electronic learning" (e-learning), through "mobile learning" (m-learning) and finally to "ubiquitous learning" (u-learning), which aims to improve learner motivation through overcoming the…

Toward a Social Approach to Learning in Community Service Learning

ERIC Educational Resources Information Center

Cooks, Leda; Scharrer, Erica; Paredes, Mari Castaneda

2004-01-01

The authors describe a social approach to learning in community service learning that extends the contributions of three theoretical bodies of scholarship on learning: social constructionism, critical pedagogy, and community service learning. Building on the assumptions about learning described in each of these areas, engagement, identity, and…

Understanding the essential elements of work-based learning and its relevance to everyday clinical practice.

PubMed

Williams, Caroline

2010-09-01

To critically review the work-based learning literature and explore the implications of the findings for the development of work-based learning programmes. With NHS budgets under increasing pressure, and challenges to the impact of classroom-based learning on patient outcomes, work-based learning is likely to come under increased scrutiny as a potential solution. Evidence from higher education institutions suggests that work-based learning can improve practice, but in many cases it is perceived as little more than on-the-job training to perform tasks. The CINAHL database was searched using the keywords work-based learning, work-place learning and practice-based learning. Those articles that had a focus on post-registration nursing were selected and critically reviewed. Using the review of the literature, three key issues were explored. Work-based learning has the potential to change practice. Learning how to learn and critical reflection are key features. For effective work-based learning nurses need to take control of their own learning, receive support to critically reflect on their practice and be empowered to make changes to that practice. A critical review of the literature has identified essential considerations for the implementation of work-based learning. A change in culture from classroom to work-based learning requires careful planning and consideration of learning cultures. To enable effective work-based learning, nurse managers need to develop a learning culture in their workplace. They should ensure that skilled facilitation is provided to support staff with critical reflection and effecting changes in practice. CONTRIBUTION TO NEW KNOWLEDGE: This paper has identified three key issues that need to be considered in the development of work-based learning programmes. © 2010 The Authors. Journal compilation © 2010 Blackwell Publishing Ltd.

Dopamine selectively remediates ‘model-based’ reward learning: a computational approach

PubMed Central

Sharp, Madeleine E.; Foerde, Karin; Daw, Nathaniel D.

2016-01-01

Patients with loss of dopamine due to Parkinson’s disease are impaired at learning from reward. However, it remains unknown precisely which aspect of learning is impaired. In particular, learning from reward, or reinforcement learning, can be driven by two distinct computational processes. One involves habitual stamping-in of stimulus-response associations, hypothesized to arise computationally from ‘model-free’ learning. The other, ‘model-based’ learning, involves learning a model of the world that is believed to support goal-directed behaviour. Much work has pointed to a role for dopamine in model-free learning. But recent work suggests model-based learning may also involve dopamine modulation, raising the possibility that model-based learning may contribute to the learning impairment in Parkinson’s disease. To directly test this, we used a two-step reward-learning task which dissociates model-free versus model-based learning. We evaluated learning in patients with Parkinson’s disease tested ON versus OFF their dopamine replacement medication and in healthy controls. Surprisingly, we found no effect of disease or medication on model-free learning. Instead, we found that patients tested OFF medication showed a marked impairment in model-based learning, and that this impairment was remediated by dopaminergic medication. Moreover, model-based learning was positively correlated with a separate measure of working memory performance, raising the possibility of common neural substrates. Our results suggest that some learning deficits in Parkinson’s disease may be related to an inability to pursue reward based on complete representations of the environment. PMID:26685155

Dual-learning systems during speech category learning

PubMed Central

Chandrasekaran, Bharath; Yi, Han-Gyol; Maddox, W. Todd

2013-01-01

Dual-systems models of visual category learning posit the existence of an explicit, hypothesis-testing ‘reflective’ system, as well as an implicit, procedural-based ‘reflexive’ system. The reflective and reflexive learning systems are competitive and neurally dissociable. Relatively little is known about the role of these domain-general learning systems in speech category learning. Given the multidimensional, redundant, and variable nature of acoustic cues in speech categories, our working hypothesis is that speech categories are learned reflexively. To this end, we examined the relative contribution of these learning systems to speech learning in adults. Native English speakers learned to categorize Mandarin tone categories over 480 trials. The training protocol involved trial-by-trial feedback and multiple talkers. Experiment 1 and 2 examined the effect of manipulating the timing (immediate vs. delayed) and information content (full vs. minimal) of feedback. Dual-systems models of visual category learning predict that delayed feedback and providing rich, informational feedback enhance reflective learning, while immediate and minimally informative feedback enhance reflexive learning. Across the two experiments, our results show feedback manipulations that targeted reflexive learning enhanced category learning success. In Experiment 3, we examined the role of trial-to-trial talker information (mixed vs. blocked presentation) on speech category learning success. We hypothesized that the mixed condition would enhance reflexive learning by not allowing an association between talker-related acoustic cues and speech categories. Our results show that the mixed talker condition led to relatively greater accuracies. Our experiments demonstrate that speech categories are optimally learned by training methods that target the reflexive learning system. PMID:24002965

Analysis of dermatology resident self-reported successful learning styles and implications for core competency curriculum development.

PubMed

Stratman, Erik J; Vogel, Curt A; Reck, Samuel J; Mukesh, Bickol N

2008-01-01

There are different teaching styles for delivering competency-based curricula. The education literature suggests that learning is maximized when teaching is delivered in a style preferred by learners. To determine if dermatology residents report learning style preferences aligned with adult learning. Dermatology residents attending an introductory cutaneous biology course completed a learning styles inventory assessing self-reported success in 35 active and passive learning activities. The 35 learning activities were ranked in order of preference by learners. Mean overall ratings for active learning activities were significantly higher than for passive learning activities (P = 0.002). Trends in dermatology resident learning style preferences should be considered during program curriculum development. Programs should integrate a variety of curriculum delivery methods to accommodate various learning styles, with an emphasis on the active learning styles preferred by residents.

Learning procedures from interactive natural language instructions

NASA Technical Reports Server (NTRS)

Huffman, Scott B.; Laird, John E.

1994-01-01

Despite its ubiquity in human learning, very little work has been done in artificial intelligence on agents that learn from interactive natural language instructions. In this paper, the problem of learning procedures from interactive, situated instruction is examined in which the student is attempting to perform tasks within the instructional domain, and asks for instruction when it is needed. Presented is Instructo-Soar, a system that behaves and learns in response to interactive natural language instructions. Instructo-Soar learns completely new procedures from sequences of instruction, and also learns how to extend its knowledge of previously known procedures to new situations. These learning tasks require both inductive and analytic learning. Instructo-Soar exhibits a multiple execution learning process in which initial learning has a rote, episodic flavor, and later executions allow the initially learned knowledge to be generalized properly.

Transfer Learning beyond Text Classification

NASA Astrophysics Data System (ADS)

Yang, Qiang

Transfer learning is a new machine learning and data mining framework that allows the training and test data to come from different distributions or feature spaces. We can find many novel applications of machine learning and data mining where transfer learning is necessary. While much has been done in transfer learning in text classification and reinforcement learning, there has been a lack of documented success stories of novel applications of transfer learning in other areas. In this invited article, I will argue that transfer learning is in fact quite ubiquitous in many real world applications. In this article, I will illustrate this point through an overview of a broad spectrum of applications of transfer learning that range from collaborative filtering to sensor based location estimation and logical action model learning for AI planning. I will also discuss some potential future directions of transfer learning.

Why do organizations not learn from incidents? Bottlenecks, causes and conditions for a failure to effectively learn.

PubMed

Drupsteen, Linda; Hasle, Peter

2014-11-01

If organizations would be able to learn more effectively from incidents that occurred in the past, future incidents and consequential injury or damage can be prevented. To improve learning from incidents, this study aimed to identify limiting factors, i.e. the causes of the failure to effectively learn. In seven organizations focus groups were held to discuss factors that according to employees contributed to the failure to learn. By use of a model of the learning from incidents process, the steps, where difficulties for learning arose, became visible, and the causes for these difficulties could be studied. Difficulties were identified in multiple steps of the learning process, but most difficulties became visible when planning actions, which is the phase that bridges the gap from incident investigation to actions for improvement. The main causes for learning difficulties, which were identified by the participants in this study, were tightly related to the learning process, but some indirect causes - or conditions - such as lack of ownership and limitations in expertise were also mentioned. The results illustrate that there are two types of causes for the failure to effectively learn: direct causes and indirect causes, here called conditions. By actively and systematically studying learning, more conditions might be identified and indicators for a successful learning process may be determined. Studying the learning process does, however, require a shift from learning from incidents to learning to learn. Copyright © 2014 Elsevier Ltd. All rights reserved.

Science of learning is learning of science: why we need a dialectical approach to science education research

NASA Astrophysics Data System (ADS)

Roth, Wolff-Michael

2012-06-01

Research on learning science in informal settings and the formal (sometimes experimental) study of learning in classrooms or psychological laboratories tend to be separate domains, even drawing on different theories and methods. These differences make it difficult to compare knowing and learning observed in one paradigm/context with those observed in the other. Even more interestingly, the scientists studying science learning rarely consider their own learning in relation to the phenomena they study. A dialectical, reflexive approach to learning, however, would theorize the movement of an educational science (its learning and development) as a special and general case—subject matter and method—of the phenomenon of learning (in/of) science. In the dialectical approach to the study of science learning, therefore, subject matter, method, and theory fall together. This allows for a perspective in which not only disparate fields of study—school science learning and learning in everyday life—are integrated but also where the progress in the science of science learning coincides with its topic. Following the articulation of a contradictory situation on comparing learning in different settings, I describe the dialectical approach. As a way of providing a concrete example, I then trace the historical movement of my own research group as it simultaneously and alternately studied science learning in formal and informal settings. I conclude by recommending cultural-historical, dialectical approaches to learning and interaction analysis as a context for fruitful interdisciplinary research on science learning within and across different settings.

[Good practice guidelines for health information].

PubMed

2016-01-01

Evidence-based health information is distinguished by the provision of an unbiased and trustworthy description of the current state of medical knowledge. It enables people to learn more about health and disease, and to make health-related decisions - on their own or together with others - reflecting their attitudes and lifestyle. To adequately serve this purpose, health information must be evidence-based. A working group from the German Network for Evidence-based Medicine (Deutsches Netzwerk Evidenzbasierte Medizin) has developed a first draft of good practice guidelines for health information (Gute Praxis Gesundheitsinformation) with the aim of providing support for authors and publishers of evidence-based health information. The group included researchers, patient representatives, journalists and developers of health information. The criteria for evidence-based health information were developed and agreed upon within this author group, and then made available for public comment. All submitted comments were documented and assessed regarding the need to revise or amend the draft. Changes were subsequently implemented following approval by the author group. Gute Praxis Gesundheitsinformation calls for a transparent methodological approach in the development of health information. To achieve this, evidence-based information must be based on (a) a systematic literature search, (b) a justified selection of evidence, (c) unbiased reporting of relevant results, (d) appropriate factual and linguistic communication of uncertainties, (e) either avoidance of any direct recommendations or a strict division between the reporting of results and the derivation of recommendations, (f) the consideration of current evidence on the communication of figures, risks and probabilities, and (g) transparent information about the authors and publishers of the health information, including their funding sources. Gute Praxis Gesundheitsinformation lists a total of 16 aspects to be addressed in methods papers. Gute Praxis Gesundheitsinformation is a tool that puts forward methodological aspects to be considered when developing health information. In order to be transparent, descriptions of the underlying methods and processes need to be published in easily accessible methods papers describing the general procedure. Copyright © 2015. Published by Elsevier GmbH.

Age, environment, object recognition and morphological diversity of GFAP-immunolabeled astrocytes.

PubMed

Diniz, Daniel Guerreiro; de Oliveira, Marcus Augusto; de Lima, Camila Mendes; Fôro, César Augusto Raiol; Sosthenes, Marcia Consentino Kronka; Bento-Torres, João; da Costa Vasconcelos, Pedro Fernando; Anthony, Daniel Clive; Diniz, Cristovam Wanderley Picanço

2016-10-10

Few studies have explored the glial response to a standard environment and how the response may be associated with age-related cognitive decline in learning and memory. Here we investigated aging and environmental influences on hippocampal-dependent tasks and on the morphology of an unbiased selected population of astrocytes from the molecular layer of dentate gyrus, which is the main target of perforant pathway. Six and twenty-month-old female, albino Swiss mice were housed, from weaning, in a standard or enriched environment, including running wheels for exercise and tested for object recognition and contextual memories. Young adult and aged subjects, independent of environment, were able to distinguish familiar from novel objects. All experimental groups, except aged mice from standard environment, distinguish stationary from displaced objects. Young adult but not aged mice, independent of environment, were able to distinguish older from recent objects. Only young mice from an enriched environment were able to distinguish novel from familiar contexts. Unbiased selected astrocytes from the molecular layer of the dentate gyrus were reconstructed in three-dimensions and classified using hierarchical cluster analysis of bimodal or multimodal morphological features. We found two morphological phenotypes of astrocytes and we designated type I the astrocytes that exhibited significantly higher values of morphological complexity as compared with type II. Complexity = [Sum of the terminal orders + Number of terminals] × [Total branch length/Number of primary branches]. On average, type I morphological complexity seems to be much more sensitive to age and environmental influences than that of type II. Indeed, aging and environmental impoverishment interact and reduce the morphological complexity of type I astrocytes at a point that they could not be distinguished anymore from type II. We suggest these two types of astrocytes may have different physiological roles and that the detrimental effects of aging on memory in mice from a standard environment may be associated with a reduction of astrocytes morphological diversity.

Dissociation between active and observational learning from positive and negative feedback in Parkinsonism.

PubMed

Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina; Südmeyer, Martin; Bellebaum, Christian

2012-01-01

Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson's Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson's Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson's Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning.

Effects of congruence between preferred and perceived learning environments in nursing education in Taiwan: a cross-sectional study

PubMed Central

Yeh, Ting-Kuang; Huang, Hsiu-Mei; Chan, Wing P; Chang, Chun-Yen

2016-01-01

Objective To investigate the effects of congruence between preferred and perceived learning environments on learning outcomes of nursing students. Setting A nursing course at a university in central Taiwan. Participants 124 Taiwanese nursing students enrolled in a 13-week problem-based Fundamental Nursing curriculum. Design and methods Students' preferred learning environment, perceptions about the learning environment and learning outcomes (knowledge, self-efficacy and attitudes) were assessed. On the basis of test scores measuring their preferred and perceived learning environments, students were assigned to one of two groups: a ‘preferred environment aligned with perceived learning environment’ group and a ‘preferred environment discordant with perceived learning environment’ group. Learning outcomes were analysed by group. Outcome measures Most participants preferred learning in a classroom environment that combined problem-based and lecture-based instruction. However, a mismatch of problem-based instruction with students' perceptions occurred. Learning outcomes were significantly better when students' perceptions of their instructional activities were congruent with their preferred learning environment. Conclusions As problem-based learning becomes a focus of educational reform in nursing, teachers need to be aware of students' preferences and perceptions of the learning environment. Teachers may also need to improve the match between an individual student's perception and a teacher's intention in the learning environment, and between the student's preferred and actual perceptions of the learning environment. PMID:27207620

The key to success in elite athletes? Explicit and implicit motor learning in youth elite and non-elite soccer players.

PubMed

Verburgh, L; Scherder, E J A; van Lange, P A M; Oosterlaan, J

2016-09-01

In sports, fast and accurate execution of movements is required. It has been shown that implicitly learned movements might be less vulnerable than explicitly learned movements to stressful and fast changing circumstances that exist at the elite sports level. The present study provides insight in explicit and implicit motor learning in youth soccer players with different expertise levels. Twenty-seven youth elite soccer players and 25 non-elite soccer players (aged 10-12) performed a serial reaction time task (SRTT). In the SRTT, one of the sequences must be learned explicitly, the other was implicitly learned. No main effect of group was found for implicit and explicit learning on mean reaction time (MRT) and accuracy. However, for MRT, an interaction was found between learning condition, learning phase and group. Analyses showed no group effects for the explicit learning condition, but youth elite soccer players showed better learning in the implicit learning condition. In particular, during implicit motor learning youth elite soccer showed faster MRTs in the early learning phase and earlier reached asymptote performance in terms of MRT. Present findings may be important for sports because children with superior implicit learning abilities in early learning phases may be able to learn more (durable) motor skills in a shorter time period as compared to other children.

Scaffolding in geometry based on self regulated learning

NASA Astrophysics Data System (ADS)

Bayuningsih, A. S.; Usodo, B.; Subanti, S.

2017-12-01

This research aim to know the influence of problem based learning model by scaffolding technique on junior high school student’s learning achievement. This research took location on the junior high school in Banyumas. The research data obtained through mathematic learning achievement test and self-regulated learning (SRL) questioner. Then, the data analysis used two ways ANOVA. The results showed that scaffolding has positive effect to the mathematic learning achievement. The mathematic learning achievement use PBL-Scaffolding model is better than use PBL. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

Enhancing Collaborative Learning in Web 2.0-Based E-Learning Systems: A Design Framework for Building Collaborative E-Learning Contents

ERIC Educational Resources Information Center

El Mhouti, Abderrahim; Nasseh, Azeddine; Erradi, Mohamed; Vasquèz, José Marfa

2017-01-01

Today, the implication of Web 2.0 technologies in e-learning allows envisaging new teaching and learning forms, advocating an important place to the collaboration and social interaction. However, in e-learning systems, learn in a collaborative way is not always so easy because one of the difficulties when arranging e-learning courses can be that…

Do Ten-Year-Old Children in Sweden Know How They Learn? A Study of How Young Students Believe They Learn Compared to Their Learning Styles Preferences

ERIC Educational Resources Information Center

Boström, Lena

2012-01-01

Students' individual learning strategies have been identified as important skills in order to succeed in school as well as important for lifelong learning. The Swedish steering documents are permeated by an epistemological and a methodological variation based on the individual student's learning. Learning how to learn has been identified by the EU…

M-Learning: Implications in Learning Domain Specificities, Adaptive Learning, Feedback, Augmented Reality, and the Future of Online Learning

ERIC Educational Resources Information Center

Squires, David R.

2014-01-01

The aim of this paper is to examine the potential and effectiveness of m-learning in the field of Education and Learning domains. The purpose of this research is to illustrate how mobile technology can and is affecting novel change in instruction, from m-learning and the link to adaptive learning, to the uninitiated learner and capacities of…

The Development of an E-Learning-Based Learning Service for MKDP Curriculum and Learning at the Indonesia University of Education

ERIC Educational Resources Information Center

Rusman

2016-01-01

E-learning is a general term used to refer to computer-enhanced learning based that facilitates whoever, wherever, and whenever the person is to be able to learn more fun, easier and cheaper by using Internet. In other words, E-learning is the use of network technologies to create, foster, deliver, and facilitate learning, anytime and anywhere. It…

Autonomous development and learning in artificial intelligence and robotics: Scaling up deep learning to human-like learning.

PubMed

Oudeyer, Pierre-Yves

2017-01-01

Autonomous lifelong development and learning are fundamental capabilities of humans, differentiating them from current deep learning systems. However, other branches of artificial intelligence have designed crucial ingredients towards autonomous learning: curiosity and intrinsic motivation, social learning and natural interaction with peers, and embodiment. These mechanisms guide exploration and autonomous choice of goals, and integrating them with deep learning opens stimulating perspectives.

[Effects of Learning Activities on Application of Learning Portfolio in Nursing Management Course].

PubMed

Choi, So Eun; Kim, Eun A

2016-02-01

This study was conducted to examine effects of a learning portfolio by identifying the learning of nursing students taking a learning portfolio-utilized nursing management class. A non-equivalent control group pretest-posttest design was used. Participants were 83 senior students taking the nursing management course in one of the Departments of Nursing at 2 Universities. Experimental group (n=42) received a learning portfolio-utilized nursing management class 15 times over 15 weeks (3 hours weekly). Self-directed learning abilities, approaches to learning and learning flow of the participants were examined with self-report structured questionnaires. Data were collected between September 2 and December 16, 2014, and were analyzed using chi-square test, Fisher's exact test, independent t-test and ANCOVA with SPSS/PC version 21.0. After the intervention the experimental group showed significant increases in self-directed learning abilities, deep approaches to learning and learning flow compared to the control group. However, no significant difference was found between groups for surface approaches to learning. Learning activities using the learning portfolios could be effective in cultivating the learning competency for growth of knowledge, technology and professionalism by increasing personal concentration and organization ability of the nursing students so that they can react to the rapidly changing environment.

Science Learning Outcomes in Alignment with Learning Environment Preferences

NASA Astrophysics Data System (ADS)

Chang, Chun-Yen; Hsiao, Chien-Hua; Chang, Yueh-Hsia

2011-04-01

This study investigated students' learning environment preferences and compared the relative effectiveness of instructional approaches on students' learning outcomes in achievement and attitude among 10th grade earth science classes in Taiwan. Data collection instruments include the Earth Science Classroom Learning Environment Inventory and Earth Science Learning Outcomes Inventory. The results showed that most students preferred learning in a classroom environment where student-centered and teacher-centered instructional approaches coexisted over a teacher-centered learning environment. A multivariate analysis of covariance also revealed that the STBIM students' cognitive achievement and attitude toward earth science were enhanced when the learning environment was congruent with their learning environment preference.

Kinespell: Kinesthetic Learning Activity and Assessment in a Digital Game-Based Learning Environment

NASA Astrophysics Data System (ADS)

Cariaga, Ada Angeli; Salvador, Jay Andrae; Solamo, Ma. Rowena; Feria, Rommel

Various approaches in learning are commonly classified into visual, auditory and kinesthetic (VAK) learning styles. One way of addressing the VAK learning styles is through game-based learning which motivates learners pursue knowledge holistically. The paper presents Kinespell, an unconventional method of learning through digital game-based learning. Kinespell is geared towards enhancing not only the learner’s spelling abilities but also the motor skills through utilizing wireless controllers. It monitors player’s performance through integrated assessment scheme. Results show that Kinespell may accommodate the VAK learning styles and is a promising alternative to established methods in learning and assessing students’ performance in Spelling.

Do Science Teachers Distinguish Between Their own Learning and the Learning of Their Students?

NASA Astrophysics Data System (ADS)

Brauer, Heike; Wilde, Matthias

2018-02-01

Learning beliefs influence learning and teaching. For this reason, teachers and teacher educators need to be aware of them. To support students' knowledge construction, teachers must develop appropriate learning and teaching beliefs. Teachers appear to have difficulties when analysing students' learning. This seems to be due to the inability to differentiate the beliefs about their students' learning from those about their own learning. Both types of beliefs seem to be intertwined. This study focuses on whether pre-service teachers' beliefs about their own learning are identical to those about their students' learning. Using a sample of pre-service teachers, we measured general beliefs about "constructivist" and "transmissive" learning and science-specific beliefs about "connectivity" and "taking pre-concepts into account". We also analysed the development of these four beliefs during teacher professionalisation by comparing beginning and advanced pre-service teachers. Our results show that although pre-service teachers make the distinction between their own learning and the learning of their students for the general tenets of constructivist and transmissive learning, there is no significant difference for science-specific beliefs. The beliefs pre-service teachers hold about their students' science learning remain closely tied to their own.

No Trade-Off between Learning Speed and Associative Flexibility in Bumblebees: A Reversal Learning Test with Multiple Colonies

PubMed Central

Raine, Nigel E.; Chittka, Lars

2012-01-01

Potential trade-offs between learning speed and memory-related performance could be important factors in the evolution of learning. Here, we test whether rapid learning interferes with the acquisition of new information using a reversal learning paradigm. Bumblebees (Bombus terrestris) were trained to associate yellow with a floral reward. Subsequently the association between colour and reward was reversed, meaning bees then had to learn to visit blue flowers. We demonstrate that individuals that were fast to learn yellow as a predictor of reward were also quick to reverse this association. Furthermore, overnight memory retention tests suggest that faster learning individuals are also better at retaining previously learned information. There is also an effect of relatedness: colonies whose workers were fast to learn the association between yellow and reward also reversed this association rapidly. These results are inconsistent with a trade-off between learning speed and the reversal of a previously made association. On the contrary, they suggest that differences in learning performance and cognitive (behavioural) flexibility could reflect more general differences in colony learning ability. Hence, this study provides additional evidence to support the idea that rapid learning and behavioural flexibility have adaptive value. PMID:23028779

Lesions of the fornix and anterior thalamic nuclei dissociate different aspects of hippocampal-dependent spatial learning: implications for the neural basis of scene learning.

PubMed

Aggleton, John P; Poirier, Guillaume L; Aggleton, Hugh S; Vann, Seralynne D; Pearce, John M

2009-06-01

The present study used 2 different discrimination tasks designed to isolate distinct components of visuospatial learning: structural learning and geometric learning. Structural learning refers to the ability to learn the precise combination of stimulus identity with stimulus location. Rats with anterior thalamic lesions and fornix lesions were unimpaired on a configural learning task in which the rats learned 3 concurrent mirror-image discriminations (structural learning). Indeed, both lesions led to facilitated learning. In contrast, anterior thalamic lesions impaired the geometric discrimination (e.g., swim to the corner with the short wall to the right of the long wall). Finally, both the fornix and anterior thalamic lesions severely impaired T-maze alternation, a task that taxes an array of spatial strategies including allocentric learning. This pattern of dissociations and double dissociations highlights how distinct classes of spatial learning rely on different systems, even though they may converge on the hippocampus. Consequently, the findings suggest that structural learning is heavily dependent on cortico-hippocampal interactions. In contrast, subcortical inputs (such as those from the anterior thalamus) contribute to geometric learning. Copyright (c) 2009 APA, all rights reserved.

Inductive learning of thyroid functional states using the ID3 algorithm. The effect of poor examples on the learning result.

PubMed

Forsström, J

1992-01-01

The ID3 algorithm for inductive learning was tested using preclassified material for patients suspected to have a thyroid illness. Classification followed a rule-based expert system for the diagnosis of thyroid function. Thus, the knowledge to be learned was limited to the rules existing in the knowledge base of that expert system. The learning capability of the ID3 algorithm was tested with an unselected learning material (with some inherent missing data) and with a selected learning material (no missing data). The selected learning material was a subgroup which formed a part of the unselected learning material. When the number of learning cases was increased, the accuracy of the program improved. When the learning material was large enough, an increase in the learning material did not improve the results further. A better learning result was achieved with the selected learning material not including missing data as compared to unselected learning material. With this material we demonstrate a weakness in the ID3 algorithm: it can not find available information from good example cases if we add poor examples to the data.

LEARNING AND ASSOCIATED PHENOMENA IN INVERTEBRATES.

DTIC Science & Technology

cnidarians; Cannibals, chemicals and contiguity; Behaviour of planaria in instrumental learning paradigms; Learning in planarians ; Learning in annelids...Research and theory on conditioning of annelids; Descartes, mechanistic biology and animal behaviour; Planarian learning; Learning and movement in

Learning Styles.

ERIC Educational Resources Information Center

Missouri Univ., Columbia. Coll. of Education.

Information is provided regarding major learning styles and other factors important to student learning. Several typically asked questions are presented regarding different learning styles (visual, auditory, tactile and kinesthetic, and multisensory learning), associated considerations, determining individuals' learning styles, and appropriate…

Distributing vs. Blocking Learning Questions in a Web-Based Learning Environment

ERIC Educational Resources Information Center

Kapp, Felix; Proske, Antje; Narciss, Susanne; Körndle, Hermann

2015-01-01

Effective studying in web-based learning environments (web-LEs) requires cognitive engagement and demands learners to regulate their learning activities. One way to support learners in web-LEs is to provide interactive learning questions within the learning environment. Even though research on learning questions has a long tradition, there are…

Assessing Learning Styles among Students with and without Learning Disabilities at a Distance-Learning University

ERIC Educational Resources Information Center

Heiman, Tali

2006-01-01

Differences in the learning styles of students with and without learning disabilities (LD) at a distance-learning university were examined. Two hundred and twelve students answered self-report questionnaires on their learning styles. Results revealed that students with LD preferred to use more stepwise processing, including memorizing and…

E-Learning in Malaysia: Moving forward in Open Distance Learning

ERIC Educational Resources Information Center

Abas, Zoraini Wati

2009-01-01

Many higher education institutions have embarked on e-learning as a means to support their learning and teaching activities. In distance learning institutions, e-learning has enabled them to reach out to students dispersed over a wide geographical area, locally and internationally. In some countries, e-learning has also given students the…

Using Cooperative Structures to Promote Deep Learning

ERIC Educational Resources Information Center

Millis, Barbara J.

2014-01-01

The author explores concrete ways to help students learn more and have fun doing it while they support each other's learning. The article specifically shows the relationships between cooperative learning and deep learning. Readers will become familiar with the tenets of cooperative learning and its power to enhance learning--even more so when…

Examining Informal Learning Using Mobile Devices in the Healthcare Workplace

ERIC Educational Resources Information Center

Fahlman, Dorothy

2013-01-01

The study of workplace learning and informal learning are not new to adult education and pedagogy. However, the use of mobile devices as learning tools for informal learning in the workplace is an understudied area. Using theories on informal learning and constructivism as a framework, this paper explores informal learning of registered nurses…

Contribution of Content Knowledge and Learning Ability to the Learning of Facts.

ERIC Educational Resources Information Center

Kuhara-Kojima, Keiko; Hatano, Giyoo

1991-01-01

In 3 experiments, 1,598 Japanese college students were examined concerning the learning of facts in 2 content domains, baseball and music. Content knowledge facilitated fact learning only in the relevant domain; learning ability facilitated fact learning in both domains. Effects of content knowledge and learning ability were additive. (SLD)

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

ERIC Educational Resources Information Center

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…

Applying Learning Analytics to Investigate Timed Release in Online Learning

ERIC Educational Resources Information Center

Martin, Florence; Whitmer, John C.

2016-01-01

Adaptive learning gives learners control of context, pace, and scope of their learning experience. This strategy can be implemented in online learning by using the "Adaptive Release" feature in learning management systems. The purpose of this study was to use learning analytics research methods to explore the extent to which the adaptive…

New Perspectives on Teaching and Working with Languages in the Digital Era

ERIC Educational Resources Information Center

Pareja-Lora, Antonio, Ed.; Calle-Martínez, Cristina, Ed.; Rodríguez-Arancón, Pilar, Ed.

2016-01-01

This volume offers a comprehensive, up-to-date, empirical and methodological view over the new scenarios and environments for language teaching and learning recently emerged (e.g. blended learning, e-learning, ubiquitous learning, social learning, autonomous learning or lifelong learning), and also over some of the new approaches to language…

Applying Learning Design to Work-Based Learning

ERIC Educational Resources Information Center

Miao, Yongwu; Hoppe, Heinz Ulrich

2011-01-01

Learning design is currently slanted to reflect a course-based approach to learning. This article explores whether the concept of learning design could be applied to support the informal aspects of work-based learning (WBL). It also discusses the characteristics of WBL and presents a WBL-specific learning design that highlights the key features…

The Development of a Comprehensive and Coherent Theory of Learning

ERIC Educational Resources Information Center

Illeris, Knud

2015-01-01

This article is an account of how the author developed a comprehensive understanding of human learning over a period of almost 50 years. The learning theory includes the structure of learning, different types of learning, barriers of learning as well as how individual dispositions, age, the learning environment and general social and societal…

Adaptable, Personalised E-Learning Incorporating Learning Styles

ERIC Educational Resources Information Center

Peter, Sophie E.; Bacon, Elizabeth; Dastbaz, Mohammad

2010-01-01

Purpose: The purpose of this paper is to discuss how learning styles and theories are currently used within personalised adaptable e-learning adaptive systems. This paper then aims to describe the e-learning platform iLearn and how this platform is designed to incorporate learning styles as part of the personalisation offered by the system.…

Experiential Learning Theory as One of the Foundations of Adult Learning Practice Worldwide

ERIC Educational Resources Information Center

Dernova, Maiya

2015-01-01

The paper presents the analysis of existing theory, assumptions, and models of adult experiential learning. The experiential learning is a learning based on a learning cycle guided by the dual dialectics of action-reflection and experience-abstraction. It defines learning as a process of knowledge creation through experience transformation, so…

Enhancing Deep Learning: Lessons from the Introduction of Learning Teams in Management Education in France

ERIC Educational Resources Information Center

Borredon, Liz; Deffayet, Sylvie; Baker, Ann C.; Kolb, David

2011-01-01

Drawing from the reflective teaching and learning practices recommended in influential publications on learning styles, experiential learning, deep learning, and dialogue, the authors tested the concept of "learning teams" in the framework of a leadership program implemented for the first time in a top French management school…

Technology-Assisted Learning: A Longitudinal Field Study of Knowledge Category, Learning Effectiveness and Satisfaction in Language Learning

ERIC Educational Resources Information Center

Hui, W.; Hu, P. J.-H.; Clark, T. H. K.; Tam, K. Y.; Milton, J.

2008-01-01

A field experiment compares the effectiveness and satisfaction associated with technology-assisted learning with that of face-to-face learning. The empirical evidence suggests that technology-assisted learning effectiveness depends on the target knowledge category. Building on Kolb's experiential learning model, we show that technology-assisted…

Learning Together: The Role of the Online Community in Army Professional Education

DTIC Science & Technology

2005-05-26

Kolb , Experiential Learning : Experience as the Source of Learning and Development... Experiential Learning One model frequently discussed is experiential learning .15 Kolb develops this model through analysis of older models. One of the...observations about the experience. Kolb develops several characteristics of adult learning . Kolb discusses his model of experiential learning

Aberrant Learning Achievement Detection Based on Person-Fit Statistics in Personalized e-Learning Systems

ERIC Educational Resources Information Center

Liu, Ming-Tsung; Yu, Pao-Ta

2011-01-01

A personalized e-learning service provides learning content to fit learners' individual differences. Learning achievements are influenced by cognitive as well as non-cognitive factors such as mood, motivation, interest, and personal styles. This paper proposes the Learning Caution Indexes (LCI) to detect aberrant learning patterns. The philosophy…

Forum for Organisational Learning: Combining Learning at Work, Organisational Learning and Training in New Ways.

ERIC Educational Resources Information Center

Simons, P. R. J.; Germans, J.; Ruijters, M.

2003-01-01

The Forum for Organisational Learning is designed to bridge gaps among individual, group/team, and organizational learning. Organizational representatives form communities of learning; their core content involves five paradoxes: top-down and bottom-up approaches, working and learning, individual and organizational goals, structure and empowerment…

Mobile Learning for Teacher Professional Learning: Benefits, Obstacles and Issues

ERIC Educational Resources Information Center

Aubusson, Peter; Schuck, Sandy; Burden, Kevin

2009-01-01

This paper reflects on the role of mobile learning in teachers' professional learning. It argues that effective professional learning requires reflection and collaboration and that mobile learning is ideally suited to allow reflection-in-action and to capture the spontaneity of learning moments. The paper also argues for the value of…

Relationships between Learning Styles and Online Learning

ERIC Educational Resources Information Center

Santo, Susan A.

2006-01-01

This paper examines research on learning styles as related to online learning for adult learners. There is much disagreement regarding the definition of learning style. This paper defines it as an individual's preferred way of learning. The focus is on the extent to which learning styles are able to predict student success (e.g., grades,…

Learning "While" Working: Success Stories on Workplace Learning in Europe

ERIC Educational Resources Information Center

Lardinois, Rocio

2011-01-01

Cedefop's report "Learning while working: success stories on workplace learning in Europe" presents an overview of key trends in adult learning in the workplace. It takes stock of previous research carried out by Cedefop between 2003 and 2010 on key topics for adult learning: governance and the learning regions; social partner roles in…

E-Learning and Technologies for Open Distance Learning in Management Accounting

ERIC Educational Resources Information Center

Kashora, Trust; van der Poll, Huibrecht M.; van der Poll, John A.

2016-01-01

This research develops a knowledge acquisition and construction framework for e-learning for Management Accounting students at the University of South Africa, an Open Distance Learning institution which utilises e-learning. E-learning refers to the use of electronic applications and processes for learning, including the transfer of skills and…

From Learning Object to Learning Cell: A Resource Organization Model for Ubiquitous Learning

ERIC Educational Resources Information Center

Yu, Shengquan; Yang, Xianmin; Cheng, Gang

2013-01-01

The key to implementing ubiquitous learning is the construction and organization of learning resources. While current research on ubiquitous learning has primarily focused on concept models, supportive environments and small-scale empirical research, exploring ways to organize learning resources to make them available anywhere on-demand is also…

Course Management Systems and Blended Learning: An Innovative Learning Approach

ERIC Educational Resources Information Center

Chou, Amy Y.; Chou, David C.

2011-01-01

This article utilizes Rogers' innovation-decision process model (2003) and Beckman and Berry's innovation process model (2007) to create an innovative learning map that illustrates three learning methods (i.e., face-to-face learning, online learning, and blended learning) in two types of innovation (i.e., incremental innovation and radical…

Mobile Learning: Challenges for Teachers of Indian Open Universities

ERIC Educational Resources Information Center

Awadhiya, Ashish Kumar; Miglani, Anshu

2016-01-01

"Mobile Learning" (m-Learning) has emerged as a trend in the field of Open and Distance Learning (ODL). It is removing the time and geographical barriers for learning by placing learning opportunities at the fingertips of learners. ODL institutes in India are also adopting m-learning in different forms; however, it is not fully…

The Use of Vocabulary Learning Strategies in Teaching Turkish as a Second Language

ERIC Educational Resources Information Center

Baskin, Sami; Iscan, Adem; Karagoz, Beytullah; Birol, Gülnur

2017-01-01

Vocabulary learning is the basis of the language learning process in teaching Turkish as a second language. Vocabulary learning strategies need to be used in order for vocabulary learning to take place effectively. The use of vocabulary learning strategies facilitates vocabulary learning and increases student achievement. Each student uses a…

A Blended Mobile Learning Environment for Museum Learning

ERIC Educational Resources Information Center

Hou, Huei-Tse; Wu, Sheng-Yi; Lin, Peng-Chun; Sung, Yao-Ting; Lin, Jhe-Wei; Chang, Kuo-En

2014-01-01

The use of mobile devices for informal learning has gained attention over recent years. Museum learning is also regarded as an important research topic in the field of informal learning. This study explored a blended mobile museum learning environment (BMMLE). Moreover, this study applied three blended museum learning modes: (a) the traditional…

Learning with Collaborative Inquiry: A Science Learning Environment for Secondary Students

ERIC Educational Resources Information Center

Sun, Daner; Looi, Chee-Kit; Xie, Wenting

2017-01-01

When inquiry-based learning is designed for a collaborative context, the interactions that arise in the learning environment can become fairly complex. While the learning effectiveness of such learning environments has been reported in the literature, there have been fewer studies on the students' learning processes. To address this, the article…

MEAT: An Authoring Tool for Generating Adaptable Learning Resources

ERIC Educational Resources Information Center

Kuo, Yen-Hung; Huang, Yueh-Min

2009-01-01

Mobile learning (m-learning) is a new trend in the e-learning field. The learning services in m-learning environments are supported by fundamental functions, especially the content and assessment services, which need an authoring tool to rapidly generate adaptable learning resources. To fulfill the imperious demand, this study proposes an…

Learning Leaders for Learning Schools

ERIC Educational Resources Information Center

Brown, Frederick; Psencik, Kay

2017-01-01

Principals who pay attention to their own learning serve as models for others. What principals do every day, how they view and value student and educator learning, how they organize their staff into learning communities, and the designs they support for those teams to learn make a significant difference in the learning of those they serve. In this…

Investigation of the Relationship between Learning Process and Learning Outcomes in E-Learning Environments

ERIC Educational Resources Information Center

Yurdugül, Halil; Menzi Çetin, Nihal

2015-01-01

Problem Statement: Learners can access and participate in online learning environments regardless of time and geographical barriers. This brings up the umbrella concept of learner autonomy that contains self-directed learning, self-regulated learning and the studying process. Motivation and learning strategies are also part of this umbrella…

Development and Validation of Mobile Learning Acceptance Measure

ERIC Educational Resources Information Center

Sharma, Sujeet Kumar; Sarrab, Mohamed; Al-Shihi, Hafedh

2017-01-01

The growth of Smartphone usage, increased acceptance of electronic learning (E-learning), the availability of high reliability mobile networks and need for flexibility in learning have resulted in the growth of mobile learning (M-learning). This has led to a tremendous interest in the acceptance behaviors related to M-learning users among the…

Learning in a u-Museum: Developing a Context-Aware Ubiquitous Learning Environment

ERIC Educational Resources Information Center

Chen, Chia-Chen; Huang, Tien-Chi

2012-01-01

Context-awareness techniques can support learners in learning without time or location constraints by using mobile devices and associated learning activities in a real learning environment. Enrichment of context-aware technologies has enabled students to learn in an environment that integrates learning resources from both the real world and the…

The Relationship between Learning Conditions in the Workplace and Informal Learning Outcomes: A Study among Police Inspectors

ERIC Educational Resources Information Center

Janssens, Liezelot; Smet, Kelly; Onghena, Patrick; Kyndt, Eva

2017-01-01

Informal workplace learning has become a prominent reality in the knowledge society of today. For this reason, developing appropriate learning conditions in order to enhance workplace learning is dominating organizational agendas. However, research that investigates the relationship between important learning conditions and learning outcomes…

Investigating the Learning-Theory Foundations of Game-Based Learning: A Meta-Analysis

ERIC Educational Resources Information Center

Wu, W-H.; Hsiao, H-C.; Wu, P-L.; Lin, C-H.; Huang, S-H.

2012-01-01

Past studies on the issue of learning-theory foundations in game-based learning stressed the importance of establishing learning-theory foundation and provided an exploratory examination of established learning theories. However, we found research seldom addressed the development of the use or failure to use learning-theory foundations and…

Relational Analysis of High School Students' Cognitive Self-Regulated Learning Strategies and Conceptions of Learning Biology

ERIC Educational Resources Information Center

Sadi, Özlem

2017-01-01

The purpose of this study was to analyze the relation between students' cognitive learning strategies and conceptions of learning biology. The two scales, "Cognitive Learning Strategies" and "Conceptions of Learning Biology", were revised and adapted to biology in order to measure the students' learning strategies and…

Pre-Service English Teachers in Blended Learning Environment in Respect to Their Learning Approaches

ERIC Educational Resources Information Center

Yilmaz, M. Betul; Orhan, Feza

2010-01-01

Blended learning environment (BLE) is increasingly used in the world, especially in university degrees and it is based on integrating web-based learning and face-to-face (FTF) learning environments. Besides integrating different learning environments, BLE also addresses to students with different learning approaches. The "learning…

But Does It Work? Reflective Activities, Learning Outcomes and Instrumental Learning in Continuing Professional Development

ERIC Educational Resources Information Center

Roessger, Kevin M.

2015-01-01

This paper examines the relationship between reflective practice and instrumental learning within the context of continuing professional development (CPD). It is argued that instrumental learning is a unique process of adult learning, and reflective practice's impact on learning outcomes in instrumental learning contexts remains unclear. A…

The Effect of Integrated Learning Model and Critical Thinking Skill of Science Learning Outcomes

NASA Astrophysics Data System (ADS)

Fazriyah, N.; Supriyati, Y.; Rahayu, W.

2017-02-01

This study aimed to determine the effect of integrated learning model and critical thinking skill toward science learning outcomes. The study was conducted in SDN Kemiri Muka 1 Depok in fifth grade school year 2014/2015 using cluster random sampling was done to 80 students. Retrieval of data obtained through tests and analysis by Variance (ANOVA) and two lines with the design treatment by level 2x2. The results showed that: (1) science learning outcomes students that given thematic integrated learning model is higher than in the group of students given fragmented learning model, (2) there is an interaction effect between critical thinking skills with integrated learning model, (3) for students who have high critical thinking skills, science learning outcomes students who given by thematic integrated learning model higher than fragmented learning model and (4) for students who have the ability to think critically low yield higher learning science fragmented model. The results of this study indicate that thematic learning model with critical thinking skills can improve science learning outcomes of students.

Learning Bridge: Curricular Integration of Didactic and Experiential Education

PubMed Central

Arendt, Cassandra S.; Cawley, Pauline; Buhler, Amber V.; Elbarbry, Fawzy; Roberts, Sigrid C.

2010-01-01

Objectives To assess the impact of a program to integrate introductory pharmacy practice experiences with pharmaceutical science topics by promoting active learning, self-directed learning skills, and critical-thinking skills. Design The Learning Bridge, a curriculum program, was created to better integrate the material first-year (P1) students learned in pharmaceutical science courses into their introductory pharmacy practice experiences. Four Learning Bridge assignments required students to interact with their preceptors and answer questions relating to the pharmaceutical science material concurrently covered in their didactic courses. Assessment Surveys of students and preceptors were conducted to measure the effectiveness of the Learning Bridge process. Feedback indicated the Learning Bridge promoted students' interaction with their preceptors as well as development of active learning, self-directed learning, and critical-thinking skills. Students also indicated that the Learning Bridge assignments increased their learning, knowledge of drug information, and comprehension of relevant data in package inserts. Conclusion The Learning Bridge process integrated the didactic and experiential components of the curriculum, enhancing student learning in both areas, and offered students educational opportunities to interact more with their preceptors. PMID:20498741

Adaptive and perceptual learning technologies in medical education and training.

PubMed

Kellman, Philip J

2013-10-01

Recent advances in the learning sciences offer remarkable potential to improve medical education and maximize the benefits of emerging medical technologies. This article describes 2 major innovation areas in the learning sciences that apply to simulation and other aspects of medical learning: Perceptual learning (PL) and adaptive learning technologies. PL technology offers, for the first time, systematic, computer-based methods for teaching pattern recognition, structural intuition, transfer, and fluency. Synergistic with PL are new adaptive learning technologies that optimize learning for each individual, embed objective assessment, and implement mastery criteria. The author describes the Adaptive Response-Time-based Sequencing (ARTS) system, which uses each learner's accuracy and speed in interactive learning to guide spacing, sequencing, and mastery. In recent efforts, these new technologies have been applied in medical learning contexts, including adaptive learning modules for initial medical diagnosis and perceptual/adaptive learning modules (PALMs) in dermatology, histology, and radiology. Results of all these efforts indicate the remarkable potential of perceptual and adaptive learning technologies, individually and in combination, to improve learning in a variety of medical domains. Reprint & Copyright © 2013 Association of Military Surgeons of the U.S.

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-01-01

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Using computer-assisted learning to engage diverse learning styles in understanding business management principles.

PubMed

Frost, Mary E; Derby, Dustin C; Haan, Andrea G

2013-06-27

Objective : Changes in small business and insurance present challenges for newly graduated chiropractors. Technology that reaches identified, diverse learning styles may assist the chiropractic student in business classes to meet course outcomes better. Thus, the purpose of our study is to determine if the use of technology-based instructional aids enhance students' mastery of course learning outcomes. Methods : Using convenience sampling, 86 students completed a survey assessing course learning outcomes, learning style, and the helpfulness of lecture and computer-assisted learning related to content mastery. Quantitative analyses occurred. Results : Although respondents reported not finding the computer-assisted learning as helpful as the lecture, significant relationships were found between pre- and post-assisted learning measures of the learning outcomes 1 and 2 for the visual and kinesthetic groups. Surprisingly, however, all learning style groups exhibited significant pre- and post-assisted learning appraisal relationships with learning outcomes 3 and 4. Conclusion : While evidence exists within the current study of a relationship between students' learning of the course content corollary to the use of technologic instructional aids, the exact nature of the relationship remains unclear.

Examining the benefits of combining two learning strategies on recall of functional information in persons with multiple sclerosis.

PubMed

Goverover, Yael; Basso, Michael; Wood, Hali; Chiaravalloti, Nancy; DeLuca, John

2011-12-01

Forgetfulness occurs commonly in people with multiple sclerosis (MS), but few treatments alleviate this problem. This study examined the combined effect of two cognitive rehabilitation strategies to improve learning and memory in MS: self-generation and spaced learning. The hypothesis was that the combination of spaced learning and self-generation would yield better learning and memory recall performance than spaced learning alone. Using a within groups design, 20 participants with MS and 18 healthy controls (HC) were presented with three tasks (learning names, appointment, and object location), each in three learning conditions (Massed, Spaced Learning, and combination of spaced and generated information). Participants were required to recall the information they learned in each of these conditions immediately and 30 min following the initial presentation. The combination of spaced learning and self-generation yielded better recall than did spaced learning alone. In turn, spaced learning resulted in better recall than the massed rehearsal condition. These findings reveal that the combination of these two learning strategies may possess utility as a cognitive rehabilitation strategy.

Vocabulary learning in primary school children: working memory and long-term memory components.

PubMed

Morra, Sergio; Camba, Roberta

2009-10-01

The goal of this study was to investigate which working memory and long-term memory components predict vocabulary learning. We used a nonword learning paradigm in which 8- to 10-year-olds learned picture-nonword pairs. The nonwords varied in length (two vs. four syllables) and phonology (native sounding vs. including one Russian phoneme). Short, phonologically native nonwords were learned best, whereas learning long nonwords leveled off after a few presentation cycles. Linear structural equation analyses showed an influence of three constructs-phonological sensitivity, vocabulary knowledge, and central attentional resources (M capacity)-on nonword learning, but the extent of their contributions depended on specific characteristics of the nonwords to be learned. Phonological sensitivity predicted learning of all nonword types except short native nonwords, vocabulary predicted learning of only short native nonwords, and M capacity predicted learning of short nonwords but not long nonwords. The discussion considers three learning processes-effortful activation of phonological representations, lexical mediation, and passive associative learning-that use different cognitive resources and could be involved in learning different nonword types.

Learning to make things happen: Infants' observational learning of social and physical causal events.

PubMed

Waismeyer, Anna; Meltzoff, Andrew N

2017-10-01

Infants learn about cause and effect through hands-on experience; however, they also can learn about causality simply from observation. Such observational causal learning is a central mechanism by which infants learn from and about other people. Across three experiments, we tested infants' observational causal learning of both social and physical causal events. Experiment 1 assessed infants' learning of a physical event in the absence of visible spatial contact between the causes and effects. Experiment 2 developed a novel paradigm to assess whether infants could learn about a social causal event from third-party observation of a social interaction between two people. Experiment 3 compared learning of physical and social events when the outcomes occurred probabilistically (happening some, but not all, of the time). Infants demonstrated significant learning in all three experiments, although learning about probabilistic cause-effect relations was most difficult. These findings about infant observational causal learning have implications for children's rapid nonverbal learning about people, things, and their causal relations. Copyright © 2017 Elsevier Inc. All rights reserved.

Comparing team-based and mixed active-learning methods in an ambulatory care elective course.

PubMed

Zingone, Michelle M; Franks, Andrea S; Guirguis, Alexander B; George, Christa M; Howard-Thompson, Amanda; Heidel, Robert E

2010-11-10

To assess students' performance and perceptions of team-based and mixed active-learning methods in 2 ambulatory care elective courses, and to describe faculty members' perceptions of team-based learning. Using the 2 teaching methods, students' grades were compared. Students' perceptions were assessed through 2 anonymous course evaluation instruments. Faculty members who taught courses using the team-based learning method were surveyed regarding their impressions of team-based learning. The ambulatory care course was offered to 64 students using team-based learning (n = 37) and mixed active learning (n = 27) formats. The mean quality points earned were 3.7 (team-based learning) and 3.3 (mixed active learning), p < 0.001. Course evaluations for both courses were favorable. All faculty members who used the team-based learning method reported that they would consider using team-based learning in another course. Students were satisfied with both teaching methods; however, student grades were significantly higher in the team-based learning course. Faculty members recognized team-based learning as an effective teaching strategy for small-group active learning.

Beta phase synchronization in the frontal-temporal-cerebellar network during auditory-to-motor rhythm learning.

PubMed

Edagawa, Kouki; Kawasaki, Masahiro

2017-02-22

Rhythm is an essential element of dancing and music. To investigate the neural mechanisms underlying how rhythm is learned, we recorded electroencephalographic (EEG) data during a rhythm-reproducing task that asked participants to memorize an auditory stimulus and reproduce it via tapping. Based on the behavioral results, we divided the participants into Learning and No-learning groups. EEG analysis showed that error-related negativity (ERN) in the Learning group was larger than in the No-learning group. Time-frequency analysis of the EEG data showed that the beta power in right and left temporal area at the late learning stage was smaller than at the early learning stage in the Learning group. Additionally, the beta power in the temporal and cerebellar areas in the Learning group when learning to reproduce the rhythm were larger than in the No Learning group. Moreover, phase synchronization between frontal and temporal regions and between temporal and cerebellar regions at late stages of learning were larger than at early stages. These results indicate that the frontal-temporal-cerebellar beta neural circuits might be related to auditory-motor rhythm learning.

Describing the on-line graduate science student: An examination of learning style, learning strategy, and motivation

NASA Astrophysics Data System (ADS)

Spevak, Arlene J.

Research in science education has presented investigations and findings related to the significance of particular learning variables. For example, the factors of learning style, learning strategy and motivational orientation have been shown to have considerable impact upon learning in a traditional classroom setting. Although these data have been somewhat generous for the face-to-face learning situation, this does not appear to be the case for distance education, particularly the Internet-based environment. The purpose of this study was to describe the on-line graduate science student, regarding the variables of learning style, learning strategy and motivational orientation. It was believed that by understanding the characteristics of adult science learners and by identifying their learning needs, Web course designers and science educators could create on-line learning programs that best utilized students' strengths in learning science. A case study method using a questionnaire, inventories, telephone interviews and documents was applied to nine graduate science students who participated for ten weeks in an asynchronous, exclusively Internet mediated graduate science course at a large, Northeastern university. Within-case and cross-case analysis indicated that these learners displayed several categories of learning styles as well as learning strategies. The students also demonstrated high levels of both intrinsic and extrinsic motivation, and this, together with varying strategy use, may have compensated for any mismatch between their preferred learning styles and their learning environment. Recommendations include replicating this study in other online graduate science courses, administration of learning style and learning strategy inventories to perspective online graduate science students, incorporation of synchronous communication into on-line science courses, and implementation of appropriate technology that supports visual and kinesthetic learners. Although the study was limited to nine participants, the implications of the findings are clear. Most adult science students experience learning in an on-line environment. Those who are independent, highly motivated learners and utilize a variety of learning strategies can adapt their learning style to the situational aspects of the learning environment. This further indicates that Internet-based graduate science education institutions should become aware of different learning styles and strategies, and be prepared to address this variety when developing and delivering such programming.

Effects of cooperative learning strategy on undergraduate kinesiology students' learning styles.

PubMed

Meeuwsen, Harry J; King, George A; Pederson, Rockie

2005-10-01

A growing body of research supports cooperative learning as an effective teaching strategy. A specific cooperative learning strategy, Team-based Learning, was applied to a convenience sample of four undergraduate sophomore-level motor behavior courses over four semesters from Fall 2002 to Spring 2004 to examine whether this strategy would affect students' learning styles. The data from the Grasha-Reichmann Student Learning Style Scales indicated that this teaching strategy was associated with a significant decrease in the negative Avoidant and Dependent learning styles and an improvement in the positive Participant learning style.

Working memory supports inference learning just like classification learning.

PubMed

Craig, Stewart; Lewandowsky, Stephan

2013-08-01

Recent research has found a positive relationship between people's working memory capacity (WMC) and their speed of category learning. To date, only classification-learning tasks have been considered, in which people learn to assign category labels to objects. It is unknown whether learning to make inferences about category features might also be related to WMC. We report data from a study in which 119 participants undertook classification learning and inference learning, and completed a series of WMC tasks. Working memory capacity was positively related to people's classification and inference learning performance.

Problem based learning with scaffolding technique on geometry

NASA Astrophysics Data System (ADS)

Bayuningsih, A. S.; Usodo, B.; Subanti, S.

2018-05-01

Geometry as one of the branches of mathematics has an important role in the study of mathematics. This research aims to explore the effectiveness of Problem Based Learning (PBL) with scaffolding technique viewed from self-regulation learning toward students’ achievement learning in mathematics. The research data obtained through mathematics learning achievement test and self-regulated learning (SRL) questionnaire. This research employed quasi-experimental research. The subjects of this research are students of the junior high school in Banyumas Central Java. The result of the research showed that problem-based learning model with scaffolding technique is more effective to generate students’ mathematics learning achievement than direct learning (DL). This is because in PBL model students are more able to think actively and creatively. The high SRL category student has better mathematic learning achievement than middle and low SRL categories, and then the middle SRL category has better than low SRL category. So, there are interactions between learning model with self-regulated learning in increasing mathematic learning achievement.

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

Do emergency medicine residents and faculty have similar learning styles when assessed with the Kolb learning style assessment tool?

PubMed

Fredette, Jenna; O'Brien, Corinne; Poole, Christy; Nomura, Jason

2015-04-01

Experiential learning theory and the Kolb Learning Style Inventory (Kolb LSI) have influenced educators worldwide for decades. Knowledge of learning styles can create efficient learning environments, increase information retention, and improve learner satisfaction. Learning styles have been examined in medicine previously, but not specifically with Emergency Medicine (EM) residents and attendings. Using the Kolb LSI, the learning styles of Emergency Medicine residents and attendings were assessed. The findings showed that the majority of EM residents and attendings shared the accommodating learning style. This result was different than prior studies that found the majority of medical professionals had a converging learning style and other studies that found attendings often have different learning styles than residents. The issue of learning styles among emergency medical residents and attendings is important because learning style knowledge may have an impact on how a residency program structures curriculum and how EM residents are successfully, efficiently, and creatively educated.

Assessing the effect of cognitive styles with different learning modes on learning outcome.

PubMed

Liao, Chechen; Chuang, Shu-Hui

2007-08-01

In this study, similarities and differences in learning outcome associated with individual differences in cognitive styles are examined using the traditional (face-to-face) and web-based learning modes. 140 undergraduate students were categorized as having analytic or holistic cognitive styles by their scores on the Style of Learning and Thinking questionnaire. Four different conditions were studies; students with analytic cognitive style in a traditional learning mode, analytic cognitive style in a web-based learning mode, holistic cognitive style in a traditional learning mode, and holistic cognitive style in a web-based learning mode. Analysis of the data show that analytic style in traditional mode lead to significantly higher performance and perceived satisfaction than in other conditions. Satisfaction did not differ significantly between students with analytic style in web-based learning and those with holistic style in traditional learning. This suggest that integrating different learning modes into the learning environment may be insufficient to improve learners' satisfaction.

Early clinical experience: do students learn what we expect?

PubMed

Helmich, Esther; Bolhuis, Sanneke; Laan, Roland; Koopmans, Raymond

2011-07-01

Early clinical experience is thought to contribute to the professional development of medical students, but little is known about the kind of learning processes that actually take place. Learning in practice is highly informal and may be difficult to direct by predefined learning outcomes. Learning in medical practice includes a socialisation process in which some learning outcomes may be valued, but others neglected or discouraged. This study describes students' learning goals (prior to a Year 1 nursing attachment) and learning outcomes (after the attachment) in relation to institutional educational goals, and evaluates associations between learning outcomes, student characteristics and place of attachment. A questionnaire containing open-ended questions about learning goals and learning outcomes was administered to all Year 1 medical students (n = 347) before and directly after a 4-week nursing attachment in either a hospital or a nursing home. Two confirmatory focus group interviews were conducted and data were analysed using qualitative and quantitative content analyses. Students' learning goals corresponded with educational goals with a main emphasis on communication and empathy. Other learning goals included gaining insight into the organisation of health care and learning to deal with emotions. Self-reported learning outcomes were the same, but students additionally mentioned reflection on professional behaviour and their own future development. Women and younger students mentioned communication and empathy more often than men and older students. Individual learning goals, with the exception of communicating and empathising with patients, did not predict learning outcomes. Students' learning goals closely match educational goals, which are adequately met in early nursing attachments in both hospitals and nursing homes. Learning to deal with emotions was under-represented as a learning goal and learning outcome, which may indicate that emotional aspects of medical students' professional development are neglected in the first year of medical education. © Blackwell Publishing Ltd 2011.

A Literature Review of the Factors Influencing E-Learning and Blended Learning in Relation to Learning Outcome, Student Satisfaction and Engagement

ERIC Educational Resources Information Center

Nortvig, Anne-Mette; Petersen, Anne Kristine; Balle, Søren Hattesen

2018-01-01

In higher education, e-learning is gaining more and more impact, especially in the format of blended learning, and this new kind of traditional teaching and learning can be practiced in many ways. Several studies have compared face-to-face teaching to online learning and/or blended learning in order to try to define which of the formats provides,…

Mobile learning in medicine

NASA Astrophysics Data System (ADS)

Serkan Güllüoüǧlu, Sabri

2013-03-01

This paper outlines the main infrastructure for implicating mobile learning in medicine and present a sample mobile learning application for medical learning within the framework of mobile learning systems. Mobile technology is developing nowadays. In this case it will be useful to develop different learning environments using these innovations in internet based distance education. M-learning makes the most of being on location, providing immediate access, being connected, and acknowledges learning that occurs beyond formal learning settings, in places such as the workplace, home, and outdoors. Central to m-learning is the principle that it is the learner who is mobile rather than the device used to deliver m learning. The integration of mobile technologies into training has made learning more accessible and portable. Mobile technologies make it possible for a learner to have access to a computer and subsequently learning material and activities; at any time and in any place. Mobile devices can include: mobile phone, personal digital assistants (PDAs), personal digital media players (eg iPods, MP3 players), portable digital media players, portable digital multimedia players. Mobile learning (m-learning) is particularly important in medical education, and the major users of mobile devices are in the field of medicine. The contexts and environment in which learning occurs necessitates m-learning. Medical students are placed in hospital/clinical settings very early in training and require access to course information and to record and reflect on their experiences while on the move. As a result of this paper, this paper strives to compare and contrast mobile learning with normal learning in medicine from various perspectives and give insights and advises into the essential characteristics of both for sustaining medical education.

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

NASA Astrophysics Data System (ADS)

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.

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

PubMed

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

2016-02-01

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

Does the acceptance of hybrid learning affect learning approaches in France?

PubMed

Marco, Lionel Di; Venot, Alain; Gillois, Pierre

2017-01-01

Acceptance of a learning technology affects students' intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students' way of learning. We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (r s = 0.42, P= 0.03). Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students' time utilization, which explains their neutral intention to use the system.

The influence of tutor training for peer tutors in the dissection course on the learning behavior of students.

PubMed

Shiozawa, T; Hirt, B; Lammerding-Koeppel, M

2016-11-01

Student tutors in the dissection course are expected to meet high demands in their job, to fulfill these expectations they receive training. Combined tutor training is well accepted by tutors and tutees, however, it is not known how tutor training influences student learning. Deduced from the learning goals of the tutor training, a randomized, controlled, single-blinded study was set up with a quantitative cross-sectional analysis to compare student learning behavior. A total of 197 medical students, coached either by ten trained or ten untrained tutors, were enlisted in the study. To assess the students' learning behavior we employed the LIST questionnaire. A common factor analysis was calculated to extract dimensions. Factor scores of the extracted dimensions were calculated for both groups to estimate differences in learning behavior. Factor analysis of the LIST questionnaire revealed eight factors explaining 47.57% of the overall variance. The eight factors comprise: deep learning, attention, learning organization, cooperative learning, time management, learning effort, superficial learning and learning environment. Comparing the factor scores of the extracted dimensions, students coached by trained tutors learned significantly more with their fellow students (factor score in cooperative learning 0.194 vs. -0.205, p<0.05), than students trained by untrained tutors. Students coached by trained tutors also tend to be better organized in their learning (factor score in learning organization 0.115 vs. -0.122, p=0.16). The learning behavior of students coached by trained tutors differs from the learning behavior of students coached by untrained tutors. Students coached by trained tutors learn significantly more often in teams than their colleagues and are better organized. Copyright © 2016 Elsevier GmbH. All rights reserved.

Does the acceptance of hybrid learning affect learning approaches in France?

PubMed Central

2017-01-01

Purpose Acceptance of a learning technology affects students’ intention to use that technology, but the influence of the acceptance of a learning technology on learning approaches has not been investigated in the literature. A deep learning approach is important in the field of health, where links must be created between skills, knowledge, and habits. Our hypothesis was that acceptance of a hybrid learning model would affect students’ way of learning. Methods We analysed these concepts, and their correlations, in the context of a flipped classroom method using a local learning management system. In a sample of all students within a single year of study in the midwifery program (n= 38), we used 3 validated scales to evaluate these concepts (the Study Process Questionnaire, My Intellectual Work Tools, and the Hybrid E-Learning Acceptance Model: Learner Perceptions). Results Our sample had a positive acceptance of the learning model, but a neutral intention to use it. Students reported that they were distractible during distance learning. They presented a better mean score for the deep approach than for the superficial approach (P< 0.001), which is consistent with their declared learning strategies (personal reorganization of information; search and use of examples). There was no correlation between poor acceptance of the learning model and inadequate learning approaches. The strategy of using deep learning techniques was moderately correlated with acceptance of the learning model (rs= 0.42, P= 0.03). Conclusion Learning approaches were not affected by acceptance of a hybrid learning model, due to the flexibility of the tool. However, we identified problems in the students’ time utilization, which explains their neutral intention to use the system. PMID:29051406

Supporting cognitive engagement in a learning-by-doing learning environment: Case studies of participant engagement and social configurations in Kitchen Science Investigators

NASA Astrophysics Data System (ADS)

Gardner, Christina M.

Learning-by-doing learning environments support a wealth of physical engagement in activities. However, there is also a lot of variability in what participants learn in each enactment of these types of environments. Therefore, it is not always clear how participants are learning in these environments. In order to design technologies to support learning in these environments, we must have a greater understanding of how participants engage in learning activities, their goals for their engagement, and the types of help they need to cognitively engage in learning activities. To gain a greater understanding of participant engagement and factors and circumstances that promote and inhibit engagement, this dissertation explores and answers several questions: What are the types of interactions and experiences that promote and /or inhibit learning and engagement in learning-by-doing learning environments? What are the types of configurations that afford or inhibit these interactions and experiences in learning-by-doing learning environments? I explore answers to these questions through the context of two enactments of Kitchen Science Investigators (KSI), a learning-by-doing learning environment where middle-school aged children learn science through cooking from customizing recipes to their own taste and texture preferences. In small groups, they investigate effects of ingredients through the design of cooking and science experiments, through which they experience and learn about chemical, biological, and physical science phenomena and concepts (Clegg, Gardner, Williams, & Kolodner, 2006). The research reported in this dissertation sheds light on the different ways participant engagement promotes and/or inhibits cognitive engagement in by learning-by-doing learning environments through two case studies. It also provides detailed descriptions of the circumstances (social, material, and physical configurations) that promote and/or inhibit participant engagement in these learning environments through cross-case analyses of these cases. Finally, it offers suggestions about structuring activities, selecting materials and resources, and designing facilitation and software-realized scaffolding in the design of these types of learning environments. These design implications focus on affording participant engagement in science content and practices learning. Overall, the case studies, cross-case analyses, and empirically-based design implications begin to bridge the gap between theory and practice in the design and implementation of these learning environments. This is demonstrated by providing detailed and explanatory examples and factors that affect how participants take up the affordances of the learning opportunities designed into these learning environments.

Conceptualizing impact assessment as a learning process

DOE Office of Scientific and Technical Information (OSTI.GOV)

Sánchez, Luis E., E-mail: lsanchez@usp.br; Mitchell, Ross, E-mail: ross.mitchell@ualberta.net

This paper explores how project developers and their consultants, government regulators and stakeholders can learn from the impact assessment (IA) process, thus potentially improving its effectiveness and enhancing project sustainability. Despite the benefits that learning can bring to an organization, failure to learn appears commonplace both within the IA process and, once approved, subsequent industrial development. To nurture organizational learning through IA, enabling structures that foster information sharing and interpretation and enhance organizational memory are needed. In this paper learning outcomes are grouped into three categories: acquisition of knowledge and skills, developing new behaviors and developing sustainability-oriented norms and values.more » Means to achieve such outcomes include education and training, experiential learning, learning through public participation (social learning) and a ‘learning organization approach’. Societal expectations increasingly demand not only projects that ‘pass’ the review criteria of regulators, financiers and the community, but IA processes capable of delivering sustainable outcomes that include learning and sharing of knowledge. It is proposed that learning be treated as a purposeful – not as an accidental – outcome of IA, and facilitated by adopting a ‘learning organization approach’ coupled with best practice such as early stakeholder engagement. - Highlights: • Proponents are challenged to develop projects that deliver sustainable outcomes. • Passing the test of government approval may be insufficient to obtain a social license. • Learning by all stakeholders is vital to meet these challenges. • Learning outcomes have to go beyond instrumental learning to reach new behaviors, norms and values. • A “learning organization approach” can promote mutual learning and improve project design.« less

Strategies in probabilistic feedback learning in Parkinson patients OFF medication.

PubMed

Bellebaum, C; Kobza, S; Ferrea, S; Schnitzler, A; Pollok, B; Südmeyer, M

2016-04-21

Studies on classification learning suggested that altered dopamine function in Parkinson's Disease (PD) specifically affects learning from feedback. In patients OFF medication, enhanced learning from negative feedback has been described. This learning bias was not seen in observational learning from feedback, indicating different neural mechanisms for this type of learning. The present study aimed to compare the acquisition of stimulus-response-outcome associations in PD patients OFF medication and healthy control subjects in active and observational learning. 16 PD patients OFF medication and 16 controls were examined with three parallel learning tasks each, two feedback-based (active and observational) and one non-feedback-based paired associates task. No acquisition deficit was seen in the patients for any of the tasks. More detailed analyses on the learning strategies did, however, reveal that the patients showed more lose-shift responses during active feedback learning than controls, and that lose-shift and win-stay responses more strongly determined performance accuracy in patients than controls. For observational feedback learning, the performance of both groups correlated similarly with the performance in non-feedback-based paired associates learning and with the accuracy of observed performance. Also, patients and controls showed comparable evidence of feedback processing in observational learning. In active feedback learning, PD patients use alternative learning strategies than healthy controls. Analyses on observational learning did not yield differences between patients and controls, adding to recent evidence of a differential role of the human striatum in active and observational learning from feedback. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Validation of learning style measures: implications for medical education practice.

PubMed

Chapman, Dane M; Calhoun, Judith G

2006-06-01

It is unclear which learners would most benefit from the more individualised, student-structured, interactive approaches characteristic of problem-based and computer-assisted learning. The validity of learning style measures is uncertain, and there is no unifying learning style construct identified to predict such learners. This study was conducted to validate learning style constructs and to identify the learners most likely to benefit from problem-based and computer-assisted curricula. Using a cross-sectional design, 3 established learning style inventories were administered to 97 post-Year 2 medical students. Cognitive personality was measured by the Group Embedded Figures Test, information processing by the Learning Styles Inventory, and instructional preference by the Learning Preference Inventory. The 11 subscales from the 3 inventories were factor-analysed to identify common learning constructs and to verify construct validity. Concurrent validity was determined by intercorrelations of the 11 subscales. A total of 94 pre-clinical medical students completed all 3 inventories. Five meaningful learning style constructs were derived from the 11 subscales: student- versus teacher-structured learning; concrete versus abstract learning; passive versus active learning; individual versus group learning, and field-dependence versus field-independence. The concurrent validity of 10 of 11 subscales was supported by correlation analysis. Medical students most likely to thrive in a problem-based or computer-assisted learning environment would be expected to score highly on abstract, active and individual learning constructs and would be more field-independent. Learning style measures were validated in a medical student population and learning constructs were established for identifying learners who would most likely benefit from a problem-based or computer-assisted curriculum.

3D Game-Based Learning System for Improving Learning Achievement in Software Engineering Curriculum

ERIC Educational Resources Information Center

Su,Chung-Ho; Cheng, Ching-Hsue

2013-01-01

The advancement of game-based learning has encouraged many related studies, such that students could better learn curriculum by 3-dimension virtual reality. To enhance software engineering learning, this paper develops a 3D game-based learning system to assist teaching and assess the students' motivation, satisfaction and learning achievement. A…

Affective e-Learning: Using "Emotional" Data to Improve Learning in Pervasive Learning Environment

ERIC Educational Resources Information Center

Shen, Liping; Wang, Minjuan; Shen, Ruimin

2009-01-01

Using emotion detection technologies from biophysical signals, this study explored how emotion evolves during learning process and how emotion feedback could be used to improve learning experiences. This article also described a cutting-edge pervasive e-Learning platform used in a Shanghai online college and proposed an affective e-Learning model,…

The Interplay of Perceptions of the Learning Environment, Personality and Learning Strategies: A Study amongst International Business Studies Students

ERIC Educational Resources Information Center

Nijhuis, Jan; Segers, Mien; Gijselaers, Wim

2007-01-01

Previous research on students' learning strategies has examined the relationships between either perceptions of the learning environment or personality and learning strategies. The focus of this study was on the joint relationships between the students' perceptions of the learning environment, their personality, and the learning strategies they…

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

ERIC Educational Resources Information Center

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…

Assessment of Adaptive PBL's Impact on HOT Development of Computer Science Students

ERIC Educational Resources Information Center

Raiyn, Jamal; Tilchin, Oleg

2015-01-01

Meaningful learning based on PBL is new learning strategy. Compared to traditional learning strategy, the meaningful learning strategy put the student in center of the learning process. The roles of the student in the meaningful learning strategy will be increased. The Problem-based Learning (PBL) model is considered the most productive way to…

Work-Based Learning: Learning To Work; Working To Learn; Learning To Learn.

ERIC Educational Resources Information Center

Strumpf, Lori; Mains, Kristine

This document describes a work-based learning approach designed to integrate work and learning at the workplace and thereby help young people develop the skills required for changing workplaces. The following considerations in designing work-based programs are discussed: the trend toward high performance workplaces and changes in the way work is…

Student Reflections on an LIS Internship from a Service Learning Perspective Supporting Multiple Learning Theories

ERIC Educational Resources Information Center

Cooper, Linda Z.

2013-01-01

This paper presents a case study that examines an internship as service learning and participating students' perceptions of their learning in two learning environments. The internship experience in this situation is first examined to ascertain that it qualifies as service learning. At the conclusion of this service learning internship experience,…

Addressing Cognitive Processes in e-learning: TSOI Hybrid Learning Model

ERIC Educational Resources Information Center

Tsoi, Mun Fie; Goh, Ngoh Khang

2008-01-01

The development of e-learning materials for teaching and learning often needs to be guided by appropriate educational theories or models. As such, this paper provides alternative e-learning design pedagogy, the TSOI Hybrid Learning Model as a pedagogic model for the design of e-learning cognitively in science and chemistry education. This model is…

Supporting Interoperability and Context-Awareness in E-Learning through Situation-Driven Learning Processes

ERIC Educational Resources Information Center

Dietze, Stefan; Gugliotta, Alessio; Domingue, John

2009-01-01

Current E-Learning technologies primarily follow a data and metadata-centric paradigm by providing the learner with composite content containing the learning resources and the learning process description, usually based on specific metadata standards such as ADL SCORM or IMS Learning Design. Due to the design-time binding of learning resources,…

Web-Based Learning in a Geometry Course

ERIC Educational Resources Information Center

Chan, Hsungrow; Tsai, Pengheng; Huang, Tien-Yu

2006-01-01

This study concerns applying Web-based learning with learner controlled instructional materials in a geometry course. The experimental group learned in a Web-based learning environment, and the control group learned in a classroom. We observed that the learning method accounted for a total variation in learning effect of 19.1% in the 3rd grade and…

A Five-Stage Prediction-Observation-Explanation Inquiry-Based Learning Model to Improve Students' Learning Performance in Science Courses

ERIC Educational Resources Information Center

Hsiao, Hsien-Sheng; Chen, Jyun-Chen; Hong, Jon-Chao; Chen, Po-Hsi; Lu, Chow-Chin; Chen, Sherry Y.

2017-01-01

A five-stage prediction-observation-explanation inquiry-based learning (FPOEIL) model was developed to improve students' scientific learning performance. In order to intensify the science learning effect, the repertory grid technology-assisted learning (RGTL) approach and the collaborative learning (CL) approach were utilized. A quasi-experimental…

Learning Style, Sense of Community and Learning Effectiveness in Hybrid Learning Environment

ERIC Educational Resources Information Center

Chen, Bryan H.; Chiou, Hua-Huei

2014-01-01

The purpose of this study is to investigate how hybrid learning instruction affects undergraduate students' learning outcome, satisfaction and sense of community. The other aim of the present study is to examine the relationship between students' learning style and learning conditions in mixed online and face-to-face courses. A quasi-experimental…

The Nature of Self-Directed Learning and Transformational Learning in Self-Managing Bipolar Disorder to Stay Well

ERIC Educational Resources Information Center

Francik, Wendy A.

2012-01-01

The purpose of the research was to explore the self-directed learning and transformational learning experiences among persons with bipolar disorder. A review of previous research pointed out how personal experiences with self-directed learning and transformational learning facilitated individuals' learning to manage HIV, Methicillan-resitant…

Transformative Education through International Service-­Learning: Realising an Ethical Ecology of Learning. Routledge Research in International and Comparative Education

ERIC Educational Resources Information Center

Bamber, Philip M.

2016-01-01

Transformative learning is a compelling approach to learning that is becoming increasingly popular in a diverse range of educational settings and encounters. This book reconceptualises transformative learning through an investigation of the learning process and outcomes of International Service-Learning (ISL), a pedagogical approach that blends…

Adaptation Criteria for the Personalised Delivery of Learning Materials: A Multi-Stage Empirical Investigation

ERIC Educational Resources Information Center

Thalmann, Stefan

2014-01-01

Personalised e-Learning represents a major step-change from the one-size-fits-all approach of traditional learning platforms to a more customised and interactive provision of learning materials. Adaptive learning can support the learning process by tailoring learning materials to individual needs. However, this requires the initial preparation of…

A Research on the Generative Learning Model Supported by Context-Based Learning

ERIC Educational Resources Information Center

Ulusoy, Fatma Merve; Onen, Aysem Seda

2014-01-01

This study is based on the generative learning model which involves context-based learning. Using the generative learning model, we taught the topic of Halogens. This topic is covered in the grade 10 chemistry curriculum using activities which are designed in accordance with the generative learning model supported by context-based learning. The…

Investigating the Determinants and Age and Gender Differences in the Acceptance of Mobile Learning

ERIC Educational Resources Information Center

Wang, Yi-Shun; Wu, Ming-Cheng; Wang, Hsiu-Yuan

2009-01-01

With the proliferation of mobile computing technology, mobile learning (m-learning) will play a vital role in the rapidly growing electronic learning market. M-learning is the delivery of learning to students anytime and anywhere through the use of wireless Internet and mobile devices. However, acceptance of m-learning by individuals is critical…

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

ERIC Educational Resources Information Center

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,…

Assessing Experiential Learning Styles: A Methodological Reconstruction and Validation of the Kolb Learning Style Inventory

ERIC Educational Resources Information Center

Manolis, Chris; Burns, David J.; Assudani, Rashmi; Chinta, Ravi

2013-01-01

To understand experiential learning, many have reiterated the need to be able to identify students' learning styles. Kolb's Learning Style Model is the most widely accepted learning style model and has received a substantial amount of empirical support. Kolb's Learning Style Inventory (LSI), although one of the most widely utilized instruments to…

College Students Attitudes toward Learning Process and Outcome of Online Instruction and Distance Learning across Learning Styles

ERIC Educational Resources Information Center

Nguyen, Dat-Dao; Zhang, Yue

2011-01-01

This study uses the Learning-Style Inventory--LSI (Smith & Kolb, 1985) to explore to what extent student attitudes toward learning process and outcome of online instruction and Distance Learning are affected by their cognitive styles and learning behaviors. It finds that there are not much statistically significant differences in perceptions…

Applying HOPSCOTCH as an Exer-Learning Game in English Lessons: Two Exploratory Studies

ERIC Educational Resources Information Center

Lucht, Martina; Heidig, Steffi

2013-01-01

This article describes HOPSCOTCH, a design concept for an "exer-learning game" to engage elementary school children in learning. Exer-learning is a new genre of digital learning games that combines playing and learning with physical activity (exercise). HOPSCOTCH is a first design concept for exer-learning games that can be applied to…

"Learning-in-Action" and "Learning Inaction": Advancing the Theory and Practice of Critical Action Learning

ERIC Educational Resources Information Center

Vince, Russ

2008-01-01

This paper seeks to improve our understanding of the emotional and political dynamics that are generated (and too often avoided) in action learning. The idea at the centre of the paper is a distinction between "learning-in-action" and "learning inaction". The phrase "learning-in-action" represents the value of action…

Invited Reaction: Influences of Formal Learning, Personal Learning Orientation, and Supportive Learning Environment on Informal Learning

ERIC Educational Resources Information Center

Cseh, Maria; Manikoth, Nisha N.

2011-01-01

As the authors of the preceding article (Choi and Jacobs, 2011) have noted, the workplace learning literature shows evidence of the complementary and integrated nature of formal and informal learning in the development of employee competencies. The importance of supportive learning environments in the workplace and of employees' personal learning…

Investigating Agricultural Instructors' Attitudes toward E-Learning in Iran

ERIC Educational Resources Information Center

Mohammadi, Davoud; Hosseini, Seyed Mahmoud; Fami, Hossein Shabanali

2011-01-01

With the rapid changes in all types of learning and teaching environments, there is a need to implement electronic learning (e-learning) to train students with new technologies. However the trend of using e-learning as learning and/or teaching tool is now rapidly expanding into education. Although e-learning environments are popular, there is…

A Methodological Approach to Encourage the Service-Oriented Learning Systems Development

ERIC Educational Resources Information Center

Diez, David; Malizia, Alessio; Aedo, Ignacio; Diaz, Paloma; Fernandez, Camino; Dodero, Juan-Manuel

2009-01-01

The basic idea of service-oriented learning is that a learning environment should be conceived as a set of independent units of learning packaged as learning services. The design, development and deployment of a learning system based on integrating different learning services needs both a technological platform to support the system as well as a…

What Every Worker Wants? Evidence about Employee Demand for Learning

ERIC Educational Resources Information Center

Findlay, Jeanette; Findlay, Patricia; Warhurst, Chris

2012-01-01

In order to boost learning, recent UK governments have invested in trade union-led workplace learning. Investing in the supply of learning is useful but ignores the demand for learning by workers, about which there is little research. This paper addresses this lacunae by analysing worker demand for learning, which workers want learning, what…

To Activate English Learning: Listen and Speak in Real Life Context with an AR Featured U-Learning System

ERIC Educational Resources Information Center

Ho, Shu-Chun; Hsieh, Sheng-Wen; Sun, Pei-Chen; Chen, Cheng-Ming

2017-01-01

The increasing advance of mobile devices and wireless technologies has generated great interest in ubiquitous learning (u-learning) among academia, practitioners, and policy makers. However, design elements that incorporate learning styles and learning strategies into u-learning system applications in English as a Foreign Language (EFL) education…

Student and Faculty Beliefs about Learning in Higher Education: Implications for Teaching

ERIC Educational Resources Information Center

Dandy, Kristina L.; Bendersky, Karen

2014-01-01

Beliefs about learning can influence whether or not a student learns course material. However, few studies in higher education have compared student and faculty beliefs about learning. In the current study, students and faculty agreed on many aspects of learning--including the definition of learning, which most hinders learning and where learning…

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

ERIC Educational Resources Information Center

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…

How an Orientation to Learning Influences the Expansive-Restrictive Nature of Teacher Learning and Change

ERIC Educational Resources Information Center

Feeney, Eric J.

2016-01-01

This study examined teachers' learning situated in a school to reveal factors that support and hinder learning in the workplace. The investigation analyzed teachers' orientation to learning, examining beliefs, practices, and experiences about teachers' learning in relation to change in the workplace. A hypothesis is that teacher learning and…

Learning during Processing: Word Learning Doesn't Wait for Word Recognition to Finish

ERIC Educational Resources Information Center

Apfelbaum, Keith S.; McMurray, Bob

2017-01-01

Previous research on associative learning has uncovered detailed aspects of the process, including what types of things are learned, how they are learned, and where in the brain such learning occurs. However, perceptual processes, such as stimulus recognition and identification, take time to unfold. Previous studies of learning have not addressed…

A Peer-Assisted Learning Experience in Computer Programming Language Learning and Developing Computer Programming Skills

ERIC Educational Resources Information Center

Altintas, Tugba; Gunes, Ali; Sayan, Hamiyet

2016-01-01

Peer learning or, as commonly expressed, peer-assisted learning (PAL) involves school students who actively assist others to learn and in turn benefit from an effective learning environment. This research was designed to support students in becoming more autonomous in their learning, help them enhance their confidence level in tackling computer…

Multidimensionality of Teachers' Graded Responses for Preschoolers' Stylistic Learning Behavior: The Learning-to-Learn Scales

ERIC Educational Resources Information Center

McDermott, Paul A.; Fantuzzo, John W.; Warley, Heather P.; Waterman, Clare; Angelo, Lauren E.; Gadsden, Vivian L.; Sekino, Yumiko

2011-01-01

Assessment of preschool learning behavior has become very popular as a mechanism to inform cognitive development and promote successful interventions. The most widely used measures offer sound predictions but distinguish only a few types of stylistic learning and lack sensitive growth detection. The Learning-to-Learn Scales was designed to…

Transformative Learning: Patterns of Psychophysiologic Response and Technology-Enabled Learning and Intervention Systems

DTIC Science & Technology

2008-09-01

Psychophysiologic Response and Technology -Enabled Learning and Intervention Systems PRINCIPAL INVESTIGATOR: Leigh W. Jerome, Ph.D...NUMBER Transformative Learning : Patterns of Psychophysiologic Response and Technology - Enabled Learning and Intervention Systems 5b. GRANT NUMBER...project entitled “Transformative Learning : Patterns of Psychophysiologic Response in Technology Enabled Learning and Intervention Systems.” The

Exploring Students' Perceptions of Service-Learning Experiences in an Undergraduate Web Design Course

ERIC Educational Resources Information Center

Lee, Sang Joon; Wilder, Charlie; Yu, Chien

2018-01-01

Service-learning is an experiential learning experience where students learn and develop through active participation in community service to meet the needs of a community. This study explored student learning experiences in a service-learning group project and their perceptions of service-learning in an undergraduate web design course. The data…

Representing Authentic Learning Designs Supporting the Development of Online Communities of Learners

ERIC Educational Resources Information Center

Oliver, Ron; Herrington, Anthony; Herrington, Jan; Reeves, Thomas C.

2007-01-01

Authentic learning designs have been explored for some time now and have frequently been shown to provide learning settings that provide many meaningful contexts for learning. These meaningful contexts provide not only encouragement for students to learn but also a raft of learning enhancements including higher-order learning and forms of learning…

Test of e-Learning Related Attitudes (TeLRA) Scale: Development, Reliability and Validity Study

ERIC Educational Resources Information Center

Kisanga, D. H.; Ireson, G.

2016-01-01

The Tanzanian education system is in transition from face-to-face classroom learning to e-learning. E-learning is a new learning approach in Tanzanian Higher Learning Institutions [HLIs] and with teachers being the key stakeholders of all formal education, investigating their attitude towards e-learning is essential. So far, however, there has…

Students' Feedback of mDPBL Approach and the Learning Impact towards Computer Networks Teaching and Learning

ERIC Educational Resources Information Center

Winarno, Sri; Muthu, Kalaiarasi Sonai; Ling, Lew Sook

2018-01-01

This study presents students' feedback and learning impact on design and development of a multimedia learning in Direct Problem-Based Learning approach (mDPBL) for Computer Networks in Dian Nuswantoro University, Indonesia. This study examined the usefulness, contents and navigation of the multimedia learning as well as learning impacts towards…

The Effects of Mobile Natural-Science Learning Based on the 5E Learning Cycle: A Case Study

ERIC Educational Resources Information Center

Liu, Tzu-Chien; Peng, Hsinyi; Wu, Wen-Hsuan; Lin, Ming-Sheng

2009-01-01

This study has three major purposes, including designing mobile natural-science learning activities that rest on the 5E Learning Cycle, examining the effects of these learning activities on students' performances of learning aquatic plants, and exploring students' perceptions toward these learning activities. A case-study method is utilized and…

Stories of Practitioner Enquiry: Using Narrative Interviews to Explore Teachers' Perspectives of Learning to Learn

ERIC Educational Resources Information Center

Thomas, Ulrike; Tiplady, Lucy; Wall, Kate

2014-01-01

The Campaign for Learning's Learning to Learn Phase 4 was a research project in which teachers undertook practitioner enquiry to explore innovative pedagogies under the umbrella term of learning to learn. In 2008, to gain greater understanding of what this process meant to the participating teachers the research team at Newcastle University…

Integrating Learning, Problem Solving, and Engagement in Narrative-Centered Learning Environments

ERIC Educational Resources Information Center

Rowe, Jonathan P.; Shores, Lucy R.; Mott, Bradford W.; Lester, James C.

2011-01-01

A key promise of narrative-centered learning environments is the ability to make learning engaging. However, there is concern that learning and engagement may be at odds in these game-based learning environments. This view suggests that, on the one hand, students interacting with a game-based learning environment may be engaged but unlikely to…

Teaching Smart People How to Learn.

ERIC Educational Resources Information Center

Argyris, Chris

1991-01-01

Professionals frequently are least able to learn because they have rarely experienced learning-related failure and are prone to defensive reasoning. Companies can become learning organizations by helping managers and employees learn to analyze their behavior and learn productively. (SK)

Blended Learning as Transformational Institutional Learning

ERIC Educational Resources Information Center

VanDerLinden, Kim

2014-01-01

This chapter reviews institutional approaches to blended learning and the ways in which institutions support faculty in the intentional redesign of courses to produce optimal learning. The chapter positions blended learning as a strategic opportunity to engage in organizational learning.

Evoked prior learning experience and approach to learning as predictors of academic achievement.

PubMed

Trigwell, Keith; Ashwin, Paul; Millan, Elena S

2013-09-01

In separate studies and research from different perspectives, five factors are found to be among those related to higher quality outcomes of student learning (academic achievement). Those factors are higher self-efficacy, deeper approaches to learning, higher quality teaching, students' perceptions that their workload is appropriate, and greater learning motivation. University learning improvement strategies have been built on these research results. To investigate how students' evoked prior experience, perceptions of their learning environment, and their approaches to learning collectively contribute to academic achievement. This is the first study to investigate motivation and self-efficacy in the same educational context as conceptions of learning, approaches to learning and perceptions of the learning environment. Undergraduate students (773) from the full range of disciplines were part of a group of over 2,300 students who volunteered to complete a survey of their learning experience. On completing their degrees 6 and 18 months later, their academic achievement was matched with their learning experience survey data. A 77-item questionnaire was used to gather students' self-report of their evoked prior experience (self-efficacy, learning motivation, and conceptions of learning), perceptions of learning context (teaching quality and appropriate workload), and approaches to learning (deep and surface). Academic achievement was measured using the English honours degree classification system. Analyses were conducted using correlational and multi-variable (structural equation modelling) methods. The results from the correlation methods confirmed those found in numerous earlier studies. The results from the multi-variable analyses indicated that surface approach to learning was the strongest predictor of academic achievement, with self-efficacy and motivation also found to be directly related. In contrast to the correlation results, a deep approach to learning was not related to academic achievement, and teaching quality and conceptions of learning were only indirectly related to achievement. Research aimed at understanding how students experience their learning environment and how that experience relates to the quality of their learning needs to be conducted using a wider range of variables and more sophisticated analytical methods. In this study of one context, some of the relations found in earlier bivariate studies, and on which learning intervention strategies have been built, are not confirmed when more holistic teaching-learning contexts are analysed using multi-variable methods. © 2012 The British Psychological Society.

Effects of congruence between preferred and perceived learning environments in nursing education in Taiwan: a cross-sectional study.

PubMed

Yeh, Ting-Kuang; Huang, Hsiu-Mei; Chan, Wing P; Chang, Chun-Yen

2016-05-20

To investigate the effects of congruence between preferred and perceived learning environments on learning outcomes of nursing students. A nursing course at a university in central Taiwan. 124 Taiwanese nursing students enrolled in a 13-week problem-based Fundamental Nursing curriculum. Students' preferred learning environment, perceptions about the learning environment and learning outcomes (knowledge, self-efficacy and attitudes) were assessed. On the basis of test scores measuring their preferred and perceived learning environments, students were assigned to one of two groups: a 'preferred environment aligned with perceived learning environment' group and a 'preferred environment discordant with perceived learning environment' group. Learning outcomes were analysed by group. Most participants preferred learning in a classroom environment that combined problem-based and lecture-based instruction. However, a mismatch of problem-based instruction with students' perceptions occurred. Learning outcomes were significantly better when students' perceptions of their instructional activities were congruent with their preferred learning environment. As problem-based learning becomes a focus of educational reform in nursing, teachers need to be aware of students' preferences and perceptions of the learning environment. Teachers may also need to improve the match between an individual student's perception and a teacher's intention in the learning environment, and between the student's preferred and actual perceptions of the learning environment. Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://www.bmj.com/company/products-services/rights-and-licensing/

Dissociation between Active and Observational Learning from Positive and Negative Feedback in Parkinsonism

PubMed Central

Kobza, Stefan; Ferrea, Stefano; Schnitzler, Alfons; Pollok, Bettina

2012-01-01

Feedback to both actively performed and observed behaviour allows adaptation of future actions. Positive feedback leads to increased activity of dopamine neurons in the substantia nigra, whereas dopamine neuron activity is decreased following negative feedback. Dopamine level reduction in unmedicated Parkinson’s Disease patients has been shown to lead to a negative learning bias, i.e. enhanced learning from negative feedback. Recent findings suggest that the neural mechanisms of active and observational learning from feedback might differ, with the striatum playing a less prominent role in observational learning. Therefore, it was hypothesized that unmedicated Parkinson’s Disease patients would show a negative learning bias only in active but not in observational learning. In a between-group design, 19 Parkinson’s Disease patients and 40 healthy controls engaged in either an active or an observational probabilistic feedback-learning task. For both tasks, transfer phases aimed to assess the bias to learn better from positive or negative feedback. As expected, actively learning patients showed a negative learning bias, whereas controls learned better from positive feedback. In contrast, no difference between patients and controls emerged for observational learning, with both groups showing better learning from positive feedback. These findings add to neural models of reinforcement-learning by suggesting that dopamine-modulated input to the striatum plays a minor role in observational learning from feedback. Future research will have to elucidate the specific neural underpinnings of observational learning. PMID:23185586

Dynamic Influence of Emotional States on Novel Word Learning

PubMed Central

Guo, Jingjing; Zou, Tiantian; Peng, Danling

2018-01-01

Many researchers realize that it's unrealistic to isolate language learning and processing from emotions. However, few studies on language learning have taken emotions into consideration so far, so that the probable influences of emotions on language learning are unclear. The current study thereby aimed to examine the effects of emotional states on novel word learning and their dynamic changes with learning continuing and task varying. Positive, negative or neutral pictures were employed to induce a given emotional state, and then participants learned the novel words through association with line-drawing pictures in four successive learning phases. At the end of each learning phase, participants were instructed to fulfill a semantic category judgment task (in Experiment 1) or a word-picture semantic consistency judgment task (in Experiment 2) to explore the effects of emotional states on different depths of word learning. Converging results demonstrated that negative emotional state led to worse performance compared with neutral condition; however, how positive emotional state affected learning varied with learning task. Specifically, a facilitative role of positive emotional state in semantic category learning was observed but disappeared in word specific meaning learning. Moreover, the emotional modulation on novel word learning was quite dynamic and changeable with learning continuing, and the final attainment of the learned words tended to be similar under different emotional states. The findings suggest that the impact of emotion can be offset when novel words became more and more familiar and a part of existent lexicon. PMID:29695994

Dynamic Influence of Emotional States on Novel Word Learning.

PubMed

Guo, Jingjing; Zou, Tiantian; Peng, Danling

2018-01-01

Many researchers realize that it's unrealistic to isolate language learning and processing from emotions. However, few studies on language learning have taken emotions into consideration so far, so that the probable influences of emotions on language learning are unclear. The current study thereby aimed to examine the effects of emotional states on novel word learning and their dynamic changes with learning continuing and task varying. Positive, negative or neutral pictures were employed to induce a given emotional state, and then participants learned the novel words through association with line-drawing pictures in four successive learning phases. At the end of each learning phase, participants were instructed to fulfill a semantic category judgment task (in Experiment 1) or a word-picture semantic consistency judgment task (in Experiment 2) to explore the effects of emotional states on different depths of word learning. Converging results demonstrated that negative emotional state led to worse performance compared with neutral condition; however, how positive emotional state affected learning varied with learning task. Specifically, a facilitative role of positive emotional state in semantic category learning was observed but disappeared in word specific meaning learning. Moreover, the emotional modulation on novel word learning was quite dynamic and changeable with learning continuing, and the final attainment of the learned words tended to be similar under different emotional states. The findings suggest that the impact of emotion can be offset when novel words became more and more familiar and a part of existent lexicon.

Main factors in E-Learning for the Equivalency Education Program (E-LEEP)

NASA Astrophysics Data System (ADS)

Yel, M. B.; Sfenrianto

2018-03-01

There is a tremendous learning gap between formal education and non-formal education. E-Learning can facilitate non-formal education learners in improving the learning process. In this study, we present the main factors behind the E-learning for the Equivalency Education Program (E-LEEP) initiative in Indonesia. There are four main factors proposed, namely: standardization, learning materials, learning process, and learners’ characteristics. Each factor supports each other to achieve the learning process of E-LEEP in Indonesia. Although not yet proven, the E-learning should be developed followed the main factors for the non-formal education. This is because those factors can improve the quality of E-Learning for the Equivalency Education Program.

The evolution of eLearning background, blends and blackboard....

PubMed

Sleator, Roy D

2010-01-01

This review of eLearning is divided into three sections: the first charts the evolution of eLearning from early correspondence courses to the current computer mediated approaches to distributed learning. The second section deals with the concept of blended learning; combining best practice in face-to-face and online learning. The final section focuses on current platform technologies in eLearning and outlines the strengths and weaknesses of learning management systems such as Blackboard.

[E-learning and university nursing education: an overview of reviews].

PubMed

De Caro, Walter; Marucci, Anna Rita; Giordani, Mauro; Sansoni, Julita

2014-01-01

The increasing use of digital technologies and e-learning in nursing education and the health professions was also reflected in the time to many studies and reviews. The aim of this overview was to analyze education through e-learning technologies for nursing and health professional students. A comprehensive search of literature was conducted using database PubMed/MEDLINE, Ebsco/CINAHL, 2003-2013. The search strategy resulted in the inclusion, in first instance, of 9732 items. After the reduction of duplicates, applying limits and other parameters of inclusion/exclusion and, at the end, evaluation of quality through AMSTARD check list, we included in this overview, 22 reviews. The analized reviews were allowed to spread in different topic areas: study population (students and faculty), e-learning methods (blended learning Game/3D/situated learning) and evaluation (information technology, learning satisfaction comparison of e-learning with the traditional teaching methods) This overview demonstrates that e-learning in nursing academic education is a valid alternative to traditional learning. If e-learning activities are well structured and modulated, some advantages and economies are clear possible. Regard effects of e-learning on the improvement of ability, data are at the momenti limited when compared to traditional learning. Often e-learning appear as an adjunct respect traditional learning, but is necessary consider e-learning and digital tecnology as priority for the future of education of nursing students.

Broadening conceptions of learning in medical education: the message from teamworking.

PubMed

Bleakley, Alan

2006-02-01

There is a mismatch between the broad range of learning theories offered in the wider education literature and a relatively narrow range of theories privileged in the medical education literature. The latter are usually described under the heading of 'adult learning theory'. This paper critically addresses the limitations of the current dominant learning theories informing medical education. An argument is made that such theories, which address how an individual learns, fail to explain how learning occurs in dynamic, complex and unstable systems such as fluid clinical teams. Models of learning that take into account distributed knowing, learning through time as well as space, and the complexity of a learning environment including relationships between persons and artefacts, are more powerful in explaining and predicting how learning occurs in clinical teams. Learning theories may be privileged for ideological reasons, such as medicine's concern with autonomy. Where an increasing amount of medical education occurs in workplace contexts, sociocultural learning theories offer a best-fit exploration and explanation of such learning. We need to continue to develop testable models of learning that inform safe work practice. One type of learning theory will not inform all practice contexts and we need to think about a range of fit-for-purpose theories that are testable in practice. Exciting current developments include dynamicist models of learning drawing on complexity theory.

Distance learning in academic health education.

PubMed

Mattheos, N; Schittek, M; Attström, R; Lyon, H C

2001-05-01

Distance learning is an apparent alternative to traditional methods in education of health care professionals. Non-interactive distance learning, interactive courses and virtual learning environments exist as three different generations in distance learning, each with unique methodologies, strengths and potential. Different methodologies have been recommended for distance learning, varying from a didactic approach to a problem-based learning procedure. Accreditation, teamwork and personal contact between the tutors and the students during a course provided by distance learning are recommended as motivating factors in order to enhance the effectiveness of the learning. Numerous assessment methods for distance learning courses have been proposed. However, few studies report adequate tests for the effectiveness of the distance-learning environment. Available information indicates that distance learning may significantly decrease the cost of academic health education at all levels. Furthermore, such courses can provide education to students and professionals not accessible by traditional methods. Distance learning applications still lack the support of a solid theoretical framework and are only evaluated to a limited extent. Cases reported so far tend to present enthusiastic results, while more carefully-controlled studies suggest a cautious attitude towards distance learning. There is a vital need for research evidence to identify the factors of importance and variables involved in distance learning. The effectiveness of distance learning courses, especially in relation to traditional teaching methods, must therefore be further investigated.

Skill learning and the evolution of social learning mechanisms.

PubMed

van der Post, Daniel J; Franz, Mathias; Laland, Kevin N

2016-08-24

Social learning is potentially advantageous, but evolutionary theory predicts that (i) its benefits may be self-limiting because social learning can lead to information parasitism, and (ii) these limitations can be mitigated via forms of selective copying. However, these findings arise from a functional approach in which learning mechanisms are not specified, and which assumes that social learning avoids the costs of asocial learning but does not produce information about the environment. Whether these findings generalize to all kinds of social learning remains to be established. Using a detailed multi-scale evolutionary model, we investigate the payoffs and information production processes of specific social learning mechanisms (including local enhancement, stimulus enhancement and observational learning) and their evolutionary consequences in the context of skill learning in foraging groups. We find that local enhancement does not benefit foraging success, but could evolve as a side-effect of grouping. In contrast, stimulus enhancement and observational learning can be beneficial across a wide range of environmental conditions because they generate opportunities for new learning outcomes. In contrast to much existing theory, we find that the functional outcomes of social learning are mechanism specific. Social learning nearly always produces information about the environment, and does not always avoid the costs of asocial learning or support information parasitism. Our study supports work emphasizing the value of incorporating mechanistic detail in functional analyses.

Individual differences in implicit motor learning: task specificity in sensorimotor adaptation and sequence learning.

PubMed

Stark-Inbar, Alit; Raza, Meher; Taylor, Jordan A; Ivry, Richard B

2017-01-01

In standard taxonomies, motor skills are typically treated as representative of implicit or procedural memory. We examined two emblematic tasks of implicit motor learning, sensorimotor adaptation and sequence learning, asking whether individual differences in learning are correlated between these tasks, as well as how individual differences within each task are related to different performance variables. As a prerequisite, it was essential to establish the reliability of learning measures for each task. Participants were tested twice on a visuomotor adaptation task and on a sequence learning task, either the serial reaction time task or the alternating reaction time task. Learning was evident in all tasks at the group level and reliable at the individual level in visuomotor adaptation and the alternating reaction time task but not in the serial reaction time task. Performance variability was predictive of learning in both domains, yet the relationship was in the opposite direction for adaptation and sequence learning. For the former, faster learning was associated with lower variability, consistent with models of sensorimotor adaptation in which learning rates are sensitive to noise. For the latter, greater learning was associated with higher variability and slower reaction times, factors that may facilitate the spread of activation required to form predictive, sequential associations. Interestingly, learning measures of the different tasks were not correlated. Together, these results oppose a shared process for implicit learning in sensorimotor adaptation and sequence learning and provide insight into the factors that account for individual differences in learning within each task domain. We investigated individual differences in the ability to implicitly learn motor skills. As a prerequisite, we assessed whether individual differences were reliable across test sessions. We found that two commonly used tasks of implicit learning, visuomotor adaptation and the alternating serial reaction time task, exhibited good test-retest reliability in measures of learning and performance. However, the learning measures did not correlate between the two tasks, arguing against a shared process for implicit motor learning. Copyright © 2017 the American Physiological Society.

Blended Learning Educational Format for Third-Year Pediatrics Clinical Rotation.

PubMed

Langenau, Erik E; Lee, Robert; Fults, Marci

2017-04-01

Traditional medical education is shifting to incorporate learning technologies and online educational activities with traditional face-to-face clinical instruction to engage students, especially at remote clinical training sites. To describe and evaluate the effectiveness of the blended learning format (combining online and face-to-face instruction) for third-year osteopathic medical students during their pediatric rotation. Third-year medical students who completed the 4-week clerkship in pediatrics during the 2014-2015 academic year were divided into a standard learning group and a blended learning group with online activities (discussion boards, blogs, virtual patient encounters, narrated video presentations, and online training modules). Comprehensive Osteopathic Medical Achievement Test scores and final course grades were compared between the standard learning and blended learning groups. Students in the blended learning group completed a postsurvey regarding their experiences. Of 264 third-year students who completed the 4-week clerkship in pediatrics during the 2014-2015 academic year, 78 (29.5%) participated in the blended learning supplement with online activities. Of 53 students who completed the postsurvey in the blended learning group, 44 (83.0%) agreed or strongly agreed that "The integration of e-learning and face-to-face learning helped me learn pediatrics." Open-ended comments supported this overall satisfaction with the course format; however, 26 of 100 comments reflected a desire to increase the amount of clinical exposure and face-to-face time with patients. No statistical differences were seen between the standard learning (n=186) and blended learning (n=78) groups with regard to Comprehensive Osteopathic Medical Achievement Test scores (P=.321). Compared with the standard learning group, more students in the blended learning group received a final course grade of honors (P=.015). Results of this study support the use of blended learning in a clinical training environment. As more medical educators use blended learning, it is important to investigate the best balance between learning with technology and learning in a face-to-face setting. Online activities may enhance but should never fully replace face-to-face learning with real patients.

Determining the distribution of probes between different subcellular locations through automated unmixing of subcellular patterns.

PubMed

Peng, Tao; Bonamy, Ghislain M C; Glory-Afshar, Estelle; Rines, Daniel R; Chanda, Sumit K; Murphy, Robert F

2010-02-16

Many proteins or other biological macromolecules are localized to more than one subcellular structure. The fraction of a protein in different cellular compartments is often measured by colocalization with organelle-specific fluorescent markers, requiring availability of fluorescent probes for each compartment and acquisition of images for each in conjunction with the macromolecule of interest. Alternatively, tailored algorithms allow finding particular regions in images and quantifying the amount of fluorescence they contain. Unfortunately, this approach requires extensive hand-tuning of algorithms and is often cell type-dependent. Here we describe a machine-learning approach for estimating the amount of fluorescent signal in different subcellular compartments without hand tuning, requiring only the acquisition of separate training images of markers for each compartment. In testing on images of cells stained with mixtures of probes for different organelles, we achieved a 93% correlation between estimated and expected amounts of probes in each compartment. We also demonstrated that the method can be used to quantify drug-dependent protein translocations. The method enables automated and unbiased determination of the distributions of protein across cellular compartments, and will significantly improve imaging-based high-throughput assays and facilitate proteome-scale localization efforts.

Classification of neocortical interneurons using affinity propagation.

PubMed

Santana, Roberto; McGarry, Laura M; Bielza, Concha; Larrañaga, Pedro; Yuste, Rafael

2013-01-01

In spite of over a century of research on cortical circuits, it is still unknown how many classes of cortical neurons exist. In fact, neuronal classification is a difficult problem because it is unclear how to designate a neuronal cell class and what are the best characteristics to define them. Recently, unsupervised classifications using cluster analysis based on morphological, physiological, or molecular characteristics, have provided quantitative and unbiased identification of distinct neuronal subtypes, when applied to selected datasets. However, better and more robust classification methods are needed for increasingly complex and larger datasets. Here, we explored the use of affinity propagation, a recently developed unsupervised classification algorithm imported from machine learning, which gives a representative example or exemplar for each cluster. As a case study, we applied affinity propagation to a test dataset of 337 interneurons belonging to four subtypes, previously identified based on morphological and physiological characteristics. We found that affinity propagation correctly classified most of the neurons in a blind, non-supervised manner. Affinity propagation outperformed Ward's method, a current standard clustering approach, in classifying the neurons into 4 subtypes. Affinity propagation could therefore be used in future studies to validly classify neurons, as a first step to help reverse engineer neural circuits.

Plasma biomarkers of depressive symptoms in older adults.

PubMed

Arnold, S E; Xie, S X; Leung, Y-Y; Wang, L-S; Kling, M A; Han, X; Kim, E J; Wolk, D A; Bennett, D A; Chen-Plotkin, A; Grossman, M; Hu, W; Lee, V M-Y; Mackin, R Scott; Trojanowski, J Q; Wilson, R S; Shaw, L M

2012-01-03

The pathophysiology of negative affect states in older adults is complex, and a host of central nervous system and peripheral systemic mechanisms may play primary or contributing roles. We conducted an unbiased analysis of 146 plasma analytes in a multiplex biochemical biomarker study in relation to number of depressive symptoms endorsed by 566 participants in the Alzheimer's Disease Neuroimaging Initiative (ADNI) at their baseline and 1-year assessments. Analytes that were most highly associated with depressive symptoms included hepatocyte growth factor, insulin polypeptides, pregnancy-associated plasma protein-A and vascular endothelial growth factor. Separate regression models assessed contributions of past history of psychiatric illness, antidepressant or other psychotropic medicine, apolipoprotein E genotype, body mass index, serum glucose and cerebrospinal fluid (CSF) τ and amyloid levels, and none of these values significantly attenuated the main effects of the candidate analyte levels for depressive symptoms score. Ensemble machine learning with Random Forests found good accuracy (~80%) in classifying groups with and without depressive symptoms. These data begin to identify biochemical biomarkers of depressive symptoms in older adults that may be useful in investigations of pathophysiological mechanisms of depression in aging and neurodegenerative dementias and as targets of novel treatment approaches.

Protocol matters: which methylome are you actually studying?

PubMed Central

Robinson, Mark D; Statham, Aaron L; Speed, Terence P; Clark, Susan J

2011-01-01

The field of epigenetics is now capitalizing on the vast number of emerging technologies, largely based on second-generation sequencing, which interrogate DNA methylation status and histone modifications genome-wide. However, getting an exhaustive and unbiased view of a methylome at a reasonable cost is proving to be a significant challenge. In this article, we take a closer look at the impact of the DNA sequence and bias effects introduced to datasets by genome-wide DNA methylation technologies and where possible, explore the bioinformatics tools that deconvolve them. There remains much to be learned about the performance of genome-wide technologies, the data we mine from these assays and how it reflects the actual biology. While there are several methods to interrogate the DNA methylation status genome-wide, our opinion is that no single technique suitably covers the minimum criteria of high coverage and, high resolution at a reasonable cost. In fact, the fraction of the methylome that is studied currently depends entirely on the inherent biases of the protocol employed. There is promise for this to change, as the third generation of sequencing technologies is expected to again ‘revolutionize’ the way that we study genomes and epigenomes. PMID:21566704

A General Method for Predicting Amino Acid Residues Experiencing Hydrogen Exchange

PubMed Central

Wang, Boshen; Perez-Rathke, Alan; Li, Renhao; Liang, Jie

2018-01-01

Information on protein hydrogen exchange can help delineate key regions involved in protein-protein interactions and provides important insight towards determining functional roles of genetic variants and their possible mechanisms in disease processes. Previous studies have shown that the degree of hydrogen exchange is affected by hydrogen bond formations, solvent accessibility, proximity to other residues, and experimental conditions. However, a general predictive method for identifying residues capable of hydrogen exchange transferable to a broad set of proteins is lacking. We have developed a machine learning method based on random forest that can predict whether a residue experiences hydrogen exchange. Using data from the Start2Fold database, which contains information on 13,306 residues (3,790 of which experience hydrogen exchange and 9,516 which do not exchange), our method achieves good performance. Specifically, we achieve an overall out-of-bag (OOB) error, an unbiased estimate of the test set error, of 20.3 percent. Using a randomly selected test data set consisting of 500 residues experiencing hydrogen exchange and 500 which do not, our method achieves an accuracy of 0.79, a recall of 0.74, a precision of 0.82, and an F1 score of 0.78.

Valuing our differences. How to manage a culturally diverse work force.

PubMed

Veninga, R L

1994-12-01

How can we become aware of cultural blind spots that keep us from understanding one another? To adequately prepare for the new work force, healthcare organizations must establish work force diversity goals. Of course, goals by themselves will not empower minority workers. And if goals are perceived as "window dressing," resentment builds. Most organizations claim their hiring practices are not biased. One way to ensure that your hiring practices are unbiased is to ask important questions: Does the ethnic makeup of our work force resemble that of the community? If not, what can be done to strengthen our affirmative action programs? In a multicultural work force, misunderstandings are bound to arise because human behavior is conditioned by cultural factors. One way for an organization to identify problems that are culturally based is for supervisors and subordinates to meet informally to ensure that the organization is maximizing the minority worker's talents. Climate surveys and exit interviews are two other frequently used methods. Cultural diversity training programs can also make a difference in an organization. Some training programs help participants learn how culture influences the way we communicate. Knowledge of the cultural basis of how we interact is one factor in building bridges of understanding.

Sensor Characteristics Reference Guide

DOE Office of Scientific and Technical Information (OSTI.GOV)

Cree, Johnathan V.; Dansu, A.; Fuhr, P.

The Buildings Technologies Office (BTO), within the U.S. Department of Energy (DOE), Office of Energy Efficiency and Renewable Energy (EERE), is initiating a new program in Sensor and Controls. The vision of this program is: • Buildings operating automatically and continuously at peak energy efficiency over their lifetimes and interoperating effectively with the electric power grid. • Buildings that are self-configuring, self-commissioning, self-learning, self-diagnosing, self-healing, and self-transacting to enable continuous peak performance. • Lower overall building operating costs and higher asset valuation. The overarching goal is to capture 30% energy savings by enhanced management of energy consuming assets and systemsmore » through development of cost-effective sensors and controls. One step in achieving this vision is the publication of this Sensor Characteristics Reference Guide. The purpose of the guide is to inform building owners and operators of the current status, capabilities, and limitations of sensor technologies. It is hoped that this guide will aid in the design and procurement process and result in successful implementation of building sensor and control systems. DOE will also use this guide to identify research priorities, develop future specifications for potential market adoption, and provide market clarity through unbiased information« less

Development of Super-Ensemble techniques for ocean analyses: the Mediterranean Sea case

NASA Astrophysics Data System (ADS)

Pistoia, Jenny; Pinardi, Nadia; Oddo, Paolo; Collins, Matthew; Korres, Gerasimos; Drillet, Yann

2017-04-01

Short-term ocean analyses for Sea Surface Temperature SST in the Mediterranean Sea can be improved by a statistical post-processing technique, called super-ensemble. This technique consists in a multi-linear regression algorithm applied to a Multi-Physics Multi-Model Super-Ensemble (MMSE) dataset, a collection of different operational forecasting analyses together with ad-hoc simulations produced by modifying selected numerical model parameterizations. A new linear regression algorithm based on Empirical Orthogonal Function filtering techniques is capable to prevent overfitting problems, even if best performances are achieved when we add correlation to the super-ensemble structure using a simple spatial filter applied after the linear regression. Our outcomes show that super-ensemble performances depend on the selection of an unbiased operator and the length of the learning period, but the quality of the generating MMSE dataset has the largest impact on the MMSE analysis Root Mean Square Error (RMSE) evaluated with respect to observed satellite SST. Lower RMSE analysis estimates result from the following choices: 15 days training period, an overconfident MMSE dataset (a subset with the higher quality ensemble members), and the least square algorithm being filtered a posteriori.

Communication in Collaborative Discovery Learning

ERIC Educational Resources Information Center

Saab, Nadira; van Joolingen, Wouter R.; van Hout-Wolters, Bernadette H. A. M.

2005-01-01

Background: Constructivist approaches to learning focus on learning environments in which students have the opportunity to construct knowledge themselves, and negotiate this knowledge with others. "Discovery learning" and "collaborative learning" are examples of learning contexts that cater for knowledge construction processes. We introduce a…

Understanding the Context of Learning in an Online Social Network for Health Professionals' Informal Learning.

PubMed

Li, Xin; Gray, Kathleen; Verspoor, Karin; Barnett, Stephen

2017-01-01

Online social networks (OSN) enable health professionals to learn informally, for example by sharing medical knowledge, or discussing practice management challenges and clinical issues. Understanding the learning context in OSN is necessary to get a complete picture of the learning process, in order to better support this type of learning. This study proposes critical contextual factors for understanding the learning context in OSN for health professionals, and demonstrates how these contextual factors can be used to analyse the learning context in a designated online learning environment for health professionals.

Recent developments in learning control and system identification for robots and structures

NASA Technical Reports Server (NTRS)

Phan, M.; Juang, J.-N.; Longman, R. W.

1990-01-01

This paper reviews recent results in learning control and learning system identification, with particular emphasis on discrete-time formulation, and their relation to adaptive theory. Related continuous-time results are also discussed. Among the topics presented are proportional, derivative, and integral learning controllers, time-domain formulation of discrete learning algorithms. Newly developed techniques are described including the concept of the repetition domain, and the repetition domain formulation of learning control by linear feedback, model reference learning control, indirect learning control with parameter estimation, as well as related basic concepts, recursive and non-recursive methods for learning identification.

Fuzzy Q-Learning for Generalization of Reinforcement Learning

NASA Technical Reports Server (NTRS)

Berenji, Hamid R.

1996-01-01

Fuzzy Q-Learning, introduced earlier by the author, is an extension of Q-Learning into fuzzy environments. GARIC is a methodology for fuzzy reinforcement learning. In this paper, we introduce GARIC-Q, a new method for doing incremental Dynamic Programming using a society of intelligent agents which are controlled at the top level by Fuzzy Q-Learning and at the local level, each agent learns and operates based on GARIC. GARIC-Q improves the speed and applicability of Fuzzy Q-Learning through generalization of input space by using fuzzy rules and bridges the gap between Q-Learning and rule based intelligent systems.

Detection Learning Style Vark For Out Of School Children (OSC)

NASA Astrophysics Data System (ADS)

Amran, Ali; Desiani, Anita; Hasibuan, MS

2017-04-01

Learning style is different for every learner especially for out of school children or OSC. They are not like formal students, they are learners but they don’t have a teacher as a guide for learning. E-learning is one of the solutions to help OSC to get education. E-learning should have preferred learning styles of learners. Data for identifying the learning style in this study were collected with a VARK questionnaire from 25 OSC in junior high school level from 5 municipalities in Palembang. The validity of the questionnaire was considered on basis of experts’ views and its reliability was calculated by using Cronbach’s alpha coefficients (α=0.68). Overall, 55% preferred to use a single learning style (Uni-modal). Of these, 27,76% preferred Aural, 20,57% preferred Reading Writing, 33,33% preferred Kinaesthetic and 23,13% preferred Visual. 45% of OSC preferred more than one style, 30% chose two-modes (bimodal), and 15% chose three-modes (tri-modal). The Most preferred Learning style of OSC is kinaesthetic learning. Kinaesthetic learning requires body movements, interactivities, and direct contacts with learning materials, these things can be difficult to implement in eLearning, but E-learning should be able to adopt any learning styles which are flexible in terms of time, period, curriculum, pedagogy, location, and language.

Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing

PubMed Central

Lefebvre, Germain; Blakemore, Sarah-Jayne

2017-01-01

Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice. PMID:28800597

An e-learning course in medical immunology: does it improve learning outcome?

PubMed

Boye, Sondre; Moen, Torolf; Vik, Torstein

2012-01-01

E-learning is used by most medical students almost daily and several studies have shown e-learning to improve learning outcome in small-scale interventions. However, few studies have explored the effects of e-learning in immunology. To study the effect of an e-learning package in immunology on learning outcomes in a written integrated examination and to examine student satisfaction with the e-learning package. All second-year students at a Norwegian medical school were offered an animated e-learning package in basic immunology as a supplement to the regular teaching. Each student's log-on-time was recorded and linked with the student's score on multiple choice questions included in an integrated end-of-the-year written examination. Student satisfaction was assessed through a questionnaire. The intermediate-range students (interquartile range) on average scored 3.6% better on the immunology part of the examination per hour they had used the e-learning package (p = 0.0046) and log-on-time explained 17% of the variance in immunology score. The best and the less skilled students' examination outcomes were not affected by the e-learning. The e-learning was well appreciated among the students. Use of an e-learning package in immunology in addition to regular teaching improved learning outcomes for intermediate-range students.

Confirmation bias in human reinforcement learning: Evidence from counterfactual feedback processing.

PubMed

Palminteri, Stefano; Lefebvre, Germain; Kilford, Emma J; Blakemore, Sarah-Jayne

2017-08-01

Previous studies suggest that factual learning, that is, learning from obtained outcomes, is biased, such that participants preferentially take into account positive, as compared to negative, prediction errors. However, whether or not the prediction error valence also affects counterfactual learning, that is, learning from forgone outcomes, is unknown. To address this question, we analysed the performance of two groups of participants on reinforcement learning tasks using a computational model that was adapted to test if prediction error valence influences learning. We carried out two experiments: in the factual learning experiment, participants learned from partial feedback (i.e., the outcome of the chosen option only); in the counterfactual learning experiment, participants learned from complete feedback information (i.e., the outcomes of both the chosen and unchosen option were displayed). In the factual learning experiment, we replicated previous findings of a valence-induced bias, whereby participants learned preferentially from positive, relative to negative, prediction errors. In contrast, for counterfactual learning, we found the opposite valence-induced bias: negative prediction errors were preferentially taken into account, relative to positive ones. When considering valence-induced bias in the context of both factual and counterfactual learning, it appears that people tend to preferentially take into account information that confirms their current choice.

A new vision for distance learning and continuing medical education.

PubMed

Harden, Ronald M

2005-01-01

Increasing demands on continuing medical education (CME) are taking place at a time of significant developments in educational thinking and new learning technologies. Such developments allow today's CME providers to better meet the CRISIS criteria for effective continuing education: convenience, relevance, individualization, self-assessment, independent learning, and a systematic approach. The International Virtual Medical School (IVIMEDS) provides a case study that illustrates how rapid growth of the Internet and e-learning can alter undergraduate education and has the potential to alter the nature of CME. Key components are a bank of reusable learning objects, a virtual practice with virtual patients, a learning-outcomes framework, and self-assessment instruments. Learning is facilitated by a curriculum map, guided-learning resources, "ask-the-expert" opportunities, and collaborative or peer-to-peer learning. The educational philosophy is "just-for-you" learning (learning customized to the content, educational strategy, and distribution needs of the individual physician) and "just-in-time" learning (learning resources available to physicians when they are required). Implications of the new learning technologies are profound. E-learning provides a bridge between the cutting edge of education and training and outdated procedures embedded in institutions and professional organizations. There are important implications, too, for globalization in medical education, for multiprofessional education, and for the continuum of education from undergraduate to postgraduate and continuing education.

Effects of dorsal hippocampus catecholamine depletion on paired-associates learning and place learning in rats.

PubMed

Roschlau, Corinna; Hauber, Wolfgang

2017-04-14

Growing evidence suggests that the catecholamine (CA) neurotransmitters dopamine and noradrenaline support hippocampus-mediated learning and memory. However, little is known to date about which forms of hippocampus-mediated spatial learning are modulated by CA signaling in the hippocampus. Therefore, in the current study we examined the effects of 6-hydroxydopamine-induced CA depletion in the dorsal hippocampus on two prominent forms of hippocampus-based spatial learning, that is learning of object-location associations (paired-associates learning) as well as learning and choosing actions based on a representation of the context (place learning). Results show that rats with CA depletion of the dorsal hippocampus were able to learn object-location associations in an automated touch screen paired-associates learning (PAL) task. One possibility to explain this negative result is that object-location learning as tested in the touchscreen PAL task seems to require relatively little hippocampal processing. Results further show that in rats with CA depletion of the dorsal hippocampus the use of a response strategy was facilitated in a T-maze spatial learning task. We suspect that impaired hippocampus CA signaling may attenuate hippocampus-based place learning and favor dorsolateral striatum-based response learning. Copyright © 2017 Elsevier B.V. All rights reserved.

Undergraduate students' earth science learning: relationships among conceptions, approaches, and learning self-efficacy in Taiwan

NASA Astrophysics Data System (ADS)

Shen, Kuan-Ming; Lee, Min-Hsien; Tsai, Chin-Chung; Chang, Chun-Yen

2016-06-01

In the area of science education research, studies have attempted to investigate conceptions of learning, approaches to learning, and self-efficacy, mainly focusing on science in general or on specific subjects such as biology, physics, and chemistry. However, few empirical studies have probed students' earth science learning. This study aimed to explore the relationships among undergraduates' conceptions of, approaches to, and self-efficacy for learning earth science by adopting the structural equation modeling technique. A total of 268 Taiwanese undergraduates (144 females) participated in this study. Three instruments were modified to assess the students' conceptions of, approaches to, and self-efficacy for learning earth science. The results indicated that students' conceptions of learning made a significant contribution to their approaches to learning, which were consequently correlated with their learning self-efficacy. More specifically, students with stronger agreement that learning earth science involves applying the knowledge and skills learned to unknown problems were prone to possess higher confidence in learning earth science. Moreover, students viewing earth science learning as understanding earth science knowledge were more likely to adopt meaningful strategies to learn earth science, and hence expressed a higher sense of self-efficacy. Based on the results, practical implications and suggestions for future research are discussed.

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

NASA Astrophysics Data System (ADS)

Apipah, S.; Kartono; Isnarto

2018-03-01

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

A model of blended learning in a preclinical course in prosthetic dentistry.

PubMed

Reissmann, Daniel R; Sierwald, Ira; Berger, Florian; Heydecke, Guido

2015-02-01

The aim of this study was to evaluate the use of blending learning that added online tools to traditional learning methods in a preclinical course in prosthetic dentistry at one dental school in Germany. The e-learning modules were comprised of three main components: fundamental principles, additional information, and learning objective tests. Video recordings of practical demonstrations were prepared and cut into sequences meant to achieve single learning goals. The films were accompanied by background information and, after digital processing, were made available online. Additionally, learning objective tests and learning contents were integrated. Evaluations of 71 of 89 students (response rate: 80%) in the course with the integrated e-learning content were available for the study. Compared with evaluation results of the previous years, a substantial and statistically significant increase in satisfaction with learning content (from 30% and 34% to 86%, p<0.001) and learning effect (from 65% and 63% to 83%, p<0.05) was observed. Satisfaction ratings stayed on a high level in three subsequent courses with the modules. Qualitative evaluation revealed mostly positive responses, with not a single negative comment regarding the blended learning concept. The results showed that the e-learning tool was appreciated by the students and suggest that learning objective tests can be successfully implemented in blended learning.

Creativity of Biology Students in Online Learning: Case Study of Universitas Terbuka, Indonesia

NASA Astrophysics Data System (ADS)

Diki, Diki

This is a study about the effect of students' attitudes of creativity toward their learning achievement and persistence in an online learning program. The study also investigated if there was an effect of indirect effect of attitudes of creativity toward learning achievement and persistence through learning strategies. There are three learning strategies, which are deep-learning, strategic-learning, and surface-learning. The participants were students of the department of biology and the department of biology teacher training in Universitas Terbuka (UT -- Indonesia Open University), a distance learning university in Indonesia. The researcher sent the questionnaire through email to students who lived throughout Indonesia. There were 102 students participated in the survey. The instruments were rCAB test for value and attitudes toward creativity (Runco, 2012) and approaches and Study Skills Inventory for Students (ASSIST) test (Speth, 2013). There were four research questions (RQ) in this study. The first was if there was a relationship between attitudes of creativity and persistence. The researcher used independent samples t test technique for RQ 1. The second was if there is a relationship between attitudes of creativity and learning outcome. The researcher used multiple regressions for RQ2. The third was if there was an indirect relationship between attitudes of creativity and persistence through learning strategy. The fourth question was if there is an indirect relationship between attitudes of creativity and learning outcome through learning strategy. The researcher used multiple regression for RQ3 and path analysis for RQ 4. Controlling variables were age, income, departments, gender, high school GPA, and daily online activities. The result showed that fun, and being unconventional negatively predicted learning outcomes while high school GPA positively predicted learning outcome. Age and high school GPA negatively predicted persistence while being unconventional positively predicted persistence. Two variables of deep-learning strategy predicted learning outcome. There were indirect relationships between attitudes of creativity and learning outcomes through deep-learning strategy.

Learning Situations in Nursing Education: A Concept Analysis.

PubMed

Shahsavari, Hooman; Zare, Zahra; Parsa-Yekta, Zohreh; Griffiths, Pauline; Vaismoradi, Mojtaba

2018-02-01

The nursing student requires opportunities to learn within authentic contexts so as to enable safe and competent practice. One strategy to facilitate such learning is the creation of learning situations. A lack of studies on the learning situation in nursing and other health care fields has resulted in insufficient knowledge of the characteristics of the learning situation, its antecedents, and consequences. Nurse educators need to have comprehensive and practical knowledge of the definition and characteristics of the learning situation so as to enable their students to achieve enhanced learning outcomes. The aim of this study was to clarify the concept of the learning situation as it relates to the education of nurses and improve understanding of its characteristics, antecedents, and consequences. The Bonis method of concept analysis, as derived from the Rodgers' evolutionary method, provided the framework for analysis. Data collection and analysis were undertaken in two phases: "interdisciplinary" and "intra-disciplinary." The data source was a search of the literature, encompassing nursing and allied health care professions, published from 1975 to 2016. No agreement on the conceptual phenomenon was discovered in the international literature. The concept of a learning situation was used generally in two ways and thus classified into the themes of: "formal/informal learning situation" and "biologic/nonbiologic learning situation." Antecedents to the creation of a learning situation included personal and environmental factors. The characteristics of a learning situation were described in terms of being complex, dynamic, and offering potential and effective learning opportunities. Consequences of the learning situation included enhancement of the students' learning, professionalization, and socialization into the professional role. The nurse educator, when considering the application of the concept of a learning situation in their educational planning, must acknowledge that the application of this concept will include the student's clinical learning experiences. More studies are required to determine factors influencing the creation of a successful learning situation from the perspectives of nurse educators and nursing students, clinical nurses and patients.

Using appreciative inquiry to help students identify strategies to overcome handicaps of their learning styles.

PubMed

Kumar, Latha Rajendra; Chacko, Thomas Vengail

2012-01-01

In India, as in some other neighboring Asian countries, students and teachers are generally unaware of the differences in the learning styles among learners, which can handicap students with learning styles alien to the common teaching/learning modality within the institution. This study aims to find out whether making students aware of their learning styles and then using the Appreciative Inquiry approach to help them discover learning strategies that worked for them and others with similar learning styles within the institution made them perceive that this experience improved their learning and performance in exams. The visual, auditory, read-write, and kinesthetic (VARK) inventory of learning styles questionnaire was administered to all 100 first-year medical students of the Father Muller's Medical College in Mangalore India to make them aware of their individual learning styles. An Appreciate Inquiry intervention was administered to 62 student volunteers who were counseled about the different learning styles and their adaptive strategies. Pre and post intervention change in student's perception about usefulness of knowing learning styles on their learning, learning behavior, and performance in examinations was collected from the students using a prevalidated questionnaire. Post intervention mean scores showed a significant change (P < 0.0001) in student's self-perceptions about usefulness of knowing one's learning style and discovering strategies that worked within the institutional environment. There was agreement among students that the intervention helped them become more confident in learning (84%), facilitating learning in general (100%), and in understanding concepts (100%). However, only 29% of the students agreed that the intervention has brought about their capability improvement in application of learning and 31% felt it improved their performance in exams. Appreciate Inquiry was perceived as useful in helping students discover learning strategies that work for different individual learning styles and sharing them within the group helped students choose strategies to help overcome the handicap presented by the school's teaching methods.

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction

PubMed Central

de Greeff, Joachim; Belpaeme, Tony

2015-01-01

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children’s social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a “mental model” of the robot, tailoring the tutoring to the robot’s performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot’s bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance. PMID:26422143

Why Robots Should Be Social: Enhancing Machine Learning through Social Human-Robot Interaction.

PubMed

de Greeff, Joachim; Belpaeme, Tony

2015-01-01

Social learning is a powerful method for cultural propagation of knowledge and skills relying on a complex interplay of learning strategies, social ecology and the human propensity for both learning and tutoring. Social learning has the potential to be an equally potent learning strategy for artificial systems and robots in specific. However, given the complexity and unstructured nature of social learning, implementing social machine learning proves to be a challenging problem. We study one particular aspect of social machine learning: that of offering social cues during the learning interaction. Specifically, we study whether people are sensitive to social cues offered by a learning robot, in a similar way to children's social bids for tutoring. We use a child-like social robot and a task in which the robot has to learn the meaning of words. For this a simple turn-based interaction is used, based on language games. Two conditions are tested: one in which the robot uses social means to invite a human teacher to provide information based on what the robot requires to fill gaps in its knowledge (i.e. expression of a learning preference); the other in which the robot does not provide social cues to communicate a learning preference. We observe that conveying a learning preference through the use of social cues results in better and faster learning by the robot. People also seem to form a "mental model" of the robot, tailoring the tutoring to the robot's performance as opposed to using simply random teaching. In addition, the social learning shows a clear gender effect with female participants being responsive to the robot's bids, while male teachers appear to be less receptive. This work shows how additional social cues in social machine learning can result in people offering better quality learning input to artificial systems, resulting in improved learning performance.

Theories of Learning for the Workplace: Building Blocks for Training and Professional Development Programs. Routledge Psychology in Education

ERIC Educational Resources Information Center

Dochy, Filip; Gijbels, David; Segers, Mien; Van den Bossche, Piet

2011-01-01

Workplace and professional learning, lifelong learning, adult learning, learning in different contexts have become of more and more interest and now dominate all aspects of 21st century life. Learning is no longer about "storing and recall" but "development and flow". "Theories of Learning in the Workplace" offers fascinating overviews into some…

Learning Materials Recommendation Using Good Learners' Ratings and Content-Based Filtering

ERIC Educational Resources Information Center

Ghauth, Khairil Imran; Abdullah, Nor Aniza

2010-01-01

The enormity of the amount of learning materials in e-learning has led to the difficulty of locating suitable learning materials for a particular learning topic, creating the need for recommendation tools within a learning context. In this paper, we aim to address this need by proposing a novel e-learning recommender system framework that is based…

The Planning Illusion: Does Active Planning of a Learning Route Support Learning as Well as Learners Think It Does?

ERIC Educational Resources Information Center

Bonestroo, Wilco J.; de Jong, Ton

2012-01-01

Is actively planning one's learning route through a learning domain beneficial for learning? Moreover, can learners accurately judge the extent to which planning has been beneficial for them? This study examined the effects of active planning on learning. Participants received a tool in which they created a learning route themselves before…

Effects of Learning Styles and Interest on Concentration and Achievement of Students in Mobile Learning

ERIC Educational Resources Information Center

Li, Xiaojie; Yang, Xianmin

2016-01-01

Learning concentration deserves in-depth investigation in the field of mobile learning. Therefore, this study examined the interaction effects of learning styles and interest on the learning concentration and academic achievement of students who were asked to learn conceptual knowledge via their mobile phones in a classroom setting. A total of 92…

The Lifelong Learning Iceberg of Information Systems Academics--A Study of On-Going Formal and Informal Learning by Academics

ERIC Educational Resources Information Center

Davey, Bill; Tatnall, Arthur

2007-01-01

This article describes a study that examined the lifelong learning of information systems academics in relation to their normal work. It begins by considering the concept of lifelong learning, its relationship to real-life learning and that lifelong learning should encompass the whole spectrum of formal, non-formal and informal learning. Most…

Creative and Playful Learning: Learning through Game Co-Creation and Games in a Playful Learning Environment

ERIC Educational Resources Information Center

Kangas, Marjaana

2010-01-01

This paper reports on a pilot study in which children aged 7-12 (N = 68) had an opportunity to study in a novel formal and informal learning setting. The learning activities were extended from the classroom to the playful learning environment (PLE), an innovative playground enriched by technological tools. Curriculum-based learning was intertwined…

Ensuring the Continuum of Learning: The Role of Assessment for Lifelong Learning

ERIC Educational Resources Information Center

Su, Yahui

2015-01-01

This article explores how assessment plays a role in helping learners to learn on a continuous, sustainable basis. It begins by exploring the paradigm of lifelong learning, which implies a shift in the way we think about learning and knowledge. Based on knowledge formation rooted in a flux of learning, lifelong learning assessment is not so much…

Assessing the Impact of Learning Environments on Students' Approaches to Learning: Comparing Conventional and Action Learning Designs

ERIC Educational Resources Information Center

Wilson, Keithia; Fowler, Jane

2005-01-01

This study investigated whether students' approaches to learning were influenced by the design of university courses. Pre- and post-evaluations of the approaches to learning of the same group of students concurrently enrolled in a conventional course (lectures and tutorials) and an action learning-based course (project work, learning groups) were…

Does Learning a Complex Task Have To Be Complex?: A Study in Learning Decomposition.

ERIC Educational Resources Information Center

Lee, Frank J.; Anderson, John R.

2001-01-01

Decomposed the learning in the Kanfer-Ackerman Air-Traffic Controller Task (P. Ackerman, 1988) down to learning at the keyboard level. Reanalyzed the Ackerman data to show that learning in this complex task reflects learning at the keystroke level. Conducted an eye-tracking experiment with 10 adults that showed that learning at the key stroke…

An Object Oriented Approach to Improve the Precision of Learning Object Retrieval in a Self Learning Environment

ERIC Educational Resources Information Center

Raghuveer, V. R.; Tripathy, B. K.

2012-01-01

With the advancements in the WWW and ICT, the e-learning domain has developed very fast. Even many educational institutions these days have shifted their focus towards the e-learning and mobile learning environments. However, from the quality of learning point of view, which is measured in terms of "active learning" taking place, the…

An Adaptive E-Learning System Based on Students' Learning Styles: An Empirical Study

ERIC Educational Resources Information Center

Drissi, Samia; Amirat, Abdelkrim

2016-01-01

Personalized e-learning implementation is recognized as one of the most interesting research areas in the distance web-based education. Since the learning style of each learner is different one must fit e-learning with the different needs of learners. This paper presents an approach to integrate learning styles into adaptive e-learning hypermedia.…

Effectiveness of Personalised Learning Paths on Students Learning Experiences in an e-Learning Environment

ERIC Educational Resources Information Center

Santally, Mohammad Issack; Senteni, Alain

2013-01-01

Personalisation of e-learning environments is an interesting research area in which the learning experience of learners is generally believed to be improved when his or her personal learning preferences are taken into account. One such learning preference is the V-A-K instrument that classifies learners as visual, auditory or kinaesthetic. In this…

Towards High-Quality Reflective Learning amongst Law Undergraduate Students: Analysing Students' Reflective Journals during a Problem-Based Learning Course

ERIC Educational Resources Information Center

Rué, Joan; Font, Antoni; Cebrián, Gisela

2013-01-01

There is wide agreement that problem-based learning is a key strategy to promote individual abilities for "learning how to learn". This paper presents the main contributions that reflective journals and the problem-based learning approach can make to foster professional knowledge and quality learning in higher education. Thirty-six…

Problem-based Learning Behavior: The Impact of Differences in Problem-Based Learning Style and Activity on Students' Achievement.

ERIC Educational Resources Information Center

van Til, Cita T.; And Others

Problem-based learning (PBL) as a new instructional method is becoming increasingly popular. PBL is hypothesized to have a number of advantages for learning because it applies insights from cognitive learning theory and it fosters a lifelong learning strategy. As in all learning programs there are individual differences between students. This…

A Study on Mobile Learning as a Learning Style in Modern Research Practice

ERIC Educational Resources Information Center

Joan, D. R. Robert

2013-01-01

Mobile learning is a kind of learning that takes place via a portable handheld electronic device. It also refers to learning via other kinds of mobile devices such as tablet computers, net-books and digital readers. The objective of mobile learning is to provide the learner the ability to assimilate learning anywhere and at anytime. Mobile devices…

Development of Competency-Based Web Learning Material and Effect Evaluation of Self-Directed Learning Aptitudes on Learning Achievements

ERIC Educational Resources Information Center

Chang, Chi-Cheng

2006-01-01

This study aims to develop and evaluate competency-based web learning material (CBWLM) for the college practicum Microprocessor Laboratory. After using the CBWLM for 8 weeks, this study investigates CBWL's learning effects and self-directed learning aptitudes (SDLAs) as well as exploring the influence of SDLA on learning effects based on the…

A Descriptive Review of Mainline E-Learning Projects in the European Union: E-Learning Action Plan and E-Learning Program

ERIC Educational Resources Information Center

Uzunboylu, Huseyin

2006-01-01

This study's purpose was to survey the literature on European Union (EU) e-learning strategies specifically related to two mainline e-learning projects: the learning Action Plan and the E-Learning Program. Results of the evaluation and interpretation of the literature show that the European Commission has positively impacted European Union…

Comparing Problem-Based Learning Students to Students in a Lecture-Based Curriculum: Learning Strategies and the Relation with Self-Study Time

ERIC Educational Resources Information Center

Wijnen, Marit; Loyens, Sofie M. M.; Smeets, Guus; Kroeze, Maarten; van der Molen, Henk

2017-01-01

In educational theory, deep processing (i.e., connecting different study topics together) and self-regulation (i.e., taking control over one's own learning process) are considered effective learning strategies. These learning strategies can be influenced by the learning environment. Problem-based learning (PBL), a student-centered educational…

Risks and Opportunities in the Age of Information Technology: E-Learning, Commercialization, and Measures of Success.

ERIC Educational Resources Information Center

Rhodes, Elizabeth Moore

This position paper describes a theoretical framework for learning that encompasses new conceptions of learning, namely learning as social practice, new views of the learner as self-directed, and paradigm shifts in learning as it is mandated in new social contexts. Social learning theory, especially that of situated learning, provides a new…

Putting the Learning in Service Learning: From Soup Kitchen Models to the Black Metropolis Model

ERIC Educational Resources Information Center

Manley, Theodoric, Jr.; Buffa, Avery S.; Dube, Caleb; Reed, Lauren

2006-01-01

Results of the Black Metropolis Model (BMM) of service learning are analyzed and illustrated in this article to explain how to "put the learning in service learning." There are many soup kitchens or nontransforming models of service learning where students are asked to serve needy populations but internalize and learn little about the…

Teaching & Learning for International Students in a "Learning Community": Creating, Sharing and Building Knowledge

ERIC Educational Resources Information Center

Kemp, Linzi

2010-01-01

This article considers the culture of learning communities for effective teaching. A learning community is defined here as an environment where learners are brought together to share information, to learn from each other, and to create new knowledge. The individual student develops her/his own learning by building on learning from others. In a…

"Mastery Learning" Como Metodo Psicoeducativo para Ninos con Problemas Especificos de Aprendizaje. ("Mastery Learning" as a Psychoeducational Method for Children with Specific Learning Problems.)

ERIC Educational Resources Information Center

Coya, Liliam de Barbosa; Perez-Coffie, Jorge

1982-01-01

"Mastery Learning" was compared with the "conventional" method of teaching reading skills to Puerto Rican children with specific learning disabilities. The "Mastery Learning" group showed significant gains in the cognitive and affective domains. Results suggested Mastery Learning is a more effective method of teaching…

Applications of Adaptive Learning Controller to Synthetic Aperture Radar.

DTIC Science & Technology

1985-02-01

FIGURE 37. Location of Two Sub- Phase Histories to be Utilized in Estimating Misfocus Coefficients A and C . . . A8 FIGURES 38.-94. ALC Learning Curves ...FIGURES (Concl uded) FIGURE 23. ALC Learning Curve .... .................. ... 45 .- " FIGURE 24. ALC Learning Curve ......... ................. 47 FIGURE...25. ALC Learning Curve .... .................. ... 48 FIGURE 26. ALC Learning Curve ....... .... ... .... 50 FIGURE 27. ALC Learning Curve

A Comparative Analysis of Student Engagement, Learning, and Satisfaction in Lecture Hall and Online Learning Settings

ERIC Educational Resources Information Center

Rabe-Hemp, Cara; Woollen, Susan; Humiston, Gail Sears

2009-01-01

The current study involves a comparison of student levels of engagement, ability to learn autonomously, and interaction with peers and faculty in two different learning settings: a large lecture hall and online. Results suggest that learning mechanism drives the styles of learning and teaching practiced in traditional and online learning settings.…

Model of Learning Using iLearning on Independent Study Classes at University

ERIC Educational Resources Information Center

Sudaryono; Padeli; Febriyanto, Erick

2017-01-01

Raharja College is one of the universities who apply a learning method that is quite different which does not only rely on the conventional learning system in which Teaching and Learning Activity is done by students and lecturers are required to come face to face directly, but also applying e-learning method learning or better known as iLearning…

Exploring the Effects of Active Learning on High School Students' Outcomes and Teachers' Perceptions of Biotechnology and Genetics Instruction

ERIC Educational Resources Information Center

Mueller, Ashley L.; Knobloch, Neil A.; Orvis, Kathryn S.

2015-01-01

Active learning can engage high school students to learn science, yet there is limited understanding if active learning can help students learn challenging science concepts such as genetics and biotechnology. This quasi-experimental study explored the effects of active learning compared to passive learning regarding high school students'…

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

ERIC Educational Resources Information Center

Yang, Kai-Hsiang

2017-01-01

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

The Effectiveness of Inquiry Learning Method to Enhance Students' Learning Outcome: A Theoritical and Empirical Review

ERIC Educational Resources Information Center

Andrini, Vera Septi

2016-01-01

The necessities of the 21st century requires education to continue creating the young generation to have life skills. Life skills are trained through the learning process and identified through the learning outcomes of students. One of the affecting factors for low learning outcomes is learning models. The learning model is a design study that…

Blended Learning Based on Schoology: Effort of Improvement Learning Outcome and Practicum Chance in Vocational High School

ERIC Educational Resources Information Center

Irawan, Vincentius Tjandra; Sutadji, Eddy; Widiyanti

2017-01-01

The aims of this study were to determine: (1) the differences in learning outcome between Blended Learning based on Schoology and Problem-Based Learning, (2) the differences in learning outcome between students with prior knowledge of high, medium, and low, and (3) the interaction between Blended Learning based on Schoology and prior knowledge to…

Task Characteristics and Learning Potentials--Empirical Results of Three Diary Studies on Workplace Learning

ERIC Educational Resources Information Center

Rausch, Andreas

2013-01-01

Most learning in the workplace occurs while pursuing working rather than learning goals. The studies at hand aimed to identify task characteristics that foster learning in the workplace. Task characteristics are supposed to exert a major effect on the learning potential. However, the fact that learning is more often than not a rather unconscious…

Supporting Orthographic Learning at the Beginning Stage of Learning to Read Chinese as a Second Language

ERIC Educational Resources Information Center

Chang, Li-Yun; Xu, Yi; Perfetti, Charles A.; Zhang, Juan; Chen, Hsueh-Chih

2014-01-01

Learning to read a second language (L2) is especially challenging when a target L2 requires learning new graphic forms. Learning Chinese, which consists of thousands of characters composed of hundreds of basic writing units, presents such a challenge of orthographic learning for adult English speakers at the beginning stages of learning. In this…

Towards Adaptive Open Learning Environments: Evaluating the Precision of Identifying Learning Styles by Tracking Learners' Behaviours

ERIC Educational Resources Information Center

Fasihuddin, Heba; Skinner, Geoff; Athauda, Rukshan

2017-01-01

Open learning represents a new form of online learning where courses are provided freely online for large numbers of learners. MOOCs are examples of this form of learning. The authors see an opportunity for personalising open learning environments by adapting to learners' learning styles and providing adaptive support to meet individual learner…

From Learning Cultures to Educational Cultures: Values and Judgements in Educational Research and Educational Improvement

ERIC Educational Resources Information Center

Biesta, Gert

2011-01-01

This article outlines a new approach to the study of learning and the improvement of education. The approach consists of two elements: a theory of learning cultures and a cultural theory of learning. Learning cultures are different from learning contexts or learning environments in that they are to be understood as the social practices through…

The profile of students’ self-regulated learning at vocational high school

NASA Astrophysics Data System (ADS)

Ciptaningtyas, Asih; Pratiwi, Hasih; Mardiyana

2018-05-01

Self-regulated learning is a power in the individual through the individualization process. Self-regulated learning will occur when the student is active to control himself from everything done, plan something, evaluate, and deeply reflect what he has experienced. This study aims to determine the profile of students’ self-regulated learning in SMK Giripuro, Sumpiuh, Banyumas Regency. This study is a qualitative research with questionnaire and interview methods. This study used triangulation method technique to obtain from the questionnaire and interview to get valid data. The subjects in this study are three 10th Grade students who have different self-regulated learning in SMK Giripuro Sumpiuh. The results showed that the high self-regulated learning student has characteristics: 1) independent of others, 2) believe in their abilities, 3) awareness in learning, and 4) be able to reflect on their learning. Medium self-regulated learning student has characteristics: 1) independent of others, 2) believe in their abilities, 3) awareness in learning, and 4) do not reflect on learning. Low self-regulated learning student has characteristics: 1) dependent on others, 2) do not believe in their abilities, 3) lack awareness of learning, and 4) do not reflect on learning.

What’s about Peer Tutoring Learning Model?

NASA Astrophysics Data System (ADS)

Muthma'innah, M.

2017-09-01

Mathematics learning outcomes in Indonesia in general is still far from satisfactory. One effort that could be expected to solve the problem is to apply the model of peer tutoring learning in mathematics. This study aims to determine whether the results of students’ mathematics learning can be enhanced through peer tutoring learning models. This type of research is the study of literature, so that the method used is to summarize and analyze the results of relevant research that has been done. Peer tutoring learning model is a model of learning in which students learn in small groups that are grouped with different ability levels, all group members to work together and help each other to understand the material. By paying attention to the syntax of the learning, then learning will be invaluable peer tutoring for students who served as teachers and students are taught. In mathematics, the implementation of this learning model can make students understand each other mathematical concepts and help students in solving mathematical problems that are poorly understood, due to the interaction between students in learning. Then it will be able to improve learning outcomes in mathematics. The impact, it can be applied in mathematics learning.

How does tele-learning compare with other forms of education delivery? A systematic review of tele-learning educational outcomes for health professionals.

PubMed

Tomlinson, Jo; Shaw, Tim; Munro, Ana; Johnson, Ros; Madden, D Lynne; Phillips, Rosemary; McGregor, Deborah

2013-11-01

Telecommuniciation technologies, including audio and videoconferencing facilities, afford geographically dispersed health professionals the opportunity to connect and collaborate with others. Recognised for enabling tele-consultations and tele-collaborations between teams of health care professionals and their patients, these technologies are also well suited to the delivery of distance learning programs, known as tele-learning. To determine whether tele-learning delivery methods achieve equivalent learning outcomes when compared with traditional face-to-face education delivery methods. A systematic literature review was commissioned by the NSW Ministry of Health to identify results relevant to programs applying tele-learning delivery methods in the provision of education to health professionals. The review found few studies that rigorously compared tele-learning with traditional formats. There was some evidence, however, to support the premise that tele-learning models achieve comparable learning outcomes and that participants are generally satisfied with and accepting of this delivery method. The review illustrated that tele-learning technologies not only enable distance learning opportunities, but achieve comparable learning outcomes to traditional face-to-face models. More rigorous evidence is required to strengthen these findings and should be the focus of future tele-learning research.

The Effectiveness of Guided Inquiry Learning for Comparison Topics

NASA Astrophysics Data System (ADS)

Asnidar; Khabibah, S.; Sulaiman, R.

2018-01-01

This research aims at producing a good quality learning device using guided inquiry for comparison topics and describing the effectiveness of guided inquiry learning for comparison topics. This research is a developmental research using 4-D model. The result is learning device consisting of lesson plan, student’s worksheet, and achievement test. The subjects of the study were class VII students, each of which has 46 students. Based on the result in the experimental class, the learning device using guided inquiry for comparison topics has good quality. The learning device has met the valid, practical, and effective aspects. The result, especially in the implementation class, showed that the learning process with guided inquiry has fulfilled the effectiveness indicators. The ability of the teacher to manage the learning process has fulfilled the criteria good. In addition, the students’ activity has fulfilled the criteria of, at least, good. Moreover, the students’ responses to the learning device and the learning activities were positive, and the students were able to complete the classical learning. Based on the result of this research, it is expected that the learning device resulted can be used as an alternative learning device for teachers in implementing mathematic learning for comparison topics.

Social learning and evolution: the cultural intelligence hypothesis

PubMed Central

van Schaik, Carel P.; Burkart, Judith M.

2011-01-01

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer. PMID:21357223

Social learning and evolution: the cultural intelligence hypothesis.

PubMed

van Schaik, Carel P; Burkart, Judith M

2011-04-12

If social learning is more efficient than independent individual exploration, animals should learn vital cultural skills exclusively, and routine skills faster, through social learning, provided they actually use social learning preferentially. Animals with opportunities for social learning indeed do so. Moreover, more frequent opportunities for social learning should boost an individual's repertoire of learned skills. This prediction is confirmed by comparisons among wild great ape populations and by social deprivation and enculturation experiments. These findings shaped the cultural intelligence hypothesis, which complements the traditional benefit hypotheses for the evolution of intelligence by specifying the conditions in which these benefits can be reaped. The evolutionary version of the hypothesis argues that species with frequent opportunities for social learning should more readily respond to selection for a greater number of learned skills. Because improved social learning also improves asocial learning, the hypothesis predicts a positive interspecific correlation between social-learning performance and individual learning ability. Variation among primates supports this prediction. The hypothesis also predicts that more heavily cultural species should be more intelligent. Preliminary tests involving birds and mammals support this prediction too. The cultural intelligence hypothesis can also account for the unusual cognitive abilities of humans, as well as our unique mechanisms of skill transfer.

Development of a model for whole brain learning of physiology.

PubMed

Eagleton, Saramarie; Muller, Anton

2011-12-01

In this report, a model was developed for whole brain learning based on Curry's onion model. Curry described the effect of personality traits as the inner layer of learning, information-processing styles as the middle layer of learning, and environmental and instructional preferences as the outer layer of learning. The model that was developed elaborates on these layers by relating the personality traits central to learning to the different quadrants of brain preference, as described by Neethling's brain profile, as the inner layer of the onion. This layer is encircled by the learning styles that describe different information-processing preferences for each brain quadrant. For the middle layer, the different stages of Kolb's learning cycle are classified into the four brain quadrants associated with the different brain processing strategies within the information processing circle. Each of the stages of Kolb's learning cycle is also associated with a specific cognitive learning strategy. These two inner circles are enclosed by the circle representing the role of the environment and instruction on learning. It relates environmental factors that affect learning and distinguishes between face-to-face and technology-assisted learning. This model informs on the design of instructional interventions for physiology to encourage whole brain learning.

Learning strategies during clerkships and their effects on clinical performance.

PubMed

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.

Native-language N400 and P600 predict dissociable language-learning abilities in adults

PubMed Central

Qi, Zhenghan; Beach, Sara D.; Finn, Amy S.; Minas, Jennifer; Goetz, Calvin; Chan, Brian; Gabrieli, John D.E.

2018-01-01

Language learning aptitude during adulthood varies markedly across individuals. An individual’s native-language ability has been associated with success in learning a new language as an adult. However, little is known about how native-language processing affects learning success and what neural markers of native-language processing, if any, are related to success in learning. We therefore related variation in electrophysiology during native-language processing to success in learning a novel artificial language. Event-related potentials (ERPs) were recorded while native English speakers judged the acceptability of English sentences prior to learning an artificial language. There was a trend towards a double dissociation between native-language ERPs and their relationships to novel syntax and vocabulary learning. Individuals who exhibited a greater N400 effect when processing English semantics showed better future learning of the artificial language overall. The N400 effect was related to syntax learning via its specific relationship to vocabulary learning. In contrast, the P600 effect size when processing English syntax predicted future syntax learning but not vocabulary learning. These findings show that distinct neural signatures of native-language processing relate to dissociable abilities for learning novel semantic and syntactic information. PMID:27737775

Quantum-Enhanced Machine Learning

NASA Astrophysics Data System (ADS)

Dunjko, Vedran; Taylor, Jacob M.; Briegel, Hans J.

2016-09-01

The emerging field of quantum machine learning has the potential to substantially aid in the problems and scope of artificial intelligence. This is only enhanced by recent successes in the field of classical machine learning. In this work we propose an approach for the systematic treatment of machine learning, from the perspective of quantum information. Our approach is general and covers all three main branches of machine learning: supervised, unsupervised, and reinforcement learning. While quantum improvements in supervised and unsupervised learning have been reported, reinforcement learning has received much less attention. Within our approach, we tackle the problem of quantum enhancements in reinforcement learning as well, and propose a systematic scheme for providing improvements. As an example, we show that quadratic improvements in learning efficiency, and exponential improvements in performance over limited time periods, can be obtained for a broad class of learning problems.