Mapping Learning Outcomes and Assignment Tasks for SPIDER Activities

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Lyn Brodie

2011-05-01

Full Text Available Modern engineering programs have to address rapidly changing technical content and have to enable students to develop transferable skills such as critical evaluation, communication skills and lifelong learning. This paper introduces a combined learning and assessment activity that provides students with opportunities to develop and practice their soft skills, but also extends their theoretical knowledge base. Key tasks included self directed inquiry, oral and written communication as well as peer assessment. To facilitate the SPIDER activities (Select, Prepare and Investigate, Discuss, Evaluate, Reflect, a software tool has been implemented in the learning management system Moodle. Evidence shows increased student engagement and better learning outcomes for both transferable as well as technical skills. The study focuses on generalising the relationship between learning outcomes and assignment tasks as well as activities that drive these tasks. Trail results inform the approach. Staff evaluations and their views of assignments and intended learning outcomes also supported this analysis.

Not all choices are created equal: Task-relevant choices enhance motor learning compared to task-irrelevant choices.

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Carter, Michael J; Ste-Marie, Diane M

2017-12-01

Lewthwaite et al. (2015) reported that the learning benefits of exercising choice (i.e., their self-controlled condition) are not restricted to task-relevant features (e.g., feedback). They found that choosing one's golf ball color (Exp. 1) or choosing which of two tasks to perform at a later time plus which of two artworks to hang (Exp. 2) resulted in better retention than did being denied these same choices (i.e., yoked condition). The researchers concluded that the learning benefits derived from choice, whether irrelevant or relevant to the to-be-learned task, are predominantly motivational because choice is intrinsically rewarding and satisfies basic psychological needs. However, the absence of a group that made task-relevant choices and the lack of psychological measures significantly weakened their conclusions. Here, we investigated how task-relevant and task-irrelevant choices affect motor-skill learning. Participants practiced a spatiotemporal motor task in either a task-relevant group (choice over feedback schedule), a task-irrelevant group (choice over the color of an arm-wrap plus game selection), or a no-choice group. The results showed significantly greater learning in the task-relevant group than in both the task-irrelevant and no-choice groups, who did not differ significantly. Critically, these learning differences were not attributed to differences in perceptions of competence or autonomy, but instead to superior error-estimation abilities. These results challenge the perspective that motivational influences are the root cause of self-controlled learning advantages. Instead, the findings add to the growing evidence highlighting that the informational value gained from task-relevant choices makes a greater relative contribution to these advantages than motivational influences do.

Changes in prefrontal neuronal activity after learning to perform a spatial working memory task.

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Qi, Xue-Lian; Meyer, Travis; Stanford, Terrence R; Constantinidis, Christos

2011-12-01

The prefrontal cortex is considered essential for learning to perform cognitive tasks though little is known about how the representation of stimulus properties is altered by learning. To address this issue, we recorded neuronal activity in monkeys before and after training on a task that required visual working memory. After the subjects learned to perform the task, we observed activation of more prefrontal neurons and increased activity during working memory maintenance. The working memory-related increase in firing rate was due mostly to regular-spiking putative pyramidal neurons. Unexpectedly, the selectivity of neurons for stimulus properties and the ability of neurons to discriminate between stimuli decreased as the information about stimulus properties was apparently present in neural firing prior to training and neuronal selectivity degraded after training in the task. The effect was robust and could not be accounted for by differences in sampling sites, selection of neurons, level of performance, or merely the elapse of time. The results indicate that, in contrast to the effects of perceptual learning, mastery of a cognitive task degrades the apparent stimulus selectivity as neurons represent more abstract information related to the task. This effect is countered by the recruitment of more neurons after training.

Multi-task Vector Field Learning.

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Lin, Binbin; Yang, Sen; Zhang, Chiyuan; Ye, Jieping; He, Xiaofei

2012-01-01

Multi-task learning (MTL) aims to improve generalization performance by learning multiple related tasks simultaneously and identifying the shared information among tasks. Most of existing MTL methods focus on learning linear models under the supervised setting. We propose a novel semi-supervised and nonlinear approach for MTL using vector fields. A vector field is a smooth mapping from the manifold to the tangent spaces which can be viewed as a directional derivative of functions on the manifold. We argue that vector fields provide a natural way to exploit the geometric structure of data as well as the shared differential structure of tasks, both of which are crucial for semi-supervised multi-task learning. In this paper, we develop multi-task vector field learning (MTVFL) which learns the predictor functions and the vector fields simultaneously. MTVFL has the following key properties. (1) The vector fields MTVFL learns are close to the gradient fields of the predictor functions. (2) Within each task, the vector field is required to be as parallel as possible which is expected to span a low dimensional subspace. (3) The vector fields from all tasks share a low dimensional subspace. We formalize our idea in a regularization framework and also provide a convex relaxation method to solve the original non-convex problem. The experimental results on synthetic and real data demonstrate the effectiveness of our proposed approach.

Effects of Mode of Target Task Selection on Learning about Plants in a Mobile Learning Environment: Effortful Manual Selection versus Effortless QR-Code Selection

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Gao, Yuan; Liu, Tzu-Chien; Paas, Fred

2016-01-01

This study compared the effects of effortless selection of target plants using quick respond (QR) code technology to effortful manual search and selection of target plants on learning about plants in a mobile device supported learning environment. In addition, it was investigated whether the effectiveness of the 2 selection methods was…

Presentation-Practice-Production and Task-Based Learning in the Light of Second Language Learning Theories.

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Ritchie, Graeme

2003-01-01

Features of presentation-practice-production (PPP) and task-based learning (TBL) models for language teaching are discussed with reference to language learning theories. Pre-selection of target structures, use of controlled repetition, and explicit grammar instruction in a PPP lesson are given. Suggests TBL approaches afford greater learning…

How attention can create synaptic tags for the learning of working memories in sequential tasks.

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Jaldert O Rombouts

2015-03-01

Full Text Available Intelligence is our ability to learn appropriate responses to new stimuli and situations. Neurons in association cortex are thought to be essential for this ability. During learning these neurons become tuned to relevant features and start to represent them with persistent activity during memory delays. This learning process is not well understood. Here we develop a biologically plausible learning scheme that explains how trial-and-error learning induces neuronal selectivity and working memory representations for task-relevant information. We propose that the response selection stage sends attentional feedback signals to earlier processing levels, forming synaptic tags at those connections responsible for the stimulus-response mapping. Globally released neuromodulators then interact with tagged synapses to determine their plasticity. The resulting learning rule endows neural networks with the capacity to create new working memory representations of task relevant information as persistent activity. It is remarkably generic: it explains how association neurons learn to store task-relevant information for linear as well as non-linear stimulus-response mappings, how they become tuned to category boundaries or analog variables, depending on the task demands, and how they learn to integrate probabilistic evidence for perceptual decisions.

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

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

2013-03-01

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

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

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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

The effect of haptic guidance and visual feedback on learning a complex tennis task.

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Marchal-Crespo, Laura; van Raai, Mark; Rauter, Georg; Wolf, Peter; Riener, Robert

2013-11-01

While haptic guidance can improve ongoing performance of a motor task, several studies have found that it ultimately impairs motor learning. However, some recent studies suggest that the haptic demonstration of optimal timing, rather than movement magnitude, enhances learning in subjects trained with haptic guidance. Timing of an action plays a crucial role in the proper accomplishment of many motor skills, such as hitting a moving object (discrete timing task) or learning a velocity profile (time-critical tracking task). The aim of the present study is to evaluate which feedback conditions-visual or haptic guidance-optimize learning of the discrete and continuous elements of a timing task. The experiment consisted in performing a fast tennis forehand stroke in a virtual environment. A tendon-based parallel robot connected to the end of a racket was used to apply haptic guidance during training. In two different experiments, we evaluated which feedback condition was more adequate for learning: (1) a time-dependent discrete task-learning to start a tennis stroke and (2) a tracking task-learning to follow a velocity profile. The effect that the task difficulty and subject's initial skill level have on the selection of the optimal training condition was further evaluated. Results showed that the training condition that maximizes learning of the discrete time-dependent motor task depends on the subjects' initial skill level. Haptic guidance was especially suitable for less-skilled subjects and in especially difficult discrete tasks, while visual feedback seems to benefit more skilled subjects. Additionally, haptic guidance seemed to promote learning in a time-critical tracking task, while visual feedback tended to deteriorate the performance independently of the task difficulty and subjects' initial skill level. Haptic guidance outperformed visual feedback, although additional studies are needed to further analyze the effect of other types of feedback visualization on

Learning a New Selection Rule in Visual and Frontal Cortex.

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van der Togt, Chris; Stănişor, Liviu; Pooresmaeili, Arezoo; Albantakis, Larissa; Deco, Gustavo; Roelfsema, Pieter R

2016-08-01

How do you make a decision if you do not know the rules of the game? Models of sensory decision-making suggest that choices are slow if evidence is weak, but they may only apply if the subject knows the task rules. Here, we asked how the learning of a new rule influences neuronal activity in the visual (area V1) and frontal cortex (area FEF) of monkeys. We devised a new icon-selection task. On each day, the monkeys saw 2 new icons (small pictures) and learned which one was relevant. We rewarded eye movements to a saccade target connected to the relevant icon with a curve. Neurons in visual and frontal cortex coded the monkey's choice, because the representation of the selected curve was enhanced. Learning delayed the neuronal selection signals and we uncovered the cause of this delay in V1, where learning to select the relevant icon caused an early suppression of surrounding image elements. These results demonstrate that the learning of a new rule causes a transition from fast and random decisions to a more considerate strategy that takes additional time and they reveal the contribution of visual and frontal cortex to the learning process. © The Author 2016. Published by Oxford University Press.

Selective visual attention and motivation: the consequences of value learning in an attentional blink task.

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Raymond, Jane E; O'Brien, Jennifer L

2009-08-01

Learning to associate the probability and value of behavioral outcomes with specific stimuli (value learning) is essential for rational decision making. However, in demanding cognitive conditions, access to learned values might be constrained by limited attentional capacity. We measured recognition of briefly presented faces seen previously in a value-learning task involving monetary wins and losses; the recognition task was performed both with and without constraints on available attention. Regardless of available attention, recognition was substantially enhanced for motivationally salient stimuli (i.e., stimuli highly predictive of outcomes), compared with equally familiar stimuli that had weak or no motivational salience, and this effect was found regardless of valence (win or loss). However, when attention was constrained (because stimuli were presented during an attentional blink, AB), valence determined recognition; win-associated faces showed no AB, but all other faces showed large ABs. Motivational salience acts independently of attention to modulate simple perceptual decisions, but when attention is limited, visual processing is biased in favor of reward-associated stimuli.

Multi-task feature learning by using trace norm regularization

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Jiangmei Zhang

2017-11-01

Full Text Available Multi-task learning can extract the correlation of multiple related machine learning problems to improve performance. This paper considers applying the multi-task learning method to learn a single task. We propose a new learning approach, which employs the mixture of expert model to divide a learning task into several related sub-tasks, and then uses the trace norm regularization to extract common feature representation of these sub-tasks. A nonlinear extension of this approach by using kernel is also provided. Experiments conducted on both simulated and real data sets demonstrate the advantage of the proposed approach.

You see what you have learned. Evidence for an interrelation of associative learning and visual selective attention.

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Feldmann-Wüstefeld, Tobias; Uengoer, Metin; Schubö, Anna

2015-11-01

Besides visual salience and observers' current intention, prior learning experience may influence deployment of visual attention. Associative learning models postulate that observers pay more attention to stimuli previously experienced as reliable predictors of specific outcomes. To investigate the impact of learning experience on deployment of attention, we combined an associative learning task with a visual search task and measured event-related potentials of the EEG as neural markers of attention deployment. In the learning task, participants categorized stimuli varying in color/shape with only one dimension being predictive of category membership. In the search task, participants searched a shape target while disregarding irrelevant color distractors. Behavioral results showed that color distractors impaired performance to a greater degree when color rather than shape was predictive in the learning task. Neurophysiological results show that the amplified distraction was due to differential attention deployment (N2pc). Experiment 2 showed that when color was predictive for learning, color distractors captured more attention in the search task (ND component) and more suppression of color distractor was required (PD component). The present results thus demonstrate that priority in visual attention is biased toward predictive stimuli, which allows learning experience to shape selection. We also show that learning experience can overrule strong top-down control (blocked tasks, Experiment 3) and that learning experience has a longer-term effect on attention deployment (tasks on two successive days, Experiment 4). © 2015 Society for Psychophysiological Research.

Task Demands in OSCEs Influence Learning Strategies.

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Lafleur, Alexandre; Laflamme, Jonathan; Leppink, Jimmie; Côté, Luc

2017-01-01

Models on pre-assessment learning effects confirmed that task demands stand out among the factors assessors can modify in an assessment to influence learning. However, little is known about which tasks in objective structured clinical examinations (OSCEs) improve students' cognitive and metacognitive processes. Research is needed to support OSCE designs that benefit students' metacognitive strategies when they are studying, reinforcing a hypothesis-driven approach. With that intent, hypothesis-driven physical examination (HDPE) assessments ask students to elicit and interpret findings of the physical exam to reach a diagnosis ("Examine this patient with a painful shoulder to reach a diagnosis"). When studying for HDPE, students will dedicate more time to hypothesis-driven discussions and practice than when studying for a part-task OSCE ("Perform the shoulder exam"). It is expected that the whole-task nature of HDPE will lead to a hypothesis-oriented use of the learning resources, a frequent use of adjustment strategies, and persistence with learning. In a mixed-methods study, 40 medical students were randomly paired and filmed while studying together for two hypothetical OSCE stations. Each 25-min study period began with video cues asking to study for either a part-task OSCE or an HDPE. In a crossover design, sequences were randomized for OSCEs and contents (shoulder or spine). Time-on-task for discussions or practice were categorized as "hypothesis-driven" or "sequence of signs and maneuvers." Content analysis of focus group interviews summarized students' perception of learning resources, adjustment strategies, and persistence with learning. When studying for HDPE, students allocate significantly more time for hypothesis-driven discussions and practice. Students use resources contrasting diagnoses and report persistence with learning. When studying for part-task OSCEs, time-on-task is reversed, spent on rehearsing a sequence of signs and maneuvers. OSCEs with

Probabilistic Category Learning in Developmental Dyslexia: Evidence from Feedback and Paired-Associate Weather Prediction Tasks

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Gabay, Yafit; Vakil, Eli; Schiff, Rachel; Holt, Lori L.

2015-01-01

Objective Developmental dyslexia is presumed to arise from specific phonological impairments. However, an emerging theoretical framework suggests that phonological impairments may be symptoms stemming from an underlying dysfunction of procedural learning. Method We tested procedural learning in adults with dyslexia (n=15) and matched-controls (n=15) using two versions of the Weather Prediction Task: Feedback (FB) and Paired-associate (PA). In the FB-based task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of response. In the PA-based learning task, participants viewed the cue and its associated outcome simultaneously without overt response or feedback. In both versions, participants trained across 150 trials. Learning was assessed in a subsequent test without presentation of the outcome, or corrective feedback. Results The Dyslexia group exhibited impaired learning compared with the Control group on both the FB and PA versions of the weather prediction task. Conclusions The results indicate that the ability to learn by feedback is not selectively impaired in dyslexia. Rather it seems that the probabilistic nature of the task, shared by the FB and PA versions of the weather prediction task, hampers learning in those with dyslexia. Results are discussed in light of procedural learning impairments among participants with dyslexia. PMID:25730732

Elementary Students' Learning of Materials Science Practices Through Instruction Based on Engineering Design Tasks

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Wendell, Kristen Bethke; Lee, Hee-Sun

2010-12-01

Materials science, which entails the practices of selecting, testing, and characterizing materials, is an important discipline within the study of matter. This paper examines how third grade students' materials science performance changes over the course of instruction based on an engineering design challenge. We conducted a case study of nine students who participated in engineering design-based science instruction with the goal of constructing a stable, quiet, thermally comfortable model house. The learning outcome of materials science practices was assessed by clinical interviews conducted before and after the instruction, and the learning process was assessed by students' workbooks completed during the instruction. The interviews included two materials selection tasks for designing a sturdy stepstool and an insulated pet habitat. Results indicate that: (1) students significantly improved on both materials selection tasks, (2) their gains were significantly positively associated with the degree of completion of their workbooks, and (3) students who were highly engaged with the workbook's reflective record-keeping tasks showed the greatest improvement on the interviews. These findings suggest the important role workbooks can play in facilitating elementary students' learning of science through authentic activity such as engineering design.

Motivated Learning with Digital Learning Tasks: What about Autonomy and Structure?

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van Loon, Anne-Marieke; Ros, Anje; Martens, Rob

2012-01-01

In the present study, the ways in which digital learning tasks contribute to students' intrinsic motivation and learning outcomes were examined. In particular, this study explored the relative contributions of autonomy support and the provision of structure in digital learning tasks. Participants were 320 fifth- and sixth-grade students from eight…

Task-irrelevant emotion facilitates face discrimination learning.

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Lorenzino, Martina; Caudek, Corrado

2015-03-01

We understand poorly how the ability to discriminate faces from one another is shaped by visual experience. The purpose of the present study is to determine whether face discrimination learning can be facilitated by facial emotions. To answer this question, we used a task-irrelevant perceptual learning paradigm because it closely mimics the learning processes that, in daily life, occur without a conscious intention to learn and without an attentional focus on specific facial features. We measured face discrimination thresholds before and after training. During the training phase (4 days), participants performed a contrast discrimination task on face images. They were not informed that we introduced (task-irrelevant) subtle variations in the face images from trial to trial. For the Identity group, the task-irrelevant features were variations along a morphing continuum of facial identity. For the Emotion group, the task-irrelevant features were variations along an emotional expression morphing continuum. The Control group did not undergo contrast discrimination learning and only performed the pre-training and post-training tests, with the same temporal gap between them as the other two groups. Results indicate that face discrimination improved, but only for the Emotion group. Participants in the Emotion group, moreover, showed face discrimination improvements also for stimulus variations along the facial identity dimension, even if these (task-irrelevant) stimulus features had not been presented during training. The present results highlight the importance of emotions for face discrimination learning. Copyright © 2015 Elsevier Ltd. All rights reserved.

Self-Efficacy, Task Complexity and Task Performance: Exploring Interactions in Two Versions of Vocabulary Learning Tasks

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

2012-01-01

The present study aimed for better understanding of the interactions between task complexity and students' self-efficacy beliefs and students' use of learning strategies, and finally their interacting effects on task performance. This investigation was carried out in the context of Chinese students learning English as a foreign language in a…

Dizocilpine (MK-801) impairs learning in the active place avoidance task but has no effect on the performance during task/context alternation.

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Vojtechova, Iveta; Petrasek, Tomas; Hatalova, Hana; Pistikova, Adela; Vales, Karel; Stuchlik, Ales

2016-05-15

The prevention of engram interference, pattern separation, flexibility, cognitive coordination and spatial navigation are usually studied separately at the behavioral level. Impairment in executive functions is often observed in patients suffering from schizophrenia. We have designed a protocol for assessing these functions all together as behavioral separation. This protocol is based on alternated or sequential training in two tasks testing different hippocampal functions (the Morris water maze and active place avoidance), and alternated or sequential training in two similar environments of the active place avoidance task. In Experiment 1, we tested, in adult rats, whether the performance in two different spatial tasks was affected by their order in sequential learning, or by their day-to-day alternation. In Experiment 2, rats learned to solve the active place avoidance task in two environments either alternately or sequentially. We found that rats are able to acquire both tasks and to discriminate both similar contexts without obvious problems regardless of the order or the alternation. We used two groups of rats, controls and a rat model of psychosis induced by a subchronic intraperitoneal application of 0.08mg/kg of dizocilpine (MK-801), a non-competitive antagonist of NMDA receptors. Dizocilpine had no selective effect on parallel/sequential learning of tasks/contexts. However, it caused hyperlocomotion and a significant deficit in learning in the active place avoidance task regardless of the task alternation. Cognitive coordination tested by this task is probably more sensitive to dizocilpine than spatial orientation because no hyperactivity or learning impairment was observed in the Morris water maze. Copyright © 2016 Elsevier B.V. All rights reserved.

Self-regulated learning processes of medical students during an academic learning task.

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Gandomkar, Roghayeh; Mirzazadeh, Azim; Jalili, Mohammad; Yazdani, Kamran; Fata, Ladan; Sandars, John

2016-10-01

This study was designed to identify the self-regulated learning (SRL) processes of medical students during a biomedical science learning task and to examine the associations of the SRL processes with previous performance in biomedical science examinations and subsequent performance on a learning task. A sample of 76 Year 1 medical students were recruited based on their performance in biomedical science examinations and stratified into previous high and low performers. Participants were asked to complete a biomedical science learning task. Participants' SRL processes were assessed before (self-efficacy, goal setting and strategic planning), during (metacognitive monitoring) and after (causal attributions and adaptive inferences) their completion of the task using an SRL microanalytic interview. Descriptive statistics were used to analyse the means and frequencies of SRL processes. Univariate and multiple logistic regression analyses were conducted to examine the associations of SRL processes with previous examination performance and the learning task performance. Most participants (from 88.2% to 43.4%) reported task-specific processes for SRL measures. Students who exhibited higher self-efficacy (odds ratio [OR] 1.44, 95% confidence interval [CI] 1.09-1.90) and reported task-specific processes for metacognitive monitoring (OR 6.61, 95% CI 1.68-25.93) and causal attributions (OR 6.75, 95% CI 2.05-22.25) measures were more likely to be high previous performers. Multiple analysis revealed that similar SRL measures were associated with previous performance. The use of task-specific processes for causal attributions (OR 23.00, 95% CI 4.57-115.76) and adaptive inferences (OR 27.00, 95% CI 3.39-214.95) measures were associated with being a high learning task performer. In multiple analysis, only the causal attributions measure was associated with high learning task performance. Self-efficacy, metacognitive monitoring and causal attributions measures were associated

Is it better to select or to receive? Learning via active and passive hypothesis testing.

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Markant, Douglas B; Gureckis, Todd M

2014-02-01

People can test hypotheses through either selection or reception. In a selection task, the learner actively chooses observations to test his or her beliefs, whereas in reception tasks data are passively encountered. People routinely use both forms of testing in everyday life, but the critical psychological differences between selection and reception learning remain poorly understood. One hypothesis is that selection learning improves learning performance by enhancing generic cognitive processes related to motivation, attention, and engagement. Alternatively, we suggest that differences between these 2 learning modes derives from a hypothesis-dependent sampling bias that is introduced when a person collects data to test his or her own individual hypothesis. Drawing on influential models of sequential hypothesis-testing behavior, we show that such a bias (a) can lead to the collection of data that facilitates learning compared with reception learning and (b) can be more effective than observing the selections of another person. We then report a novel experiment based on a popular category learning paradigm that compares reception and selection learning. We additionally compare selection learners to a set of "yoked" participants who viewed the exact same sequence of observations under reception conditions. The results revealed systematic differences in performance that depended on the learner's role in collecting information and the abstract structure of the problem.

Manifold regularized multi-task feature selection for multi-modality classification in Alzheimer's disease.

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Jie, Biao; Zhang, Daoqiang; Cheng, Bo; Shen, Dinggang

2013-01-01

Accurate diagnosis of Alzheimer's disease (AD), as well as its prodromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer's Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method.

Pairwise Constraint-Guided Sparse Learning for Feature Selection.

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Liu, Mingxia; Zhang, Daoqiang

2016-01-01

Feature selection aims to identify the most informative features for a compact and accurate data representation. As typical supervised feature selection methods, Lasso and its variants using L1-norm-based regularization terms have received much attention in recent studies, most of which use class labels as supervised information. Besides class labels, there are other types of supervised information, e.g., pairwise constraints that specify whether a pair of data samples belong to the same class (must-link constraint) or different classes (cannot-link constraint). However, most of existing L1-norm-based sparse learning methods do not take advantage of the pairwise constraints that provide us weak and more general supervised information. For addressing that problem, we propose a pairwise constraint-guided sparse (CGS) learning method for feature selection, where the must-link and the cannot-link constraints are used as discriminative regularization terms that directly concentrate on the local discriminative structure of data. Furthermore, we develop two variants of CGS, including: 1) semi-supervised CGS that utilizes labeled data, pairwise constraints, and unlabeled data and 2) ensemble CGS that uses the ensemble of pairwise constraint sets. We conduct a series of experiments on a number of data sets from University of California-Irvine machine learning repository, a gene expression data set, two real-world neuroimaging-based classification tasks, and two large-scale attribute classification tasks. Experimental results demonstrate the efficacy of our proposed methods, compared with several established feature selection methods.

Goal selection versus process control while learning to use a brain-computer interface

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Royer, Audrey S.; Rose, Minn L.; He, Bin

2011-06-01

A brain-computer interface (BCI) can be used to accomplish a task without requiring motor output. Two major control strategies used by BCIs during task completion are process control and goal selection. In process control, the user exerts continuous control and independently executes the given task. In goal selection, the user communicates their goal to the BCI and then receives assistance executing the task. A previous study has shown that goal selection is more accurate and faster in use. An unanswered question is, which control strategy is easier to learn? This study directly compares goal selection and process control while learning to use a sensorimotor rhythm-based BCI. Twenty young healthy human subjects were randomly assigned either to a goal selection or a process control-based paradigm for eight sessions. At the end of the study, the best user from each paradigm completed two additional sessions using all paradigms randomly mixed. The results of this study were that goal selection required a shorter training period for increased speed, accuracy, and information transfer over process control. These results held for the best subjects as well as in the general subject population. The demonstrated characteristics of goal selection make it a promising option to increase the utility of BCIs intended for both disabled and able-bodied users.

Investigating Antecedents of Task Commitment and Task Attraction in Service Learning Team Projects

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Schaffer, Bryan S.; Manegold, Jennifer G.

2018-01-01

The authors investigated the antecedents of team task cohesiveness in service learning classroom environments. Focusing on task commitment and task attraction as key dependent variables representing cohesiveness, and task interdependence as the primary independent variable, the authors position three important task action phase processes as…

Applications of Task-Based Learning in TESOL

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Shehadeh, Ali, Ed.; Coombe, Christine, Ed.

2010-01-01

Why are many teachers around the world moving toward task-based learning (TBL)? This shift is based on the strong belief that TBL facilitates second language acquisition and makes second language learning and teaching more principled and effective. Based on insights gained from using tasks as research tools, this volume shows how teachers can use…

Deep imitation learning for 3D navigation tasks.

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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.

Using a task-based approach to teaching and learning Chinese as a Foreign Language in a university beginner's level class

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Ruan, Youjin; Duan, Xiaoju; Wang, Li

2015-01-01

to learning Chinese as a foreign language. Chinese culture elements were also integrated into the tasks and the learning process. By analysing seven items of a post-course survey, this paper investigates the learners’ opinions toward the task-based language teaching and learning method, as well as the methods......The task-based method is regarded as an effective approach for promoting interaction and collaboration in language learning. In a beginner Chinese language course offered as an elective at Aalborg University, Denmark, a selection of tasks was designed and used to attract the students’ interests...... used in integrating culture with the language learning in this course. The results indicated that course participants were generally positive about their learning experiences and processes during the course. They appreciated not only the task-based method, but also the ways in which culture...

Algorithm-Dependent Generalization Bounds for Multi-Task Learning.

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Liu, Tongliang; Tao, Dacheng; Song, Mingli; Maybank, Stephen J

2017-02-01

Often, tasks are collected for multi-task learning (MTL) because they share similar feature structures. Based on this observation, in this paper, we present novel algorithm-dependent generalization bounds for MTL by exploiting the notion of algorithmic stability. We focus on the performance of one particular task and the average performance over multiple tasks by analyzing the generalization ability of a common parameter that is shared in MTL. When focusing on one particular task, with the help of a mild assumption on the feature structures, we interpret the function of the other tasks as a regularizer that produces a specific inductive bias. The algorithm for learning the common parameter, as well as the predictor, is thereby uniformly stable with respect to the domain of the particular task and has a generalization bound with a fast convergence rate of order O(1/n), where n is the sample size of the particular task. When focusing on the average performance over multiple tasks, we prove that a similar inductive bias exists under certain conditions on the feature structures. Thus, the corresponding algorithm for learning the common parameter is also uniformly stable with respect to the domains of the multiple tasks, and its generalization bound is of the order O(1/T), where T is the number of tasks. These theoretical analyses naturally show that the similarity of feature structures in MTL will lead to specific regularizations for predicting, which enables the learning algorithms to generalize fast and correctly from a few examples.

Manifold Regularized Multi-Task Feature Selection for Multi-Modality Classification in Alzheimer’s Disease

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Jie, Biao; Cheng, Bo

2014-01-01

Accurate diagnosis of Alzheimer’s disease (AD), as well as its pro-dromal stage (i.e., mild cognitive impairment, MCI), is very important for possible delay and early treatment of the disease. Recently, multi-modality methods have been used for fusing information from multiple different and complementary imaging and non-imaging modalities. Although there are a number of existing multi-modality methods, few of them have addressed the problem of joint identification of disease-related brain regions from multi-modality data for classification. In this paper, we proposed a manifold regularized multi-task learning framework to jointly select features from multi-modality data. Specifically, we formulate the multi-modality classification as a multi-task learning framework, where each task focuses on the classification based on each modality. In order to capture the intrinsic relatedness among multiple tasks (i.e., modalities), we adopted a group sparsity regularizer, which ensures only a small number of features to be selected jointly. In addition, we introduced a new manifold based Laplacian regularization term to preserve the geometric distribution of original data from each task, which can lead to the selection of more discriminative features. Furthermore, we extend our method to the semi-supervised setting, which is very important since the acquisition of a large set of labeled data (i.e., diagnosis of disease) is usually expensive and time-consuming, while the collection of unlabeled data is relatively much easier. To validate our method, we have performed extensive evaluations on the baseline Magnetic resonance imaging (MRI) and fluorodeoxyglucose positron emission tomography (FDG-PET) data of Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. Our experimental results demonstrate the effectiveness of the proposed method. PMID:24505676

Differences in perceptual learning transfer as a function of training task.

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Green, C Shawn; Kattner, Florian; Siegel, Max H; Kersten, Daniel; Schrater, Paul R

2015-01-01

A growing body of research--including results from behavioral psychology, human structural and functional imaging, single-cell recordings in nonhuman primates, and computational modeling--suggests that perceptual learning effects are best understood as a change in the ability of higher-level integration or association areas to read out sensory information in the service of particular decisions. Work in this vein has argued that, depending on the training experience, the "rules" for this read-out can either be applicable to new contexts (thus engendering learning generalization) or can apply only to the exact training context (thus resulting in learning specificity). Here we contrast learning tasks designed to promote either stimulus-specific or stimulus-general rules. Specifically, we compare learning transfer across visual orientation following training on three different tasks: an orientation categorization task (which permits an orientation-specific learning solution), an orientation estimation task (which requires an orientation-general learning solution), and an orientation categorization task in which the relevant category boundary shifts on every trial (which lies somewhere between the two tasks above). While the simple orientation-categorization training task resulted in orientation-specific learning, the estimation and moving categorization tasks resulted in significant orientation learning generalization. The general framework tested here--that task specificity or generality can be predicted via an examination of the optimal learning solution--may be useful in building future training paradigms with certain desired outcomes.

Different Neuroplasticity for Task Targets and Distractors

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Spingath, Elsie Y.; Kang, Hyun Sug; Plummer, Thane; Blake, David T.

2011-01-01

Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from nonselective

Different neuroplasticity for task targets and distractors.

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Elsie Y Spingath

2011-01-01

Full Text Available Adult learning-induced sensory cortex plasticity results in enhanced action potential rates in neurons that have the most relevant information for the task, or those that respond strongly to one sensory stimulus but weakly to its comparison stimulus. Current theories suggest this plasticity is caused when target stimulus evoked activity is enhanced by reward signals from neuromodulatory nuclei. Prior work has found evidence suggestive of nonselective enhancement of neural responses, and suppression of responses to task distractors, but the differences in these effects between detection and discrimination have not been directly tested. Using cortical implants, we defined physiological responses in macaque somatosensory cortex during serial, matched, detection and discrimination tasks. Nonselective increases in neural responsiveness were observed during detection learning. Suppression of responses to task distractors was observed during discrimination learning, and this suppression was specific to cortical locations that sampled responses to the task distractor before learning. Changes in receptive field size were measured as the area of skin that had a significant response to a constant magnitude stimulus, and these areal changes paralleled changes in responsiveness. From before detection learning until after discrimination learning, the enduring changes were selective suppression of cortical locations responsive to task distractors, and nonselective enhancement of responsiveness at cortical locations selective for target and control skin sites. A comparison of observations in prior studies with the observed plasticity effects suggests that the non-selective response enhancement and selective suppression suffice to explain known plasticity phenomena in simple spatial tasks. This work suggests that differential responsiveness to task targets and distractors in primary sensory cortex for a simple spatial detection and discrimination task arise from

Exploring the role of task performance and learning style on prefrontal hemodynamics during a working memory task.

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Anderson, Afrouz A; Parsa, Kian; Geiger, Sydney; Zaragoza, Rachel; Kermanian, Riley; Miguel, Helga; Dashtestani, Hadis; Chowdhry, Fatima A; Smith, Elizabeth; Aram, Siamak; Gandjbakhche, Amir H

2018-01-01

Existing literature outlines the quality and location of activation in the prefrontal cortex (PFC) during working memory (WM) tasks. However, the effects of individual differences on the underlying neural process of WM tasks are still unclear. In this functional near infrared spectroscopy study, we administered a visual and auditory n-back task to examine activation in the PFC while considering the influences of task performance, and preferred learning strategy (VARK score). While controlling for age, results indicated that high performance (HP) subjects (accuracy > 90%) showed task dependent lower activation compared to normal performance subjects in PFC region Specifically HP groups showed lower activation in left dorsolateral PFC (DLPFC) region during performance of auditory task whereas during visual task they showed lower activation in the right DLPFC. After accounting for learning style, we found a correlation between visual and aural VARK score and level of activation in the PFC. Subjects with higher visual VARK scores displayed lower activation during auditory task in left DLPFC, while those with higher visual scores exhibited higher activation during visual task in bilateral DLPFC. During performance of auditory task, HP subjects had higher visual VARK scores compared to NP subjects indicating an effect of learning style on the task performance and activation. The results of this study show that learning style and task performance can influence PFC activation, with applications toward neurological implications of learning style and populations with deficits in auditory or visual processing.

Selective increase of auditory cortico-striatal coherence during auditory-cued Go/NoGo discrimination learning.

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Andreas L. Schulz

2016-01-01

Full Text Available Goal directed behavior and associated learning processes are tightly linked to neuronal activity in the ventral striatum. Mechanisms that integrate task relevant sensory information into striatal processing during decision making and learning are implicitly assumed in current reinforcementmodels, yet they are still weakly understood. To identify the functional activation of cortico-striatal subpopulations of connections during auditory discrimination learning, we trained Mongolian gerbils in a two-way active avoidance task in a shuttlebox to discriminate between falling and rising frequency modulated tones with identical spectral properties. We assessed functional coupling by analyzing the field-field coherence between the auditory cortex and the ventral striatum of animals performing the task. During the course of training, we observed a selective increase of functionalcoupling during Go-stimulus presentations. These results suggest that the auditory cortex functionally interacts with the ventral striatum during auditory learning and that the strengthening of these functional connections is selectively goal-directed.

Deep Multi-Task Learning for Tree Genera Classification

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Ko, C.; Kang, J.; Sohn, G.

2018-05-01

The goal for our paper is to classify tree genera using airborne Light Detection and Ranging (LiDAR) data with Convolution Neural Network (CNN) - Multi-task Network (MTN) implementation. Unlike Single-task Network (STN) where only one task is assigned to the learning outcome, MTN is a deep learning architect for learning a main task (classification of tree genera) with other tasks (in our study, classification of coniferous and deciduous) simultaneously, with shared classification features. The main contribution of this paper is to improve classification accuracy from CNN-STN to CNN-MTN. This is achieved by introducing a concurrence loss (Lcd) to the designed MTN. This term regulates the overall network performance by minimizing the inconsistencies between the two tasks. Results show that we can increase the classification accuracy from 88.7 % to 91.0 % (from STN to MTN). The second goal of this paper is to solve the problem of small training sample size by multiple-view data generation. The motivation of this goal is to address one of the most common problems in implementing deep learning architecture, the insufficient number of training data. We address this problem by simulating training dataset with multiple-view approach. The promising results from this paper are providing a basis for classifying a larger number of dataset and number of classes in the future.

Selective bilateral amygdala lesions in rhesus monkeys fail to disrupt object reversal learning.

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Izquierdo, Alicia; Murray, Elisabeth A

2007-01-31

Neuropsychological studies in nonhuman primates have led to the view that the amygdala plays an essential role in stimulus-reward association. The main evidence in support of this idea is that bilateral aspirative or radiofrequency lesions of the amygdala yield severe impairments on object reversal learning, a task that assesses the ability to shift choices of objects based on the presence or absence of food reward (i.e., reward contingency). The behavioral effects of different lesion techniques, however, can vary. The present study therefore evaluated the effects of selective, excitotoxic lesions of the amygdala in rhesus monkeys on object reversal learning. For comparison, we tested the same monkeys on a task known to be sensitive to amygdala damage, the reinforcer devaluation task. Contrary to previous results based on less selective lesion techniques, monkeys with complete excitotoxic amygdala lesions performed object reversal learning as quickly as controls. As predicted, however, the same operated monkeys were impaired in making object choices after devaluation of the associated food reinforcer. The results suggest two conclusions. First, the results demonstrate that the amygdala makes a selective contribution to stimulus-reward association; the amygdala is critical for guiding object choices after changes in reward value but not after changes in reward contingency. Second, the results implicate a critical contribution to object reversal learning of structures nearby the amygdala, perhaps the subjacent rhinal cortex.

Learning and transfer of category knowledge in an indirect categorization task.

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Helie, Sebastien; Ashby, F Gregory

2012-05-01

Knowledge representations acquired during category learning experiments are 'tuned' to the task goal. A useful paradigm to study category representations is indirect category learning. In the present article, we propose a new indirect categorization task called the "same"-"different" categorization task. The same-different categorization task is a regular same-different task, but the question asked to the participants is about the stimulus category membership instead of stimulus identity. Experiment 1 explores the possibility of indirectly learning rule-based and information-integration category structures using the new paradigm. The results suggest that there is little learning about the category structures resulting from an indirect categorization task unless the categories can be separated by a one-dimensional rule. Experiment 2 explores whether a category representation learned indirectly can be used in a direct classification task (and vice versa). The results suggest that previous categorical knowledge acquired during a direct classification task can be expressed in the same-different categorization task only when the categories can be separated by a rule that is easily verbalized. Implications of these results for categorization research are discussed.

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

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

2014-01-01

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

The Effect of MALL-Based Tasks on EFL Learners' Grammar Learning

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Khodabandeh, Farzaneh; Alian, Jalal ed-din; Soleimani, Hassan

2017-01-01

Many studies have confirmed the importance of tasks on language learning. Nowadays, many teachers apply different kinds of tasks in their classrooms. The current study investigated the effect of mobile assisted language learning tasks (MALL) on participants' English grammar learning. The researcher administered a pre-validated grammar test to 90…

Embedded interruptions and task complexity influence schema-related cognitive load progression in an abstract learning task.

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Wirzberger, Maria; Esmaeili Bijarsari, Shirin; Rey, Günter Daniel

2017-09-01

Cognitive processes related to schema acquisition comprise an essential source of demands in learning situations. Since the related amount of cognitive load is supposed to change over time, plausible temporal models of load progression based on different theoretical backgrounds are inspected in this study. A total of 116 student participants completed a basal symbol sequence learning task, which provided insights into underlying cognitive dynamics. Two levels of task complexity were determined by the amount of elements within the symbol sequence. In addition, interruptions due to an embedded secondary task occurred at five predefined stages over the task. Within the resulting 2x5-factorial mixed between-within design, the continuous monitoring of efficiency in learning performance enabled assumptions on relevant resource investment. From the obtained results, a nonlinear change of learning efficiency over time seems most plausible in terms of cognitive load progression. Moreover, different effects of the induced interruptions show up in conditions of task complexity, which indicate the activation of distinct cognitive mechanisms related to structural aspects of the task. Findings are discussed in the light of evidence from research on memory and information processing. Copyright © 2017 Elsevier B.V. All rights reserved.

Interleaved Practice in Multi-Dimensional Learning Tasks: Which Dimension Should We Interleave?

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Rau, Martina A.; Aleven, Vincent; Rummel, Nikol

2013-01-01

Research shows that multiple representations can enhance student learning. Many curricula use multiple representations across multiple task types. The temporal sequence of representations and task types is likely to impact student learning. Research on contextual interference shows that interleaving learning tasks leads to better learning results…

The Role of Executive Control of Attention and Selective Encoding for Preschoolers' Learning

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Roderer, Thomas; Krebs, Saskia; Schmid, Corinne; Roebers, Claudia M.

2012-01-01

Selectivity in encoding, aspects of attentional control and their contribution to learning performance were explored in a sample of preschoolers. While the children are performing a learning task, their encoding of relevant and attention towards irrelevant information was recorded through an eye-tracking device. Recognition of target items was…

The effect of cognitive aging on implicit sequence learning and dual tasking

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Jochen eVandenbossche

2014-02-01

Full Text Available We investigated the influence of attentional demands on sequence-specific learning by means of the serial reaction time (SRT task (Nissen & Bullemer, 1987 in young (age 18-25 and aged (age 55-75 adults. Participants had to respond as fast as possible to a stimulus presented in one of four horizontal locations by pressing a key corresponding to the spatial position of the stimulus. During the training phase sequential blocks were accompanied by (1 no secondary task (single, (2 a secondary tone counting task (dual tone, or (3 a secondary shape counting task (dual shape. Both secondary tasks were administered to investigate whether low and high interference tasks interact with implicit learning and age. The testing phase, under baseline single condition, was implemented to assess differences in sequence-specific learning between young and aged adults. Results indicate that (1 aged subjects show less sequence learning compared to young adults, (2 young participants show similar implicit learning effects under both single and dual task conditions when we account for explicit awareness, and (3 aged adults demonstrate reduced learning when the primary task is accompanied with a secondary task, even when explicit awareness is included as a covariate in the analysis. These findings point to implicit learning deficits under dual task conditions that can be related to cognitive aging, demonstrating the need for sufficient cognitive resources while performing a sequence learning task.

Leadership for Learning: Tasks of Learning Culture

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Corrigan, Joe

2012-01-01

This is a comparative analysis of leadership related to organizational culture and change that occurred at a large Canadian university during a twenty year period 1983-2003. From an institutional development perspective, leadership is characterized as a culture creation and development responsibility. By centering on the tasks of learning culture,…

Integrating the behavioral and neural dynamics of response selection in a dual-task paradigm: a dynamic neural field model of Dux et al. (2009).

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Buss, Aaron T; Wifall, Tim; Hazeltine, Eliot; Spencer, John P

2014-02-01

People are typically slower when executing two tasks than when only performing a single task. These dual-task costs are initially robust but are reduced with practice. Dux et al. (2009) explored the neural basis of dual-task costs and learning using fMRI. Inferior frontal junction (IFJ) showed a larger hemodynamic response on dual-task trials compared with single-task trial early in learning. As dual-task costs were eliminated, dual-task hemodynamics in IFJ reduced to single-task levels. Dux and colleagues concluded that the reduction of dual-task costs is accomplished through increased efficiency of information processing in IFJ. We present a dynamic field theory of response selection that addresses two questions regarding these results. First, what mechanism leads to the reduction of dual-task costs and associated changes in hemodynamics? We show that a simple Hebbian learning mechanism is able to capture the quantitative details of learning at both the behavioral and neural levels. Second, is efficiency isolated to cognitive control areas such as IFJ, or is it also evident in sensory motor areas? To investigate this, we restrict Hebbian learning to different parts of the neural model. None of the restricted learning models showed the same reductions in dual-task costs as the unrestricted learning model, suggesting that efficiency is distributed across cognitive control and sensory motor processing systems.

Distraction during learning with hypermedia: Difficult tasks help to keep task goals on track

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Katharina eScheiter

2014-03-01

Full Text Available In educational hypermedia environments, students are often confronted with potential sources of distraction arising from additional information that, albeit interesting, is unrelated to their current task goal. The paper investigates the conditions under which distraction occurs and hampers performance. Based on theories of volitional action control it was hypothesized that interesting information, especially if related to a pending goal, would interfere with task performance only when working on easy, but not on difficult tasks. In Experiment 1, 66 students learned about probability theory using worked examples and solved corresponding test problems, whose task difficulty was manipulated. As a second factor, the presence of interesting information unrelated to the primary task was varied. Results showed that students solved more easy than difficult probability problems correctly. However, the presence of interesting, but task-irrelevant information did not interfere with performance. In Experiment 2, 68 students again engaged in example-based learning and problem solving in the presence of task-irrelevant information. Problem-solving difficulty was varied as a first factor. Additionally, the presence of a pending goal related to the task-irrelevant information was manipulated. As expected, problem-solving performance declined when a pending goal was present during working on easy problems, whereas no interference was observed for difficult problems. Moreover, the presence of a pending goal reduced the time on task-relevant information and increased the time on task-irrelevant information while working on easy tasks. However, as revealed by mediation analyses these changes in overt information processing behavior did not explain the decline in problem-solving performance. As an alternative explanation it is suggested that goal conflicts resulting from pending goals claim cognitive resources, which are then no longer available for learning and

[Connectionist models of social learning: a case of learning by observing a simple task].

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Paignon, A; Desrichard, O; Bollon, T

2004-03-01

This article proposes a connectionist model of the social learning theory developed by Bandura (1977). The theory posits that an individual in an interactive situation is capable of learning new behaviours merely by observing them in others. Such learning is acquired through an initial phase in which the individual memorizes what he has observed (observation phase), followed by a second phase where he puts the recorded observations to use as a guide for adjusting his own behaviour (reproduction phase). We shall refer to the two above-mentioned phases to demonstrate that it is conceivable to simulate learning by observation otherwise than through the recording of perceived information using symbolic representation. To this end we shall rely on the formalism of ecological neuron networks (Parisi, Cecconi, & Nolfi, 1990) to implement an agent provided with the major processes identified as essential to learning through observation. The connectionist model so designed shall implement an agent capable of recording perceptive information and producing motor behaviours. The learning situation we selected associates an agent demonstrating goal-achievement behaviour and an observer agent learning the same behaviour by observation. Throughout the acquisition phase, the demonstrator supervises the observer's learning process based on association between spatial information (input) and behavioural information (output). Representation thus constructed then serves as an adjustment guide during the production phase, involving production by the observer of a sequence of actions which he compares to the representation stored in distributed form as constructed through observation. An initial simulation validates model architecture by confirming the requirement for both phases identified in the literature (Bandura, 1977) to simulate learning through observation. The representation constructed over the observation phase evidences acquisition of observed behaviours, although this phase

The Neural Mechanisms Underlying Internally and Externally Guided Task Selection

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Orr, Joseph M.; Banich, Marie T.

2013-01-01

While some prior work suggests that medial prefrontal cortex (MFC) regions mediate freely chosen actions, other work suggests that the lateral frontal pole (LFP) is responsible for control of abstract, internal goals. The present study uses fMRI to determine whether the voluntary selection of a task in pursuit of an overall goal relies on MFC regions or the LFP. To do so, we used a modified voluntary task switching (VTS) paradigm, in which participants choose an individual task to perform on each trial (i.e., a subgoal), under instructions to perform the tasks equally often and in a random order (i.e. the overall goal). In conjunction, we examined patterns of activation in the face of irrelevant, but task-related external stimuli that might nonetheless influence task selection. While there was some evidence that the MFC was involved in voluntary task selection, we found that the LFP and anterior insula (AI) were crucial to task selection in the pursuit of an overall goal. In addition, activation of the LFP and AI increased in the face of environmental stimuli that might serve as an interfering or conflicting external bias on voluntary task choice. These findings suggest that the LFP supports task selection according to abstract, internal goals, and leaves open the possibility that MFC may guide action selection in situations lacking in such top-down biases. As such, the current study represents a critical step towards understanding the neural underpinnings of how tasks are selected voluntarily to enable an overarching goal. PMID:23994316

Robot Learning from Demonstration: A Task-level Planning Approach

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Staffan Ekvall

2008-09-01

Full Text Available In this paper, we deal with the problem of learning by demonstration, task level learning and planning for robotic applications that involve object manipulation. Preprogramming robots for execution of complex domestic tasks such as setting a dinner table is of little use, since the same order of subtasks may not be conceivable in the run time due to the changed state of the world. In our approach, we aim to learn the goal of the task and use a task planner to reach the goal given different initial states of the world. For some tasks, there are underlying constraints that must be fulfille, and knowing just the final goal is not sufficient. We propose two techniques for constraint identification. In the first case, the teacher can directly instruct the system about the underlying constraints. In the second case, the constraints are identified by the robot itself based on multiple observations. The constraints are then considered in the planning phase, allowing the task to be executed without violating any of them. We evaluate our work on a real robot performing pick-and-place tasks.

Impedance learning for robotic contact tasks using natural actor-critic algorithm.

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Kim, Byungchan; Park, Jooyoung; Park, Shinsuk; Kang, Sungchul

2010-04-01

Compared with their robotic counterparts, humans excel at various tasks by using their ability to adaptively modulate arm impedance parameters. This ability allows us to successfully perform contact tasks even in uncertain environments. This paper considers a learning strategy of motor skill for robotic contact tasks based on a human motor control theory and machine learning schemes. Our robot learning method employs impedance control based on the equilibrium point control theory and reinforcement learning to determine the impedance parameters for contact tasks. A recursive least-square filter-based episodic natural actor-critic algorithm is used to find the optimal impedance parameters. The effectiveness of the proposed method was tested through dynamic simulations of various contact tasks. The simulation results demonstrated that the proposed method optimizes the performance of the contact tasks in uncertain conditions of the environment.

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

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Cardis, Marco; Casadio, Maura; Ranganathan, Rajiv

2018-01-01

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

Heuristic for Task-Worker Assignment with Varying Learning Slopes

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Wipawee Tharmmaphornphilas

2010-04-01

Full Text Available Fashion industry has variety products, so the multi-skilled workers are required to improve flexibility in production and assignment. Generally the supervisor will assign task to the workers based on skill and skill levels of worker. Since in fashion industry new product styles are launched more frequently and the order size tends to be smaller, the workers always learn when the raw material and the production process changes. Consequently they require less time to produce the succeeding units of a task based on their learning ability. Since the workers have both experience and inexperience workers, so each worker has different skill level and learning ability. Consequently, the assignment which assumed constant skill level is not proper to use. This paper proposes a task-worker assignment considering worker skill levels and learning abilities. Processing time of each worker changes along production period due to a worker learning ability. We focus on a task-worker assignment in a fashion industry where tasks are ordered in series; the number of tasks is greater than the number of workers. Therefore, workers can perform multiple assignments followed the precedence restriction as an assembly line balancing problem. The problem is formulated in an integer linear programming model with objective to minimize makespan. A heuristic is proposed to determine the lower bound (LB and the upper bound (UB of the problem and the best assignment is determined. The performance of the heuristic method is tested by comparing quality of solution and computational time to optimal solutions.

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

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Zeng, Xueqiang; Luo, Gang

2017-12-01

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

Tasks and learner motivation in learning Chinese as a foreign language

DEFF Research Database (Denmark)

Ruan, Youjin; Duan, Xiaoju; Du, Xiangyun

2015-01-01

This study focuses on how beginner learners in a task-based teaching and learning (TBTL) environment perceive what is motivating to them in the process of learning Chinese as a foreign language (CFL) at Aalborg University (AAU), Denmark. Drawing upon empirical data from surveys, group interviews...... and participant observation, this study explores which kinds of tasks are perceived as motivating from the students’ perspective and which characteristics the learners associate with motivating tasks. The study indicates that it is important to consider the learners’ affective factors and learning situation...... factors, which can boost learners’ intrinsic motivation, when designing a task, especially at a beginning stage of foreign language learning, and to integrate cultural elements into tasks as an added value to motivate learners. Finally, this study identifies challenges and barriers related to TBTL...

Endogenously- and Exogenously-Driven Selective Sustained Attention: Contributions to Learning in Kindergarten Children

Science.gov (United States)

Erickson, Lucy C.; Thiessen, Erik D.; Godwin, Karrie E.; Dickerson, John P.; Fisher, Anna V.

2015-01-01

Selective sustained attention is vital for higher order cognition. Although endogenous and exogenous factors influence selective sustained attention, assessment of the degree to which these factors influence performance and learning is often challenging. We report findings from the Track-It task, a paradigm that aims to assess the contribution of…

Feedback-based probabilistic category learning is selectively impaired in attention/hyperactivity deficit disorder.

Science.gov (United States)

Gabay, Yafit; Goldfarb, Liat

2017-07-01

Although Attention-Deficit Hyperactivity Disorder (ADHD) is closely linked to executive function deficits, it has recently been attributed to procedural learning impairments that are quite distinct from the former. These observations challenge the ability of the executive function framework solely to account for the diverse range of symptoms observed in ADHD. A recent neurocomputational model emphasizes the role of striatal dopamine (DA) in explaining ADHD's broad range of deficits, but the link between this model and procedural learning impairments remains unclear. Significantly, feedback-based procedural learning is hypothesized to be disrupted in ADHD because of the involvement of striatal DA in this type of learning. In order to test this assumption, we employed two variants of a probabilistic category learning task known from the neuropsychological literature. Feedback-based (FB) and paired associate-based (PA) probabilistic category learning were employed in a non-medicated sample of ADHD participants and neurotypical participants. In the FB task, participants learned associations between cues and outcomes initially by guessing and subsequently through feedback indicating the correctness of the response. In the PA learning task, participants viewed the cue and its associated outcome simultaneously without receiving an overt response or corrective feedback. In both tasks, participants were trained across 150 trials. Learning was assessed in a subsequent test without a presentation of the outcome or corrective feedback. Results revealed an interesting disassociation in which ADHD participants performed as well as control participants in the PA task, but were impaired compared with the controls in the FB task. The learning curve during FB training differed between the two groups. Taken together, these results suggest that the ability to incrementally learn by feedback is selectively disrupted in ADHD participants. These results are discussed in relation to both

Web 2.0 Tasks in Action: EFL Learning in the U.S. Embassy School Election Project 2012

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Joannis Kaliampos

2014-10-01

Full Text Available Exploring topics that are personally relevant and interesting to young adult English as a foreign language (EFL learners remains a core challenge in language teaching. At the same time, the advent of Web 2.0 applications has many repercussions for authentic language learning. The “U.S. Embassy School Election Project 2012” has addressed these questions by combining a close focus on the U.S. Presidential Election with an interactive project scenario. Over 1,400 students across Germany participated in this project and produced an election forecast for an assigned U.S. state based on a survey of regional news media and social network data. Their predictions were in many cases more accurate than those of major U.S. broadcasting networks. This paper discusses the general educational potential of such projects in the contexts of computer-assisted language learning (CALL, intercultural learning, and learning in a task-based project environment. The authors have applied a multimodal qualitative approach to analyze tasks and learner perceptions of tasks in the context of the election project. In a first step, the micro-perspective of the perception of web-based tasks is investigated by example of one selected task cycle and a focus group of three learners. The second part of the analysis represents a bird’s-eye view on the learner products arising out of such tasks.

Optimizing the number of steps in learning tasks for complex skills.

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Nadolski, Rob J; Kirschner, Paul A; van Merriënboer, Jeroen J G

2005-06-01

Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimized for efficient and effective learning. The aim of the study is to investigate the relation between the number of steps provided to learners and the quality of their learning of complex skills. It is hypothesized that students receiving an optimized number of steps will learn better than those receiving either the whole task in only one step or those receiving a large number of steps. Participants were 35 sophomore law students studying at Dutch universities, mean age=22.8 years (SD=3.5), 63% were female. Participants were randomly assigned to 1 of 3 computer-delivered versions of a multimedia programme on how to prepare and carry out a law plea. The versions differed only in the number of learning steps provided. Videotaped plea-performance results were determined, various related learning measures were acquired and all computer actions were logged and analyzed. Participants exposed to an intermediate (i.e. optimized) number of steps outperformed all others on the compulsory learning task. No differences in performance on a transfer task were found. A high number of steps proved to be less efficient for carrying out the learning task. An intermediate number of steps is the most effective, proving that the number of steps can be optimized for improving learning.

End-task versus in-task feedback to increase procedural learning retention during spinal anaesthesia training of novices.

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Lean, Lyn Li; Hong, Ryan Yee Shiun; Ti, Lian Kah

2017-08-01

Communication of feedback during teaching of practical procedures is a fine balance of structure and timing. We investigate if continuous in-task (IT) or end-task feedback (ET) is more effective in teaching spinal anaesthesia to medical students. End-task feedback was hypothesized to improve both short-term and long-term procedural learning retention as experiential learning promotes active learning after encountering errors during practice. Upon exposure to a 5-min instructional video, students randomized to IT or ET feedbacks were trained using a spinal simulator mannequin. A blinded expert tested the students using a spinal anaesthesia checklist in the short term (immediate) and long-term (average 4 months). Sixty-five students completed the training and testing. There were no differences in demographics of age or gender within IT or ET distributions. Both short-term and long-term learning retention of spinal anaesthesia ET feedback proved to be better (P feedback. The time taken for ET students was shorter at long-term testing. End-task feedback improves both short-term and long-term procedural learning retention.

Asymmetrical learning between a tactile and visual serial RT task

NARCIS (Netherlands)

Abrahamse, E.L.; van der Lubbe, Robert Henricus Johannes; Verwey, Willem B.

2007-01-01

According to many researchers, implicit learning in the serial reaction-time task is predominantly motor based and therefore should be independent of stimulus modality. Previous research on the task, however, has focused almost completely on the visual domain. Here we investigated sequence learning

Task-specific effect of transcranial direct current stimulation on motor learning

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Cinthia Maria Saucedo Marquez

2013-07-01

Full Text Available Transcranial direct current stimulation (tDCS is a relatively new non-invasive brain stimulation technique that modulates neural processes. When applied to the human primary motor cortex (M1, tDCS has beneficial effects on motor skill learning and consolidation in healthy controls and in patients. However, it remains unclear whether tDCS improves motor learning in a general manner or whether these effects depend on which motor task is acquired. Here we compare whether the effect of tDCS differs when the same individual acquires (1 a Sequential Finger Tapping Task (SEQTAP and (2 a Visual Isometric Pinch Force Task (FORCE. Both tasks have been shown to be sensitive to tDCS applied over M1, however, the underlying processes mediating learning and memory formation might benefit differently from anodal-tDCS. Thirty healthy subjects were randomly assigned to an anodal-tDCS group or sham-group. Using a double-blind, sham-controlled cross-over design, tDCS was applied over M1 while subjects acquired each of the motor tasks over 3 consecutive days, with the order being randomized across subjects. We found that anodal-tDCS affected each task differently: The SEQTAP task benefited from anodal-tDCS during learning, whereas the FORCE task showed improvements only at retention. These findings suggest that anodal tDCS applied over M1 appears to have a task-dependent effect on learning and memory formation.

Robust visual tracking via multi-task sparse learning

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

2012-01-01

In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates

Cross-domain and multi-task transfer learning of deep convolutional neural network for breast cancer diagnosis in digital breast tomosynthesis

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Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir; Helvie, Mark A.; Richter, Caleb; Cha, Kenny

2018-02-01

We propose a cross-domain, multi-task transfer learning framework to transfer knowledge learned from non-medical images by a deep convolutional neural network (DCNN) to medical image recognition task while improving the generalization by multi-task learning of auxiliary tasks. A first stage cross-domain transfer learning was initiated from ImageNet trained DCNN to mammography trained DCNN. 19,632 regions-of-interest (ROI) from 2,454 mass lesions were collected from two imaging modalities: digitized-screen film mammography (SFM) and full-field digital mammography (DM), and split into training and test sets. In the multi-task transfer learning, the DCNN learned the mass classification task simultaneously from the training set of SFM and DM. The best transfer network for mammography was selected from three transfer networks with different number of convolutional layers frozen. The performance of single-task and multitask transfer learning on an independent SFM test set in terms of the area under the receiver operating characteristic curve (AUC) was 0.78+/-0.02 and 0.82+/-0.02, respectively. In the second stage cross-domain transfer learning, a set of 12,680 ROIs from 317 mass lesions on DBT were split into validation and independent test sets. We first studied the data requirements for the first stage mammography trained DCNN by varying the mammography training data from 1% to 100% and evaluated its learning on the DBT validation set in inference mode. We found that the entire available mammography set provided the best generalization. The DBT validation set was then used to train only the last four fully connected layers, resulting in an AUC of 0.90+/-0.04 on the independent DBT test set.

Studying different tasks of implicit learning across multiple test sessions conducted on the web

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Werner eSævland

2016-06-01

Full Text Available Implicit learning is usually studied through individual performance on a single task, with the most common tasks being Serial Reaction Time task (SRT; Nissen and Bullemer, 1987, Dynamic System Control task (DSC; (Berry and Broadbent, 1984 and artificial Grammar Learning task (AGL; (Reber, 1967. Few attempts have been made to compare performance across different implicit learning tasks within the same experiment. The current experiment was designed study the relationship between performance on the DSC Sugar factory task (Berry and Broadbent, 1984 and the Alternating Serial Reaction Time task (ASRT; (Howard and Howard, 1997. We also addressed another limitation to traditional implicit learning experiments, namely that implicit learning is usually studied in laboratory settings over a restricted time span lasting for less than an hour (Berry and Broadbent, 1984; Nissen and Bullemer, 1987; Reber, 1967. In everyday situations, implicit learning is assumed to involve a gradual accumulation of knowledge across several learning episodes over a larger time span (Norman and Price, 2012. One way to increase the ecological validity of implicit learning experiments could be to present the learning material repeatedly across shorter experimental sessions (Howard and Howard, 1997; Cleeremans and McClelland, 1991. This can most easily be done by using a web-based setup that participants can access from home. We therefore created an online web-based system for measuring implicit learning that could be administered in either single or multiple sessions. Participants (n = 66 were assigned to either a single-session or a multi-session condition. Learning and the degree of conscious awareness of the learned regularities was compared across condition (single vs. multiple sessions and tasks (DSC vs. ASRT. Results showed that learning on the two tasks was not related. However, participants in the multiple sessions condition did show greater improvements in reaction

Robust visual tracking via multi-task sparse learning

KAUST Repository

Zhang, Tianzhu

2012-06-01

In this paper, we formulate object tracking in a particle filter framework as a multi-task sparse learning problem, which we denote as Multi-Task Tracking (MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in MTT. By employing popular sparsity-inducing p, q mixed norms (p D; 1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L 1 tracker [15] is a special case of our MTT formulation (denoted as the L 11 tracker) when p q 1. The learning problem can be efficiently solved using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, MTT is computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that MTT methods consistently outperform state-of-the-art trackers. © 2012 IEEE.

Multisensory perceptual learning is dependent upon task difficulty.

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De Niear, Matthew A; Koo, Bonhwang; Wallace, Mark T

2016-11-01

There has been a growing interest in developing behavioral tasks to enhance temporal acuity as recent findings have demonstrated changes in temporal processing in a number of clinical conditions. Prior research has demonstrated that perceptual training can enhance temporal acuity both within and across different sensory modalities. Although certain forms of unisensory perceptual learning have been shown to be dependent upon task difficulty, this relationship has not been explored for multisensory learning. The present study sought to determine the effects of task difficulty on multisensory perceptual learning. Prior to and following a single training session, participants completed a simultaneity judgment (SJ) task, which required them to judge whether a visual stimulus (flash) and auditory stimulus (beep) presented in synchrony or at various stimulus onset asynchronies (SOAs) occurred synchronously or asynchronously. During the training session, participants completed the same SJ task but received feedback regarding the accuracy of their responses. Participants were randomly assigned to one of three levels of difficulty during training: easy, moderate, and hard, which were distinguished based on the SOAs used during training. We report that only the most difficult (i.e., hard) training protocol enhanced temporal acuity. We conclude that perceptual training protocols for enhancing multisensory temporal acuity may be optimized by employing audiovisual stimuli for which it is difficult to discriminate temporal synchrony from asynchrony.

Task-Based Language Learning and Teaching: An Action-Research Study

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Calvert, Megan; Sheen, Younghee

2015-01-01

The creation, implementation, and evaluation of language learning tasks remain a challenge for many teachers, especially those with limited experience with using tasks in their teaching. This action-research study reports on one teacher's experience of developing, implementing, critically reflecting on, and modifying a language learning task…

Jointly Feature Learning and Selection for Robust Tracking via a Gating Mechanism.

Directory of Open Access Journals (Sweden)

Bineng Zhong

Full Text Available To achieve effective visual tracking, a robust feature representation composed of two separate components (i.e., feature learning and selection for an object is one of the key issues. Typically, a common assumption used in visual tracking is that the raw video sequences are clear, while real-world data is with significant noise and irrelevant patterns. Consequently, the learned features may be not all relevant and noisy. To address this problem, we propose a novel visual tracking method via a point-wise gated convolutional deep network (CPGDN that jointly performs the feature learning and feature selection in a unified framework. The proposed method performs dynamic feature selection on raw features through a gating mechanism. Therefore, the proposed method can adaptively focus on the task-relevant patterns (i.e., a target object, while ignoring the task-irrelevant patterns (i.e., the surrounding background of a target object. Specifically, inspired by transfer learning, we firstly pre-train an object appearance model offline to learn generic image features and then transfer rich feature hierarchies from an offline pre-trained CPGDN into online tracking. In online tracking, the pre-trained CPGDN model is fine-tuned to adapt to the tracking specific objects. Finally, to alleviate the tracker drifting problem, inspired by an observation that a visual target should be an object rather than not, we combine an edge box-based object proposal method to further improve the tracking accuracy. Extensive evaluation on the widely used CVPR2013 tracking benchmark validates the robustness and effectiveness of the proposed method.

Elementary School Students' Strategic Learning: Does Task-Type Matter?

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Malmberg, Jonna; Järvelä, Sanna; Kirschner, Paul A.

2014-01-01

This study investigated what types of learning patterns and strategies elementary school students use to carry out ill- and well-structured tasks. Specifically, it was investigated which and when learning patterns actually emerge with respect to students' task solutions. The present study uses computer log file traces to investigate how…

Multi-task feature selection in microarray data by binary integer programming.

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Lan, Liang; Vucetic, Slobodan

2013-12-20

A major challenge in microarray classification is that the number of features is typically orders of magnitude larger than the number of examples. In this paper, we propose a novel feature filter algorithm to select the feature subset with maximal discriminative power and minimal redundancy by solving a quadratic objective function with binary integer constraints. To improve the computational efficiency, the binary integer constraints are relaxed and a low-rank approximation to the quadratic term is applied. The proposed feature selection algorithm was extended to solve multi-task microarray classification problems. We compared the single-task version of the proposed feature selection algorithm with 9 existing feature selection methods on 4 benchmark microarray data sets. The empirical results show that the proposed method achieved the most accurate predictions overall. We also evaluated the multi-task version of the proposed algorithm on 8 multi-task microarray datasets. The multi-task feature selection algorithm resulted in significantly higher accuracy than when using the single-task feature selection methods.

Word learning emerges from the interaction of online referent selection and slow associative learning

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McMurray, Bob; Horst, Jessica S.; Samuelson, Larissa K.

2013-01-01

Classic approaches to word learning emphasize the problem of referential ambiguity: in any naming situation the referent of a novel word must be selected from many possible objects, properties, actions, etc. To solve this problem, researchers have posited numerous constraints, and inference strategies, but assume that determining the referent of a novel word is isomorphic to learning. We present an alternative model in which referent selection is an online process that is independent of long-term learning. This two timescale approach creates significant power in the developing system. We illustrate this with a dynamic associative model in which referent selection is simulated as dynamic competition between competing referents, and learning is simulated using associative (Hebbian) learning. This model can account for a range of findings including the delay in expressive vocabulary relative to receptive vocabulary, learning under high degrees of referential ambiguity using cross-situational statistics, accelerating (vocabulary explosion) and decelerating (power-law) learning rates, fast-mapping by mutual exclusivity (and differences in bilinguals), improvements in familiar word recognition with development, and correlations between individual differences in speed of processing and learning. Five theoretical points are illustrated. 1) Word learning does not require specialized processes – general association learning buttressed by dynamic competition can account for much of the literature. 2) The processes of recognizing familiar words are not different than those that support novel words (e.g., fast-mapping). 3) Online competition may allow the network (or child) to leverage information available in the task to augment performance or behavior despite what might be relatively slow learning or poor representations. 4) Even associative learning is more complex than previously thought – a major contributor to performance is the pruning of incorrect associations

Task design for improving students’ engagement in mathematics learning

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Khairunnisa

2018-01-01

This article analysed the importance of task design as one of the instruments in the learning and its application in several studies. Through task design, students engage in learning caused them enthusiastically in expressing ideas, opinion or knowledge of them. Thus, the teacher was able to gain an idea of knowledge belonging to students. By using this information, teachers are able to develop the thinking ability of students.

Hebbian Learning in a Random Network Captures Selectivity Properties of the Prefrontal Cortex

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Lindsay, Grace W.

2017-01-01

Complex cognitive behaviors, such as context-switching and rule-following, are thought to be supported by the prefrontal cortex (PFC). Neural activity in the PFC must thus be specialized to specific tasks while retaining flexibility. Nonlinear “mixed” selectivity is an important neurophysiological trait for enabling complex and context-dependent behaviors. Here we investigate (1) the extent to which the PFC exhibits computationally relevant properties, such as mixed selectivity, and (2) how such properties could arise via circuit mechanisms. We show that PFC cells recorded from male and female rhesus macaques during a complex task show a moderate level of specialization and structure that is not replicated by a model wherein cells receive random feedforward inputs. While random connectivity can be effective at generating mixed selectivity, the data show significantly more mixed selectivity than predicted by a model with otherwise matched parameters. A simple Hebbian learning rule applied to the random connectivity, however, increases mixed selectivity and enables the model to match the data more accurately. To explain how learning achieves this, we provide analysis along with a clear geometric interpretation of the impact of learning on selectivity. After learning, the model also matches the data on measures of noise, response density, clustering, and the distribution of selectivities. Of two styles of Hebbian learning tested, the simpler and more biologically plausible option better matches the data. These modeling results provide clues about how neural properties important for cognition can arise in a circuit and make clear experimental predictions regarding how various measures of selectivity would evolve during animal training. SIGNIFICANCE STATEMENT The prefrontal cortex is a brain region believed to support the ability of animals to engage in complex behavior. How neurons in this area respond to stimuli—and in particular, to combinations of stimuli (�

HD-MTL: Hierarchical Deep Multi-Task Learning for Large-Scale Visual Recognition.

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Fan, Jianping; Zhao, Tianyi; Kuang, Zhenzhong; Zheng, Yu; Zhang, Ji; Yu, Jun; Peng, Jinye

2017-02-09

In this paper, a hierarchical deep multi-task learning (HD-MTL) algorithm is developed to support large-scale visual recognition (e.g., recognizing thousands or even tens of thousands of atomic object classes automatically). First, multiple sets of multi-level deep features are extracted from different layers of deep convolutional neural networks (deep CNNs), and they are used to achieve more effective accomplishment of the coarseto- fine tasks for hierarchical visual recognition. A visual tree is then learned by assigning the visually-similar atomic object classes with similar learning complexities into the same group, which can provide a good environment for determining the interrelated learning tasks automatically. By leveraging the inter-task relatedness (inter-class similarities) to learn more discriminative group-specific deep representations, our deep multi-task learning algorithm can train more discriminative node classifiers for distinguishing the visually-similar atomic object classes effectively. Our hierarchical deep multi-task learning (HD-MTL) algorithm can integrate two discriminative regularization terms to control the inter-level error propagation effectively, and it can provide an end-to-end approach for jointly learning more representative deep CNNs (for image representation) and more discriminative tree classifier (for large-scale visual recognition) and updating them simultaneously. Our incremental deep learning algorithms can effectively adapt both the deep CNNs and the tree classifier to the new training images and the new object classes. Our experimental results have demonstrated that our HD-MTL algorithm can achieve very competitive results on improving the accuracy rates for large-scale visual recognition.

Incidental orthographic learning during a color detection task.

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Protopapas, Athanassios; Mitsi, Anna; Koustoumbardis, Miltiadis; Tsitsopoulou, Sofia M; Leventi, Marianna; Seitz, Aaron R

2017-09-01

Orthographic learning refers to the acquisition of knowledge about specific spelling patterns forming words and about general biases and constraints on letter sequences. It is thought to occur by strengthening simultaneously activated visual and phonological representations during reading. Here we demonstrate that a visual perceptual learning procedure that leaves no time for articulation can result in orthographic learning evidenced in improved reading and spelling performance. We employed task-irrelevant perceptual learning (TIPL), in which the stimuli to be learned are paired with an easy task target. Assorted line drawings and difficult-to-spell words were presented in red color among sequences of other black-colored words and images presented in rapid succession, constituting a fast-TIPL procedure with color detection being the explicit task. In five experiments, Greek children in Grades 4-5 showed increased recognition of words and images that had appeared in red, both during and after the training procedure, regardless of within-training testing, and also when targets appeared in blue instead of red. Significant transfer to reading and spelling emerged only after increased training intensity. In a sixth experiment, children in Grades 2-3 showed generalization to words not presented during training that carried the same derivational affixes as in the training set. We suggest that reinforcement signals related to detection of the target stimuli contribute to the strengthening of orthography-phonology connections beyond earlier levels of visually-based orthographic representation learning. These results highlight the potential of perceptual learning procedures for the reinforcement of higher-level orthographic representations. Copyright © 2017 The Authors. Published by Elsevier B.V. All rights reserved.

E-learning, dual-task, and cognitive load: The anatomy of a failed experiment.

Science.gov (United States)

Van Nuland, Sonya E; Rogers, Kem A

2016-01-01

The rising popularity of commercial anatomy e-learning tools has been sustained, in part, due to increased annual enrollment and a reduction in laboratory hours across educational institutions. While e-learning tools continue to gain popularity, the research methodologies used to investigate their impact on learning remain imprecise. As new user interfaces are introduced, it is critical to understand how functionality can influence the load placed on a student's memory resources, also known as cognitive load. To study cognitive load, a dual-task paradigm wherein a learner performs two tasks simultaneously is often used, however, its application within educational research remains uncommon. Using previous paradigms as a guide, a dual-task methodology was developed to assess the cognitive load imposed by two commercial anatomical e-learning tools. Results indicate that the standard dual-task paradigm, as described in the literature, is insensitive to the cognitive load disparities across e-learning tool interfaces. Confounding variables included automation of responses, task performance tradeoff, and poor understanding of primary task cognitive load requirements, leading to unreliable quantitative results. By modifying the secondary task from a basic visual response to a more cognitively demanding task, such as a modified Stroop test, the automation of secondary task responses can be reduced. Furthermore, by recording baseline measures for the primary task as well as the secondary task, it is possible for task performance tradeoff to be detected. Lastly, it is imperative that the cognitive load of the primary task be designed such that it does not overwhelm the individual's ability to learn new material. © 2015 American Association of Anatomists.

Using Goal Setting and Task Analysis to Enhance Task-Based Language Learning and Teaching

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Rubin, Joan

2015-01-01

Task-Based Language Learning and Teaching has received sustained attention from teachers and researchers for over thirty years. It is a well-established pedagogy that includes the following characteristics: major focus on authentic and real-world tasks, choice of linguistic resources by learners, and a clearly defined non-linguistic outcome. This…

Addressing grammar in the interaction task-based learning environment

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Davis Brent M.

2017-01-01

Full Text Available One of the major problems in language teaching is developing grammatical accuracy. This paper proposes that using error correction based on a functional grammar in a task-based learning approach may be a suitable solution. Towards this end an emic (using categories intrinsic to the language functional grammar of the verb phrase is proposed and a description of how this fits into the focus on form component of task-based learning is provided.

Learning and inference using complex generative models in a spatial localization task.

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Bejjanki, Vikranth R; Knill, David C; Aslin, Richard N

2016-01-01

A large body of research has established that, under relatively simple task conditions, human observers integrate uncertain sensory information with learned prior knowledge in an approximately Bayes-optimal manner. However, in many natural tasks, observers must perform this sensory-plus-prior integration when the underlying generative model of the environment consists of multiple causes. Here we ask if the Bayes-optimal integration seen with simple tasks also applies to such natural tasks when the generative model is more complex, or whether observers rely instead on a less efficient set of heuristics that approximate ideal performance. Participants localized a "hidden" target whose position on a touch screen was sampled from a location-contingent bimodal generative model with different variances around each mode. Over repeated exposure to this task, participants learned the a priori locations of the target (i.e., the bimodal generative model), and integrated this learned knowledge with uncertain sensory information on a trial-by-trial basis in a manner consistent with the predictions of Bayes-optimal behavior. In particular, participants rapidly learned the locations of the two modes of the generative model, but the relative variances of the modes were learned much more slowly. Taken together, our results suggest that human performance in a more complex localization task, which requires the integration of sensory information with learned knowledge of a bimodal generative model, is consistent with the predictions of Bayes-optimal behavior, but involves a much longer time-course than in simpler tasks.

The importance of task appropriateness in computer-supported collaborative learning

Directory of Open Access Journals (Sweden)

Kathy Buckner

1999-12-01

Full Text Available The study of learning in collaborative electronic environments is becoming established as Computer Supported Collaborative Learning (CSCL - an emergent sub-discipline of the more established Computer Supported Co-operative Work (CSCW discipline (Webb, 1995. Using computers for the development of shared understanding through collaboration has been explored by Crook who suggests that success may depend partly on having a clearly specified purpose or goal (Crook, 1994. It is our view that the appropriateness of the task given to the student is central to the success or otherwise of the learning experience. However, the tasks that are given to facilitate collaborative learning in face-toface situations are not always suitable for direct transfer to the electronic medium. It may be necessary to consider redesigning these tasks in relation to the medium in which they are to be undertaken and the functionality of the electronic conferencing software used.

Active controllers and the time duration to learn a task

Science.gov (United States)

Repperger, D. W.; Goodyear, C.

1986-01-01

An active controller was used to help train naive subjects involved in a compensatory tracking task. The controller is called active in this context because it moves the subject's hand in a direction to improve tracking. It is of interest here to question whether the active controller helps the subject to learn a task more rapidly than the passive controller. Six subjects, inexperienced to compensatory tracking, were run to asymptote root mean square error tracking levels with an active controller or a passive controller. The time required to learn the task was defined several different ways. The results of the different measures of learning were examined across pools of subjects and across controllers using statistical tests. The comparison between the active controller and the passive controller as to their ability to accelerate the learning process as well as reduce levels of asymptotic tracking error is reported here.

A Developmental Perspective in Learning the Mirror-Drawing Task

Directory of Open Access Journals (Sweden)

Mona Sharon Julius

2016-03-01

Full Text Available Is there late maturation of skill learning? This notion has been raised to explain an adult advantage in learning a variety of tasks, such as auditory temporal-interval discrimination, locomotion adaptation, and drawing visually-distorted spatial patterns (mirror-drawing. Here, we test this assertion by following the practice of the mirror-drawing task in two 5 min daily sessions separated by a 10 min break, over the course of two days, in 5–6-year-old kindergarten children, 7–8-year-old second-graders, and young adults. In the mirror-drawing task, participants were required to trace a square while looking at their hand only as a reflection in a mirror. Kindergarteners did not show learning of the visual-motor mapping, and on average, did not produce even one full side of a square correctly. Second-graders showed increased online movement control with longer strokes, and robust learning of the visual-motor mapping, resulting in a between-day increase in the number of correctly drawn sides with no loss in accuracy. Overall, kindergarteners and second-graders producing at least one correct polygon-side on Day 1 were more likely to improve their performance between days. Adults showed better performance with greater improvements in the number of correctly drawn sides between- and within-days, and in accuracy between days. It has been suggested that 5-year-olds cannot learn the task due to their inability to detect and encapsulate previously produced accurate movements. Our findings suggest, instead, that these children did not have initial, accurate performance that could be enhanced through training. Recently, it has been shown that in a simple grapho-motor task the three age-groups improved their speed of performance within a session and between-days, while maintaining accuracy scores. Taken together, these data suggest that children's motor skill learning depends on the task’s characteristics and their adopting an efficient performance

Neural correlates of context-dependent feature conjunction learning in visual search tasks.

Science.gov (United States)

Reavis, Eric A; Frank, Sebastian M; Greenlee, Mark W; Tse, Peter U

2016-06-01

Many perceptual learning experiments show that repeated exposure to a basic visual feature such as a specific orientation or spatial frequency can modify perception of that feature, and that those perceptual changes are associated with changes in neural tuning early in visual processing. Such perceptual learning effects thus exert a bottom-up influence on subsequent stimulus processing, independent of task-demands or endogenous influences (e.g., volitional attention). However, it is unclear whether such bottom-up changes in perception can occur as more complex stimuli such as conjunctions of visual features are learned. It is not known whether changes in the efficiency with which people learn to process feature conjunctions in a task (e.g., visual search) reflect true bottom-up perceptual learning versus top-down, task-related learning (e.g., learning better control of endogenous attention). Here we show that feature conjunction learning in visual search leads to bottom-up changes in stimulus processing. First, using fMRI, we demonstrate that conjunction learning in visual search has a distinct neural signature: an increase in target-evoked activity relative to distractor-evoked activity (i.e., a relative increase in target salience). Second, we demonstrate that after learning, this neural signature is still evident even when participants passively view learned stimuli while performing an unrelated, attention-demanding task. This suggests that conjunction learning results in altered bottom-up perceptual processing of the learned conjunction stimuli (i.e., a perceptual change independent of the task). We further show that the acquired change in target-evoked activity is contextually dependent on the presence of distractors, suggesting that search array Gestalts are learned. Hum Brain Mapp 37:2319-2330, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Learning a locomotor task: with or without errors?

Science.gov (United States)

Marchal-Crespo, Laura; Schneider, Jasmin; Jaeger, Lukas; Riener, Robert

2014-03-04

Robotic haptic guidance is the most commonly used robotic training strategy to reduce performance errors while training. However, research on motor learning has emphasized that errors are a fundamental neural signal that drive motor adaptation. Thus, researchers have proposed robotic therapy algorithms that amplify movement errors rather than decrease them. However, to date, no study has analyzed with precision which training strategy is the most appropriate to learn an especially simple task. In this study, the impact of robotic training strategies that amplify or reduce errors on muscle activation and motor learning of a simple locomotor task was investigated in twenty two healthy subjects. The experiment was conducted with the MAgnetic Resonance COmpatible Stepper (MARCOS) a special robotic device developed for investigations in the MR scanner. The robot moved the dominant leg passively and the subject was requested to actively synchronize the non-dominant leg to achieve an alternating stepping-like movement. Learning with four different training strategies that reduce or amplify errors was evaluated: (i) Haptic guidance: errors were eliminated by passively moving the limbs, (ii) No guidance: no robot disturbances were presented, (iii) Error amplification: existing errors were amplified with repulsive forces, (iv) Noise disturbance: errors were evoked intentionally with a randomly-varying force disturbance on top of the no guidance strategy. Additionally, the activation of four lower limb muscles was measured by the means of surface electromyography (EMG). Strategies that reduce or do not amplify errors limit muscle activation during training and result in poor learning gains. Adding random disturbing forces during training seems to increase attention, and therefore improve motor learning. Error amplification seems to be the most suitable strategy for initially less skilled subjects, perhaps because subjects could better detect their errors and correct them

Robust visual tracking via structured multi-task sparse learning

KAUST Repository

Zhang, Tianzhu

2012-11-09

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary templates that are updated dynamically, learning the representation of each particle is considered a single task in Multi-Task Tracking (MTT). By employing popular sparsity-inducing lp,q mixed norms (specifically p∈2,∞ and q=1), we regularize the representation problem to enforce joint sparsity and learn the particle representations together. As compared to previous methods that handle particles independently, our results demonstrate that mining the interdependencies between particles improves tracking performance and overall computational complexity. Interestingly, we show that the popular L1 tracker (Mei and Ling, IEEE Trans Pattern Anal Mach Intel 33(11):2259-2272, 2011) is a special case of our MTT formulation (denoted as the L11 tracker) when p=q=1. Under the MTT framework, some of the tasks (particle representations) are often more closely related and more likely to share common relevant covariates than other tasks. Therefore, we extend the MTT framework to take into account pairwise structural correlations between particles (e.g. spatial smoothness of representation) and denote the novel framework as S-MTT. The problem of learning the regularized sparse representation in MTT and S-MTT can be solved efficiently using an Accelerated Proximal Gradient (APG) method that yields a sequence of closed form updates. As such, S-MTT and MTT are computationally attractive. We test our proposed approach on challenging sequences involving heavy occlusion, drastic illumination changes, and large pose variations. Experimental results show that S-MTT is much better than MTT, and both methods consistently outperform state-of-the-art trackers. © 2012 Springer Science+Business Media New York.

The Effect of Haptic Guidance on Learning a Hybrid Rhythmic-Discrete Motor Task.

Science.gov (United States)

Marchal-Crespo, Laura; Bannwart, Mathias; Riener, Robert; Vallery, Heike

2015-01-01

Bouncing a ball with a racket is a hybrid rhythmic-discrete motor task, combining continuous rhythmic racket movements with discrete impact events. Rhythmicity is exceptionally important in motor learning, because it underlies fundamental movements such as walking. Studies suggested that rhythmic and discrete movements are governed by different control mechanisms at different levels of the Central Nervous System. The aim of this study is to evaluate the effect of fixed/fading haptic guidance on learning to bounce a ball to a desired apex in virtual reality with varying gravity. Changing gravity changes dominance of rhythmic versus discrete control: The higher the value of gravity, the more rhythmic the task; lower values reduce the bouncing frequency and increase dwell times, eventually leading to a repetitive discrete task that requires initiation and termination, resembling target-oriented reaching. Although motor learning in the ball-bouncing task with varying gravity has been studied, the effect of haptic guidance on learning such a hybrid rhythmic-discrete motor task has not been addressed. We performed an experiment with thirty healthy subjects and found that the most effective training condition depended on the degree of rhythmicity: Haptic guidance seems to hamper learning of continuous rhythmic tasks, but it seems to promote learning for repetitive tasks that resemble discrete movements.

Effect of methylphenidate on enhancement of spatial learning by novel alternated dual task.

Science.gov (United States)

Veetil, Praveen Kottath; Mukkadan, Joseph Kurian

2011-01-01

The novel alternated dual task (ADT) arranged rats to learn T-maze spontaneous alternation task and radial arm maze (RAM) task alternatively, and by doing ADT, rats could acquire the tasks more easily than non alternated dual task (NADT) group. Also retention capacity of ADT group was significantly more and ADT help to learn a complex task faster than learning it in isolation from other tasks. In the present study effect of methylphenidate (MPD), a mood elevator, known to enhance learning and memory, on ADT procedure is assessed. Also effect of ADT procedure and MPD on spatial learning and memory are compared. Different groups were assigned by administering MPD (intraperitoneal injection at a dose of 3 mg/kg body weight) during different phases of behavioural experiments, and control groups received saline injection. MPD administration increased both acquisition and retention capacities. The amelioration attained for retention of complex task by ADT procedure, could be achieved by NADT rats only by administration of MPD. The influence of ADT procedure on acquisition and retention of TM and RAM tasks were similar to the effects of MPD, especially for the RAM task. MPD at low dose is found to enhance the learning and memory capacity in rats, than deteriorating it, supporting the use of MPD as a drug to treat attention deficit hyperactive disorder. The recent reports suggesting the effect of MPD only on retention and not on acquisition could not be confirmed, as enhancement for both acquisition and retention was found in this study.

Code-specific learning rules improve action selection by populations of spiking neurons.

Science.gov (United States)

Friedrich, Johannes; Urbanczik, Robert; Senn, Walter

2014-08-01

Population coding is widely regarded as a key mechanism for achieving reliable behavioral decisions. We previously introduced reinforcement learning for population-based decision making by spiking neurons. Here we generalize population reinforcement learning to spike-based plasticity rules that take account of the postsynaptic neural code. We consider spike/no-spike, spike count and spike latency codes. The multi-valued and continuous-valued features in the postsynaptic code allow for a generalization of binary decision making to multi-valued decision making and continuous-valued action selection. We show that code-specific learning rules speed up learning both for the discrete classification and the continuous regression tasks. The suggested learning rules also speed up with increasing population size as opposed to standard reinforcement learning rules. Continuous action selection is further shown to explain realistic learning speeds in the Morris water maze. Finally, we introduce the concept of action perturbation as opposed to the classical weight- or node-perturbation as an exploration mechanism underlying reinforcement learning. Exploration in the action space greatly increases the speed of learning as compared to exploration in the neuron or weight space.

PENGGUNAAN METODE TASK-BASED LEARNING UNTUK MENINGKATKAN KETERAMPILAN MENULIS MAHASISWA

Directory of Open Access Journals (Sweden)

Tri Kusnawati

2014-04-01

Full Text Available This study aims to increase the writing skills of students of French Education Department of Language and Art Faculty of Yogyakarta State University by using the task-based learning method in Expression Ecrite IV teaching. This is a classroom action research project consisting of two cycles. The subjects’ of the study were 15 students who took Writing IV (Expression Ecrite IV including the lecturer. Data were collected using a test, an observation, and a questionnaire. The data of the use of teaching method of task-based learning in Expression Ecrite IV obtained by using an observation and a questionnaire was interpreted qualitatively, while the data of students’ learning achievement in writing was analyzed quantitatively. Findings show that the use of learning method of task-based learning in Expression Ecrite IV could increase writing skills of the students. It was shown by the better comprehension and the mastery of materials. It was proven by the increase of the means in the posttest, that were 6.3 in cycle 1 and 7.2 in cycle 2. Besides, there was an improvement of learning process of writing skill IV as indicated by decreasing students’ passivity and increasing participation in meaningful learning activities.

How do task characteristics affect learning and performance? The roles of variably mapped and dynamic tasks.

Science.gov (United States)

Macnamara, Brooke N; Frank, David J

2018-05-01

For well over a century, scientists have investigated individual differences in performance. The majority of studies have focused on either differences in practice, or differences in cognitive resources. However, the predictive ability of either practice or cognitive resources varies considerably across tasks. We are the first to examine task characteristics' impact on learning and performance in a complex task while controlling for other task characteristics. In 2 experiments we test key theoretical task characteristic thought to moderate the relationship between practice, cognitive resources, and performance. We devised a task where each of several key task characteristics can be manipulated independently. Participants played 5 rounds of a game similar to the popular tower defense videogame Plants vs. Zombies where both cognitive load and game characteristics were manipulated. In Experiment 1, participants either played a consistently mapped version-the stimuli and the associated meaning of their properties were constant across the 5 rounds-or played a variably mapped version-the stimuli and the associated meaning of their properties changed every few minutes. In Experiment 2, participants either played a static version-that is, turn taking with no time pressure-or played a dynamic version-that is, the stimuli moved regardless of participants' response rates. In Experiment 1, participants' accuracy and efficiency were substantially hindered in the variably mapped conditions. In Experiment 2, learning and performance accuracy were hindered in the dynamic conditions, especially when under cognitive load. Our results suggest that task characteristics impact the relative importance of cognitive resources and practice on predicting learning and performance. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Robust visual tracking via structured multi-task sparse learning

KAUST Repository

Zhang, Tianzhu; Ghanem, Bernard; Liu, Si; Ahuja, Narendra

2012-01-01

In this paper, we formulate object tracking in a particle filter framework as a structured multi-task sparse learning problem, which we denote as Structured Multi-Task Tracking (S-MTT). Since we model particles as linear combinations of dictionary

A numeric comparison of variable selection algorithms for supervised learning

International Nuclear Information System (INIS)

Palombo, G.; Narsky, I.

2009-01-01

Datasets in modern High Energy Physics (HEP) experiments are often described by dozens or even hundreds of input variables. Reducing a full variable set to a subset that most completely represents information about data is therefore an important task in analysis of HEP data. We compare various variable selection algorithms for supervised learning using several datasets such as, for instance, imaging gamma-ray Cherenkov telescope (MAGIC) data found at the UCI repository. We use classifiers and variable selection methods implemented in the statistical package StatPatternRecognition (SPR), a free open-source C++ package developed in the HEP community ( (http://sourceforge.net/projects/statpatrec/)). For each dataset, we select a powerful classifier and estimate its learning accuracy on variable subsets obtained by various selection algorithms. When possible, we also estimate the CPU time needed for the variable subset selection. The results of this analysis are compared with those published previously for these datasets using other statistical packages such as R and Weka. We show that the most accurate, yet slowest, method is a wrapper algorithm known as generalized sequential forward selection ('Add N Remove R') implemented in SPR.

Fear of negative evaluation biases social evaluation inference: evidence from a probabilistic learning task.

Science.gov (United States)

Button, Katherine S; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M; Lewis, Glyn; Munafò, Marcus R

2015-01-01

Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences "I think [you are / George is]…". Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. As FNE increased participants selected fewer positive words (β = -0.4, 95% CI -0.7, -0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health.

A specific implicit sequence learning deficit as an underlying cause of dyslexia? Investigating the role of attention in implicit learning tasks.

Science.gov (United States)

Staels, Eva; Van den Broeck, Wim

2017-05-01

Recently, a general implicit sequence learning deficit was proposed as an underlying cause of dyslexia. This new hypothesis was investigated in the present study by including a number of methodological improvements, for example, the inclusion of appropriate control conditions. The second goal of the study was to explore the role of attentional functioning in implicit and explicit learning tasks. In a 2 × 2 within-subjects design 4 tasks were administered in 30 dyslexic and 38 control children: an implicit and explicit serial reaction time (RT) task and an implicit and explicit contextual cueing task. Attentional functioning was also administered. The entire learning curves of all tasks were analyzed using latent growth curve modeling in order to compare performances between groups and to examine the role of attentional functioning on the learning curves. The amount of implicit learning was similar for both groups. However, the dyslexic group showed slower RTs throughout the entire task. This group difference reduced and became nonsignificant after controlling for attentional functioning. Both implicit learning tasks, but none of the explicit learning tasks, were significantly affected by attentional functioning. Dyslexic children do not suffer from a specific implicit sequence learning deficit. The slower RTs of the dyslexic children throughout the entire implicit sequence learning process are caused by their comorbid attention problems and overall slowness. A key finding of the present study is that, in contrast to what was assumed for a long time, implicit learning relies on attentional resources, perhaps even more than explicit learning does. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

The Role of Subjective Task Value in Service-Learning Engagement among Chinese College Students.

Science.gov (United States)

Li, Yulan; Guo, Fangfang; Yao, Meilin; Wang, Cong; Yan, Wenfan

2016-01-01

Most service-learning studies in higher education focused on its effects on students' development. The dynamic processes and mechanisms of students' development during service-learning, however, have not been explored thoroughly. Student engagement in service-learning may affect service-learning outcomes and be affected by subjective task value at the same time. The present study aimed to explore the effect of subjective task value on Chinese college student engagement during service-learning. Fifty-four Chinese college students participated in a 9-weeks service-learning program of interacting with children with special needs. Students' engagement and subjective task value were assessed via self-report questionnaires and 433 weekly reflective journals. The results indicated that the cognitive, emotional and behavioral engagement of Chinese college students demonstrated different developmental trends during service-learning process. Subjective task value played an essential role in student engagement in service-learning activities. However, the role of subjective task value varied with different stages. Finally, the implications for implementing service-learning in Chinese education were discussed.

The Role of Subjective Task Value in Service-Learning Engagement among Chinese College Students

Science.gov (United States)

Li, Yulan; Guo, Fangfang; Yao, Meilin; Wang, Cong; Yan, Wenfan

2016-01-01

Most service-learning studies in higher education focused on its effects on students’ development. The dynamic processes and mechanisms of students’ development during service-learning, however, have not been explored thoroughly. Student engagement in service-learning may affect service-learning outcomes and be affected by subjective task value at the same time. The present study aimed to explore the effect of subjective task value on Chinese college student engagement during service-learning. Fifty-four Chinese college students participated in a 9-weeks service-learning program of interacting with children with special needs. Students’ engagement and subjective task value were assessed via self-report questionnaires and 433 weekly reflective journals. The results indicated that the cognitive, emotional and behavioral engagement of Chinese college students demonstrated different developmental trends during service-learning process. Subjective task value played an essential role in student engagement in service-learning activities. However, the role of subjective task value varied with different stages. Finally, the implications for implementing service-learning in Chinese education were discussed. PMID:27445919

Autonomous Learning through Task-Based Instruction in Fully Online Language Courses

Science.gov (United States)

Lee, Lina

2016-01-01

This study investigated the affordances for autonomous learning in a fully online learning environment involving the implementation of task-based instruction in conjunction with Web 2.0 technologies. To that end, four-skill-integrated tasks and digital tools were incorporated into the coursework. Data were collected using midterm reflections,…

Dynamic, continuous multitasking training leads to task-specific improvements but does not transfer across action selection tasks

Science.gov (United States)

Bender, Angela D.; Filmer, Hannah L.; Naughtin, Claire K.; Dux, Paul E.

2017-12-01

The ability to perform multiple tasks concurrently is an ever-increasing requirement in our information-rich world. Despite this, multitasking typically compromises performance due to the processing limitations associated with cognitive control and decision-making. While intensive dual-task training is known to improve multitasking performance, only limited evidence suggests that training-related performance benefits can transfer to untrained tasks that share overlapping processes. In the real world, however, coordinating and selecting several responses within close temporal proximity will often occur in high-interference environments. Over the last decade, there have been notable reports that training on video action games that require dynamic multitasking in a demanding environment can lead to transfer effects on aspects of cognition such as attention and working memory. Here, we asked whether continuous and dynamic multitasking training extends benefits to tasks that are theoretically related to the trained tasks. To examine this issue, we asked a group of participants to train on a combined continuous visuomotor tracking task and a perceptual discrimination task for six sessions, while an active control group practiced the component tasks in isolation. A battery of tests measuring response selection, response inhibition, and spatial attention was administered before and immediately after training to investigate transfer. Multitasking training resulted in substantial, task-specific gains in dual-task ability, but there was no evidence that these benefits generalized to other action control tasks. The findings suggest that training on a combined visuomotor tracking and discrimination task results in task-specific benefits but provides no additional value for untrained action selection tasks.

Task-Based Language Teaching and Expansive Learning Theory

Science.gov (United States)

Robertson, Margaret

2014-01-01

Task-Based Language Teaching (TBLT) has become increasingly recognized as an effective pedagogy, but its location in generalized sociocultural theories of learning has led to misunderstandings and criticism. The purpose of this article is to explain the congruence between TBLT and Expansive Learning Theory and the benefits of doing so. The merit…

THE ROLE OF TASK-INDUCED INVOLVEMENT IN VOCABULARY LEARNING OF IRANIAN LANGUAGE LEARNERS

Directory of Open Access Journals (Sweden)

Fatemeh Khonamri

2013-01-01

Full Text Available This study investigated Laufer and Hustijn’s (2001 Involvement Load Hypothesis in vocabulary learning. It comprised two experiments. Experiment 1 examined whether two tasks with equal involvement load but different distribution of components would yield the same result in initial learning and retention of target words. Experiment 2 investigated whether two tasks, one input and another output, with equal involvement load and the same distribution of components would result in equivalent initial learning and retention of target words. 126 advanced English learners completed one of three vocabulary learning tasks that equated in the amount of involvement they induced: sentence writing, fill-in, and translation (L2-L1. Receptive knowledge of the target words was assessed immediately after treatment and two weeks later, and one month interval after the first delayed posttest. The result of t-test for Experiment 1 showed that when two tasks had equal involvement load but different distribution of components they resulted in similar amounts of initial learning and retention of new words. The findings of Experiment 2 indicated when two tasks, one input and another output, had equal involvement load and the same distribution of components, they led to superiority of fill-in task over translation task in initial vocabulary learning, however, not in retention of new words.

Collaborative Tasks in Wiki-Based Environment in EFL Learning

Science.gov (United States)

Zou, Bin; Wang, Dongshuo; Xing, Minjie

2016-01-01

Wikis provide users with opportunities to post and edit messages to collaborate in the language learning process. Many studies have offered findings to show positive impact of Wiki-based language learning for learners. This paper explores the effect of collaborative task in error correction for English as a Foreign Language learning in an online…

Multi-task learning with group information for human action recognition

Science.gov (United States)

Qian, Li; Wu, Song; Pu, Nan; Xu, Shulin; Xiao, Guoqiang

2018-04-01

Human action recognition is an important and challenging task in computer vision research, due to the variations in human motion performance, interpersonal differences and recording settings. In this paper, we propose a novel multi-task learning framework with group information (MTL-GI) for accurate and efficient human action recognition. Specifically, we firstly obtain group information through calculating the mutual information according to the latent relationship between Gaussian components and action categories, and clustering similar action categories into the same group by affinity propagation clustering. Additionally, in order to explore the relationships of related tasks, we incorporate group information into multi-task learning. Experimental results evaluated on two popular benchmarks (UCF50 and HMDB51 datasets) demonstrate the superiority of our proposed MTL-GI framework.

Perceptual learning of basic visual features remains task specific with Training-Plus-Exposure (TPE) training.

Science.gov (United States)

Cong, Lin-Juan; Wang, Ru-Jie; Yu, Cong; Zhang, Jun-Yun

2016-01-01

Visual perceptual learning is known to be specific to the trained retinal location, feature, and task. However, location and feature specificity can be eliminated by double-training or TPE training protocols, in which observers receive additional exposure to the transfer location or feature dimension via an irrelevant task besides the primary learning task Here we tested whether these new training protocols could even make learning transfer across different tasks involving discrimination of basic visual features (e.g., orientation and contrast). Observers practiced a near-threshold orientation (or contrast) discrimination task. Following a TPE training protocol, they also received exposure to the transfer task via performing suprathreshold contrast (or orientation) discrimination in alternating blocks of trials in the same sessions. The results showed no evidence for significant learning transfer to the untrained near-threshold contrast (or orientation) discrimination task after discounting the pretest effects and the suprathreshold practice effects. These results thus do not support a hypothetical task-independent component in perceptual learning of basic visual features. They also set the boundary of the new training protocols in their capability to enable learning transfer.

The effect of the external regulator's absence on children's speech use, manifested self-regulation, and task performance during learning tasks

NARCIS (Netherlands)

Agina, Adel M.; Agina, Adel Masaud; Kommers, Petrus A.M.; Steehouder, M.F.

2011-01-01

The present study was conducted to explore the effect of the absence of the external regulators on children’s use of speech (private/social), task performance, and self-regulation during learning tasks. A novel methodology was employed through a computer-based learning environment that proposed

Informal learning of secondary-school students and learning tasks of the family

Directory of Open Access Journals (Sweden)

Sanja Berčnik

2006-12-01

Full Text Available The' author speaks about the role of informal learning for young people and their family, differences about spending free-time and possibilities of using free-time for informal learning. The presupposition is that while learning scope is constantly expanding, also learning tasks of the family are increasing. Because of different social environments of young people, there is a question, what are actual possibilities for informal learning in their domestic environment and how this affects their development. The most important question, which must be asked according to the author is, whether parents are ware of their influence, of the influence of their actions on development and learning of their children.

Gene selection for microarray data classification via subspace learning and manifold regularization.

Science.gov (United States)

Tang, Chang; Cao, Lijuan; Zheng, Xiao; Wang, Minhui

2017-12-19

With the rapid development of DNA microarray technology, large amount of genomic data has been generated. Classification of these microarray data is a challenge task since gene expression data are often with thousands of genes but a small number of samples. In this paper, an effective gene selection method is proposed to select the best subset of genes for microarray data with the irrelevant and redundant genes removed. Compared with original data, the selected gene subset can benefit the classification task. We formulate the gene selection task as a manifold regularized subspace learning problem. In detail, a projection matrix is used to project the original high dimensional microarray data into a lower dimensional subspace, with the constraint that the original genes can be well represented by the selected genes. Meanwhile, the local manifold structure of original data is preserved by a Laplacian graph regularization term on the low-dimensional data space. The projection matrix can serve as an importance indicator of different genes. An iterative update algorithm is developed for solving the problem. Experimental results on six publicly available microarray datasets and one clinical dataset demonstrate that the proposed method performs better when compared with other state-of-the-art methods in terms of microarray data classification. Graphical Abstract The graphical abstract of this work.

Fear of Negative Evaluation Biases Social Evaluation Inference: Evidence from a Probabilistic Learning Task

Science.gov (United States)

Button, Katherine S.; Kounali, Daphne; Stapinski, Lexine; Rapee, Ronald M.; Lewis, Glyn; Munafò, Marcus R.

2015-01-01

Background Fear of negative evaluation (FNE) defines social anxiety yet the process of inferring social evaluation, and its potential role in maintaining social anxiety, is poorly understood. We developed an instrumental learning task to model social evaluation learning, predicting that FNE would specifically bias learning about the self but not others. Methods During six test blocks (3 self-referential, 3 other-referential), participants (n = 100) met six personas and selected a word from a positive/negative pair to finish their social evaluation sentences “I think [you are / George is]…”. Feedback contingencies corresponded to 3 rules, liked, neutral and disliked, with P[positive word correct] = 0.8, 0.5 and 0.2, respectively. Results As FNE increased participants selected fewer positive words (β = −0.4, 95% CI −0.7, −0.2, p = 0.001), which was strongest in the self-referential condition (FNE × condition 0.28, 95% CI 0.01, 0.54, p = 0.04), and the neutral and dislike rules (FNE × condition × rule, p = 0.07). At low FNE the proportion of positive words selected for self-neutral and self-disliked greatly exceeded the feedback contingency, indicating poor learning, which improved as FNE increased. Conclusions FNE is associated with differences in processing social-evaluative information specifically about the self. At low FNE this manifests as insensitivity to learning negative self-referential evaluation. High FNE individuals are equally sensitive to learning positive or negative evaluation, which although objectively more accurate, may have detrimental effects on mental health. PMID:25853835

Robust Online Multi-Task Learning with Correlative and Personalized Structures

KAUST Repository

Yang, Peng

2017-06-29

Multi-Task Learning (MTL) can enhance a classifier\\'s generalization performance by learning multiple related tasks simultaneously. Conventional MTL works under the offline setting and suffers from expensive training cost and poor scalability. To address such issues, online learning techniques have been applied to solve MTL problems. However, most existing algorithms of online MTL constrain task relatedness into a presumed structure via a single weight matrix, which is a strict restriction that does not always hold in practice. In this paper, we propose a robust online MTL framework that overcomes this restriction by decomposing the weight matrix into two components: the first one captures the low-rank common structure among tasks via a nuclear norm; the second one identifies the personalized patterns of outlier tasks via a group lasso. Theoretical analysis shows the proposed algorithm can achieve a sub-linear regret with respect to the best linear model in hindsight. However, the nuclear norm that simply adds all nonzero singular values together may not be a good low-rank approximation. To improve the results, we use a log-determinant function as a non-convex rank approximation. Experimental results on a number of real-world applications also verify the efficacy of our approaches.

Robust Online Multi-Task Learning with Correlative and Personalized Structures

KAUST Repository

Yang, Peng; Zhao, Peilin; Gao, Xin

2017-01-01

Multi-Task Learning (MTL) can enhance a classifier's generalization performance by learning multiple related tasks simultaneously. Conventional MTL works under the offline setting and suffers from expensive training cost and poor scalability. To address such issues, online learning techniques have been applied to solve MTL problems. However, most existing algorithms of online MTL constrain task relatedness into a presumed structure via a single weight matrix, which is a strict restriction that does not always hold in practice. In this paper, we propose a robust online MTL framework that overcomes this restriction by decomposing the weight matrix into two components: the first one captures the low-rank common structure among tasks via a nuclear norm; the second one identifies the personalized patterns of outlier tasks via a group lasso. Theoretical analysis shows the proposed algorithm can achieve a sub-linear regret with respect to the best linear model in hindsight. However, the nuclear norm that simply adds all nonzero singular values together may not be a good low-rank approximation. To improve the results, we use a log-determinant function as a non-convex rank approximation. Experimental results on a number of real-world applications also verify the efficacy of our approaches.

Task type and incidental L2 vocabulary learning: Repetition versus ...

African Journals Online (AJOL)

This study investigated the effect of task type on incidental L2 vocabulary learning. The different tasks investigated in this study differed in terms of repetition of encounters and task involvement load. In a within-subjects design, 72 Iranian learners of English practised 18 target words in three exercise conditions: three ...

Identifying beneficial task relations for multi-task learning in deep neural networks

DEFF Research Database (Denmark)

Bingel, Joachim; Søgaard, Anders

2017-01-01

Multi-task learning (MTL) in deep neural networks for NLP has recently received increasing interest due to some compelling benefits, including its potential to efficiently regularize models and to reduce the need for labeled data. While it has brought significant improvements in a number of NLP...

Designing Digital Problem Based Learning Tasks that Motivate Students

Science.gov (United States)

van Loon, Anne-Marieke; Ros, Anje; Martens, Rob

2013-01-01

This study examines whether teachers are able to apply the principles of autonomy support and structure support in designing digital problem based learning (PBL) tasks. We examine whether these tasks are more autonomy- and structure-supportive and whether primary and secondary school students experience greater autonomy, competence, and motivation…

Concurrent Learning of Control in Multi agent Sequential Decision Tasks

Science.gov (United States)

2018-04-17

Concurrent Learning of Control in Multi-agent Sequential Decision Tasks The overall objective of this project was to develop multi-agent reinforcement... learning (MARL) approaches for intelligent agents to autonomously learn distributed control policies in decentral- ized partially observable... learning of policies in Dec-POMDPs, established performance bounds, evaluated these algorithms both theoretically and empirically, The views

Multi-population genomic prediction using a multi-task Bayesian learning model.

Science.gov (United States)

Chen, Liuhong; Li, Changxi; Miller, Stephen; Schenkel, Flavio

2014-05-03

Genomic prediction in multiple populations can be viewed as a multi-task learning problem where tasks are to derive prediction equations for each population and multi-task learning property can be improved by sharing information across populations. The goal of this study was to develop a multi-task Bayesian learning model for multi-population genomic prediction with a strategy to effectively share information across populations. Simulation studies and real data from Holstein and Ayrshire dairy breeds with phenotypes on five milk production traits were used to evaluate the proposed multi-task Bayesian learning model and compare with a single-task model and a simple data pooling method. A multi-task Bayesian learning model was proposed for multi-population genomic prediction. Information was shared across populations through a common set of latent indicator variables while SNP effects were allowed to vary in different populations. Both simulation studies and real data analysis showed the effectiveness of the multi-task model in improving genomic prediction accuracy for the smaller Ayshire breed. Simulation studies suggested that the multi-task model was most effective when the number of QTL was small (n = 20), with an increase of accuracy by up to 0.09 when QTL effects were lowly correlated between two populations (ρ = 0.2), and up to 0.16 when QTL effects were highly correlated (ρ = 0.8). When QTL genotypes were included for training and validation, the improvements were 0.16 and 0.22, respectively, for scenarios of the low and high correlation of QTL effects between two populations. When the number of QTL was large (n = 200), improvement was small with a maximum of 0.02 when QTL genotypes were not included for genomic prediction. Reduction in accuracy was observed for the simple pooling method when the number of QTL was small and correlation of QTL effects between the two populations was low. For the real data, the multi-task model achieved an

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems

OpenAIRE

Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed...

Concrete and abstract visualizations in history learning tasks

NARCIS (Netherlands)

Prangsma, Maaike; Van Boxtel, Carla; Kanselaar, Gellof; Kirschner, Paul A.

2010-01-01

Prangsma, M. E., Van Boxtel, C. A. M., Kanselaar, G., & Kirschner, P. A. (2009). Concrete and abstract visualizations in history learning tasks. British Journal of Educational Psychology, 79, 371-387.

How learning might strengthen existing visual object representations in human object-selective cortex.

Science.gov (United States)

Brants, Marijke; Bulthé, Jessica; Daniels, Nicky; Wagemans, Johan; Op de Beeck, Hans P

2016-02-15

Visual object perception is an important function in primates which can be fine-tuned by experience, even in adults. Which factors determine the regions and the neurons that are modified by learning is still unclear. Recently, it was proposed that the exact cortical focus and distribution of learning effects might depend upon the pre-learning mapping of relevant functional properties and how this mapping determines the informativeness of neural units for the stimuli and the task to be learned. From this hypothesis we would expect that visual experience would strengthen the pre-learning distributed functional map of the relevant distinctive object properties. Here we present a first test of this prediction in twelve human subjects who were trained in object categorization and differentiation, preceded and followed by a functional magnetic resonance imaging session. Specifically, training increased the distributed multi-voxel pattern information for trained object distinctions in object-selective cortex, resulting in a generalization from pre-training multi-voxel activity patterns to after-training activity patterns. Simulations show that the increased selectivity combined with the inter-session generalization is consistent with a training-induced strengthening of a pre-existing selectivity map. No training-related neural changes were detected in other regions. In sum, training to categorize or individuate objects strengthened pre-existing representations in human object-selective cortex, providing a first indication that the neuroanatomical distribution of learning effects depends upon the pre-learning mapping of visual object properties. Copyright © 2015 Elsevier Inc. All rights reserved.

Explicit goal-driven attention, unlike implicitly learned attention, spreads to secondary tasks.

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Addleman, Douglas A; Tao, Jinyi; Remington, Roger W; Jiang, Yuhong V

2018-03-01

To what degree does spatial attention for one task spread to all stimuli in the attended region, regardless of task relevance? Most models imply that spatial attention acts through a unitary priority map in a task-general manner. We show that implicit learning, unlike endogenous spatial cuing, can bias spatial attention within one task without biasing attention to a spatially overlapping secondary task. Participants completed a visual search task superimposed on a background containing scenes, which they were told to encode for a later memory task. Experiments 1 and 2 used explicit instructions to bias spatial attention to one region for visual search; Experiment 3 used location probability cuing to implicitly bias spatial attention. In location probability cuing, a target appeared in one region more than others despite participants not being told of this. In all experiments, search performance was better in the cued region than in uncued regions. However, scene memory was better in the cued region only following endogenous guidance, not after implicit biasing of attention. These data support a dual-system view of top-down attention that dissociates goal-driven and implicitly learned attention. Goal-driven attention is task general, amplifying processing of a cued region across tasks, whereas implicit statistical learning is task-specific. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The effect of encoding conditions on learning in the prototype distortion task.

Science.gov (United States)

Lee, Jessica C; Livesey, Evan J

2017-06-01

The prototype distortion task demonstrates that it is possible to learn about a category of physically similar stimuli through mere observation. However, there have been few attempts to test whether different encoding conditions affect learning in this task. This study compared prototypicality gradients produced under incidental learning conditions in which participants performed a visual search task, with those produced under intentional learning conditions in which participants were required to memorize the stimuli. Experiment 1 showed that similar prototypicality gradients could be obtained for category endorsement and familiarity ratings, but also found (weaker) prototypicality gradients in the absence of exposure. In Experiments 2 and 3, memorization was found to strengthen prototypicality gradients in familiarity ratings in comparison to visual search, but there were no group differences in participants' ability to discriminate between novel and presented exemplars. Although the Search groups in Experiments 2 and 3 produced prototypicality gradients, they were no different in magnitude to those produced in the absence of stimulus exposure in Experiment 1, suggesting that incidental learning during visual search was not conducive to producing prototypicality gradients. This study suggests that learning in the prototype distortion task is not implicit in the sense of resulting automatically from exposure, is affected by the nature of encoding, and should be considered in light of potential learning-at-test effects.

Horses fail to use social learning when solving spatial detour tasks

DEFF Research Database (Denmark)

Rørvang, Maria Vilain; Peerstrup Ahrendt, Line; Christensen, Janne Winther

2015-01-01

Social animals should have plenty of opportunities to learn from conspecifics, but most studies have failed to document social learning in horses. This study investigates whether young Icelandic horses can learn a spatial detour task through observation of a trained demonstrator horse of either...... the same age (Experiments 1 and 2, n = 22) or older (Experiment 3, n = 24). Observer horses were allowed to observe the demonstrator being led three times through the detour route immediately before being given the opportunity to solve the task themselves. Controls were allowed only to observe...

Effect of tDCS on task relevant and irrelevant perceptual learning of complex objects.

Science.gov (United States)

Van Meel, Chayenne; Daniels, Nicky; de Beeck, Hans Op; Baeck, Annelies

2016-01-01

During perceptual learning the visual representations in the brain are altered, but these changes' causal role has not yet been fully characterized. We used transcranial direct current stimulation (tDCS) to investigate the role of higher visual regions in lateral occipital cortex (LO) in perceptual learning with complex objects. We also investigated whether object learning is dependent on the relevance of the objects for the learning task. Participants were trained in two tasks: object recognition using a backward masking paradigm and an orientation judgment task. During both tasks, an object with a red line on top of it were presented in each trial. The crucial difference between both tasks was the relevance of the object: the object was relevant for the object recognition task, but not for the orientation judgment task. During training, half of the participants received anodal tDCS stimulation targeted at the lateral occipital cortex (LO). Afterwards, participants were tested on how well they recognized the trained objects, the irrelevant objects presented during the orientation judgment task and a set of completely new objects. Participants stimulated with tDCS during training showed larger improvements of performance compared to participants in the sham condition. No learning effect was found for the objects presented during the orientation judgment task. To conclude, this study suggests a causal role of LO in relevant object learning, but given the rather low spatial resolution of tDCS, more research on the specificity of this effect is needed. Further, mere exposure is not sufficient to train object recognition in our paradigm.

Task-Oriented Spoken Dialog System for Second-Language Learning

Science.gov (United States)

Kwon, Oh-Woog; Kim, Young-Kil; Lee, Yunkeun

2016-01-01

This paper introduces a Dialog-Based Computer Assisted second-Language Learning (DB-CALL) system using task-oriented dialogue processing technology. The system promotes dialogue with a second-language learner for a specific task, such as purchasing tour tickets, ordering food, passing through immigration, etc. The dialog system plays a role of a…

The relationship between explicit learning and consciousness-raising tasks within a communicative language context

Directory of Open Access Journals (Sweden)

Roscioli, Deise Caldart

2015-01-01

Full Text Available This study aims at investigating whether consciousness-raising tasks, used in a communicative learning environment of EFL, can be considered a valid instrument for eliciting explicit learning in that context. Five participants enrolled in the second level of a language course answered a cycle of tasks that intended to teach the use of comparatives. The materials used in this study consisted of a pre-task, consciousness-raising tasks, an untimed grammaticality judgment test, and a self-report questionnaire. Results showed that the instruments used in this research were of a valid nature for eliciting explicit learning. The findings also provide empirical support regarding the importance of consciousness-raising tasks to assist students’ second language learning in a communicative classroom environment. Despite being a small scale research, this study may contribute to a greater understanding of the SLA processes within a communicative context and highlight the importance of explicit knowledge learning within a meaning focused approach

How well do elderly people cope with uncertainty in a learning task?

Science.gov (United States)

Chasseigne, G; Grau, S; Mullet, E; Cama, V

1999-11-01

The relation between age, task complexity and learning performance in a Multiple Cue Probability Learning task was studied by systematically varying the level of uncertainty present in the task, keeping constant the direction of relationships. Four age groups were constituted: young adults (mean age = 21), middle-aged adults (45), elderly people (69) and very elderly people (81). Five uncertainty levels were considered: predictability = 0.96, 0.80, 0.64, 0.48, and 0.32. All relationships involved were direct ones. A strong effect of uncertainty on 'control', a measure of the subject's consistency with respect to a linear model, was found. This effect was essentially a linear one. To each decrement in predictability of the task corresponded an equal decrement in participants' level of control. This level of decrement was the same, regardless of the age of the participant. It can be concluded that elderly people cope with uncertainty in probability learning tasks as well as young adults.

Age-related changes in learning across early childhood: a new imitation task.

Science.gov (United States)

Dickerson, Kelly; Gerhardstein, Peter; Zack, Elizabeth; Barr, Rachel

2013-11-01

Imitation plays a critical role in social and cognitive development, but the social learning mechanisms contributing to the development of imitation are not well understood. We developed a new imitation task designed to examine social learning mechanisms across the early childhood period. The new task involves assembly of abstract-shaped puzzle pieces in an arbitrary sequence on a magnet board. Additionally, we introduce a new scoring system that extends traditional goal-directed imitation scoring to include measures of both children's success at copying gestures (sliding the puzzle pieces) and goals (connecting the puzzle pieces). In Experiment 1, we demonstrated an age-invariant baseline from 1.5 to 3.5 years of age, accompanied by age-related changes in success at copying goals and gestures from a live demonstrator. In Experiment 2, we applied our new task to learning following a video demonstration. Imitation performance in the video demonstration group lagged behind that of the live demonstration group, showing a protracted video deficit effect. Across both experiments, children were more likely to copy gestures at earlier ages, suggesting mimicry, and only later copy both goals and gestures, suggesting imitation. Taken together, the findings suggest that different social learning strategies may predominate in imitation learning dependent upon the degree of object affordance, task novelty, and task complexity. © 2012 Wiley Periodicals, Inc.

The effects of autonomous difficulty selection on engagement, motivation, and learning in a motion-controlled video game task.

Science.gov (United States)

Leiker, Amber M; Bruzi, Alessandro T; Miller, Matthew W; Nelson, Monica; Wegman, Rebecca; Lohse, Keith R

2016-10-01

This experiment investigated the relationship between motivation, engagement, and learning in a video game task. Previous studies have shown increased autonomy during practice leads to superior retention of motor skills, but it is not clear why this benefit occurs. Some studies suggest this benefit arises from increased motivation during practice; others suggest the benefit arises from better information processing. Sixty novice participants were randomly assigned to a self-controlled group, who chose the progression of difficulty during practice, or to a yoked group, who experienced the same difficulty progression but did not have choice. At the end of practice, participants completed surveys measuring intrinsic motivation and engagement. One week later, participants returned for a series of retention tests at three different difficulty levels. RM-ANCOVA (controlling for pre-test) showed that the self-controlled group had improved retention compared to the yoked group, on average, β=46.78, 95% CI=[2.68, 90.87], p=0.04, but this difference was only statistically significant on the moderate difficulty post-test (p=0.004). The self-controlled group also showed greater intrinsic motivation during practice, t(58)=2.61, p=0.01. However, there was no evidence that individual differences in engagement (p=0.20) or motivation (p=0.87) were associated with learning, which was the relationship this experiment was powered to detect. These data are inconsistent with strictly motivational accounts of how autonomy benefits learning, instead suggesting the benefits of autonomy may be mediated through other mechanisms. For instance, within the information processing framework, the learning benefits may emerge from learners appropriately adjusting difficulty to maintain an appropriate level of challenge (i.e., maintaining the relationship between task demands and cognitive resources). Copyright © 2016 Elsevier B.V. All rights reserved.

Measuring learning potential in people with schizophrenia: A comparison of two tasks.

Science.gov (United States)

Rempfer, Melisa V; McDowd, Joan M; Brown, Catana E

2017-12-01

Learning potential measures utilize dynamic assessment methods to capture performance changes following training on a cognitive task. Learning potential has been explored in schizophrenia research as a predictor of functional outcome and there have been calls for psychometric development in this area. Because the majority of learning potential studies have utilized the Wisconsin Card Sorting Test (WCST), we extended this work using a novel measure, the Rey Osterrieth Complex Figure Test (ROCFT). This study had the following aims: 1) to examine relationships among different learning potential indices for two dynamic assessment tasks, 2) to examine the association between WCST and ROCFT learning potential measures, and 3) to address concurrent validity with a performance-based measure of functioning (Test of Grocery Shopping Skills; TOGSS). Eighty-one adults with schizophrenia or schizoaffective disorder completed WCST and ROCFT learning measures and the TOGSS. Results indicated the various learning potential computational indices are intercorrelated and, similar to other studies, we found support for regression residuals and post-test scores as optimal indices. Further, we found modest relationships between the two learning potential measures and the TOGSS. These findings suggest learning potential includes both general and task-specific constructs but future research is needed to further explore this question. Copyright © 2017 Elsevier B.V. All rights reserved.

Relationships among Individual Task Self-Efficacy, Self-Regulated Learning Strategy Use and Academic Performance in a Computer-Supported Collaborative Learning Environment

Science.gov (United States)

Wilson, Kimberly; Narayan, Anupama

2016-01-01

This study investigates relationships between self-efficacy, self-regulated learning strategy use and academic performance. Participants were 96 undergraduate students working on projects with three subtasks (idea generation task, methodical task and data collection) in a blended learning environment. Task self-efficacy was measured with…

Pretraining Cortical Thickness Predicts Subsequent Perceptual Learning Rate in a Visual Search Task.

Science.gov (United States)

Frank, Sebastian M; Reavis, Eric A; Greenlee, Mark W; Tse, Peter U

2016-03-01

We report that preexisting individual differences in the cortical thickness of brain areas involved in a perceptual learning task predict the subsequent perceptual learning rate. Participants trained in a motion-discrimination task involving visual search for a "V"-shaped target motion trajectory among inverted "V"-shaped distractor trajectories. Motion-sensitive area MT+ (V5) was functionally identified as critical to the task: after 3 weeks of training, activity increased in MT+ during task performance, as measured by functional magnetic resonance imaging. We computed the cortical thickness of MT+ from anatomical magnetic resonance imaging volumes collected before training started, and found that it significantly predicted subsequent perceptual learning rates in the visual search task. Participants with thicker neocortex in MT+ before training learned faster than those with thinner neocortex in that area. A similar association between cortical thickness and training success was also found in posterior parietal cortex (PPC). © The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

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

Science.gov (United States)

Vakil, Eli; Lev-Ran Galon, Carmit

2014-01-01

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

Autonomous Inter-Task Transfer in Reinforcement Learning Domains

Science.gov (United States)

2008-08-01

Mountain Car. However, because the source task uses a car with a motor more than twice as powerful as in the 3D task, the tran- sition function learned in...powerful car motor or changing the surface friction of the hill • s: changing the range of the state variables • si: changing where the car starts...Aamodt and Enric Plaza. Case-based reasoning: Foundational issues, methodological variations, and system approaches, 1994. Mazda Ahmadi, Matthew E

Selective immunotoxic lesions of basal forebrain cholinergic cells: effects on learning and memory in rats.

Science.gov (United States)

Baxter, Mark G; Bucci, David J; Gorman, Linda K; Wiley, Ronald G; Gallagher, Michela

2013-10-01

Male Long-Evans rats were given injections of either 192 IgG-saporin, an apparently selective toxin for basal forebrain cholinergic neurons (LES), or vehicle (CON) into either the medial septum and vertical limb of the diagonal band (MS/VDB) or bilaterally into the nucleus basalis magnocellularis and substantia innominata (nBM/SI). Place discrimination in the Morris water maze assessed spatial learning, and a trial-unique matching-to-place task in the water maze assessed memory for place information over varying delays. MS/VDB-LES and nBM/SI-LES rats were not impaired relative to CON rats in acquisition of the place discrimination, but were mildly impaired relative to CON rats in performance of the memory task even at the shortest delay, suggesting a nonmnemonic deficit. These results contrast with effects of less selective lesions, which have been taken to support a role for basal forebrain cholinergic neurons in learning and memory. 2013 APA, all rights reserved

Automatic motor task selection via a bandit algorithm for a brain-controlled button

Science.gov (United States)

Fruitet, Joan; Carpentier, Alexandra; Munos, Rémi; Clerc, Maureen

2013-02-01

Objective. Brain-computer interfaces (BCIs) based on sensorimotor rhythms use a variety of motor tasks, such as imagining moving the right or left hand, the feet or the tongue. Finding the tasks that yield best performance, specifically to each user, is a time-consuming preliminary phase to a BCI experiment. This study presents a new adaptive procedure to automatically select (online) the most promising motor task for an asynchronous brain-controlled button. Approach. We develop for this purpose an adaptive algorithm UCB-classif based on the stochastic bandit theory and design an EEG experiment to test our method. We compare (offline) the adaptive algorithm to a naïve selection strategy which uses uniformly distributed samples from each task. We also run the adaptive algorithm online to fully validate the approach. Main results. By not wasting time on inefficient tasks, and focusing on the most promising ones, this algorithm results in a faster task selection and a more efficient use of the BCI training session. More precisely, the offline analysis reveals that the use of this algorithm can reduce the time needed to select the most appropriate task by almost half without loss in precision, or alternatively, allow us to investigate twice the number of tasks within a similar time span. Online tests confirm that the method leads to an optimal task selection. Significance. This study is the first one to optimize the task selection phase by an adaptive procedure. By increasing the number of tasks that can be tested in a given time span, the proposed method could contribute to reducing ‘BCI illiteracy’.

Task-selective memory effects for successfully implemented encoding strategies.

Science.gov (United States)

Leshikar, Eric D; Duarte, Audrey; Hertzog, Christopher

2012-01-01

Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies--visual imagery and sentence generation--facilitate memory through the production of different types of mediators (e.g., mental images and sentences). Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator). It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences) for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness) of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study.

Learning stochastic reward distributions in a speeded pointing task.

Science.gov (United States)

Seydell, Anna; McCann, Brian C; Trommershäuser, Julia; Knill, David C

2008-04-23

Recent studies have shown that humans effectively take into account task variance caused by intrinsic motor noise when planning fast hand movements. However, previous evidence suggests that humans have greater difficulty accounting for arbitrary forms of stochasticity in their environment, both in economic decision making and sensorimotor tasks. We hypothesized that humans can learn to optimize movement strategies when environmental randomness can be experienced and thus implicitly learned over several trials, especially if it mimics the kinds of randomness for which subjects might have generative models. We tested the hypothesis using a task in which subjects had to rapidly point at a target region partly covered by three stochastic penalty regions introduced as "defenders." At movement completion, each defender jumped to a new position drawn randomly from fixed probability distributions. Subjects earned points when they hit the target, unblocked by a defender, and lost points otherwise. Results indicate that after approximately 600 trials, subjects approached optimal behavior. We further tested whether subjects simply learned a set of stimulus-contingent motor plans or the statistics of defenders' movements by training subjects with one penalty distribution and then testing them on a new penalty distribution. Subjects immediately changed their strategy to achieve the same average reward as subjects who had trained with the second penalty distribution. These results indicate that subjects learned the parameters of the defenders' jump distributions and used this knowledge to optimally plan their hand movements under conditions involving stochastic rewards and penalties.

Accuracy Feedback Improves Word Learning from Context: Evidence from a Meaning-Generation Task

Science.gov (United States)

Frishkoff, Gwen A.; Collins-Thompson, Kevyn; Hodges, Leslie; Crossley, Scott

2016-01-01

The present study asked whether accuracy feedback on a meaning generation task would lead to improved contextual word learning (CWL). Active generation can facilitate learning by increasing task engagement and memory retrieval, which strengthens new word representations. However, forced generation results in increased errors, which can be…

Integrating the Use of Interdisciplinary Learning Activity Task in Creating Students' Mathematical Knowledge

Science.gov (United States)

Mahanin, Hajah Umisuzimah Haji; Shahrill, Masitah; Tan, Abby; Mahadi, Mar Aswandi

2017-01-01

This study investigated the use of interdisciplinary learning activity task to construct students' knowledge in Mathematics, specifically on the topic of scale drawing application. The learning activity task involved more than one academic discipline, which is Mathematics, English Language, Art, Geography and integrating the Brunei Darussalam…

Measurement of functional task difficulty during motor learning: What level of difficulty corresponds to the optimal challenge point?

Science.gov (United States)

Akizuki, Kazunori; Ohashi, Yukari

2015-10-01

The relationship between task difficulty and learning benefit was examined, as was the measurability of task difficulty. Participants were required to learn a postural control task on an unstable surface at one of four different task difficulty levels. Results from the retention test showed an inverted-U relationship between task difficulty during acquisition and motor learning. The second-highest level of task difficulty was the most effective for motor learning, while learning was delayed at the most and least difficult levels. Additionally, the results indicate that salivary α-amylase and the performance dimension of the National Aeronautics and Space Administration-Task Load Index (NASA-TLX) are useful indices of task difficulty. Our findings suggested that instructors may be able to adjust task difficulty based on salivary α-amylase and the performance dimension of the NASA-TLX to enhance learning. Copyright © 2015 Elsevier B.V. All rights reserved.

Selection as a learning experience: an exploratory study.

Science.gov (United States)

de Visser, Marieke; Laan, Roland F; Engbers, Rik; Cohen-Schotanus, Janke; Fluit, Cornelia

2018-01-01

Research on selection for medical school does not explore selection as a learning experience, despite growing attention for the learning effects of assessment in general. Insight in the learning effects allows us to take advantage of selection as an inclusive part of medical students' learning process to become competent professionals. The aims of this study at Radboud University Medical Center, the Netherlands, were 1) to determine whether students have learning experiences in the selection process, and, if so, what experiences; and 2) to understand what students need in order to utilize the learning effects of the selection process at the start of the formal curriculum. We used focus groups to interview 30 students admitted in 2016 about their learning experiences in the selection process. Thematic analysis was used to explore the outcomes of the interviews and to define relevant themes. In the selection process, students learned about the curriculum, themselves, their relation to others, and the profession they had been selected to enter, although this was not explicitly perceived as learning. Students needed a connection between selection and the curriculum as well as feedback to be able to really use their learning experiences for their further development. Medical school selection qualifies as a learning experience, and students as well as medical schools can take advantage of this. We recommend a careful design of the selection procedure, integrating relevant selection learning experiences into the formal curriculum, providing feedback and explicitly approaching the selection and the formal curriculum as interconnected contributors to students' development.

Learning Task Knowledge from Dialog and Web Access

Directory of Open Access Journals (Sweden)

Vittorio Perera

2015-06-01

Full Text Available We present KnoWDiaL, an approach for Learning and using task-relevant Knowledge from human-robot Dialog and access to the Web. KnoWDiaL assumes that there is an autonomous agent that performs tasks, as requested by humans through speech. The agent needs to “understand” the request, (i.e., to fully ground the task until it can proceed to plan for and execute it. KnoWDiaL contributes such understanding by using and updating a Knowledge Base, by dialoguing with the user, and by accessing the web. We believe that KnoWDiaL, as we present it, can be applied to general autonomous agents. However, we focus on our work with our autonomous collaborative robot, CoBot, which executes service tasks in a building, moving around and transporting objects between locations. Hence, the knowledge acquired and accessed consists of groundings of language to robot actions, and building locations, persons, and objects. KnoWDiaL handles the interpretation of voice commands, is robust regarding speech recognition errors, and is able to learn commands involving referring expressions in an open domain, (i.e., without requiring a lexicon. We present in detail the multiple components of KnoWDiaL, namely a frame-semantic parser, a probabilistic grounding model, a web-based predicate evaluator, a dialog manager, and the weighted predicate-based Knowledge Base. We illustrate the knowledge access and updates from the dialog and Web access, through detailed and complete examples. We further evaluate the correctness of the predicate instances learned into the Knowledge Base, and show the increase in dialog efficiency as a function of the number of interactions. We have extensively and successfully used KnoWDiaL in CoBot dialoguing and accessing the Web, and extract a few corresponding example sequences from captured videos.

Selective effects of cholinergic modulation on task performance during selective attention.

Science.gov (United States)

Furey, Maura L; Pietrini, Pietro; Haxby, James V; Drevets, Wayne C

2008-03-01

The cholinergic neurotransmitter system is critically linked to cognitive functions including attention. The current studies were designed to evaluate the effect of a cholinergic agonist and an antagonist on performance during a selective visual attention task where the inherent salience of attended/unattended stimuli was modulated. Two randomized, placebo-controlled, crossover studies were performed, one (n=9) with the anticholinesterase physostigmine (1.0 mg/h), and the other (n=30) with the anticholinergic scopolamine (0.4 mc/kg). During the task, two double-exposure pictures of faces and houses were presented side by side. Subjects were cued to attend to either the face or the house component of the stimuli, and were instructed to perform a matching task with the two exemplars from the attended category. The cue changed every 4-7 trials to instruct subjects to shift attention from one stimulus component to the other. During placebo in both studies, reaction time (RT) associated with the first trial following a cued shift in attention was longer than RT associated with later trials (pattention to houses condition (pattention to faces. Scopolamine increased RT relative to placebo selectively during trials greater than one (pattention to faces condition (pselective attention (ie trials greater than 1). Moreover, effects of cholinergic manipulation depend on the selective attention condition (ie faces vs houses), which may suggest that cholinergic activity interacts with stimulus salience. The findings are discussed within the context of the role of acetylcholine both in stimulus processing and stimulus salience, and in establishing attention biases through top-down and bottom-up mechanisms of attention.

Concrete and abstract visualizations in history learning tasks

NARCIS (Netherlands)

Prangsma, M.E.; van Boxtel, C.A.M.; Kanselaar, G.; Kirschner, P.A.

2009-01-01

Background: History learning requires that students understand historical phenomena, abstract concepts and the relations between them. Students have problems grasping, using and relating complex historical developments and structures. Aims: A study was conducted to determine the effects of tasks

Feature selection and multi-kernel learning for sparse representation on a manifold

KAUST Repository

Wang, Jim Jing-Yan

2014-03-01

Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao etal. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. © 2013 Elsevier Ltd.

Feature selection and multi-kernel learning for sparse representation on a manifold.

Science.gov (United States)

Wang, Jim Jing-Yan; Bensmail, Halima; Gao, Xin

2014-03-01

Sparse representation has been widely studied as a part-based data representation method and applied in many scientific and engineering fields, such as bioinformatics and medical imaging. It seeks to represent a data sample as a sparse linear combination of some basic items in a dictionary. Gao et al. (2013) recently proposed Laplacian sparse coding by regularizing the sparse codes with an affinity graph. However, due to the noisy features and nonlinear distribution of the data samples, the affinity graph constructed directly from the original feature space is not necessarily a reliable reflection of the intrinsic manifold of the data samples. To overcome this problem, we integrate feature selection and multiple kernel learning into the sparse coding on the manifold. To this end, unified objectives are defined for feature selection, multiple kernel learning, sparse coding, and graph regularization. By optimizing the objective functions iteratively, we develop novel data representation algorithms with feature selection and multiple kernel learning respectively. Experimental results on two challenging tasks, N-linked glycosylation prediction and mammogram retrieval, demonstrate that the proposed algorithms outperform the traditional sparse coding methods. Copyright © 2013 Elsevier Ltd. All rights reserved.

Enhanced motor learning following task-concurrent dual transcranial direct current stimulation.

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Sophia Karok

Full Text Available OBJECTIVE: Transcranial direct current stimulation (tDCS of the primary motor cortex (M1 has beneficial effects on motor performance and motor learning in healthy subjects and is emerging as a promising tool for motor neurorehabilitation. Applying tDCS concurrently with a motor task has recently been found to be more effective than applying stimulation before the motor task. This study extends this finding to examine whether such task-concurrent stimulation further enhances motor learning on a dual M1 montage. METHOD: Twenty healthy, right-handed subjects received anodal tDCS to the right M1, dual tDCS (anodal current over right M1 and cathodal over left M1 and sham tDCS in a repeated-measures design. Stimulation was applied for 10 mins at 1.5 mA during an explicit motor learning task. Response times (RT and accuracy were measured at baseline, during, directly after and 15 mins after stimulation. Motor cortical excitability was recorded from both hemispheres before and after stimulation using single-pulse transcranial magnetic stimulation. RESULTS: Task-concurrent stimulation with a dual M1 montage significantly reduced RTs by 23% as early as with the onset of stimulation (p<0.01 with this effect increasing to 30% at the final measurement. Polarity-specific changes in cortical excitability were observed with MEPs significantly reduced by 12% in the left M1 and increased by 69% in the right M1. CONCLUSION: Performance improvement occurred earliest in the dual M1 condition with a stable and lasting effect. Unilateral anodal stimulation resulted only in trendwise improvement when compared to sham. Therefore, task-concurrent dual M1 stimulation is most suited for obtaining the desired neuromodulatory effects of tDCS in explicit motor learning.

Categorization difficulty modulates the mediated route for response selection in task switching.

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Schneider, Darryl W

2017-12-22

Conflict during response selection in task switching is indicated by the response congruency effect: worse performance for incongruent targets (requiring different responses across tasks) than for congruent targets (requiring the same response). The effect can be explained by dual-task processing in a mediated route for response selection, whereby targets are categorized with respect to both tasks. In the present study, the author tested predictions for the modulation of response congruency effects by categorization difficulty derived from a relative-speed-of-processing hypothesis. Categorization difficulty was manipulated for the relevant and irrelevant task dimensions in a novel spatial task-switching paradigm that involved judging the locations of target dots in a grid, without repetition of dot configurations. Response congruency effects were observed and they varied systematically with categorization difficulty (e.g., being larger when irrelevant categorization was easy than when it was hard). These results are consistent with the relative-speed-of-processing hypothesis and suggest that task-switching models that implement variations of the mediated route for response selection need to address the time course of categorization.

Group social rank is associated with performance on a spatial learning task.

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Langley, Ellis J G; van Horik, Jayden O; Whiteside, Mark A; Madden, Joah R

2018-02-01

Dominant individuals differ from subordinates in their performances on cognitive tasks across a suite of taxa. Previous studies often only consider dyadic relationships, rather than the more ecologically relevant social hierarchies or networks, hence failing to account for how dyadic relationships may be adjusted within larger social groups. We used a novel statistical method: randomized Elo-ratings, to infer the social hierarchy of 18 male pheasants, Phasianus colchicus , while in a captive, mixed-sex group with a linear hierarchy. We assayed individual learning performance of these males on a binary spatial discrimination task to investigate whether inter-individual variation in performance is associated with group social rank. Task performance improved with increasing trial number and was positively related to social rank, with higher ranking males showing greater levels of success. Motivation to participate in the task was not related to social rank or task performance, thus indicating that these rank-related differences are not a consequence of differences in motivation to complete the task. Our results provide important information about how variation in cognitive performance relates to an individual's social rank within a group. Whether the social environment causes differences in learning performance or instead, inherent differences in learning ability predetermine rank remains to be tested.

Using dual-task methodology to dissociate automatic from nonautomatic processes involved in artificial grammar learning.

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Hendricks, Michelle A; Conway, Christopher M; Kellogg, Ronald T

2013-09-01

Previous studies have suggested that both automatic and intentional processes contribute to the learning of grammar and fragment knowledge in artificial grammar learning (AGL) tasks. To explore the relative contribution of automatic and intentional processes to knowledge gained in AGL, we utilized dual-task methodology to dissociate automatic and intentional grammar- and fragment-based knowledge in AGL at both acquisition and at test. Both experiments used a balanced chunk strength grammar to assure an equal proportion of fragment cues (i.e., chunks) in grammatical and nongrammatical test items. In Experiment 1, participants engaged in a working memory dual-task either during acquisition, test, or both acquisition and test. The results showed that participants performing the dual-task during acquisition learned the artificial grammar as well as the single-task group, presumably by relying on automatic learning mechanisms. A working memory dual-task at test resulted in attenuated grammar performance, suggesting a role for intentional processes for the expression of grammatical learning at test. Experiment 2 explored the importance of perceptual cues by changing letters between the acquisition and test phase; unlike Experiment 1, there was no significant learning of grammatical information for participants under dual-task conditions in Experiment 2, suggesting that intentional processing is necessary for successful acquisition and expression of grammar-based knowledge under transfer conditions. In sum, it appears that some aspects of learning in AGL are indeed relatively automatic, although the expression of grammatical information and the learning of grammatical patterns when perceptual similarity is eliminated both appear to require explicit resources. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Task-selective memory effects for successfully implemented encoding strategies.

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Eric D Leshikar

Full Text Available Previous behavioral evidence suggests that instructed strategy use benefits associative memory formation in paired associate tasks. Two such effective encoding strategies--visual imagery and sentence generation--facilitate memory through the production of different types of mediators (e.g., mental images and sentences. Neuroimaging evidence suggests that regions of the brain support memory reflecting the mental operations engaged at the time of study. That work, however, has not taken into account self-reported encoding task success (i.e., whether participants successfully generated a mediator. It is unknown, therefore, whether task-selective memory effects specific to each strategy might be found when encoding strategies are successfully implemented. In this experiment, participants studied pairs of abstract nouns under either visual imagery or sentence generation encoding instructions. At the time of study, participants reported their success at generating a mediator. Outside of the scanner, participants further reported the quality of the generated mediator (e.g., images, sentences for each word pair. We observed task-selective memory effects for visual imagery in the left middle occipital gyrus, the left precuneus, and the lingual gyrus. No such task-selective effects were observed for sentence generation. Intriguingly, activity at the time of study in the left precuneus was modulated by the self-reported quality (vividness of the generated mental images with greater activity for trials given higher ratings of quality. These data suggest that regions of the brain support memory in accord with the encoding operations engaged at the time of study.

Semi-supervised Learning for Phenotyping Tasks.

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Dligach, Dmitriy; Miller, Timothy; Savova, Guergana K

2015-01-01

Supervised learning is the dominant approach to automatic electronic health records-based phenotyping, but it is expensive due to the cost of manual chart review. Semi-supervised learning takes advantage of both scarce labeled and plentiful unlabeled data. In this work, we study a family of semi-supervised learning algorithms based on Expectation Maximization (EM) in the context of several phenotyping tasks. We first experiment with the basic EM algorithm. When the modeling assumptions are violated, basic EM leads to inaccurate parameter estimation. Augmented EM attenuates this shortcoming by introducing a weighting factor that downweights the unlabeled data. Cross-validation does not always lead to the best setting of the weighting factor and other heuristic methods may be preferred. We show that accurate phenotyping models can be trained with only a few hundred labeled (and a large number of unlabeled) examples, potentially providing substantial savings in the amount of the required manual chart review.

Technology-enhanced learning on campus: insights from EUNIS e-Learning Task Force

OpenAIRE

Ferrell, Gill; Alves, Paulo; Bubas, Goran; Engert, Steffi; Epelboin, Yves; Madey, Jan; Palma, José; Piteira, Martinha; Restivo, T.M.; Ribeiro, Ligia; Sidelmann Rossen, Dorte; Soares, Filomena; Uhomoibhi, James

2011-01-01

In 2010 the EUNIS e-Learning Task Force (ELTF) members collaborated on a review of tools and technologies in use across our member institutions. One of the key features of that paper was the use of technology to give off-campus learners, such as distance learners, those undertaking field studies and learners in the workplace a richly supported learning experience. Building on the success of that collaboration, the ELTF members have turned their attention this year to the use of technology on ...

The attention habit: how reward learning shapes attentional selection.

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Anderson, Brian A

2016-04-01

There is growing consensus that reward plays an important role in the control of attention. Until recently, reward was thought to influence attention indirectly by modulating task-specific motivation and its effects on voluntary control over selection. Such an account was consistent with the goal-directed (endogenous) versus stimulus-driven (exogenous) framework that had long dominated the field of attention research. Now, a different perspective is emerging. Demonstrations that previously reward-associated stimuli can automatically capture attention even when physically inconspicuous and task-irrelevant challenge previously held assumptions about attentional control. The idea that attentional selection can be value driven, reflecting a distinct and previously unrecognized control mechanism, has gained traction. Since these early demonstrations, the influence of reward learning on attention has rapidly become an area of intense investigation, sparking many new insights. The result is an emerging picture of how the reward system of the brain automatically biases information processing. Here, I review the progress that has been made in this area, synthesizing a wealth of recent evidence to provide an integrated, up-to-date account of value-driven attention and some of its broader implications. © 2015 New York Academy of Sciences.

Task-specificity of unilateral anodal and dual-M1 tDCS effects on motor learning.

Science.gov (United States)

Karok, Sophia; Fletcher, David; Witney, Alice G

2017-01-08

Task-specific effects of transcranial direct current stimulation (tDCS) on motor learning were investigated in 30 healthy participants. In a sham-controlled, mixed design, participants trained on 3 different motor tasks (Purdue Pegboard Test, Visuomotor Grip Force Tracking Task and Visuomotor Wrist Rotation Speed Control Task) over 3 consecutive days while receiving either unilateral anodal over the right primary motor cortex (M1), dual-M1 or sham stimulation. Retention sessions were administered 7 and 28 days after the end of training. In the Purdue Pegboard Test, both anodal and dual-M1 stimulation reduced average completion time approximately equally, an improvement driven by online learning effects and maintained for about 1 week. The Visuomotor Grip Force Tracking Task and the Visuomotor Wrist Rotation Speed Control Task were associated with an advantage of dual-M1 tDCS in consolidation processes both between training sessions and when testing at long-term retention; both were maintained for at least 1 month. This study demonstrates that M1-tDCS enhances and sustains motor learning with different electrode montages. Stimulation-induced effects emerged at different learning phases across the tasks, which strongly suggests that the influence of tDCS on motor learning is dynamic with respect to the functional recruitment of the distributed motor system at the time of stimulation. Divergent findings regarding M1-tDCS effects on motor learning may partially be ascribed to task-specific consequences and the effects of offline consolidation. Copyright © 2016 Elsevier Ltd. All rights reserved.

Multi-task transfer learning deep convolutional neural network: application to computer-aided diagnosis of breast cancer on mammograms

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Samala, Ravi K.; Chan, Heang-Ping; Hadjiiski, Lubomir M.; Helvie, Mark A.; Cha, Kenny H.; Richter, Caleb D.

2017-12-01

Transfer learning in deep convolutional neural networks (DCNNs) is an important step in its application to medical imaging tasks. We propose a multi-task transfer learning DCNN with the aim of translating the ‘knowledge’ learned from non-medical images to medical diagnostic tasks through supervised training and increasing the generalization capabilities of DCNNs by simultaneously learning auxiliary tasks. We studied this approach in an important application: classification of malignant and benign breast masses. With Institutional Review Board (IRB) approval, digitized screen-film mammograms (SFMs) and digital mammograms (DMs) were collected from our patient files and additional SFMs were obtained from the Digital Database for Screening Mammography. The data set consisted of 2242 views with 2454 masses (1057 malignant, 1397 benign). In single-task transfer learning, the DCNN was trained and tested on SFMs. In multi-task transfer learning, SFMs and DMs were used to train the DCNN, which was then tested on SFMs. N-fold cross-validation with the training set was used for training and parameter optimization. On the independent test set, the multi-task transfer learning DCNN was found to have significantly (p  =  0.007) higher performance compared to the single-task transfer learning DCNN. This study demonstrates that multi-task transfer learning may be an effective approach for training DCNN in medical imaging applications when training samples from a single modality are limited.

Investigating Language Learning Activity Using a CALL Task in the Self-access Centre

Directory of Open Access Journals (Sweden)

Carlos Montoro

2011-09-01

Full Text Available This article describes a small study of the language learning activity of individual learners using a CALL task in a self-access environment. The research focuses on the nature of the language learning activity, the most salient elements that make up its structure and major disturbances observed between and within some of those elements. It is set in the context of computer-assisted language learning (CALL and activity theory. A CALL task designed by the authors was made available online to be used as a research and learning tool. Empirical data was collected from two participants using ethnographic tools, such as participant observation and stimulated recall sessions. The analysis focuses on disturbances mainly involving the subject (i.e., the learner, mediating artefacts (e.g., the CALL task, the community (e.g., management and other self-access centre users and the object of the activity (i.e., learning English. It is recommended that future studies should look deeper into contradictions in the learning activity from a cultural-historical perspective.

Expectancy-value theory in persistence of learning effects in schizophrenia: role of task value and perceived competency.

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Choi, Jimmy; Fiszdon, Joanna M; Medalia, Alice

2010-09-01

Expectancy-value theory, a widely accepted model of motivation, posits that expectations of success on a learning task and the individual value placed on the task are central determinants of motivation to learn. This is supported by research in healthy controls suggesting that beliefs of self-and-content mastery can be so influential they can predict the degree of improvement on challenging cognitive tasks even more so than general cognitive ability. We examined components of expectancy-value theory (perceived competency and task value), along with baseline arithmetic performance and neuropsychological performance, as possible predictors of learning outcome in a sample of 70 outpatients with schizophrenia randomized to 1 of 2 different arithmetic learning conditions and followed up after 3 months. Results indicated that as with nonpsychiatric samples, perceived self-competency for the learning task was significantly related to perceptions of task value attributed to the learning task. Baseline expectations of success predicted persistence of learning on the task at 3-month follow-up, even after accounting for variance attributable to different arithmetic instruction, baseline arithmetic ability, attention, and self-reports of task interest and task value. We also found that expectation of success is a malleable construct, with posttraining improvements persisting at follow-up. These findings support the notion that expectancy-value theory is operative in schizophrenia. Thus, similar to the nonpsychiatric population, treatment benefits may be enhanced and better maintained if remediation programs also focus on perceptions of self-competency for the training tasks. Treatment issues related to instilling self-efficacy in cognitive recovery programs are discussed.

Elementary school students’ strategic learning and quality of strategy use: Does task type matter?

NARCIS (Netherlands)

Malmberg, Jonna; Järvelä, Sanna; Kirschner, Paul A.

2018-01-01

This study investigated what types of learning patterns and strategies elementary school students use to carry out ill- and- well-structured tasks. Specifically, it was investigated which and when learning patterns actually emerge with respect to students’ task solutions. The present study uses

Cortical ensemble activity increasingly predicts behaviour outcomes during learning of a motor task

Science.gov (United States)

Laubach, Mark; Wessberg, Johan; Nicolelis, Miguel A. L.

2000-06-01

When an animal learns to make movements in response to different stimuli, changes in activity in the motor cortex seem to accompany and underlie this learning. The precise nature of modifications in cortical motor areas during the initial stages of motor learning, however, is largely unknown. Here we address this issue by chronically recording from neuronal ensembles located in the rat motor cortex, throughout the period required for rats to learn a reaction-time task. Motor learning was demonstrated by a decrease in the variance of the rats' reaction times and an increase in the time the animals were able to wait for a trigger stimulus. These behavioural changes were correlated with a significant increase in our ability to predict the correct or incorrect outcome of single trials based on three measures of neuronal ensemble activity: average firing rate, temporal patterns of firing, and correlated firing. This increase in prediction indicates that an association between sensory cues and movement emerged in the motor cortex as the task was learned. Such modifications in cortical ensemble activity may be critical for the initial learning of motor tasks.

Feature Selection with Conjunctions of Decision Stumps and Learning from Microarray Data.

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Shah, M; Marchand, M; Corbeil, J

2012-01-01

One of the objectives of designing feature selection learning algorithms is to obtain classifiers that depend on a small number of attributes and have verifiable future performance guarantees. There are few, if any, approaches that successfully address the two goals simultaneously. To the best of our knowledge, such algorithms that give theoretical bounds on the future performance have not been proposed so far in the context of the classification of gene expression data. In this work, we investigate the premise of learning a conjunction (or disjunction) of decision stumps in Occam's Razor, Sample Compression, and PAC-Bayes learning settings for identifying a small subset of attributes that can be used to perform reliable classification tasks. We apply the proposed approaches for gene identification from DNA microarray data and compare our results to those of the well-known successful approaches proposed for the task. We show that our algorithm not only finds hypotheses with a much smaller number of genes while giving competitive classification accuracy but also having tight risk guarantees on future performance, unlike other approaches. The proposed approaches are general and extensible in terms of both designing novel algorithms and application to other domains.

Lexical selection in the semantically blocked cyclic naming task: The role of cognitive control and learning

Directory of Open Access Journals (Sweden)

Jason E. Crowther

2014-01-01

Full Text Available Studies of semantic interference in language production have provided evidence for a role of cognitive control mechanisms in regulating the activation of semantic competitors during naming. The present study investigated the relationship between individual differences in cognitive control abilities, for both younger and older adults, and the degree of semantic interference in a blocked cyclic naming task. We predicted that individuals with lower working memory capacity (as measured by word span, lesser ability to inhibit distracting responses (as measured by Stroop interference, and a lesser ability to resolve proactive interference (as measured by a recent negatives task would show a greater increase in semantic interference in naming, with effects being larger for older adults. Instead, measures of cognitive control were found to relate to specific indices of semantic interference in the naming task, rather than overall degree of semantic interference, and few interactions with age were found, with younger and older adults performing similarly. The increase in naming latencies across naming trials within a cycle were negatively correlated with word span for both related and unrelated conditions, suggesting a strategy of narrowing response alternatives based upon memory for the set of item names. Evidence for a role of inhibition in response selection was obtained, as Stroop interference correlated positively with the change in naming latencies across cycles for the related, but not unrelated, condition. In contrast, recent negatives interference correlated negatively with the change in naming latencies across unrelated cycles, suggesting that individual differences in this tap the degree of strengthening of links in a lexical network based upon prior exposure. Results are discussed in terms of current models of lexical selection and consequences for word retrieval in more naturalistic production.

Task Characteristics, Managerial Socialization, and Media Selection.

Science.gov (United States)

Donabedian, Bairj; McKinnon, Sharon M.; Bruns, William J., Jr.

1998-01-01

Questions why managers choose one communication medium in preference to another. Proposes a role for social factors in media selection. Finds, employing a large field-collected sample, strong support for Information Richness Theory, a rational-choice model connecting managers' media choice to task characteristics like variety and analyzability.…

Sonification and haptic feedback in addition to visual feedback enhances complex motor task learning.

Science.gov (United States)

Sigrist, Roland; Rauter, Georg; Marchal-Crespo, Laura; Riener, Robert; Wolf, Peter

2015-03-01

Concurrent augmented feedback has been shown to be less effective for learning simple motor tasks than for complex tasks. However, as mostly artificial tasks have been investigated, transfer of results to tasks in sports and rehabilitation remains unknown. Therefore, in this study, the effect of different concurrent feedback was evaluated in trunk-arm rowing. It was then investigated whether multimodal audiovisual and visuohaptic feedback are more effective for learning than visual feedback only. Naïve subjects (N = 24) trained in three groups on a highly realistic virtual reality-based rowing simulator. In the visual feedback group, the subject's oar was superimposed to the target oar, which continuously became more transparent when the deviation between the oars decreased. Moreover, a trace of the subject's trajectory emerged if deviations exceeded a threshold. The audiovisual feedback group trained with oar movement sonification in addition to visual feedback to facilitate learning of the velocity profile. In the visuohaptic group, the oar movement was inhibited by path deviation-dependent braking forces to enhance learning of spatial aspects. All groups significantly decreased the spatial error (tendency in visual group) and velocity error from baseline to the retention tests. Audiovisual feedback fostered learning of the velocity profile significantly more than visuohaptic feedback. The study revealed that well-designed concurrent feedback fosters complex task learning, especially if the advantages of different modalities are exploited. Further studies should analyze the impact of within-feedback design parameters and the transferability of the results to other tasks in sports and rehabilitation.

Heuristic Task Analysis on E-Learning Course Development: A Formative Research Study

Science.gov (United States)

Lee, Ji-Yeon; Reigeluth, Charles M.

2009-01-01

Utilizing heuristic task analysis (HTA), a method developed for eliciting, analyzing, and representing expertise in complex cognitive tasks, a formative research study was conducted on the task of e-learning course development to further improve the HTA process. Three instructional designers from three different post-secondary institutions in the…

Dreaming of a Learning Task is Associated with Enhanced Sleep-Dependent Memory Consolidation

Science.gov (United States)

Wamsley, Erin J.; Tucker, Matthew; Payne, Jessica D.; Benavides, Joseph; Stickgold, Robert

2010-01-01

Summary It is now well established that post-learning sleep is beneficial for human memory performance [1–5]. Meanwhile, human and animal studies demonstrate that learning-related neural activity is re-expressed during post-training non-rapid eye movement sleep (NREM) [6–9]. NREM sleep processes appear to be particularly beneficial for hippocampus-dependent forms of memory [1–3, 10]. These observations suggest that learning triggers the reactivation and reorganization of memory traces during sleep, a systems-level process that in turn enhances behavioral performance. Here, we hypothesized that dreaming about a learning experience during NREM sleep would be associated with improved performance on a hippocampus-dependent spatial memory task. Subjects (n=99) were trained on a virtual navigation task, and then retested on the same task 5 hours after initial training. Improved performance at retest was strongly associated with task-related dream imagery during an intervening afternoon nap. Task-related thoughts during wakefulness, in contrast, did not predict improved performance. These observations suggest that sleep-dependent memory consolidation in humans is facilitated by the offline reactivation of recently formed memories, and furthermore, that dream experiences reflect this memory processing. That similar effects were not seen during wakefulness suggests that these mnemonic processes are specific to the sleep state. PMID:20417102

Optimizing learning of a locomotor task: amplifying errors as needed.

Science.gov (United States)

Marchal-Crespo, Laura; López-Olóriz, Jorge; Jaeger, Lukas; Riener, Robert

2014-01-01

Research on motor learning has emphasized that errors drive motor adaptation. Thereby, several researchers have proposed robotic training strategies that amplify movement errors rather than decrease them. In this study, the effect of different robotic training strategies that amplify errors on learning a complex locomotor task was investigated. The experiment was conducted with a one degree-of freedom robotic stepper (MARCOS). Subjects were requested to actively coordinate their legs in a desired gait-like pattern in order to track a Lissajous figure presented on a visual display. Learning with three different training strategies was evaluated: (i) No perturbation: the robot follows the subjects' movement without applying any perturbation, (ii) Error amplification: existing errors were amplified with repulsive forces proportional to errors, (iii) Noise disturbance: errors were evoked with a randomly-varying force disturbance. Results showed that training without perturbations was especially suitable for a subset of initially less-skilled subjects, while error amplification seemed to benefit more skilled subjects. Training with error amplification, however, limited transfer of learning. Random disturbing forces benefited learning and promoted transfer in all subjects, probably because it increased attention. These results suggest that learning a locomotor task can be optimized when errors are randomly evoked or amplified based on subjects' initial skill level.

Better and Faster: Knowledge Transfer from Multiple Self-supervised Learning Tasks via Graph Distillation for Video Classification

OpenAIRE

Zhang, Chenrui; Peng, Yuxin

2018-01-01

Video representation learning is a vital problem for classification task. Recently, a promising unsupervised paradigm termed self-supervised learning has emerged, which explores inherent supervisory signals implied in massive data for feature learning via solving auxiliary tasks. However, existing methods in this regard suffer from two limitations when extended to video classification. First, they focus only on a single task, whereas ignoring complementarity among different task-specific feat...

Monetary reward modulates task-irrelevant perceptual learning for invisible stimuli.

Science.gov (United States)

Pascucci, David; Mastropasqua, Tommaso; Turatto, Massimo

2015-01-01

Task Irrelevant Perceptual Learning (TIPL) shows that the brain's discriminative capacity can improve also for invisible and unattended visual stimuli. It has been hypothesized that this form of "unconscious" neural plasticity is mediated by an endogenous reward mechanism triggered by the correct task performance. Although this result has challenged the mandatory role of attention in perceptual learning, no direct evidence exists of the hypothesized link between target recognition, reward and TIPL. Here, we manipulated the reward value associated with a target to demonstrate the involvement of reinforcement mechanisms in sensory plasticity for invisible inputs. Participants were trained in a central task associated with either high or low monetary incentives, provided only at the end of the experiment, while subliminal stimuli were presented peripherally. Our results showed that high incentive-value targets induced a greater degree of perceptual improvement for the subliminal stimuli, supporting the role of reinforcement mechanisms in TIPL.

With task experience students learn to ignore the content, not just the location of irrelevant information

NARCIS (Netherlands)

Rop, Gertjan; Verkoeijen, Peter P J L; van Gog, Tamara

2017-01-01

Presentation of irrelevant additional information hampers learning. However, using a word-learning task, recent research demonstrated that an initial negative effect of mismatching pictures on learning no longer occurred once learners gained task experience. It is unclear, however, whether learners

Multi-level gene/MiRNA feature selection using deep belief nets and active learning.

Science.gov (United States)

Ibrahim, Rania; Yousri, Noha A; Ismail, Mohamed A; El-Makky, Nagwa M

2014-01-01

Selecting the most discriminative genes/miRNAs has been raised as an important task in bioinformatics to enhance disease classifiers and to mitigate the dimensionality curse problem. Original feature selection methods choose genes/miRNAs based on their individual features regardless of how they perform together. Considering group features instead of individual ones provides a better view for selecting the most informative genes/miRNAs. Recently, deep learning has proven its ability in representing the data in multiple levels of abstraction, allowing for better discrimination between different classes. However, the idea of using deep learning for feature selection is not widely used in the bioinformatics field yet. In this paper, a novel multi-level feature selection approach named MLFS is proposed for selecting genes/miRNAs based on expression profiles. The approach is based on both deep and active learning. Moreover, an extension to use the technique for miRNAs is presented by considering the biological relation between miRNAs and genes. Experimental results show that the approach was able to outperform classical feature selection methods in hepatocellular carcinoma (HCC) by 9%, lung cancer by 6% and breast cancer by around 10% in F1-measure. Results also show the enhancement in F1-measure of our approach over recently related work in [1] and [2].

Self-Control of Task Difficulty During Early Practice Promotes Motor Skill Learning.

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Andrieux, Mathieu; Boutin, Arnaud; Thon, Bernard

2016-01-01

This study was designed to determine whether the effect of self-control of task difficulty on motor learning is a function of the period of self-control administration. In a complex anticipation-coincidence task that required participants to intercept 3 targets with a virtual racquet, the task difficulty was either self-controlled or imposed to the participants in the two phases of the acquisition session. First, the results confirmed the beneficial effects of self-control over fully prescribed conditions. Second, the authors also demonstrated that a partial self-control of task difficulty better promotes learning than does a complete self-controlled procedure. Overall, the results revealed that these benefits are increased when this choice is allowed during early practice. The findings are discussed in terms of theoretical and applied perspectives.

Social learning of an associative foraging task in zebrafish

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Zala, Sarah M.; Määttänen, Ilmari

2013-05-01

The zebrafish ( Danio rerio) is increasingly becoming an important model species for studies on the genetic and neural mechanisms controlling behaviour and cognition. Here, we utilized a conditioned place preference (CPP) paradigm to study social learning in zebrafish. We tested whether social interactions with conditioned demonstrators enhance the ability of focal naïve individuals to learn an associative foraging task. We found that the presence of conditioned demonstrators improved focal fish foraging behaviour through the process of social transmission, whereas the presence of inexperienced demonstrators interfered with the learning of the control focal fish. Our results indicate that zebrafish use social learning for finding food and that this CPP paradigm is an efficient assay to study social learning and memory in zebrafish.

Darwinian algorithms and the Wason selection task: a factorial analysis of social contract selection task problems.

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Platt, R D; Griggs, R A

1993-08-01

In four experiments with 760 subjects, the present study examined Cosmides' Darwinian algorithm theory of reasoning: specifically, its explanation of facilitation on the Wason selection task. The first experiment replicated Cosmides' finding of facilitation for social contract versions of the selection task, using both her multiple-problem format and a single-problem format. Experiment 2 examined performance on Cosmides' three main social contract problems while manipulating the perspective of the subject and the presence and absence of cost-benefit information. The presence of cost-benefit information improved performance in two of the three problems while the perspective manipulation had no effect. In Experiment 3, the cost-benefit effect was replicated; and performance on one of the three problems was enhanced by the presence of explicit negatives on the NOT-P and NOT-Q cards. Experiment 4 examined the role of the deontic term "must" in the facilitation observed for two of the social contract problems. The presence of "must" led to a significant improvement in performance. The results of these experiments are strongly supportive of social contract theory in that cost-benefit information is necessary for substantial facilitation to be observed in Cosmides' problems. These findings also suggest the presence of other cues that can help guide subjects to a deontic social contract interpretation when the social contract nature of the problem is not clear.

Contingency learning is not affected by conflict experience: Evidence from a task conflict-free, item-specific Stroop paradigm.

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Levin, Yulia; Tzelgov, Joseph

2016-02-01

A contingency learning account of the item-specific proportion congruent effect has been described as an associative stimulus-response learning process that has nothing to do with controlling the Stroop conflict. As supportive evidence, contingency learning has been demonstrated with response conflict-free stimuli, such as neutral words. However, what gives rise to response conflict and to Stroop interference in general is task conflict. The present study investigated whether task conflict can constitute a trigger or, alternatively, a booster to the contingency learning process. This was done by employing a "task conflict-free" condition (i.e., geometric shapes) and comparing it with a "task conflict" condition (i.e., neutral words). The results showed a significant contingency learning effect in both conditions, refuting the possibility that contingency learning is triggered by the presence of a task conflict. Contingency learning was also not enhanced by the task conflict experience, indicating its complete insensitivity to Stroop conflict(s). Thus, the results showed no evidence that performance optimization as a result of contingency learning is greater under conflict, implying that contingency learning is not recruited to assist the control system to overcome conflict. Copyright © 2015 Elsevier B.V. All rights reserved.

Stress before extinction learning enhances and generalizes extinction memory in a predictive learning task.

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Meir Drexler, Shira; Hamacher-Dang, Tanja C; Wolf, Oliver T

2017-05-01

In extinction learning, the individual learns that a previously acquired association (e.g. between a threat and its predictor) is no longer valid. This learning is the principle underlying many cognitive-behavioral psychotherapeutic treatments, e.g. 'exposure therapy'. However, extinction is often highly-context dependent, leading to renewal (relapse of extinguished conditioned response following context change). We have previously shown that post-extinction stress leads to a more context-dependent extinction memory in a predictive learning task. Yet as stress prior to learning can impair the integration of contextual cues, here we aim to create a more generalized extinction memory by inducing stress prior to extinction. Forty-nine men and women learned the associations between stimuli and outcomes in a predictive learning task (day 1), extinguished them shortly after an exposure to a stress/control condition (day 2), and were tested for renewal (day 3). No group differences were seen in acquisition and extinction learning, and a renewal effect was present in both groups. However, the groups differed in the strength and context-dependency of the extinction memory. Compared to the control group, the stress group showed an overall reduced recovery of responding to the extinguished stimuli, in particular in the acquisition context. These results, together with our previous findings, demonstrate that the effects of stress exposure on extinction memory depend on its timing. While post-extinction stress makes the memory more context-bound, pre-extinction stress strengthens its consolidation for the acquisition context as well, making it potentially more resistant to relapse. These results have implications for the use of glucocorticoids as extinction-enhancers in exposure therapy. Copyright © 2017 Elsevier Inc. All rights reserved.

Paired-Associate and Feedback-Based Weather Prediction Tasks Support Multiple Category Learning Systems.

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Li, Kaiyun; Fu, Qiufang; Sun, Xunwei; Zhou, Xiaoyan; Fu, Xiaolan

2016-01-01

It remains unclear whether probabilistic category learning in the feedback-based weather prediction task (FB-WPT) can be mediated by a non-declarative or procedural learning system. To address this issue, we compared the effects of training time and verbal working memory, which influence the declarative learning system but not the non-declarative learning system, in the FB and paired-associate (PA) WPTs, as the PA task recruits a declarative learning system. The results of Experiment 1 showed that the optimal accuracy in the PA condition was significantly decreased when the training time was reduced from 7 to 3 s, but this did not occur in the FB condition, although shortened training time impaired the acquisition of explicit knowledge in both conditions. The results of Experiment 2 showed that the concurrent working memory task impaired the optimal accuracy and the acquisition of explicit knowledge in the PA condition but did not influence the optimal accuracy or the acquisition of self-insight knowledge in the FB condition. The apparent dissociation results between the FB and PA conditions suggested that a non-declarative or procedural learning system is involved in the FB-WPT and provided new evidence for the multiple-systems theory of human category learning.

Didactical design based on sharing and jumping tasks for senior high school chemistry learning

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Fatimah, I.; Hendayana, S.; Supriatna, A.

2018-05-01

The purpose of this research is to develop the didactical design of senior high school chemistry learning based on sharing and jumping tasks in shift equilibrium chemistry. Sharing tasks used to facilitate students slow learners with help by other students of fast learners so they engage in learning. While jumping tasks used to challenge fast learners students so they didn’t feel bored in learning. In developing the didactic design, teacher activity is not only to focus on students and learning materials but also on the relationship between students and learning materials. The results of the analysis teaching plan of shift equilibrium chemistry in attached Senior High School to Indonesia University of Education showed that the learning activities more focus on how the teacher teaches instead of how the process of students’ learning. The use of research method is didactical design research (DDR). Didactical design consisted of three steps i.e. (a) analysing didactical condition before learning, (b) analyzing metapedadidactical, and (c) analyzing retrospective. Data were collected by test, observations, interviews, documentation and recordings (audio and video).The result showed that the didactical design on shift equilibrium chemistry was valid.

Valence of Facial Cues Influences Sheep Learning in a Visual Discrimination Task

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Lucille G. A. Bellegarde

2017-11-01

Full Text Available Sheep are one of the most studied farm species in terms of their ability to process information from faces, but little is known about their face-based emotion recognition abilities. We investigated (a whether sheep could use images of sheep faces taken in situation of varying valence as cues in a simultaneous discrimination task and (b whether the valence of the situation affects their learning performance. To accomplish this, we photographed faces of sheep in three situations inducing emotional states of neutral (ruminating in the home pen or negative valence (social isolation or aggressive interaction. Sheep (n = 35 first had to learn a discrimination task with colored cards. Animals that reached the learning criterion (n = 16 were then presented with pairs of images of the face of a single individual taken in the neutral situation and in one of the negative situations. Finally, sheep had to generalize what they had learned to new pairs of images of faces taken in the same situation, but of a different conspecific. All sheep that learned the discrimination task with colored cards reached the learning criterion with images of faces. Sheep that had to associate a negative image with a food reward learned faster than sheep that had to associate a neutral image with a reward. With the exception of sheep from the aggression-rewarded group, sheep generalized this discrimination to images of faces of different individuals. Our results suggest that sheep can perceive the emotional valence displayed on faces of conspecifics and that this valence affects learning processes.

Reinforcement learning modulates the stability of cognitive control settings for object selection

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Anthony William Sali

2013-12-01

Full Text Available Cognitive flexibility reflects both a trait that reliably differs between individuals and a state that can fluctuate moment-to-moment. Whether individuals can undergo persistent changes in cognitive flexibility as a result of reward learning is less understood. Here, we investigated whether reinforcing a periodic shift in an object selection strategy can make an individual more prone to switch strategies in a subsequent unrelated task. Participants completed two different choice tasks in which they selected one of four objects in an attempt to obtain a hidden reward on each trial. During a training phase, objects were defined by color. Participants received either consistent reward contingencies in which one color was more often rewarded, or contingencies in which the color that was more often rewarded changed periodically and without warning. Following the training phase, all participants completed a test phase in which reward contingencies were defined by spatial location and the location that was more often rewarded remained constant across the entire task. Those participants who received inconsistent contingencies during training continued to make more variable selections during the test phase in comparison to those who received the consistent training. Furthermore, a difference in the likelihood to switch selections on a trial-by-trial basis emerged between training groups: participants who received consistent contingencies during training were less likely to switch object selections following an unrewarded trial and more likely to repeat a selection following reward. Our findings provide evidence that the extent to which priority shifting is reinforced modulates the stability of cognitive control settings in a persistent manner, such that individuals become generally more or less prone to shifting priorities in the future.

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

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Romero, Margarida; Usart, Mireia

2013-01-01

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

Monetary reward modulates task-irrelevant perceptual learning for invisible stimuli.

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David Pascucci

Full Text Available Task Irrelevant Perceptual Learning (TIPL shows that the brain's discriminative capacity can improve also for invisible and unattended visual stimuli. It has been hypothesized that this form of "unconscious" neural plasticity is mediated by an endogenous reward mechanism triggered by the correct task performance. Although this result has challenged the mandatory role of attention in perceptual learning, no direct evidence exists of the hypothesized link between target recognition, reward and TIPL. Here, we manipulated the reward value associated with a target to demonstrate the involvement of reinforcement mechanisms in sensory plasticity for invisible inputs. Participants were trained in a central task associated with either high or low monetary incentives, provided only at the end of the experiment, while subliminal stimuli were presented peripherally. Our results showed that high incentive-value targets induced a greater degree of perceptual improvement for the subliminal stimuli, supporting the role of reinforcement mechanisms in TIPL.

E-learning task analysis making temporal evolution graphics on symptoms of waves and the ability to solve problems

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Rosdiana, L.; Widodo, W.; Nurita, T.; Fauziah, A. N. M.

2018-04-01

This study aimed to describe the ability of pre-service teachers to create graphs, solve the problem of spatial and temporal evolution on the symptoms of vibrations and waves. The learning was conducted using e-learning method. The research design is a quasi-experimental design with one-shot case study. The e-learning contained learning materials and tasks involving answering tasks, making questions, solving their own questions, and making graphs. The participants of the study was 28 students of Science Department, Universitas Negeri Surabaya. The results obtained by using the e-learning were that the students’ ability increase gradually from task 1 to task 3 (the tasks consisted of three tasks). Additionally, based on the questionnaire with 28 respondents, it showed that 24 respondents stated that making graphs via e-learning were still difficult. Four respondents said that it was easy to make graphs via e-learning. Nine respondents stated that the e-learning did not help them in making graphs and 19 respondents stated that the e-learning help in creating graphs. The conclusion of the study is that the students was able to make graphs on paper sheet, but they got difficulty to make the graphs in e-learning (the virtual form).

Selection of executors for realization of individual tasks of the project

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Asanov Askhat

2017-01-01

Full Text Available This article deals with the task of selection of executors for the realization of individual tasks of a new project. A short review of approaches to the estimation of personnel based on intellectual methods is provided. Two approaches to the task solution of executors’ selection are reviewed. The first approach allows considering estimation of competence of potential executors and data about projects that have already been realized. These data and requirements to the tasks of new projects are presented with the help of cognitive map with correspondent vertices. In the article, a methodologic example of the suggested approach use is introduced. The second approach suggests the use of Hopfield’s neural network. Neural networks allow using the already available experience of project activities during realization of new projects.

The Impact of Learning Task Design on Students' Situational Interest in Physical Education

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Roure, Cédric; Pasco, Denis

2018-01-01

Purpose: Based on the framework of interest, studies have shown that teachers can enhance students' situational interest (SI) by manipulating the components of learning tasks. The purpose of this study was to examine the impact of learning task design on students' SI in physical education (PE). Method: The participants were 167 secondary school…

Optimizing the number of steps in learning tasks for complex skills.

NARCIS (Netherlands)

Nadolski, Rob; Kirschner, Paul A.; Van Merriënboer, Jeroen

2007-01-01

Background. Carrying out whole tasks is often too difficult for novice learners attempting to acquire complex skills. The common solution is to split up the tasks into a number of smaller steps. The number of steps must be optimised for efficient and effective learning. Aim. The aim of the study is

Performance of children with developmental dyslexia on high and low topological entropy artificial grammar learning task.

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Katan, Pesia; Kahta, Shani; Sasson, Ayelet; Schiff, Rachel

2017-07-01

Graph complexity as measured by topological entropy has been previously shown to affect performance on artificial grammar learning tasks among typically developing children. The aim of this study was to examine the effect of graph complexity on implicit sequential learning among children with developmental dyslexia. Our goal was to determine whether children's performance depends on the complexity level of the grammar system learned. We conducted two artificial grammar learning experiments that compared performance of children with developmental dyslexia with that of age- and reading level-matched controls. Experiment 1 was a high topological entropy artificial grammar learning task that aimed to establish implicit learning phenomena in children with developmental dyslexia using previously published experimental conditions. Experiment 2 is a lower topological entropy variant of that task. Results indicated that given a high topological entropy grammar system, children with developmental dyslexia who were similar to the reading age-matched control group had substantial difficulty in performing the task as compared to typically developing children, who exhibited intact implicit learning of the grammar. On the other hand, when tested on a lower topological entropy grammar system, all groups performed above chance level, indicating that children with developmental dyslexia were able to identify rules from a given grammar system. The results reinforced the significance of graph complexity when experimenting with artificial grammar learning tasks, particularly with dyslexic participants.

Combining Conflicting Environmental and Task Requirements in Evolutionary Robotics

NARCIS (Netherlands)

Haasdijk, E.W.

2015-01-01

The MONEE framework endows collective adaptive robotic systems with the ability to combine environment- and task-driven selection pressures: it enables distributed online algorithms for learning behaviours that ensure both survival and accomplishment of user-defined tasks. This paper explores the

Feature selection and multi-kernel learning for adaptive graph regularized nonnegative matrix factorization

KAUST Repository

Wang, Jim Jing-Yan

2014-09-20

Nonnegative matrix factorization (NMF), a popular part-based representation technique, does not capture the intrinsic local geometric structure of the data space. Graph regularized NMF (GNMF) was recently proposed to avoid this limitation by regularizing NMF with a nearest neighbor graph constructed from the input data set. However, GNMF has two main bottlenecks. First, using the original feature space directly to construct the graph is not necessarily optimal because of the noisy and irrelevant features and nonlinear distributions of data samples. Second, one possible way to handle the nonlinear distribution of data samples is by kernel embedding. However, it is often difficult to choose the most suitable kernel. To solve these bottlenecks, we propose two novel graph-regularized NMF methods, AGNMFFS and AGNMFMK, by introducing feature selection and multiple-kernel learning to the graph regularized NMF, respectively. Instead of using a fixed graph as in GNMF, the two proposed methods learn the nearest neighbor graph that is adaptive to the selected features and learned multiple kernels, respectively. For each method, we propose a unified objective function to conduct feature selection/multi-kernel learning, NMF and adaptive graph regularization simultaneously. We further develop two iterative algorithms to solve the two optimization problems. Experimental results on two challenging pattern classification tasks demonstrate that the proposed methods significantly outperform state-of-the-art data representation methods.

Procedural learning in Tourette syndrome, ADHD, and comorbid Tourette-ADHD: Evidence from a probabilistic sequence learning task.

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Takács, Ádám; Shilon, Yuval; Janacsek, Karolina; Kóbor, Andrea; Tremblay, Antoine; Németh, Dezső; Ullman, Michael T

2017-10-01

Procedural memory, which is rooted in the basal ganglia, plays an important role in the implicit learning of motor and cognitive skills. Few studies have examined procedural learning in either Tourette syndrome (TS) or Attention Deficit Hyperactivity Disorder (ADHD), despite basal ganglia abnormalities in both of these neurodevelopmental disorders. We aimed to assess procedural learning in children with TS (n=13), ADHD (n=22), and comorbid TS-ADHD (n=20), as well as in typically developing children (n=21). Procedural learning was measured with a well-studied implicit probabilistic sequence learning task, the alternating serial reaction time task. All four groups showed evidence of sequence learning, and moreover did not differ from each other in sequence learning. This result, from the first study to examine procedural memory across TS, ADHD and comorbid TS-ADHD, is consistent with previous findings of intact procedural learning of sequences in both TS and ADHD. In contrast, some studies have found impaired procedural learning of non-sequential probabilistic categories in TS. This suggests that sequence learning may be spared in TS and ADHD, while at least some other forms of learning in procedural memory are impaired, at least in TS. Our findings indicate that disorders associated with basal ganglia abnormalities do not necessarily show procedural learning deficits, and provide a possible path for more effective diagnostic tools, and educational and training programs. Copyright © 2017 Elsevier Inc. All rights reserved.

REM sleep selectively prunes and maintains new synapses in development and learning.

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Li, Wei; Ma, Lei; Yang, Guang; Gan, Wen-Biao

2017-03-01

The functions and underlying mechanisms of rapid eye movement (REM) sleep remain unclear. Here we show that REM sleep prunes newly formed postsynaptic dendritic spines of layer 5 pyramidal neurons in the mouse motor cortex during development and motor learning. This REM sleep-dependent elimination of new spines facilitates subsequent spine formation during development and when a new motor task is learned, indicating a role for REM sleep in pruning to balance the number of new spines formed over time. Moreover, REM sleep also strengthens and maintains newly formed spines, which are critical for neuronal circuit development and behavioral improvement after learning. We further show that dendritic calcium spikes arising during REM sleep are important for pruning and strengthening new spines. Together, these findings indicate that REM sleep has multifaceted functions in brain development, learning and memory consolidation by selectively eliminating and maintaining newly formed synapses via dendritic calcium spike-dependent mechanisms.

Fingerprint-Based Machine Learning Approach to Identify Potent and Selective 5-HT2BR Ligands

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Krzysztof Rataj

2018-05-01

Full Text Available The identification of subtype-selective GPCR (G-protein coupled receptor ligands is a challenging task. In this study, we developed a computational protocol to find compounds with 5-HT2BR versus 5-HT1BR selectivity. Our approach employs the hierarchical combination of machine learning methods, docking, and multiple scoring methods. First, we applied machine learning tools to filter a large database of druglike compounds by the new Neighbouring Substructures Fingerprint (NSFP. This two-dimensional fingerprint contains information on the connectivity of the substructural features of a compound. Preselected subsets of the database were then subjected to docking calculations. The main indicators of compounds’ selectivity were their different interactions with the secondary binding pockets of both target proteins, while binding modes within the orthosteric binding pocket were preserved. The combined methodology of ligand-based and structure-based methods was validated prospectively, resulting in the identification of hits with nanomolar affinity and ten-fold to ten thousand-fold selectivities.

Learning an operant conditioning task differentially induces gliogenesis in the medial prefrontal cortex and neurogenesis in the hippocampus.

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Maximiliano Rapanelli

Full Text Available Circuit modification associated with learning and memory involves multiple events, including the addition and remotion of newborn cells trough adulthood. Adult neurogenesis and gliogenesis were mainly described in models of voluntary exercise, enriched environments, spatial learning and memory task; nevertheless, it is unknown whether it is a common mechanism among different learning paradigms, like reward dependent tasks. Therefore, we evaluated cell proliferation, neurogenesis, astrogliogenesis, survival and neuronal maturation in the medial prefrontal cortex (mPFC and the hippocampus (HIPP during learning an operant conditioning task. This was performed by using endogenous markers of cell proliferation, and a bromodeoxiuridine (BrdU injection schedule in two different phases of learning. Learning an operant conditioning is divided in two phases: a first phase when animals were considered incompletely trained (IT, animals that were learning the task when they performed between 50% and 65% of the responses, and a second phase when animals were considered trained (Tr, animals that completely learned the task when they reached 100% of the responses with a latency time lower than 5 seconds. We found that learning an operant conditioning task promoted cell proliferation in both phases of learning in the mPFC and HIPP. Additionally, the results presented showed that astrogliogenesis was induced in the medial prefrontal cortex (mPFC in both phases, however, the first phase promoted survival of these new born astrocytes. On the other hand, an increased number of new born immature neurons was observed in the HIPP only in the first phase of learning, whereas, decreased values were observed in the second phase. Finally, we found that neuronal maturation was induced only during the first phase. This study shows for the first time that learning a reward-dependent task, like the operant conditioning, promotes neurogenesis, astrogliogenesis, survival and

Position-aware deep multi-task learning for drug-drug interaction extraction.

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Zhou, Deyu; Miao, Lei; He, Yulan

2018-05-01

A drug-drug interaction (DDI) is a situation in which a drug affects the activity of another drug synergistically or antagonistically when being administered together. The information of DDIs is crucial for healthcare professionals to prevent adverse drug events. Although some known DDIs can be found in purposely-built databases such as DrugBank, most information is still buried in scientific publications. Therefore, automatically extracting DDIs from biomedical texts is sorely needed. In this paper, we propose a novel position-aware deep multi-task learning approach for extracting DDIs from biomedical texts. In particular, sentences are represented as a sequence of word embeddings and position embeddings. An attention-based bidirectional long short-term memory (BiLSTM) network is used to encode each sentence. The relative position information of words with the target drugs in text is combined with the hidden states of BiLSTM to generate the position-aware attention weights. Moreover, the tasks of predicting whether or not two drugs interact with each other and further distinguishing the types of interactions are learned jointly in multi-task learning framework. The proposed approach has been evaluated on the DDIExtraction challenge 2013 corpus and the results show that with the position-aware attention only, our proposed approach outperforms the state-of-the-art method by 0.99% for binary DDI classification, and with both position-aware attention and multi-task learning, our approach achieves a micro F-score of 72.99% on interaction type identification, outperforming the state-of-the-art approach by 1.51%, which demonstrates the effectiveness of the proposed approach. Copyright © 2018 Elsevier B.V. All rights reserved.

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks.

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Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention.

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks

Science.gov (United States)

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnöve; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dual-tasking) did not recruit additional cortical regions, but resulted in increased activity in medial and lateral frontal regions which were also activated by the component tasks when performed separately. Areas involved in semantic language processing were revealed predominantly in the left lateral prefrontal cortex by contrasting incongruent with congruent sentences. These areas also showed significant activity increases during divided attention in relation to selective attention. In the sensory cortices, no crossmodal inhibition was observed during divided attention when compared with selective attention to one modality. Our results suggest that the observed performance decrements during dual-tasking are due to interference of the two tasks because they utilize the same part of the cortex. Moreover, semantic dual-tasking did not appear to recruit additional brain areas in comparison with single tasking, and no crossmodal inhibition was observed during intermodal divided attention. PMID:25745395

Individual personality differences in goats predict their performance in visual learning and non-associative cognitive tasks.

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Nawroth, Christian; Prentice, Pamela M; McElligott, Alan G

2017-01-01

Variation in common personality traits, such as boldness or exploration, is often associated with risk-reward trade-offs and behavioural flexibility. To date, only a few studies have examined the effects of consistent behavioural traits on both learning and cognition. We investigated whether certain personality traits ('exploration' and 'sociability') of individuals were related to cognitive performance, learning flexibility and learning style in a social ungulate species, the goat (Capra hircus). We also investigated whether a preference for feature cues rather than impaired learning abilities can explain performance variation in a visual discrimination task. We found that personality scores were consistent across time and context. Less explorative goats performed better in a non-associative cognitive task, in which subjects had to follow the trajectory of a hidden object (i.e. testing their ability for object permanence). We also found that less sociable subjects performed better compared to more sociable goats in a visual discrimination task. Good visual learning performance was associated with a preference for feature cues, indicating personality-dependent learning strategies in goats. Our results suggest that personality traits predict the outcome in visual discrimination and non-associative cognitive tasks in goats and that impaired performance in a visual discrimination tasks does not necessarily imply impaired learning capacities, but rather can be explained by a varying preference for feature cues. Copyright © 2016 Elsevier B.V. All rights reserved.

The Role of CLEAR Thinking in Learning Science from Multiple-Document Inquiry Tasks

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Thomas D. GRIFFIN

2012-10-01

Full Text Available The main goal for the current study was to investigate whether individual differences in domaingeneral thinking dispositions might affect learning from multiple-document inquiry tasks in science.Middle school students were given a set of documents and were tasked with understanding how and why recent patterns in global temperature might be different from what has been observed in the past from those documents. Understanding was assessed with two measures: an essay task and an inference verification task. Domain-general thinking dispositions were assessed with a Commitment to Logic, Evidence, and Reasoning (CLEAR thinking scale. The measures of understanding wereuniquely predicted by both reading skills and CLEAR thinking scores, and these effects were not attributable to prior knowledge or interest. The results suggest independent roles for thinkingdispositions and reading ability when students read to learn from multiple-document inquiry tasks in science.

Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

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Rop, Gertjan; van Wermeskerken, Margot; de Nooijer, Jacqueline A.; Verkoeijen, Peter P. J. L.; van Gog, Tamara

2018-01-01

Research on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking research suggests that task experience might be a boundary…

Selection of maintenance tasks

Energy Technology Data Exchange (ETDEWEB)

Dean, B; Rombos, P [Wardrop (W.L.) and Associates Ltd., Winnipeg, MB (Canada)

1995-10-01

Two methodologies for maintenance task selection, Reliability Centre Maintenance (RCM) and Degradation Mode Analysis (DMA), are compared with regard to application in the nuclear industry and potential for application at CANDU nuclear power plants. RCM is the favoured one of the two methodologies. It is more thorough than DMA, is well supported within the US nuclear industry, and - with experience in application - is gaining cost effectiveness. There is interest in the use of RCM in other nations, including France and Japan, and it is already being implemented at Bruce A NGS and Bruce B NGS in Canada. DMA lags behind RCM in development and currently there is little experience to support claims of major benefits at reduced cost. Significant advantages over RCM need to be demonstrated if DMA is to gain acceptance in the nuclear industry. (author). 41 refs., 7 tabs., 8 figs.

Selection of maintenance tasks

International Nuclear Information System (INIS)

Dean, B.; Rombos, P.

1995-10-01

Two methodologies for maintenance task selection, Reliability Centre Maintenance (RCM) and Degradation Mode Analysis (DMA), are compared with regard to application in the nuclear industry and potential for application at CANDU nuclear power plants. RCM is the favoured one of the two methodologies. It is more thorough than DMA, is well supported within the US nuclear industry, and - with experience in application - is gaining cost effectiveness. There is interest in the use of RCM in other nations, including France and Japan, and it is already being implemented at Bruce A NGS and Bruce B NGS in Canada. DMA lags behind RCM in development and currently there is little experience to support claims of major benefits at reduced cost. Significant advantages over RCM need to be demonstrated if DMA is to gain acceptance in the nuclear industry. (author). 41 refs., 7 tabs., 8 figs

Sucrose Responsiveness, Learning Success, and Task Specialization in Ants

Science.gov (United States)

Perez, Margot; Rolland, Uther; Giurfa,, Martin; d'Ettorre, Patrizia

2013-01-01

Social insects possess remarkable learning capabilities, which are crucial for their ecological success. They also exhibit interindividual differences in responsiveness to environmental stimuli, which underlie task specialization and division of labor. Here we investigated for the first time the relationships between sucrose responsiveness,…

Task Complexity Modulates Sleep-Related Offline Learning in Sequential Motor Skills

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Klaus Blischke

2017-07-01

Full Text Available Recently, a number of authors have advocated the introduction of gross motor tasks into research on sleep-related motor offline learning. Such tasks are often designed to be more complex than traditional key-pressing tasks. However, until now, little effort has been undertaken to scrutinize the role of task complexity in any systematic way. Therefore, the effect of task complexity on the consolidation of gross motor sequence memory was examined by our group in a series of three experiments. Criterion tasks always required participants to produce unrestrained arm movement sequences by successively fitting a small peg into target holes on a pegboard. The sequences always followed a certain spatial pattern in the horizontal plane. The targets were visualized prior to each transport movement on a computer screen. The tasks differed with respect to sequence length and structural complexity. In each experiment, half of the participants initially learned the task in the morning and were retested 12 h later following a wake retention interval. The other half of the subjects underwent practice in the evening and was retested 12 h later following a night of sleep. The dependent variables were the error rate and total sequence execution time (inverse to the sequence execution speed. Performance generally improved during acquisition. The error rate was always low and remained stable during retention. The sequence execution time significantly decreased again following sleep but not after waking when the sequence length was long and structural complexity was high. However, sleep-related offline improvements were absent when the sequence length was short or when subjects performed a highly regular movement pattern. It is assumed that the occurrence of sleep-related offline performance improvements in sequential motor tasks is associated with a sufficient amount of motor task complexity.

Thrive or overload? The effect of task complexity on novices' simulation-based learning.

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Haji, Faizal A; Cheung, Jeffrey J H; Woods, Nicole; Regehr, Glenn; de Ribaupierre, Sandrine; Dubrowski, Adam

2016-09-01

Fidelity is widely viewed as an important element of simulation instructional design based on its purported relationship with transfer of learning. However, higher levels of fidelity may increase task complexity to a point at which novices' cognitive resources become overloaded. In this experiment, we investigate the effects of variations in task complexity on novices' cognitive load and learning during simulation-based procedural skills training. Thirty-eight medical students were randomly assigned to simulation training on a simple or complex lumbar puncture (LP) task. Participants completed four practice trials on this task (skill acquisition). After 10 days of rest, all participants completed one additional trial on their assigned task (retention) and one trial on a 'very complex' simulation designed to be similar to the complex task (transfer). We assessed LP performance and cognitive load on each trial using multiple measures. In both groups, LP performance improved significantly during skill acquisition (p ≤ 0.047, f = 0.29-0.96) and was maintained at retention. The simple task group demonstrated superior performance compared with the complex task group throughout these phases (p ≤ 0.002, d = 1.13-2.31). Cognitive load declined significantly in the simple task group (p Education.

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

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

1989-01-01

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

Canonical Correlational Models of Students’ Perceptions of Assessment Tasks, Motivational Orientations, and Learning Strategies

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Hussain Alkharusi

2013-01-01

Full Text Available The present study aims at deriving correlational models of students' perceptions of assessment tasks, motivational orientations, and learning strategies using canonical analyses. Data were collected from 198 Omani tenth grade students. Results showed that high degrees of authenticity and transparency in assessment were associated with positive students' self-efficacy and task value. Also, high degrees of authenticity, transparency, and diversity in assessment were associated with a strong reliance on deep learning strategies; whereas a high degree of congruence with planned learning and a low degree of authenticity were associated with more reliance on surface learning strategies. Implications for classroom assessment practice and research were discussed.

Stroop-like effects in a new-code learning task: A cognitive load theory perspective.

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Hazan-Liran, Batel; Miller, Paul

2017-09-01

To determine whether and how learning is biased by competing task-irrelevant information that creates extraneous cognitive load, we assessed the efficiency of university students with a learning paradigm in two experiments. The paradigm asked participants to learn associations between eight words and eight digits. We manipulated congruity of the digits' ink colour with the words' semantics. In Experiment 1 word stimuli were colour words (e.g., blue, yellow) and in Experiment 2 colour-related word concepts (e.g., sky, banana). Marked benefits and costs on learning due to variation in extraneous cognitive load originating from processing task-irrelevant information were evident. Implications for cognitive load theory and schooling are discussed.

EEG correlates of task engagement and mental workload in vigilance, learning, and memory tasks.

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Berka, Chris; Levendowski, Daniel J; Lumicao, Michelle N; Yau, Alan; Davis, Gene; Zivkovic, Vladimir T; Olmstead, Richard E; Tremoulet, Patrice D; Craven, Patrick L

2007-05-01

The ability to continuously and unobtrusively monitor levels of task engagement and mental workload in an operational environment could be useful in identifying more accurate and efficient methods for humans to interact with technology. This information could also be used to optimize the design of safer, more efficient work environments that increase motivation and productivity. The present study explored the feasibility of monitoring electroencephalo-graphic (EEG) indices of engagement and workload acquired unobtrusively and quantified during performance of cognitive tests. EEG was acquired from 80 healthy participants with a wireless sensor headset (F3-F4,C3-C4,Cz-POz,F3-Cz,Fz-C3,Fz-POz) during tasks including: multi-level forward/backward-digit-span, grid-recall, trails, mental-addition, 20-min 3-Choice Vigilance, and image-learning and memory tests. EEG metrics for engagement and workload were calculated for each 1 -s of EEG. Across participants, engagement but not workload decreased over the 20-min vigilance test. Engagement and workload were significantly increased during the encoding period of verbal and image-learning and memory tests when compared with the recognition/ recall period. Workload but not engagement increased linearly as level of difficulty increased in forward and backward-digit-span, grid-recall, and mental-addition tests. EEG measures correlated with both subjective and objective performance metrics. These data in combination with previous studies suggest that EEG engagement reflects information-gathering, visual processing, and allocation of attention. EEG workload increases with increasing working memory load and during problem solving, integration of information, analytical reasoning, and may be more reflective of executive functions. Inspection of EEG on a second-by-second timescale revealed associations between workload and engagement levels when aligned with specific task events providing preliminary evidence that second

Oxytocin selectively facilitates learning with social feedback and increases activity and functional connectivity in emotional memory and reward processing regions.

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Hu, Jiehui; Qi, Song; Becker, Benjamin; Luo, Lizhu; Gao, Shan; Gong, Qiyong; Hurlemann, René; Kendrick, Keith M

2015-06-01

In male Caucasian subjects, learning is facilitated by receipt of social compared with non-social feedback, and the neuropeptide oxytocin (OXT) facilitates this effect. In this study, we have first shown a cultural difference in that male Chinese subjects actually perform significantly worse in the same reinforcement associated learning task with social (emotional faces) compared with non-social feedback. Nevertheless, in two independent double-blind placebo (PLC) controlled between-subject design experiments we found OXT still selectively facilitated learning with social feedback. Similar to Caucasian subjects this OXT effect was strongest with feedback using female rather than male faces. One experiment performed in conjunction with functional magnetic resonance imaging showed that during the response, but not feedback phase of the task, OXT selectively increased activity in the amygdala, hippocampus, parahippocampal gyrus and putamen during the social feedback condition, and functional connectivity between the amygdala and insula and caudate. Therefore, OXT may be increasing the salience and reward value of anticipated social feedback. In the PLC group, response times and state anxiety scores during social feedback were associated with signal changes in these same regions but not in the OXT group. OXT may therefore have also facilitated learning by reducing anxiety in the social feedback condition. Overall our results provide the first evidence for cultural differences in social facilitation of learning per se, but a similar selective enhancement of learning with social feedback under OXT. This effect of OXT may be associated with enhanced responses and functional connectivity in emotional memory and reward processing regions. © 2015 Wiley Periodicals, Inc.

Effects of practice schedule and task specificity on the adaptive process of motor learning.

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Barros, João Augusto de Camargo; Tani, Go; Corrêa, Umberto Cesar

2017-10-01

This study investigated the effects of practice schedule and task specificity based on the perspective of adaptive process of motor learning. For this purpose, tasks with temporal and force control learning requirements were manipulated in experiments 1 and 2, respectively. Specifically, the task consisted of touching with the dominant hand the three sequential targets with specific movement time or force for each touch. Participants were children (N=120), both boys and girls, with an average age of 11.2years (SD=1.0). The design in both experiments involved four practice groups (constant, random, constant-random, and random-constant) and two phases (stabilisation and adaptation). The dependent variables included measures related to the task goal (accuracy and variability of error of the overall movement and force patterns) and movement pattern (macro- and microstructures). Results revealed a similar error of the overall patterns for all groups in both experiments and that they adapted themselves differently in terms of the macro- and microstructures of movement patterns. The study concludes that the effects of practice schedules on the adaptive process of motor learning were both general and specific to the task. That is, they were general to the task goal performance and specific regarding the movement pattern. Copyright © 2017 Elsevier B.V. All rights reserved.

TMI-2 Lessons Learned Task Force. Final report

International Nuclear Information System (INIS)

1979-10-01

In its final report reviewing the Three Mile Island accident, the TMI-2 Lessons Learned Task Force has suggested change in several fundamental aspects of basic safety policy for nuclear power plants. Changes in nuclear power plant design and operations and in the regulatory process are discussed in terms of general goals. The appendix sets forth specific recommendations for reaching these goals

No effects of transcranial DLPFC stimulation on implicit task sequence learning and consolidation.

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Savic, Branislav; Cazzoli, Dario; Müri, René; Meier, Beat

2017-08-29

Neurostimulation of the dorsolateral prefrontal cortex (DLPFC) can modulate performance in cognitive tasks. In a recent study, however, transcranial direct current stimulation (tDCS) of the DLPFC did not affect implicit task sequence learning and consolidation in a paradigm that involved bimanual responses. Because bimanual performance increases the coupling between homologous cortical areas of the hemispheres and left and right DLPFC were stimulated separately the null findings may have been due to the bimanual setup. The aim of the present study was to test the effect of neuro-stimulation on sequence learning in a uni-manual setup. For this purpose two experiments were conducted. In Experiment 1, the DLPFC was stimulated with tDCS. In Experiment 2 the DLPFC was stimulated with transcranial magnetic stimulation (TMS). In both experiments, consolidation was measured 24 hours later. The results showed that sequence learning was present in all conditions and sessions, but it was not influenced by stimulation. Likewise, consolidation of sequence learning was robust across sessions, but it was not influenced by stimulation. These results replicate and extend previous findings. They indicate that established tDCS and TMS protocols on the DLPFC do not influence implicit task sequence learning and consolidation.

Sex differences in a landmark environmental re-orientation task only during the learning phase.

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Piccardi, Laura; Bianchini, Filippo; Iasevoli, Luigi; Giannone, Gianluca; Guariglia, Cecilia

2011-10-10

Sex differences are consistently reported in human navigation. Indeed, to orient themselves during navigation women are more likely to use landmark-based strategies and men Euclidean-based strategies. The difference could be due to selective social pressure, which fosters greater spatial ability in men, or biological factors. And the great variability of the results reported in the literature could be due to the experimental setting more than real differences in ability. In this study, navigational behaviour was assessed by means of a place-learning task in which a modified version of the Morris water maze for humans was used to evaluate sex differences. In using landmarks, sex differences emerged only during the learning phase. Although the men were faster than the women in locating the target position, the differences between the sexes disappeared in delayed recall. Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.

Emergence of motor synergy in vertical reaching task via tacit learning.

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Hayashibe, Mitsuhiro; Shimoda, Shingo

2013-01-01

The dynamics of multijoint limbs often causes complex dynamic interaction torques which are the inertial effect of other joints motion. It is known that Cerebellum takes important role in a motor learning by developing the internal model. In this paper, we propose a novel computational control paradigm in vertical reaching task which involves the management of interaction torques and gravitational effect. The obtained results demonstrate that the proposed method is valid for acquiring motor synergy in the system with actuation redundancy and resulted in the energy efficient solutions. It is highlighted that the tacit learning in vertical reaching task can bring computational adaptability and optimality with model-free and cost-function-free approach differently from previous studies.

Emotion-based learning: Insights from the Iowa Gambling Task

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Oliver Hugh Turnbull

2014-03-01

Full Text Available Interest in the cognitive and/or emotional basis of complex decision-making, and the related phenomenon of emotion-based learning, has been heavily influenced by the Iowa Gambling Task. A number of psychological variables have been investigated as potentially important in understanding emotion-based learning. This paper reviews the extent to which humans are explicitly aware of how we make such decisions; the biasing influence of pre-existing emotional labels; and the extent to which emotion-based systems are anatomically and functionally independent of episodic memory. Systematic review suggests that (i an aspect of conscious awareness does appear to be readily achieved during the IGT, but as a relatively unfocused emotion-based ‘gut-feeling’, akin to intuition; (ii Several studies have manipulated the affective pre-loading of IGT tasks, and make it clear that such labelling has a substantial influence on performance, an experimental manipulation similar to the phenomenon of prejudice. (iii Finally, it appears that complex emotion-based learning can remain intact despite profound amnesia, at least in some neurological patients, a finding with a range of potentially important clinical implications: in the management of dementia; in explaining infantile amnesia; and in understanding of the possible mechanisms of psychotherapy.

Gender Effects When Learning Manipulative Tasks from Instructional Animations and Static Presentations

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Wong, Mona; Castro-Alonso, Juan C.; Ayres, Paul; Paas, Fred

2015-01-01

Humans have an evolved embodied cognition that equips them to deal easily with the natural movements of object manipulations. Hence, learning a manipulative task is generally more effective when watching animations that show natural motions of the task, rather than equivalent static pictures. The present study was completed to explore this…

Aerobic fitness relates to learning on a virtual morris water task and hippocampal volume in adolescents

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Herting, Megan M.; Nagel, Bonnie J.

2012-01-01

In rodents, exercise increases hippocampal neurogenesis and allows for better learning and memory performance on water maze tasks. While exercise has also been shown to be beneficial for the brain and behavior in humans, no study has examined how exercise impacts spatial learning using a directly translational water maze task, or if these relationships exist during adolescence – a developmental period which the animal literature has shown to be especially vulnerable to exercise effects. In this study, we investigated the influence of aerobic fitness on hippocampal size and subsequent learning and memory, including visuospatial memory using a human analogue of the Morris Water Task, in 34 adolescents. Results showed that higher aerobic fitness predicted better learning on the virtual Morris Water Task and larger hippocampal volumes. No relationship between virtual Morris Water Task memory recall and aerobic fitness was detected. Aerobic fitness, however, did not relate to global brain volume, or verbal learning, which might suggest some specificity of the influence of aerobic fitness on the adolescent brain. This study provides a direct translational approach to the existing animal literature on exercise, as well as adds to the sparse research that exists on how aerobic exercise impacts the developing human brain and memory. PMID:22610054

Aerobic fitness relates to learning on a virtual Morris Water Task and hippocampal volume in adolescents.

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Herting, Megan M; Nagel, Bonnie J

2012-08-01

In rodents, exercise increases hippocampal neurogenesis and allows for better learning and memory performance on water maze tasks. While exercise has also been shown to be beneficial for the brain and behavior in humans, no study has examined how exercise impacts spatial learning using a directly translational water maze task, or if these relationships exist during adolescence--a developmental period which the animal literature has shown to be especially vulnerable to exercise effects. In this study, we investigated the influence of aerobic fitness on hippocampal size and subsequent learning and memory, including visuospatial memory using a human analogue of the Morris Water Task, in 34 adolescents. Results showed that higher aerobic fitness predicted better learning on the virtual Morris Water Task and larger hippocampal volumes. No relationship between virtual Morris Water Task memory recall and aerobic fitness was detected. Aerobic fitness, however, did not relate to global brain volume or verbal learning, which might suggest some specificity of the influence of aerobic fitness on the adolescent brain. This study provides a direct translational approach to the existing animal literature on exercise, as well as adds to the sparse research that exists on how aerobic exercise impacts the developing human brain and memory. Published by Elsevier B.V.

Task path planning, scheduling and learning for free-ranging robot systems

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Wakefield, G. Steve

1987-01-01

The development of robotics applications for space operations is often restricted by the limited movement available to guided robots. Free ranging robots can offer greater flexibility than physically guided robots in these applications. Presented here is an object oriented approach to path planning and task scheduling for free-ranging robots that allows the dynamic determination of paths based on the current environment. The system also provides task learning for repetitive jobs. This approach provides a basis for the design of free-ranging robot systems which are adaptable to various environments and tasks.

Selecting a Response in Task Switching: Testing a Model of Compound Cue Retrieval

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Schneider, Darryl W.; Logan, Gordon D.

2009-01-01

How can a task-appropriate response be selected for an ambiguous target stimulus in task-switching situations? One answer is to use compound cue retrieval, whereby stimuli serve as joint retrieval cues to select a response from long-term memory. In the present study, the authors tested how well a model of compound cue retrieval could account for a…

Positive versus Negative Communication Strategies in Task-Based Learning

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Rohani, Siti

2013-01-01

This study aimed at describing how the implementation of Task-Based Learning (TBL) would shape or change students' use of oral communication strategies. Students' problems and strategies to solve the problems during the implementation of TBL were also explored. The study was a mixed method, employing both quantitative and qualitative analysis…

Comparison of learning ability and memory retention in altricial (Bengalese finch, Lonchura striata var. domestica) and precocial (blue-breasted quail, Coturnix chinensis) birds using a color discrimination task.

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Ueno, Aki; Suzuki, Kaoru

2014-02-01

The present study sought to assess the potential application of avian models with different developmental modes to studies on cognition and neuroscience. Six altricial Bengalese finches (Lonchura striata var. domestica), and eight precocial blue-breasted quails (Coturnix chinensis) were presented with color discrimination tasks to compare their respective faculties for learning and memory retention within the context of the two developmental modes. Tasks consisted of presenting birds with discriminative cues in the form of colored feeder lids, and birds were considered to have learned a task when 80% of their attempts at selecting the correctly colored lid in two consecutive blocks of 10 trials were successful. All of the finches successfully performed the required experimental tasks, whereas only half of the quails were able to execute the same tasks. In the learning test, finches required significantly fewer trials than quails to learn the task (finches: 13.5 ± 9.14 trials, quails: 45.8 ± 4.35 trials, P memory retention tests, which were conducted 45 days after the learning test, finches retained the ability to discriminate between colors correctly (95.0 ± 4.47%), whereas quails did not retain any memory of the experimental procedure and so could not be tested. These results suggested that altricial and precocial birds both possess the faculty for learning and retaining discrimination-type tasks, but that altricial birds perform better than precocial birds in both faculties. The present findings imply that developmental mode is an important consideration for assessing the suitability of bird species for particular experiments. © 2013 Japanese Society of Animal Science.

Towards Sustaining Levels of Reflective Learning: How Do Transformational Leadership, Task Interdependence, and Self-Efficacy Shape Teacher Learning in Schools?

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Arnoud Oude Groote Beverborg

2015-03-01

Full Text Available Whereas cross-sectional research has shown that transformational leadership, task interdependence, and self-efficacy are positively related to teachers’ engagement in reflective learning activities, the causal direction of these relations needs further inquiry. At the same time, individual teacher learning might play a mutual role in strengthening school-level capacity for sustained improvement. Building on previous research, this longitudinal study therefore examines how transformational leadership, task interdependence, self-efficacy, and teachers’ engagement in self-reflection mutually affect each other over time. Questionnaire data gathered on three measurement occasions from 655 Dutch Vocational Education and Training teachers was analyzed using a multivariate Latent Difference Score model. Results indicate that self-reflection and task interdependence reciprocally influence each other’s change. A considerate and stimulating transformational leader was found to contribute to this process. Change in self-efficacy was influenced by self-reflection, indicating that learning leads to competency beliefs. Together, the findings point to the important role transformational leadership practices play in facilitating teamwork, and sustaining teachers’ levels of learning in schools.

Learner Perspectives on Task Design for Oral-Visual eTandem Language Learning

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El-Hariri, Yasmin

2016-01-01

Constituting a more specific form of online collaboration, eTandem Language Learning (eTLL) shows great potential for non-formal, self-directed language learning. Research in this field, particularly regarding task design, is still scarce. Focusing on their beliefs and attitudes, this article examines what learners think about how…

Over-Selectivity as a Learned Response

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Reed, Phil; Petrina, Neysa; McHugh, Louise

2011-01-01

An experiment investigated the effects of different levels of task complexity in pre-training on over-selectivity in a subsequent match-to-sample (MTS) task. Twenty human participants were divided into two groups; exposed either to a 3-element, or a 9-element, compound stimulus as a sample during MTS training. After the completion of training,…

Task-based Language Learning in Bilingual Montessori Elementary Schools: Customizing Foreign Language Learning and Promoting L2 Speaking Skills

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Jana Winnefeld

2012-01-01

Full Text Available Foreign language learning has been a part of German elementary schools for several years now. Montessori schools focusing on individual learning, i.e. mostly independent from the teacher and based on auto-education, interest, and free choice, are also asked to teach an L2. The original lack of a concept of L2 learning for this environment has brought forth different approaches. Bilingual education seems to be feasible and applicable in Montessori education. The downside to this is that even in a bilingual classroom the Montessori way of learning may not allow for very much oral production of the foreign language. The role of L2 production (cf. Swain 1985, 1995, 2005 for language acquisition has been theoretically claimed and empirically investigated. Output can have a positive influence on L2 learning (cf. e.g. Izumi 2002, Keck et al. 2006. This also applies to interaction (cf. Long 1996, where negotiation of meaning and modified output are factors supporting L2 development (cf. e.g. de la Fuente 2002, McDonough 2005. Task-based Language Learning (TBLL presents itself as one way to promote oral language production and to provide opportunities for meaning-negotiation. Especially tasks with required information exchange and a closed outcome have been shown to be beneficial for the elicitation of negotiation of meaning and modified output. This paper argues that TBLL is a promising approach for the facilitation of L2 production and thus the development of speaking skills in a Montessori context. It also hypothesizes that TBLL can be implemented in a bilingual Montessori environment while still making the Montessori way of learning possible. Different tasks on various topics, examples of which are presented in this article, can lay the foundation for this. Offering such tasks in a bilingual Montessori elementary classroom promises to foster language production and the use of communication strategies like negotiation of meaning, both being

More insight into the interplay of response selection and visual attention in dual-tasks: masked visual search and response selection are performed in parallel.

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Reimer, Christina B; Schubert, Torsten

2017-09-15

Both response selection and visual attention are limited in capacity. According to the central bottleneck model, the response selection processes of two tasks in a dual-task situation are performed sequentially. In conjunction search, visual attention is required to select the items and to bind their features (e.g., color and form), which results in a serial search process. Search time increases as items are added to the search display (i.e., set size effect). When the search display is masked, visual attention deployment is restricted to a brief period of time and target detection decreases as a function of set size. Here, we investigated whether response selection and visual attention (i.e., feature binding) rely on a common or on distinct capacity limitations. In four dual-task experiments, participants completed an auditory Task 1 and a conjunction search Task 2 that were presented with an experimentally modulated temporal interval between them (Stimulus Onset Asynchrony, SOA). In Experiment 1, Task 1 was a two-choice discrimination task and the conjunction search display was not masked. In Experiment 2, the response selection difficulty in Task 1 was increased to a four-choice discrimination and the search task was the same as in Experiment 1. We applied the locus-of-slack method in both experiments to analyze conjunction search time, that is, we compared the set size effects across SOAs. Similar set size effects across SOAs (i.e., additive effects of SOA and set size) would indicate sequential processing of response selection and visual attention. However, a significantly smaller set size effect at short SOA compared to long SOA (i.e., underadditive interaction of SOA and set size) would indicate parallel processing of response selection and visual attention. In both experiments, we found underadditive interactions of SOA and set size. In Experiments 3 and 4, the conjunction search display in Task 2 was masked. Task 1 was the same as in Experiments 1 and 2

Cueing and Anxiety in a Visual Concept Learning Task.

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Turner, Philip M.

This study investigated the relationship of two anxiety measures (the State-Trait Anxiety Inventory-Trait Form and the S-R Inventory of Anxiousness-Exam Form) to performance on a visual concept-learning task with embedded criterial information. The effect on anxiety reduction of cueing criterial information was also examined, and two levels of…

A single session of prefrontal cortex transcranial direct current stimulation does not modulate implicit task sequence learning and consolidation.

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Savic, Branislav; Müri, René; Meier, Beat

Transcranial direct current stimulation (tDCS) is assumed to affect cortical excitability and dependent on the specific stimulation conditions either to increase or decrease learning. The purpose of this study was to modulate implicit task sequence learning with tDCS. As cortico-striatal loops are critically involved in implicit task sequence learning, tDCS was applied above the dorsolateral prefrontal cortex (DLPFC). In Experiment 1, anodal, cathodal, or sham tDCS was applied before the start of the sequence learning task. In Experiment 2, stimulation was applied during the sequence learning task. Consolidation of learning was assessed after 24 h. The results of both experiments showed that implicit task sequence learning occurred consistently but it was not modulated by different tDCS conditions. Similarly, consolidation measured after a 24 h-interval including sleep was also not affected by stimulation. These results indicate that a single session of DLPFC tDCS is not sufficient to modulate implicit task sequence learning. This study adds to the accumulating evidence that tDCS may not be as effective as originally thought. Copyright © 2017 Elsevier Inc. All rights reserved.

Minimal groups increase young children's motivation and learning on group-relevant tasks.

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Master, Allison; Walton, Gregory M

2013-01-01

Three experiments (N = 130) used a minimal group manipulation to show that just perceived membership in a social group boosts young children's motivation for and learning from group-relevant tasks. In Experiment 1, 4-year-old children assigned to a minimal "puzzles group" persisted longer on a challenging puzzle than children identified as the "puzzles child" or children in a control condition. Experiment 2 showed that this boost in motivation occurred only when the group was associated with the task. In Experiment 3, children assigned to a minimal group associated with word learning learned more words than children assigned an analogous individual identity. The studies demonstrate that fostering shared motivations may be a powerful means by which to shape young children's academic outcomes. © 2012 The Authors. Child Development © 2012 Society for Research in Child Development, Inc.

Effect of Error Augmentation on Brain Activation and Motor Learning of a Complex Locomotor Task

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Laura Marchal-Crespo

2017-09-01

Full Text Available Up to date, the functional gains obtained after robot-aided gait rehabilitation training are limited. Error augmenting strategies have a great potential to enhance motor learning of simple motor tasks. However, little is known about the effect of these error modulating strategies on complex tasks, such as relearning to walk after a neurologic accident. Additionally, neuroimaging evaluation of brain regions involved in learning processes could provide valuable information on behavioral outcomes. We investigated the effect of robotic training strategies that augment errors—error amplification and random force disturbance—and training without perturbations on brain activation and motor learning of a complex locomotor task. Thirty-four healthy subjects performed the experiment with a robotic stepper (MARCOS in a 1.5 T MR scanner. The task consisted in tracking a Lissajous figure presented on a display by coordinating the legs in a gait-like movement pattern. Behavioral results showed that training without perturbations enhanced motor learning in initially less skilled subjects, while error amplification benefited better-skilled subjects. Training with error amplification, however, hampered transfer of learning. Randomly disturbing forces induced learning and promoted transfer in all subjects, probably because the unexpected forces increased subjects' attention. Functional MRI revealed main effects of training strategy and skill level during training. A main effect of training strategy was seen in brain regions typically associated with motor control and learning, such as, the basal ganglia, cerebellum, intraparietal sulcus, and angular gyrus. Especially, random disturbance and no perturbation lead to stronger brain activation in similar brain regions than error amplification. Skill-level related effects were observed in the IPS, in parts of the superior parietal lobe (SPL, i.e., precuneus, and temporal cortex. These neuroimaging findings

Different levels of food restriction reveal genotype-specific differences in learning a visual discrimination task.

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Kalina Makowiecki

Full Text Available In behavioural experiments, motivation to learn can be achieved using food rewards as positive reinforcement in food-restricted animals. Previous studies reduce animal weights to 80-90% of free-feeding body weight as the criterion for food restriction. However, effects of different degrees of food restriction on task performance have not been assessed. We compared learning task performance in mice food-restricted to 80 or 90% body weight (BW. We used adult wildtype (WT; C57Bl/6j and knockout (ephrin-A2⁻/⁻ mice, previously shown to have a reverse learning deficit. Mice were trained in a two-choice visual discrimination task with food reward as positive reinforcement. When mice reached criterion for one visual stimulus (80% correct in three consecutive 10 trial sets they began the reverse learning phase, where the rewarded stimulus was switched to the previously incorrect stimulus. For the initial learning and reverse phase of the task, mice at 90%BW took almost twice as many trials to reach criterion as mice at 80%BW. Furthermore, WT 80 and 90%BW groups significantly differed in percentage correct responses and learning strategy in the reverse learning phase, whereas no differences between weight restriction groups were observed in ephrin-A2⁻/⁻ mice. Most importantly, genotype-specific differences in reverse learning strategy were only detected in the 80%BW groups. Our results indicate that increased food restriction not only results in better performance and a shorter training period, but may also be necessary for revealing behavioural differences between experimental groups. This has important ethical and animal welfare implications when deciding extent of diet restriction in behavioural studies.

A 1-night operant learning task without food-restriction differentiates among mouse strains in an automated home-cage environment.

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Remmelink, Esther; Loos, Maarten; Koopmans, Bastijn; Aarts, Emmeke; van der Sluis, Sophie; Smit, August B; Verhage, Matthijs

2015-04-15

Individuals are able to change their behavior based on its consequences, a process involving instrumental learning. Studying instrumental learning in mice can provide new insights in this elementary aspect of cognition. Conventional appetitive operant learning tasks that facilitate the study of this form of learning in mice, as well as more complex operant paradigms, require labor-intensive handling and food deprivation to motivate the animals. Here, we describe a 1-night operant learning protocol that exploits the advantages of automated home-cage testing and circumvents the interfering effects of food restriction. The task builds on behavior that is part of the spontaneous exploratory repertoire during the days before the task. We compared the behavior of C57BL/6J, BALB/cJ and DBA/2J mice and found various differences in behavior during this task, but no differences in learning curves. BALB/cJ mice showed the largest instrumental learning response, providing a superior dynamic range and statistical power to study instrumental learning by using this protocol. Insights gained with this home-cage-based learning protocol without food restriction will be valuable for the development of other, more complex, cognitive tasks in automated home-cages. Copyright © 2015 Elsevier B.V. All rights reserved.

Task-Driven Dictionary Learning Based on Mutual Information for Medical Image Classification.

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Diamant, Idit; Klang, Eyal; Amitai, Michal; Konen, Eli; Goldberger, Jacob; Greenspan, Hayit

2017-06-01

We present a novel variant of the bag-of-visual-words (BoVW) method for automated medical image classification. Our approach improves the BoVW model by learning a task-driven dictionary of the most relevant visual words per task using a mutual information-based criterion. Additionally, we generate relevance maps to visualize and localize the decision of the automatic classification algorithm. These maps demonstrate how the algorithm works and show the spatial layout of the most relevant words. We applied our algorithm to three different tasks: chest x-ray pathology identification (of four pathologies: cardiomegaly, enlarged mediastinum, right consolidation, and left consolidation), liver lesion classification into four categories in computed tomography (CT) images and benign/malignant clusters of microcalcifications (MCs) classification in breast mammograms. Validation was conducted on three datasets: 443 chest x-rays, 118 portal phase CT images of liver lesions, and 260 mammography MCs. The proposed method improves the classical BoVW method for all tested applications. For chest x-ray, area under curve of 0.876 was obtained for enlarged mediastinum identification compared to 0.855 using classical BoVW (with p-value 0.01). For MC classification, a significant improvement of 4% was achieved using our new approach (with p-value = 0.03). For liver lesion classification, an improvement of 6% in sensitivity and 2% in specificity were obtained (with p-value 0.001). We demonstrated that classification based on informative selected set of words results in significant improvement. Our new BoVW approach shows promising results in clinically important domains. Additionally, it can discover relevant parts of images for the task at hand without explicit annotations for training data. This can provide computer-aided support for medical experts in challenging image analysis tasks.

Implicit visual learning and the expression of learning.

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Haider, Hilde; Eberhardt, Katharina; Kunde, Alexander; Rose, Michael

2013-03-01

Although the existence of implicit motor learning is now widely accepted, the findings concerning perceptual implicit learning are ambiguous. Some researchers have observed perceptual learning whereas other authors have not. The review of the literature provides different reasons to explain this ambiguous picture, such as differences in the underlying learning processes, selective attention, or differences in the difficulty to express this knowledge. In three experiments, we investigated implicit visual learning within the original serial reaction time task. We used different response devices (keyboard vs. mouse) in order to manipulate selective attention towards response dimensions. Results showed that visual and motor sequence learning differed in terms of RT-benefits, but not in terms of the amount of knowledge assessed after training. Furthermore, visual sequence learning was modulated by selective attention. However, the findings of all three experiments suggest that selective attention did not alter implicit but rather explicit learning processes. Copyright © 2012 Elsevier Inc. All rights reserved.

Neural Control of a Tracking Task via Attention-Gated Reinforcement Learning for Brain-Machine Interfaces.

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Wang, Yiwen; Wang, Fang; Xu, Kai; Zhang, Qiaosheng; Zhang, Shaomin; Zheng, Xiaoxiang

2015-05-01

Reinforcement learning (RL)-based brain machine interfaces (BMIs) enable the user to learn from the environment through interactions to complete the task without desired signals, which is promising for clinical applications. Previous studies exploited Q-learning techniques to discriminate neural states into simple directional actions providing the trial initial timing. However, the movements in BMI applications can be quite complicated, and the action timing explicitly shows the intention when to move. The rich actions and the corresponding neural states form a large state-action space, imposing generalization difficulty on Q-learning. In this paper, we propose to adopt attention-gated reinforcement learning (AGREL) as a new learning scheme for BMIs to adaptively decode high-dimensional neural activities into seven distinct movements (directional moves, holdings and resting) due to the efficient weight-updating. We apply AGREL on neural data recorded from M1 of a monkey to directly predict a seven-action set in a time sequence to reconstruct the trajectory of a center-out task. Compared to Q-learning techniques, AGREL could improve the target acquisition rate to 90.16% in average with faster convergence and more stability to follow neural activity over multiple days, indicating the potential to achieve better online decoding performance for more complicated BMI tasks.

Evaluating gaze-based interface tools to facilitate point-and-select tasks with small targets

DEFF Research Database (Denmark)

Skovsgaard, Henrik; Mateo, Julio C.; Hansen, John Paulin

2011-01-01

-and-select tasks. We conducted two experiments comparing the performance of dwell, magnification and zoom methods in point-and-select tasks with small targets in single- and multiple-target layouts. Both magnification and zoom showed higher hit rates than dwell. Hit rates were higher when using magnification than...

Successfully Carrying out Complex Learning-Tasks through Guiding Teams' Qualitative and Quantitative Reasoning

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Slof, B.; Erkens, G.; Kirschner, P. A.; Janssen, J.; Jaspers, J. G. M.

2012-01-01

This study investigated whether and how scripting learners' use of representational tools in a computer supported collaborative learning (CSCL)-environment fostered their collaborative performance on a complex business-economics task. Scripting the problem-solving process sequenced and made its phase-related part-task demands explicit, namely…

Does learning or instinct shape habitat selection?

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Scott E Nielsen

Full Text Available Habitat selection is an important behavioural process widely studied for its population-level effects. Models of habitat selection are, however, often fit without a mechanistic consideration. Here, we investigated whether patterns in habitat selection result from instinct or learning for a population of grizzly bears (Ursus arctos in Alberta, Canada. We found that habitat selection and relatedness were positively correlated in female bears during the fall season, with a trend in the spring, but not during any season for males. This suggests that habitat selection is a learned behaviour because males do not participate in parental care: a genetically predetermined behaviour (instinct would have resulted in habitat selection and relatedness correlations for both sexes. Geographic distance and home range overlap among animals did not alter correlations indicating that dispersal and spatial autocorrelation had little effect on the observed trends. These results suggest that habitat selection in grizzly bears are partly learned from their mothers, which could have implications for the translocation of wildlife to novel environments.

Concurrent deployment of visual attention and response selection bottleneck in a dual-task: Electrophysiological and behavioural evidence.

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Reimer, Christina B; Strobach, Tilo; Schubert, Torsten

2017-12-01

Visual attention and response selection are limited in capacity. Here, we investigated whether visual attention requires the same bottleneck mechanism as response selection in a dual-task of the psychological refractory period (PRP) paradigm. The dual-task consisted of an auditory two-choice discrimination Task 1 and a conjunction search Task 2, which were presented at variable temporal intervals (stimulus onset asynchrony, SOA). In conjunction search, visual attention is required to select items and to bind their features resulting in a serial search process around the items in the search display (i.e., set size). We measured the reaction time of the visual search task (RT2) and the N2pc, an event-related potential (ERP), which reflects lateralized visual attention processes. If the response selection processes in Task 1 influence the visual attention processes in Task 2, N2pc latency and amplitude would be delayed and attenuated at short SOA compared to long SOA. The results, however, showed that latency and amplitude were independent of SOA, indicating that visual attention was concurrently deployed to response selection. Moreover, the RT2 analysis revealed an underadditive interaction of SOA and set size. We concluded that visual attention does not require the same bottleneck mechanism as response selection in dual-tasks.

Interindividual Differences in Learning Performance: The Effects of Age, Intelligence, and Strategic Task Approach

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Kliegel, Matthias; Altgassen, Mareike

2006-01-01

The present study investigated fluid and crystallized intelligence as well as strategic task approaches as potential sources of age-related differences in adult learning performance. Therefore, 45 young and 45 old adults were asked to learn pictured objects. Overall, young participants outperformed old participants in this learning test. However,…

Integration of Teaching Processes and Learning Assessment in the Prefrontal Cortex during a Video Game Teaching-learning Task.

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Takeuchi, Naoyuki; Mori, Takayuki; Suzukamo, Yoshimi; Izumi, Shin-Ichi

2016-01-01

Human teaching is a social interaction that supports reciprocal and dynamical feedback between the teacher and the student. The prefrontal cortex (PFC) is a region of particular interest due to its demonstrated role in social interaction. In the present study, we evaluated the PFC activity simultaneously in two individuals playing the role of a teacher and student in a video game teaching-learning task. For that, we used two wearable near-infrared spectroscopy (NIRS) devices in order to elucidate the neural mechanisms underlying cognitive interactions between teachers and students. Fifteen teacher-student pairs in total ( N = 30) participated in this study. Each teacher was instructed to teach the video game to their student partner, without speaking. The PFC activity was simultaneously evaluated in both participants using a wearable 16-channel NIRS system during the video game teaching-learning task. Two sessions, each including a triplet of a 30-s teaching-learning task, were performed in order to evaluate changes in PFC activity after advancement of teaching-learning state. Changes in the teachers' left PFC activity between the first and second session positively correlated with those observed in students ( r = 0.694, p = 0.004). Moreover, among teachers, multiple regression analysis revealed a correlation between the left PFC activity and the assessment gap between one's own teaching and the student's understanding ( β = 0.649, p = 0.009). Activity in the left PFC changed synchronously in both teachers and students after advancement of the teaching-learning state. The left PFC of teachers may be involved in integrating information regarding one's own teaching process and the student's learning state. The present observations indicate that simultaneous recording and analysis of brain activity data during teacher-student interactions may be useful in the field of educational neuroscience.

Five-Year-Olds’ Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study

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Arslan, Burcu; Taatgen, Niels A.; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback “Wrong,” they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children’s failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy. PMID:28293206

Five-Year-Olds' Systematic Errors in Second-Order False Belief Tasks Are Due to First-Order Theory of Mind Strategy Selection: A Computational Modeling Study.

Science.gov (United States)

Arslan, Burcu; Taatgen, Niels A; Verbrugge, Rineke

2017-01-01

The focus of studies on second-order false belief reasoning generally was on investigating the roles of executive functions and language with correlational studies. Different from those studies, we focus on the question how 5-year-olds select and revise reasoning strategies in second-order false belief tasks by constructing two computational cognitive models of this process: an instance-based learning model and a reinforcement learning model. Unlike the reinforcement learning model, the instance-based learning model predicted that children who fail second-order false belief tasks would give answers based on first-order theory of mind (ToM) reasoning as opposed to zero-order reasoning. This prediction was confirmed with an empirical study that we conducted with 72 5- to 6-year-old children. The results showed that 17% of the answers were correct and 83% of the answers were wrong. In line with our prediction, 65% of the wrong answers were based on a first-order ToM strategy, while only 29% of them were based on a zero-order strategy (the remaining 6% of subjects did not provide any answer). Based on our instance-based learning model, we propose that when children get feedback "Wrong," they explicitly revise their strategy to a higher level instead of implicitly selecting one of the available ToM strategies. Moreover, we predict that children's failures are due to lack of experience and that with exposure to second-order false belief reasoning, children can revise their wrong first-order reasoning strategy to a correct second-order reasoning strategy.

Quality of E-Learners’ Time and Learning Performance Beyond Quantitative Time-on-Task

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Margarida Romero

2011-06-01

Full Text Available AbstractAlong with the amount of time spent learning (or time-on-task, the quality of learning time has a real influence on learning performance. Quality of time in online learning depends on students’ time availability and their willingness to devote quality cognitive time to learning activities. However, the quantity and quality of the time spent by adult e-learners on learning activities can be reduced by professional, family, and social commitments. Considering that the main time pattern followed by most adult e-learners is a professional one, it may be beneficial for online education programs to offer a certain degree of flexibility in instructional time that might allow adult learners to adjust their learning times to their professional constraints. However, using the time left over once professional and family requirements have been fulfilled could lead to a reduction in quality time for learning. This paper starts by introducing the concept of quality of learning time from an online student-centred perspective. The impact of students’ time-related variables (working hours, time-on-task engagement, time flexibility, time of day, day of week is then analyzed according to individual and collaborative grades achieved during an online master’s degree program. The data show that both students’ time flexibility (r = .98 and especially their availability to learn in the morning are related to better grades in individual (r = .93 and collaborative activities (r = .46.

On the road to invariant recognition: explaining tradeoff and morph properties of cells in inferotemporal cortex using multiple-scale task-sensitive attentive learning.

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Grossberg, Stephen; Markowitz, Jeffrey; Cao, Yongqiang

2011-12-01

Visual object recognition is an essential accomplishment of advanced brains. Object recognition needs to be tolerant, or invariant, with respect to changes in object position, size, and view. In monkeys and humans, a key area for recognition is the anterior inferotemporal cortex (ITa). Recent neurophysiological data show that ITa cells with high object selectivity often have low position tolerance. We propose a neural model whose cells learn to simulate this tradeoff, as well as ITa responses to image morphs, while explaining how invariant recognition properties may arise in stages due to processes across multiple cortical areas. These processes include the cortical magnification factor, multiple receptive field sizes, and top-down attentive matching and learning properties that may be tuned by task requirements to attend to either concrete or abstract visual features with different levels of vigilance. The model predicts that data from the tradeoff and image morph tasks emerge from different levels of vigilance in the animals performing them. This result illustrates how different vigilance requirements of a task may change the course of category learning, notably the critical features that are attended and incorporated into learned category prototypes. The model outlines a path for developing an animal model of how defective vigilance control can lead to symptoms of various mental disorders, such as autism and amnesia. Copyright © 2011 Elsevier Ltd. All rights reserved.

Showing a model's eye movements in examples does not improve learning of problem-solving tasks

NARCIS (Netherlands)

van Marlen, Tim; van Wermeskerken, Margot; Jarodzka, Halszka; van Gog, Tamara

2016-01-01

Eye movement modeling examples (EMME) are demonstrations of a computer-based task by a human model (e.g., a teacher), with the model's eye movements superimposed on the task to guide learners' attention. EMME have been shown to enhance learning of perceptual classification tasks; however, it is an

Finance Students' Experiences of Lecture-Based Active Learning Tasks

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McCullough, Kerry; Munro, Nicholas

2018-01-01

Consistent with current higher education concerns with student engagement and the student experience, this study explored third-year undergraduate Finance students' experiences of lecture-based active learning tasks. Finance students from the 2012 and 2014 cohorts from a South African university were invited to complete an anonymous questionnaire…

The Role of CLEAR Thinking in Learning Science from Multiple-Document Inquiry Tasks

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Griffin, Thomas D.; Wiley, Jennifer; Britt, M. Anne; Salas, Carlos R.

2012-01-01

The main goal for the current study was to investigate whether individual differences in domain-general thinking dispositions might affect learning from multiple-document inquiry tasks in science. Middle school students were given a set of documents and were tasked with understanding how and why recent patterns in global temperature might be…

Joint Feature Selection and Classification for Multilabel Learning.

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Huang, Jun; Li, Guorong; Huang, Qingming; Wu, Xindong

2018-03-01

Multilabel learning deals with examples having multiple class labels simultaneously. It has been applied to a variety of applications, such as text categorization and image annotation. A large number of algorithms have been proposed for multilabel learning, most of which concentrate on multilabel classification problems and only a few of them are feature selection algorithms. Current multilabel classification models are mainly built on a single data representation composed of all the features which are shared by all the class labels. Since each class label might be decided by some specific features of its own, and the problems of classification and feature selection are often addressed independently, in this paper, we propose a novel method which can perform joint feature selection and classification for multilabel learning, named JFSC. Different from many existing methods, JFSC learns both shared features and label-specific features by considering pairwise label correlations, and builds the multilabel classifier on the learned low-dimensional data representations simultaneously. A comparative study with state-of-the-art approaches manifests a competitive performance of our proposed method both in classification and feature selection for multilabel learning.

Selective role for DNMT3a in learning and memory.

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Morris, Michael J; Adachi, Megumi; Na, Elisa S; Monteggia, Lisa M

2014-11-01

Methylation of cytosine nucleotides is governed by DNA methyltransferases (DNMTs) that establish de novo DNA methylation patterns in early embryonic development (e.g., DNMT3a and DNMT3b) or maintain those patterns on hemimethylated DNA in dividing cells (e.g., DNMT1). DNMTs continue to be expressed at high levels in mature neurons, however their impact on neuronal function and behavior are unclear. To address this issue we examined DNMT1 and DNMT3a expression following associative learning. We also generated forebrain specific conditional Dnmt1 or Dnmt3a knockout mice and characterized them in learning and memory paradigms as well as for alterations in long-term potentiation (LTP) and synaptic plasticity. Here, we report that experience in an associative learning task impacts expression of Dnmt3a, but not Dnmt1, in brain areas that mediate learning of this task. We also found that Dnmt3a knockout mice, and not Dnmt1 knockouts have synaptic alterations as well as learning deficits on several associative and episodic memory tasks. These findings indicate that the de novo DNA methylating enzyme DNMT3a in postmitotic neurons is necessary for normal memory formation and its function cannot be substituted by the maintenance DNA methylating enzyme DNMT1. Copyright © 2014 Elsevier Inc. All rights reserved.

Designing Task-Based Syllabus For Writing Class

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Sundari Hanna

2018-01-01

Full Text Available Writing is viewed as the most complex skill to learn and to teach. Beside learner factors, teacher, materials and syllabus may also affect the process of learning language as foreign language. Syllabus, in general, can be defined as a set of what is taught (content and the way it is taught (procedure. This current research aims to design a task-based syllabus for writing class at university level. This study was conducted by qualitative descriptive design with 92 students and 4 lecturers as respondents. As part of research and development project in one private university in Jakarta, a developed task-based syllabus was based on need analysis and the principles of task-based language teaching. Students’ proficiency levels are fair with sentence patterns and grammar as the most difficult aspects. Academic writing is more preferable orientation with the small portions of creative writing. Then, the developed task-based syllabus has been proposed for writing class which covers the components of goal (learning outcome, course description and objectives, a set of writing tasks, features of content focus and language focus and course evaluation. The developed syllabus, then, can guide the lecturers in designing lesson plan and selecting materials for writing class.

Selective Cooperation in Early Childhood - How to Choose Models and Partners.

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Jonas Hermes

Full Text Available Cooperation is essential for human society, and children engage in cooperation from early on. It is unclear, however, how children select their partners for cooperation. We know that children choose selectively whom to learn from (e.g. preferring reliable over unreliable models on a rational basis. The present study investigated whether children (and adults also choose their cooperative partners selectively and what model characteristics they regard as important for cooperative partners and for informants about novel words. Three- and four-year-old children (N = 64 and adults (N = 14 saw contrasting pairs of models differing either in physical strength or in accuracy (in labeling known objects. Participants then performed different tasks (cooperative problem solving and word learning requiring the choice of a partner or informant. Both children and adults chose their cooperative partners selectively. Moreover they showed the same pattern of selective model choice, regarding a wide range of model characteristics as important for cooperation (preferring both the strong and the accurate model for a strength-requiring cooperation tasks, but only prior knowledge as important for word learning (preferring the knowledgeable but not the strong model for word learning tasks. Young children's selective model choice thus reveals an early rational competence: They infer characteristics from past behavior and flexibly consider what characteristics are relevant for certain tasks.

Spatiotemporal oscillatory dynamics of visual selective attention during a flanker task.

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McDermott, Timothy J; Wiesman, Alex I; Proskovec, Amy L; Heinrichs-Graham, Elizabeth; Wilson, Tony W

2017-08-01

The flanker task is a test of visual selective attention that has been widely used to probe error monitoring, response conflict, and related constructs. However, to date, few studies have focused on the selective attention component of this task and imaged the underlying oscillatory dynamics serving task performance. In this study, 21 healthy adults successfully completed an arrow-based version of the Eriksen flanker task during magnetoencephalography (MEG). All MEG data were pre-processed and transformed into the time-frequency domain. Significant oscillatory brain responses were imaged using a beamforming approach, and voxel time series were extracted from the peak responses to identify the temporal dynamics. Across both congruent and incongruent flanker conditions, our results indicated robust decreases in alpha (9-12Hz) activity in medial and lateral occipital regions, bilateral parietal cortices, and cerebellar areas during task performance. In parallel, increases in theta (3-7Hz) oscillatory activity were detected in dorsal and ventral frontal regions, and the anterior cingulate. As per conditional effects, stronger alpha responses (i.e., greater desynchronization) were observed in parietal, occipital, and cerebellar cortices during incongruent relative to congruent trials, whereas the opposite pattern emerged for theta responses (i.e., synchronization) in the anterior cingulate, left dorsolateral prefrontal, and ventral prefrontal cortices. Interestingly, the peak latency of theta responses in these latter brain regions was significantly correlated with reaction time, and may partially explain the amplitude difference observed between congruent and incongruent trials. Lastly, whole-brain exploratory analyses implicated the frontal eye fields, right temporoparietal junction, and premotor cortices. These findings suggest that regions of both the dorsal and ventral attention networks contribute to visual selective attention processes during incongruent trials

Selective visual scaling of time-scale processes facilitates broadband learning of isometric force frequency tracking.

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King, Adam C; Newell, Karl M

2015-10-01

The experiment investigated the effect of selectively augmenting faster time scales of visual feedback information on the learning and transfer of continuous isometric force tracking tasks to test the generality of the self-organization of 1/f properties of force output. Three experimental groups tracked an irregular target pattern either under a standard fixed gain condition or with selectively enhancement in the visual feedback display of intermediate (4-8 Hz) or high (8-12 Hz) frequency components of the force output. All groups reduced tracking error over practice, with the error lowest in the intermediate scaling condition followed by the high scaling and fixed gain conditions, respectively. Selective visual scaling induced persistent changes across the frequency spectrum, with the strongest effect in the intermediate scaling condition and positive transfer to novel feedback displays. The findings reveal an interdependence of the timescales in the learning and transfer of isometric force output frequency structures consistent with 1/f process models of the time scales of motor output variability.

Motivating Learning in Mathematics Through Collaborative Problem Solving: A Focus on Using Rich Tasks

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Nasreen Hussain

2014-06-01

Full Text Available This paper is based on the concept that lively and interactive math classes are possible by incorporating rich tasks to meet the needs of students operating at different levels in the classrooms. A study was carried out to find out the impact on learning and motivation of using rich tasks at secondary level in the maths class by incorporating co-operative learning. Qualitative research paradigm was opted for the study using an action research approach and the data were collected through two semi-structured interviews conducted at the onset of the research and after the intervention. Few important findings indicate that rich tasks demand different levels of challenge and extend opportunities to those students who need them.

The Effectiveness of the Continuation Task on Second Language Learning of English Articles

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Jiang, Lin

2015-01-01

This article aims to uncover how alignment in the continuation task affects second language (L2) learning of English articles. Two classes of 47 Chinese students participated in the study which employed a pretest-treatment-posttest research design and lasted for a period of 20 weeks. One class received the continuation task treatment, during which…

A Task-Cycling Pedagogy Using Stimulated Refelction and Audio-Conferencing in Foreign Language Learning

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Mike Levy

2004-05-01

Full Text Available The aim of this paper is to describe a task-cycling pedagogy for language learning using a technique we have called Stimulated Reflection. This pedagogical approach has been developed in the light of the new technology options available, especially those that facilitate audiovisual forms of interaction among language learners and teachers. In this instance, the pedagogy is implemented in the context of introducing students to audio-conferencing (A-C tools as a support for their ongoing independent learning. The approach is designed to develop a balance for learners between attention to fluency and meaning on one hand, and form and accuracy on the other. The particular focus here is on the learning of Italian as a foreign language, although the ideas and principles are presented with a view to the teaching and learning of any language. The article is in three parts. The first considers appropriate theoretical frameworks for the use of technology-mediated tools in language learning, with a particular emphasis on the focus-on-form literature and task design (Doughty, 2003; Doughty & Williams, 1998; Skehan, 1998. The second part sets out the approach we have taken in the Italian project and discusses specifically the idea of task cycling (Willis, 1996 and Stimulated Reflection. The third part presents extracts of stimulated reflection episodes that serve to illustrate the new pedagogic approach.

Expectancy-Value Theory in Persistence of Learning Effects in Schizophrenia: Role of Task Value and Perceived Competency

OpenAIRE

Choi, Jimmy; Fiszdon, Joanna M.; Medalia, Alice

2010-01-01

Expectancy-value theory, a widely accepted model of motivation, posits that expectations of success on a learning task and the individual value placed on the task are central determinants of motivation to learn. This is supported by research in healthy controls suggesting that beliefs of self-and-content mastery can be so influential they can predict the degree of improvement on challenging cognitive tasks even more so than general cognitive ability. We examined components of expectancy-value...

A New Semantic List Learning Task to Probe Functioning of the Papez Circuit

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Schallmo, Michael-Paul; Kassel, Michelle T.; Weisenbach, Sara L.; Walker, Sara J.; Guidotti-Breting, Leslie M.; Rao, Julia A.; Hazlett, Kathleen E.; Considine, Ciaran M.; Sethi, Gurpriya; Vats, Naalti; Pecina, Marta; Welsh, Robert C.; Starkman, Monica N.; Giordani, Bruno; Langenecker, Scott A.

2016-01-01

Introduction List learning tasks are powerful clinical tools for studying memory, yet have been relatively underutilized within the functional imaging literature. This limits understanding of regions such as the Papez circuit which support memory performance in healthy, non-demented adults. Method The current study characterized list learning performance in 40 adults who completed a Semantic List Learning Task (SLLT) with a Brown-Peterson manipulation during functional MRI (fMRI). Cued recall with semantic cues, and recognition memory were assessed after imaging. Internal reliability and convergent and discriminant validity were evaluated. Results Subjects averaged 38% accuracy in recall (62% for recognition), with primacy but no recency effects observed. Validity and reliability were demonstrated by showing that the SLLT was correlated with the California Verbal Learning test (CVLT), but not with executive functioning tests, and high intraclass correlation coefficient across lists for recall (.91). fMRI measurements during Encoding (vs. Silent Rehearsal) revealed significant activation in bilateral hippocampus, parahippocampus, and bilateral anterior and posterior cingulate cortex. Post-hoc analyses showed increased activation in anterior and middle hippocampus, subgenual cingulate, and mammillary bodies specific to Encoding. In addition, increasing age was positively associated with increased activation in a diffuse network, particularly frontal cortex and specific Papez regions for correctly recalled words. Gender differences were specific to left inferior and superior frontal cortex. Conclusions This is a clinically relevant list learning task that can be used in studies of groups for which the Papez circuit is damaged or disrupted, in mixed or crossover studies at imaging and clinical sites. PMID:26313512

How task characteristics and social support relate to managerial learning: empirical evidence from Dutch home care.

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Ouweneel, A P Else; Taris, Toon W; Van Zolingen, Simone J; Schreurs, Paul J G

2009-01-01

Researchers have revealed that managers profit most from informal and on-the-job learning. Moreover, research has shown that task characteristics and social support affect informal learning. On the basis of these insights, the authors examined the effects of task characteristics (psychological job demands, job control) and social support from the supervisor and colleagues on informal on-the-job learning among 1588 managers in the Dutch home-care sector. A regression analysis revealed that high demands, high control, and high colleague and supervisor support were each associated with high levels of informal learning. The authors found no evidence for statistical interactions among the effects of these concepts. They concluded that to promote managers' informal workplace learning, employers should especially increase job control.

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

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Simon Gingins

2018-05-01

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

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

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

2018-01-01

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

Upper Extremity Motor Learning among Individuals with Parkinson's Disease: A Meta-Analysis Evaluating Movement Time in Simple Tasks

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K. Felix

2012-01-01

Full Text Available Motor learning has been found to occur in the rehabilitation of individuals with Parkinson's disease (PD. Through repetitive structured practice of motor tasks, individuals show improved performance, confirming that motor learning has probably taken place. Although a number of studies have been completed evaluating motor learning in people with PD, the sample sizes were small and the improvements were variable. The purpose of this meta-analysis was to determine the ability of people with PD to learn motor tasks. Studies which measured movement time in upper extremity reaching tasks and met the inclusion criteria were included in the analysis. Results of the meta-analysis indicated that people with PD and neurologically healthy controls both demonstrated motor learning, characterized by a decrease in movement time during upper extremity movements. Movement time improvements were greater in the control group than in individuals with PD. These results support the findings that the practice of upper extremity reaching tasks is beneficial in reducing movement time in persons with PD and has important implications for rehabilitation.

A Measure of Student Involvement in Learning: Time-on-Task.

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Anderson, Lorin W.

The importance of appropriate task relevant behaviors as a necessary condition for school learning has long been noted. This paper suggests a multiple measure of one set of student classroom behaviors, presents a brief theoretical basis for the measure, provides some empirical support for the use of the measure, and indicates some educational…

A Selective Role for Dopamine in Learning to Maximize Reward But Not to Minimize Effort: Evidence from Patients with Parkinson's Disease.

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Skvortsova, Vasilisa; Degos, Bertrand; Welter, Marie-Laure; Vidailhet, Marie; Pessiglione, Mathias

2017-06-21

Instrumental learning is a fundamental process through which agents optimize their choices, taking into account various dimensions of available options such as the possible reward or punishment outcomes and the costs associated with potential actions. Although the implication of dopamine in learning from choice outcomes is well established, less is known about its role in learning the action costs such as effort. Here, we tested the ability of patients with Parkinson's disease (PD) to maximize monetary rewards and minimize physical efforts in a probabilistic instrumental learning task. The implication of dopamine was assessed by comparing performance ON and OFF prodopaminergic medication. In a first sample of PD patients ( n = 15), we observed that reward learning, but not effort learning, was selectively impaired in the absence of treatment, with a significant interaction between learning condition (reward vs effort) and medication status (OFF vs ON). These results were replicated in a second, independent sample of PD patients ( n = 20) using a simplified version of the task. According to Bayesian model selection, the best account for medication effects in both studies was a specific amplification of reward magnitude in a Q-learning algorithm. These results suggest that learning to avoid physical effort is independent from dopaminergic circuits and strengthen the general idea that dopaminergic signaling amplifies the effects of reward expectation or obtainment on instrumental behavior. SIGNIFICANCE STATEMENT Theoretically, maximizing reward and minimizing effort could involve the same computations and therefore rely on the same brain circuits. Here, we tested whether dopamine, a key component of reward-related circuitry, is also implicated in effort learning. We found that patients suffering from dopamine depletion due to Parkinson's disease were selectively impaired in reward learning, but not effort learning. Moreover, anti-parkinsonian medication restored the

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

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Zendehrouh, Sareh

2015-11-01

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

Multimodal Task-Driven Dictionary Learning for Image Classification

Science.gov (United States)

2015-12-18

recognition, multi-view face recognition, multi-view action recognition, and multimodal biometric recognition. It is also shown that, compared to the...improvement in several multi-task learning applications such as target classification, biometric recognitions, and multiview face recognition [12], [14], [17...relevant samples from other modalities for a given unimodal query. However, α1 α2 …αS D1 … Index finger Thumb finger … Iris x1 x2 xS D2 DS … … … J o in

Extending the Peak Bandwidth of Parameters for Softmax Selection in Reinforcement Learning.

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Iwata, Kazunori

2016-05-11

Softmax selection is one of the most popular methods for action selection in reinforcement learning. Although various recently proposed methods may be more effective with full parameter tuning, implementing a complicated method that requires the tuning of many parameters can be difficult. Thus, softmax selection is still worth revisiting, considering the cost savings of its implementation and tuning. In fact, this method works adequately in practice with only one parameter appropriately set for the environment. The aim of this paper is to improve the variable setting of this method to extend the bandwidth of good parameters, thereby reducing the cost of implementation and parameter tuning. To achieve this, we take advantage of the asymptotic equipartition property in a Markov decision process to extend the peak bandwidth of softmax selection. Using a variety of episodic tasks, we show that our setting is effective in extending the bandwidth and that it yields a better policy in terms of stability. The bandwidth is quantitatively assessed in a series of statistical tests.

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study.

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Liu, Qi; Xu, Qian; Zheng, Vincent W; Xue, Hong; Cao, Zhiwei; Yang, Qiang

2010-04-10

Gene silencing using exogenous small interfering RNAs (siRNAs) is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC) to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs) have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. The knowledge gained from our study provides useful insights on how to analyze various cross-platform RNAi data for uncovering

Multi-task learning for cross-platform siRNA efficacy prediction: an in-silico study

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Xue Hong

2010-04-01

Full Text Available Abstract Background Gene silencing using exogenous small interfering RNAs (siRNAs is now a widespread molecular tool for gene functional study and new-drug target identification. The key mechanism in this technique is to design efficient siRNAs that incorporated into the RNA-induced silencing complexes (RISC to bind and interact with the mRNA targets to repress their translations to proteins. Although considerable progress has been made in the computational analysis of siRNA binding efficacy, few joint analysis of different RNAi experiments conducted under different experimental scenarios has been done in research so far, while the joint analysis is an important issue in cross-platform siRNA efficacy prediction. A collective analysis of RNAi mechanisms for different datasets and experimental conditions can often provide new clues on the design of potent siRNAs. Results An elegant multi-task learning paradigm for cross-platform siRNA efficacy prediction is proposed. Experimental studies were performed on a large dataset of siRNA sequences which encompass several RNAi experiments recently conducted by different research groups. By using our multi-task learning method, the synergy among different experiments is exploited and an efficient multi-task predictor for siRNA efficacy prediction is obtained. The 19 most popular biological features for siRNA according to their jointly importance in multi-task learning were ranked. Furthermore, the hypothesis is validated out that the siRNA binding efficacy on different messenger RNAs(mRNAs have different conditional distribution, thus the multi-task learning can be conducted by viewing tasks at an "mRNA"-level rather than at the "experiment"-level. Such distribution diversity derived from siRNAs bound to different mRNAs help indicate that the properties of target mRNA have important implications on the siRNA binding efficacy. Conclusions The knowledge gained from our study provides useful insights on how to

POSITIVE VERSUS NEGATIVE COMMUNICATION STRATEGIES IN TASK-BASED LEARNING

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Siti Rohani

2013-07-01

Full Text Available This study aimed at describing how the implementation of Task Based Learning (TBL would shape or change students’ use of oral communication strategies. Students’ problems and strategies to solve the problems during the implementation of TBL were also explored. The study was a mixed method, employing both quantitative and qualitative analysis throughmulti-methods of questionnaire, interviews, focus group discussion, learning journals, and classroom observation. Participants were 26 second year students of the State Polytechnic of Malang. Data collection was conducted for one semester. Findingsshow linguistic and non-linguistic problems encountered by students during one-semester implementation of TBL. Students also performedincreased use of positive strategies but reduced use of negative strategies after the implementation of TBL.

Multi-layer network utilizing rewarded spike time dependent plasticity to learn a foraging task.

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Pavel Sanda

2017-09-01

Full Text Available Neural networks with a single plastic layer employing reward modulated spike time dependent plasticity (STDP are capable of learning simple foraging tasks. Here we demonstrate advanced pattern discrimination and continuous learning in a network of spiking neurons with multiple plastic layers. The network utilized both reward modulated and non-reward modulated STDP and implemented multiple mechanisms for homeostatic regulation of synaptic efficacy, including heterosynaptic plasticity, gain control, output balancing, activity normalization of rewarded STDP and hard limits on synaptic strength. We found that addition of a hidden layer of neurons employing non-rewarded STDP created neurons that responded to the specific combinations of inputs and thus performed basic classification of the input patterns. When combined with a following layer of neurons implementing rewarded STDP, the network was able to learn, despite the absence of labeled training data, discrimination between rewarding patterns and the patterns designated as punishing. Synaptic noise allowed for trial-and-error learning that helped to identify the goal-oriented strategies which were effective in task solving. The study predicts a critical set of properties of the spiking neuronal network with STDP that was sufficient to solve a complex foraging task involving pattern classification and decision making.

How Important Are Student-Selected versus Instructor-Selected Literature Resources for Students' Learning and Motivation in Problem-Based Learning?

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Wijnia, Lisette; Loyens, Sofie M.; Derous, Eva; Schmidt, Henk G.

2015-01-01

In problem-based learning students are responsible for their own learning process, which becomes evident when they must act independently, for example, when selecting literature resources for individual study. It is a matter of debate whether it is better to have students select their own literature resources or to present them with a list of…

EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task.

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Küssner, Mats B; de Groot, Annette M B; Hofman, Winni F; Hillen, Marij A

2016-01-01

As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is-partly due to a lack of theory-driven research-no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck's theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence). Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and exact replications

EEG Beta Power but Not Background Music Predicts the Recall Scores in a Foreign-Vocabulary Learning Task.

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Mats B Küssner

Full Text Available As tantalizing as the idea that background music beneficially affects foreign vocabulary learning may seem, there is-partly due to a lack of theory-driven research-no consistent evidence to support this notion. We investigated inter-individual differences in the effects of background music on foreign vocabulary learning. Based on Eysenck's theory of personality we predicted that individuals with a high level of cortical arousal should perform worse when learning with background music compared to silence, whereas individuals with a low level of cortical arousal should be unaffected by background music or benefit from it. Participants were tested in a paired-associate learning paradigm consisting of three immediate word recall tasks, as well as a delayed recall task one week later. Baseline cortical arousal assessed with spontaneous EEG measurement in silence prior to the learning rounds was used for the analyses. Results revealed no interaction between cortical arousal and the learning condition (background music vs. silence. Instead, we found an unexpected main effect of cortical arousal in the beta band on recall, indicating that individuals with high beta power learned more vocabulary than those with low beta power. To substantiate this finding we conducted an exact replication of the experiment. Whereas the main effect of cortical arousal was only present in a subsample of participants, a beneficial main effect of background music appeared. A combined analysis of both experiments suggests that beta power predicts the performance in the word recall task, but that there is no effect of background music on foreign vocabulary learning. In light of these findings, we discuss whether searching for effects of background music on foreign vocabulary learning, independent of factors such as inter-individual differences and task complexity, might be a red herring. Importantly, our findings emphasize the need for sufficiently powered research designs and

FMRQ-A Multiagent Reinforcement Learning Algorithm for Fully Cooperative Tasks.

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Zhang, Zhen; Zhao, Dongbin; Gao, Junwei; Wang, Dongqing; Dai, Yujie

2017-06-01

In this paper, we propose a multiagent reinforcement learning algorithm dealing with fully cooperative tasks. The algorithm is called frequency of the maximum reward Q-learning (FMRQ). FMRQ aims to achieve one of the optimal Nash equilibria so as to optimize the performance index in multiagent systems. The frequency of obtaining the highest global immediate reward instead of immediate reward is used as the reinforcement signal. With FMRQ each agent does not need the observation of the other agents' actions and only shares its state and reward at each step. We validate FMRQ through case studies of repeated games: four cases of two-player two-action and one case of three-player two-action. It is demonstrated that FMRQ can converge to one of the optimal Nash equilibria in these cases. Moreover, comparison experiments on tasks with multiple states and finite steps are conducted. One is box-pushing and the other one is distributed sensor network problem. Experimental results show that the proposed algorithm outperforms others with higher performance.

Role of accentuation in the selection/rejection task framing effect.

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Chen, Jing; Proctor, Robert W

2017-04-01

Procedure invariance is a basic assumption of rational theories of choice, however, it has been shown to be violated: Different response modes, or task frames, sometimes reveal opposite preferences. The current study focused on selection and rejection task frames, involving a unique type of problem with enriched and impoverished options, which has previously led to conflicting findings and theoretical explanations: the compatibility hypothesis (Shafir, 1993) and the accentuation hypothesis (Wedell, 1997). We examined the role of task frame by distinguishing these 2 hypotheses and evaluating the information-processing basis of the choices. Experiments conducted online (Experiments 1 and 3) and in-lab (Experiment 4 with eye-tracking technique) revealed a difference between the 2 task frames in the choice data (i.e., the task-framing effect) as a function of the relative attractiveness of the options. Also, this task-framing effect was not influenced by imposed time constraints (Experiments 5 and 6) and was similarly evident with a more direct measure for the option attractiveness (obtained in Experiment 7). Experiment 2, conducted in a lab setting with verbal-protocol requirements, yielded no task-framing effect, suggesting that a requirement to verbalize reasons for choice minimizes accentuation. With this exception, the choice data are in agreement with the accentuation hypothesis, and the combined findings in choice, decision time, task confusion, and eye-tracking data provide evidence of a basis in cognitive effort rather than motivation, as Wedell proposed. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Selective attention to task-irrelevant emotional distractors is unaffected by the perceptual load associated with a foreground task.

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Hindi Attar, Catherine; Müller, Matthias M

2012-01-01

A number of studies have shown that emotionally arousing stimuli are preferentially processed in the human brain. Whether or not this preference persists under increased perceptual load associated with a task at hand remains an open question. Here we manipulated two possible determinants of the attentional selection process, perceptual load associated with a foreground task and the emotional valence of concurrently presented task-irrelevant distractors. As a direct measure of sustained attentional resource allocation in early visual cortex we used steady-state visual evoked potentials (SSVEPs) elicited by distinct flicker frequencies of task and distractor stimuli. Subjects either performed a detection (low load) or discrimination (high load) task at a centrally presented symbol stream that flickered at 8.6 Hz while task-irrelevant neutral or unpleasant pictures from the International Affective Picture System (IAPS) flickered at a frequency of 12 Hz in the background of the stream. As reflected in target detection rates and SSVEP amplitudes to both task and distractor stimuli, unpleasant relative to neutral background pictures more strongly withdrew processing resources from the foreground task. Importantly, this finding was unaffected by the factor 'load' which turned out to be a weak modulator of attentional processing in human visual cortex.

Selective attention to task-irrelevant emotional distractors is unaffected by the perceptual load associated with a foreground task.

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Catherine Hindi Attar

Full Text Available A number of studies have shown that emotionally arousing stimuli are preferentially processed in the human brain. Whether or not this preference persists under increased perceptual load associated with a task at hand remains an open question. Here we manipulated two possible determinants of the attentional selection process, perceptual load associated with a foreground task and the emotional valence of concurrently presented task-irrelevant distractors. As a direct measure of sustained attentional resource allocation in early visual cortex we used steady-state visual evoked potentials (SSVEPs elicited by distinct flicker frequencies of task and distractor stimuli. Subjects either performed a detection (low load or discrimination (high load task at a centrally presented symbol stream that flickered at 8.6 Hz while task-irrelevant neutral or unpleasant pictures from the International Affective Picture System (IAPS flickered at a frequency of 12 Hz in the background of the stream. As reflected in target detection rates and SSVEP amplitudes to both task and distractor stimuli, unpleasant relative to neutral background pictures more strongly withdrew processing resources from the foreground task. Importantly, this finding was unaffected by the factor 'load' which turned out to be a weak modulator of attentional processing in human visual cortex.

Interhemispheric interaction expands attentional capacity in an auditory selective attention task.

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Scalf, Paige E; Banich, Marie T; Erickson, Andrew B

2009-04-01

Previous work from our laboratory indicates that interhemispheric interaction (IHI) functionally increases the attentional capacity available to support performance on visual tasks (Banich in The asymmetrical brain, pp 261-302, 2003). Because manipulations of both computational complexity and selection demand alter the benefits of IHI to task performance, we argue that IHI may be a general strategy for meeting increases in attentional demand. Other researchers, however, have suggested that the apparent benefits of IHI to attentional capacity are an epiphenomenon of the organization of the visual system (Fecteau and Enns in Neuropsychologia 43:1412-1428, 2005; Marsolek et al. in Neuropsychologia 40:1983-1999, 2002). In the current experiment, we investigate whether IHI increases attentional capacity outside the visual system by manipulating the selection demands of an auditory temporal pattern-matching task. We find that IHI expands attentional capacity in the auditory system. This suggests that the benefits of requiring IHI derive from a functional increase in attentional capacity rather than the organization of a specific sensory modality.

The effects of inspecting and constructing part-task-specific visualizations on team and individual learning

NARCIS (Netherlands)

Slof, Bert; Erkens, Gijsbert; Kirschner, Paul A.; Helms-Lorenz, Michelle

This study examined whether inspecting and constructing different part-task-specific visualizations differentially affects learning. To this end, a complex business-economics problem was structured into three phase-related part-tasks: (1) determining core concepts, (2) proposing multiple solutions,

Brain activity during divided and selective attention to auditory and visual sentence comprehension tasks

OpenAIRE

Moisala, Mona; Salmela, Viljami; Salo, Emma; Carlson, Synnove; Vuontela, Virve; Salonen, Oili; Alho, Kimmo

2015-01-01

Using functional magnetic resonance imaging (fMRI), we measured brain activity of human participants while they performed a sentence congruence judgment task in either the visual or auditory modality separately, or in both modalities simultaneously. Significant performance decrements were observed when attention was divided between the two modalities compared with when one modality was selectively attended. Compared with selective attention (i.e., single tasking), divided attention (i.e., dua...

Nonstrategic Contributions to Putatively Strategic Effects in Selective Attention Tasks

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Risko, Evan F.; Blais, Chris; Stolz, Jennifer A.; Besner, Derek

2008-01-01

Proportion compatible manipulations are often used to index strategic processes in selective attention tasks. Here, a subtle confound in proportion compatible manipulations is considered. Specifically, as the proportion of compatible trials increases, the ratio of complete repetitions and complete alternations to partial repetitions increases on…

Formative use of select-and-fill-in concept maps in online instruction: Implications for students of different learning styles

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Kaminski, Charles William

The purpose of this research was to investigate the formative use of Select and Fill-In (SAFI) maps in online instruction and the cognitive, metacognitive, and affective responses of students to their use. In particular, the implications of their use with students of different learning styles was considered. The research question investigated in this qualitative study was: How do students of different learning styles respond to online instruction in which SAFI maps are utilized? This question was explored by using an emergent, collective case study. Each case consisted of community college students who shared a dominant learning style and were enrolled in an online course in environmental studies. Cases in the study were determined using Kolb's Learning Style Inventory (LSI). Seven forms of data were collected during the study. During the first phase of data collection, dominant learning style and background information on student experience with concept mapping and online instruction was determined. In the second phase of data collection, participants completed SAFI maps and quiz items that corresponded to the content of the maps. Achievement data on the map activities and quiz and student responses to a post-SAFI survey and questionnaire were recorded to identify learner cognitive, metacognitive, and affective responses to the tasks. Upon completion of data collection, cases were constructed and compared across learning styles. Cases are presented using the trends, across participants sharing the same dominant learning style, in achievement, behaviors and attitudes as seen in the evidence present in the data. Triangulation of multiple data sources increased reliability and validity, through cross-case analyses, and produced a thick description of the relationship between the cases for each learning style. Evidence suggesting a cognitive response to the SAFI tasks was inconsistent across cases. However, learners with an affinity towards reflective learning

Uncertainty-handling assessment using nondeterministic learning tasks in pilot selection

OpenAIRE

Matton , Nadine; Raufaste , Éric; Vautier , Stéphane

2008-01-01

International audience; This paper addresses selection for entry into the French commercial pilot ab initio training, namely the ENAC (École Nationale de l'Aviation Civile). Applicants are mainly (more than 80%) coming from scientific preparatory classes for competitive admission to the "Grandes Écoles". Therefore these applicants are hand-picked based on their school grades in mathematics and physics. To give a hint, in 2005, only 15% of the French GCE A-Level students were selected for entr...

Effects of short-term training on behavioral learning and skill acquisition during intraoral fine motor task

DEFF Research Database (Denmark)

Kumar, Abhishek; Grigoriadis, Joannis; Trulsson, Mats

2015-01-01

Sensory information from the orofacial mechanoreceptors are used by the nervous system to optimize the positioning of food, determine the force levels, and force vectors involved in biting of food morsels. Moreover, practice resulting from repetition could be a key to learning and acquiring a motor...... movements. Thirty healthy volunteers were asked to intraorally manipulate and split a chocolate candy, into two equal halves. The participants performed three series (with ten 10 trials) of the task before and after a short-term (approximately 30min) training. The accuracy of the split and vertical jaw...... task induces behavior learning, skill acquisition and optimization of jaw movements in terms of better performance and reduction in the duration of jaw movements, during the task. The finding of the present study provides insights on into how humans learn oral motor behaviors or the kind of adaptation...

Stochastic subset selection for learning with kernel machines.

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Rhinelander, Jason; Liu, Xiaoping P

2012-06-01

Kernel machines have gained much popularity in applications of machine learning. Support vector machines (SVMs) are a subset of kernel machines and generalize well for classification, regression, and anomaly detection tasks. The training procedure for traditional SVMs involves solving a quadratic programming (QP) problem. The QP problem scales super linearly in computational effort with the number of training samples and is often used for the offline batch processing of data. Kernel machines operate by retaining a subset of observed data during training. The data vectors contained within this subset are referred to as support vectors (SVs). The work presented in this paper introduces a subset selection method for the use of kernel machines in online, changing environments. Our algorithm works by using a stochastic indexing technique when selecting a subset of SVs when computing the kernel expansion. The work described here is novel because it separates the selection of kernel basis functions from the training algorithm used. The subset selection algorithm presented here can be used in conjunction with any online training technique. It is important for online kernel machines to be computationally efficient due to the real-time requirements of online environments. Our algorithm is an important contribution because it scales linearly with the number of training samples and is compatible with current training techniques. Our algorithm outperforms standard techniques in terms of computational efficiency and provides increased recognition accuracy in our experiments. We provide results from experiments using both simulated and real-world data sets to verify our algorithm.

Efficient abstraction selection in reinforcement learning

NARCIS (Netherlands)

Seijen, H. van; Whiteson, S.; Kester, L.

2013-01-01

This paper introduces a novel approach for abstraction selection in reinforcement learning problems modelled as factored Markov decision processes (MDPs), for which a state is described via a set of state components. In abstraction selection, an agent must choose an abstraction from a set of

Analytical reasoning task reveals limits of social learning in networks.

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Rahwan, Iyad; Krasnoshtan, Dmytro; Shariff, Azim; Bonnefon, Jean-François

2014-04-06

Social learning-by observing and copying others-is a highly successful cultural mechanism for adaptation, outperforming individual information acquisition and experience. Here, we investigate social learning in the context of the uniquely human capacity for reflective, analytical reasoning. A hallmark of the human mind is its ability to engage analytical reasoning, and suppress false associative intuitions. Through a set of laboratory-based network experiments, we find that social learning fails to propagate this cognitive strategy. When people make false intuitive conclusions and are exposed to the analytic output of their peers, they recognize and adopt this correct output. But they fail to engage analytical reasoning in similar subsequent tasks. Thus, humans exhibit an 'unreflective copying bias', which limits their social learning to the output, rather than the process, of their peers' reasoning-even when doing so requires minimal effort and no technical skill. In contrast to much recent work on observation-based social learning, which emphasizes the propagation of successful behaviour through copying, our findings identify a limit on the power of social networks in situations that require analytical reasoning.

A dissociation between engagement and learning: Enthusiastic instructions fail to reliably improve performance on a memory task.

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Benjamin A Motz

Full Text Available Despite widespread assertions that enthusiasm is an important quality of effective teaching, empirical research on the effect of enthusiasm on learning and memory is mixed and largely inconclusive. To help resolve these inconsistencies, we conducted a carefully-controlled laboratory experiment, investigating whether enthusiastic instructions for a memory task would improve recall accuracy. Scripted videos, either enthusiastic or neutral, were used to manipulate the delivery of task instructions. We also manipulated the sequence of learning items, replicating the spacing effect, a known cognitive technique for memory improvement. Although spaced study reliably improved test performance, we found no reliable effect of enthusiasm on memory performance across two experiments. We did, however, find that enthusiastic instructions caused participants to respond to more item prompts, leaving fewer test questions blank, an outcome typically associated with increased task motivation. We find no support for the popular claim that enthusiastic instruction will improve learning, although it may still improve engagement. This dissociation between motivation and learning is discussed, as well as its implications for education and future research on student learning.

A dissociation between engagement and learning: Enthusiastic instructions fail to reliably improve performance on a memory task.

Science.gov (United States)

Motz, Benjamin A; de Leeuw, Joshua R; Carvalho, Paulo F; Liang, Kaley L; Goldstone, Robert L

2017-01-01

Despite widespread assertions that enthusiasm is an important quality of effective teaching, empirical research on the effect of enthusiasm on learning and memory is mixed and largely inconclusive. To help resolve these inconsistencies, we conducted a carefully-controlled laboratory experiment, investigating whether enthusiastic instructions for a memory task would improve recall accuracy. Scripted videos, either enthusiastic or neutral, were used to manipulate the delivery of task instructions. We also manipulated the sequence of learning items, replicating the spacing effect, a known cognitive technique for memory improvement. Although spaced study reliably improved test performance, we found no reliable effect of enthusiasm on memory performance across two experiments. We did, however, find that enthusiastic instructions caused participants to respond to more item prompts, leaving fewer test questions blank, an outcome typically associated with increased task motivation. We find no support for the popular claim that enthusiastic instruction will improve learning, although it may still improve engagement. This dissociation between motivation and learning is discussed, as well as its implications for education and future research on student learning.

Reversal Learning in Humans and Gerbils: Dynamic Control Network Facilitates Learning.

Science.gov (United States)

Jarvers, Christian; Brosch, Tobias; Brechmann, André; Woldeit, Marie L; Schulz, Andreas L; Ohl, Frank W; Lommerzheim, Marcel; Neumann, Heiko

2016-01-01

Biologically plausible modeling of behavioral reinforcement learning tasks has seen great improvements over the past decades. Less work has been dedicated to tasks involving contingency reversals, i.e., tasks in which the original behavioral goal is reversed one or multiple times. The ability to adjust to such reversals is a key element of behavioral flexibility. Here, we investigate the neural mechanisms underlying contingency-reversal tasks. We first conduct experiments with humans and gerbils to demonstrate memory effects, including multiple reversals in which subjects (humans and animals) show a faster learning rate when a previously learned contingency re-appears. Motivated by recurrent mechanisms of learning and memory for object categories, we propose a network architecture which involves reinforcement learning to steer an orienting system that monitors the success in reward acquisition. We suggest that a model sensory system provides feature representations which are further processed by category-related subnetworks which constitute a neural analog of expert networks. Categories are selected dynamically in a competitive field and predict the expected reward. Learning occurs in sequentialized phases to selectively focus the weight adaptation to synapses in the hierarchical network and modulate their weight changes by a global modulator signal. The orienting subsystem itself learns to bias the competition in the presence of continuous monotonic reward accumulation. In case of sudden changes in the discrepancy of predicted and acquired reward the activated motor category can be switched. We suggest that this subsystem is composed of a hierarchically organized network of dis-inhibitory mechanisms, dubbed a dynamic control network (DCN), which resembles components of the basal ganglia. The DCN selectively activates an expert network, corresponding to the current behavioral strategy. The trace of the accumulated reward is monitored such that large sudden

Autism: Too eager to learn? Event related potential findings of increased dependency on intentional learning in a serial reaction time task.

Science.gov (United States)

Zwart, Fenny S; Vissers, Constance Th W M; van der Meij, Roemer; Kessels, Roy P C; Maes, Joseph H R

2017-09-01

It has been suggested that people with autism spectrum disorder (ASD) have an increased tendency to use explicit (or intentional) learning strategies. This altered learning may play a role in the development of the social communication difficulties characterizing ASD. In the current study, we investigated incidental and intentional sequence learning using a Serial Reaction Time (SRT) task in an adult ASD population. Response times and event related potentials (ERP) components (N2b and P3) were assessed as indicators of learning and knowledge. Findings showed that behaviorally, sequence learning and ensuing explicit knowledge were similar in ASD and typically developing (TD) controls. However, ERP findings showed that learning in the TD group was characterized by an enhanced N2b, while learning in the ASD group was characterized by an enhanced P3. These findings suggest that learning in the TD group might be more incidental in nature, whereas learning in the ASD group is more intentional or effortful. Increased intentional learning might serve as a strategy for individuals with ASD to control an overwhelming environment. Although this led to similar behavioral performances on the SRT task, it is very plausible that this intentional learning has adverse effects in more complex social situations, and hence contributes to the social impairments found in ASD. Autism Res 2017, 10: 1533-1543. © 2017 International Society for Autism Research, Wiley Periodicals, Inc. © 2017 International Society for Autism Research, Wiley Periodicals, Inc.

TMI-2 Lessons Learned Task Force status report and short-term recommendations

International Nuclear Information System (INIS)

1979-07-01

Review of the Three Mile Island accident by the TMI-2 Lessons Learned Task Force has disclosed a number of actions in the areas of design and analysis and plant operations that the Task Force recommends be required in the short term to provide substantial additional protection which is required for the public health and safety. All nuclear power plants in operation or in various stages of construction or licensing action are affected to varying degrees by the specific recommendations. The Task Force is continuing work in areas of general safety criteria, systems design requirements, nuclear power plant operations, and nuclear power plant licensing

Altered brain activation in a reversal learning task unmasks adaptive changes in cognitive control in writer's cramp.

Science.gov (United States)

Zeuner, Kirsten E; Knutzen, Arne; Granert, Oliver; Sablowsky, Simone; Götz, Julia; Wolff, Stephan; Jansen, Olav; Dressler, Dirk; Schneider, Susanne A; Klein, Christine; Deuschl, Günther; van Eimeren, Thilo; Witt, Karsten

2016-01-01

Previous receptor binding studies suggest dopamine function is altered in the basal ganglia circuitry in task-specific dystonia, a condition characterized by contraction of agonist and antagonist muscles while performing specific tasks. Dopamine plays a role in reward-based learning. Using fMRI, this study compared 31 right-handed writer's cramp patients to 35 controls in reward-based learning of a probabilistic reversal-learning task. All subjects chose between two stimuli and indicated their response with their left or right index finger. One stimulus response was rewarded 80%, the other 20%. After contingencies reversal, the second stimulus response was rewarded in 80%. We further linked the DRD2/ANKK1-TaqIa polymorphism, which is associated with 30% reduction of the striatal dopamine receptor density with reward-based learning and assumed impaired reversal learning in A + subjects. Feedback learning in patients was normal. Blood-oxygen level dependent (BOLD) signal in controls increased with negative feedback in the insula, rostral cingulate cortex, middle frontal gyrus and parietal cortex (pFWE based learning. The dACC is connected with the basal ganglia-thalamo-loop modulated by dopaminergic signaling. This finding suggests disturbed integration of reinforcement history in decision making and implicate that the reward system might contribute to the pathogenesis in writer's cramp.

Chinese Preservice Teachers' Professional Identity Links with Education Program Performance: The Roles of Task Value Belief and Learning Motivations.

Science.gov (United States)

Zhang, Yan; Hawk, Skyler T; Zhang, Xiaohui; Zhao, Hongyu

2016-01-01

Professional identity is a key issue spanning the entirety of teachers' career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education) and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA) of courses (both subject and pedagogy courses) was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first 3 years of a teacher-training program indicated that: (1) variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2) professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM); (3) task value belief was positively linked to intrinsic and extrinsic learning motivation; (4) higher extrinsic (but not intrinsic) learning motivation was associated with increased program performance; and (5) task value belief and extrinsic learning motivation were significant mediators in the model.

Chinese Preservice Teachers’ Professional Identity Links with Education Program Performance: The Roles of Task Value Belief and Learning Motivations

Science.gov (United States)

Zhang, Yan; Hawk, Skyler T.; Zhang, Xiaohui; Zhao, Hongyu

2016-01-01

Professional identity is a key issue spanning the entirety of teachers’ career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education) and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA) of courses (both subject and pedagogy courses) was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first 3 years of a teacher-training program indicated that: (1) variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2) professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM); (3) task value belief was positively linked to intrinsic and extrinsic learning motivation; (4) higher extrinsic (but not intrinsic) learning motivation was associated with increased program performance; and (5) task value belief and extrinsic learning motivation were significant mediators in the model. PMID:27199810

Effect of task-related continuous auditory feedback during learning of tracking motion exercises

Directory of Open Access Journals (Sweden)

Rosati Giulio

2012-10-01

Full Text Available Abstract Background This paper presents the results of a set of experiments in which we used continuous auditory feedback to augment motor training exercises. This feedback modality is mostly underexploited in current robotic rehabilitation systems, which usually implement only very basic auditory interfaces. Our hypothesis is that properly designed continuous auditory feedback could be used to represent temporal and spatial information that could in turn, improve performance and motor learning. Methods We implemented three different experiments on healthy subjects, who were asked to track a target on a screen by moving an input device (controller with their hand. Different visual and auditory feedback modalities were envisaged. The first experiment investigated whether continuous task-related auditory feedback can help improve performance to a greater extent than error-related audio feedback, or visual feedback alone. In the second experiment we used sensory substitution to compare different types of auditory feedback with equivalent visual feedback, in order to find out whether mapping the same information on a different sensory channel (the visual channel yielded comparable effects with those gained in the first experiment. The final experiment applied a continuously changing visuomotor transformation between the controller and the screen and mapped kinematic information, computed in either coordinate system (controller or video, to the audio channel, in order to investigate which information was more relevant to the user. Results Task-related audio feedback significantly improved performance with respect to visual feedback alone, whilst error-related feedback did not. Secondly, performance in audio tasks was significantly better with respect to the equivalent sensory-substituted visual tasks. Finally, with respect to visual feedback alone, video-task-related sound feedback decreased the tracking error during the learning of a novel

Task Experience as a Boundary Condition for the Negative Effects of Irrelevant Information on Learning

NARCIS (Netherlands)

G. Rop (Gertjan); M. van Wermeskerken (Margot); J.A. de Nooijer (Jacqueline); P.P.J.L. Verkoeijen (Peter); T.A.J.M. van Gog (Tamara)

2016-01-01

textabstractResearch on multimedia learning has shown that learning is hampered when a multimedia message includes extraneous information that is not relevant for the task, because processing the extraneous information uses up scarce attention and working memory resources. However, eye-tracking

Improving Learning Tasks for Mentally Handicapped People Using AmI Environments Based on Cyber-Physical Systems

Directory of Open Access Journals (Sweden)

Diego Martín

2018-01-01

Full Text Available A prototype to improve learning tasks for mentally handicapped people is shown in this research paper using ambient intelligence techniques and based on cyber-physical systems. The whole system is composed of a worktable, a cyber-glove (both with several RFID and NFC detection zones, and an AmI software application for modeling and workflow guidance. A case study was carried out by the authors where sixteen mentally handicapped people and 3 trainers were involved in the experiment. The experiment consisted in the execution of several memorization tasks of movements of objects using the approach presented in this paper. The results obtained were very interesting, indicating that this kind of solutions are feasible and allow the learning of complex tasks to some types of mentally handicapped people. In addition, at the end of the paper are presented some lessons learned after performing the experimentation.

Fast Gaussian kernel learning for classification tasks based on specially structured global optimization.

Science.gov (United States)

Zhong, Shangping; Chen, Tianshun; He, Fengying; Niu, Yuzhen

2014-09-01

For a practical pattern classification task solved by kernel methods, the computing time is mainly spent on kernel learning (or training). However, the current kernel learning approaches are based on local optimization techniques, and hard to have good time performances, especially for large datasets. Thus the existing algorithms cannot be easily extended to large-scale tasks. In this paper, we present a fast Gaussian kernel learning method by solving a specially structured global optimization (SSGO) problem. We optimize the Gaussian kernel function by using the formulated kernel target alignment criterion, which is a difference of increasing (d.i.) functions. Through using a power-transformation based convexification method, the objective criterion can be represented as a difference of convex (d.c.) functions with a fixed power-transformation parameter. And the objective programming problem can then be converted to a SSGO problem: globally minimizing a concave function over a convex set. The SSGO problem is classical and has good solvability. Thus, to find the global optimal solution efficiently, we can adopt the improved Hoffman's outer approximation method, which need not repeat the searching procedure with different starting points to locate the best local minimum. Also, the proposed method can be proven to converge to the global solution for any classification task. We evaluate the proposed method on twenty benchmark datasets, and compare it with four other Gaussian kernel learning methods. Experimental results show that the proposed method stably achieves both good time-efficiency performance and good classification performance. Copyright © 2014 Elsevier Ltd. All rights reserved.

Cognitive Developmental Level Gender, and the Development of Learned Helplessness on Mathematical Calculation and Reasoning Tasks.

Science.gov (United States)

Monaco, Nanci M.; Gentile, J. Ronald

1987-01-01

This study was designed to test whether a learned helplessness treatment would decrease performance on mathematical tasks and to extend learned helplessness findings to include the cognitive development dimension. Results showed no differential advantages to either sex in resisting effects of learned helplessness or in benefiting from strategy…

Robot soccer action selection based on Q learning

Institute of Scientific and Technical Information of China (English)

无

2001-01-01

This paper researches robot soccer action selection based on Q learning . The robot learn to activate particular behavior given their current situation and reward signal. We adopt neural network to implementations of Q learning for their generalization properties and limited computer memory requirements

Feature diagnosticity and task context shape activity in human scene-selective cortex.

Science.gov (United States)

Lowe, Matthew X; Gallivan, Jason P; Ferber, Susanne; Cant, Jonathan S

2016-01-15

Scenes are constructed from multiple visual features, yet previous research investigating scene processing has often focused on the contributions of single features in isolation. In the real world, features rarely exist independently of one another and likely converge to inform scene identity in unique ways. Here, we utilize fMRI and pattern classification techniques to examine the interactions between task context (i.e., attend to diagnostic global scene features; texture or layout) and high-level scene attributes (content and spatial boundary) to test the novel hypothesis that scene-selective cortex represents multiple visual features, the importance of which varies according to their diagnostic relevance across scene categories and task demands. Our results show for the first time that scene representations are driven by interactions between multiple visual features and high-level scene attributes. Specifically, univariate analysis of scene-selective cortex revealed that task context and feature diagnosticity shape activity differentially across scene categories. Examination using multivariate decoding methods revealed results consistent with univariate findings, but also evidence for an interaction between high-level scene attributes and diagnostic visual features within scene categories. Critically, these findings suggest visual feature representations are not distributed uniformly across scene categories but are shaped by task context and feature diagnosticity. Thus, we propose that scene-selective cortex constructs a flexible representation of the environment by integrating multiple diagnostically relevant visual features, the nature of which varies according to the particular scene being perceived and the goals of the observer. Copyright © 2015 Elsevier Inc. All rights reserved.

Impaired Value Learning for Faces in Preschoolers With Autism Spectrum Disorder.

Science.gov (United States)

Wang, Quan; DiNicola, Lauren; Heymann, Perrine; Hampson, Michelle; Chawarska, Katarzyna

2018-01-01

One of the common findings in autism spectrum disorder (ASD) is limited selective attention toward social objects, such as faces. Evidence from both human and nonhuman primate studies suggests that selection of objects for processing is guided by the appraisal of object values. We hypothesized that impairments in selective attention in ASD may reflect a disruption of a system supporting learning about object values in the social domain. We examined value learning in social (faces) and nonsocial (fractals) domains in preschoolers with ASD (n = 25) and typically developing (TD) controls (n = 28), using a novel value learning task implemented on a gaze-contingent eye-tracking platform consisting of value learning and a selective attention choice test. Children with ASD performed more poorly than TD controls on the social value learning task, but both groups performed similarly on the nonsocial task. Within-group comparisons indicated that value learning in TD children was enhanced on the social compared to the nonsocial task, but no such enhancement was seen in children with ASD. Performance in the social and nonsocial conditions was correlated in the ASD but not in the TD group. The study provides support for a domain-specific impairment in value learning for faces in ASD, and suggests that, in ASD, value learning in social and nonsocial domains may rely on a shared mechanism. These findings have implications both for models of selective social attention deficits in autism and for identification of novel treatment targets. Copyright © 2017 American Academy of Child and Adolescent Psychiatry. Published by Elsevier Inc. All rights reserved.

Dual-task results and the lateralization of spatial orientation: artifact of test selection?

Science.gov (United States)

Bowers, C A; Milham, L M; Price, C

1998-01-01

An investigation was conducted to identify the degree to which results regarding the lateralization of spatial orientation among men and women are artifacts of test selection. A dual-task design was used to study possible lateralization differences, providing baseline and dual-task measures of spatial-orientation performance, right- and left-hand tapping, and vocalization of "cat, dog, horse." The Guilford-Zimmerman Test (Guilford & Zimmerman, 1953), the Eliot-Price Test (Eliot & Price, 1976), and the Stumpf-Fay Cube Perspectives Test (Stumpf & Fay, 1983) were the three spatial-orientation tests used to investigate possible artifacts of test selection. Twenty-eight right-handed male and 39 right-handed female undergraduates completed random baseline and dual-task sessions. Analyses indicated no significant sex-related differences in spatial-orientation ability for all three tests. Furthermore, there was no evidence of differential lateralization of spatial orientation between the sexes.

Novel Automatic Filter-Class Feature Selection for Machine Learning Regression

DEFF Research Database (Denmark)

Wollsen, Morten Gill; Hallam, John; Jørgensen, Bo Nørregaard

2017-01-01

With the increased focus on application of Big Data in all sectors of society, the performance of machine learning becomes essential. Efficient machine learning depends on efficient feature selection algorithms. Filter feature selection algorithms are model-free and therefore very fast, but require...... model in the feature selection process. PCA is often used in machine learning litterature and can be considered the default feature selection method. RDESF outperformed PCA in both experiments in both prediction error and computational speed. RDESF is a new step into filter-based automatic feature...

Rapid e-Learning Tools Selection Process for Cognitive and Psychomotor Learning Objectives

Science.gov (United States)

Ku, David Tawei; Huang, Yung-Hsin

2012-01-01

This study developed a decision making process for the selection of rapid e-learning tools that could match different learning domains. With the development of the Internet, the speed of information updates has become faster than ever. E-learning has rapidly become the mainstream for corporate training and academic instruction. In order to reduce…

Learning-induced uncertainty reduction in perceptual decisions is task-dependent

Directory of Open Access Journals (Sweden)

Feitong eYang

2014-05-01

Full Text Available Perceptual decision making in which decisions are reached primarily from extracting and evaluating sensory information requires close interactions between the sensory system and decision-related networks in the brain. Uncertainty pervades every aspect of this process and can be considered related to either the stimulus signal or decision criterion. Here, we investigated the learning-induced reduction of both the signal and criterion uncertainty in two perceptual decision tasks based on two Glass pattern stimulus sets. This was achieved by manipulating spiral angle and signal level of radial and concentric Glass patterns. The behavioral results showed that the participants trained with a task based on criterion comparison improved their categorization accuracy for both tasks, whereas the participants who were trained on a task based on signal detection improved their categorization accuracy only on their trained task. We fitted the behavioral data with a computational model that can dissociate the contribution of the signal and criterion uncertainties. The modeling results indicated that the participants trained on the criterion comparison task reduced both the criterion and signal uncertainty. By contrast, the participants who were trained on the signal detection task only reduced their signal uncertainty after training. Our results suggest that the signal uncertainty can be resolved by training participants to extract signals from noisy environments and to discriminate between clear signals, which are evidenced by reduced perception variance after both training procedures. Conversely, the criterion uncertainty can only be resolved by the training of fine discrimination. These findings demonstrate that uncertainty in perceptual decision-making can be reduced with training but that the reduction of different types of uncertainty is task-dependent.

Selective Inhibition and Naming Performance in Semantic Blocking, Picture-Word Interference, and Color-Word Stroop Tasks

Science.gov (United States)

Shao, Zeshu; Roelofs, Ardi; Martin, Randi C.; Meyer, Antje S.

2015-01-01

In 2 studies, we examined whether explicit distractors are necessary and sufficient to evoke selective inhibition in 3 naming tasks: the semantic blocking, picture-word interference, and color-word Stroop task. Delta plots were used to quantify the size of the interference effects as a function of reaction time (RT). Selective inhibition was…

Chinese preservice teachers’ professional identity links with education program performance: The roles of task value belief and learning motivations

Directory of Open Access Journals (Sweden)

Yan eZhang

2016-04-01

Full Text Available AbstractProfessional identity is a key issue spanning the entirety of teachers’ career development. Despite the abundance of existing research examining professional identity, its link with occupation-related behavior at the primary career stage (i.e., GPA in preservice education and the potential process that underlies this association is still not fully understood. This study explored the professional identity of Chinese preservice teachers, and its links with task value belief, intrinsic learning motivation, extrinsic learning motivation, and performance in the education program. Grade-point average (GPA of courses (both subject and pedagogy courses was examined as an indicator of performance, and questionnaires were used to measure the remaining variables. Data from 606 preservice teachers in the first three years of a teacher-training program indicated that: (1 variables in this research were all significantly correlated with each other, except the correlation between intrinsic learning motivation and program performance; (2 professional identity was positively linked to task value belief, intrinsic and extrinsic learning motivations, and program performance in a structural equation model (SEM; (3 task value belief was positively linked to intrinsic and extrinsic learning motivation; (4 higher extrinsic (but not intrinsic learning motivation was associated with increased program performance; and (5 task value belief and extrinsic learning motivation were significant mediators in the model.

The Effect of Using Online Collaborative Tasks on Incidental Vocabulary Learning of Impulsive vs. Reflective Iranian EFL Learners

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Khalil Motallebzadeh

2017-09-01

Full Text Available Incidental vocabulary learning is one of the most significant sources of learning vocabulary for language learners Laufer  & Hulstjin, 2001. This study endeavored to investigate the effect of using online collaborative tasks on incidental vocabulary learning of impulsive vs. reflective Iranian EFL learners. To this end, Nelson vocabulary proficiency test was administered to 100 Iranian EFL learners as the homogeneity test and the pretest. Using random sampling procedure, 75 learners were selected as the main participants for this study. Kember, McKay, Sinclair and Wong (2008 reflective thinking questionnaire was administered to these learners, based on which they were distinguished based on their cognitive thinking styles, i.e., impulsivity and reflectivity. The participants were homogenously distributed into 3 main groups (impulsive experimental group, reflective experimental group, and the control group. All participants went through 4 weeks of treatment. Experimental groups were conducted using Telegram software and the control group was conducted in a classroom. The results of t-test after 4 weeks of treatment revealed that reflective learners benefited from online collaborative groups with regard to incidental vocabulary learning. The findings of the study are discussed in light of previous research.

Enhancement of selective attention by tDCS: interaction with interference in a Sternberg task

NARCIS (Netherlands)

Gladwin, T.E.; den Uyl, T.E.; Fregni, F.F.; Wiers, R.W.

2012-01-01

Transcranial Direct Current Stimulation (tDCS) enhances performance on working memory tasks. However, such effects may be dependent on modulation of specific aspects of working memory. We therefore tested the hypothesis that tDCS improves selective attention in the context of a Sternberg task.

The Role of Self-Regulated Learning Capacities in Iranian EFL Undergraduates’ Argumentative Writing Task Performance

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Ali Akbar Khomeijani Farahani

2017-09-01

Full Text Available The current study was an attempt to explore the relationship between Iranian EFL learners’ self-regulatory capacities and their argumentative writing task performance in order to analyze measures of complexity, accuracy, and fluency (CAF. To this end, 44 Iranian EFL undergraduates majoring in English literature at the University of Tehran were recruited based on convenience sampling to participate in this study. Employing a correlational design, the participants were required to perform an argumentative writing task and complete the Motivated Strategies for Learning Questionnaire designed by Pintrich, Smith, Garcia, and McKeachie (1991. Pearson product moment correlation indicated a significant relationship between self-regulated learning and writing task performance in relation to CAF measures. In addition, the results of multiple regression showed that resource management strategies and value component predicted 56.9% of grammatical accuracy of writing task. It was also shown that resource management strategies, value, and expectancy components predicted 56.5% of lexical complexity of writing task. Lastly, cognitive and metacognitive strategies, expectancy, and value components predicted 55.2% of the fluency of writing task. The findings of this study informs EFL writing pedagogy and English language teachers and syllabus designers  with regard to the benefits of applying self-regulatory strategies in teaching and assessing writing.

Feature-selective Attention in Frontoparietal Cortex: Multivoxel Codes Adjust to Prioritize Task-relevant Information.

Science.gov (United States)

Jackson, Jade; Rich, Anina N; Williams, Mark A; Woolgar, Alexandra

2017-02-01

Human cognition is characterized by astounding flexibility, enabling us to select appropriate information according to the objectives of our current task. A circuit of frontal and parietal brain regions, often referred to as the frontoparietal attention network or multiple-demand (MD) regions, are believed to play a fundamental role in this flexibility. There is evidence that these regions dynamically adjust their responses to selectively process information that is currently relevant for behavior, as proposed by the "adaptive coding hypothesis" [Duncan, J. An adaptive coding model of neural function in prefrontal cortex. Nature Reviews Neuroscience, 2, 820-829, 2001]. Could this provide a neural mechanism for feature-selective attention, the process by which we preferentially process one feature of a stimulus over another? We used multivariate pattern analysis of fMRI data during a perceptually challenging categorization task to investigate whether the representation of visual object features in the MD regions flexibly adjusts according to task relevance. Participants were trained to categorize visually similar novel objects along two orthogonal stimulus dimensions (length/orientation) and performed short alternating blocks in which only one of these dimensions was relevant. We found that multivoxel patterns of activation in the MD regions encoded the task-relevant distinctions more strongly than the task-irrelevant distinctions: The MD regions discriminated between stimuli of different lengths when length was relevant and between the same objects according to orientation when orientation was relevant. The data suggest a flexible neural system that adjusts its representation of visual objects to preferentially encode stimulus features that are currently relevant for behavior, providing a neural mechanism for feature-selective attention.

The effects of response cost and species-typical behaviors on a daily time-place learning task.

Science.gov (United States)

Deibel, Scott H; Thorpe, Christina M

2013-03-01

Two theories that have been hypothesized to mediate acquisition in daily time-place learning (TPL) tasks were investigated in a free operant daily TPL task: the response cost hypothesis and the species-typical behavior hypothesis. One lever at the end of one of the choice arms of a T-maze provided food in the morning, and 6 h later, a lever in the other choice arm provided food. Four groups were used to assess the effect of two possible sources of response cost: physical effort of the task and costs associated with foraging ecology. One group was used to assess the effect of explicitly allowing for species-typical behaviors. If only first arm choice data were considered, there was little evidence of learning. However, both first press and percentage of presses on the correct lever prior to the first reinforcement revealed evidence of TPL in most rats tested. Unexpectedly, the high response cost groups for both of the proposed sources did not perform better than the low response cost groups. The groups that allowed animals to display species-typical behaviors performed the worst. Skip session probe trials confirmed that the majority of the rats that acquired the task were using a circadian timing strategy. The results from the present study suggest that learning in free operant daily TPL tasks might not be dependent on response cost.

CONFIDENCE MASTERY AS THE FUNDAMENTAL TASK IN LEARNING A FOREIGN LANGUAGE

Directory of Open Access Journals (Sweden)

KOTEKOVÁ, Daniela

2013-06-01

Full Text Available The aim of language learning is not only to achieve an academic success carried out by a fluent speaking; mastering the grammar and vocabulary but it should also focus on the psychological comfort and the intrinsic readiness of the students to participate in their education - to receive and perform. The learners’ self-esteem plays the fundamental role in any language classroom but gaining it is the task on its own and can be quite a challenge for the teachers. How students feel is closely related to their ability to learn. Teachers’ task is thus not only to provide knowledge and information but first of all they should immerse themselves into the student’s mind and discover the best way to awake learner’s will to communicate. This paper focuses on two kinds of aspects participating on the emotional state of the learner, academic and psychological. The students of two different levels of English have answered the questionnaire, assessing their attitude, anxiety and motivation towards learning English. Each opinion has been evaluated and put into relationship with the ability to relax, understand, learn and enjoy at the same time. Their analyses have become the base of several teaching techniques that would build and encourage the students’ confidence as the main condition to start any cognitive process. If confidence is the cause or the outcome of mastering a foreign language was the question asked and answered in this work. Confidence mastery has thus played the fundamental role in the present survey.

Heterogeneous Face Attribute Estimation: A Deep Multi-Task Learning Approach.

Science.gov (United States)

Han, Hu; K Jain, Anil; Shan, Shiguang; Chen, Xilin

2017-08-10

Face attribute estimation has many potential applications in video surveillance, face retrieval, and social media. While a number of methods have been proposed for face attribute estimation, most of them did not explicitly consider the attribute correlation and heterogeneity (e.g., ordinal vs. nominal and holistic vs. local) during feature representation learning. In this paper, we present a Deep Multi-Task Learning (DMTL) approach to jointly estimate multiple heterogeneous attributes from a single face image. In DMTL, we tackle attribute correlation and heterogeneity with convolutional neural networks (CNNs) consisting of shared feature learning for all the attributes, and category-specific feature learning for heterogeneous attributes. We also introduce an unconstrained face database (LFW+), an extension of public-domain LFW, with heterogeneous demographic attributes (age, gender, and race) obtained via crowdsourcing. Experimental results on benchmarks with multiple face attributes (MORPH II, LFW+, CelebA, LFWA, and FotW) show that the proposed approach has superior performance compared to state of the art. Finally, evaluations on a public-domain face database (LAP) with a single attribute show that the proposed approach has excellent generalization ability.

Transfer and Multi-task Learning in QSAR Modeling: Advances and Challenges

Directory of Open Access Journals (Sweden)

Rodolfo S. Simões

2018-02-01

Full Text Available Medicinal chemistry projects involve some steps aiming to develop a new drug, such as the analysis of biological targets related to a given disease, the discovery and the development of drug candidates for these targets, performing parallel biological tests to validate the drug effectiveness and side effects. Approaches as quantitative study of activity-structure relationships (QSAR involve the construction of predictive models that relate a set of descriptors of a chemical compound series and its biological activities with respect to one or more targets in the human body. Datasets used to perform QSAR analyses are generally characterized by a small number of samples and this makes them more complex to build accurate predictive models. In this context, transfer and multi-task learning techniques are very suitable since they take information from other QSAR models to the same biological target, reducing efforts and costs for generating new chemical compounds. Therefore, this review will present the main features of transfer and multi-task learning studies, as well as some applications and its potentiality in drug design projects.

The cerebellum does more than sensory prediction error-based learning in sensorimotor adaptation tasks.

Science.gov (United States)

Butcher, Peter A; Ivry, Richard B; Kuo, Sheng-Han; Rydz, David; Krakauer, John W; Taylor, Jordan A

2017-09-01

Individuals with damage to the cerebellum perform poorly in sensorimotor adaptation paradigms. This deficit has been attributed to impairment in sensory prediction error-based updating of an internal forward model, a form of implicit learning. These individuals can, however, successfully counter a perturbation when instructed with an explicit aiming strategy. This successful use of an instructed aiming strategy presents a paradox: In adaptation tasks, why do individuals with cerebellar damage not come up with an aiming solution on their own to compensate for their implicit learning deficit? To explore this question, we employed a variant of a visuomotor rotation task in which, before executing a movement on each trial, the participants verbally reported their intended aiming location. Compared with healthy control participants, participants with spinocerebellar ataxia displayed impairments in both implicit learning and aiming. This was observed when the visuomotor rotation was introduced abruptly ( experiment 1 ) or gradually ( experiment 2 ). This dual deficit does not appear to be related to the increased movement variance associated with ataxia: Healthy undergraduates showed little change in implicit learning or aiming when their movement feedback was artificially manipulated to produce similar levels of variability ( experiment 3 ). Taken together the results indicate that a consequence of cerebellar dysfunction is not only impaired sensory prediction error-based learning but also a difficulty in developing and/or maintaining an aiming solution in response to a visuomotor perturbation. We suggest that this dual deficit can be explained by the cerebellum forming part of a network that learns and maintains action-outcome associations across trials. NEW & NOTEWORTHY Individuals with cerebellar pathology are impaired in sensorimotor adaptation. This deficit has been attributed to an impairment in error-based learning, specifically, from a deficit in using sensory

Effects of task-irrelevant grouping on visual selection in partial report

DEFF Research Database (Denmark)

Lunau, Rasmus; Habekost, Thomas

2017-01-01

and the selection criterion was luminance. This effect was accompanied by impaired selectivity in unsorted-color trials. Overall, the results suggest that the benefit of task-irrelevant color grouping of targets is contingent on the processing locus of the selection criterion....... the color of the elements in these trials. In the sorted-color condition, the color of the display elements was arranged according to the selection criterion, and in the unsorted-color condition, colors were randomly assigned. The distractor cost was inferred by subtracting performance in partial......-report trials from performance in a control condition that had no distractors in the display. Across five experiments, we manipulated trial order, selection criterion, and exposure duration, and found that attentional selectivity was improved in sorted-color trials when the exposure duration was 200 ms...

Feature and Region Selection for Visual Learning.

Science.gov (United States)

Zhao, Ji; Wang, Liantao; Cabral, Ricardo; De la Torre, Fernando

2016-03-01

Visual learning problems, such as object classification and action recognition, are typically approached using extensions of the popular bag-of-words (BoWs) model. Despite its great success, it is unclear what visual features the BoW model is learning. Which regions in the image or video are used to discriminate among classes? Which are the most discriminative visual words? Answering these questions is fundamental for understanding existing BoW models and inspiring better models for visual recognition. To answer these questions, this paper presents a method for feature selection and region selection in the visual BoW model. This allows for an intermediate visualization of the features and regions that are important for visual learning. The main idea is to assign latent weights to the features or regions, and jointly optimize these latent variables with the parameters of a classifier (e.g., support vector machine). There are four main benefits of our approach: 1) our approach accommodates non-linear additive kernels, such as the popular χ(2) and intersection kernel; 2) our approach is able to handle both regions in images and spatio-temporal regions in videos in a unified way; 3) the feature selection problem is convex, and both problems can be solved using a scalable reduced gradient method; and 4) we point out strong connections with multiple kernel learning and multiple instance learning approaches. Experimental results in the PASCAL VOC 2007, MSR Action Dataset II and YouTube illustrate the benefits of our approach.

The Multidimensional Card Selection Task: A new way to measure concurrent cognitive flexibility in preschoolers.

Science.gov (United States)

Podjarny, Gal; Kamawar, Deepthi; Andrews, Katherine

2017-07-01

Most executive function research examining preschoolers' cognitive flexibility, the ability to think about something in more than one way, has focused on preschoolers' facility for sequentially switching their attention from one dimension to another (e.g., sorting bivalent cards first by color and then by shape). We know very little about preschoolers' ability to coordinate more than one dimension simultaneously (concurrent cognitive flexibility). Here we report on a new task, the Multidimensional Card Selection Task, which was designed to measure children's ability to consider two dimensions, and then three dimensions, concurrently (e.g., shape and size, and then shape, size, and color). More than half of the preschoolers in our sample of 107 (50 3-year-olds and 57 4-year-olds) could coordinate three dimensions simultaneously and consistently across three test trials. Furthermore, performance on the Multidimensional Card Selection Task was related, but not identical, to performance on other cognitive tasks, including a widely used measure of switching cognitive flexibility (the Dimensional Change Card Sort). The Multidimensional Card Selection Task provides a new way to measure concurrent cognitive flexibility in preschoolers, and opens another avenue for exploring the emergence of early cognitive flexibility development. Copyright © 2017 Elsevier Inc. All rights reserved.

Cathodal Transcranial Direct Current Stimulation Over Left Dorsolateral Prefrontal Cortex Area Promotes Implicit Motor Learning in a Golf Putting Task.

Science.gov (United States)

Zhu, Frank F; Yeung, Andrew Y; Poolton, Jamie M; Lee, Tatia M C; Leung, Gilberto K K; Masters, Rich S W

2015-01-01

Implicit motor learning is characterized by low dependence on working memory and stable performance despite stress, fatigue, or multi-tasking. However, current paradigms for implicit motor learning are based on behavioral interventions that are often task-specific and limited when applied in practice. To investigate whether cathodal transcranial direct current stimulation (tDCS) over the left dorsolateral prefrontal cortex (DLPFC) area during motor learning suppressed working memory activity and reduced explicit verbal-analytical involvement in movement control, thereby promoting implicit motor learning. Twenty-seven healthy individuals practiced a golf putting task during a Training Phase while receiving either real cathodal tDCS stimulation over the left DLPFC area or sham stimulation. Their performance was assessed during a Test phase on another day. Verbal working memory capacity was assessed before and after the Training Phase, and before the Test Phase. Compared to sham stimulation, real stimulation suppressed verbal working memory activity after the Training Phase, but enhanced golf putting performance during the Training Phase and the Test Phase, especially when participants were required to multi-task. Cathodal tDCS over the left DLPFC may foster implicit motor learning and performance in complex real-life motor tasks that occur during sports, surgery or motor rehabilitation. Copyright © 2015 Elsevier Inc. All rights reserved.

Dual learning processes in interactive skill acquisition.

Science.gov (United States)

Fu, Wai-Tat; Anderson, John R

2008-06-01

Acquisition of interactive skills involves the use of internal and external cues. Experiment 1 showed that when actions were interdependent, learning was effective with and without external cues in the single-task condition but was effective only with the presence of external cues in the dual-task condition. In the dual-task condition, actions closer to the feedback were learned faster than actions farther away but this difference was reversed in the single-task condition. Experiment 2 tested how knowledge acquired in single and dual-task conditions would transfer to a new reward structure. Results confirmed the two forms of learning mediated by the secondary task: A declarative memory encoding process that simultaneously assigned credits to actions and a reinforcement-learning process that slowly propagated credits backward from the feedback. The results showed that both forms of learning were engaged during training, but only at the response selection stage, one form of knowledge may dominate over the other depending on the availability of attentional resources. (c) 2008 APA, all rights reserved

Task Rotation: Strategies for Differentiating Activities and Assessments by Learning Style. A Strategic Teacher PLC Guide

Science.gov (United States)

Silver, Harvey; Moirao, Daniel; Jackson, Joyce

2011-01-01

One of the hardest jobs in teaching is to differentiate learning activities and assessments to your students' learning styles. But you and your colleagues can learn how to do this together when each of you has this guide to the Task Rotation strategy from our ultimate guide to teaching strategies, "The Strategic Teacher". Use the guide in your…

It's the situation that matters : Affective involvement in context-oriented learning tasks

NARCIS (Netherlands)

Fechner, Sabine; van Vorst, H.; Kölbach, E.; Sumfleth, E.

2014-01-01

This chapter focuses on the evaluation of affective variables in contextbased learning (cbl) environments. Although the majority of studies in the field have shown positive effects on attitude, the need to investigate specific elements of cbl tasks has become evident. On the basis of prior research

Development of Selective Attention in Reflective and Impulsive Children.

Science.gov (United States)

Weiner, Alan S.; Berzonsky, Michael D.

Selective attention was assessed in second, fourth, and sixth grade reflective and impulsive children with an incidental learning task using pictures (animal-household object pairs) or shapes (colored forms) as stimuli. By the sixth grade, reflective children displayed less incidental learning and greater central learning than impulsive children…

Information access in a dual-task context: testing a model of optimal strategy selection

Science.gov (United States)

Wickens, C. D.; Seidler, K. S.

1997-01-01

Pilots were required to access information from a hierarchical aviation database by navigating under single-task conditions (Experiment 1) and when this task was time-shared with an altitude-monitoring task of varying bandwidth and priority (Experiment 2). In dual-task conditions, pilots had 2 viewports available, 1 always used for the information task and the other to be allocated to either task. Dual-task strategy, inferred from the decision of which task to allocate to the 2nd viewport, revealed that allocation was generally biased in favor of the monitoring task and was only partly sensitive to the difficulty of the 2 tasks and their relative priorities. Some dominant sources of navigational difficulties failed to adaptively influence selection strategy. The implications of the results are to provide tools for jumping to the top of the database, to provide 2 viewports into the common database, and to provide training as to the optimum viewport management strategy in a multitask environment.

Effects of Classroom Bilingualism on Task Shifting, Verbal Memory, and Word Learning in Children

Science.gov (United States)

Kaushanskaya, Margarita; Gross, Megan; Buac, Milijana

2014-01-01

We examined the effects of classroom bilingual experience in children on an array of cognitive skills. Monolingual English-speaking children were compared with children who spoke English as the native language and who had been exposed to Spanish in the context of dual-immersion schooling for an average of two years. The groups were compared on a measure of non-linguistic task-shifting; measures of verbal short-term and working memory; and measures of word-learning. The two groups of children did not differ on measures of non-linguistic task-shifting and verbal short-term memory. However, the classroom-exposure bilingual group outperformed the monolingual group on the measure of verbal working memory and a measure of word-learning. Together, these findings indicate that while exposure to a second language in a classroom setting may not be sufficient to engender changes in cognitive control, it can facilitate verbal memory and verbal learning. PMID:24576079

Effects of caloric restriction on learning and recovery of a spatial task in rats exposed to acute stress

Directory of Open Access Journals (Sweden)

Lamprea Rodríguez, Marisol

2009-06-01

Full Text Available The purpose of the present study was to describe the effects of caloric restriction on spatial learning and recovery in the Barnes maze in animals experimentally stressed before recovery of the spatial task. Male Wistar rats were exposed for two months to one of two conditions: ad libitum (AL or intermittent fasting (IF. Both groups were exposed then to an experimental form of acute stress, induced by movement restriction for 4 hours. IF subjects had better performance in learning tasks during the acquisition trials but required more time to complete the task after the stressor was applied. These results are discussed in light of previous data reported in the literature emphasizing differences in the instruments used to evaluate spatial learning and its interaction with experimentally induced stress.

Selection of appropriates E-learning personalization strategies from ontological perspectives

Directory of Open Access Journals (Sweden)

Fathi Essalmi

2010-10-01

Full Text Available When there are several personalization strategies of E-learning, authors of courses need to be supported for deciding which strategy will be applied for personalizing each course. In fact, the time, the efforts and the learning objects needed for preparing personalized learning scenarios depend on the personalization strategy to be applied. This paper presents an approach for selecting personalization strategies according to the feasibility of generating personalized learning scenarios with minimal intervention of the author. Several metrics are proposed for putting in order and selecting useful personalization strategies. The calculus of these metrics is automated based on the analyses of the LOM (Learning Object Metadata standard according to the semantic relations between data elements and learners’ characteristics represented in the Ontology for Selection of Personalization Strategies (OSPS.

Sensorimotor Learning during a Marksmanship Task in Immersive Virtual Reality

Directory of Open Access Journals (Sweden)

Hrishikesh M. Rao

2018-02-01

Full Text Available Sensorimotor learning refers to improvements that occur through practice in the performance of sensory-guided motor behaviors. Leveraging novel technical capabilities of an immersive virtual environment, we probed the component kinematic processes that mediate sensorimotor learning. Twenty naïve subjects performed a simulated marksmanship task modeled after Olympic Trap Shooting standards. We measured movement kinematics and shooting performance as participants practiced 350 trials while receiving trial-by-trial feedback about shooting success. Spatiotemporal analysis of motion tracking elucidated the ballistic and refinement phases of hand movements. We found systematic changes in movement kinematics that accompanied improvements in shot accuracy during training, though reaction and response times did not change over blocks. In particular, we observed longer, slower, and more precise ballistic movements that replaced effort spent on corrections and refinement. Collectively, these results leverage developments in immersive virtual reality technology to quantify and compare the kinematics of movement during early learning of full-body sensorimotor orienting.

Sensorimotor Learning during a Marksmanship Task in Immersive Virtual Reality.

Science.gov (United States)

Rao, Hrishikesh M; Khanna, Rajan; Zielinski, David J; Lu, Yvonne; Clements, Jillian M; Potter, Nicholas D; Sommer, Marc A; Kopper, Regis; Appelbaum, Lawrence G

2018-01-01

Sensorimotor learning refers to improvements that occur through practice in the performance of sensory-guided motor behaviors. Leveraging novel technical capabilities of an immersive virtual environment, we probed the component kinematic processes that mediate sensorimotor learning. Twenty naïve subjects performed a simulated marksmanship task modeled after Olympic Trap Shooting standards. We measured movement kinematics and shooting performance as participants practiced 350 trials while receiving trial-by-trial feedback about shooting success. Spatiotemporal analysis of motion tracking elucidated the ballistic and refinement phases of hand movements. We found systematic changes in movement kinematics that accompanied improvements in shot accuracy during training, though reaction and response times did not change over blocks. In particular, we observed longer, slower, and more precise ballistic movements that replaced effort spent on corrections and refinement. Collectively, these results leverage developments in immersive virtual reality technology to quantify and compare the kinematics of movement during early learning of full-body sensorimotor orienting.

Engineering development of selective agglomeration: Task 5, Bench- scale process testing

Energy Technology Data Exchange (ETDEWEB)

1991-09-01

Under the overall objectives of DOE Contract ``Engineering Development of Selective Agglomeration,`` there were a number of specific objectives in the Task 5 program. The prime objectives of Task 5 are highlighted below: (1) Maximize process performance in pyritic sulfur rejection and BTU recovery, (2) Produce a low ash product, (3) Compare the performance of the heavy agglomerant process based on diesel and the light agglomerant process using heptane, (4) Define optimum processing conditions for engineering design, (5) Provide first-level evaluation of product handleability, and (6) Explore and investigate process options/ideas which may enhance process performance and/or product handleability.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task

Directory of Open Access Journals (Sweden)

Ken eKinjo

2013-04-01

Full Text Available Linearly solvable Markov Decision Process (LMDP is a class of optimal control problem in whichthe Bellman’s equation can be converted into a linear equation by an exponential transformation ofthe state value function (Todorov, 2009. In an LMDP, the optimal value function and the correspondingcontrol policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunctionproblem in a continuous state using the knowledge of the system dynamics and the action, state, andterminal cost functions.In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in whichthe dynamics of the body and the environment have to be learned from experience. We first perform asimulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynam-ics model on the derived the action policy. The result shows that a crude linear approximation of thenonlinear dynamics can still allow solution of the task, despite with a higher total cost.We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robotplatform. The state is given by the position and the size of a battery in its camera view and two neck jointangles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servocontroller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state costfunctions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics modelperformed equivalently with the optimal linear quadratic controller (LQR. In the non-quadratic task, theLMDP controller with a linear dynamics model showed the best performance. The results demonstratethe usefulness of the LMDP framework in real robot control even when simple linear models are usedfor dynamics learning.

Evaluation of linearly solvable Markov decision process with dynamic model learning in a mobile robot navigation task.

Science.gov (United States)

Kinjo, Ken; Uchibe, Eiji; Doya, Kenji

2013-01-01

Linearly solvable Markov Decision Process (LMDP) is a class of optimal control problem in which the Bellman's equation can be converted into a linear equation by an exponential transformation of the state value function (Todorov, 2009b). In an LMDP, the optimal value function and the corresponding control policy are obtained by solving an eigenvalue problem in a discrete state space or an eigenfunction problem in a continuous state using the knowledge of the system dynamics and the action, state, and terminal cost functions. In this study, we evaluate the effectiveness of the LMDP framework in real robot control, in which the dynamics of the body and the environment have to be learned from experience. We first perform a simulation study of a pole swing-up task to evaluate the effect of the accuracy of the learned dynamics model on the derived the action policy. The result shows that a crude linear approximation of the non-linear dynamics can still allow solution of the task, despite with a higher total cost. We then perform real robot experiments of a battery-catching task using our Spring Dog mobile robot platform. The state is given by the position and the size of a battery in its camera view and two neck joint angles. The action is the velocities of two wheels, while the neck joints were controlled by a visual servo controller. We test linear and bilinear dynamic models in tasks with quadratic and Guassian state cost functions. In the quadratic cost task, the LMDP controller derived from a learned linear dynamics model performed equivalently with the optimal linear quadratic regulator (LQR). In the non-quadratic task, the LMDP controller with a linear dynamics model showed the best performance. The results demonstrate the usefulness of the LMDP framework in real robot control even when simple linear models are used for dynamics learning.

Region and task-specific activation of Arc in primary motor cortex of rats following motor skill learning.

Science.gov (United States)

Hosp, J A; Mann, S; Wegenast-Braun, B M; Calhoun, M E; Luft, A R

2013-10-10

Motor learning requires protein synthesis within the primary motor cortex (M1). Here, we show that the immediate early gene Arc/Arg3.1 is specifically induced in M1 by learning a motor skill. Arc mRNA was quantified using a fluorescent in situ hybridization assay in adult Long-Evans rats learning a skilled reaching task (SRT), in rats performing reaching-like forelimb movement without learning (ACT) and in rats that were trained in the operant but not the motor elements of the task (controls). Apart from M1, Arc expression was assessed within the rostral motor area (RMA), primary somatosensory cortex (S1), striatum (ST) and cerebellum. In SRT animals, Arc mRNA levels in M1 contralateral to the trained limb were 31% higher than ipsilateral (pmotor skill learning in rats. Copyright © 2013 IBRO. Published by Elsevier Ltd. All rights reserved.