Perceptual category learning of photographic and painterly stimuli in rhesus macaques (Macaca mulatta) and humans

PubMed Central

Jensen, Greg; Terrace, Herbert

2017-01-01

Humans are highly adept at categorizing visual stimuli, but studies of human categorization are typically validated by verbal reports. This makes it difficult to perform comparative studies of categorization using non-human animals. Interpretation of comparative studies is further complicated by the possibility that animal performance may merely reflect reinforcement learning, whereby discrete features act as discriminative cues for categorization. To assess and compare how humans and monkeys classified visual stimuli, we trained 7 rhesus macaques and 41 human volunteers to respond, in a specific order, to four simultaneously presented stimuli at a time, each belonging to a different perceptual category. These exemplars were drawn at random from large banks of images, such that the stimuli presented changed on every trial. Subjects nevertheless identified and ordered these changing stimuli correctly. Three monkeys learned to order naturalistic photographs; four others, close-up sections of paintings with distinctive styles. Humans learned to order both types of stimuli. All subjects classified stimuli at levels substantially greater than that predicted by chance or by feature-driven learning alone, even when stimuli changed on every trial. However, humans more closely resembled monkeys when classifying the more abstract painting stimuli than the photographic stimuli. This points to a common classification strategy in both species, one that humans can rely on in the absence of linguistic labels for categories. PMID:28961270

Implicit and Explicit Categorization: A Tale of Four Species

DTIC Science & Technology

2012-01-01

macaques (Macaca mulatta) and humans ( Homo sapiens ). J. Exp. Psychol. Anim. Behav. Process., 36, 54-65. Smith, J.D., Chapman, W.P., Redford, J.S...2010 (b). Stages of category learning in monkeys (Macaca mulatta) and humans ( Homo sapiens ). J. Exp. Psychol. Anim. Behav. Process., 36, 39-53...Smith, J.D., Coutinho, M.V.C., Couchman, J.J., 2011 (b). The learning of exclusive-or categories by monkeys (Macaca mulatta) and humans ( Homo sapiens ). J

Categorical Structure among Shared Features in Networks of Early-Learned Nouns

ERIC Educational Resources Information Center

Hills, Thomas T.; Maouene, Mounir; Maouene, Josita; Sheya, Adam; Smith, Linda

2009-01-01

The shared features that characterize the noun categories that young children learn first are a formative basis of the human category system. To investigate the potential categorical information contained in the features of early-learned nouns, we examine the graph-theoretic properties of noun-feature networks. The networks are built from the…

Perceptual category learning and visual processing: An exercise in computational cognitive neuroscience.

PubMed

Cantwell, George; Riesenhuber, Maximilian; Roeder, Jessica L; Ashby, F Gregory

2017-05-01

The field of computational cognitive neuroscience (CCN) builds and tests neurobiologically detailed computational models that account for both behavioral and neuroscience data. This article leverages a key advantage of CCN-namely, that it should be possible to interface different CCN models in a plug-and-play fashion-to produce a new and biologically detailed model of perceptual category learning. The new model was created from two existing CCN models: the HMAX model of visual object processing and the COVIS model of category learning. Using bitmap images as inputs and by adjusting only a couple of learning-rate parameters, the new HMAX/COVIS model provides impressively good fits to human category-learning data from two qualitatively different experiments that used different types of category structures and different types of visual stimuli. Overall, the model provides a comprehensive neural and behavioral account of basal ganglia-mediated learning. Copyright © 2017 Elsevier Ltd. All rights reserved.

Training Humans to Categorize Monkey Calls: Auditory Feature- and Category-Selective Neural Tuning Changes.

PubMed

Jiang, Xiong; Chevillet, Mark A; Rauschecker, Josef P; Riesenhuber, Maximilian

2018-04-18

Grouping auditory stimuli into common categories is essential for a variety of auditory tasks, including speech recognition. We trained human participants to categorize auditory stimuli from a large novel set of morphed monkey vocalizations. Using fMRI-rapid adaptation (fMRI-RA) and multi-voxel pattern analysis (MVPA) techniques, we gained evidence that categorization training results in two distinct sets of changes: sharpened tuning to monkey call features (without explicit category representation) in left auditory cortex and category selectivity for different types of calls in lateral prefrontal cortex. In addition, the sharpness of neural selectivity in left auditory cortex, as estimated with both fMRI-RA and MVPA, predicted the steepness of the categorical boundary, whereas categorical judgment correlated with release from adaptation in the left inferior frontal gyrus. These results support the theory that auditory category learning follows a two-stage model analogous to the visual domain, suggesting general principles of perceptual category learning in the human brain. Copyright © 2018 Elsevier Inc. All rights reserved.

Oscillatory neural network for pattern recognition: trajectory based classification and supervised learning.

PubMed

Miller, Vonda H; Jansen, Ben H

2008-12-01

Computer algorithms that match human performance in recognizing written text or spoken conversation remain elusive. The reasons why the human brain far exceeds any existing recognition scheme to date in the ability to generalize and to extract invariant characteristics relevant to category matching are not clear. However, it has been postulated that the dynamic distribution of brain activity (spatiotemporal activation patterns) is the mechanism by which stimuli are encoded and matched to categories. This research focuses on supervised learning using a trajectory based distance metric for category discrimination in an oscillatory neural network model. Classification is accomplished using a trajectory based distance metric. Since the distance metric is differentiable, a supervised learning algorithm based on gradient descent is demonstrated. Classification of spatiotemporal frequency transitions and their relation to a priori assessed categories is shown along with the improved classification results after supervised training. The results indicate that this spatiotemporal representation of stimuli and the associated distance metric is useful for simple pattern recognition tasks and that supervised learning improves classification results.

Basal ganglia and Dopamine Contributions to Probabilistic Category Learning

PubMed Central

Shohamy, D.; Myers, C.E.; Kalanithi, J.; Gluck, M.A.

2009-01-01

Studies of the medial temporal lobe and basal ganglia memory systems have recently been extended towards understanding the neural systems contributing to category learning. The basal ganglia, in particular, have been linked to probabilistic category learning in humans. A separate parallel literature in systems neuroscience has emerged, indicating a role for the basal ganglia and related dopamine inputs in reward prediction and feedback processing. Here, we review behavioral, neuropsychological, functional neuroimaging, and computational studies of basal ganglia and dopamine contributions to learning in humans. Collectively, these studies implicate the basal ganglia in incremental, feedback-based learning that involves integrating information across multiple experiences. The medial temporal lobes, by contrast, contribute to rapid encoding of relations between stimuli and support flexible generalization of learning to novel contexts and stimuli. By breaking down our understanding of the cognitive and neural mechanisms contributing to different aspects of learning, recent studies are providing insight into how, and when, these different processes support learning, how they may interact with each other, and the consequence of different forms of learning for the representation of knowledge. PMID:18061261

What Counts as Knowledge: Learning to Use Categories in Computer Environments

ERIC Educational Resources Information Center

Ludvigsen, Sten R.

2012-01-01

In this article, I develop a perspective on learning as multilayered phenomena. I take a socio-genetic approach in order to understand human activity and to show how categories are a fundamental part of learning in a specific type of institutional practice. In the empirical section, student dialogue is analysed in relation to a set of categories…

One Giant Leap for Categorizers: One Small Step for Categorization Theory

PubMed Central

Smith, J. David; Ell, Shawn W.

2015-01-01

We explore humans’ rule-based category learning using analytic approaches that highlight their psychological transitions during learning. These approaches confirm that humans show qualitatively sudden psychological transitions during rule learning. These transitions contribute to the theoretical literature contrasting single vs. multiple category-learning systems, because they seem to reveal a distinctive learning process of explicit rule discovery. A complete psychology of categorization must describe this learning process, too. Yet extensive formal-modeling analyses confirm that a wide range of current (gradient-descent) models cannot reproduce these transitions, including influential rule-based models (e.g., COVIS) and exemplar models (e.g., ALCOVE). It is an important theoretical conclusion that existing models cannot explain humans’ rule-based category learning. The problem these models have is the incremental algorithm by which learning is simulated. Humans descend no gradient in rule-based tasks. Very different formal-modeling systems will be required to explain humans’ psychology in these tasks. An important next step will be to build a new generation of models that can do so. PMID:26332587

Multi-task learning with group information for human action recognition

NASA Astrophysics Data System (ADS)

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.

Putting the psychology back into psychological models: mechanistic versus rational approaches.

PubMed

Sakamoto, Yasuaki; Jones, Mattr; Love, Bradley C

2008-09-01

Two basic approaches to explaining the nature of the mind are the rational and the mechanistic approaches. Rational analyses attempt to characterize the environment and the behavioral outcomes that humans seek to optimize, whereas mechanistic models attempt to simulate human behavior using processes and representations analogous to those used by humans. We compared these approaches with regard to their accounts of how humans learn the variability of categories. The mechanistic model departs in subtle ways from rational principles. In particular, the mechanistic model incrementally updates its estimates of category means and variances through error-driven learning, based on discrepancies between new category members and the current representation of each category. The model yields a prediction, which we verify, regarding the effects of order manipulations that the rational approach does not anticipate. Although both rational and mechanistic models can successfully postdict known findings, we suggest that psychological advances are driven primarily by consideration of process and representation and that rational accounts trail these breakthroughs.

Combining Computational Modeling and Neuroimaging to Examine Multiple Category Learning Systems in the Brain

PubMed Central

Nomura, Emi M.; Reber, Paul J.

2012-01-01

Considerable evidence has argued in favor of multiple neural systems supporting human category learning, one based on conscious rule inference and one based on implicit information integration. However, there have been few attempts to study potential system interactions during category learning. The PINNACLE (Parallel Interactive Neural Networks Active in Category Learning) model incorporates multiple categorization systems that compete to provide categorization judgments about visual stimuli. Incorporating competing systems requires inclusion of cognitive mechanisms associated with resolving this competition and creates a potential credit assignment problem in handling feedback. The hypothesized mechanisms make predictions about internal mental states that are not always reflected in choice behavior, but may be reflected in neural activity. Two prior functional magnetic resonance imaging (fMRI) studies of category learning were re-analyzed using PINNACLE to identify neural correlates of internal cognitive states on each trial. These analyses identified additional brain regions supporting the two types of category learning, regions particularly active when the systems are hypothesized to be in maximal competition, and found evidence of covert learning activity in the “off system” (the category learning system not currently driving behavior). These results suggest that PINNACLE provides a plausible framework for how competing multiple category learning systems are organized in the brain and shows how computational modeling approaches and fMRI can be used synergistically to gain access to cognitive processes that support complex decision-making machinery. PMID:24962771

Learning and retention through predictive inference and classification.

PubMed

Sakamoto, Yasuaki; Love, Bradley C

2010-12-01

Work in category learning addresses how humans acquire knowledge and, thus, should inform classroom practices. In two experiments, we apply and evaluate intuitions garnered from laboratory-based research in category learning to learning tasks situated in an educational context. In Experiment 1, learning through predictive inference and classification were compared for fifth-grade students using class-related materials. Making inferences about properties of category members and receiving feedback led to the acquisition of both queried (i.e., tested) properties and nonqueried properties that were correlated with a queried property (e.g., even if not queried, students learned about a species' habitat because it correlated with a queried property, like the species' size). In contrast, classifying items according to their species and receiving feedback led to knowledge of only the property most diagnostic of category membership. After multiple-day delay, the fifth-graders who learned through inference selectively retained information about the queried properties, and the fifth-graders who learned through classification retained information about the diagnostic property, indicating a role for explicit evaluation in establishing memories. Overall, inference learning resulted in fewer errors, better retention, and more liking of the categories than did classification learning. Experiment 2 revealed that querying a property only a few times was enough to manifest the full benefits of inference learning in undergraduate students. These results suggest that classroom teaching should emphasize reasoning from the category to multiple properties rather than from a set of properties to the category. (PsycINFO Database Record (c) 2010 APA, all rights reserved).

Aversive Learning Modulates Cortical Representations of Object Categories

PubMed Central

Dunsmoor, Joseph E.; Kragel, Philip A.; Martin, Alex; LaBar, Kevin S.

2014-01-01

Experimental studies of conditioned learning reveal activity changes in the amygdala and unimodal sensory cortex underlying fear acquisition to simple stimuli. However, real-world fears typically involve complex stimuli represented at the category level. A consequence of category-level representations of threat is that aversive experiences with particular category members may lead one to infer that related exemplars likewise pose a threat, despite variations in physical form. Here, we examined the effect of category-level representations of threat on human brain activation using 2 superordinate categories (animals and tools) as conditioned stimuli. Hemodynamic activity in the amygdala and category-selective cortex was modulated by the reinforcement contingency, leading to widespread fear of different exemplars from the reinforced category. Multivariate representational similarity analyses revealed that activity patterns in the amygdala and object-selective cortex were more similar among exemplars from the threat versus safe category. Learning to fear animate objects was additionally characterized by enhanced functional coupling between the amygdala and fusiform gyrus. Finally, hippocampal activity co-varied with object typicality and amygdala activation early during training. These findings provide novel evidence that aversive learning can modulate category-level representations of object concepts, thereby enabling individuals to express fear to a range of related stimuli. PMID:23709642

Memory Errors Reveal a Bias to Spontaneously Generalize to Categories

ERIC Educational Resources Information Center

Sutherland, Shelbie L.; Cimpian, Andrei; Leslie, Sarah-Jane; Gelman, Susan A.

2015-01-01

Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that--beyond simply being able to perform such generalizations--people are "biased" to generalize to categories, such that they routinely make spontaneous, implicit…

Fine-grained temporal coding of visually-similar categories in the ventral visual pathway and prefrontal cortex

PubMed Central

Xu, Yang; D'Lauro, Christopher; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2013-01-01

Humans are remarkably proficient at categorizing visually-similar objects. To better understand the cortical basis of this categorization process, we used magnetoencephalography (MEG) to record neural activity while participants learned–with feedback–to discriminate two highly-similar, novel visual categories. We hypothesized that although prefrontal regions would mediate early category learning, this role would diminish with increasing category familiarity and that regions within the ventral visual pathway would come to play a more prominent role in encoding category-relevant information as learning progressed. Early in learning we observed some degree of categorical discriminability and predictability in both prefrontal cortex and the ventral visual pathway. Predictability improved significantly above chance in the ventral visual pathway over the course of learning with the left inferior temporal and fusiform gyri showing the greatest improvement in predictability between 150 and 250 ms (M200) during category learning. In contrast, there was no comparable increase in discriminability in prefrontal cortex with the only significant post-learning effect being a decrease in predictability in the inferior frontal gyrus between 250 and 350 ms (M300). Thus, the ventral visual pathway appears to encode learned visual categories over the long term. At the same time these results add to our understanding of the cortical origins of previously reported signature temporal components associated with perceptual learning. PMID:24146656

Inferential Learning of Serial Order of Perceptual Categories by Rhesus Monkeys (Macaca mulatta)

PubMed Central

2017-01-01

Category learning in animals is typically trained explicitly, in most instances by varying the exemplars of a single category in a matching-to-sample task. Here, we show that male rhesus macaques can learn categories by a transitive inference paradigm in which novel exemplars of five categories were presented throughout training. Instead of requiring decisions about a constant set of repetitively presented stimuli, we studied the macaque's ability to determine the relative order of multiple exemplars of particular stimuli that were rarely repeated. Ordinal decisions generalized both to novel stimuli and, as a consequence, to novel pairings. Thus, we showed that rhesus monkeys could learn to categorize on the basis of implied ordinal position, without prior matching-to-sample training, and that they could then make inferences about category order. Our results challenge the plausibility of association models of category learning and broaden the scope of the transitive inference paradigm. SIGNIFICANCE STATEMENT The cognitive abilities of nonhuman animals are of enduring interest to scientists and the general public because they blur the dividing line between human and nonhuman intelligence. Categorization and sequence learning are highly abstract cognitive abilities each in their own right. This study is the first to provide evidence that visual categories can be ordered serially by macaque monkeys using a behavioral paradigm that provides no explicit feedback about category or serial order. These results strongly challenge accounts of learning based on stimulus–response associations. PMID:28546309

A probabilistic model of cross-categorization.

PubMed

Shafto, Patrick; Kemp, Charles; Mansinghka, Vikash; Tenenbaum, Joshua B

2011-07-01

Most natural domains can be represented in multiple ways: we can categorize foods in terms of their nutritional content or social role, animals in terms of their taxonomic groupings or their ecological niches, and musical instruments in terms of their taxonomic categories or social uses. Previous approaches to modeling human categorization have largely ignored the problem of cross-categorization, focusing on learning just a single system of categories that explains all of the features. Cross-categorization presents a difficult problem: how can we infer categories without first knowing which features the categories are meant to explain? We present a novel model that suggests that human cross-categorization is a result of joint inference about multiple systems of categories and the features that they explain. We also formalize two commonly proposed alternative explanations for cross-categorization behavior: a features-first and an objects-first approach. The features-first approach suggests that cross-categorization is a consequence of attentional processes, where features are selected by an attentional mechanism first and categories are derived second. The objects-first approach suggests that cross-categorization is a consequence of repeated, sequential attempts to explain features, where categories are derived first, then features that are poorly explained are recategorized. We present two sets of simulations and experiments testing the models' predictions about human categorization. We find that an approach based on joint inference provides the best fit to human categorization behavior, and we suggest that a full account of human category learning will need to incorporate something akin to these capabilities. Copyright © 2011 Elsevier B.V. All rights reserved.

Syntax-induced pattern deafness

PubMed Central

Endress, Ansgar D.; Hauser, Marc D.

2009-01-01

Perceptual systems often force systematically biased interpretations upon sensory input. These interpretations are obligatory, inaccessible to conscious control, and prevent observers from perceiving alternative percepts. Here we report a similarly impenetrable phenomenon in the domain of language, where the syntactic system prevents listeners from detecting a simple perceptual pattern. Healthy human adults listened to three-word sequences conforming to patterns readily learned even by honeybees, rats, and sleeping human neonates. Specifically, sequences either started or ended with two words from the same syntactic category (e.g., noun–noun–verb or verb–verb–noun). Although participants readily processed the categories and learned repetition patterns over nonsyntactic categories (e.g., animal–animal–clothes), they failed to learn the repetition pattern over syntactic categories, even when explicitly instructed to look for it. Further experiments revealed that participants successfully learned the repetition patterns only when they were consistent with syntactically possible structures, irrespective of whether these structures were attested in English or in other languages unknown to the participants. When the repetition patterns did not match such syntactically possible structures, participants failed to learn them. Our results suggest that when human adults hear a string of nouns and verbs, their syntactic system obligatorily attempts an interpretation (e.g., in terms of subjects, objects, and predicates). As a result, subjects fail to perceive the simpler pattern of repetitions—a form of syntax-induced pattern deafness that is reminiscent of how other perceptual systems force specific interpretations upon sensory input. PMID:19920182

Building phonetic categories: an argument for the role of sleep

PubMed Central

Earle, F. Sayako; Myers, Emily B.

2014-01-01

The current review provides specific predictions for the role of sleep-mediated memory consolidation in the formation of new speech sound representations. Specifically, this discussion will highlight selected literature on the different ideas concerning category representation in speech, followed by a broad overview of memory consolidation and how it relates to human behavior, as relevant to speech/perceptual learning. In combining behavioral and physiological accounts from animal models with insights from the human consolidation literature on auditory skill/word learning, we are in the early stages of understanding how the transfer of experiential information between brain structures during sleep manifests in changes to online perception. Arriving at the conclusion that this process is crucial in perceptual learning and the formation of novel categories, further speculation yields the adjacent claim that the habitual disruption in this process leads to impoverished quality in the representation of speech sounds. PMID:25477828

Category Learning Research in the Interactive Online Environment Second Life

NASA Technical Reports Server (NTRS)

Andrews, Jan; Livingston, Ken; Sturm, Joshua; Bliss, Daniel; Hawthorne, Daniel

2011-01-01

The interactive online environment Second Life allows users to create novel three-dimensional stimuli that can be manipulated in a meaningful yet controlled environment. These features suggest Second Life's utility as a powerful tool for investigating how people learn concepts for unfamiliar objects. The first of two studies was designed to establish that cognitive processes elicited in this virtual world are comparable to those tapped in conventional settings by attempting to replicate the established finding that category learning systematically influences perceived similarity . From the perspective of an avatar, participants navigated a course of unfamiliar three-dimensional stimuli and were trained to classify them into two labeled categories based on two visual features. Participants then gave similarity ratings for pairs of stimuli and their responses were compared to those of control participants who did not learn the categories. Results indicated significant compression, whereby objects classified together were judged to be more similar by learning than control participants, thus supporting the validity of using Second Life as a laboratory for studying human cognition. A second study used Second Life to test the novel hypothesis that effects of learning on perceived similarity do not depend on the presence of verbal labels for categories. We presented the same stimuli but participants classified them by selecting between two complex visual patterns designed to be extremely difficult to label. While learning was more challenging in this condition , those who did learn without labels showed a compression effect identical to that found in the first study using verbal labels. Together these studies establish that at least some forms of human learning in Second Life parallel learning in the actual world and thus open the door to future studies that will make greater use of the enriched variety of objects and interactions possible in simulated environments compared to traditional experimental situations.

Category Induction via Distributional Analysis: Evidence from a Serial Reaction Time Task

ERIC Educational Resources Information Center

Hunt, Ruskin H.; Aslin, Richard N.

2010-01-01

Category formation lies at the heart of a number of higher-order behaviors, including language. We assessed the ability of human adults to learn, from distributional information alone, categories embedded in a sequence of input stimuli using a serial reaction time task. Artificial grammars generated corpora of input strings containing a…

The Success of Advanced Learning Technologies for Instruction: Research and Evaluation of Human Factors Issues.

ERIC Educational Resources Information Center

Coldeway, Dan O.

2002-01-01

Data from three graduate programs using advanced learning technologies (ALTs) identified important human factors issues in technology use in three categories: learners (needs, skills, support, and motivation related to ALTs); faculty (attitudes, skills, support, and motivation related to ALTs); and technical staff (methods of providing assistance,…

Transcranial infrared laser stimulation improves rule-based, but not information-integration, category learning in humans.

PubMed

Blanco, Nathaniel J; Saucedo, Celeste L; Gonzalez-Lima, F

2017-03-01

This is the first randomized, controlled study comparing the cognitive effects of transcranial laser stimulation on category learning tasks. Transcranial infrared laser stimulation is a new non-invasive form of brain stimulation that shows promise for wide-ranging experimental and neuropsychological applications. It involves using infrared laser to enhance cerebral oxygenation and energy metabolism through upregulation of the respiratory enzyme cytochrome oxidase, the primary infrared photon acceptor in cells. Previous research found that transcranial infrared laser stimulation aimed at the prefrontal cortex can improve sustained attention, short-term memory, and executive function. In this study, we directly investigated the influence of transcranial infrared laser stimulation on two neurobiologically dissociable systems of category learning: a prefrontal cortex mediated reflective system that learns categories using explicit rules, and a striatally mediated reflexive learning system that forms gradual stimulus-response associations. Participants (n=118) received either active infrared laser to the lateral prefrontal cortex or sham (placebo) stimulation, and then learned one of two category structures-a rule-based structure optimally learned by the reflective system, or an information-integration structure optimally learned by the reflexive system. We found that prefrontal rule-based learning was substantially improved following transcranial infrared laser stimulation as compared to placebo (treatment X block interaction: F(1, 298)=5.117, p=0.024), while information-integration learning did not show significant group differences (treatment X block interaction: F(1, 288)=1.633, p=0.202). These results highlight the exciting potential of transcranial infrared laser stimulation for cognitive enhancement and provide insight into the neurobiological underpinnings of category learning. Copyright © 2017 Elsevier Inc. All rights reserved.

The role of feedback contingency in perceptual category learning.

PubMed

Ashby, F Gregory; Vucovich, Lauren E

2016-11-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from 2 or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all 4 conditions, and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects, as well as their theoretical implications, are discussed. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

The Role of Feedback Contingency in Perceptual Category Learning

PubMed Central

Ashby, F. Gregory; Vucovich, Lauren E.

2016-01-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how feedback contingency affects category learning, and current theories assign little or no importance to this variable. Two experiments examined the effects of contingency degradation on rule-based and information-integration category learning. In rule-based tasks, optimal accuracy is possible with a simple explicit rule, whereas optimal accuracy in information-integration tasks requires integrating information from two or more incommensurable perceptual dimensions. In both experiments, participants each learned rule-based or information-integration categories under either high or low levels of feedback contingency. The exact same stimuli were used in all four conditions and optimal accuracy was identical in every condition. Learning was good in both high-contingency conditions, but most participants showed little or no evidence of learning in either low-contingency condition. Possible causes of these effects are discussed, as well as their theoretical implications. PMID:27149393

Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic.

PubMed

van der Ham, Sabine; de Boer, Bart

2015-10-01

When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults' generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants' reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories.

Cognitive Bias for Learning Speech Sounds From a Continuous Signal Space Seems Nonlinguistic

PubMed Central

de Boer, Bart

2015-01-01

When learning language, humans have a tendency to produce more extreme distributions of speech sounds than those observed most frequently: In rapid, casual speech, vowel sounds are centralized, yet cross-linguistically, peripheral vowels occur almost universally. We investigate whether adults’ generalization behavior reveals selective pressure for communication when they learn skewed distributions of speech-like sounds from a continuous signal space. The domain-specific hypothesis predicts that the emergence of sound categories is driven by a cognitive bias to make these categories maximally distinct, resulting in more skewed distributions in participants’ reproductions. However, our participants showed more centered distributions, which goes against this hypothesis, indicating that there are no strong innate linguistic biases that affect learning these speech-like sounds. The centralization behavior can be explained by a lack of communicative pressure to maintain categories. PMID:27648212

Birth of an Abstraction: A Dynamical Systems Account of the Discovery of an Elsewhere Principle in a Category Learning Task

ERIC Educational Resources Information Center

Tabor, Whitney; Cho, Pyeong W.; Dankowicz, Harry

2013-01-01

Human participants and recurrent ("connectionist") neural networks were both trained on a categorization system abstractly similar to natural language systems involving irregular ("strong") classes and a default class. Both the humans and the networks exhibited staged learning and a generalization pattern reminiscent of the…

More than words: Adults learn probabilities over categories and relationships between them.

PubMed

Hudson Kam, Carla L

2009-04-01

This study examines whether human learners can acquire statistics over abstract categories and their relationships to each other. Adult learners were exposed to miniature artificial languages containing variation in the ordering of the Subject, Object, and Verb constituents. Different orders (e.g. SOV, VSO) occurred in the input with different frequencies, but the occurrence of one order versus another was not predictable. Importantly, the language was constructed such that participants could only match the overall input probabilities if they were tracking statistics over abstract categories, not over individual words. At test, participants reproduced the probabilities present in the input with a high degree of accuracy. Closer examination revealed that learner's were matching the probabilities associated with individual verbs rather than the category as a whole. However, individual nouns had no impact on word orders produced. Thus, participants learned the probabilities of a particular ordering of the abstract grammatical categories Subject and Object associated with each verb. Results suggest that statistical learning mechanisms are capable of tracking relationships between abstract linguistic categories in addition to individual items.

View-invariant object category learning, recognition, and search: how spatial and object attention are coordinated using surface-based attentional shrouds.

PubMed

Fazl, Arash; Grossberg, Stephen; Mingolla, Ennio

2009-02-01

How does the brain learn to recognize an object from multiple viewpoints while scanning a scene with eye movements? How does the brain avoid the problem of erroneously classifying parts of different objects together? How are attention and eye movements intelligently coordinated to facilitate object learning? A neural model provides a unified mechanistic explanation of how spatial and object attention work together to search a scene and learn what is in it. The ARTSCAN model predicts how an object's surface representation generates a form-fitting distribution of spatial attention, or "attentional shroud". All surface representations dynamically compete for spatial attention to form a shroud. The winning shroud persists during active scanning of the object. The shroud maintains sustained activity of an emerging view-invariant category representation while multiple view-specific category representations are learned and are linked through associative learning to the view-invariant object category. The shroud also helps to restrict scanning eye movements to salient features on the attended object. Object attention plays a role in controlling and stabilizing the learning of view-specific object categories. Spatial attention hereby coordinates the deployment of object attention during object category learning. Shroud collapse releases a reset signal that inhibits the active view-invariant category in the What cortical processing stream. Then a new shroud, corresponding to a different object, forms in the Where cortical processing stream, and search using attention shifts and eye movements continues to learn new objects throughout a scene. The model mechanistically clarifies basic properties of attention shifts (engage, move, disengage) and inhibition of return. It simulates human reaction time data about object-based spatial attention shifts, and learns with 98.1% accuracy and a compression of 430 on a letter database whose letters vary in size, position, and orientation. The model provides a powerful framework for unifying many data about spatial and object attention, and their interactions during perception, cognition, and action.

How may the basal ganglia contribute to auditory categorization and speech perception?

PubMed Central

Lim, Sung-Joo; Fiez, Julie A.; Holt, Lori L.

2014-01-01

Listeners must accomplish two complementary perceptual feats in extracting a message from speech. They must discriminate linguistically-relevant acoustic variability and generalize across irrelevant variability. Said another way, they must categorize speech. Since the mapping of acoustic variability is language-specific, these categories must be learned from experience. Thus, understanding how, in general, the auditory system acquires and represents categories can inform us about the toolbox of mechanisms available to speech perception. This perspective invites consideration of findings from cognitive neuroscience literatures outside of the speech domain as a means of constraining models of speech perception. Although neurobiological models of speech perception have mainly focused on cerebral cortex, research outside the speech domain is consistent with the possibility of significant subcortical contributions in category learning. Here, we review the functional role of one such structure, the basal ganglia. We examine research from animal electrophysiology, human neuroimaging, and behavior to consider characteristics of basal ganglia processing that may be advantageous for speech category learning. We also present emerging evidence for a direct role for basal ganglia in learning auditory categories in a complex, naturalistic task intended to model the incidental manner in which speech categories are acquired. To conclude, we highlight new research questions that arise in incorporating the broader neuroscience research literature in modeling speech perception, and suggest how understanding contributions of the basal ganglia can inform attempts to optimize training protocols for learning non-native speech categories in adulthood. PMID:25136291

Prediction of skin sensitization potency using machine learning approaches.

PubMed

Zang, Qingda; Paris, Michael; Lehmann, David M; Bell, Shannon; Kleinstreuer, Nicole; Allen, David; Matheson, Joanna; Jacobs, Abigail; Casey, Warren; Strickland, Judy

2017-07-01

The replacement of animal use in testing for regulatory classification of skin sensitizers is a priority for US federal agencies that use data from such testing. Machine learning models that classify substances as sensitizers or non-sensitizers without using animal data have been developed and evaluated. Because some regulatory agencies require that sensitizers be further classified into potency categories, we developed statistical models to predict skin sensitization potency for murine local lymph node assay (LLNA) and human outcomes. Input variables for our models included six physicochemical properties and data from three non-animal test methods: direct peptide reactivity assay; human cell line activation test; and KeratinoSens™ assay. Models were built to predict three potency categories using four machine learning approaches and were validated using external test sets and leave-one-out cross-validation. A one-tiered strategy modeled all three categories of response together while a two-tiered strategy modeled sensitizer/non-sensitizer responses and then classified the sensitizers as strong or weak sensitizers. The two-tiered model using the support vector machine with all assay and physicochemical data inputs provided the best performance, yielding accuracy of 88% for prediction of LLNA outcomes (120 substances) and 81% for prediction of human test outcomes (87 substances). The best one-tiered model predicted LLNA outcomes with 78% accuracy and human outcomes with 75% accuracy. By comparison, the LLNA predicts human potency categories with 69% accuracy (60 of 87 substances correctly categorized). These results suggest that computational models using non-animal methods may provide valuable information for assessing skin sensitization potency. Copyright © 2017 John Wiley & Sons, Ltd. Copyright © 2017 John Wiley & Sons, Ltd.

A Bayesian generative model for learning semantic hierarchies

PubMed Central

Mittelman, Roni; Sun, Min; Kuipers, Benjamin; Savarese, Silvio

2014-01-01

Building fine-grained visual recognition systems that are capable of recognizing tens of thousands of categories, has received much attention in recent years. The well known semantic hierarchical structure of categories and concepts, has been shown to provide a key prior which allows for optimal predictions. The hierarchical organization of various domains and concepts has been subject to extensive research, and led to the development of the WordNet domains hierarchy (Fellbaum, 1998), which was also used to organize the images in the ImageNet (Deng et al., 2009) dataset, in which the category count approaches the human capacity. Still, for the human visual system, the form of the hierarchy must be discovered with minimal use of supervision or innate knowledge. In this work, we propose a new Bayesian generative model for learning such domain hierarchies, based on semantic input. Our model is motivated by the super-subordinate organization of domain labels and concepts that characterizes WordNet, and accounts for several important challenges: maintaining context information when progressing deeper into the hierarchy, learning a coherent semantic concept for each node, and modeling uncertainty in the perception process. PMID:24904452

Definitions of Interdisciplinary Research: Toward Graduate-Level Interdisciplinary Learning Outcomes

ERIC Educational Resources Information Center

Borrego, Maura; Newswander, Lynita K.

2010-01-01

Combining the interdisciplinary studies (primarily humanities) literature with the content analysis of 129 successful National Science Foundation proposals written predominantly by science and engineering faculty members, the authors identify five categories of learning outcomes for interdisciplinary graduate education: disciplinary grounding,…

Dissociable changes in functional network topology underlie early category learning and development of automaticity

PubMed Central

Soto, Fabian A.; Bassett, Danielle S.; Ashby, F. Gregory

2016-01-01

Recent work has shown that multimodal association areas–including frontal, temporal and parietal cortex–are focal points of functional network reconfiguration during human learning and performance of cognitive tasks. On the other hand, neurocomputational theories of category learning suggest that the basal ganglia and related subcortical structures are focal points of functional network reconfiguration during early learning of some categorization tasks, but become less so with the development of automatic categorization performance. Using a combination of network science and multilevel regression, we explore how changes in the connectivity of small brain regions can predict behavioral changes during training in a visual categorization task. We find that initial category learning, as indexed by changes in accuracy, is predicted by increasingly efficient integrative processing in subcortical areas, with higher functional specialization, more efficient integration across modules, but a lower cost in terms of redundancy of information processing. The development of automaticity, as indexed by changes in the speed of correct responses, was predicted by lower clustering (particularly in subcortical areas), higher strength (highest in cortical areas) and higher betweenness centrality. By combining neurocomputational theories and network scientific methods, these results synthesize the dissociative roles of multimodal association areas and subcortical structures in the development of automaticity during category learning. PMID:27453156

Pigeons and humans use action and pose information to categorize complex human behaviors.

PubMed

Qadri, Muhammad A J; Cook, Robert G

2017-02-01

The biological mechanisms used to categorize and recognize behaviors are poorly understood in both human and non-human animals. Using animated digital models, we have recently shown that pigeons can categorize different locomotive animal gaits and types of complex human behaviors. In the current experiments, pigeons (go/no-go task) and humans (choice task) both learned to conditionally categorize two categories of human behaviors that did not repeat and were comprised of the coordinated motions of multiple limbs. These "martial arts" and "Indian dance" action sequences were depicted by a digital human model. Depending upon whether the model was in motion or not, each species was required to engage in different and opposing responses to the two behavioral categories. Both species learned to conditionally and correctly act on this dynamic and static behavioral information, indicating that both species use a combination of static pose cues that are available from stimulus onset in addition to less rapidly available action information in order to successfully discriminate between the behaviors. Human participants additionally demonstrated a bias towards the dynamic information in the display when re-learning the task. Theories that rely on generalized, non-specific visual mechanisms involving channels for motion and static cues offer a parsimonious account of how humans and pigeons recognize and categorize behaviors within and across species. Copyright © 2016 Elsevier Ltd. All rights reserved.

Comparing the effects of positive and negative feedback in information-integration category learning.

PubMed

Freedberg, Michael; Glass, Brian; Filoteo, J Vincent; Hazeltine, Eliot; Maddox, W Todd

2017-01-01

Categorical learning is dependent on feedback. Here, we compare how positive and negative feedback affect information-integration (II) category learning. Ashby and O'Brien (2007) demonstrated that both positive and negative feedback are required to solve II category problems when feedback was not guaranteed on each trial, and reported no differences between positive-only and negative-only feedback in terms of their effectiveness. We followed up on these findings and conducted 3 experiments in which participants completed 2,400 II categorization trials across three days under 1 of 3 conditions: positive feedback only (PFB), negative feedback only (NFB), or both types of feedback (CP; control partial). An adaptive algorithm controlled the amount of feedback given to each group so that feedback was nearly equated. Using different feedback control procedures, Experiments 1 and 2 demonstrated that participants in the NFB and CP group were able to engage II learning strategies, whereas the PFB group was not. Additionally, the NFB group was able to achieve significantly higher accuracy than the PFB group by Day 3. Experiment 3 revealed that these differences remained even when we equated the information received on feedback trials. Thus, negative feedback appears significantly more effective for learning II category structures. This suggests that the human implicit learning system may be capable of learning in the absence of positive feedback.

The lasting effects of process-specific versus stimulus-specific learning during infancy.

PubMed

Hadley, Hillary; Pickron, Charisse B; Scott, Lisa S

2015-09-01

The capacity to tell the difference between two faces within an infrequently experienced face group (e.g. other species, other race) declines from 6 to 9 months of age unless infants learn to match these faces with individual-level names. Similarly, the use of individual-level labels can also facilitate differentiation of a group of non-face objects (strollers). This early learning leads to increased neural specialization for previously unfamiliar face or object groups. The current investigation aimed to determine whether early conceptual learning between 6 and 9 months leads to sustained behavioral advantages and neural changes in these same children at 4-6 years of age. Results suggest that relative to a control group of children with no previous training and to children with infant category-level naming experience, children with early individual-level training exhibited faster response times to human faces. Further, individual-level training with a face group - but not an object group - led to more adult-like neural responses for human faces. These results suggest that early individual-level learning results in long-lasting process-specific effects, which benefit categories that continue to be perceived and recognized at the individual level (e.g. human faces). © 2014 John Wiley & Sons Ltd.

Failed State: A New (Old) Definition

DTIC Science & Technology

2010-04-21

school curriculum into CD-ROMs so students can learn interactively with the aid of computers. Programa Escuelas de Calidad, or quality schools program...12 Ibid., 133. 13 David Hume, Treatise on Human Nature (London: Longmans, 1874), 415. 14 Charles de Secondat Montesquieu, The...category political legitimacy and the sub-categories of regime inclusions , factionalism, political salience of elite ethnicity, polity fragmentation

Information-integration category learning and the human uncertainty response.

PubMed

Paul, Erick J; Boomer, Joseph; Smith, J David; Ashby, F Gregory

2011-04-01

The human response to uncertainty has been well studied in tasks requiring attention and declarative memory systems. However, uncertainty monitoring and control have not been studied in multi-dimensional, information-integration categorization tasks that rely on non-declarative procedural memory. Three experiments are described that investigated the human uncertainty response in such tasks. Experiment 1 showed that following standard categorization training, uncertainty responding was similar in information-integration tasks and rule-based tasks requiring declarative memory. In Experiment 2, however, uncertainty responding in untrained information-integration tasks impaired the ability of many participants to master those tasks. Finally, Experiment 3 showed that the deficit observed in Experiment 2 was not because of the uncertainty response option per se, but rather because the uncertainty response provided participants a mechanism via which to eliminate stimuli that were inconsistent with a simple declarative response strategy. These results are considered in the light of recent models of category learning and metacognition.

The Adoption of E-Learning across Professional Groups

ERIC Educational Resources Information Center

Gallaher, James; Wentling, Tim L.

2004-01-01

The purpose of the study was to determine the impact of professional group membership on the rate of adoption of e-learning. The sample consisted of Engineering, Finance, Human Resources, Legal, and Marketing professionals from a Fortune 500 manufacturing company. Professional groups were categorized based on Rogers (1995) five categories of…

Evolution of a Rapidly Learned Representation for Speech.

ERIC Educational Resources Information Center

Nakisa, Ramin Charles; Plunkett, Kim

1998-01-01

Describes a connectionist model accounting for newborn infants' ability to finely discriminate almost all human speech contrasts and the fact that their phonemic category boundaries are identical, even for phonemes outside their target language. The model posits an innately guided learning in which an artificial neural network is stored in a…

Hierarchical control of procedural and declarative category-learning systems

PubMed Central

Turner, Benjamin O.; Crossley, Matthew J.; Ashby, F. Gregory

2017-01-01

Substantial evidence suggests that human category learning is governed by the interaction of multiple qualitatively distinct neural systems. In this view, procedural memory is used to learn stimulus-response associations, and declarative memory is used to apply explicit rules and test hypotheses about category membership. However, much less is known about the interaction between these systems: how is control passed between systems as they interact to influence motor resources? Here, we used fMRI to elucidate the neural correlates of switching between procedural and declarative categorization systems. We identified a key region of the cerebellum (left Crus I) whose activity was bidirectionally modulated depending on switch direction. We also identified regions of the default mode network (DMN) that were selectively connected to left Crus I during switching. We propose that the cerebellum—in coordination with the DMN—serves a critical role in passing control between procedural and declarative memory systems. PMID:28213114

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

PubMed

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.

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

PubMed Central

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. PMID:27445958

"Detached concern" of medical students in a cadaver dissection course: A phenomenological study.

PubMed

Tseng, Wei-Ting; Lin, Ya-Ping

2016-05-06

The cadaver dissection course remains a time-honored tradition in medical education, partly because of its importance in cultivating professional attitudes in students. This study aims to investigate students' attitudes-specifically characterized as "detached concern"-in a cadaver dissection course. An interpretative phenomenological analysis was performed with semi-structured, focus group interviews among 12 third-year medical students from a Taiwanese medical school to reveal their perceptions and learning experiences regarding human cadaver dissection. Based on these interviews, four relevant categories of perspectives were delineated: (1) initial emotional impact, (2) human referents, (3) coping strategies, and (4) ways of perceiving cadavers. Students were divided into two groups based on these categories. Students in Group 1 developed mechanisms described as "detachment" to cope with their initial emotional reactions to cadaveric dissection, which was noted to have disruptive effects on their learning. They considered human referents to be learning obstacles and avoided contact with or thinking about the human referents while performing dissections. Some of them faced a conflict between perceiving the cadaver as a learning tool versus as a human being. This impasse could be resolved if they latently adopted a "perspective switch" between the concept of a learning tool (rational aspect) and a human being (sensitive aspect). The students in Group 2 had no obvious initial emotional reaction. For them, the human referents functioned as learning supports, and the cadavers were consistently perceived as humans. These students held the notion that "cadaver dissection is an act of love"; therefore, they did not experience any need to detach themselves from their feelings during dissection. This alternative attitude revealed that detached concern alone is not sufficient to describe the entire range of medical students' attitudes toward cadaver dissection. Anat Sci Educ 9: 265-271. © 2015 American Association of Anatomists. © 2015 American Association of Anatomists.

Children Use Object-Level Category Knowledge to Detect Changes in Complex Auditory Scenes

ERIC Educational Resources Information Center

Vanden Bosch der Nederlanden, Christina M.; Snyder, Joel S.; Hannon, Erin E.

2016-01-01

Children interact with and learn about all types of sound sources, including dogs, bells, trains, and human beings. Although it is clear that knowledge of semantic categories for everyday sights and sounds develops during childhood, there are very few studies examining how children use this knowledge to make sense of auditory scenes. We used a…

The Role of Feedback Contingency in Perceptual Category Learning

ERIC Educational Resources Information Center

Ashby, F. Gregory; Vucovich, Lauren E.

2016-01-01

Feedback is highly contingent on behavior if it eventually becomes easy to predict, and weakly contingent on behavior if it remains difficult or impossible to predict even after learning is complete. Many studies have demonstrated that humans and nonhuman animals are highly sensitive to feedback contingency, but no known studies have examined how…

Out of sight, out of mind: Categorization learning and normal aging.

PubMed

Schenk, Sabrina; Minda, John P; Lech, Robert K; Suchan, Boris

2016-10-01

The present combined EEG and eye tracking study examined the process of categorization learning at different age ranges and aimed to investigate to which degree categorization learning is mediated by visual attention and perceptual strategies. Seventeen young subjects and ten elderly subjects had to perform a visual categorization task with two abstract categories. Each category consisted of prototypical stimuli and an exception. The categorization of prototypical stimuli was learned very early during the experiment, while the learning of exceptions was delayed. The categorization of exceptions was accompanied by higher P150, P250 and P300 amplitudes. In contrast to younger subjects, elderly subjects had problems in the categorization of exceptions, but showed an intact categorization performance for prototypical stimuli. Moreover, elderly subjects showed higher fixation rates for important stimulus features and higher P150 amplitudes, which were positively correlated with the categorization performances. These results indicate that elderly subjects compensate for cognitive decline through enhanced perceptual and attentional processing of individual stimulus features. Additionally, a computational approach has been applied and showed a transition away from purely abstraction-based learning to an exemplar-based learning in the middle block for both groups. However, the calculated models provide a better fit for younger subjects than for elderly subjects. The current study demonstrates that human categorization learning is based on early abstraction-based processing followed by an exemplar-memorization stage. This strategy combination facilitates the learning of real world categories with a nuanced category structure. In addition, the present study suggests that categorization learning is affected by normal aging and modulated by perceptual processing and visual attention. Copyright © 2016 Elsevier Ltd. All rights reserved.

Diagnosticity and Prototypicality in Category Learning: A Comparison of Inference Learning and Classification Learning

ERIC Educational Resources Information Center

Chin-Parker, Seth; Ross, Brian H.

2004-01-01

Category knowledge allows for both the determination of category membership and an understanding of what the members of a category are like. Diagnostic information is used to determine category membership; prototypical information reflects the most likely features given category membership. Two experiments examined 2 means of category learning,…

The cost of selective attention in category learning: Developmental differences between adults and infants

PubMed Central

Best, Catherine A.; Yim, Hyungwook; Sloutsky, Vladimir M.

2013-01-01

Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6–8 months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. PMID:23773914

Supervised and Unsupervised Learning of Multidimensional Acoustic Categories

ERIC Educational Resources Information Center

Goudbeek, Martijn; Swingley, Daniel; Smits, Roel

2009-01-01

Learning to recognize the contrasts of a language-specific phonemic repertoire can be viewed as forming categories in a multidimensional psychophysical space. Research on the learning of distributionally defined visual categories has shown that categories defined over 1 dimension are easy to learn and that learning multidimensional categories is…

Incidental Auditory Category Learning

PubMed Central

Gabay, Yafit; Dick, Frederic K.; Zevin, Jason D.; Holt, Lori L.

2015-01-01

Very little is known about how auditory categories are learned incidentally, without instructions to search for category-diagnostic dimensions, overt category decisions, or experimenter-provided feedback. This is an important gap because learning in the natural environment does not arise from explicit feedback and there is evidence that the learning systems engaged by traditional tasks are distinct from those recruited by incidental category learning. We examined incidental auditory category learning with a novel paradigm, the Systematic Multimodal Associations Reaction Time (SMART) task, in which participants rapidly detect and report the appearance of a visual target in one of four possible screen locations. Although the overt task is rapid visual detection, a brief sequence of sounds precedes each visual target. These sounds are drawn from one of four distinct sound categories that predict the location of the upcoming visual target. These many-to-one auditory-to-visuomotor correspondences support incidental auditory category learning. Participants incidentally learn categories of complex acoustic exemplars and generalize this learning to novel exemplars and tasks. Further, learning is facilitated when category exemplar variability is more tightly coupled to the visuomotor associations than when the same stimulus variability is experienced across trials. We relate these findings to phonetic category learning. PMID:26010588

Dual-learning systems during speech category learning

PubMed Central

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

2013-01-01

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

Children's Category-Based Inferences Affect Classification

ERIC Educational Resources Information Center

Ross, Brian H.; Gelman, Susan A.; Rosengren, Karl S.

2005-01-01

Children learn many new categories and make inferences about these categories. Much work has examined how children make inferences on the basis of category knowledge. However, inferences may also affect what is learned about a category. Four experiments examine whether category-based inferences during category learning influence category knowledge…

Transfer between local and global processing levels by pigeons (Columba livia) and humans (Homo sapiens) in exemplar- and rule-based categorization tasks.

PubMed

Aust, Ulrike; Braunöder, Elisabeth

2015-02-01

The present experiment investigated pigeons' and humans' processing styles-local or global-in an exemplar-based visual categorization task in which category membership of every stimulus had to be learned individually, and in a rule-based task in which category membership was defined by a perceptual rule. Group Intact was trained with the original pictures (providing both intact local and global information), Group Scrambled was trained with scrambled versions of the same pictures (impairing global information), and Group Blurred was trained with blurred versions (impairing local information). Subsequently, all subjects were tested for transfer to the 2 untrained presentation modes. Humans outperformed pigeons regarding learning speed and accuracy as well as transfer performance and showed good learning irrespective of group assignment, whereas the pigeons of Group Blurred needed longer to learn the training tasks than the pigeons of Groups Intact and Scrambled. Also, whereas humans generalized equally well to any novel presentation mode, pigeons' transfer from and to blurred stimuli was impaired. Both species showed faster learning and, for the most part, better transfer in the rule-based than in the exemplar-based task, but there was no evidence of the used processing mode depending on the type of task (exemplar- or rule-based). Whereas pigeons relied on local information throughout, humans did not show a preference for either processing level. Additional tests with grayscale versions of the training stimuli, with versions that were both blurred and scrambled, and with novel instances of the rule-based task confirmed and further extended these findings. PsycINFO Database Record (c) 2015 APA, all rights reserved.

A Meta-Analysis Suggests Different Neural Correlates for Implicit and Explicit Learning.

PubMed

Loonis, Roman F; Brincat, Scott L; Antzoulatos, Evan G; Miller, Earl K

2017-10-11

A meta-analysis of non-human primates performing three different tasks (Object-Match, Category-Match, and Category-Saccade associations) revealed signatures of explicit and implicit learning. Performance improved equally following correct and error trials in the Match (explicit) tasks, but it improved more after correct trials in the Saccade (implicit) task, a signature of explicit versus implicit learning. Likewise, error-related negativity, a marker for error processing, was greater in the Match (explicit) tasks. All tasks showed an increase in alpha/beta (10-30 Hz) synchrony after correct choices. However, only the implicit task showed an increase in theta (3-7 Hz) synchrony after correct choices that decreased with learning. In contrast, in the explicit tasks, alpha/beta synchrony increased with learning and decreased thereafter. Our results suggest that explicit versus implicit learning engages different neural mechanisms that rely on different patterns of oscillatory synchrony. Copyright © 2017 Elsevier Inc. All rights reserved.

Toward a dual-learning systems model of speech category learning

PubMed Central

Chandrasekaran, Bharath; Koslov, Seth R.; Maddox, W. T.

2014-01-01

More than two decades of work in vision posits the existence of dual-learning systems of category learning. The reflective system uses working memory to develop and test rules for classifying in an explicit fashion, while the reflexive system operates by implicitly associating perception with actions that lead to reinforcement. Dual-learning systems models hypothesize that in learning natural categories, learners initially use the reflective system and, with practice, transfer control to the reflexive system. The role of reflective and reflexive systems in auditory category learning and more specifically in speech category learning has not been systematically examined. In this article, we describe a neurobiologically constrained dual-learning systems theoretical framework that is currently being developed in speech category learning and review recent applications of this framework. Using behavioral and computational modeling approaches, we provide evidence that speech category learning is predominantly mediated by the reflexive learning system. In one application, we explore the effects of normal aging on non-speech and speech category learning. Prominently, we find a large age-related deficit in speech learning. The computational modeling suggests that older adults are less likely to transition from simple, reflective, unidimensional rules to more complex, reflexive, multi-dimensional rules. In a second application, we summarize a recent study examining auditory category learning in individuals with elevated depressive symptoms. We find a deficit in reflective-optimal and an enhancement in reflexive-optimal auditory category learning. Interestingly, individuals with elevated depressive symptoms also show an advantage in learning speech categories. We end with a brief summary and description of a number of future directions. PMID:25132827

The cost of selective attention in category learning: developmental differences between adults and infants.

PubMed

Best, Catherine A; Yim, Hyungwook; Sloutsky, Vladimir M

2013-10-01

Selective attention plays an important role in category learning. However, immaturities of top-down attentional control during infancy coupled with successful category learning suggest that early category learning is achieved without attending selectively. Research presented here examines this possibility by focusing on category learning in infants (6-8months old) and adults. Participants were trained on a novel visual category. Halfway through the experiment, unbeknownst to participants, the to-be-learned category switched to another category, where previously relevant features became irrelevant and previously irrelevant features became relevant. If participants attend selectively to the relevant features of the first category, they should incur a cost of selective attention immediately after the unknown category switch. Results revealed that adults demonstrated a cost, as evidenced by a decrease in accuracy and response time on test trials as well as a decrease in visual attention to newly relevant features. In contrast, infants did not demonstrate a similar cost of selective attention as adults despite evidence of learning both to-be-learned categories. Findings are discussed as supporting multiple systems of category learning and as suggesting that learning mechanisms engaged by adults may be different from those engaged by infants. Copyright © 2013 Elsevier Inc. All rights reserved.

Human Factors in Accidents Involving Remotely Piloted Aircraft

NASA Technical Reports Server (NTRS)

Merlin, Peter William

2013-01-01

This presentation examines human factors that contribute to RPA mishaps and provides analysis of lessons learned. RPA accident data from U.S. military and government agencies were reviewed and analyzed to identify human factors issues. Common contributors to RPA mishaps fell into several major categories: cognitive factors (pilot workload), physiological factors (fatigue and stress), environmental factors (situational awareness), staffing factors (training and crew coordination), and design factors (human machine interface).

Generating action descriptions from statistically integrated representations of human motions and sentences.

PubMed

Takano, Wataru; Kusajima, Ikuo; Nakamura, Yoshihiko

2016-08-01

It is desirable for robots to be able to linguistically understand human actions during human-robot interactions. Previous research has developed frameworks for encoding human full body motion into model parameters and for classifying motion into specific categories. For full understanding, the motion categories need to be connected to the natural language such that the robots can interpret human motions as linguistic expressions. This paper proposes a novel framework for integrating observation of human motion with that of natural language. This framework consists of two models; the first model statistically learns the relations between motions and their relevant words, and the second statistically learns sentence structures as word n-grams. Integration of these two models allows robots to generate sentences from human motions by searching for words relevant to the motion using the first model and then arranging these words in appropriate order using the second model. This allows making sentences that are the most likely to be generated from the motion. The proposed framework was tested on human full body motion measured by an optical motion capture system. In this, descriptive sentences were manually attached to the motions, and the validity of the system was demonstrated. Copyright © 2016 Elsevier Ltd. All rights reserved.

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

PubMed

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

2017-05-01

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

The Future of Contextual Fear Learning for PTSD Research: A Methodological Review of Neuroimaging Studies.

PubMed

Glenn, Daniel E; Risbrough, Victoria B; Simmons, Alan N; Acheson, Dean T; Stout, Daniel M

2017-10-21

There has been a great deal of recent interest in human models of contextual fear learning, particularly due to the use of such paradigms for investigating neural mechanisms related to the etiology of posttraumatic stress disorder. However, the construct of "context" in fear conditioning research is broad, and the operational definitions and methods used to investigate contextual fear learning in humans are wide ranging and lack specificity, making it difficult to interpret findings about neural activity. Here we will review neuroimaging studies of contextual fear acquisition in humans. We will discuss the methodology associated with four broad categories of how contextual fear learning is manipulated in imaging studies (colored backgrounds, static picture backgrounds, virtual reality, and configural stimuli) and highlight findings for the primary neural circuitry involved in each paradigm. Additionally, we will offer methodological recommendations for human studies of contextual fear acquisition, including using stimuli that distinguish configural learning from discrete cue associations and clarifying how context is experimentally operationalized.

Mere exposure alters category learning of novel objects.

PubMed

Folstein, Jonathan R; Gauthier, Isabel; Palmeri, Thomas J

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning.

Mere Exposure Alters Category Learning of Novel Objects

PubMed Central

Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.

2010-01-01

We investigated how mere exposure to complex objects with correlated or uncorrelated object features affects later category learning of new objects not seen during exposure. Correlations among pre-exposed object dimensions influenced later category learning. Unlike other published studies, the collection of pre-exposed objects provided no information regarding the categories to be learned, ruling out unsupervised or incidental category learning during pre-exposure. Instead, results are interpreted with respect to statistical learning mechanisms, providing one of the first demonstrations of how statistical learning can influence visual object learning. PMID:21833209

Individual Differences in Learning Talker Categories: The Role of Working Memory

PubMed Central

Levi, Susannah V.

2016-01-01

The current study explores the question of how an auditory category is learned by having school-age listeners learn to categorize speech not in terms of linguistic categories, but instead in terms of talker categories (i.e., who is talking). Findings from visual-category learning indicate that working memory skills affect learning, but the literature is equivocal: sometimes better working memory is advantageous, and sometimes not. The current study examined the role of different components of working memory to test which component skills benefit, and which hinder, learning talker categories. Results revealed that the short-term storage component positively predicted learning, but that the Central Executive and Episodic Buffer negatively predicted learning. As with visual categories, better working memory is not always an advantage. PMID:25721393

Statistical Inference in the Learning of Novel Phonetic Categories

ERIC Educational Resources Information Center

Zhao, Yuan

2010-01-01

Learning a phonetic category (or any linguistic category) requires integrating different sources of information. A crucial unsolved problem for phonetic learning is how this integration occurs: how can we update our previous knowledge about a phonetic category as we hear new exemplars of the category? One model of learning is Bayesian Inference,…

Classification versus inference learning contrasted with real-world categories.

PubMed

Jones, Erin L; Ross, Brian H

2011-07-01

Categories are learned and used in a variety of ways, but the research focus has been on classification learning. Recent work contrasting classification with inference learning of categories found important later differences in category performance. However, theoretical accounts differ on whether this is due to an inherent difference between the tasks or to the implementation decisions. The inherent-difference explanation argues that inference learners focus on the internal structure of the categories--what each category is like--while classification learners focus on diagnostic information to predict category membership. In two experiments, using real-world categories and controlling for earlier methodological differences, inference learners learned more about what each category was like than did classification learners, as evidenced by higher performance on a novel classification test. These results suggest that there is an inherent difference between learning new categories by classifying an item versus inferring a feature.

Learning about the internal structure of categories through classification and feature inference.

PubMed

Jee, Benjamin D; Wiley, Jennifer

2014-01-01

Previous research on category learning has found that classification tasks produce representations that are skewed toward diagnostic feature dimensions, whereas feature inference tasks lead to richer representations of within-category structure. Yet, prior studies often measure category knowledge through tasks that involve identifying only the typical features of a category. This neglects an important aspect of a category's internal structure: how typical and atypical features are distributed within a category. The present experiments tested the hypothesis that inference learning results in richer knowledge of internal category structure than classification learning. We introduced several new measures to probe learners' representations of within-category structure. Experiment 1 found that participants in the inference condition learned and used a wider range of feature dimensions than classification learners. Classification learners, however, were more sensitive to the presence of atypical features within categories. Experiment 2 provided converging evidence that classification learners were more likely to incorporate atypical features into their representations. Inference learners were less likely to encode atypical category features, even in a "partial inference" condition that focused learners' attention on the feature dimensions relevant to classification. Overall, these results are contrary to the hypothesis that inference learning produces superior knowledge of within-category structure. Although inference learning promoted representations that included a broad range of category-typical features, classification learning promoted greater sensitivity to the distribution of typical and atypical features within categories.

Generalization of Pain-Related Fear Based on Conceptual Knowledge.

PubMed

Meulders, Ann; Vandael, Kristof; Vlaeyen, Johan W S

2017-05-01

Increasing evidence suggests that pain-related fear is key to the transition from acute to chronic pain. Previous research has shown that perceptual similarity with a pain-associated movement fosters the generalization of fear to novel movements. Perceptual generalization of pain-related fear is adaptive as it enables individuals to extrapolate the threat value of one movement to another without the necessity to learn anew. However, excessive spreading of fear to safe movements may become maladaptive and may lead to sustained anxiety, dysfunctional avoidance behaviors, and severe disability. A hallmark of human cognition is the ability to extract conceptual knowledge from a learning episode as well. Although this conceptual pathway may be important to understand fear generalization in chronic pain, research on this topic is lacking. We investigated acquisition and generalization of concept-based pain-related fear. During acquisition, unique exemplars of one action category (CS+; e.g., opening boxes) were followed by pain, whereas exemplars of another action category (CS-; e.g., closing boxes) were not. Subsequently, spreading of pain-related fear to novel exemplars of both action categories was tested. Participants learned to expect the pain to occur and reported more pain-related fear to the exemplars of the CS+ category compared with those of the CS- category. During generalization, fear and expectancy generalized to novel exemplars of the CS+ category, but not to the CS- category. This pattern was not corroborated in the eyeblink startle measures. This is the first study that demonstrates that pain-related fear can be acquired and generalized based on conceptual knowledge. Copyright © 2016. Published by Elsevier Ltd.

Category Learning in Rhesus Monkeys: A Study of the Shepard, Hovland, and Jenkins (1961) Tasks

ERIC Educational Resources Information Center

Smith, J. David; Minda, John Paul; Washburn, David A.

2004-01-01

In influential research, R. N. Shepard, C. I. Hovland, and H. M. Jenkins (1961) surveyed humans' categorization abilities using tasks based in rules, exclusive-or (XOR) relations, and exemplar memorization. Humans' performance was poorly predicted by cue-conditioning or stimulus-generalization theories, causing Shepard et al. to describe it in…

Learning new color names produces rapid increase in gray matter in the intact adult human cortex

PubMed Central

Kwok, Veronica; Niu, Zhendong; Kay, Paul; Zhou, Ke; Mo, Lei; Jin, Zhen; So, Kwok-Fai; Tan, Li Hai

2011-01-01

The human brain has been shown to exhibit changes in the volume and density of gray matter as a result of training over periods of several weeks or longer. We show that these changes can be induced much faster by using a training method that is claimed to simulate the rapid learning of word meanings by children. Using whole-brain magnetic resonance imaging (MRI) we show that learning newly defined and named subcategories of the universal categories green and blue in a period of 2 h increases the volume of gray matter in V2/3 of the left visual cortex, a region known to mediate color vision. This pattern of findings demonstrates that the anatomical structure of the adult human brain can change very quickly, specifically during the acquisition of new, named categories. Also, prior behavioral and neuroimaging research has shown that differences between languages in the boundaries of named color categories influence the categorical perception of color, as assessed by judgments of relative similarity, by response time in alternative forced-choice tasks, and by visual search. Moreover, further behavioral studies (visual search) and brain imaging studies have suggested strongly that the categorical effect of language on color processing is left-lateralized, i.e., mediated by activity in the left cerebral hemisphere in adults (hence “lateralized Whorfian” effects). The present results appear to provide a structural basis in the brain for the behavioral and neurophysiologically observed indices of these Whorfian effects on color processing. PMID:21464316

Contextual modulation of attention in human category learning.

PubMed

George, David N; Kruschke, John K

2012-12-01

In a category-learning experiment, we assessed whether participants were able to selectively attend to different components of a compound stimulus in two distinct contexts. The participants were presented with stimulus compounds for which they had to learn categorical labels. Each compound comprised one feature from each of two dimensions, and on different trials the compound was presented in two contexts, X and Y. In Context X, Dimension A was relevant to the solution of the categorization task and Dimension B was irrelevant, whereas in Context Y, Dimension A was irrelevant and Dimension B was relevant. The results of transfer tests to novel stimuli suggested that people learned to attend selectively to Dimension A in Context X and Dimension B in Context Y. These findings contribute to the growing body of evidence that people can learn to selectively attend to particular dimensions of stimuli dependent on the context in which the stimuli are presented. Furthermore, the findings demonstrate that context-dependent changes in attention transfer to other categorization tasks involving novel stimuli.

Analyse von Unterrichtsmaterialien der Menschenrechtsbildung

NASA Astrophysics Data System (ADS)

Lenhart, Volker

2002-07-01

This article surveys five manuals on human rights education, examining and comparing them according to a set of basic categories such as the educational level of the target audience, the learning objectives and the educational content. This approach is used to establish the overall curricular orientation of the manuals. In addition, one teaching unit from each manual is selected for special analysis. Based on the results of this survey, the author argues that the tradition of moral education elaborated by Lawrence Kohlberg should be integrated into our concept of human rights teaching and learning.

The Effects of Concurrent Verbal and Visual Tasks on Category Learning

ERIC Educational Resources Information Center

Miles, Sarah J.; Minda, John Paul

2011-01-01

Current theories of category learning posit separate verbal and nonverbal learning systems. Past research suggests that the verbal system relies on verbal working memory and executive functioning and learns rule-defined categories; the nonverbal system does not rely on verbal working memory and learns non-rule-defined categories (E. M. Waldron…

A reappraisal of the uncanny valley: categorical perception or frequency-based sensitization?

PubMed Central

Burleigh, Tyler J.; Schoenherr, Jordan R.

2015-01-01

The uncanny valley (UCV) hypothesis describes a non-linear relationship between perceived human-likeness and affective response. The “uncanny valley” refers to an intermediate level of human-likeness that is associated with strong negative affect. Recent studies have suggested that the uncanny valley might result from the categorical perception of human-like stimuli during identification. When presented with stimuli sharing human-like traits, participants attempt to segment the continuum in “human” and “non-human” categories. Due to the ambiguity of stimuli located at a category boundary, categorization difficulty gives rise to a strong, negative affective response. Importantly, researchers who have studied the UCV in terms of categorical perception have focused on categorization responses rather than affective ratings. In the present study, we examined whether the negative affect associated with the UCV might be explained in terms of an individual's degree of exposure to stimuli. In two experiments, we tested a frequency-based model against a categorical perception model using a category-learning paradigm. We manipulated the frequency of exemplars that were presented to participants from two categories during a training phase. We then examined categorization and affective responses functions, as well as the relationship between categorization and affective responses. Supporting previous findings, categorization responses suggested that participants acquired novel category structures that reflected a category boundary. These category structures appeared to influence affective ratings of eeriness. Crucially, participants' ratings of eeriness were additionally affected by exemplar frequency. Taken together, these findings suggest that the UCV is determined by both categorical properties as well as the frequency of individual exemplars retained in memory. PMID:25653623

Adaptive learning in a compartmental model of visual cortex—how feedback enables stable category learning and refinement

PubMed Central

Layher, Georg; Schrodt, Fabian; Butz, Martin V.; Neumann, Heiko

2014-01-01

The categorization of real world objects is often reflected in the similarity of their visual appearances. Such categories of objects do not necessarily form disjunct sets of objects, neither semantically nor visually. The relationship between categories can often be described in terms of a hierarchical structure. For instance, tigers and leopards build two separate mammalian categories, both of which are subcategories of the category Felidae. In the last decades, the unsupervised learning of categories of visual input stimuli has been addressed by numerous approaches in machine learning as well as in computational neuroscience. However, the question of what kind of mechanisms might be involved in the process of subcategory learning, or category refinement, remains a topic of active investigation. We propose a recurrent computational network architecture for the unsupervised learning of categorial and subcategorial visual input representations. During learning, the connection strengths of bottom-up weights from input to higher-level category representations are adapted according to the input activity distribution. In a similar manner, top-down weights learn to encode the characteristics of a specific stimulus category. Feedforward and feedback learning in combination realize an associative memory mechanism, enabling the selective top-down propagation of a category's feedback weight distribution. We suggest that the difference between the expected input encoded in the projective field of a category node and the current input pattern controls the amplification of feedforward-driven representations. Large enough differences trigger the recruitment of new representational resources and the establishment of additional (sub-) category representations. We demonstrate the temporal evolution of such learning and show how the proposed combination of an associative memory with a modulatory feedback integration successfully establishes category and subcategory representations. PMID:25538637

Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning.

PubMed

Minda, John P; Rabi, Rahel

2015-01-01

Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants' executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory.

Ego depletion interferes with rule-defined category learning but not non-rule-defined category learning

PubMed Central

Minda, John P.; Rabi, Rahel

2015-01-01

Considerable research on category learning has suggested that many cognitive and environmental factors can have a differential effect on the learning of rule-defined (RD) categories as opposed to the learning of non-rule-defined (NRD) categories. Prior research has also suggested that ego depletion can temporarily reduce the capacity for executive functioning and cognitive flexibility. The present study examined whether temporarily reducing participants’ executive functioning via a resource depletion manipulation would differentially impact RD and NRD category learning. Participants were either asked to write a story with no restrictions (the control condition), or without using two common letters (the ego depletion condition). Participants were then asked to learn either a set of RD categories or a set of NRD categories. Resource depleted participants performed more poorly than controls on the RD task, but did not differ from controls on the NRD task, suggesting that self regulatory resources are required for successful RD category learning. These results lend support to multiple systems theories and clarify the role of self-regulatory resources within this theory. PMID:25688220

Feature Inference Learning and Eyetracking

ERIC Educational Resources Information Center

Rehder, Bob; Colner, Robert M.; Hoffman, Aaron B.

2009-01-01

Besides traditional supervised classification learning, people can learn categories by inferring the missing features of category members. It has been proposed that feature inference learning promotes learning a category's internal structure (e.g., its typical features and interfeature correlations) whereas classification promotes the learning of…

Chromatic Perceptual Learning but No Category Effects without Linguistic Input.

PubMed

Grandison, Alexandra; Sowden, Paul T; Drivonikou, Vicky G; Notman, Leslie A; Alexander, Iona; Davies, Ian R L

2016-01-01

Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce emerging category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest.

Consider the category: The effect of spacing depends on individual learning histories.

PubMed

Slone, Lauren K; Sandhofer, Catherine M

2017-07-01

The spacing effect refers to increased retention following learning instances that are spaced out in time compared with massed together in time. By one account, the advantages of spaced learning should be independent of task particulars and previous learning experiences given that spacing effects have been demonstrated in a variety of tasks across the lifespan. However, by another account, spaced learning should be affected by previous learning because past learning affects the memory and attention processes that form the crux of the spacing effect. The current study investigated whether individuals' learning histories affect the role of spacing in category learning. We examined the effect of spacing on 24 2- to 3.5-year-old children's learning of categories organized by properties to which children's previous learning experiences have biased them to attend (i.e., shape) and properties to which children are less biased to attend (i.e., texture and color). Spaced presentations led to significantly better learning of shape categories, but not of texture or color categories, compared with massed presentations. In addition, generalized estimating equations analyses revealed positive relations between the size of children's "shape-side" productive vocabularies and their shape category learning and between the size of children's "against-the-system" productive vocabularies and their texture category learning. These results suggest that children's attention to and memory for novel object categories are strongly related to their individual word-learning histories. Moreover, children's learned attentional biases affected the types of categories for which spacing facilitated learning. These findings highlight the importance of considering how learners' previous experiences may influence future learning. Copyright © 2017 Elsevier Inc. All rights reserved.

Relative risk of probabilistic category learning deficits in patients with schizophrenia and their siblings

PubMed Central

Weickert, Thomas W.; Goldberg, Terry E.; Egan, Michael F.; Apud, Jose A.; Meeter, Martijn; Myers, Catherine E.; Gluck, Mark A; Weinberger, Daniel R.

2010-01-01

Background While patients with schizophrenia display an overall probabilistic category learning performance deficit, the extent to which this deficit occurs in unaffected siblings of patients with schizophrenia is unknown. There are also discrepant findings regarding probabilistic category learning acquisition rate and performance in patients with schizophrenia. Methods A probabilistic category learning test was administered to 108 patients with schizophrenia, 82 unaffected siblings, and 121 healthy participants. Results Patients with schizophrenia displayed significant differences from their unaffected siblings and healthy participants with respect to probabilistic category learning acquisition rates. Although siblings on the whole failed to differ from healthy participants on strategy and quantitative indices of overall performance and learning acquisition, application of a revised learning criterion enabling classification into good and poor learners based on individual learning curves revealed significant differences between percentages of sibling and healthy poor learners: healthy (13.2%), siblings (34.1%), patients (48.1%), yielding a moderate relative risk. Conclusions These results clarify previous discrepant findings pertaining to probabilistic category learning acquisition rate in schizophrenia and provide the first evidence for the relative risk of probabilistic category learning abnormalities in unaffected siblings of patients with schizophrenia, supporting genetic underpinnings of probabilistic category learning deficits in schizophrenia. These findings also raise questions regarding the contribution of antipsychotic medication to the probabilistic category learning deficit in schizophrenia. The distinction between good and poor learning may be used to inform genetic studies designed to detect schizophrenia risk alleles. PMID:20172502

The contribution of temporary storage and executive processes to category learning.

PubMed

Wang, Tengfei; Ren, Xuezhu; Schweizer, Karl

2015-09-01

Three distinctly different working memory processes, temporary storage, mental shifting and inhibition, were proposed to account for individual differences in category learning. A sample of 213 participants completed a classic category learning task and two working memory tasks that were experimentally manipulated for tapping specific working memory processes. Fixed-links models were used to decompose data of the category learning task into two independent components representing basic performance and improvement in performance in category learning. Processes of working memory were also represented by fixed-links models. In a next step the three working memory processes were linked to components of category learning. Results from modeling analyses indicated that temporary storage had a significant effect on basic performance and shifting had a moderate effect on improvement in performance. In contrast, inhibition showed no effect on any component of the category learning task. These results suggest that temporary storage and the shifting process play different roles in the course of acquiring new categories. Copyright © 2015 Elsevier B.V. All rights reserved.

The mirror-neuron system.

PubMed

Rizzolatti, Giacomo; Craighero, Laila

2004-01-01

A category of stimuli of great importance for primates, humans in particular, is that formed by actions done by other individuals. If we want to survive, we must understand the actions of others. Furthermore, without action understanding, social organization is impossible. In the case of humans, there is another faculty that depends on the observation of others' actions: imitation learning. Unlike most species, we are able to learn by imitation, and this faculty is at the basis of human culture. In this review we present data on a neurophysiological mechanism--the mirror-neuron mechanism--that appears to play a fundamental role in both action understanding and imitation. We describe first the functional properties of mirror neurons in monkeys. We review next the characteristics of the mirror-neuron system in humans. We stress, in particular, those properties specific to the human mirror-neuron system that might explain the human capacity to learn by imitation. We conclude by discussing the relationship between the mirror-neuron system and language.

Category transfer in sequential causal learning: the unbroken mechanism hypothesis.

PubMed

Hagmayer, York; Meder, Björn; von Sydow, Momme; Waldmann, Michael R

2011-07-01

The goal of the present set of studies is to explore the boundary conditions of category transfer in causal learning. Previous research has shown that people are capable of inducing categories based on causal learning input, and they often transfer these categories to new causal learning tasks. However, occasionally learners abandon the learned categories and induce new ones. Whereas previously it has been argued that transfer is only observed with essentialist categories in which the hidden properties are causally relevant for the target effect in the transfer relation, we here propose an alternative explanation, the unbroken mechanism hypothesis. This hypothesis claims that categories are transferred from a previously learned causal relation to a new causal relation when learners assume a causal mechanism linking the two relations that is continuous and unbroken. The findings of two causal learning experiments support the unbroken mechanism hypothesis. Copyright © 2011 Cognitive Science Society, Inc.

Chromatic Perceptual Learning but No Category Effects without Linguistic Input

PubMed Central

Grandison, Alexandra; Sowden, Paul T.; Drivonikou, Vicky G.; Notman, Leslie A.; Alexander, Iona; Davies, Ian R. L.

2016-01-01

Perceptual learning involves an improvement in perceptual judgment with practice, which is often specific to stimulus or task factors. Perceptual learning has been shown on a range of visual tasks but very little research has explored chromatic perceptual learning. Here, we use two low level perceptual threshold tasks and a supra-threshold target detection task to assess chromatic perceptual learning and category effects. Experiment 1 investigates whether chromatic thresholds reduce as a result of training and at what level of analysis learning effects occur. Experiment 2 explores the effect of category training on chromatic thresholds, whether training of this nature is category specific and whether it can induce categorical responding. Experiment 3 investigates the effect of category training on a higher level, lateralized target detection task, previously found to be sensitive to category effects. The findings indicate that performance on a perceptual threshold task improves following training but improvements do not transfer across retinal location or hue. Therefore, chromatic perceptual learning is category specific and can occur at relatively early stages of visual analysis. Additionally, category training does not induce category effects on a low level perceptual threshold task, as indicated by comparable discrimination thresholds at the newly learned hue boundary and adjacent test points. However, category training does induce emerging category effects on a supra-threshold target detection task. Whilst chromatic perceptual learning is possible, learnt category effects appear to be a product of left hemisphere processing, and may require the input of higher level linguistic coding processes in order to manifest. PMID:27252669

Retrieval cues that trigger reconsolidation of associative fear memory are not necessarily an exact replica of the original learning experience.

PubMed

Soeter, Marieke; Kindt, Merel

2015-01-01

Disrupting the process of memory reconsolidation may point to a novel therapeutic strategy for the permanent reduction of fear in patients suffering from anxiety disorders. However both in animal and human studies the retrieval cue typically involves a re-exposure to the original fear-conditioned stimulus (CS). A relevant question is whether abstract cues not directly associated with the threat event also trigger reconsolidation, given that anxiety disorders often result from vicarious or unobtrusive learning for which no explicit memory exists. Insofar as the fear memory involves a flexible representation of the original learning experience, we hypothesized that the process of memory reconsolidation may also be triggered by abstract cues. We addressed this hypothesis by using a differential human fear-conditioning procedure in two distinct fear-learning groups. We predicted that if fear learning involves discrimination on basis of perceptual cues within one semantic category (i.e., the perceptual-learning group, n = 15), the subsequent ambiguity of the abstract retrieval cue would not trigger memory reconsolidation. In contrast, if fear learning involves discriminating between two semantic categories (i.e., categorical-learning group, n = 15), an abstract retrieval cue would unequivocally reactivate the fear memory and might subsequently trigger memory reconsolidation. Here we show that memory reconsolidation may indeed be triggered by another cue than the one that was present during the original learning occasion, but this effect depends on the learning history. Evidence for fear memory reconsolidation was inferred from the fear-erasing effect of one pill of propranolol (40 mg) systemically administered upon exposure to the abstract retrieval cue. Our finding that reconsolidation of a specific fear association does not require exposure to the original retrieval cue supports the feasibility of reconsolidation-based interventions for emotional disorders.

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

PubMed

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.

From Concrete Examples to Abstract Relations: The Rostrolateral Prefrontal Cortex Integrates Novel Examples into Relational Categories.

PubMed

Davis, Tyler; Goldwater, Micah; Giron, Josue

2017-04-01

The ability to form relational categories for objects that share few features in common is a hallmark of human cognition. For example, anything that can play a preventative role, from a boulder to poverty, can be a "barrier." However, neurobiological research has focused solely on how people acquire categories defined by features. The present functional magnetic resonance imaging study examines how relational and feature-based category learning compare in well-matched learning tasks. Using a computational model-based approach, we observed a cluster in left rostrolateral prefrontal cortex (rlPFC) that tracked quantitative predictions for the representational distance between test and training examples during relational categorization. Contrastingly, medial and dorsal PFC exhibited graded activation that tracked decision evidence during both feature-based and relational categorization. The results suggest that rlPFC computes an alignment signal that is critical for integrating novel examples during relational categorization whereas other PFC regions support more general decision functions. © The Author 2016. Published by Oxford University Press. All rights reserved. For Permissions, please e-mail: journals.permissions@oup.com.

Heterogeneity in perceptual category learning by high functioning children with autism spectrum disorder

PubMed Central

Mercado, Eduardo; Church, Barbara A.; Coutinho, Mariana V. C.; Dovgopoly, Alexander; Lopata, Christopher J.; Toomey, Jennifer A.; Thomeer, Marcus L.

2015-01-01

Previous research suggests that high functioning (HF) children with autism spectrum disorder (ASD) sometimes have problems learning categories, but often appear to perform normally in categorization tasks. The deficits that individuals with ASD show when learning categories have been attributed to executive dysfunction, general deficits in implicit learning, atypical cognitive strategies, or abnormal perceptual biases and abilities. Several of these psychological explanations for category learning deficits have been associated with neural abnormalities such as cortical underconnectivity. The present study evaluated how well existing neurally based theories account for atypical perceptual category learning shown by HF children with ASD across multiple category learning tasks involving novel, abstract shapes. Consistent with earlier results, children’s performances revealed two distinct patterns of learning and generalization associated with ASD: one was indistinguishable from performance in typically developing children; the other revealed dramatic impairments. These two patterns were evident regardless of training regimen or stimulus set. Surprisingly, some children with ASD showed both patterns. Simulations of perceptual category learning could account for the two observed patterns in terms of differences in neural plasticity. However, no current psychological or neural theory adequately explains why a child with ASD might show such large fluctuations in category learning ability across training conditions or stimulus sets. PMID:26157368

Cross-Situational Learning with Bayesian Generative Models for Multimodal Category and Word Learning in Robots

PubMed Central

Taniguchi, Akira; Taniguchi, Tadahiro; Cangelosi, Angelo

2017-01-01

In this paper, we propose a Bayesian generative model that can form multiple categories based on each sensory-channel and can associate words with any of the four sensory-channels (action, position, object, and color). This paper focuses on cross-situational learning using the co-occurrence between words and information of sensory-channels in complex situations rather than conventional situations of cross-situational learning. We conducted a learning scenario using a simulator and a real humanoid iCub robot. In the scenario, a human tutor provided a sentence that describes an object of visual attention and an accompanying action to the robot. The scenario was set as follows: the number of words per sensory-channel was three or four, and the number of trials for learning was 20 and 40 for the simulator and 25 and 40 for the real robot. The experimental results showed that the proposed method was able to estimate the multiple categorizations and to learn the relationships between multiple sensory-channels and words accurately. In addition, we conducted an action generation task and an action description task based on word meanings learned in the cross-situational learning scenario. The experimental results showed that the robot could successfully use the word meanings learned by using the proposed method. PMID:29311888

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

NASA Astrophysics Data System (ADS)

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

2018-04-01

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

What you learn is more than what you see: what can sequencing effects tell us about inductive category learning?

PubMed Central

Carvalho, Paulo F.; Goldstone, Robert L.

2015-01-01

Inductive category learning takes place across time. As such, it is not surprising that the sequence in which information is studied has an impact in what is learned and how efficient learning is. In this paper we review research on different learning sequences and how this impacts learning. We analyze different aspects of interleaved (frequent alternation between categories during study) and blocked study (infrequent alternation between categories during study) that might explain how and when one sequence of study results in improved learning. While these different sequences of study differ in the amount of temporal spacing and temporal juxtaposition between items of different categories, these aspects do not seem to account for the majority of the results available in the literature. However, differences in the type of category being studied and the duration of the retention interval between study and test may play an important role. We conclude that there is no single aspect that is able to account for all the evidence available. Understanding learning as a process of sequential comparisons in time and how different sequences fundamentally alter the statistics of this experience offers a promising framework for understanding sequencing effects in category learning. We use this framework to present novel predictions and hypotheses for future research on sequencing effects in inductive category learning. PMID:25983699

Learning through Feature Prediction: An Initial Investigation into Teaching Categories to Children with Autism through Predicting Missing Features

ERIC Educational Resources Information Center

Sweller, Naomi

2015-01-01

Individuals with autism have difficulty generalising information from one situation to another, a process that requires the learning of categories and concepts. Category information may be learned through: (1) classifying items into categories, or (2) predicting missing features of category items. Predicting missing features has to this point been…

Modeling a flexible representation machinery of human concept learning.

PubMed

Matsuka, Toshihiko; Sakamoto, Yasuaki; Chouchourelou, Arieta

2008-01-01

It is widely acknowledged that categorically organized abstract knowledge plays a significant role in high-order human cognition. Yet, there are many unknown issues about the nature of how categories are internally represented in our mind. Traditionally, it has been considered that there is a single innate internal representation system for categorical knowledge, such as Exemplars, Prototypes, or Rules. However, results of recent empirical and computational studies collectively suggest that the human internal representation system is apparently capable of exhibiting behaviors consistent with various types of internal representation schemes. We, then, hypothesized that humans' representational system as a dynamic mechanism, capable of selecting a representation scheme that meets situational characteristics, including complexities of category structure. The present paper introduces a framework for a cognitive model that integrates robust and flexible internal representation machinery. Three simulation studies were conducted. The results showed that SUPERSET, our new model, successfully exhibited cognitive behaviors that are consistent with three main theories of the human internal representation system. Furthermore, a simulation study on social cognitive behaviors showed that the model was capable of acquiring knowledge with high commonality, even for a category structure with numerous valid conceptualizations.

The semantic representation of prejudice and stereotypes.

PubMed

Bhatia, Sudeep

2017-07-01

We use a theory of semantic representation to study prejudice and stereotyping. Particularly, we consider large datasets of newspaper articles published in the United States, and apply latent semantic analysis (LSA), a prominent model of human semantic memory, to these datasets to learn representations for common male and female, White, African American, and Latino names. LSA performs a singular value decomposition on word distribution statistics in order to recover word vector representations, and we find that our recovered representations display the types of biases observed in human participants using tasks such as the implicit association test. Importantly, these biases are strongest for vector representations with moderate dimensionality, and weaken or disappear for representations with very high or very low dimensionality. Moderate dimensional LSA models are also the best at learning race, ethnicity, and gender-based categories, suggesting that social category knowledge, acquired through dimensionality reduction on word distribution statistics, can facilitate prejudiced and stereotyped associations. Copyright © 2017 Elsevier B.V. All rights reserved.

When more is less: Feedback effects in perceptual category learning ☆

PubMed Central

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether their response was correct or incorrect, but are not informed of the correct category assignment. With full feedback subjects are informed of the correctness of their response and are also informed of the correct category assignment. An examination of the distinct neural circuits that subserve rule-based and information-integration category learning leads to the counterintuitive prediction that full feedback should facilitate rule-based learning but should also hinder information-integration learning. This prediction was supported in the experiment reported below. The implications of these results for theories of learning are discussed. PMID:18455155

Discontinuous categories affect information-integration but not rule-based category learning.

PubMed

Maddox, W Todd; Filoteo, J Vincent; Lauritzen, J Scott; Connally, Emily; Hejl, Kelli D

2005-07-01

Three experiments were conducted that provide a direct examination of within-category discontinuity manipulations on the implicit, procedural-based learning and the explicit, hypothesis-testing systems proposed in F. G. Ashby, L. A. Alfonso-Reese, A. U. Turken, and E. M. Waldron's (1998) competition between verbal and implicit systems model. Discontinuous categories adversely affected information-integration but not rule-based category learning. Increasing the magnitude of the discontinuity did not lead to a significant decline in performance. The distance to the bound provides a reasonable description of the generalization profile associated with the hypothesis-testing system, whereas the distance to the bound plus the distance to the trained response region provides a reasonable description of the generalization profile associated with the procedural-based learning system. These results suggest that within-category discontinuity differentially impacts information-integration but not rule-based category learning and provides information regarding the detailed processing characteristics of each category learning system. ((c) 2005 APA, all rights reserved).

Differential impact of relevant and irrelevant dimension primes on rule-based and information-integration category learning.

PubMed

Grimm, Lisa R; Maddox, W Todd

2013-11-01

Research has identified multiple category-learning systems with each being "tuned" for learning categories with different task demands and each governed by different neurobiological systems. Rule-based (RB) classification involves testing verbalizable rules for category membership while information-integration (II) classification requires the implicit learning of stimulus-response mappings. In the first study to directly test rule priming with RB and II category learning, we investigated the influence of the availability of information presented at the beginning of the task. Participants viewed lines that varied in length, orientation, and position on the screen, and were primed to focus on stimulus dimensions that were relevant or irrelevant to the correct classification rule. In Experiment 1, we used an RB category structure, and in Experiment 2, we used an II category structure. Accuracy and model-based analyses suggested that a focus on relevant dimensions improves RB task performance later in learning while a focus on an irrelevant dimension improves II task performance early in learning. © 2013.

When It Hurts (and Helps) to Try: The Role of Effort in Language Learning

PubMed Central

Finn, Amy S.; Lee, Taraz; Kraus, Allison; Hudson Kam, Carla L.

2014-01-01

Compared to children, adults are bad at learning language. This is counterintuitive; adults outperform children on most measures of cognition, especially those that involve effort (which continue to mature into early adulthood). The present study asks whether these mature effortful abilities interfere with language learning in adults and further, whether interference occurs equally for aspects of language that adults are good (word-segmentation) versus bad (grammar) at learning. Learners were exposed to an artificial language comprised of statistically defined words that belong to phonologically defined categories (grammar). Exposure occurred under passive or effortful conditions. Passive learners were told to listen while effortful learners were instructed to try to 1) learn the words, 2) learn the categories, or 3) learn the category-order. Effortful learners showed an advantage for learning words while passive learners showed an advantage for learning the categories. Effort can therefore hurt the learning of categories. PMID:25047901

When it hurts (and helps) to try: the role of effort in language learning.

PubMed

Finn, Amy S; Lee, Taraz; Kraus, Allison; Hudson Kam, Carla L

2014-01-01

Compared to children, adults are bad at learning language. This is counterintuitive; adults outperform children on most measures of cognition, especially those that involve effort (which continue to mature into early adulthood). The present study asks whether these mature effortful abilities interfere with language learning in adults and further, whether interference occurs equally for aspects of language that adults are good (word-segmentation) versus bad (grammar) at learning. Learners were exposed to an artificial language comprised of statistically defined words that belong to phonologically defined categories (grammar). Exposure occurred under passive or effortful conditions. Passive learners were told to listen while effortful learners were instructed to try to 1) learn the words, 2) learn the categories, or 3) learn the category-order. Effortful learners showed an advantage for learning words while passive learners showed an advantage for learning the categories. Effort can therefore hurt the learning of categories.

Use of Inverse Reinforcement Learning for Identity Prediction

NASA Technical Reports Server (NTRS)

Hayes, Roy; Bao, Jonathan; Beling, Peter; Horowitz, Barry

2011-01-01

We adopt Markov Decision Processes (MDP) to model sequential decision problems, which have the characteristic that the current decision made by a human decision maker has an uncertain impact on future opportunity. We hypothesize that the individuality of decision makers can be modeled as differences in the reward function under a common MDP model. A machine learning technique, Inverse Reinforcement Learning (IRL), was used to learn an individual's reward function based on limited observation of his or her decision choices. This work serves as an initial investigation for using IRL to analyze decision making, conducted through a human experiment in a cyber shopping environment. Specifically, the ability to determine the demographic identity of users is conducted through prediction analysis and supervised learning. The results show that IRL can be used to correctly identify participants, at a rate of 68% for gender and 66% for one of three college major categories.

Scaffolding in geometry based on self regulated learning

NASA Astrophysics Data System (ADS)

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

2017-12-01

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

Learning, retention, and generalization of haptic categories

NASA Astrophysics Data System (ADS)

Do, Phuong T.

This dissertation explored how haptic concepts are learned, retained, and generalized to the same or different modality. Participants learned to classify objects into three categories either visually or haptically via different training procedures, followed by an immediate or delayed transfer test. Experiment I involved visual versus haptic learning and transfer. Intermodal matching between vision and haptics was investigated in Experiment II. Experiments III and IV examined intersensory conflict in within- and between-category bimodal situations to determine the degree of perceptual dominance between sight and touch. Experiment V explored the intramodal relationship between similarity and categorization in a psychological space, as revealed by MDS analysis of similarity judgments. Major findings were: (1) visual examination resulted in relatively higher performance accuracy than haptic learning; (2) systematic training produced better category learning of haptic concepts across all modality conditions; (3) the category prototypes were rated newer than any transfer stimulus followed learning both immediately and after a week delay; and, (4) although they converged at the apex of two transformational trajectories, the category prototypes became more central to their respective categories and increasingly structured as a function of learning. Implications for theories of multimodal similarity and categorization behavior are discussed in terms of discrimination learning, sensory integration, and dominance relation.

Feature highlighting enhances learning of a complex natural-science category.

PubMed

Miyatsu, Toshiya; Gouravajhala, Reshma; Nosofsky, Robert M; McDaniel, Mark A

2018-04-26

Learning naturalistic categories, which tend to have fuzzy boundaries and vary on many dimensions, can often be harder than learning well defined categories. One method for facilitating the category learning of naturalistic stimuli may be to provide explicit feature descriptions that highlight the characteristic features of each category. Although this method is commonly used in textbooks and classrooms, theoretically it remains uncertain whether feature descriptions should advantage learning complex natural-science categories. In three experiments, participants were trained on 12 categories of rocks, either without or with a brief description highlighting key features of each category. After training, they were tested on their ability to categorize both old and new rocks from each of the categories. Providing feature descriptions as a caption under a rock image failed to improve category learning relative to providing only the rock image with its category label (Experiment 1). However, when these same feature descriptions were presented such that they were explicitly linked to the relevant parts of the rock image (feature highlighting), participants showed significantly higher performance on both immediate generalization to new rocks (Experiment 2) and generalization after a 2-day delay (Experiment 3). Theoretical and practical implications are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

The impact of category structure and training methodology on learning and generalizing within-category representations.

PubMed

Ell, Shawn W; Smith, David B; Peralta, Gabriela; Hélie, Sébastien

2017-08-01

When interacting with categories, representations focused on within-category relationships are often learned, but the conditions promoting within-category representations and their generalizability are unclear. We report the results of three experiments investigating the impact of category structure and training methodology on the learning and generalization of within-category representations (i.e., correlational structure). Participants were trained on either rule-based or information-integration structures using classification (Is the stimulus a member of Category A or Category B?), concept (e.g., Is the stimulus a member of Category A, Yes or No?), or inference (infer the missing component of the stimulus from a given category) and then tested on either an inference task (Experiments 1 and 2) or a classification task (Experiment 3). For the information-integration structure, within-category representations were consistently learned, could be generalized to novel stimuli, and could be generalized to support inference at test. For the rule-based structure, extended inference training resulted in generalization to novel stimuli (Experiment 2) and inference training resulted in generalization to classification (Experiment 3). These data help to clarify the conditions under which within-category representations can be learned. Moreover, these results make an important contribution in highlighting the impact of category structure and training methodology on the generalization of categorical knowledge.

Changes in Visual Object Recognition Precede the Shape Bias in Early Noun Learning

PubMed Central

Yee, Meagan; Jones, Susan S.; Smith, Linda B.

2012-01-01

Two of the most formidable skills that characterize human beings are language and our prowess in visual object recognition. They may also be developmentally intertwined. Two experiments, a large sample cross-sectional study and a smaller sample 6-month longitudinal study of 18- to 24-month-olds, tested a hypothesized developmental link between changes in visual object representation and noun learning. Previous findings in visual object recognition indicate that children’s ability to recognize common basic level categories from sparse structural shape representations of object shape emerges between the ages of 18 and 24 months, is related to noun vocabulary size, and is lacking in children with language delay. Other research shows in artificial noun learning tasks that during this same developmental period, young children systematically generalize object names by shape, that this shape bias predicts future noun learning, and is lacking in children with language delay. The two experiments examine the developmental relation between visual object recognition and the shape bias for the first time. The results show that developmental changes in visual object recognition systematically precede the emergence of the shape bias. The results suggest a developmental pathway in which early changes in visual object recognition that are themselves linked to category learning enable the discovery of higher-order regularities in category structure and thus the shape bias in novel noun learning tasks. The proposed developmental pathway has implications for understanding the role of specific experience in the development of both visual object recognition and the shape bias in early noun learning. PMID:23227015

On Learning Natural-Science Categories That Violate the Family-Resemblance Principle.

PubMed

Nosofsky, Robert M; Sanders, Craig A; Gerdom, Alex; Douglas, Bruce J; McDaniel, Mark A

2017-01-01

The general view in psychological science is that natural categories obey a coherent, family-resemblance principle. In this investigation, we documented an example of an important exception to this principle: Results of a multidimensional-scaling study of igneous, metamorphic, and sedimentary rocks (Experiment 1) suggested that the structure of these categories is disorganized and dispersed. This finding motivated us to explore what might be the optimal procedures for teaching dispersed categories, a goal that is likely critical to science education in general. Subjects in Experiment 2 learned to classify pictures of rocks into compact or dispersed high-level categories. One group learned the categories through focused high-level training, whereas a second group was required to simultaneously learn classifications at a subtype level. Although high-level training led to enhanced performance when the categories were compact, subtype training was better when the categories were dispersed. We provide an interpretation of the results in terms of an exemplar-memory model of category learning.

Human Resource Consulting Education: Professional Development for the Personnel Consulting Industry.

ERIC Educational Resources Information Center

Bone, John

1996-01-01

Interviews and surveys of 200 personnel consultants revealed an urgent need for basic and ongoing professional development education and for national competence standards and accreditation. Skill needs clustered in three categories: recruitment, selection, and sales/marketing. Professional education should recognize lifelong learning, take…

How does the brain rapidly learn and reorganize view-invariant and position-invariant object representations in the inferotemporal cortex?

PubMed

Cao, Yongqiang; Grossberg, Stephen; Markowitz, Jeffrey

2011-12-01

All primates depend for their survival on being able to rapidly learn about and recognize objects. Objects may be visually detected at multiple positions, sizes, and viewpoints. How does the brain rapidly learn and recognize objects while scanning a scene with eye movements, without causing a combinatorial explosion in the number of cells that are needed? How does the brain avoid the problem of erroneously classifying parts of different objects together at the same or different positions in a visual scene? In monkeys and humans, a key area for such invariant object category learning and recognition is the inferotemporal cortex (IT). A neural model is proposed to explain how spatial and object attention coordinate the ability of IT to learn invariant category representations of objects that are seen at multiple positions, sizes, and viewpoints. The model clarifies how interactions within a hierarchy of processing stages in the visual brain accomplish this. These stages include the retina, lateral geniculate nucleus, and cortical areas V1, V2, V4, and IT in the brain's What cortical stream, as they interact with spatial attention processes within the parietal cortex of the Where cortical stream. The model builds upon the ARTSCAN model, which proposed how view-invariant object representations are generated. The positional ARTSCAN (pARTSCAN) model proposes how the following additional processes in the What cortical processing stream also enable position-invariant object representations to be learned: IT cells with persistent activity, and a combination of normalizing object category competition and a view-to-object learning law which together ensure that unambiguous views have a larger effect on object recognition than ambiguous views. The model explains how such invariant learning can be fooled when monkeys, or other primates, are presented with an object that is swapped with another object during eye movements to foveate the original object. The swapping procedure is predicted to prevent the reset of spatial attention, which would otherwise keep the representations of multiple objects from being combined by learning. Li and DiCarlo (2008) have presented neurophysiological data from monkeys showing how unsupervised natural experience in a target swapping experiment can rapidly alter object representations in IT. The model quantitatively simulates the swapping data by showing how the swapping procedure fools the spatial attention mechanism. More generally, the model provides a unifying framework, and testable predictions in both monkeys and humans, for understanding object learning data using neurophysiological methods in monkeys, and spatial attention, episodic learning, and memory retrieval data using functional imaging methods in humans. Copyright © 2011 Elsevier Ltd. All rights reserved.

Similarity of Cortical Activity Patterns Predicts generalization Behavior

PubMed Central

Engineer, Crystal T.; Perez, Claudia A.; Carraway, Ryan S.; Chang, Kevin Q.; Roland, Jarod L.; Sloan, Andrew M.; Kilgard, Michael P.

2013-01-01

Humans and animals readily generalize previously learned knowledge to new situations. Determining similarity is critical for assigning category membership to a novel stimulus. We tested the hypothesis that category membership is initially encoded by the similarity of the activity pattern evoked by a novel stimulus to the patterns from known categories. We provide behavioral and neurophysiological evidence that activity patterns in primary auditory cortex contain sufficient information to explain behavioral categorization of novel speech sounds by rats. Our results suggest that category membership might be encoded by the similarity of the activity pattern evoked by a novel speech sound to the patterns evoked by known sounds. Categorization based on featureless pattern matching may represent a general neural mechanism for ensuring accurate generalization across sensory and cognitive systems. PMID:24147140

Event-Related fMRI of Category Learning: Differences in Classification and Feedback Networks

ERIC Educational Resources Information Center

Little, Deborah M.; Shin, Silvia S.; Sisco, Shannon M.; Thulborn, Keith R.

2006-01-01

Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification…

Category learning in the color-word contingency learning paradigm.

PubMed

Schmidt, James R; Augustinova, Maria; De Houwer, Jan

2018-04-01

In the typical color-word contingency learning paradigm, participants respond to the print color of words where each word is presented most often in one color. Learning is indicated by faster and more accurate responses when a word is presented in its usual color, relative to another color. To eliminate the possibility that this effect is driven exclusively by the familiarity of item-specific word-color pairings, we examine whether contingency learning effects can be observed also when colors are related to categories of words rather than to individual words. To this end, the reported experiments used three categories of words (animals, verbs, and professions) that were each predictive of one color. Importantly, each individual word was presented only once, thus eliminating individual color-word contingencies. Nevertheless, for the first time, a category-based contingency effect was observed, with faster and more accurate responses when a category item was presented in the color in which most of the other items of that category were presented. This finding helps to constrain episodic learning models and sets the stage for new research on category-based contingency learning.

Learning-dependent plasticity in human auditory cortex during appetitive operant conditioning.

PubMed

Puschmann, Sebastian; Brechmann, André; Thiel, Christiane M

2013-11-01

Animal experiments provide evidence that learning to associate an auditory stimulus with a reward causes representational changes in auditory cortex. However, most studies did not investigate the temporal formation of learning-dependent plasticity during the task but rather compared auditory cortex receptive fields before and after conditioning. We here present a functional magnetic resonance imaging study on learning-related plasticity in the human auditory cortex during operant appetitive conditioning. Participants had to learn to associate a specific category of frequency-modulated tones with a reward. Only participants who learned this association developed learning-dependent plasticity in left auditory cortex over the course of the experiment. No differential responses to reward predicting and nonreward predicting tones were found in auditory cortex in nonlearners. In addition, learners showed similar learning-induced differential responses to reward-predicting and nonreward-predicting tones in the ventral tegmental area and the nucleus accumbens, two core regions of the dopaminergic neurotransmitter system. This may indicate a dopaminergic influence on the formation of learning-dependent plasticity in auditory cortex, as it has been suggested by previous animal studies. Copyright © 2012 Wiley Periodicals, Inc.

Strategically Allocating Resources to Support Teaching and Learning

ERIC Educational Resources Information Center

Lynch, Matthew

2012-01-01

As the enduring economic recession forces state and local governments to cut education budgets, astute allocation of resources is becoming more important. The author analyses three basic categories of educational resources: money, human capital, and time before moving to a discussion of resources as a component of school reform. The author…

Caring and the Elementary Curriculum.

ERIC Educational Resources Information Center

Ediger, Marlow

In light of the amount of violence reported in public media and increasing rudeness of public behavior, it is imperative that elementary school students learn to care for other human beings. This paper makes recommendations for developing an elementary school curriculum of caring. The paper recommends three categories of objectives--knowledge,…

Exploring the Conceptual Universe

ERIC Educational Resources Information Center

Kemp, Charles

2012-01-01

Humans can learn to organize many kinds of domains into categories, including real-world domains such as kinsfolk and synthetic domains such as sets of geometric figures that vary along several dimensions. Psychologists have studied many individual domains in detail, but there have been few attempts to characterize or explore the full space of…

Hidden Dimensions in the So-Called Reality of a Mathematics Classroom.

ERIC Educational Resources Information Center

Bauersfeld, Heinrich

1980-01-01

Teaching and learning mathematics in classrooms is interpreted as human interaction in an institutionalized setting. Using theories and categories from different disciplines, a classroom episode is reanalyzed. Four hidden dimensions in the classroom process and thus deficient areas of research are identified. Consequences for teacher training are…

Rule-Based and Information-Integration Category Learning in Normal Aging

ERIC Educational Resources Information Center

Maddox, W. Todd; Pacheco, Jennifer; Reeves, Maia; Zhu, Bo; Schnyer, David M.

2010-01-01

The basal ganglia and prefrontal cortex play critical roles in category learning. Both regions evidence age-related structural and functional declines. The current study examined rule-based and information-integration category learning in a group of older and younger adults. Rule-based learning is thought to involve explicit, frontally mediated…

Metacognitive monitoring during category learning: how success affects future behaviour.

PubMed

Doyle, Mario E; Hourihan, Kathleen L

2016-10-01

The purpose of this study was to see how people perceive their own learning during a category learning task, and whether their perceptions matched their performance. In two experiments, participants were asked to learn natural categories, of both high and low variability, and make category learning judgements (CLJs). Variability was manipulated by varying the number of exemplars and the number of times each exemplar was presented within each category. Experiment 1 showed that participants were generally overconfident in their knowledge of low variability families, suggesting that they considered repetition to be more useful for learning than it actually was. Also, a correct trial, for a particular category, was more likely to occur if the previous trial was correct. CLJs had the largest increase when a trial was correct following an incorrect trial and the largest decrease when an incorrect trial followed a correct trial. Experiment 2 replicated these results, but also demonstrated that global CLJ ratings showed the same bias towards repetition. These results indicate that we generally identify success as being the biggest determinant of learning, but do not always recognise cues, such as variability, that enhance learning.

Working memory supports inference learning just like classification learning.

PubMed

Craig, Stewart; Lewandowsky, Stephan

2013-08-01

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

Observation versus classification in supervised category learning.

PubMed

Levering, Kimery R; Kurtz, Kenneth J

2015-02-01

The traditional supervised classification paradigm encourages learners to acquire only the knowledge needed to predict category membership (a discriminative approach). An alternative that aligns with important aspects of real-world concept formation is learning with a broader focus to acquire knowledge of the internal structure of each category (a generative approach). Our work addresses the impact of a particular component of the traditional classification task: the guess-and-correct cycle. We compare classification learning to a supervised observational learning task in which learners are shown labeled examples but make no classification response. The goals of this work sit at two levels: (1) testing for differences in the nature of the category representations that arise from two basic learning modes; and (2) evaluating the generative/discriminative continuum as a theoretical tool for understand learning modes and their outcomes. Specifically, we view the guess-and-correct cycle as consistent with a more discriminative approach and therefore expected it to lead to narrower category knowledge. Across two experiments, the observational mode led to greater sensitivity to distributional properties of features and correlations between features. We conclude that a relatively subtle procedural difference in supervised category learning substantially impacts what learners come to know about the categories. The results demonstrate the value of the generative/discriminative continuum as a tool for advancing the psychology of category learning and also provide a valuable constraint for formal models and associated theories.

Phonetic diversity, statistical learning, and acquisition of phonology.

PubMed

Pierrehumbert, Janet B

2003-01-01

In learning to perceive and produce speech, children master complex language-specific patterns. Daunting language-specific variation is found both in the segmental domain and in the domain of prosody and intonation. This article reviews the challenges posed by results in phonetic typology and sociolinguistics for the theory of language acquisition. It argues that categories are initiated bottom-up from statistical modes in use of the phonetic space, and sketches how exemplar theory can be used to model the updating of categories once they are initiated. It also argues that bottom-up initiation of categories is successful thanks to the perception-production loop operating in the speech community. The behavior of this loop means that the superficial statistical properties of speech available to the infant indirectly reflect the contrastiveness and discriminability of categories in the adult grammar. The article also argues that the developing system is refined using internal feedback from type statistics over the lexicon, once the lexicon is well-developed. The application of type statistics to a system initiated with surface statistics does not cause a fundamental reorganization of the system. Instead, it exploits confluences across levels of representation which characterize human language and make bootstrapping possible.

On the Safety of Machine Learning: Cyber-Physical Systems, Decision Sciences, and Data Products.

PubMed

Varshney, Kush R; Alemzadeh, Homa

2017-09-01

Machine learning algorithms increasingly influence our decisions and interact with us in all parts of our daily lives. Therefore, just as we consider the safety of power plants, highways, and a variety of other engineered socio-technical systems, we must also take into account the safety of systems involving machine learning. Heretofore, the definition of safety has not been formalized in a machine learning context. In this article, we do so by defining machine learning safety in terms of risk, epistemic uncertainty, and the harm incurred by unwanted outcomes. We then use this definition to examine safety in all sorts of applications in cyber-physical systems, decision sciences, and data products. We find that the foundational principle of modern statistical machine learning, empirical risk minimization, is not always a sufficient objective. We discuss how four different categories of strategies for achieving safety in engineering, including inherently safe design, safety reserves, safe fail, and procedural safeguards can be mapped to a machine learning context. We then discuss example techniques that can be adopted in each category, such as considering interpretability and causality of predictive models, objective functions beyond expected prediction accuracy, human involvement for labeling difficult or rare examples, and user experience design of software and open data.

Object-graphs for context-aware visual category discovery.

PubMed

Lee, Yong Jae; Grauman, Kristen

2012-02-01

How can knowing about some categories help us to discover new ones in unlabeled images? Unsupervised visual category discovery is useful to mine for recurring objects without human supervision, but existing methods assume no prior information and thus tend to perform poorly for cluttered scenes with multiple objects. We propose to leverage knowledge about previously learned categories to enable more accurate discovery, and address challenges in estimating their familiarity in unsegmented, unlabeled images. We introduce two variants of a novel object-graph descriptor to encode the 2D and 3D spatial layout of object-level co-occurrence patterns relative to an unfamiliar region and show that by using them to model the interaction between an image’s known and unknown objects, we can better detect new visual categories. Rather than mine for all categories from scratch, our method identifies new objects while drawing on useful cues from familiar ones. We evaluate our approach on several benchmark data sets and demonstrate clear improvements in discovery over conventional purely appearance-based baselines.

Incidental learning of sound categories is impaired in developmental dyslexia.

PubMed

Gabay, Yafit; Holt, Lori L

2015-12-01

Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. Copyright © 2015 Elsevier Ltd. All rights reserved.

Incidental Learning of Sound Categories is Impaired in Developmental Dyslexia

PubMed Central

Gabay, Yafit; Holt, Lori L.

2015-01-01

Developmental dyslexia is commonly thought to arise from specific phonological impairments. However, recent evidence is consistent with the possibility that phonological impairments arise as symptoms of an underlying dysfunction of procedural learning. The nature of the link between impaired procedural learning and phonological dysfunction is unresolved. Motivated by the observation that speech processing involves the acquisition of procedural category knowledge, the present study investigates the possibility that procedural learning impairment may affect phonological processing by interfering with the typical course of phonetic category learning. The present study tests this hypothesis while controlling for linguistic experience and possible speech-specific deficits by comparing auditory category learning across artificial, nonlinguistic sounds among dyslexic adults and matched controls in a specialized first-person shooter videogame that has been shown to engage procedural learning. Nonspeech auditory category learning was assessed online via within-game measures and also with a post-training task involving overt categorization of familiar and novel sound exemplars. Each measure reveals that dyslexic participants do not acquire procedural category knowledge as effectively as age- and cognitive-ability matched controls. This difference cannot be explained by differences in perceptual acuity for the sounds. Moreover, poor nonspeech category learning is associated with slower phonological processing. Whereas phonological processing impairments have been emphasized as the cause of dyslexia, the current results suggest that impaired auditory category learning, general in nature and not specific to speech signals, could contribute to phonological deficits in dyslexia with subsequent negative effects on language acquisition and reading. Implications for the neuro-cognitive mechanisms of developmental dyslexia are discussed. PMID:26409017

Discovery learning with SAVI approach in geometry learning

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

Is the devil in the detail? Evidence for S-S learning after unconditional stimulus revaluation in human evaluative conditioning under a broader set of experimental conditions.

PubMed

Jensen-Fielding, Hannah; Luck, Camilla C; Lipp, Ottmar V

2017-11-28

Whether valence change during evaluative conditioning is mediated by a link between the conditional stimulus (CS) and the unconditional stimulus (US; S-S learning) or between the CS and the unconditional response (S-R learning) is a matter of continued debate. Changing the valence of the US after conditioning, known as US revaluation, can be used to dissociate these accounts. Changes in CS valence after US revaluation provide evidence for S-S learning but if CS valence does not change, evidence for S-R learning is found. Support for S-S learning has been provided by most past revaluation studies, but typically the CS and US have been from the same stimulus category, the task instructions have suggested that judgements of the CS should be based on the US, and USs have been mildly valenced stimuli. These factors may bias the results in favour of S-S learning. We examined whether S-R learning would be evident when CSs and USs were taken from different categories, the task instructions were removed, and more salient USs were used. US revaluation was found to influence explicit US evaluations and explicit and implicit CS evaluations, supporting an S-S learning account and suggesting that past results are stable across procedural changes.

Mechanisms of object recognition: what we have learned from pigeons

PubMed Central

Soto, Fabian A.; Wasserman, Edward A.

2014-01-01

Behavioral studies of object recognition in pigeons have been conducted for 50 years, yielding a large body of data. Recent work has been directed toward synthesizing this evidence and understanding the visual, associative, and cognitive mechanisms that are involved. The outcome is that pigeons are likely to be the non-primate species for which the computational mechanisms of object recognition are best understood. Here, we review this research and suggest that a core set of mechanisms for object recognition might be present in all vertebrates, including pigeons and people, making pigeons an excellent candidate model to study the neural mechanisms of object recognition. Behavioral and computational evidence suggests that error-driven learning participates in object category learning by pigeons and people, and recent neuroscientific research suggests that the basal ganglia, which are homologous in these species, may implement error-driven learning of stimulus-response associations. Furthermore, learning of abstract category representations can be observed in pigeons and other vertebrates. Finally, there is evidence that feedforward visual processing, a central mechanism in models of object recognition in the primate ventral stream, plays a role in object recognition by pigeons. We also highlight differences between pigeons and people in object recognition abilities, and propose candidate adaptive specializations which may explain them, such as holistic face processing and rule-based category learning in primates. From a modern comparative perspective, such specializations are to be expected regardless of the model species under study. The fact that we have a good idea of which aspects of object recognition differ in people and pigeons should be seen as an advantage over other animal models. From this perspective, we suggest that there is much to learn about human object recognition from studying the “simple” brains of pigeons. PMID:25352784

Developmental Changes between Childhood and Adulthood in Passive Observational and Interactive Feedback-Based Categorization Rule Learning

ERIC Educational Resources Information Center

Hammer, Rubi; Kloet, Jim; Booth, James R.

2016-01-01

As children start attending school they are more likely to face situations where they have to autonomously learn about novel object categories (e.g. by reading a picture book with descriptions of novel animals). Such autonomous observational category learning (OCL) gradually complements interactive feedback-based category learning (FBCL), where a…

Elevated depressive symptoms enhance reflexive but not reflective auditory category learning.

PubMed

Maddox, W Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G

2014-09-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. Copyright © 2014 Elsevier Ltd. All rights reserved.

Elevated Depressive Symptoms Enhance Reflexive but not Reflective Auditory Category Learning

PubMed Central

Maddox, W. Todd; Chandrasekaran, Bharath; Smayda, Kirsten; Yi, Han-Gyol; Koslov, Seth; Beevers, Christopher G.

2014-01-01

In vision an extensive literature supports the existence of competitive dual-processing systems of category learning that are grounded in neuroscience and are partially-dissociable. The reflective system is prefrontally-mediated and uses working memory and executive attention to develop and test rules for classifying in an explicit fashion. The reflexive system is striatally-mediated and operates by implicitly associating perception with actions that lead to reinforcement. Although categorization is fundamental to auditory processing, little is known about the learning systems that mediate auditory categorization and even less is known about the effects of individual difference in the relative efficiency of the two learning systems. Previous studies have shown that individuals with elevated depressive symptoms show deficits in reflective processing. We exploit this finding to test critical predictions of the dual-learning systems model in audition. Specifically, we examine the extent to which the two systems are dissociable and competitive. We predicted that elevated depressive symptoms would lead to reflective-optimal learning deficits but reflexive-optimal learning advantages. Because natural speech category learning is reflexive in nature, we made the prediction that elevated depressive symptoms would lead to superior speech learning. In support of our predictions, individuals with elevated depressive symptoms showed a deficit in reflective-optimal auditory category learning, but an advantage in reflexive-optimal auditory category learning. In addition, individuals with elevated depressive symptoms showed an advantage in learning a non-native speech category structure. Computational modeling suggested that the elevated depressive symptom advantage was due to faster, more accurate, and more frequent use of reflexive category learning strategies in individuals with elevated depressive symptoms. The implications of this work for dual-process approach to auditory learning and depression are discussed. PMID:25041936

Timing of quizzes during learning: Effects on motivation and retention.

PubMed

Healy, Alice F; Jones, Matt; Lalchandani, Lakshmi A; Tack, Lindsay Anderson

2017-06-01

This article investigates how the timing of quizzes given during learning impacts retention of studied material. We investigated the hypothesis that interspersing quizzes among study blocks increases student engagement, thus improving learning. Participants learned 8 artificial facts about each of 8 plant categories, with the categories blocked during learning. Quizzes about 4 of the 8 facts from each category occurred either immediately after studying the facts for that category (standard) or after studying the facts from all 8 categories (postponed). In Experiment 1, participants were given tests shortly after learning and several days later, including both the initially quizzed and unquizzed facts. Test performance was better in the standard than in the postponed condition, especially for categories learned later in the sequence. This result held even for the facts not quizzed during learning, suggesting that the advantage cannot be due to any direct testing effects. Instead the results support the hypothesis that interrupting learning with quiz questions is beneficial because it can enhance learner engagement. Experiment 2 provided further support for this hypothesis, based on participants' retrospective ratings of their task engagement during the learning phase. These findings have practical implications for when to introduce quizzes in the classroom. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

Linguistic labels, dynamic visual features, and attention in infant category learning.

PubMed

Deng, Wei Sophia; Sloutsky, Vladimir M

2015-06-01

How do words affect categorization? According to some accounts, even early in development words are category markers and are different from other features. According to other accounts, early in development words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12-month-old infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye-tracking results indicated that infants exhibited better category learning in the motion-defined condition than in the label-defined condition, and their attention was more distributed among different features when there was a dynamic visual feature compared with the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. Copyright © 2015 Elsevier Inc. All rights reserved.

Linguistic Labels, Dynamic Visual Features, and Attention in Infant Category Learning

PubMed Central

Deng, Wei (Sophia); Sloutsky, Vladimir M.

2015-01-01

How do words affect categorization? According to some accounts, even early in development, words are category markers and are different from other features. According to other accounts, early in development, words are part of the input and are akin to other features. The current study addressed this issue by examining the role of words and dynamic visual features in category learning in 8- to 12- month infants. Infants were familiarized with exemplars from one category in a label-defined or motion-defined condition and then tested with prototypes from the studied category and from a novel contrast category. Eye tracking results indicated that infants exhibited better category learning in the motion-defined than in the label-defined condition and their attention was more distributed among different features when there was a dynamic visual feature compared to the label-defined condition. These results provide little evidence for the idea that linguistic labels are category markers that facilitate category learning. PMID:25819100

Human Amygdala Tracks a Feature-Based Valence Signal Embedded within the Facial Expression of Surprise.

PubMed

Kim, M Justin; Mattek, Alison M; Bennett, Randi H; Solomon, Kimberly M; Shin, Jin; Whalen, Paul J

2017-09-27

Human amygdala function has been traditionally associated with processing the affective valence (negative vs positive) of an emotionally charged event, especially those that signal fear or threat. However, this account of human amygdala function can be explained by alternative views, which posit that the amygdala might be tuned to either (1) general emotional arousal (activation vs deactivation) or (2) specific emotion categories (fear vs happy). Delineating the pure effects of valence independent of arousal or emotion category is a challenging task, given that these variables naturally covary under many circumstances. To circumvent this issue and test the sensitivity of the human amygdala to valence values specifically, we measured the dimension of valence within the single facial expression category of surprise. Given the inherent valence ambiguity of this category, we show that surprised expression exemplars are attributed valence and arousal values that are uniquely and naturally uncorrelated. We then present fMRI data from both sexes, showing that the amygdala tracks these consensus valence values. Finally, we provide evidence that these valence values are linked to specific visual features of the mouth region, isolating the signal by which the amygdala detects this valence information. SIGNIFICANCE STATEMENT There is an open question as to whether human amygdala function tracks the valence value of cues in the environment, as opposed to either a more general emotional arousal value or a more specific emotion category distinction. Here, we demonstrate the utility of surprised facial expressions because exemplars within this emotion category take on valence values spanning the dimension of bipolar valence (positive to negative) at a consistent level of emotional arousal. Functional neuroimaging data showed that amygdala responses tracked the valence of surprised facial expressions, unconfounded by arousal. Furthermore, a machine learning classifier identified particular visual features of the mouth region that predicted this valence effect, isolating the specific visual signal that might be driving this neural valence response. Copyright © 2017 the authors 0270-6474/17/379510-09$15.00/0.

Can Semi-Supervised Learning Explain Incorrect Beliefs about Categories?

ERIC Educational Resources Information Center

Kalish, Charles W.; Rogers, Timothy T.; Lang, Jonathan; Zhu, Xiaojin

2011-01-01

Three experiments with 88 college-aged participants explored how unlabeled experiences--learning episodes in which people encounter objects without information about their category membership--influence beliefs about category structure. Participants performed a simple one-dimensional categorization task in a brief supervised learning phase, then…

Explanation and Prior Knowledge Interact to Guide Learning

ERIC Educational Resources Information Center

Williams, Joseph J.; Lombrozo, Tania

2013-01-01

How do explaining and prior knowledge contribute to learning? Four experiments explored the relationship between explanation and prior knowledge in category learning. The experiments independently manipulated whether participants were prompted to explain the category membership of study observations and whether category labels were informative in…

Conventional wisdom: negotiating conventions of reference enhances category learning.

PubMed

Voiklis, John; Corter, James E

2012-01-01

Collaborators generally coordinate their activities through communication, during which they readily negotiate a shared lexicon for activity-related objects. This social-pragmatic activity both recruits and affects cognitive and social-cognitive processes ranging from selective attention to perspective taking. We ask whether negotiating reference also facilitates category learning or might private verbalization yield comparable facilitation? Participants in three referential conditions learned to classify imaginary creatures according to combinations of functional features-nutritive and destructive-that implicitly defined four categories. Remote partners communicated in the Dialogue condition. In the Monologue condition, participants recorded audio descriptions for their own later use. Controls worked silently. Dialogue yielded better category learning, with wider distribution of attention. Monologue offered no benefits over working silently. We conclude that negotiating reference compels collaborators to find communicable structure in their shared activity; this social-pragmatic constraint accelerates category learning and likely provides much of the benefit recently ascribed to learning labeled categories. Copyright © 2012 Cognitive Science Society, Inc.

More than one kind of inference: re-examining what's learned in feature inference and classification.

PubMed

Sweller, Naomi; Hayes, Brett K

2010-08-01

Three studies examined how task demands that impact on attention to typical or atypical category features shape the category representations formed through classification learning and inference learning. During training categories were learned via exemplar classification or by inferring missing exemplar features. In the latter condition inferences were made about missing typical features alone (typical feature inference) or about both missing typical and atypical features (mixed feature inference). Classification and mixed feature inference led to the incorporation of typical and atypical features into category representations, with both kinds of features influencing inferences about familiar (Experiments 1 and 2) and novel (Experiment 3) test items. Those in the typical inference condition focused primarily on typical features. Together with formal modelling, these results challenge previous accounts that have characterized inference learning as producing a focus on typical category features. The results show that two different kinds of inference learning are possible and that these are subserved by different kinds of category representations.

Learning of Alignment Rules between Concept Hierarchies

NASA Astrophysics Data System (ADS)

Ichise, Ryutaro; Takeda, Hideaki; Honiden, Shinichi

With the rapid advances of information technology, we are acquiring much information than ever before. As a result, we need tools for organizing this data. Concept hierarchies such as ontologies and information categorizations are powerful and convenient methods for accomplishing this goal, which have gained wide spread acceptance. Although each concept hierarchy is useful, it is difficult to employ multiple concept hierarchies at the same time because it is hard to align their conceptual structures. This paper proposes a rule learning method that inputs information from a source concept hierarchy and finds suitable location for them in a target hierarchy. The key idea is to find the most similar categories in each hierarchy, where similarity is measured by the κ(kappa) statistic that counts instances belonging to both categories. In order to evaluate our method, we conducted experiments using two internet directories: Yahoo! and LYCOS. We map information instances from the source directory into the target directory, and show that our learned rules agree with a human-generated assignment 76% of the time.

Implicit Schemata and Categories in Memory-Based Language Processing

ERIC Educational Resources Information Center

van den Bosch, Antal; Daelemans, Walter

2013-01-01

Memory-based language processing (MBLP) is an approach to language processing based on exemplar storage during learning and analogical reasoning during processing. From a cognitive perspective, the approach is attractive as a model for human language processing because it does not make any assumptions about the way abstractions are shaped, nor any…

A Comparison of the neural correlates that underlie rule-based and information-integration category learning.

PubMed

Carpenter, Kathryn L; Wills, Andy J; Benattayallah, Abdelmalek; Milton, Fraser

2016-10-01

The influential competition between verbal and implicit systems (COVIS) model proposes that category learning is driven by two competing neural systems-an explicit, verbal, system, and a procedural-based, implicit, system. In the current fMRI study, participants learned either a conjunctive, rule-based (RB), category structure that is believed to engage the explicit system, or an information-integration category structure that is thought to preferentially recruit the implicit system. The RB and information-integration category structures were matched for participant error rate, the number of relevant stimulus dimensions, and category separation. Under these conditions, considerable overlap in brain activation, including the prefrontal cortex, basal ganglia, and the hippocampus, was found between the RB and information-integration category structures. Contrary to the predictions of COVIS, the medial temporal lobes and in particular the hippocampus, key regions for explicit memory, were found to be more active in the information-integration condition than in the RB condition. No regions were more activated in RB than information-integration category learning. The implications of these results for theories of category learning are discussed. Hum Brain Mapp 37:3557-3574, 2016. © 2016 Wiley Periodicals, Inc. © 2016 Wiley Periodicals, Inc.

Delayed Feedback Disrupts the Procedural-Learning System but Not the Hypothesis-Testing System in Perceptual Category Learning

ERIC Educational Resources Information Center

Maddox, W. Todd; Ing, A. David

2005-01-01

W. T. Maddox, F. G. Ashby, and C. J. Bohil (2003) found that delayed feedback adversely affects information-integration but not rule-based category learning in support of a multiple-systems approach to category learning. However, differences in the number of stimulus dimensions relevant to solving the task and perceptual similarity failed to rule…

Perceptions of nursing undergraduate students concerning the human dimension in the learning process.

PubMed

de Oliveira Camillo, Simone; Lúcia da Silva, Ana; Jefferson do Nascimento, Alan

2007-01-01

This study aimed to identify and interpret the perceptions presented by undergraduate students of a Nursing course after internship in Mental Health. Twelve nursing undergraduate students at the Nursing School of ABC Foundation - Santo André, São Paulo, Brazil were interviewed. These interviews using a semi-structure script were performed and recorded in August 2004. Through Content Analysis, thematic modality, four categories were identified, 1. mental health: providing understanding of the other; 2. respect for the human being: the importance of listening, 3. mental health: contributing for a contextualized view of the patient and 4. nursing graduation: undesirable "signs and symptoms" of the profession. The analysis and the discussion of these categories suggest the possibility of teaching based on the human condition. Thus, we support the idea of new research been carried out, considering that the Mental Health discipline must be valued in the Political and Pedagogical projects of the Nursing Undergraduate Courses.

Problem based learning with scaffolding technique on geometry

NASA Astrophysics Data System (ADS)

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

2018-05-01

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

The origins of options.

PubMed

Smaldino, Paul E; Richerson, Peter J

2012-01-01

Most research on decision making has focused on how human or animal decision makers choose between two or more options, posed in advance by the researchers. The mechanisms by which options are generated for most decisions, however, are not well understood. Models of sequential search have examined the trade-off between continued exploration and choosing one's current best option, but still cannot explain the processes by which new options are generated. We argue that understanding the origins of options is a crucial but untapped area for decision making research. We explore a number of factors which influence the generation of options, which fall broadly into two categories: psycho-biological and socio-cultural. The former category includes factors such as perceptual biases and associative memory networks. The latter category relies on the incredible human capacity for culture and social learning, which doubtless shape not only our choices but the options available for choice. Our intention is to start a discussion that brings us closer toward understanding the origins of options.

The Origins of Options

PubMed Central

Smaldino, Paul E.; Richerson, Peter J.

2012-01-01

Most research on decision making has focused on how human or animal decision makers choose between two or more options, posed in advance by the researchers. The mechanisms by which options are generated for most decisions, however, are not well understood. Models of sequential search have examined the trade-off between continued exploration and choosing one’s current best option, but still cannot explain the processes by which new options are generated. We argue that understanding the origins of options is a crucial but untapped area for decision making research. We explore a number of factors which influence the generation of options, which fall broadly into two categories: psycho-biological and socio-cultural. The former category includes factors such as perceptual biases and associative memory networks. The latter category relies on the incredible human capacity for culture and social learning, which doubtless shape not only our choices but the options available for choice. Our intention is to start a discussion that brings us closer toward understanding the origins of options. PMID:22514515

An Examination of Strategy Implementation during Abstract Nonlinguistic Category Learning in Aphasia

ERIC Educational Resources Information Center

Vallila-Rohter, Sofia; Kiran, Swathi

2015-01-01

Purpose: Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method: Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases…

Semantic Categories and Context in L2 Vocabulary Learning

ERIC Educational Resources Information Center

Bolger, Patrick; Zapata, Gabriela

2011-01-01

This article extends recent findings that presenting semantically related vocabulary simultaneously inhibits learning. It does so by adding story contexts. Participants learned 32 new labels for known concepts from four different semantic categories in stories that were either semantically related (one category per story) or semantically unrelated…

Rule-Based Category Learning in Down Syndrome

ERIC Educational Resources Information Center

Phillips, B. Allyson; Conners, Frances A.; Merrill, Edward; Klinger, Mark R.

2014-01-01

Rule-based category learning was examined in youths with Down syndrome (DS), youths with intellectual disability (ID), and typically developing (TD) youths. Two tasks measured category learning: the Modified Card Sort task (MCST) and the Concept Formation test of the Woodcock-Johnson-III (Woodcock, McGrew, & Mather, 2001). In regression-based…

Study preferences for exemplar variability in self-regulated category learning.

PubMed

Wahlheim, Christopher N; DeSoto, K Andrew

2017-02-01

Increasing exemplar variability during category learning can enhance classification of novel exemplars from studied categories. Four experiments examined whether participants preferred variability when making study choices with the goal of later classifying novel exemplars. In Experiments 1-3, participants were familiarised with exemplars of birds from multiple categories prior to making category-level assessments of learning and subsequent choices about whether to receive more variability or repetitions of exemplars during study. After study, participants classified novel exemplars from studied categories. The majority of participants showed a consistent preference for variability in their study, but choices were not related to category-level assessments of learning. Experiment 4 provided evidence that study preferences were based primarily on theoretical beliefs in that most participants indicated a preference for variability on questionnaires that did not include prior experience with exemplars. Potential directions for theoretical development and applications to education are discussed.

Learning Category-Specific Dictionary and Shared Dictionary for Fine-Grained Image Categorization.

PubMed

Gao, Shenghua; Tsang, Ivor Wai-Hung; Ma, Yi

2014-02-01

This paper targets fine-grained image categorization by learning a category-specific dictionary for each category and a shared dictionary for all the categories. Such category-specific dictionaries encode subtle visual differences among different categories, while the shared dictionary encodes common visual patterns among all the categories. To this end, we impose incoherence constraints among the different dictionaries in the objective of feature coding. In addition, to make the learnt dictionary stable, we also impose the constraint that each dictionary should be self-incoherent. Our proposed dictionary learning formulation not only applies to fine-grained classification, but also improves conventional basic-level object categorization and other tasks such as event recognition. Experimental results on five data sets show that our method can outperform the state-of-the-art fine-grained image categorization frameworks as well as sparse coding based dictionary learning frameworks. All these results demonstrate the effectiveness of our method.

Statistical learning using real-world scenes: extracting categorical regularities without conscious intent.

PubMed

Brady, Timothy F; Oliva, Aude

2008-07-01

Recent work has shown that observers can parse streams of syllables, tones, or visual shapes and learn statistical regularities in them without conscious intent (e.g., learn that A is always followed by B). Here, we demonstrate that these statistical-learning mechanisms can operate at an abstract, conceptual level. In Experiments 1 and 2, observers incidentally learned which semantic categories of natural scenes covaried (e.g., kitchen scenes were always followed by forest scenes). In Experiments 3 and 4, category learning with images of scenes transferred to words that represented the categories. In each experiment, the category of the scenes was irrelevant to the task. Together, these results suggest that statistical-learning mechanisms can operate at a categorical level, enabling generalization of learned regularities using existing conceptual knowledge. Such mechanisms may guide learning in domains as disparate as the acquisition of causal knowledge and the development of cognitive maps from environmental exploration.

There Are No New Lessons Learned, Just Old Lessons Relearned: A Case Study of Operation Iraqi Freedom Through the Eyes of Maslow

DTIC Science & Technology

2010-04-05

Abraham Maslow , a renowned American psychologist, prioritized human needs into four categories and his theory suggests that humans are motivated by...addressed through examination of other COIN and reconstruction operations. Endnotes 1 Abraham H. Maslow , Motivation and Personality, 3rd ed. (New...a basic understanding of Islam and provided a great contextual background for research. Maslow , Abraham H. Motivation and Personality, 3rd ed. New

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

ERIC Educational Resources Information Center

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

2008-01-01

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

When does fading enhance perceptual category learning?

PubMed

Pashler, Harold; Mozer, Michael C

2013-07-01

Training that uses exaggerated versions of a stimulus discrimination (fading) has sometimes been found to enhance category learning, mostly in studies involving animals and impaired populations. However, little is known about whether and when fading facilitates learning for typical individuals. This issue was explored in 7 experiments. In Experiments 1 and 2, observers discriminated stimuli based on a single sensory continuum (time duration and line length, respectively). Adaptive fading dramatically improved performance in training (unsurprisingly) but did not enhance learning as assessed in a final test. The same was true for nonadaptive linear fading (Experiment 3). However, when variation in length (predicting category membership) was embedded among other (category-irrelevant) variation, fading dramatically enhanced not only performance in training but also learning as assessed in a final test (Experiments 4 and 5). Fading also helped learners to acquire a color saturation discrimination amid category-irrelevant variation in hue and brightness, although this learning proved transitory after feedback was withdrawn (Experiment 7). Theoretical implications are discussed, and we argue that fading should have practical utility in naturalistic category learning tasks, which involve extremely high dimensional stimuli and many irrelevant dimensions. PsycINFO Database Record (c) 2013 APA, all rights reserved.

An Examination of Strategy Implementation During Abstract Nonlinguistic Category Learning in Aphasia.

PubMed

Vallila-Rohter, Sofia; Kiran, Swathi

2015-08-01

Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive-linguistic assessments. Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities.

Learning Vowel Categories from Maternal Speech in Gurindji Kriol

ERIC Educational Resources Information Center

Jones, Caroline; Meakins, Felicity; Muawiyath, Shujau

2012-01-01

Distributional learning is a proposal for how infants might learn early speech sound categories from acoustic input before they know many words. When categories in the input differ greatly in relative frequency and overlap in acoustic space, research in bilingual development suggests that this affects the course of development. In the present…

Characterizing Rule-Based Category Learning Deficits in Patients with Parkinson's Disease

ERIC Educational Resources Information Center

Filoteo, J. Vincent; Maddox, W. Todd; Ing, A. David; Song, David D.

2007-01-01

Parkinson's disease (PD) patients and normal controls were tested in three category learning experiments to determine if previously observed rule-based category learning impairments in PD patients were due to deficits in selective attention or working memory. In Experiment 1, optimal categorization required participants to base their decision on a…

[Emergent topics of educators' perspectives on their own education for retired health care professionals].

PubMed

Lourdes, C; Reus, Velázquez

2002-09-01

The purpose of the study was to explore the nature of seven retired educators' perspectives on their own education. Each educator was from a different health profession. Berger and Luckmann's thesis on the social construction of reality served as the conceptual framework of the study Throughout the study the researcher was able to appreciate that even though the reality of everyday life is a subjective interpretation of the world, there is a continuous correspondence between the researcher's perceptions of meaning and those of others. The in-depth interview method provided an adequate mechanism for the reconstruction of participants' everyday life experiences, and for the construction of categories of meaning. The researcher applied the method of inductive analysis in the identification of the themes and issues and in the construction of the categories. Nine categories of meaning emerged from the participants' reconstruction: 1) the legitimization of retirement; 2) understandings surrounding one's education; 3) understanding of the human aging process; 4) the legitimization of death; 5) the bonds between human beings as a fundamental element of human reality; 6) the roles within, and the objectification of, human activity; 7) the legitimization of religion and the element of spirituality; 8) understandings surrounding one's self; and 9) the reconstruction of the past: traditions and legitimate practices. Within the categories are areas of convergence between the signification of "one's own education" as a modality of life, and the signification of learning and of its propitiatory and restrictive conditions. As to the understandings of meaning and the emergent categories of meaning, the researcher constructed specific educational recommendations, which emphasize the educational processes of the old adult.

Personality, Category, and Cross-Linguistic Speech Sound Processing: A Connectivistic View

PubMed Central

Li, Will X. Y.

2014-01-01

Category formation of human perception is a vital part of cognitive ability. The disciplines of neuroscience and linguistics, however, seldom mention it in the marrying of the two. The present study reviews the neurological view of language acquisition as normalization of incoming speech signal, and attempts to suggest how speech sound category formation may connect personality with second language speech perception. Through a questionnaire, (being thick or thin) ego boundary, a correlate found to be related to category formation, was proven a positive indicator of personality types. Following the qualitative study, thick boundary and thin boundary English learners native in Cantonese were given a speech-signal perception test using an ABX discrimination task protocol. Results showed that thick-boundary learners performed significantly lower in accuracy rate than thin-boundary learners. It was implied that differences in personality do have an impact on language learning. PMID:24757425

How learning one category influences the learning of another: intercategory generalization based on analogy and specific stimulus information.

PubMed

Nahinsky, Irwin D; Lucas, Barbara A; Edgell, Stephen E; Overfelt, Joseph; Loeb, Richard

2004-01-01

We investigated the effect of learning one category structure on the learning of a related category structure. Photograph-name combinations, called identifiers, were associated with values of four demographic attributes. Two problems were related by analogous demographic attributes, common identifiers, or both to examine the impact of common identifier, related general characteristics, and the interaction of the two variables in mediating learning transfer from one category structure to another. Problems sharing the same identifier information prompted greater positive transfer than those not sharing the same identifier information. In contrast, analogous defining characteristics in the two problems did not facilitate transfer. We computed correlations between responses to first-problem stimuli and responses to analogous second-problem stimuli for each participant. The analogous characteristics produced a tendency to respond in the same way to corresponding stimuli in the two problems. The results support an alignment between category structures related by analogous defining characteristics, which is facilitated by specific identifier information shared by two category structures.

When More Is Less: Feedback Effects in Perceptual Category Learning

ERIC Educational Resources Information Center

Maddox, W. Todd; Love, Bradley C.; Glass, Brian D.; Filoteo, J. Vincent

2008-01-01

Rule-based and information-integration category learning were compared under minimal and full feedback conditions. Rule-based category structures are those for which the optimal rule is verbalizable. Information-integration category structures are those for which the optimal rule is not verbalizable. With minimal feedback subjects are told whether…

Incremental Bayesian Category Learning from Natural Language

ERIC Educational Resources Information Center

Frermann, Lea; Lapata, Mirella

2016-01-01

Models of category learning have been extensively studied in cognitive science and primarily tested on perceptual abstractions or artificial stimuli. In this paper, we focus on categories acquired from natural language stimuli, that is, words (e.g., "chair" is a member of the furniture category). We present a Bayesian model that, unlike…

Categorization: The View from Animal Cognition.

PubMed

Smith, J David; Zakrzewski, Alexandria C; Johnson, Jennifer M; Valleau, Jeanette C; Church, Barbara A

2016-06-15

Exemplar, prototype, and rule theory have organized much of the enormous literature on categorization. From this theoretical foundation have arisen the two primary debates in the literature-the prototype-exemplar debate and the single system-multiple systems debate. We review these theories and debates. Then, we examine the contribution that animal-cognition studies have made to them. Animals have been crucial behavioral ambassadors to the literature on categorization. They reveal the roots of human categorization, the basic assumptions of vertebrates entering category tasks, the surprising weakness of exemplar memory as a category-learning strategy. They show that a unitary exemplar theory of categorization is insufficient to explain human and animal categorization. They show that a multiple-systems theoretical account-encompassing exemplars, prototypes, and rules-will be required for a complete explanation. They show the value of a fitness perspective in understanding categorization, and the value of giving categorization an evolutionary depth and phylogenetic breadth. They raise important questions about the internal similarity structure of natural kinds and categories. They demonstrate strong continuities with humans in categorization, but discontinuities, too. Categorization's great debates are resolving themselves, and to these resolutions animals have made crucial contributions.

Categorization: The View from Animal Cognition

PubMed Central

Smith, J. David; Zakrzewski, Alexandria C.; Johnson, Jennifer M.; Valleau, Jeanette C.; Church, Barbara A.

2016-01-01

Exemplar, prototype, and rule theory have organized much of the enormous literature on categorization. From this theoretical foundation have arisen the two primary debates in the literature—the prototype-exemplar debate and the single system-multiple systems debate. We review these theories and debates. Then, we examine the contribution that animal-cognition studies have made to them. Animals have been crucial behavioral ambassadors to the literature on categorization. They reveal the roots of human categorization, the basic assumptions of vertebrates entering category tasks, the surprising weakness of exemplar memory as a category-learning strategy. They show that a unitary exemplar theory of categorization is insufficient to explain human and animal categorization. They show that a multiple-systems theoretical account—encompassing exemplars, prototypes, and rules—will be required for a complete explanation. They show the value of a fitness perspective in understanding categorization, and the value of giving categorization an evolutionary depth and phylogenetic breadth. They raise important questions about the internal similarity structure of natural kinds and categories. They demonstrate strong continuities with humans in categorization, but discontinuities, too. Categorization’s great debates are resolving themselves, and to these resolutions animals have made crucial contributions. PMID:27314392

Deep Neural Networks as a Computational Model for Human Shape Sensitivity

PubMed Central

Op de Beeck, Hans P.

2016-01-01

Theories of object recognition agree that shape is of primordial importance, but there is no consensus about how shape might be represented, and so far attempts to implement a model of shape perception that would work with realistic stimuli have largely failed. Recent studies suggest that state-of-the-art convolutional ‘deep’ neural networks (DNNs) capture important aspects of human object perception. We hypothesized that these successes might be partially related to a human-like representation of object shape. Here we demonstrate that sensitivity for shape features, characteristic to human and primate vision, emerges in DNNs when trained for generic object recognition from natural photographs. We show that these models explain human shape judgments for several benchmark behavioral and neural stimulus sets on which earlier models mostly failed. In particular, although never explicitly trained for such stimuli, DNNs develop acute sensitivity to minute variations in shape and to non-accidental properties that have long been implicated to form the basis for object recognition. Even more strikingly, when tested with a challenging stimulus set in which shape and category membership are dissociated, the most complex model architectures capture human shape sensitivity as well as some aspects of the category structure that emerges from human judgments. As a whole, these results indicate that convolutional neural networks not only learn physically correct representations of object categories but also develop perceptually accurate representational spaces of shapes. An even more complete model of human object representations might be in sight by training deep architectures for multiple tasks, which is so characteristic in human development. PMID:27124699

The time course of explicit and implicit categorization.

PubMed

Smith, J David; Zakrzewski, Alexandria C; Herberger, Eric R; Boomer, Joseph; Roeder, Jessica L; Ashby, F Gregory; Church, Barbara A

2015-10-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization.

Testing Prepares Students to Learn Better: The Forward Effect of Testing in Category Learning

ERIC Educational Resources Information Center

Lee, Hee Seung; Ahn, Dahwi

2018-01-01

The forward effect of testing occurs when testing on previously studied information facilitates subsequent learning. The present research investigated whether interim testing on initially studied materials enhances the learning of new materials in category learning and examined the metacognitive judgments of such learning. Across the 4…

Normal Aging and the Dissociable Prototype Learning Systems

PubMed Central

Glass, Brian D.; Chotibut, Tanya; Pacheco, Jennifer; Schnyer, David M.; Maddox, W. Todd

2011-01-01

Dissociable prototype learning systems have been demonstrated behaviorally and with neuroimaging in younger adults as well as with patient populations. In A/not-A (AN) prototype learning, participants are shown members of category A during training, and during test are asked to decide whether novel items are in category A or are not in category A. Research suggests that AN learning is mediated by a perceptual learning system. In A/B (AB) prototype learning, participants are shown members of category A and B during training, and during test are asked to decide whether novel items are in category A or category B. In contrast to AN, research suggests that AB learning is mediated by a declarative memory system. The current study examined the effects of normal aging on AN and AB prototype learning. We observed an age-related deficit in AB learning, but an age-related advantage in AN learning. Computational modeling supports one possible interpretation based on narrower selective attentional focus in older adults in the AB task and broader selective attention in the AN task. Neuropsychological testing in older participants suggested that executive functioning and attentional control were associated with better performance in both tasks. However, nonverbal memory was associated with better AN performance, while visual attention was associated with worse AB performance. The results support an interactive memory systems approach and suggest that age-related declines in one memory system can lead to deficits in some tasks, but to enhanced performance in others. PMID:21875215

Studies of Complex Behavior and Their Relation to Trouble Shooting in Electronic Equipment.

DTIC Science & Technology

1957-06-01

discussed. It has been concluded that the study of human problem • . solving, concept formation, probability learning, and so forth, has i. provided litt 1...five actions) used by men in trouble shooting radio problemson the MASTS , AUTOMI STS, arid a job—sample test . There were five L categories so defined...Defense Human Research Unit ’ s proposed Task MA INTRAIN• will be drawn upon as needed for the non—trouble —shooting topics. I

Word-level information influences phonetic learning in adults and infants

PubMed Central

Feldman, Naomi H.; Myers, Emily B.; White, Katherine S.; Griffiths, Thomas L.; Morgan, James L.

2013-01-01

Infants begin to segment words from fluent speech during the same time period that they learn phonetic categories. Segmented words can provide a potentially useful cue for phonetic learning, yet accounts of phonetic category acquisition typically ignore the contexts in which sounds appear. We present two experiments to show that, contrary to the assumption that phonetic learning occurs in isolation, learners are sensitive to the words in which sounds appear and can use this information to constrain their interpretation of phonetic variability. Experiment 1 shows that adults use word-level information in a phonetic category learning task, assigning acoustically similar vowels to different categories more often when those sounds consistently appear in different words. Experiment 2 demonstrates that eight-month-old infants similarly pay attention to word-level information and that this information affects how they treat phonetic contrasts. These findings suggest that phonetic category learning is a rich, interactive process that takes advantage of many different types of cues that are present in the input. PMID:23562941

Toward interactive search in remote sensing imagery

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

Porter, Reid B; Hush, Do; Harvey, Neal

2010-01-01

To move from data to information in almost all science and defense applications requires a human-in-the-loop to validate information products, resolve inconsistencies, and account for incomplete and potentially deceptive sources of information. This is a key motivation for visual analytics which aims to develop techniques that complement and empower human users. By contrast, the vast majority of algorithms developed in machine learning aim to replace human users in data exploitation. In this paper we describe a recently introduced machine learning problem, called rare category detection, which may be a better match to visual analytic environments. We describe a new designmore » criteria for this problem, and present comparisons to existing techniques with both synthetic and real-world datasets. We conclude by describing an application in broad-area search of remote sensing imagery.« less

INCREASES IN FUNCTIONAL CONNECTIVITY BETWEEN PREFRONTAL CORTEX AND STRIATUM DURING CATEGORY LEARNING

PubMed Central

Antzoulatos, Evan G.; Miller, Earl K.

2014-01-01

SUMMARY Functional connectivity between the prefrontal cortex (PFC) and striatum (STR) is thought critical for cognition, and has been linked to conditions like autism and schizophrenia. We recorded from multiple electrodes in PFC and STR while monkeys acquired new categories. Category learning was accompanied by an increase in beta-band synchronization of LFPs between, but not within, the PFC and STR. After learning, different pairs of PFC-STR electrodes showed stronger synchrony for one or the other category, suggesting category-specific functional circuits. This category-specific synchrony was also seen between PFC spikes and STR LFPs, but not the reverse, reflecting the direct monosynaptic connections from the PFC to STR. However, causal connectivity analyses suggested that the polysynaptic connections from STR to the PFC exerted a stronger overall influence. This supports models positing that the basal ganglia “train” the PFC. Category learning may depend on the formation of functional circuits between the PFC and STR. PMID:24930701

Visual variability affects early verb learning.

PubMed

Twomey, Katherine E; Lush, Lauren; Pearce, Ruth; Horst, Jessica S

2014-09-01

Research demonstrates that within-category visual variability facilitates noun learning; however, the effect of visual variability on verb learning is unknown. We habituated 24-month-old children to a novel verb paired with an animated star-shaped actor. Across multiple trials, children saw either a single action from an action category (identical actions condition, for example, travelling while repeatedly changing into a circle shape) or multiple actions from that action category (variable actions condition, for example, travelling while changing into a circle shape, then a square shape, then a triangle shape). Four test trials followed habituation. One paired the habituated verb with a new action from the habituated category (e.g., 'dacking' + pentagon shape) and one with a completely novel action (e.g., 'dacking' + leg movement). The others paired a new verb with a new same-category action (e.g., 'keefing' + pentagon shape), or a completely novel category action (e.g., 'keefing' + leg movement). Although all children discriminated novel verb/action pairs, children in the identical actions condition discriminated trials that included the completely novel verb, while children in the variable actions condition discriminated the out-of-category action. These data suggest that - as in noun learning - visual variability affects verb learning and children's ability to form action categories. © 2014 The British Psychological Society.

An Examination of Strategy Implementation During Abstract Nonlinguistic Category Learning in Aphasia

PubMed Central

Kiran, Swathi

2015-01-01

Purpose Our purpose was to study strategy use during nonlinguistic category learning in aphasia. Method Twelve control participants without aphasia and 53 participants with aphasia (PWA) completed a computerized feedback-based category learning task consisting of training and testing phases. Accuracy rates of categorization in testing phases were calculated. To evaluate strategy use, strategy analyses were conducted over training and testing phases. Participant data were compared with model data that simulated complex multi-cue, single feature, and random pattern strategies. Learning success and strategy use were evaluated within the context of standardized cognitive–linguistic assessments. Results Categorization accuracy was higher among control participants than among PWA. The majority of control participants implemented suboptimal or optimal multi-cue and single-feature strategies by testing phases of the experiment. In contrast, a large subgroup of PWA implemented random patterns, or no strategy, during both training and testing phases of the experiment. Conclusions Person-to-person variability arises not only in category learning ability but also in the strategies implemented to complete category learning tasks. PWA less frequently developed effective strategies during category learning tasks than control participants. Certain PWA may have impairments of strategy development or feedback processing not captured by language and currently probed cognitive abilities. PMID:25908438

Effect of explicit dimension instruction on speech category learning

PubMed Central

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

2015-01-01

Learning non-native speech categories is often considered a challenging task in adulthood. This difficulty is driven by cross-language differences in weighting critical auditory dimensions that differentiate speech categories. For example, previous studies have shown that differentiating Mandarin tonal categories requires attending to dimensions related to pitch height and direction. Relative to native speakers of Mandarin, the pitch direction dimension is under-weighted by native English speakers. In the current study, we examined the effect of explicit instructions (dimension instruction) on native English speakers' Mandarin tone category learning within the framework of a dual-learning systems (DLS) model. This model predicts that successful speech category learning is initially mediated by an explicit, reflective learning system that frequently utilizes unidimensional rules, with an eventual switch to a more implicit, reflexive learning system that utilizes multidimensional rules. Participants were explicitly instructed to focus and/or ignore the pitch height dimension, the pitch direction dimension, or were given no explicit prime. Our results show that instruction instructing participants to focus on pitch direction, and instruction diverting attention away from pitch height resulted in enhanced tone categorization. Computational modeling of participant responses suggested that instruction related to pitch direction led to faster and more frequent use of multidimensional reflexive strategies, and enhanced perceptual selectivity along the previously underweighted pitch direction dimension. PMID:26542400

Learning Object Names at Different Hierarchical Levels Using Cross-Situational Statistics.

PubMed

Chen, Chi-Hsin; Zhang, Yayun; Yu, Chen

2018-05-01

Objects in the world usually have names at different hierarchical levels (e.g., beagle, dog, animal). This research investigates adults' ability to use cross-situational statistics to simultaneously learn object labels at individual and category levels. The results revealed that adults were able to use co-occurrence information to learn hierarchical labels in contexts where the labels for individual objects and labels for categories were presented in completely separated blocks, in interleaved blocks, or mixed in the same trial. Temporal presentation schedules significantly affected the learning of individual object labels, but not the learning of category labels. Learners' subsequent generalization of category labels indicated sensitivity to the structure of statistical input. Copyright © 2017 Cognitive Science Society, Inc.

The Role of Bottom-Up Processing in Perceptual Categorization by 3- to 4-Month-Old Infants: Simulations and Data

ERIC Educational Resources Information Center

French, Robert M.; Mareschal, Denis; Mermillod, Martial; Quinn, Paul C.

2004-01-01

Disentangling bottom-up and top-down processing in adult category learning is notoriously difficult. Studying category learning in infancy provides a simple way of exploring category learning while minimizing the contribution of top-down information. Three- to 4-month-old infants presented with cat or dog images will form a perceptual category…

The Time Course of Explicit and Implicit Categorization

PubMed Central

Zakrzewski, Alexandria C.; Herberger, Eric; Boomer, Joseph; Roeder, Jessica; Ashby, F. Gregory; Church, Barbara A.

2015-01-01

Contemporary theory in cognitive neuroscience distinguishes, among the processes and utilities that serve categorization, explicit and implicit systems of category learning that learn, respectively, category rules by active hypothesis testing or adaptive behaviors by association and reinforcement. Little is known about the time course of categorization within these systems. Accordingly, the present experiments contrasted tasks that fostered explicit categorization (because they had a one-dimensional, rule-based solution) or implicit categorization (because they had a two-dimensional, information-integration solution). In Experiment 1, participants learned categories under unspeeded or speeded conditions. In Experiment 2, they applied previously trained category knowledge under unspeeded or speeded conditions. Speeded conditions selectively impaired implicit category learning and implicit mature categorization. These results illuminate the processing dynamics of explicit/implicit categorization. PMID:26025556

Adults' and Children's Understanding of How Expertise Influences Learning.

PubMed

Danovitch, Judith H; Shenouda, Christine K

2018-01-01

Adults and children use information about expertise to infer what a person is likely to know, but it is unclear whether they realize that expertise also has implications for learning. We explore adults' and children's understanding that expertise in a particular category supports learning about a closely related category. In four experiments, 5-year-olds and adults (n = 160) judged which of two people would be better at learning about a new category. When faced with an expert and a nonexpert, adults consistently indicated that expertise supports learning in a closely related category; however, children's judgments were inconsistent and were strongly influenced by the description of the nonexpert. The results suggest that although children understand what it means to be an expert, they may judge an individual's learning capacity based on different considerations than adults.

Models as Relational Categories

NASA Astrophysics Data System (ADS)

Kokkonen, Tommi

2017-11-01

Model-based learning (MBL) has an established position within science education. It has been found to enhance conceptual understanding and provide a way for engaging students in authentic scientific activity. Despite ample research, few studies have examined the cognitive processes regarding learning scientific concepts within MBL. On the other hand, recent research within cognitive science has examined the learning of so-called relational categories. Relational categories are categories whose membership is determined on the basis of the common relational structure. In this theoretical paper, I argue that viewing models as relational categories provides a well-motivated cognitive basis for MBL. I discuss the different roles of models and modeling within MBL (using ready-made models, constructive modeling, and generative modeling) and discern the related cognitive aspects brought forward by the reinterpretation of models as relational categories. I will argue that relational knowledge is vital in learning novel models and in the transfer of learning. Moreover, relational knowledge underlies the coherent, hierarchical knowledge of experts. Lastly, I will examine how the format of external representations may affect the learning of models and the relevant relations. The nature of the learning mechanisms underlying students' mental representations of models is an interesting open question to be examined. Furthermore, the ways in which the expert-like knowledge develops and how to best support it is in need of more research. The discussion and conceptualization of models as relational categories allows discerning students' mental representations of models in terms of evolving relational structures in greater detail than previously done.

The effects of social concern goals on the value of learning and on the intentions of medical students to change their majors

PubMed Central

Park, Soowon; Cho, Seunghee; Lee, Jun-Young

2017-01-01

ABSTRACT Background: In the process of developing a professional medical expertise, goals can become a psychological impetus and act as a source of retaining an individual’s persistency. Therefore, the goals of medical students should be considered when designing a curriculum for health professions. Purpose: The purpose of this study was to examine relative effects of goal categories on the value of learning and intention to change one’s major. Method: Data were obtained from the Korea Education Longitudinal Study, which included 1938 representative Korean college freshmen majoring in medicine, engineering, natural science and humanities. They answered a survey questionnaire about goal categories (i.e., social concern, affiliation, self-growth, leisure, wealth, and fame), the value of learning, and intention to change one's major. Results: For medical students, social concern goals were positively related to the value of learning and negatively related to the intention to change one's major. Social concern goals decreased the intention to change one's major directly, and also indirectly through increased value of learning. Conclusion: Providing context for enhancing medical students’ social concern goals is necessary in a medical training curriculum, not only for the students’ professional development but also for improving society. Abbreviations: GCT: Goal contents theory GPA: Grade point average KELS: Korea education longitudinal study SDLA: Self-directed learning abilities SDT: Self-determination theory PMID:28580860

The effects of social concern goals on the value of learning and on the intentions of medical students to change their majors.

PubMed

Park, Soowon; Cho, Seunghee; Lee, Jun-Young

2017-01-01

In the process of developing a professional medical expertise, goals can become a psychological impetus and act as a source of retaining an individual's persistency. Therefore, the goals of medical students should be considered when designing a curriculum for health professions. The purpose of this study was to examine relative effects of goal categories on the value of learning and intention to change one's major. Data were obtained from the Korea Education Longitudinal Study, which included 1938 representative Korean college freshmen majoring in medicine, engineering, natural science and humanities. They answered a survey questionnaire about goal categories (i.e., social concern, affiliation, self-growth, leisure, wealth, and fame), the value of learning, and intention to change one's major. For medical students, social concern goals were positively related to the value of learning and negatively related to the intention to change one's major. Social concern goals decreased the intention to change one's major directly, and also indirectly through increased value of learning. Providing context for enhancing medical students' social concern goals is necessary in a medical training curriculum, not only for the students' professional development but also for improving society. GCT: Goal contents theory GPA: Grade point average KELS: Korea education longitudinal study SDLA: Self-directed learning abilities SDT: Self-determination theory.

Cultural dimensions of learning

NASA Astrophysics Data System (ADS)

Eyford, Glen A.

1990-06-01

How, what, when and where we learn is frequently discussed, as are content versus process, or right brain versus left brain learning. What is usually missing is the cultural dimension. This is not an easy concept to define, but various aspects can be identified. The World Decade for Cultural Development emphasizes the need for a counterbalance to a quantitative, economic approach. In the last century poets also warned against brutalizing materialism, and Sorokin and others have described culture more recently in terms of cohesive basic values expressed through aesthetics and institutions. Bloom's taxonomy incorporates the category of affective learning, which internalizes values. If cultural learning goes beyond knowledge acquisition, perhaps the surest way of understanding the cultural dimension of learning is to examine the aesthetic experience. This can use myths, metaphors and symbols, and to teach and learn by using these can help to unlock the human potential for vision and creativity.

A Note on DeCaro, Thomas, and Beilock (2008): Further Data Demonstrate Complexities in the Assessment of Information-Integration Category Learning

ERIC Educational Resources Information Center

Tharp, Ian J.; Pickering, Alan D.

2009-01-01

DeCaro et al. [DeCaro, M. S., Thomas, R. D., & Beilock, S. L. (2008). "Individual differences in category learning: Sometimes less working memory capacity is better than more." "Cognition, 107"(1), 284-294] explored how individual differences in working memory capacity differentially mediate the learning of distinct category structures.…

Fine-grained leukocyte classification with deep residual learning for microscopic images.

PubMed

Qin, Feiwei; Gao, Nannan; Peng, Yong; Wu, Zizhao; Shen, Shuying; Grudtsin, Artur

2018-08-01

Leukocyte classification and cytometry have wide applications in medical domain, previous researches usually exploit machine learning techniques to classify leukocytes automatically. However, constrained by the past development of machine learning techniques, for example, extracting distinctive features from raw microscopic images are difficult, the widely used SVM classifier only has relative few parameters to tune, these methods cannot efficiently handle fine-grained classification cases when the white blood cells have up to 40 categories. Based on deep learning theory, a systematic study is conducted on finer leukocyte classification in this paper. A deep residual neural network based leukocyte classifier is constructed at first, which can imitate the domain expert's cell recognition process, and extract salient features robustly and automatically. Then the deep neural network classifier's topology is adjusted according to the prior knowledge of white blood cell test. After that the microscopic image dataset with almost one hundred thousand labeled leukocytes belonging to 40 categories is built, and combined training strategies are adopted to make the designed classifier has good generalization ability. The proposed deep residual neural network based classifier was tested on microscopic image dataset with 40 leukocyte categories. It achieves top-1 accuracy of 77.80%, top-5 accuracy of 98.75% during the training procedure. The average accuracy on the test set is nearly 76.84%. This paper presents a fine-grained leukocyte classification method for microscopic images, based on deep residual learning theory and medical domain knowledge. Experimental results validate the feasibility and effectiveness of our approach. Extended experiments support that the fine-grained leukocyte classifier could be used in real medical applications, assist doctors in diagnosing diseases, reduce human power significantly. Copyright © 2018 Elsevier B.V. All rights reserved.

Verb Learning in 14- and 18-Month-Old English-Learning Infants

ERIC Educational Resources Information Center

He, Angela Xiaoxue; Lidz, Jeffrey

2017-01-01

The present study investigates English-learning infants' early understanding of the link between the grammatical category "verb" and the conceptual category "event," and their ability to recruit morphosyntactic information online to learn novel verb meanings. We report two experiments using an infant-controlled…

Brief Report: Simulations Suggest Heterogeneous Category Learning and Generalization in Children with Autism is a Result of Idiosyncratic Perceptual Transformations.

PubMed

Mercado, Eduardo; Church, Barbara A

2016-08-01

Children with autism spectrum disorder (ASD) sometimes have difficulties learning categories. Past computational work suggests that such deficits may result from atypical representations in cortical maps. Here we use neural networks to show that idiosyncratic transformations of inputs can result in the formation of feature maps that impair category learning for some inputs, but not for other closely related inputs. These simulations suggest that large inter- and intra-individual variations in learning capacities shown by children with ASD across similar categorization tasks may similarly result from idiosyncratic perceptual encoding that is resistant to experience-dependent changes. If so, then both feedback- and exposure-based category learning should lead to heterogeneous, stimulus-dependent deficits in children with ASD.

Attribute conjunctions and the part configuration advantage in object category learning.

PubMed

Saiki, J; Hummel, J E

1996-07-01

Five experiments demonstrated that in object category learning people are particularly sensitive to conjunctions of part shapes and relative locations. Participants learned categories defined by a part's shape and color (part-color conjunctions) or by a part's shape and its location relative to another part (part-location conjunctions). The statistical properties of the categories were identical across these conditions, as were the salience of color and relative location. Participants were better at classifying objects defined by part-location conjunctions than objects defined by part-color conjunctions. Subsequent experiments revealed that this effect was not due to the specific color manipulation or the role of location per se. These results suggest that the shape bias in object categorization is at least partly due to sensitivity to part-location conjunctions and suggest a new processing constraint on category learning.

A neurocomputational theory of how explicit learning bootstraps early procedural learning.

PubMed

Paul, Erick J; Ashby, F Gregory

2013-01-01

It is widely accepted that human learning and memory is mediated by multiple memory systems that are each best suited to different requirements and demands. Within the domain of categorization, at least two systems are thought to facilitate learning: an explicit (declarative) system depending largely on the prefrontal cortex, and a procedural (non-declarative) system depending on the basal ganglia. Substantial evidence suggests that each system is optimally suited to learn particular categorization tasks. However, it remains unknown precisely how these systems interact to produce optimal learning and behavior. In order to investigate this issue, the present research evaluated the progression of learning through simulation of categorization tasks using COVIS, a well-known model of human category learning that includes both explicit and procedural learning systems. Specifically, the model's parameter space was thoroughly explored in procedurally learned categorization tasks across a variety of conditions and architectures to identify plausible interaction architectures. The simulation results support the hypothesis that one-way interaction between the systems occurs such that the explicit system "bootstraps" learning early on in the procedural system. Thus, the procedural system initially learns a suboptimal strategy employed by the explicit system and later refines its strategy. This bootstrapping could be from cortical-striatal projections that originate in premotor or motor regions of cortex, or possibly by the explicit system's control of motor responses through basal ganglia-mediated loops.

How category learning affects object representations: Not all morphspaces stretch alike

PubMed Central

Folstein, Jonathan R.; Gauthier, Isabel; Palmeri, Thomas J.

2012-01-01

How does learning to categorize objects affect how we visually perceive them? Behavioral, neurophysiological, and neuroimaging studies have tested the degree to which category learning influences object representations, with conflicting results. Some studies find that objects become more visually discriminable along dimensions relevant to previously learned categories, while others find no such effect. One critical factor we explore here lies in the structure of the morphspaces used in different studies. Studies finding no increase in discriminability often use “blended” morphspaces, with morphparents lying at corners of the space. By contrast, studies finding increases in discriminability use “factorial” morphspaces, defined by separate morphlines forming axes of the space. Using the same four morphparents, we created both factorial and blended morphspaces matched in pairwise discriminability. Category learning caused a selective increase in discriminability along the relevant dimension of the factorial space, but not in the blended space, and led to the creation of functional dimensions in the factorial space, but not in the blended space. These findings demonstrate that not all morphspaces stretch alike: Only some morphspaces support enhanced discriminability to relevant object dimensions following category learning. Our results have important implications for interpreting neuroimaging studies reporting little or no effect of category learning on object representations in the visual system: Those studies may have been limited by their use of blended morphspaces. PMID:22746950

Field-Dependence/Independence and Active Learning of Verbal and Geometric Material.

ERIC Educational Resources Information Center

Reardon, Richard; And Others

1982-01-01

Field-dependent and independent subjects sorted geometric and verbal material according to category exemplars, forcing active learning, and then recalled the category locations. Field-independent individuals generally performed better on learning and memory tasks with a more active approach. Active versus passive learning styles are discussed.…

Associations between Chinese EFL Graduate Students' Beliefs and Language Learning Strategies

ERIC Educational Resources Information Center

Tang, Mailing; Tian, Jianrong

2015-01-01

This study, using Horwitz's Beliefs about Language Learning Inventory and Oxford's Strategy Inventory for Language Learning, investigated learners' beliefs about language learning and their choice of strategy categories among 546 graduate students in China. The correlation between learners' beliefs and their strategy categories use was examined.…

Impact of feature saliency on visual category learning.

PubMed

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the 'essence' of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies.

Impact of feature saliency on visual category learning

PubMed Central

Hammer, Rubi

2015-01-01

People have to sort numerous objects into a large number of meaningful categories while operating in varying contexts. This requires identifying the visual features that best predict the ‘essence’ of objects (e.g., edibility), rather than categorizing objects based on the most salient features in a given context. To gain this capacity, visual category learning (VCL) relies on multiple cognitive processes. These may include unsupervised statistical learning, that requires observing multiple objects for learning the statistics of their features. Other learning processes enable incorporating different sources of supervisory information, alongside the visual features of the categorized objects, from which the categorical relations between few objects can be deduced. These deductions enable inferring that objects from the same category may differ from one another in some high-saliency feature dimensions, whereas lower-saliency feature dimensions can best differentiate objects from distinct categories. Here I illustrate how feature saliency affects VCL, by also discussing kinds of supervisory information enabling reflective categorization. Arguably, principles debated here are often being ignored in categorization studies. PMID:25954220

Tracking Multiple Statistics: Simultaneous Learning of Object Names and Categories in English and Mandarin Speakers.

PubMed

Chen, Chi-Hsin; Gershkoff-Stowe, Lisa; Wu, Chih-Yi; Cheung, Hintat; Yu, Chen

2017-08-01

Two experiments were conducted to examine adult learners' ability to extract multiple statistics in simultaneously presented visual and auditory input. Experiment 1 used a cross-situational learning paradigm to test whether English speakers were able to use co-occurrences to learn word-to-object mappings and concurrently form object categories based on the commonalities across training stimuli. Experiment 2 replicated the first experiment and further examined whether speakers of Mandarin, a language in which final syllables of object names are more predictive of category membership than English, were able to learn words and form object categories when trained with the same type of structures. The results indicate that both groups of learners successfully extracted multiple levels of co-occurrence and used them to learn words and object categories simultaneously. However, marked individual differences in performance were also found, suggesting possible interference and competition in processing the two concurrent streams of regularities. Copyright © 2016 Cognitive Science Society, Inc.

Inductive reasoning about causally transmitted properties.

PubMed

Shafto, Patrick; Kemp, Charles; Bonawitz, Elizabeth Baraff; Coley, John D; Tenenbaum, Joshua B

2008-11-01

Different intuitive theories constrain and guide inferences in different contexts. Formalizing simple intuitive theories as probabilistic processes operating over structured representations, we present a new computational model of category-based induction about causally transmitted properties. A first experiment demonstrates undergraduates' context-sensitive use of taxonomic and food web knowledge to guide reasoning about causal transmission and shows good qualitative agreement between model predictions and human inferences. A second experiment demonstrates strong quantitative and qualitative fits to inferences about a more complex artificial food web. A third experiment investigates human reasoning about complex novel food webs where species have known taxonomic relations. Results demonstrate a double-dissociation between the predictions of our causal model and a related taxonomic model [Kemp, C., & Tenenbaum, J. B. (2003). Learning domain structures. In Proceedings of the 25th annual conference of the cognitive science society]: the causal model predicts human inferences about diseases but not genes, while the taxonomic model predicts human inferences about genes but not diseases. We contrast our framework with previous models of category-based induction and previous formal instantiations of intuitive theories, and outline challenges in developing a complete model of context-sensitive reasoning.

A Novel Clustering Method Curbing the Number of States in Reinforcement Learning

NASA Astrophysics Data System (ADS)

Kotani, Naoki; Nunobiki, Masayuki; Taniguchi, Kenji

We propose an efficient state-space construction method for a reinforcement learning. Our method controls the number of categories with improving the clustering method of Fuzzy ART which is an autonomous state-space construction method. The proposed method represents weight vector as the mean value of input vectors in order to curb the number of new categories and eliminates categories whose state values are low to curb the total number of categories. As the state value is updated, the size of category becomes small to learn policy strictly. We verified the effectiveness of the proposed method with simulations of a reaching problem for a two-link robot arm. We confirmed that the number of categories was reduced and the agent achieved the complex task quickly.

Decoding Multiple Sound Categories in the Human Temporal Cortex Using High Resolution fMRI

PubMed Central

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C. M.

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain’s representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases. PMID:25692885

Decoding multiple sound categories in the human temporal cortex using high resolution fMRI.

PubMed

Zhang, Fengqing; Wang, Ji-Ping; Kim, Jieun; Parrish, Todd; Wong, Patrick C M

2015-01-01

Perception of sound categories is an important aspect of auditory perception. The extent to which the brain's representation of sound categories is encoded in specialized subregions or distributed across the auditory cortex remains unclear. Recent studies using multivariate pattern analysis (MVPA) of brain activations have provided important insights into how the brain decodes perceptual information. In the large existing literature on brain decoding using MVPA methods, relatively few studies have been conducted on multi-class categorization in the auditory domain. Here, we investigated the representation and processing of auditory categories within the human temporal cortex using high resolution fMRI and MVPA methods. More importantly, we considered decoding multiple sound categories simultaneously through multi-class support vector machine-recursive feature elimination (MSVM-RFE) as our MVPA tool. Results show that for all classifications the model MSVM-RFE was able to learn the functional relation between the multiple sound categories and the corresponding evoked spatial patterns and classify the unlabeled sound-evoked patterns significantly above chance. This indicates the feasibility of decoding multiple sound categories not only within but across subjects. However, the across-subject variation affects classification performance more than the within-subject variation, as the across-subject analysis has significantly lower classification accuracies. Sound category-selective brain maps were identified based on multi-class classification and revealed distributed patterns of brain activity in the superior temporal gyrus and the middle temporal gyrus. This is in accordance with previous studies, indicating that information in the spatially distributed patterns may reflect a more abstract perceptual level of representation of sound categories. Further, we show that the across-subject classification performance can be significantly improved by averaging the fMRI images over items, because the irrelevant variations between different items of the same sound category are reduced and in turn the proportion of signals relevant to sound categorization increases.

Distributional Language Learning: Mechanisms and Models of ategory Formation.

PubMed

Aslin, Richard N; Newport, Elissa L

2014-09-01

In the past 15 years, a substantial body of evidence has confirmed that a powerful distributional learning mechanism is present in infants, children, adults and (at least to some degree) in nonhuman animals as well. The present article briefly reviews this literature and then examines some of the fundamental questions that must be addressed for any distributional learning mechanism to operate effectively within the linguistic domain. In particular, how does a naive learner determine the number of categories that are present in a corpus of linguistic input and what distributional cues enable the learner to assign individual lexical items to those categories? Contrary to the hypothesis that distributional learning and category (or rule) learning are separate mechanisms, the present article argues that these two seemingly different processes---acquiring specific structure from linguistic input and generalizing beyond that input to novel exemplars---actually represent a single mechanism. Evidence in support of this single-mechanism hypothesis comes from a series of artificial grammar-learning studies that not only demonstrate that adults can learn grammatical categories from distributional information alone, but that the specific patterning of distributional information among attested utterances in the learning corpus enables adults to generalize to novel utterances or to restrict generalization when unattested utterances are consistently absent from the learning corpus. Finally, a computational model of distributional learning that accounts for the presence or absence of generalization is reviewed and the implications of this model for linguistic-category learning are summarized.

Nursing students experienced personal inadequacy, vulnerability and transformation during their patient care encounter: A qualitative meta-synthesis.

PubMed

Kaldal, Maiken Holm; Kristiansen, Jette; Uhrenfeldt, Lisbeth

2018-05-01

To identify, appraise and synthesize the best available evidence exploring nursing students' experiences of professional patient care encounters in a hospital unit. The Joanna Briggs Institute (JBI) guidelines were followed and a meta-synthesis was conducted. Qualitative research articles were considered for inclusion in the review, and JBI's meta-aggregative approach to synthesizing qualitative evidence was followed. An extensive search for relevant literature was undertaken in scientific databases. Data were extracted from the included research articles, and qualitative research findings were pooled using the Qualitative Assessment and Review Instrument. This involved categorization of findings on the basis of similarity of meaning and aggregation of these categories to produce a comprehensive set of synthesized findings. A total of five research articles met the inclusion criteria and were included in the review. The review process resulted in 46 subcategories that were aggregated into 13 categories. The categories generated four synthesized findings: personal existence; personal learning and development; being a professional fellow human; and clinical learning environment. We meta-synthesized that: Nursing students experienced personal inadequacy, vulnerability and a transformation during their patient care encounter. Copyright © 2018 Elsevier Ltd. All rights reserved.

Auditory working memory predicts individual differences in absolute pitch learning.

PubMed

Van Hedger, Stephen C; Heald, Shannon L M; Koch, Rachelle; Nusbaum, Howard C

2015-07-01

Absolute pitch (AP) is typically defined as the ability to label an isolated tone as a musical note in the absence of a reference tone. At first glance the acquisition of AP note categories seems like a perceptual learning task, since individuals must assign a category label to a stimulus based on a single perceptual dimension (pitch) while ignoring other perceptual dimensions (e.g., loudness, octave, instrument). AP, however, is rarely discussed in terms of domain-general perceptual learning mechanisms. This is because AP is typically assumed to depend on a critical period of development, in which early exposure to pitches and musical labels is thought to be necessary for the development of AP precluding the possibility of adult acquisition of AP. Despite this view of AP, several previous studies have found evidence that absolute pitch category learning is, to an extent, trainable in a post-critical period adult population, even if the performance typically achieved by this population is below the performance of a "true" AP possessor. The current studies attempt to understand the individual differences in learning to categorize notes using absolute pitch cues by testing a specific prediction regarding cognitive capacity related to categorization - to what extent does an individual's general auditory working memory capacity (WMC) predict the success of absolute pitch category acquisition. Since WMC has been shown to predict performance on a wide variety of other perceptual and category learning tasks, we predict that individuals with higher WMC should be better at learning absolute pitch note categories than individuals with lower WMC. Across two studies, we demonstrate that auditory WMC predicts the efficacy of learning absolute pitch note categories. These results suggest that a higher general auditory WMC might underlie the formation of absolute pitch categories for post-critical period adults. Implications for understanding the mechanisms that underlie the phenomenon of AP are also discussed. Copyright © 2015. Published by Elsevier B.V.

Effect of between-category similarity on basic-level superiority in pigeons

PubMed Central

Lazareva, Olga F.; Soto, Fabián A.; Wasserman, Edward A.

2010-01-01

Children categorize stimuli at the basic level faster than at the superordinate level. We hypothesized that between-category similarity may affect this basic-level superiority effect. Dissimilar categories may be easy to distinguish at the basic level but be difficult to group at the superordinate level, whereas similar categories may be easy to group at the superordinate level but be difficult to distinguish at the basic level. Consequently, similar basic-level categories may produce a superordinate-before-basic learning trend, whereas dissimilar basic-level categories may result in a basic-before-superordinate learning trend. We tested this hypothesis in pigeons by constructing superordinate-level categories out of basic-level categories with known similarity. In Experiment 1, we experimentally evaluated the between-category similarity of four basic-level photographic categories using multiple fixed interval-extinction training (Astley & Wasserman, 1992). We used the resultant similarity matrices in Experiment 2 to construct two superordinate-level categories from basic-level categories with high between-category similarity (cars and persons; chairs and flowers). We then trained pigeons to concurrently classify those photographs into either the proper basic-level category or the proper superordinate-level category. Under these conditions, the pigeons learned the superordinate-level discrimination faster than the basic-level discrimination, confirming our hypothesis that basic-level superiority is affected by between-category similarity. PMID:20600696

Category learning increases discriminability of relevant object dimensions in visual cortex.

PubMed

Folstein, Jonathan R; Palmeri, Thomas J; Gauthier, Isabel

2013-04-01

Learning to categorize objects can transform how they are perceived, causing relevant perceptual dimensions predictive of object category to become enhanced. For example, an expert mycologist might become attuned to species-specific patterns of spacing between mushroom gills but learn to ignore cap textures attributable to varying environmental conditions. These selective changes in perception can persist beyond the act of categorizing objects and influence our ability to discriminate between them. Using functional magnetic resonance imaging adaptation, we demonstrate that such category-specific perceptual enhancements are associated with changes in the neural discriminability of object representations in visual cortex. Regions within the anterior fusiform gyrus became more sensitive to small variations in shape that were relevant during prior category learning. In addition, extrastriate occipital areas showed heightened sensitivity to small variations in shape that spanned the category boundary. Visual representations in cortex, just like our perception, are sensitive to an object's history of categorization.

The naturalistic fallacy is modern.

PubMed

Daston, Lorraine

2014-09-01

The naturalistic fallacy appears to be ubiquitous and irresistible. The avant-garde and the rearguard, the devout and the secular, the learned elite and the lay public all seem to want to enlist nature on their side, everywhere and always. Yet a closer look at the history of the term "naturalistic fallacy" and its associated arguments suggests that this way of understanding (and criticizing) appeals to nature's authority in human affairs is of relatively modern origin. To apply this category cross-historically masks considerable variability and naturalizes our own assumptions about the natural and the human.

Frontiers in Learning. The Association of Higher Education Facilities Officers Educational Conference and Annual Meeting Proceedings (83rd, Salt Lake City, Utah, July 21-23, 1996).

ERIC Educational Resources Information Center

APPA: Association of Higher Education Facilities Officers, Alexandria, VA.

These 25 papers from a conference of higher education facilities offices are grouped into 5 categories: business management; energy and environment; human resources; operations and maintenance; and planning, design and construction. Papers are: (1) "Provider of Choice" (Jerry C. Black); (2) "Re-Engineering--'Inside-Inside' or Outside-Inside': A…

Non-linguistic learning in aphasia: Effects of training method and stimulus characteristics

PubMed Central

Vallila-Rohter, Sofia; Kiran, Swathi

2013-01-01

Purpose The purpose of the current study was to explore non-linguistic learning ability in patients with aphasia, examining the impact of stimulus typicality and feedback on success with learning. Method Eighteen patients with aphasia and eight healthy controls participated in this study. All participants completed four computerized, non-linguistic category-learning tasks. We probed learning ability under two methods of instruction: feedback-based (FB) and paired-associate (PA). We also examined the impact of task complexity on learning ability, comparing two stimulus conditions: typical (Typ) and atypical (Atyp). Performance was compared between groups and across conditions. Results Results demonstrated that healthy controls were able to successfully learn categories under all conditions. For our patients with aphasia, two patterns of performance arose. One subgroup of patients was able to maintain learning across task manipulations and conditions. The other subgroup of patients demonstrated a sensitivity to task complexity, learning successfully only in the typical training conditions. Conclusions Results support the hypothesis that impairments of general learning are present in aphasia. Some patients demonstrated the ability to extract category information under complex training conditions, while others learned only under conditions that were simplified and emphasized salient category features. Overall, the typical training condition facilitated learning for all participants. Findings have implications for therapy, which are discussed. PMID:23695914

The helpfulness of category labels in semi-supervised learning depends on category structure.

PubMed

Vong, Wai Keen; Navarro, Daniel J; Perfors, Amy

2016-02-01

The study of semi-supervised category learning has generally focused on how additional unlabeled information with given labeled information might benefit category learning. The literature is also somewhat contradictory, sometimes appearing to show a benefit to unlabeled information and sometimes not. In this paper, we frame the problem differently, focusing on when labels might be helpful to a learner who has access to lots of unlabeled information. Using an unconstrained free-sorting categorization experiment, we show that labels are useful to participants only when the category structure is ambiguous and that people's responses are driven by the specific set of labels they see. We present an extension of Anderson's Rational Model of Categorization that captures this effect.

The development of the learning video for the flipped classroom model on student of open university on human skeletal system and muscles

NASA Astrophysics Data System (ADS)

Andrini, V. S.

2018-05-01

The objectives of the research are to develop the learning video for the flipped classroom model for Open University’s student and to know the effectiveness of the video. The development of the video used Research and Development ADDIE design (Analyses, Design, Development, Implementation, Evaluation). The sampling used purposive sampling was 28 students in Open University of Nganjuk. The techniques of data collection were the observation data to know the problems of the students, and learning facilities, the test (pre-test and post-test) to know a knowledge aspect, a questionnaire to know advisability of video learning, a structured interview to confirm their answer. The result of the expert of matter and media showed that the average product score was 3.75 of 4 or very good, the small-scale test showed that the average score was 3.60 of 4 and the large-scale test showed that the average score was 3.80 of 4, it had a very good category. The t-test with paired sample test showed that sig. (2-tailed) < 0.05. The N-gain score of pre and post test was 0.55, it had the medium category. It can be concluded that the development of the learning video for flipped classroom was effective to be implemented.

Similarity-Dissimilarity Competition in Disjunctive Classification Tasks

PubMed Central

Mathy, Fabien; Haladjian, Harry H.; Laurent, Eric; Goldstone, Robert L.

2013-01-01

Typical disjunctive artificial classification tasks require participants to sort stimuli according to rules such as “x likes cars only when black and coupe OR white and SUV.” For categories like this, increasing the salience of the diagnostic dimensions has two simultaneous effects: increasing the distance between members of the same category and increasing the distance between members of opposite categories. Potentially, these two effects respectively hinder and facilitate classification learning, leading to competing predictions for learning. Increasing saliency may lead to members of the same category to be considered less similar, while the members of separate categories might be considered more dissimilar. This implies a similarity-dissimilarity competition between two basic classification processes. When focusing on sub-category similarity, one would expect more difficult classification when members of the same category become less similar (disregarding the increase of between-category dissimilarity); however, the between-category dissimilarity increase predicts a less difficult classification. Our categorization study suggests that participants rely more on using dissimilarities between opposite categories than finding similarities between sub-categories. We connect our results to rule- and exemplar-based classification models. The pattern of influences of within- and between-category similarities are challenging for simple single-process categorization systems based on rules or exemplars. Instead, our results suggest that either these processes should be integrated in a hybrid model, or that category learning operates by forming clusters within each category. PMID:23403979

Developing physics learning media using 3D cartoon

NASA Astrophysics Data System (ADS)

Wati, M.; Hartini, S.; Hikmah, N.; Mahtari, S.

2018-03-01

This study focuses on developing physics learning media using 3D cartoon on the static fluid topic. The purpose of this study is to describe: (1) the validity of the learning media, (2) the practicality of the learning media, and (3) the effectiveness of the learning media. This study is a research and development using ADDIE model. The subject of the implementation of media used class XI Science of SMAN 1 Pulau Laut Timur. The data were obtained from the validation sheet of the learning media, questionnaire, and the test of learning outcomes. The results showed that: (1) the validity of the media category is valid, (2) the practicality of the media category is practice, and (3) the effectiveness of the media category is effective. It is concluded that the learning using 3D cartoon on the static fluid topic is eligible to use in learning.

Re-Evaluating Dissociations between Implicit and Explicit Category Learning: An Event-Related fMRI Study

ERIC Educational Resources Information Center

Gureckis, Todd M.; James, Thomas W.; Nosofsky, Robert M.

2011-01-01

Recent fMRI studies have found that distinct neural systems may mediate perceptual category learning under implicit and explicit learning conditions. In these previous studies, however, different stimulus-encoding processes may have been associated with implicit versus explicit learning. The present design was aimed at decoupling the influence of…

More Is Generally Better: Higher Working Memory Capacity Does Not Impair Perceptual Category Learning

ERIC Educational Resources Information Center

Kalish, Michael L.; Newell, Ben R.; Dunn, John C.

2017-01-01

It is sometimes supposed that category learning involves competing explicit and procedural systems, with only the former reliant on working memory capacity (WMC). In 2 experiments participants were trained for 3 blocks on both filtering (often said to be learned explicitly) and condensation (often said to be learned procedurally) category…

The Sequence of Study Changes What Information Is Attended to, Encoded, and Remembered during Category Learning

ERIC Educational Resources Information Center

Carvalho, Paulo F.; Goldstone, Robert L.

2017-01-01

The sequence of study influences how we learn. Previous research has identified different sequences as potentially beneficial for learning in different contexts and with different materials. Here we investigate the mechanisms involved in inductive category learning that give rise to these sequencing effects. Across 3 experiments we show evidence…

Comparison Promotes Learning and Transfer of Relational Categories

ERIC Educational Resources Information Center

Kurtz, Kenneth J.; Boukrina, Olga; Gentner, Dedre

2013-01-01

We investigated the effect of co-presenting training items during supervised classification learning of novel relational categories. Strong evidence exists that comparison induces a structural alignment process that renders common relational structure more salient. We hypothesized that comparisons between exemplars would facilitate learning and…

Category Representation for Classification and Feature Inference

ERIC Educational Resources Information Center

Johansen, Mark K.; Kruschke, John K.

2005-01-01

This research's purpose was to contrast the representations resulting from learning of the same categories by either classifying instances or inferring instance features. Prior inference learning research, particularly T. Yamauchi and A. B. Markman (1998), has suggested that feature inference learning fosters prototype representation, whereas…

Categorical vowel perception enhances the effectiveness and generalization of auditory feedback in human-machine-interfaces.

PubMed

Larson, Eric; Terry, Howard P; Canevari, Margaux M; Stepp, Cara E

2013-01-01

Human-machine interface (HMI) designs offer the possibility of improving quality of life for patient populations as well as augmenting normal user function. Despite pragmatic benefits, utilizing auditory feedback for HMI control remains underutilized, in part due to observed limitations in effectiveness. The goal of this study was to determine the extent to which categorical speech perception could be used to improve an auditory HMI. Using surface electromyography, 24 healthy speakers of American English participated in 4 sessions to learn to control an HMI using auditory feedback (provided via vowel synthesis). Participants trained on 3 targets in sessions 1-3 and were tested on 3 novel targets in session 4. An "established categories with text cues" group of eight participants were trained and tested on auditory targets corresponding to standard American English vowels using auditory and text target cues. An "established categories without text cues" group of eight participants were trained and tested on the same targets using only auditory cuing of target vowel identity. A "new categories" group of eight participants were trained and tested on targets that corresponded to vowel-like sounds not part of American English. Analyses of user performance revealed significant effects of session and group (established categories groups and the new categories group), and a trend for an interaction between session and group. Results suggest that auditory feedback can be effectively used for HMI operation when paired with established categorical (native vowel) targets with an unambiguous cue.

Identifying Strategy Use in Category Learning Tasks: A Case for More Diagnostic Data and Models

ERIC Educational Resources Information Center

Donkin, Chris; Newell, Ben R.; Kalish, Mike; Dunn, John C.; Nosofsky, Robert M.

2015-01-01

The strength of conclusions about the adoption of different categorization strategies--and their implications for theories about the cognitive and neural bases of category learning--depend heavily on the techniques for identifying strategy use. We examine performance in an often-used "information-integration" category structure and…

Perceptual advantage for category-relevant perceptual dimensions: the case of shape and motion.

PubMed

Folstein, Jonathan R; Palmeri, Thomas J; Gauthier, Isabel

2014-01-01

Category learning facilitates perception along relevant stimulus dimensions, even when tested in a discrimination task that does not require categorization. While this general phenomenon has been demonstrated previously, perceptual facilitation along dimensions has been documented by measuring different specific phenomena in different studies using different kinds of objects. Across several object domains, there is support for acquired distinctiveness, the stretching of a perceptual dimension relevant to learned categories. Studies using faces and studies using simple separable visual dimensions have also found evidence of acquired equivalence, the shrinking of a perceptual dimension irrelevant to learned categories, and categorical perception, the local stretching across the category boundary. These later two effects are rarely observed with complex non-face objects. Failures to find these effects with complex non-face objects may have been because the dimensions tested previously were perceptually integrated. Here we tested effects of category learning with non-face objects categorized along dimensions that have been found to be processed by different areas of the brain, shape and motion. While we replicated acquired distinctiveness, we found no evidence for acquired equivalence or categorical perception.

Deep Learning and Developmental Learning: Emergence of Fine-to-Coarse Conceptual Categories at Layers of Deep Belief Network.

PubMed

Sadeghi, Zahra

2016-09-01

In this paper, I investigate conceptual categories derived from developmental processing in a deep neural network. The similarity matrices of deep representation at each layer of neural network are computed and compared with their raw representation. While the clusters generated by raw representation stand at the basic level of abstraction, conceptual categories obtained from deep representation shows a bottom-up transition procedure. Results demonstrate a developmental course of learning from specific to general level of abstraction through learned layers of representations in a deep belief network. © The Author(s) 2016.

Continuous executive function disruption interferes with application of an information integration categorization strategy.

PubMed

Miles, Sarah J; Matsuki, Kazunaga; Minda, John Paul

2014-07-01

Category learning is often characterized as being supported by two separate learning systems. A verbal system learns rule-defined (RD) categories that can be described using a verbal rule and relies on executive functions (EFs) to learn via hypothesis testing. A nonverbal system learns non-rule-defined (NRD) categories that cannot be described by a verbal rule and uses automatic, procedural learning. The verbal system is dominant in that adults tend to use it during initial learning but may switch to the nonverbal system when the verbal system is unsuccessful. The nonverbal system has traditionally been thought to operate independently of EFs, but recent studies suggest that EFs may play a role in the nonverbal system-specifically, to facilitate the transition away from the verbal system. Accordingly, continuously interfering with EFs during the categorization process, so that EFs are never fully available to facilitate the transition, may be more detrimental to the nonverbal system than is temporary EF interference. Participants learned an NRD or an RD category while EFs were untaxed, taxed temporarily, or taxed continuously. When EFs were continuously taxed during NRD categorization, participants were less likely to use a nonverbal categorization strategy than when EFs were temporarily taxed, suggesting that when EFs were unavailable, the transition to the nonverbal system was hindered. For the verbal system, temporary and continuous interference had similar effects on categorization performance and on strategy use, illustrating that EFs play an important but different role in each of the category-learning systems.

Distributional learning aids linguistic category formation in school-age children.

PubMed

Hall, Jessica; Owen VAN Horne, Amanda; Farmer, Thomas

2018-05-01

The goal of this study was to determine if typically developing children could form grammatical categories from distributional information alone. Twenty-seven children aged six to nine listened to an artificial grammar which contained strategic gaps in its distribution. At test, we compared how children rated novel sentences that fit the grammar to sentences that were ungrammatical. Sentences could be distinguished only through the formation of categories of words with shared distributional properties. Children's ratings revealed that they could discriminate grammatical and ungrammatical sentences. These data lend support to the hypothesis that distributional learning is a potential mechanism for learning grammatical categories in a first language.

When Does Fading Enhance Perceptual Category Learning?

ERIC Educational Resources Information Center

Pashler, Harold; Mozer, Michael C.

2013-01-01

Training that uses exaggerated versions of a stimulus discrimination (fading) has sometimes been found to enhance category learning, mostly in studies involving animals and impaired populations. However, little is known about whether and when fading facilitates learning for typical individuals. This issue was explored in 7 experiments. In…

A Preliminary Analysis of the Theoretical Parameters of Organizaational Learning.

DTIC Science & Technology

1995-09-01

PARAMETERS OF ORGANIZATIONAL LEARNING THESIS Presented to the Faculty of the Graduate School of Logistics and Acquisition Management of the Air...Organizational Learning Parameters in the Knowledge Acquisition Category 2~™ 2-3. Organizational Learning Parameters in the Information Distribution Category...Learning Refined Scale 4-94 4-145. Composition of Refined Scale 4 Knowledge Flow 4-95 4-146. Cronbach’s Alpha Statistics for the Complete Knowledge Flow

Pattern Analyses Reveal Separate Experience-Based Fear Memories in the Human Right Amygdala.

PubMed

Braem, Senne; De Houwer, Jan; Demanet, Jelle; Yuen, Kenneth S L; Kalisch, Raffael; Brass, Marcel

2017-08-23

Learning fear via the experience of contingencies between a conditioned stimulus (CS) and an aversive unconditioned stimulus (US) is often assumed to be fundamentally different from learning fear via instructions. An open question is whether fear-related brain areas respond differently to experienced CS-US contingencies than to merely instructed CS-US contingencies. Here, we contrasted two experimental conditions where subjects were instructed to expect the same CS-US contingencies while only one condition was characterized by prior experience with the CS-US contingency. Using multivoxel pattern analysis of fMRI data, we found CS-related neural activation patterns in the right amygdala (but not in other fear-related regions) that dissociated between whether a CS-US contingency had been instructed and experienced versus merely instructed. A second experiment further corroborated this finding by showing a category-independent neural response to instructed and experienced, but not merely instructed, CS presentations in the human right amygdala. Together, these findings are in line with previous studies showing that verbal fear instructions have a strong impact on both brain and behavior. However, even in the face of fear instructions, the human right amygdala still shows a separable neural pattern response to experience-based fear contingencies. SIGNIFICANCE STATEMENT In our study, we addressed a fundamental problem of the science of human fear learning and memory, namely whether fear learning via experience in humans relies on a neural pathway that can be separated from fear learning via verbal information. Using two new procedures and recent advances in the analysis of brain imaging data, we localized purely experience-based fear processing and memory in the right amygdala, thereby making a direct link between human and animal research. Copyright © 2017 the authors 0270-6474/17/378116-15$15.00/0.

The Role of Age and Executive Function in Auditory Category Learning

PubMed Central

Reetzke, Rachel; Maddox, W. Todd; Chandrasekaran, Bharath

2015-01-01

Auditory categorization is a natural and adaptive process that allows for the organization of high-dimensional, continuous acoustic information into discrete representations. Studies in the visual domain have identified a rule-based learning system that learns and reasons via a hypothesis-testing process that requires working memory and executive attention. The rule-based learning system in vision shows a protracted development, reflecting the influence of maturing prefrontal function on visual categorization. The aim of the current study is two-fold: (a) to examine the developmental trajectory of rule-based auditory category learning from childhood through adolescence, into early adulthood; and (b) to examine the extent to which individual differences in rule-based category learning relate to individual differences in executive function. Sixty participants with normal hearing, 20 children (age range, 7–12), 21 adolescents (age range, 13–19), and 19 young adults (age range, 20–23), learned to categorize novel dynamic ripple sounds using trial-by-trial feedback. The spectrotemporally modulated ripple sounds are considered the auditory equivalent of the well-studied Gabor patches in the visual domain. Results revealed that auditory categorization accuracy improved with age, with young adults outperforming children and adolescents. Computational modeling analyses indicated that the use of the task-optimal strategy (i.e. a conjunctive rule-based learning strategy) improved with age. Notably, individual differences in executive flexibility significantly predicted auditory category learning success. The current findings demonstrate a protracted development of rule-based auditory categorization. The results further suggest that executive flexibility coupled with perceptual processes play important roles in successful rule-based auditory category learning. PMID:26491987

Hippocampal BOLD response during category learning predicts subsequent performance on transfer generalization.

PubMed

Fera, Francesco; Passamonti, Luca; Herzallah, Mohammad M; Myers, Catherine E; Veltri, Pierangelo; Morganti, Giuseppina; Quattrone, Aldo; Gluck, Mark A

2014-07-01

To test a prediction of our previous computational model of cortico-hippocampal interaction (Gluck and Myers [1993, 2001]) for characterizing individual differences in category learning, we studied young healthy subjects using an fMRI-adapted category-learning task that has two phases, an initial phase in which associations are learned through trial-and-error feedback followed by a generalization phase in which previously learned rules can be applied to novel associations (Myers et al. [2003]). As expected by our model, we found a negative correlation between learning-related hippocampal responses and accuracy during transfer, demonstrating that hippocampal adaptation during learning is associated with better behavioral scores during transfer generalization. In addition, we found an inverse relationship between Blood Oxygenation Level Dependent (BOLD) activity in the striatum and that in the hippocampal formation and the orbitofrontal cortex during the initial learning phase. Conversely, activity in the dorsolateral prefrontal cortex, orbitofrontal cortex and parietal lobes dominated over that of the hippocampal formation during the generalization phase. These findings provide evidence in support of theories of the neural substrates of category learning which argue that the hippocampal region plays a critical role during learning for appropriately encoding and representing newly learned information so that that this learning can be successfully applied and generalized to subsequent novel task demands. Copyright © 2013 Wiley Periodicals, Inc.

Test of a potential link between analytic and nonanalytic category learning and automatic, effortful processing.

PubMed

Tracy, J I; Pinsk, M; Helverson, J; Urban, G; Dietz, T; Smith, D J

2001-08-01

The link between automatic and effortful processing and nonanalytic and analytic category learning was evaluated in a sample of 29 college undergraduates using declarative memory, semantic category search, and pseudoword categorization tasks. Automatic and effortful processing measures were hypothesized to be associated with nonanalytic and analytic categorization, respectively. Results suggested that contrary to prediction strong criterion-attribute (analytic) responding on the pseudoword categorization task was associated with strong automatic, implicit memory encoding of frequency-of-occurrence information. Data are discussed in terms of the possibility that criterion-attribute category knowledge, once established, may be expressed with few attentional resources. The data indicate that attention resource requirements, even for the same stimuli and task, vary depending on the category rule system utilized. Also, the automaticity emerging from familiarity with analytic category exemplars is very different from the automaticity arising from extensive practice on a semantic category search task. The data do not support any simple mapping of analytic and nonanalytic forms of category learning onto the automatic and effortful processing dichotomy and challenge simple models of brain asymmetries for such procedures. Copyright 2001 Academic Press.

Environmental Approaches to Prehistory/Archaeology. Activities Designed to Supplement a Course in North American Prehistory/Archaeology at the Junior High or High School Level. Curriculum Series, Number 2.

ERIC Educational Resources Information Center

Carpenter, James C.; Fraser, Kathryn M.

Presented are 17 activities designed to supplement junior or senior high school studies in prehistory and archaeology. Stressed throughout the manual is the changing relationship between humans and the environment. The learning experiences fall into three categories: (1) how we study prehistoric cultures, (2) how prehistoric peoples lived, and (3)…

The Effect of Feedback Delay and Feedback Type on Perceptual Category Learning: The Limits of Multiple Systems

ERIC Educational Resources Information Center

Dunn, John C.; Newell, Ben R.; Kalish, Michael L.

2012-01-01

Evidence that learning rule-based (RB) and information-integration (II) category structures can be dissociated across different experimental variables has been used to support the view that such learning is supported by multiple learning systems. Across 4 experiments, we examined the effects of 2 variables, the delay between response and feedback…

ERP evidence for on-line syntactic computations in 2-year-olds.

PubMed

Brusini, Perrine; Dehaene-Lambertz, Ghislaine; Dutat, Michel; Goffinet, François; Christophe, Anne

2016-06-01

Syntax allows human beings to build an infinite number of sentences from a finite number of words. How this unique, productive power of human language unfolds over the course of language development is still hotly debated. When they listen to sentences comprising newly-learned words, do children generalize from their knowledge of the legal combinations of word categories or do they instead rely on strings of words stored in memory to detect syntactic errors? Using novel words taught in the lab, we recorded Evoked Response Potentials (ERPs) in two-year-olds and adults listening to grammatical and ungrammatical sentences containing syntactic contexts that had not been used during training. In toddlers, the ungrammatical use of words, even when they have been just learned, induced an early left anterior negativity (surfacing 100-400ms after target word onset) followed by a late posterior positivity (surfacing 700-900ms after target word onset) that was not observed in grammatical sentences. This late effect was remarkably similar to the P600 displayed by adults, suggesting that toddlers and adults perform similar syntactic computations. Our results thus show that toddlers build on-line expectations regarding the syntactic category of upcoming words in a sentence. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Prefrontal Contributions to Rule-Based and Information-Integration Category Learning

ERIC Educational Resources Information Center

Schnyer, David M.; Maddox, W. Todd; Ell, Shawn; Davis, Sarah; Pacheco, Jenni; Verfaellie, Mieke

2009-01-01

Previous research revealed that the basal ganglia play a critical role in category learning [Ell, S. W., Marchant, N. L., & Ivry, R. B. (2006). "Focal putamen lesions impair learning in rule-based, but not information-integration categorization tasks." "Neuropsychologia", 44(10), 1737-1751; Maddox, W. T. & Filoteo, J.…

Learning Problems and Classroom Instruction.

ERIC Educational Resources Information Center

Adelman, Howard S.

Defined are categories of learning disabilities (LD) that can be remediated in regular public school classes, and offered are remedial approaches. Stressed in four studies is the heterogeneity of LD problems. Suggested is grouping LD children into three categories: no disorder (problem is from the learning environment); minor disorder (problem is…

Statistical Learning of Phonetic Categories: Insights from a Computational Approach

ERIC Educational Resources Information Center

McMurray, Bob; Aslin, Richard N.; Toscano, Joseph C.

2009-01-01

Recent evidence (Maye, Werker & Gerken, 2002) suggests that statistical learning may be an important mechanism for the acquisition of phonetic categories in the infant's native language. We examined the sufficiency of this hypothesis and its implications for development by implementing a statistical learning mechanism in a computational model…

Learning foreign sounds in an alien world: videogame training improves non-native speech categorization.

PubMed

Lim, Sung-joo; Holt, Lori L

2011-01-01

Although speech categories are defined by multiple acoustic dimensions, some are perceptually weighted more than others and there are residual effects of native-language weightings in non-native speech perception. Recent research on nonlinguistic sound category learning suggests that the distribution characteristics of experienced sounds influence perceptual cue weights: Increasing variability across a dimension leads listeners to rely upon it less in subsequent category learning (Holt & Lotto, 2006). The present experiment investigated the implications of this among native Japanese learning English /r/-/l/ categories. Training was accomplished using a videogame paradigm that emphasizes associations among sound categories, visual information, and players' responses to videogame characters rather than overt categorization or explicit feedback. Subjects who played the game for 2.5h across 5 days exhibited improvements in /r/-/l/ perception on par with 2-4 weeks of explicit categorization training in previous research and exhibited a shift toward more native-like perceptual cue weights. Copyright © 2011 Cognitive Science Society, Inc.

Learning foreign sounds in an alien world: Videogame training improves non-native speech categorization

PubMed Central

Lim, Sung-joo; Holt, Lori L.

2011-01-01

Although speech categories are defined by multiple acoustic dimensions, some are perceptually-weighted more than others and there are residual effects of native-language weightings in non-native speech perception. Recent research on nonlinguistic sound category learning suggests that the distribution characteristics of experienced sounds influence perceptual cue weights: increasing variability across a dimension leads listeners to rely upon it less in subsequent category learning (Holt & Lotto, 2006). The present experiment investigated the implications of this among native Japanese learning English /r/-/l/ categories. Training was accomplished using a videogame paradigm that emphasizes associations among sound categories, visual information and players’ responses to videogame characters rather than overt categorization or explicit feedback. Subjects who played the game for 2.5 hours across 5 days exhibited improvements in /r/-/l/ perception on par with 2–4 weeks of explicit categorization training in previous research and exhibited a shift toward more native-like perceptual cue weights. PMID:21827533

Compensatory processing during rule-based category learning in older adults.

PubMed

Bharani, Krishna L; Paller, Ken A; Reber, Paul J; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G

2016-01-01

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex.

Compensatory Processing During Rule-Based Category Learning in Older Adults

PubMed Central

Bharani, Krishna L.; Paller, Ken A.; Reber, Paul J.; Weintraub, Sandra; Yanar, Jorge; Morrison, Robert G.

2016-01-01

Healthy older adults typically perform worse than younger adults at rule-based category learning, but better than patients with Alzheimer's or Parkinson's disease. To further investigate aging's effect on rule-based category learning, we monitored event-related potentials (ERPs) while younger and neuropsychologically typical older adults performed a visual category-learning task with a rule-based category structure and trial-by-trial feedback. Using these procedures, we previously identified ERPs sensitive to categorization strategy and accuracy in young participants. In addition, previous studies have demonstrated the importance of neural processing in the prefrontal cortex and the medial temporal lobe for this task. In this study, older adults showed lower accuracy and longer response times than younger adults, but there were two distinct subgroups of older adults. One subgroup showed near-chance performance throughout the procedure, never categorizing accurately. The other subgroup reached asymptotic accuracy that was equivalent to that in younger adults, although they categorized more slowly. These two subgroups were further distinguished via ERPs. Consistent with the compensation theory of cognitive aging, older adults who successfully learned showed larger frontal ERPs when compared with younger adults. Recruitment of prefrontal resources may have improved performance while slowing response times. Additionally, correlations of feedback-locked P300 amplitudes with category-learning accuracy differentiated successful younger and older adults. Overall, the results suggest that the ability to adapt one's behavior in response to feedback during learning varies across older individuals, and that the failure of some to adapt their behavior may reflect inadequate engagement of prefrontal cortex. PMID:26422522

Neural Changes Associated with Nonspeech Auditory Category Learning Parallel Those of Speech Category Acquisition

ERIC Educational Resources Information Center

Liu, Ran; Holt, Lori L.

2011-01-01

Native language experience plays a critical role in shaping speech categorization, but the exact mechanisms by which it does so are not well understood. Investigating category learning of nonspeech sounds with which listeners have no prior experience allows their experience to be systematically controlled in a way that is impossible to achieve by…

The Advantage of Mixing Examples in Inductive Learning: A Comparison of Three Hypotheses

ERIC Educational Resources Information Center

Guzman-Munoz, Francisco Javier

2017-01-01

Mixing examples of different categories (interleaving) has been shown to promote inductive learning as compared with presenting examples of the same category together (massing). In three studies, we tested whether the advantage of interleaving is exclusively due to the mixing of examples from different categories or to the temporal gap introduced…

The cognitive capabilities of farm animals: categorisation learning in dwarf goats (Capra hircus).

PubMed

Meyer, Susann; Nürnberg, Gerd; Puppe, Birger; Langbein, Jan

2012-07-01

The ability to establish categories enables organisms to classify stimuli, objects and events by assessing perceptual, associative or rational similarities and provides the basis for higher cognitive processing. The cognitive capabilities of farm animals are receiving increasing attention in applied ethology, a development driven primarily by scientifically based efforts to improve animal welfare. The present study investigated the learning of perceptual categories in Nigerian dwarf goats (Capra hircus) by using an automated learning device installed in the animals' pen. Thirteen group-housed goats were trained in a closed-economy approach to discriminate artificial two-dimensional symbols presented in a four-choice design. The symbols belonged to two categories: category I, black symbols with an open centre (rewarded) and category II, the same symbols but filled black (unrewarded). One symbol from category I and three different symbols from category II were used to define a discrimination problem. After the training of eight problems, the animals were presented with a transfer series containing the training problems interspersed with completely new problems made from new symbols belonging to the same categories. The results clearly demonstrate that dwarf goats are able to form categories based on similarities in the visual appearance of artificial symbols and to generalise across new symbols. However, the goats had difficulties in discriminating specific symbols. It is probable that perceptual problems caused these difficulties. Nevertheless, the present study suggests that goats housed under farming conditions have well-developed cognitive abilities, including learning of open-ended categories. This result could prove beneficial by facilitating animals' adaptation to housing environments that favour their cognitive capabilities.

Generalization of cross-modal stimulus equivalence classes: operant processes as components in human category formation.

PubMed Central

Lane, S D; Clow, J K; Innis, A; Critchfield, T S

1998-01-01

This study employed a stimulus-class rating procedure to explore whether stimulus equivalence and stimulus generalization can combine to promote the formation of open-ended categories incorporating cross-modal stimuli. A pretest of simple auditory discrimination indicated that subjects (college students) could discriminate among a range of tones used in the main study. Before beginning the main study, 10 subjects learned to use a rating procedure for categorizing sets of stimuli as class consistent or class inconsistent. After completing conditional discrimination training with new stimuli (shapes and tones), the subjects demonstrated the formation of cross-modal equivalence classes. Subsequently, the class-inclusion rating procedure was reinstituted, this time with cross-modal sets of stimuli drawn from the equivalence classes. On some occasions, the tones of the equivalence classes were replaced by novel tones. The probability that these novel sets would be rated as class consistent was generally a function of the auditory distance between the novel tone and the tone that was explicitly included in the equivalence class. These data extend prior work on generalization of equivalence classes, and support the role of operant processes in human category formation. PMID:9821680

Development of a standardized battery of performance tests for the assessment of noise stress effects

NASA Technical Reports Server (NTRS)

Theologus, G. C.; Wheaton, G. R.; Mirabella, A.; Brahlek, R. E.

1973-01-01

A set of 36 relatively independent categories of human performance were identified. These categories encompass human performance in the cognitive, perceptual, and psychomotor areas, and include diagnostic measures and sensitive performance metrics. Then a prototype standardized test battery was constructed, and research was conducted to obtain information on the sensitivity of the tests to stress, the sensitivity of selected categories of performance degradation, the time course of stress effects on each of the selected tests, and the learning curves associated with each test. A research project utilizing a three factor partially repeated analysis of covariance design was conducted in which 60 male subjects were exposed to variations in noise level and quality during performance testing. Effects of randomly intermittent noise on performance of the reaction time tests were observed, but most of the other performance tests showed consistent stability. The results of 14 analyses of covariance of the data taken from the performance of the 60 subjects on the prototype standardized test battery provided information which will enable the final development and test of a standardized test battery and the associated development of differential sensitivity metrics and diagnostic classificatory system.

Using Active Learning to Identify Health Information Technology Related Patient Safety Events.

PubMed

Fong, Allan; Howe, Jessica L; Adams, Katharine T; Ratwani, Raj M

2017-01-18

The widespread adoption of health information technology (HIT) has led to new patient safety hazards that are often difficult to identify. Patient safety event reports, which are self-reported descriptions of safety hazards, provide one view of potential HIT-related safety events. However, identifying HIT-related reports can be challenging as they are often categorized under other more predominate clinical categories. This challenge of identifying HIT-related reports is exacerbated by the increasing number and complexity of reports which pose challenges to human annotators that must manually review reports. In this paper, we apply active learning techniques to support classification of patient safety event reports as HIT-related. We evaluated different strategies and demonstrated a 30% increase in average precision of a confirmatory sampling strategy over a baseline no active learning approach after 10 learning iterations.

Incidental category learning and cognitive load in a multisensory environment across childhood.

PubMed

Broadbent, H J; Osborne, T; Rea, M; Peng, A; Mareschal, D; Kirkham, N Z

2018-06-01

Multisensory information has been shown to facilitate learning (Bahrick & Lickliter, 2000; Broadbent, White, Mareschal, & Kirkham, 2017; Jordan & Baker, 2011; Shams & Seitz, 2008). However, although research has examined the modulating effect of unisensory and multisensory distractors on multisensory processing, the extent to which a concurrent unisensory or multisensory cognitive load task would interfere with or support multisensory learning remains unclear. This study examined the role of concurrent task modality on incidental category learning in 6- to 10-year-olds. Participants were engaged in a multisensory learning task while also performing either a unisensory (visual or auditory only) or multisensory (audiovisual) concurrent task (CT). We found that engaging in an auditory CT led to poorer performance on incidental category learning compared with an audiovisual or visual CT, across groups. In 6-year-olds, category test performance was at chance in the auditory-only CT condition, suggesting auditory concurrent tasks may interfere with learning in younger children, but the addition of visual information may serve to focus attention. These findings provide novel insight into the use of multisensory concurrent information on incidental learning. Implications for the deployment of multisensory learning tasks within education across development and developmental changes in modality dominance and ability to switch flexibly across modalities are discussed. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Brain connections of words, perceptions and actions: A neurobiological model of spatio-temporal semantic activation in the human cortex.

PubMed

Tomasello, Rosario; Garagnani, Max; Wennekers, Thomas; Pulvermüller, Friedemann

2017-04-01

Neuroimaging and patient studies show that different areas of cortex respectively specialize for general and selective, or category-specific, semantic processing. Why are there both semantic hubs and category-specificity, and how come that they emerge in different cortical regions? Can the activation time-course of these areas be predicted and explained by brain-like network models? In this present work, we extend a neurocomputational model of human cortical function to simulate the time-course of cortical processes of understanding meaningful concrete words. The model implements frontal and temporal cortical areas for language, perception, and action along with their connectivity. It uses Hebbian learning to semantically ground words in aspects of their referential object- and action-related meaning. Compared with earlier proposals, the present model incorporates additional neuroanatomical links supported by connectivity studies and downscaled synaptic weights in order to control for functional between-area differences purely due to the number of in- or output links of an area. We show that learning of semantic relationships between words and the objects and actions these symbols are used to speak about, leads to the formation of distributed circuits, which all include neuronal material in connector hub areas bridging between sensory and motor cortical systems. Therefore, these connector hub areas acquire a role as semantic hubs. By differentially reaching into motor or visual areas, the cortical distributions of the emergent 'semantic circuits' reflect aspects of the represented symbols' meaning, thus explaining category-specificity. The improved connectivity structure of our model entails a degree of category-specificity even in the 'semantic hubs' of the model. The relative time-course of activation of these areas is typically fast and near-simultaneous, with semantic hubs central to the network structure activating before modality-preferential areas carrying semantic information. Copyright © 2017 The Authors. Published by Elsevier Ltd.. All rights reserved.

The effect of category learning on attentional modulation of visual cortex.

PubMed

Folstein, Jonathan R; Fuller, Kelly; Howard, Dorothy; DePatie, Thomas

2017-09-01

Learning about visual object categories causes changes in the way we perceive those objects. One likely mechanism by which this occurs is the application of attention to potentially relevant objects. Here we test the hypothesis that category membership influences the allocation of attention, allowing attention to be applied not only to object features, but to entire categories. Participants briefly learned to categorize a set of novel cartoon animals after which EEG was recorded while participants distinguished between a target and non-target category. A second identical EEG session was conducted after two sessions of categorization practice. The category structure and task design allowed parametric manipulation of number of target features while holding feature frequency and category membership constant. We found no evidence that category membership influenced attentional selection: a postero-lateral negative component, labeled the selection negativity/N250, increased over time and was sensitive to number of target features, not target categories. In contrast, the right hemisphere N170 was not sensitive to target features. The P300 appeared sensitive to category in the first session, but showed a graded sensitivity to number of target features in the second session, possibly suggesting a transition from rule-based to similarity based categorization. Copyright © 2017. Published by Elsevier Ltd.

Statistical learning in songbirds: from self-tutoring to song culture.

PubMed

Fehér, Olga; Ljubičić, Iva; Suzuki, Kenta; Okanoya, Kazuo; Tchernichovski, Ofer

2017-01-05

At the onset of vocal development, both songbirds and humans produce variable vocal babbling with broadly distributed acoustic features. Over development, these vocalizations differentiate into the well-defined, categorical signals that characterize adult vocal behaviour. A broadly distributed signal is ideal for vocal exploration, that is, for matching vocal production to the statistics of the sensory input. The developmental transition to categorical signals is a gradual process during which the vocal output becomes differentiated and stable. But does it require categorical input? We trained juvenile zebra finches with playbacks of their own developing song, produced just a few moments earlier, updated continuously over development. Although the vocalizations of these self-tutored (ST) birds were initially broadly distributed, birds quickly developed categorical signals, as fast as birds that were trained with a categorical, adult song template. By contrast, siblings of those birds that received no training (isolates) developed phonological categories much more slowly and never reached the same level of category differentiation as their ST brothers. Therefore, instead of simply mirroring the statistical properties of their sensory input, songbirds actively transform it into distinct categories. We suggest that the early self-generation of phonological categories facilitates the establishment of vocal culture by making the song easier to transmit at the micro level, while promoting stability of shared vocabulary at the group level over generations.This article is part of the themed issue 'New frontiers for statistical learning in the cognitive sciences'. © 2016 The Authors.

Decoding semantic information from human electrocorticographic (ECoG) signals.

PubMed

Wang, Wei; Degenhart, Alan D; Sudre, Gustavo P; Pomerleau, Dean A; Tyler-Kabara, Elizabeth C

2011-01-01

This study examined the feasibility of decoding semantic information from human cortical activity. Four human subjects undergoing presurgical brain mapping and seizure foci localization participated in this study. Electrocorticographic (ECoG) signals were recorded while the subjects performed simple language tasks involving semantic information processing, such as a picture naming task where subjects named pictures of objects belonging to different semantic categories. Robust high-gamma band (60-120 Hz) activation was observed at the left inferior frontal gyrus (LIFG) and the posterior portion of the superior temporal gyrus (pSTG) with a temporal sequence corresponding to speech production and perception. Furthermore, Gaussian Naïve Bayes and Support Vector Machine classifiers, two commonly used machine learning algorithms for pattern recognition, were able to predict the semantic category of an object using cortical activity captured by ECoG electrodes covering the frontal, temporal and parietal cortices. These findings have implications for both basic neuroscience research and development of semantic-based brain-computer interface systems (BCI) that can help individuals with severe motor or communication disorders to express their intention and thoughts.

Schematic Influences on Category Learning and Recognition Memory

ERIC Educational Resources Information Center

Sakamoto, Yasuaki; Love, Bradley C.

2004-01-01

The results from 3 category learning experiments suggest that items are better remembered when they violate a salient knowledge structure such as a rule. The more salient the knowledge structure, the stronger the memory for deviant items. The effect of learning errors on subsequent recognition appears to be mediated through the imposed knowledge…

Comparison promotes learning and transfer of relational categories.

PubMed

Kurtz, Kenneth J; Boukrina, Olga; Gentner, Dedre

2013-07-01

We investigated the effect of co-presenting training items during supervised classification learning of novel relational categories. Strong evidence exists that comparison induces a structural alignment process that renders common relational structure more salient. We hypothesized that comparisons between exemplars would facilitate learning and transfer of categories that cohere around a common relational property. The effect of comparison was investigated using learning trials that elicited a separate classification response for each item in presentation pairs that could be drawn from the same or different categories. This methodology ensures consideration of both items and invites comparison through an implicit same-different judgment inherent in making the two responses. In a test phase measuring learning and transfer, the comparison group significantly outperformed a control group receiving an equivalent training session of single-item classification learning. Comparison-based learners also outperformed the control group on a test of far transfer, that is, the ability to accurately classify items from a novel domain that was relationally alike, but surface-dissimilar, to the training materials. Theoretical and applied implications of this comparison advantage are discussed. PsycINFO Database Record (c) 2013 APA, all rights reserved.

Mental Health Risk Adjustment with Clinical Categories and Machine Learning.

PubMed

Shrestha, Akritee; Bergquist, Savannah; Montz, Ellen; Rose, Sherri

2017-12-15

To propose nonparametric ensemble machine learning for mental health and substance use disorders (MHSUD) spending risk adjustment formulas, including considering Clinical Classification Software (CCS) categories as diagnostic covariates over the commonly used Hierarchical Condition Category (HCC) system. 2012-2013 Truven MarketScan database. We implement 21 algorithms to predict MHSUD spending, as well as a weighted combination of these algorithms called super learning. The algorithm collection included seven unique algorithms that were supplied with three differing sets of MHSUD-related predictors alongside demographic covariates: HCC, CCS, and HCC + CCS diagnostic variables. Performance was evaluated based on cross-validated R 2 and predictive ratios. Results show that super learning had the best performance based on both metrics. The top single algorithm was random forests, which improved on ordinary least squares regression by 10 percent with respect to relative efficiency. CCS categories-based formulas were generally more predictive of MHSUD spending compared to HCC-based formulas. Literature supports the potential benefit of implementing a separate MHSUD spending risk adjustment formula. Our results suggest there is an incentive to explore machine learning for MHSUD-specific risk adjustment, as well as considering CCS categories over HCCs. © Health Research and Educational Trust.

Adaptive categorization of ART networks in robot behavior learning using game-theoretic formulation.

PubMed

Fung, Wai-keung; Liu, Yun-hui

2003-12-01

Adaptive Resonance Theory (ART) networks are employed in robot behavior learning. Two of the difficulties in online robot behavior learning, namely, (1) exponential memory increases with time, (2) difficulty for operators to specify learning tasks accuracy and control learning attention before learning. In order to remedy the aforementioned difficulties, an adaptive categorization mechanism is introduced in ART networks for perceptual and action patterns categorization in this paper. A game-theoretic formulation of adaptive categorization for ART networks is proposed for vigilance parameter adaptation for category size control on the categories formed. The proposed vigilance parameter update rule can help improving categorization performance in the aspect of category number stability and solve the problem of selecting initial vigilance parameter prior to pattern categorization in traditional ART networks. Behavior learning using physical robot is conducted to demonstrate the effectiveness of the proposed adaptive categorization mechanism in ART networks.

Category Specificity in Normal Episodic Learning: Applications to Object Recognition and Category-Specific Agnosia

ERIC Educational Resources Information Center

Bukach, Cindy M.; Bub, Daniel N.; Masson, Michael E. J.; Lindsay, D. Stephen

2004-01-01

Studies of patients with category-specific agnosia (CSA) have given rise to multiple theories of object recognition, most of which assume the existence of a stable, abstract semantic memory system. We applied an episodic view of memory to questions raised by CSA in a series of studies examining normal observers' recall of newly learned attributes…

Unconscious symmetrical inferences: A role of consciousness in event integration.

PubMed

Alonso, Diego; Fuentes, Luis J; Hommel, Bernhard

2006-06-01

Explicit and implicit learning have been attributed to different learning processes that create different types of knowledge structures. Consistent with that claim, our study provides evidence that people integrate stimulus events differently when consciously aware versus unaware of the relationship between the events. In a first, acquisition phase participants sorted words into two categories (A and B), which were fully predicted by task-irrelevant primes-the labels of two other, semantically unrelated categories (C and D). In a second, test phase participants performed a lexical decision task, in which all word stimuli stemmed from the previous prime categories (C and D) and the (now nonpredictive) primes were the labels of the previous target categories (A and B). Reliable priming effects in the second phase demonstrated that bidirectional associations between the respective categories had been formed in the acquisition phase (A<-->C and B<-->D), but these effects were found only in participants that were unaware of the relationship between the categories! We suggest that unconscious, implicit learning of event relationships results in the rather unsophisticated integration (i.e., bidirectional association) of the underlying event representations, whereas explicit learning takes the meaning of the order of the events into account, and thus creates unidirectional associations.

Large-scale weakly supervised object localization via latent category learning.

PubMed

Chong Wang; Kaiqi Huang; Weiqiang Ren; Junge Zhang; Maybank, Steve

2015-04-01

Localizing objects in cluttered backgrounds is challenging under large-scale weakly supervised conditions. Due to the cluttered image condition, objects usually have large ambiguity with backgrounds. Besides, there is also a lack of effective algorithm for large-scale weakly supervised localization in cluttered backgrounds. However, backgrounds contain useful latent information, e.g., the sky in the aeroplane class. If this latent information can be learned, object-background ambiguity can be largely reduced and background can be suppressed effectively. In this paper, we propose the latent category learning (LCL) in large-scale cluttered conditions. LCL is an unsupervised learning method which requires only image-level class labels. First, we use the latent semantic analysis with semantic object representation to learn the latent categories, which represent objects, object parts or backgrounds. Second, to determine which category contains the target object, we propose a category selection strategy by evaluating each category's discrimination. Finally, we propose the online LCL for use in large-scale conditions. Evaluation on the challenging PASCAL Visual Object Class (VOC) 2007 and the large-scale imagenet large-scale visual recognition challenge 2013 detection data sets shows that the method can improve the annotation precision by 10% over previous methods. More importantly, we achieve the detection precision which outperforms previous results by a large margin and can be competitive to the supervised deformable part model 5.0 baseline on both data sets.

How do general practice registrars learn from their clinical experience? A critical incident study.

PubMed

Holmwood, C

1997-01-01

This preliminary study of RACGP registrars in the period of subsequent general practice experience examines the types of clinical experiences from which registrars learn, what they learn from the experiences and the process of learning from such experiences. A critical incident method was used on a semi structured interview process. Registrars were asked to recall clinical incidents where they had learnt something of importance. Data were sorted and categorised manually. Nine registrars were interviewed before new categories of data ceased to develop. Registrars learnt from the opportunity to follow up patients. An emotional response to the interaction was an important part of the learning process. Learning from such experiences is haphazard and unstructured. Registrars accessed human resources in response to their clinical difficulties rather than text or electronic based information sources. Registrars should be aware of their emotional responses to interactions with patients; these emotional responses often indicate important learning opportunities. Clinical interactions and resultant learning could be made less haphazard by structuring consultations with patients with specific problems. These learning opportunities should be augmented by the promotion of follow up of patients.

DeepARG: a deep learning approach for predicting antibiotic resistance genes from metagenomic data.

PubMed

Arango-Argoty, Gustavo; Garner, Emily; Pruden, Amy; Heath, Lenwood S; Vikesland, Peter; Zhang, Liqing

2018-02-01

Growing concerns about increasing rates of antibiotic resistance call for expanded and comprehensive global monitoring. Advancing methods for monitoring of environmental media (e.g., wastewater, agricultural waste, food, and water) is especially needed for identifying potential resources of novel antibiotic resistance genes (ARGs), hot spots for gene exchange, and as pathways for the spread of ARGs and human exposure. Next-generation sequencing now enables direct access and profiling of the total metagenomic DNA pool, where ARGs are typically identified or predicted based on the "best hits" of sequence searches against existing databases. Unfortunately, this approach produces a high rate of false negatives. To address such limitations, we propose here a deep learning approach, taking into account a dissimilarity matrix created using all known categories of ARGs. Two deep learning models, DeepARG-SS and DeepARG-LS, were constructed for short read sequences and full gene length sequences, respectively. Evaluation of the deep learning models over 30 antibiotic resistance categories demonstrates that the DeepARG models can predict ARGs with both high precision (> 0.97) and recall (> 0.90). The models displayed an advantage over the typical best hit approach, yielding consistently lower false negative rates and thus higher overall recall (> 0.9). As more data become available for under-represented ARG categories, the DeepARG models' performance can be expected to be further enhanced due to the nature of the underlying neural networks. Our newly developed ARG database, DeepARG-DB, encompasses ARGs predicted with a high degree of confidence and extensive manual inspection, greatly expanding current ARG repositories. The deep learning models developed here offer more accurate antimicrobial resistance annotation relative to current bioinformatics practice. DeepARG does not require strict cutoffs, which enables identification of a much broader diversity of ARGs. The DeepARG models and database are available as a command line version and as a Web service at http://bench.cs.vt.edu/deeparg .

Patient rights and medical education: clinical principles.

PubMed

Lewkonia, Ray

2011-01-01

The rights of patients may be considered within three broad categories: (i) health as a fundamental human right, (ii) equitable healthcare provision by governments and institutions, and (iii) professional relationships with individual health practitioners. Doctors should be well prepared in medical schools to understand and uphold patient rights. A simplified framework for learning and for teaching medical students about patient rights is proposed with the acronym DROIT--dignity, respect, obligation, information and trust.

Identification of Combat Unit Leader Skills and Leader-Group Interaction Processes

DTIC Science & Technology

1980-01-01

Categories of human learning. New York: Academic Press, 1964. Galton , (Sir) Francis . Hereditary genius. l-itmillan and Company, London, 1879. Garland...naissance tEam was given the mission to acquire intelligence on enemy activities in a particular area of operation (Jones, 1969). The team was to avoid...contact as the mission was strictly one of gathering intelligence . The team operating in the assigned reconnaisspnce zone came upon approximately 15 NVA

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

PubMed

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.

Interactions between statistical and semantic information in infant language development

PubMed Central

Lany, Jill; Saffran, Jenny R.

2013-01-01

Infants can use statistical regularities to form rudimentary word categories (e.g. noun, verb), and to learn the meanings common to words from those categories. Using an artificial language methodology, we probed the mechanisms by which two types of statistical cues (distributional and phonological regularities) affect word learning. Because linking distributional cues vs. phonological information to semantics make different computational demands on learners, we also tested whether their use is related to language proficiency. We found that 22-month-old infants with smaller vocabularies generalized using phonological cues; however, infants with larger vocabularies showed the opposite pattern of results, generalizing based on distributional cues. These findings suggest that both phonological and distributional cues marking word categories promote early word learning. Moreover, while correlations between these cues are important to forming word categories, we found infants’ weighting of these cues in subsequent word-learning tasks changes over the course of early language development. PMID:21884336

The structure and formation of natural categories

NASA Technical Reports Server (NTRS)

Fisher, Douglas; Langley, Pat

1990-01-01

Categorization and concept formation are critical activities of intelligence. These processes and the conceptual structures that support them raise important issues at the interface of cognitive psychology and artificial intelligence. The work presumes that advances in these and other areas are best facilitated by research methodologies that reward interdisciplinary interaction. In particular, a computational model is described of concept formation and categorization that exploits a rational analysis of basic level effects by Gluck and Corter. Their work provides a clean prescription of human category preferences that is adapted to the task of concept learning. Also, their analysis was extended to account for typicality and fan effects, and speculate on how the concept formation strategies might be extended to other facets of intelligence, such as problem solving.

Word Learning: Homophony and the Distribution of Learning Exemplars

ERIC Educational Resources Information Center

Dautriche, Isabelle; Chemla, Emmanuel; Christophe, Anne

2016-01-01

How do children infer the meaning of a word? Current accounts of word learning assume that children expect a word to map onto exactly one concept whose members form a coherent category. If this assumption was strictly true, children should infer that a homophone, such as "bat," refers to a single superordinate category that encompasses…

The Impact of Personality Traits on the Affective Category of English Language Learning Strategies

ERIC Educational Resources Information Center

Fazeli, Seyed Hossein

2011-01-01

The present study aims at discovering the impact of personality traits in the prediction use of the Affective English Language Learning Strategies (AELLSs) for learners of English as a foreign language. Four instruments were used, which were Adapted Inventory for Affective English Language Learning Strategies based on Affective category of…

The effectiveness of physics learning material based on South Kalimantan local wisdom

NASA Astrophysics Data System (ADS)

Hartini, Sri; Misbah, Helda, Dewantara, Dewi

2017-08-01

The local wisdom is essential element incorporated into learning process. However, there are no learning materials in Physics learning process which contain South Kalimantan local wisdom. Therefore, it is necessary to develop a Physics learning material based on South Kalimantan local wisdom. The objective of this research is to produce products in the form of learning material based on South Kalimantan local wisdom that is feasible and effective based on the validity, practicality, effectiveness of learning material and achievement of waja sampai kaputing (wasaka) character. This research is a research and development which refers to the ADDIE model. Data were obtained through the validation sheet of learning material, questionnaire, the test of learning outcomes and the sheet of character assesment. The research results showed that (1) the validity category of the learning material was very valid, (2) the practicality category of the learning material was very practical, (3) the effectiveness category of thelearning material was very effective, and (4) the achivement of wasaka characters was very good. In conclusion, the Physics learning materials based on South Kalimantan local wisdom are feasible and effective to be used in learning activities.

Category Learning Strategies in Younger and Older Adults: Rule Abstraction and Memorization

PubMed Central

Wahlheim, Christopher N.; McDaniel, Mark A.; Little, Jeri L.

2016-01-01

Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, both age groups had comparable frequencies of rule- and exemplar-based learners, but older adults had a higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies). Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. PMID:26950225

Online learning and control of attraction basins for the development of sensorimotor control strategies.

PubMed

de Rengervé, Antoine; Andry, Pierre; Gaussier, Philippe

2015-04-01

Imitation and learning from humans require an adequate sensorimotor controller to learn and encode behaviors. We present the Dynamic Muscle Perception-Action(DM-PerAc) model to control a multiple degrees-of-freedom (DOF) robot arm. In the original PerAc model, path-following or place-reaching behaviors correspond to the sensorimotor attractors resulting from the dynamics of learned sensorimotor associations. The DM-PerAc model, inspired by human muscles, permits one to combine impedance-like control with the capability of learning sensorimotor attraction basins. We detail a solution to learn incrementally online the DM-PerAc visuomotor controller. Postural attractors are learned by adapting the muscle activations in the model depending on movement errors. Visuomotor categories merging visual and proprioceptive signals are associated with these muscle activations. Thus, the visual and proprioceptive signals activate the motor action generating an attractor which satisfies both visual and proprioceptive constraints. This visuomotor controller can serve as a basis for imitative behaviors. In addition, the muscle activation patterns can define directions of movement instead of postural attractors. Such patterns can be used in state-action couples to generate trajectories like in the PerAc model. We discuss a possible extension of the DM-PerAc controller by adapting the Fukuyori's controller based on the Langevin's equation. This controller can serve not only to reach attractors which were not explicitly learned, but also to learn the state/action couples to define trajectories.

From brain synapses to systems for learning and memory: Object recognition, spatial navigation, timed conditioning, and movement control.

PubMed

Grossberg, Stephen

2015-09-24

This article provides an overview of neural models of synaptic learning and memory whose expression in adaptive behavior depends critically on the circuits and systems in which the synapses are embedded. It reviews Adaptive Resonance Theory, or ART, models that use excitatory matching and match-based learning to achieve fast category learning and whose learned memories are dynamically stabilized by top-down expectations, attentional focusing, and memory search. ART clarifies mechanistic relationships between consciousness, learning, expectation, attention, resonance, and synchrony. ART models are embedded in ARTSCAN architectures that unify processes of invariant object category learning, recognition, spatial and object attention, predictive remapping, and eye movement search, and that clarify how conscious object vision and recognition may fail during perceptual crowding and parietal neglect. The generality of learned categories depends upon a vigilance process that is regulated by acetylcholine via the nucleus basalis. Vigilance can get stuck at too high or too low values, thereby causing learning problems in autism and medial temporal amnesia. Similar synaptic learning laws support qualitatively different behaviors: Invariant object category learning in the inferotemporal cortex; learning of grid cells and place cells in the entorhinal and hippocampal cortices during spatial navigation; and learning of time cells in the entorhinal-hippocampal system during adaptively timed conditioning, including trace conditioning. Spatial and temporal processes through the medial and lateral entorhinal-hippocampal system seem to be carried out with homologous circuit designs. Variations of a shared laminar neocortical circuit design have modeled 3D vision, speech perception, and cognitive working memory and learning. A complementary kind of inhibitory matching and mismatch learning controls movement. This article is part of a Special Issue entitled SI: Brain and Memory. Copyright © 2014 Elsevier B.V. All rights reserved.

Higher order thinking skills: using e-portfolio in project-based learning

NASA Astrophysics Data System (ADS)

Lukitasari, M.; Handhika, J.; Murtafiah, W.

2018-03-01

The purpose of this research is to describe students' higher-order thinking skills through project-based learning using e-portfolio. The method used in this research is descriptive qualitative method. The research instruments used were test, unstructured interview, and documentation. Research subjects were students of mathematics, physics and biology education department who take the Basics Physics course. The result shows that through project-based learning using e-portfolio the students’ ability to: analyze (medium category, N-Gain 0.67), evaluate (medium category, N-Gain 0.51), and create (medium Category, N-Gain 0.44) are improved.

From Statistics to Meaning: Infants’ Acquisition of Lexical Categories

PubMed Central

Lany, Jill; Saffran, Jenny R.

2013-01-01

Infants are highly sensitive to statistical patterns in their auditory language input that mark word categories (e.g., noun and verb). However, it is unknown whether experience with these cues facilitates the acquisition of semantic properties of word categories. In a study testing this hypothesis, infants first listened to an artificial language in which word categories were reliably distinguished by statistical cues (experimental group) or in which these properties did not cue category membership (control group). Both groups were then trained on identical pairings between the words and pictures from two categories (animals and vehicles). Only infants in the experimental group learned the trained associations between specific words and pictures. Moreover, these infants generalized the pattern to include novel pairings. These results suggest that experience with statistical cues marking lexical categories sets the stage for learning the meanings of individual words and for generalizing meanings to new category members. PMID:20424058

Assessing the Neural Basis of Uncertainty in Perceptual Category Learning through Varying Levels of Distortion

ERIC Educational Resources Information Center

Daniel, Reka; Wagner, Gerd; Koch, Kathrin; Reichenbach, Jurgen R.; Sauer, Heinrich; Schlosser, Ralf G. M.

2011-01-01

The formation of new perceptual categories involves learning to extract that information from a wide range of often noisy sensory inputs, which is critical for selecting between a limited number of responses. To identify brain regions involved in visual classification learning under noisy conditions, we developed a task on the basis of the…

Word Learning and Attention Allocation Based on Word Class and Category Knowledge

ERIC Educational Resources Information Center

Hupp, Julie M.

2015-01-01

Attention allocation in word learning may vary developmentally based on the novelty of the object. It has been suggested that children differentially learn verbs based on the novelty of the agent, but adults do not because they automatically infer the object's category and thus treat it like a familiar object. The current research examined…

Differential Impact of Posterior Lesions in the Left and Right Hemisphere on Visual Category Learning and Generalization to Contrast Reversal

ERIC Educational Resources Information Center

Langguth, Berthold; Juttner, Martin; Landis, Theodor; Regard, Marianne; Rentschler, Ingo

2009-01-01

Hemispheric differences in the learning and generalization of pattern categories were explored in two experiments involving sixteen patients with unilateral posterior, cerebral lesions in the left (LH) or right (RH) hemisphere. In each experiment participants were first trained to criterion in a supervised learning paradigm to categorize a set of…

Statistical Learning Is Constrained to Less Abstract Patterns in Complex Sensory Input (but not the Least)

PubMed Central

Emberson, Lauren L.; Rubinstein, Dani

2016-01-01

The influence of statistical information on behavior (either through learning or adaptation) is quickly becoming foundational to many domains of cognitive psychology and cognitive neuroscience, from language comprehension to visual development. We investigate a central problem impacting these diverse fields: when encountering input with rich statistical information, are there any constraints on learning? This paper examines learning outcomes when adult learners are given statistical information across multiple levels of abstraction simultaneously: from abstract, semantic categories of everyday objects to individual viewpoints on these objects. After revealing statistical learning of abstract, semantic categories with scrambled individual exemplars (Exp. 1), participants viewed pictures where the categories as well as the individual objects predicted picture order (e.g., bird1—dog1, bird2—dog2). Our findings suggest that participants preferentially encode the relationships between the individual objects, even in the presence of statistical regularities linking semantic categories (Exps. 2 and 3). In a final experiment we investigate whether learners are biased towards learning object-level regularities or simply construct the most detailed model given the data (and therefore best able to predict the specifics of the upcoming stimulus) by investigating whether participants preferentially learn from the statistical regularities linking individual snapshots of objects or the relationship between the objects themselves (e.g., bird_picture1— dog_picture1, bird_picture2—dog_picture2). We find that participants fail to learn the relationships between individual snapshots, suggesting a bias towards object-level statistical regularities as opposed to merely constructing the most complete model of the input. This work moves beyond the previous existence proofs that statistical learning is possible at both very high and very low levels of abstraction (categories vs. individual objects) and suggests that, at least with the current categories and type of learner, there are biases to pick up on statistical regularities between individual objects even when robust statistical information is present at other levels of abstraction. These findings speak directly to emerging theories about how systems supporting statistical learning and prediction operate in our structure-rich environments. Moreover, the theoretical implications of the current work across multiple domains of study is already clear: statistical learning cannot be assumed to be unconstrained even if statistical learning has previously been established at a given level of abstraction when that information is presented in isolation. PMID:27139779

Structural conceptualization of learning experiences in nursing master's degree programs utilized in occupational health nursing activities.

PubMed

Aoyama, Wakako; Tatsumi, Asami

2017-01-31

In this study, concepts were constructed that express learning experiences in nursing master's degree programs utilized in occupational health nursing activities with the aim of clarifying those characteristics. This was based on the idea that elucidation of the characteristics of learning experiences in nursing master's degree programs used in occupational health nursing activities would be meaningful in providing high-quality occupational health services that respond to the needs of society. Semi-structured interviews were conducted with 10 people who fulfilled the three conditions of having completed a master's degree programs, working as an occupational health nurse after completion of the program, and not continuing on to a doctoral program. The nursing conceptualization method of Naomi Funashima was used. From the obtained data, 512 code items expressing learning experiences in master's degree programs utilized in occupational health nursing activities were identified. These items included five core categories (concepts), 34 categories, and 69 subcategories. The five concepts constructed were "Pursuit of expertise and self-evaluation," "Mutual understanding of various people that leads to human resources utilization," "Theoretical and academic learning that influences changes in activities," "Research learning that lead to activities based on scientific evidence," and "Learning that leads to high-quality activities making use of expertise." It was found that various learning experiences in the master's program to pursue the specialty of occupational health nurses in order to recognize their roles as well as the experiences to take the initiative in learning had been integrated in their activities after completion of the course and had contributed to their high-quality occupational health nursing activities. It was suggested that the learning experiences in the master's program, which had been revealed in this study, were the experiences necessary for providing high-quality occupational health nursing activities to satisfy the social needs.

The Development of Inquiry Learning Materials to Complete Content Life System Organization in Junior High School Students

NASA Astrophysics Data System (ADS)

Mayasari, F.; Raharjo; Supardi, Z. A. I.

2018-01-01

This research aims to develop the material eligibility to complete the inquiry learning of student in the material organization system of junior high school students. Learning materials developed include syllabi, lesson plans, students’ textbook, worksheets, and learning achievement test. This research is the developmental research which employ Dick and Carey model to develop learning material. The experiment was done in Junior High School 4 Lamongan regency using One Group Pretest-Posttest Design. The data collection used validation, observation, achievement test, questionnaire administration, and documentation. Data analysis techniques used quantitative and qualitative descriptive.The results showed that the developed learning material was valid and can be used. Learning activity accomplished with good category, where student activities were observed. The aspects of attitudes were observed during the learning process are honest, responsible, and confident. Student learning achievement gained an average of 81, 85 in complete category, with N-Gain 0, 75 for a high category. The activities and student response to learning was very well categorized. Based on the results, this researcher concluded that the device classified as feasible of inquiry-based learning (valid, practical, and effective) system used on the material organization of junior high school students.

Applying Machine Learning to Star Cluster Classification

NASA Astrophysics Data System (ADS)

Fedorenko, Kristina; Grasha, Kathryn; Calzetti, Daniela; Mahadevan, Sridhar

2016-01-01

Catalogs describing populations of star clusters are essential in investigating a range of important issues, from star formation to galaxy evolution. Star cluster catalogs are typically created in a two-step process: in the first step, a catalog of sources is automatically produced; in the second step, each of the extracted sources is visually inspected by 3-to-5 human classifiers and assigned a category. Classification by humans is labor-intensive and time consuming, thus it creates a bottleneck, and substantially slows down progress in star cluster research.We seek to automate the process of labeling star clusters (the second step) through applying supervised machine learning techniques. This will provide a fast, objective, and reproducible classification. Our data is HST (WFC3 and ACS) images of galaxies in the distance range of 3.5-12 Mpc, with a few thousand star clusters already classified by humans as a part of the LEGUS (Legacy ExtraGalactic UV Survey) project. The classification is based on 4 labels (Class 1 - symmetric, compact cluster; Class 2 - concentrated object with some degree of asymmetry; Class 3 - multiple peak system, diffuse; and Class 4 - spurious detection). We start by looking at basic machine learning methods such as decision trees. We then proceed to evaluate performance of more advanced techniques, focusing on convolutional neural networks and other Deep Learning methods. We analyze the results, and suggest several directions for further improvement.

Causal learning and inference as a rational process: the new synthesis.

PubMed

Holyoak, Keith J; Cheng, Patricia W

2011-01-01

Over the past decade, an active line of research within the field of human causal learning and inference has converged on a general representational framework: causal models integrated with bayesian probabilistic inference. We describe this new synthesis, which views causal learning and inference as a fundamentally rational process, and review a sample of the empirical findings that support the causal framework over associative alternatives. Causal events, like all events in the distal world as opposed to our proximal perceptual input, are inherently unobservable. A central assumption of the causal approach is that humans (and potentially nonhuman animals) have been designed in such a way as to infer the most invariant causal relations for achieving their goals based on observed events. In contrast, the associative approach assumes that learners only acquire associations among important observed events, omitting the representation of the distal relations. By incorporating bayesian inference over distributions of causal strength and causal structures, along with noisy-logical (i.e., causal) functions for integrating the influences of multiple causes on a single effect, human judgments about causal strength and structure can be predicted accurately for relatively simple causal structures. Dynamic models of learning based on the causal framework can explain patterns of acquisition observed with serial presentation of contingency data and are consistent with available neuroimaging data. The approach has been extended to a diverse range of inductive tasks, including category-based and analogical inferences.

The effect of training methodology on knowledge representation in categorization.

PubMed

Hélie, Sébastien; Shamloo, Farzin; Ell, Shawn W

2017-01-01

Category representations can be broadly classified as containing within-category information or between-category information. Although such representational differences can have a profound impact on decision-making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule-based (RB) category structures thought to promote between-category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between-category representations whereas concept training resulted in a bias toward within-category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within-category representations. With II structures, there was a bias toward within-category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within-category representations could support generalization during the test phase. These data suggest that within-category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization.

The effect of training methodology on knowledge representation in categorization

PubMed Central

Shamloo, Farzin; Ell, Shawn W.

2017-01-01

Category representations can be broadly classified as containing within–category information or between–category information. Although such representational differences can have a profound impact on decision–making, relatively little is known about the factors contributing to the development and generalizability of different types of category representations. These issues are addressed by investigating the impact of training methodology and category structures using a traditional empirical approach as well as the novel adaptation of computational modeling techniques from the machine learning literature. Experiment 1 focused on rule–based (RB) category structures thought to promote between–category representations. Participants learned two sets of two categories during training and were subsequently tested on a novel categorization problem using the training categories. Classification training resulted in a bias toward between–category representations whereas concept training resulted in a bias toward within–category representations. Experiment 2 focused on information-integration (II) category structures thought to promote within–category representations. With II structures, there was a bias toward within–category representations regardless of training methodology. Furthermore, in both experiments, computational modeling suggests that only within–category representations could support generalization during the test phase. These data suggest that within–category representations may be dominant and more robust for supporting the reconfiguration of current knowledge to support generalization. PMID:28846732

Category inference as a function of correlational structure, category discriminability, and number of available cues.

PubMed

Lancaster, Matthew E; Shelhamer, Ryan; Homa, Donald

2013-04-01

Two experiments investigated category inference when categories were composed of correlated or uncorrelated dimensions and the categories overlapped minimally or moderately. When the categories minimally overlapped, the dimensions were strongly correlated with the category label. Following a classification learning phase, subsequent transfer required the selection of either a category label or a feature when one, two, or three features were missing. Experiments 1 and 2 differed primarily in the number of learning blocks prior to transfer. In each experiment, the inference of the category label or category feature was influenced by both dimensional and category correlations, as well as their interaction. The number of cues available at test impacted performance more when the dimensional correlations were zero and category overlap was high. However, a minimal number of cues were sufficient to produce high levels of inference when the dimensions were highly correlated; additional cues had a positive but reduced impact, even when overlap was high. Subjects were generally more accurate in inferring the category label than a category feature regardless of dimensional correlation, category overlap, or number of cues available at test. Whether the category label functioned as a special feature or not was critically dependent upon these embedded correlations, with feature inference driven more strongly by dimensional correlations.

Characterising the development of the understanding of human body systems in high-school biology students - a longitudinal study

NASA Astrophysics Data System (ADS)

Snapir, Zohar; Eberbach, Catherine; Ben-Zvi-Assaraf, Orit; Hmelo-Silver, Cindy; Tripto, Jaklin

2017-10-01

Science education today has become increasingly focused on research into complex natural, social and technological systems. In this study, we examined the development of high-school biology students' systems understanding of the human body, in a three-year longitudinal study. The development of the students' system understanding was evaluated using the Components Mechanisms Phenomena (CMP) framework for conceptual representation. We coded and analysed the repertory grid personal constructs of 67 high-school biology students at 4 points throughout the study. Our data analysis builds on the assumption that systems understanding entails a perception of all the system categories, including structures within the system (its Components), specific processes and interactions at the macro and micro levels (Mechanisms), and the Phenomena that present the macro scale of processes and patterns within a system. Our findings suggest that as the learning process progressed, the systems understanding of our students became more advanced, moving forward within each of the major CMP categories. Moreover, there was an increase in the mechanism complexity presented by the students, manifested by more students describing mechanisms at the molecular level. Thus, the 'mechanism' category and the micro level are critical components that enable students to understand system-level phenomena such as homeostasis.

Decoding human mental states by whole-head EEG+fNIRS during category fluency task performance

NASA Astrophysics Data System (ADS)

Omurtag, Ahmet; Aghajani, Haleh; Onur Keles, Hasan

2017-12-01

Objective. Concurrent scalp electroencephalography (EEG) and functional near-infrared spectroscopy (fNIRS), which we refer to as EEG+fNIRS, promises greater accuracy than the individual modalities while remaining nearly as convenient as EEG. We sought to quantify the hybrid system’s ability to decode mental states and compare it with its unimodal components. Approach. We recorded from healthy volunteers taking the category fluency test and applied machine learning techniques to the data. Main results. EEG+fNIRS’s decoding accuracy was greater than that of its subsystems, partly due to the new type of neurovascular features made available by hybrid data. Significance. Availability of an accurate and practical decoding method has potential implications for medical diagnosis, brain-computer interface design, and neuroergonomics.

[Which learning methods are expected for ultrasound training? Blended learning on trial].

PubMed

Röhrig, S; Hempel, D; Stenger, T; Armbruster, W; Seibel, A; Walcher, F; Breitkreutz, R

2014-10-01

Current teaching methods in graduate and postgraduate training often include frontal presentations. Especially in ultrasound education not only knowledge but also sensomotory and visual skills need to be taught. This requires new learning methods. This study examined which types of teaching methods are preferred by participants in ultrasound training courses before, during and after the course by analyzing a blended learning concept. It also investigated how much time trainees are willing to spend on such activities. A survey was conducted at the end of a certified ultrasound training course. Participants were asked to complete a questionnaire based on a visual analogue scale (VAS) in which three categories were defined: category (1) vote for acceptance with a two thirds majority (VAS 67-100%), category (2) simple acceptance (50-67%) and category (3) rejection (< 50%). A total of 176 trainees participated in this survey. Participants preferred an e-learning program with interactive elements, short presentations (less than 20 min), incorporating interaction with the audience, hands-on sessions in small groups, an alternation between presentations and hands-on-sessions, live demonstrations and quizzes. For post-course learning, interactive and media-assisted approaches were preferred, such as e-learning, films of the presentations and the possibility to stay in contact with instructors in order to discuss the results. Participants also voted for maintaining a logbook for documentation of results. The results of this study indicate the need for interactive learning concepts and blended learning activities. Directors of ultrasound courses may consider these aspects and are encouraged to develop sustainable learning pathways.

Perceptual Learning of Intonation Contour Categories in Adults and 9- to 11-Year-Old Children: Adults Are More Narrow-Minded.

PubMed

Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A

2017-03-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: Previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour, while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: There is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. Copyright © 2016 Cognitive Science Society, Inc.

Perceptual learning of intonation contour categories in adults and 9 to 11-year-old children: Adults are more narrow-minded

PubMed Central

Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.

2015-01-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of intonation contours: previously encountered and novel exemplars are categorized together equally often, as long as distance from the prototype is controlled. However, age-related differences in categorization performance also exist. Given the same experience, adults form narrower categories than children. In addition, adults pay more attention to the end of the contour while children appear to pay equal attention to the beginning and the end. The age range we examine appears to capture the tail-end of the developmental trajectory for learning intonation contour categories: there is a continuous effect of age on category breadth within the child group, but the oldest children (older than 10;3) are adult-like. PMID:26901251

From shared contexts to syntactic categories: The role of distributional information in learning linguistic form-classes

PubMed Central

Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.

2012-01-01

A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. PMID:23089290

From shared contexts to syntactic categories: the role of distributional information in learning linguistic form-classes.

PubMed

Reeder, Patricia A; Newport, Elissa L; Aslin, Richard N

2013-02-01

A fundamental component of language acquisition involves organizing words into grammatical categories. Previous literature has suggested a number of ways in which this categorization task might be accomplished. Here we ask whether the patterning of the words in a corpus of linguistic input (distributional information) is sufficient, along with a small set of learning biases, to extract these underlying structural categories. In a series of experiments, we show that learners can acquire linguistic form-classes, generalizing from instances of the distributional contexts of individual words in the exposure set to the full range of contexts for all the words in the set. Crucially, we explore how several specific distributional variables enable learners to form a category of lexical items and generalize to novel words, yet also allow for exceptions that maintain lexical specificity. We suggest that learners are sensitive to the contexts of individual words, the overlaps among contexts across words, the non-overlap of contexts (or systematic gaps in information), and the size of the exposure set. We also ask how learners determine the category membership of a new word for which there is very sparse contextual information. We find that, when there are strong category cues and robust category learning of other words, adults readily generalize the distributional properties of the learned category to a new word that shares just one context with the other category members. However, as the distributional cues regarding the category become sparser and contain more consistent gaps, learners show more conservatism in generalizing distributional properties to the novel word. Taken together, these results show that learners are highly systematic in their use of the distributional properties of the input corpus, using them in a principled way to determine when to generalize and when to preserve lexical specificity. Copyright © 2012 Elsevier Inc. All rights reserved.

Processing advantages for consonance: A comparison between rats (Rattus norvegicus) and humans (Homo sapiens).

PubMed

Crespo-Bojorque, Paola; Toro, Juan M

2016-05-01

Consonance is a salient perceptual feature in harmonic music associated with pleasantness. Besides being deeply rooted in how we experience music, research suggests consonant intervals are more easily processed than dissonant intervals. In the present work we explore from a comparative perspective if such processing advantage extends to more complex tasks such as the detection of abstract rules. We ran experiments on rule learning over consonant and dissonant intervals with nonhuman animals and human participants. Results show differences across species regarding the extent to which they benefit from differences in consonance. Animals learn abstract rules with the same ease independently of whether they are implemented over consonant intervals (Experiment 1), dissonant intervals (Experiment 2), or over a combination of them (Experiment 3). Humans, on the contrary, learn an abstract rule better when it is implemented over consonant (Experiment 4) than over dissonant intervals (Experiment 5). Moreover, their performance improves when there is a mapping between abstract categories defining a rule and consonant and dissonant intervals (Experiments 6 and 7). Results suggest that for humans, consonance might be used as a perceptual anchor for other cognitive processes as to facilitate the detection of abstract patterns. Lacking extensive experience with harmonic stimuli, nonhuman animals tested here do not seem to benefit from a processing advantage for consonant intervals. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Cognitive changes in conjunctive rule-based category learning: An ERP approach.

PubMed

Rabi, Rahel; Joanisse, Marc F; Zhu, Tianshu; Minda, John Paul

2018-06-25

When learning rule-based categories, sufficient cognitive resources are needed to test hypotheses, maintain the currently active rule in working memory, update rules after feedback, and to select a new rule if necessary. Prior research has demonstrated that conjunctive rules are more complex than unidimensional rules and place greater demands on executive functions like working memory. In our study, event-related potentials (ERPs) were recorded while participants performed a conjunctive rule-based category learning task with trial-by-trial feedback. In line with prior research, correct categorization responses resulted in a larger stimulus-locked late positive complex compared to incorrect responses, possibly indexing the updating of rule information in memory. Incorrect trials elicited a pronounced feedback-locked P300 elicited which suggested a disconnect between perception, and the rule-based strategy. We also examined the differential processing of stimuli that were able to be correctly classified by the suboptimal single-dimensional rule ("easy" stimuli) versus those that could only be correctly classified by the optimal, conjunctive rule ("difficult" stimuli). Among strong learners, a larger, late positive slow wave emerged for difficult compared with easy stimuli, suggesting differential processing of category items even though strong learners performed well on the conjunctive category set. Overall, the findings suggest that ERP combined with computational modelling can be used to better understand the cognitive processes involved in rule-based category learning.

Study of distributed learning as a solution to category proliferation in Fuzzy ARTMAP based neural systems.

PubMed

Parrado-Hernández, Emilio; Gómez-Sánchez, Eduardo; Dimitriadis, Yannis A

2003-09-01

An evaluation of distributed learning as a means to attenuate the category proliferation problem in Fuzzy ARTMAP based neural systems is carried out, from both qualitative and quantitative points of view. The study involves two original winner-take-all (WTA) architectures, Fuzzy ARTMAP and FasArt, and their distributed versions, dARTMAP and dFasArt. A qualitative analysis of the distributed learning properties of dARTMAP is made, focusing on the new elements introduced to endow Fuzzy ARTMAP with distributed learning. In addition, a quantitative study on a selected set of classification problems points out that problems have to present certain features in their output classes in order to noticeably reduce the number of recruited categories and achieve an acceptable classification accuracy. As part of this analysis, distributed learning was successfully adapted to a member of the Fuzzy ARTMAP family, FasArt, and similar procedures can be used to extend distributed learning capabilities to other Fuzzy ARTMAP based systems.

Analyzing Distributional Learning of Phonemic Categories in Unsupervised Deep Neural Networks

PubMed Central

Räsänen, Okko; Nagamine, Tasha; Mesgarani, Nima

2017-01-01

Infants’ speech perception adapts to the phonemic categories of their native language, a process assumed to be driven by the distributional properties of speech. This study investigates whether deep neural networks (DNNs), the current state-of-the-art in distributional feature learning, are capable of learning phoneme-like representations of speech in an unsupervised manner. We trained DNNs with unlabeled and labeled speech and analyzed the activations of each layer with respect to the phones in the input segments. The analyses reveal that the emergence of phonemic invariance in DNNs is dependent on the availability of phonemic labeling of the input during the training. No increased phonemic selectivity of the hidden layers was observed in the purely unsupervised networks despite successful learning of low-dimensional representations for speech. This suggests that additional learning constraints or more sophisticated models are needed to account for the emergence of phone-like categories in distributional learning operating on natural speech. PMID:29359204

An interplay of fusiform gyrus and hippocampus enables prototype- and exemplar-based category learning.

PubMed

Lech, Robert K; Güntürkün, Onur; Suchan, Boris

2016-09-15

The aim of the present study was to examine the contributions of different brain structures to prototype- and exemplar-based category learning using functional magnetic resonance imaging (fMRI). Twenty-eight subjects performed a categorization task in which they had to assign prototypes and exceptions to two different families. This test procedure usually produces different learning curves for prototype and exception stimuli. Our behavioral data replicated these previous findings by showing an initially superior performance for prototypes and typical stimuli and a switch from a prototype-based to an exemplar-based categorization for exceptions in the later learning phases. Since performance varied, we divided participants into learners and non-learners. Analysis of the functional imaging data revealed that the interaction of group (learners vs. non-learners) and block (Block 5 vs. Block 1) yielded an activation of the left fusiform gyrus for the processing of prototypes, and an activation of the right hippocampus for exceptions after learning the categories. Thus, successful prototype- and exemplar-based category learning is associated with activations of complementary neural substrates that constitute object-based processes of the ventral visual stream and their interaction with unique-cue representations, possibly based on sparse coding within the hippocampus. Copyright © 2016 Elsevier B.V. All rights reserved.

A study of the effectiveness of machine learning methods for classification of clinical interview fragments into a large number of categories.

PubMed

Hasan, Mehedi; Kotov, Alexander; Carcone, April; Dong, Ming; Naar, Sylvie; Hartlieb, Kathryn Brogan

2016-08-01

This study examines the effectiveness of state-of-the-art supervised machine learning methods in conjunction with different feature types for the task of automatic annotation of fragments of clinical text based on codebooks with a large number of categories. We used a collection of motivational interview transcripts consisting of 11,353 utterances, which were manually annotated by two human coders as the gold standard, and experimented with state-of-art classifiers, including Naïve Bayes, J48 Decision Tree, Support Vector Machine (SVM), Random Forest (RF), AdaBoost, DiscLDA, Conditional Random Fields (CRF) and Convolutional Neural Network (CNN) in conjunction with lexical, contextual (label of the previous utterance) and semantic (distribution of words in the utterance across the Linguistic Inquiry and Word Count dictionaries) features. We found out that, when the number of classes is large, the performance of CNN and CRF is inferior to SVM. When only lexical features were used, interview transcripts were automatically annotated by SVM with the highest classification accuracy among all classifiers of 70.8%, 61% and 53.7% based on the codebooks consisting of 17, 20 and 41 codes, respectively. Using contextual and semantic features, as well as their combination, in addition to lexical ones, improved the accuracy of SVM for annotation of utterances in motivational interview transcripts with a codebook consisting of 17 classes to 71.5%, 74.2%, and 75.1%, respectively. Our results demonstrate the potential of using machine learning methods in conjunction with lexical, semantic and contextual features for automatic annotation of clinical interview transcripts with near-human accuracy. Copyright © 2016 Elsevier Inc. All rights reserved.

Color image definition evaluation method based on deep learning method

NASA Astrophysics Data System (ADS)

Liu, Di; Li, YingChun

2018-01-01

In order to evaluate different blurring levels of color image and improve the method of image definition evaluation, this paper proposed a method based on the depth learning framework and BP neural network classification model, and presents a non-reference color image clarity evaluation method. Firstly, using VGG16 net as the feature extractor to extract 4,096 dimensions features of the images, then the extracted features and labeled images are employed in BP neural network to train. And finally achieve the color image definition evaluation. The method in this paper are experimented by using images from the CSIQ database. The images are blurred at different levels. There are 4,000 images after the processing. Dividing the 4,000 images into three categories, each category represents a blur level. 300 out of 400 high-dimensional features are trained in VGG16 net and BP neural network, and the rest of 100 samples are tested. The experimental results show that the method can take full advantage of the learning and characterization capability of deep learning. Referring to the current shortcomings of the major existing image clarity evaluation methods, which manually design and extract features. The method in this paper can extract the images features automatically, and has got excellent image quality classification accuracy for the test data set. The accuracy rate is 96%. Moreover, the predicted quality levels of original color images are similar to the perception of the human visual system.

Contrastive Constraints Guide Explanation-Based Category Learning

ERIC Educational Resources Information Center

Chin-Parker, Seth; Cantelon, Julie

2017-01-01

This paper provides evidence for a contrastive account of explanation that is motivated by pragmatic theories that recognize the contribution that context makes to the interpretation of a prompt for explanation. This study replicates the primary findings of previous work in explanation-based category learning (Williams & Lombrozo, 2010),…

Dewey, Peirce, and the Categories of Learning

ERIC Educational Resources Information Center

Wojcikiewicz, Steven K.

2010-01-01

John Dewey proposes the "educative" experience as the goal of instruction. Yet, in focusing on the educative experience, Dewey may discount other sorts of learning which occur in school, and indeed in life. This piece proposes a recapitulation of Dewey's theory through Peirce's categorical system of experience, leading to three categories of…

Form Follows Function: Learning about Function Helps Children Learn about Shape

ERIC Educational Resources Information Center

Ware, Elizabeth A.; Booth, Amy E.

2010-01-01

Object functions help young children to organize new artifact categories. However, the scope of their influence is unknown. We explore whether functions highlight property dimensions that are relevant to artifact categories in general. Specifically, using a longitudinal training procedure, we assessed whether experience with functions highlights…

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

NASA Astrophysics Data System (ADS)

Qamariah, Jumadi, Senam, Wilujeng, Insih

2017-08-01

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

Same items, different order: effects of temporal variability on infant categorization.

PubMed

Mather, Emily; Plunkett, Kim

2011-06-01

How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation minimized the perceptual distance between consecutive exemplars. In a high distance group, the order of presentation maximized the distance between successive exemplars. At test, only infants in the High Distance condition reliably discriminated between the category prototype and an atypical exemplar. Hence, the order in which infants learnt about the exemplars impacted their categorization performance. Our findings demonstrate the importance of moment-to-moment variations in similarity during infants' category learning. Copyright © 2011 Elsevier B.V. All rights reserved.

Actively learning human gaze shifting paths for semantics-aware photo cropping.

PubMed

Zhang, Luming; Gao, Yue; Ji, Rongrong; Xia, Yingjie; Dai, Qionghai; Li, Xuelong

2014-05-01

Photo cropping is a widely used tool in printing industry, photography, and cinematography. Conventional cropping models suffer from the following three challenges. First, the deemphasized role of semantic contents that are many times more important than low-level features in photo aesthetics. Second, the absence of a sequential ordering in the existing models. In contrast, humans look at semantically important regions sequentially when viewing a photo. Third, the difficulty of leveraging inputs from multiple users. Experience from multiple users is particularly critical in cropping as photo assessment is quite a subjective task. To address these challenges, this paper proposes semantics-aware photo cropping, which crops a photo by simulating the process of humans sequentially perceiving semantically important regions of a photo. We first project the local features (graphlets in this paper) onto the semantic space, which is constructed based on the category information of the training photos. An efficient learning algorithm is then derived to sequentially select semantically representative graphlets of a photo, and the selecting process can be interpreted by a path, which simulates humans actively perceiving semantics in a photo. Furthermore, we learn a prior distribution of such active graphlet paths from training photos that are marked as aesthetically pleasing by multiple users. The learned priors enforce the corresponding active graphlet path of a test photo to be maximally similar to those from the training photos. Experimental results show that: 1) the active graphlet path accurately predicts human gaze shifting, and thus is more indicative for photo aesthetics than conventional saliency maps and 2) the cropped photos produced by our approach outperform its competitors in both qualitative and quantitative comparisons.

Neural correlates of face gender discrimination learning.

PubMed

Su, Junzhu; Tan, Qingleng; Fang, Fang

2013-04-01

Using combined psychophysics and event-related potentials (ERPs), we investigated the effect of perceptual learning on face gender discrimination and probe the neural correlates of the learning effect. Human subjects were trained to perform a gender discrimination task with male or female faces. Before and after training, they were tested with the trained faces and other faces with the same and opposite genders. ERPs responding to these faces were recorded. Psychophysical results showed that training significantly improved subjects' discrimination performance and the improvement was specific to the trained gender, as well as to the trained identities. The training effect indicates that learning occurs at two levels-the category level (gender) and the exemplar level (identity). ERP analyses showed that the gender and identity learning was associated with the N170 latency reduction at the left occipital-temporal area and the N170 amplitude reduction at the right occipital-temporal area, respectively. These findings provide evidence for the facilitation model and the sharpening model on neuronal plasticity from visual experience, suggesting a faster processing speed and a sparser representation of face induced by perceptual learning.

Self-supervised ARTMAP.

PubMed

Amis, Gregory P; Carpenter, Gail A

2010-03-01

Computational models of learning typically train on labeled input patterns (supervised learning), unlabeled input patterns (unsupervised learning), or a combination of the two (semi-supervised learning). In each case input patterns have a fixed number of features throughout training and testing. Human and machine learning contexts present additional opportunities for expanding incomplete knowledge from formal training, via self-directed learning that incorporates features not previously experienced. This article defines a new self-supervised learning paradigm to address these richer learning contexts, introducing a neural network called self-supervised ARTMAP. Self-supervised learning integrates knowledge from a teacher (labeled patterns with some features), knowledge from the environment (unlabeled patterns with more features), and knowledge from internal model activation (self-labeled patterns). Self-supervised ARTMAP learns about novel features from unlabeled patterns without destroying partial knowledge previously acquired from labeled patterns. A category selection function bases system predictions on known features, and distributed network activation scales unlabeled learning to prediction confidence. Slow distributed learning on unlabeled patterns focuses on novel features and confident predictions, defining classification boundaries that were ambiguous in the labeled patterns. Self-supervised ARTMAP improves test accuracy on illustrative low-dimensional problems and on high-dimensional benchmarks. Model code and benchmark data are available from: http://techlab.eu.edu/SSART/. Copyright 2009 Elsevier Ltd. All rights reserved.

Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum.

PubMed

Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

2015-01-01

Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine.

Resonant Cholinergic Dynamics in Cognitive and Motor Decision-Making: Attention, Category Learning, and Choice in Neocortex, Superior Colliculus, and Optic Tectum

PubMed Central

Grossberg, Stephen; Palma, Jesse; Versace, Massimiliano

2016-01-01

Freely behaving organisms need to rapidly calibrate their perceptual, cognitive, and motor decisions based on continuously changing environmental conditions. These plastic changes include sharpening or broadening of cognitive and motor attention and learning to match the behavioral demands that are imposed by changing environmental statistics. This article proposes that a shared circuit design for such flexible decision-making is used in specific cognitive and motor circuits, and that both types of circuits use acetylcholine to modulate choice selectivity. Such task-sensitive control is proposed to control thalamocortical choice of the critical features that are cognitively attended and that are incorporated through learning into prototypes of visual recognition categories. A cholinergically-modulated process of vigilance control determines if a recognition category and its attended features are abstract (low vigilance) or concrete (high vigilance). Homologous neural mechanisms of cholinergic modulation are proposed to focus attention and learn a multimodal map within the deeper layers of superior colliculus. This map enables visual, auditory, and planned movement commands to compete for attention, leading to selection of a winning position that controls where the next saccadic eye movement will go. Such map learning may be viewed as a kind of attentive motor category learning. The article hereby explicates a link between attention, learning, and cholinergic modulation during decision making within both cognitive and motor systems. Homologs between the mammalian superior colliculus and the avian optic tectum lead to predictions about how multimodal map learning may occur in the mammalian and avian brain and how such learning may be modulated by acetycholine. PMID:26834535

Category learning strategies in younger and older adults: Rule abstraction and memorization.

PubMed

Wahlheim, Christopher N; McDaniel, Mark A; Little, Jeri L

2016-06-01

Despite the fundamental role of category learning in cognition, few studies have examined how this ability differs between younger and older adults. The present experiment examined possible age differences in category learning strategies and their effects on learning. Participants were trained on a category determined by a disjunctive rule applied to relational features. The utilization of rule- and exemplar-based strategies was indexed by self-reports and transfer performance. Based on self-reported strategies, the frequencies of rule- and exemplar-based learners were not significantly different between age groups, but there was a significantly higher frequency of intermediate learners (i.e., learners not identifying with a reliance on either rule- or exemplar-based strategies) in the older than younger adult group. Training performance was higher for younger than older adults regardless of the strategy utilized, showing that older adults were impaired in their ability to learn the correct rule or to remember exemplar-label associations. Transfer performance converged with strategy reports in showing higher fidelity category representations for younger adults. Younger adults with high working memory capacity were more likely to use an exemplar-based strategy, and older adults with high working memory capacity showed better training performance. Age groups did not differ in their self-reported memory beliefs, and these beliefs did not predict training strategies or performance. Overall, the present results contradict earlier findings that older adults prefer rule- to exemplar-based learning strategies, presumably to compensate for memory deficits. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Lesson plan profile of senior high school biology teachers in Subang

NASA Astrophysics Data System (ADS)

Rohayati, E.; Diana, S. W.; Priyandoko, D.

2018-05-01

Lesson plan have important role for biology teachers in teaching and learning process. The aim of this study was intended to gain an overview of lesson plan of biology teachers’ at Senior High Schools in Subang which were the members of biology teachers association in Subang. The research method was descriptive method. Data was collected from 30 biology teachers. The result of study showed that lesson plan profile in terms of subject’s identity had good category with 83.33 % of average score. Analysis on basic competence in fair category with 74.45 % of average score. The compatibility of method/strategy was in fair category with average score 72.22 %. The compatibility of instrument, media, and learning resources in fair category with 71.11 % of average score. Learning scenario was in good category with 77.00 % of average score. The compatibility of evaluation was in low category with 56.39 % of average score. It can be concluded that biology teachers in Subang were good enough in making lesson plan, however in terms of the compatibility of evaluation needed to be fixed. Furthermore, teachers’ training for biology teachers’ association was recommended to increasing teachers’ skill to be professional teachers.

Implementation of ICARE learning model using visualization animation on biotechnology course

NASA Astrophysics Data System (ADS)

Hidayat, Habibi

2017-12-01

ICARE is a learning model that directly ensure the students to actively participate in the learning process using animation media visualization. ICARE have five key elements of learning experience from children and adult that is introduction, connection, application, reflection and extension. The use of Icare system to ensure that participants have opportunity to apply what have been they learned. So that, the message delivered by lecture to students can be understood and recorded by students in a long time. Learning model that was deemed capable of improving learning outcomes and interest to learn in following learning process Biotechnology with applying the ICARE learning model using visualization animation. This learning model have been giving motivation to participate in the learning process and learning outcomes obtained becomes more increased than before. From the results of student learning in subjects Biotechnology by applying the ICARE learning model using Visualization Animation can improving study results of student from the average value of middle test amounted to 70.98 with the percentage of 75% increased value of final test to be 71.57 with the percentage of 68.63%. The interest to learn from students more increasing visits of student activities at each cycle, namely the first cycle obtained average value by 33.5 with enough category. The second cycle is obtained an average value of 36.5 to good category and third cycle the average value of 36.5 with a student activity to good category.

Discrimination of Complex Human Behavior by Pigeons (Columba livia) and Humans

PubMed Central

Qadri, Muhammad A. J.; Sayde, Justin M.; Cook, Robert G.

2014-01-01

The cognitive and neural mechanisms for recognizing and categorizing behavior are not well understood in non-human animals. In the current experiments, pigeons and humans learned to categorize two non-repeating, complex human behaviors (“martial arts” vs. “Indian dance”). Using multiple video exemplars of a digital human model, pigeons discriminated these behaviors in a go/no-go task and humans in a choice task. Experiment 1 found that pigeons already experienced with discriminating the locomotive actions of digital animals acquired the discrimination more rapidly when action information was available than when only pose information was available. Experiments 2 and 3 found this same dynamic superiority effect with naïve pigeons and human participants. Both species used the same combination of immediately available static pose information and more slowly perceived dynamic action cues to discriminate the behavioral categories. Theories based on generalized visual mechanisms, as opposed to embodied, species-specific action networks, offer a parsimonious account of how these different animals recognize behavior across and within species. PMID:25379777

An fMRI investigation of the fronto-striatal learning system in women who exhibit eating disorder behaviors

PubMed Central

Celone, Kim A.; Thompson-Brenner, Heather; Ross, Robert S.; Pratt, Elizabeth M.; Stern, Chantal E.

2013-01-01

In the present study, we sought to examine whether the fronto-striatal learning system, which has been implicated in bulimia nervosa, would demonstrate altered BOLD activity during probabilistic category learning in women who met subthreshold criteria for bulimia nervosa (Sub-BN). Sub-BN, which falls within the clinical category of Eating Disorder Not Otherwise Specified (EDNOS), is comprised of individuals who demonstrate recurrent binge eating, efforts to minimize their caloric intake and caloric retention, and elevated levels of concern about shape, weight, and/or eating, but just fail to meet the diagnostic threshold for bulimia nervosa (BN). fMRI data were collected from eighteen women with subthreshold-BN (Sub-BN) and nineteen healthy control women group-matched for age, education and body mass index (MC) during the weather prediction task. Sub-BN participants demonstrated increased caudate nucleus and dorsolateral prefrontal cortex (DLPFC) activation during the learning of probabilistic categories. Though the two subject groups did not differ in behavioral performance, over the course of learning, Sub-BN participants showed a dynamic pattern of brain activity differences when compared to matched control participants. Regions implicated in episodic memory, including the medial temporal lobe (MTL), retrosplenial cortex, middle frontal gyrus, and anterior and posterior cingulate cortex showed decreased activity in the Sub-BN participants compared to MCs during early learning which was followed by increased involvement of the DLPFC during later learning. These findings demonstrate that women with Sub-BN demonstrate differences in fronto-striatal learning system activity, as well as a distinct functional pattern between fronto-striatal and MTL learning systems during the course of implicit probabilistic category learning. PMID:21419229

Is Statistical Learning Constrained by Lower Level Perceptual Organization?

PubMed Central

Emberson, Lauren L.; Liu, Ran; Zevin, Jason D.

2013-01-01

In order for statistical information to aid in complex developmental processes such as language acquisition, learning from higher-order statistics (e.g. across successive syllables in a speech stream to support segmentation) must be possible while perceptual abilities (e.g. speech categorization) are still developing. The current study examines how perceptual organization interacts with statistical learning. Adult participants were presented with multiple exemplars from novel, complex sound categories designed to reflect some of the spectral complexity and variability of speech. These categories were organized into sequential pairs and presented such that higher-order statistics, defined based on sound categories, could support stream segmentation. Perceptual similarity judgments and multi-dimensional scaling revealed that participants only perceived three perceptual clusters of sounds and thus did not distinguish the four experimenter-defined categories, creating a tension between lower level perceptual organization and higher-order statistical information. We examined whether the resulting pattern of learning is more consistent with statistical learning being “bottom-up,” constrained by the lower levels of organization, or “top-down,” such that higher-order statistical information of the stimulus stream takes priority over the perceptual organization, and perhaps influences perceptual organization. We consistently find evidence that learning is constrained by perceptual organization. Moreover, participants generalize their learning to novel sounds that occupy a similar perceptual space, suggesting that statistical learning occurs based on regions of or clusters in perceptual space. Overall, these results reveal a constraint on learning of sound sequences, such that statistical information is determined based on lower level organization. These findings have important implications for the role of statistical learning in language acquisition. PMID:23618755

Bogus Concerns about the False Prototype Enhancement Effect

ERIC Educational Resources Information Center

Homa, Donald; Hout, Michael C.; Milliken, Laura; Milliken, Ann Marie

2011-01-01

Two experiments addressed the mechanism responsible for the false prototype effect, the phenomenon in which a prototype gradient can be obtained in the absence of learning. Previous demonstrations of this effect have occurred solely in a single-category paradigm in which transfer patterns are assigned or not to the learning category. We tested the…

Principle-Based Inferences in Young Children's Categorization: Revisiting the Impact of Function on the Naming of Artifacts.

ERIC Educational Resources Information Center

Nelson, Deborah G. Kemler

1995-01-01

Three studies investigated the influence of principle-based inferences and unprincipled similarity relations on new category learning by three- to six-year-old children. Results indicated that categorization into newly learned categories may activate self-initiated, principle-based reasoning in young children, suggesting that spontaneous…

Better Learning with More Error: Probabilistic Feedback Increases Sensitivity to Correlated Cues in Categorization

ERIC Educational Resources Information Center

Little, Daniel R.; Lewandowsky, Stephan

2009-01-01

Despite the fact that categories are often composed of correlated features, the evidence that people detect and use these correlations during intentional category learning has been overwhelmingly negative to date. Nonetheless, on other categorization tasks, such as feature prediction, people show evidence of correlational sensitivity. A…

Drift in Children's Categories: When Experienced Distributions Conflict with Prior Learning

ERIC Educational Resources Information Center

Kalish, Charles W.; Zhu, XiaoJin; Rogers, Timothy T.

2015-01-01

Psychological intuitions about natural category structure do not always correspond to the true structure of the world. The current study explores young children's responses to conflict between intuitive structure and authoritative feedback using a semi-supervised learning (Zhu et al., 2007) paradigm. In three experiments, 160 children between the…

Learning Phonemes with a Proto-Lexicon

ERIC Educational Resources Information Center

Martin, Andrew; Peperkamp, Sharon; Dupoux, Emmanuel

2013-01-01

Before the end of the first year of life, infants begin to lose the ability to perceive distinctions between sounds that are not phonemic in their native language. It is typically assumed that this developmental change reflects the construction of language-specific phoneme categories, but how these categories are learned largely remains a mystery.…

Differences in Developmental Experiences for Commonly Used Categories of Organized Youth Activities

ERIC Educational Resources Information Center

Hansen, David M.; Skorupski, William P.; Arrington, Tiffany L.

2010-01-01

The coherence of adolescents' self-reported learning experiences between subgroups of organized youth activities within five commonly used categories was evaluated. Data for the present study come from a representative sample of eleventh grade adolescents' reports on learning experiences in an organized youth activity using the Youth Experience…

Adaptable Learning Assistant for Item Bank Management

ERIC Educational Resources Information Center

Nuntiyagul, Atorn; Naruedomkul, Kanlaya; Cercone, Nick; Wongsawang, Damras

2008-01-01

We present PKIP, an adaptable learning assistant tool for managing question items in item banks. PKIP is not only able to automatically assist educational users to categorize the question items into predefined categories by their contents but also to correctly retrieve the items by specifying the category and/or the difficulty level. PKIP adapts…

Where’s Waldo? How perceptual, cognitive, and emotional brain processes cooperate during learning to categorize and find desired objects in a cluttered scene

PubMed Central

Chang, Hung-Cheng; Grossberg, Stephen; Cao, Yongqiang

2014-01-01

The Where’s Waldo problem concerns how individuals can rapidly learn to search a scene to detect, attend, recognize, and look at a valued target object in it. This article develops the ARTSCAN Search neural model to clarify how brain mechanisms across the What and Where cortical streams are coordinated to solve the Where’s Waldo problem. The What stream learns positionally-invariant object representations, whereas the Where stream controls positionally-selective spatial and action representations. The model overcomes deficiencies of these computationally complementary properties through What and Where stream interactions. Where stream processes of spatial attention and predictive eye movement control modulate What stream processes whereby multiple view- and positionally-specific object categories are learned and associatively linked to view- and positionally-invariant object categories through bottom-up and attentive top-down interactions. Gain fields control the coordinate transformations that enable spatial attention and predictive eye movements to carry out this role. What stream cognitive-emotional learning processes enable the focusing of motivated attention upon the invariant object categories of desired objects. What stream cognitive names or motivational drives can prime a view- and positionally-invariant object category of a desired target object. A volitional signal can convert these primes into top-down activations that can, in turn, prime What stream view- and positionally-specific categories. When it also receives bottom-up activation from a target, such a positionally-specific category can cause an attentional shift in the Where stream to the positional representation of the target, and an eye movement can then be elicited to foveate it. These processes describe interactions among brain regions that include visual cortex, parietal cortex, inferotemporal cortex, prefrontal cortex (PFC), amygdala, basal ganglia (BG), and superior colliculus (SC). PMID:24987339

Category priming with aliens: analysing the influence of targets' prototypicality on the centre surround inhibition mechanism.

PubMed

Frings, Christian; Göbel, Ariane; Mast, Frank; Sutter, Julia; Bermeitinger, Christina; Wentura, Dirk

2011-08-01

Marginally perceptible prototypes as primes lead to slowed reactions to related category exemplars as compared to unrelated ones. This at first glance counterintuitive finding has been interpreted as evidence for a particular mechanism of lateral inhibition, namely the centre surround inhibition mechanism. We investigated the semantic surround of category labels by experimentally manipulating the prototypicality of stimuli. Participants first learned two new categories of fantasy creatures in a 5-day-long learning phase before they worked through a semantic priming task with the category prototypes as primes and category exemplars as targets. For high-prototypical targets we observed benefit effects from related primes, whereas for low-prototypical targets we observed cost effects. The results define when the centre surround inhibition mechanism is applied, and furthermore might explain why previous studies with word stimuli (i.e., material that prevents experimental manipulation of prototypicality) observed mixed results concerning the prototypicality of targets.

The discovery of structural form

PubMed Central

Kemp, Charles; Tenenbaum, Joshua B.

2008-01-01

Algorithms for finding structure in data have become increasingly important both as tools for scientific data analysis and as models of human learning, yet they suffer from a critical limitation. Scientists discover qualitatively new forms of structure in observed data: For instance, Linnaeus recognized the hierarchical organization of biological species, and Mendeleev recognized the periodic structure of the chemical elements. Analogous insights play a pivotal role in cognitive development: Children discover that object category labels can be organized into hierarchies, friendship networks are organized into cliques, and comparative relations (e.g., “bigger than” or “better than”) respect a transitive order. Standard algorithms, however, can only learn structures of a single form that must be specified in advance: For instance, algorithms for hierarchical clustering create tree structures, whereas algorithms for dimensionality-reduction create low-dimensional spaces. Here, we present a computational model that learns structures of many different forms and that discovers which form is best for a given dataset. The model makes probabilistic inferences over a space of graph grammars representing trees, linear orders, multidimensional spaces, rings, dominance hierarchies, cliques, and other forms and successfully discovers the underlying structure of a variety of physical, biological, and social domains. Our approach brings structure learning methods closer to human abilities and may lead to a deeper computational understanding of cognitive development. PMID:18669663

A connectionist model of category learning by individuals with high-functioning autism spectrum disorder.

PubMed

Dovgopoly, Alexander; Mercado, Eduardo

2013-06-01

Individuals with autism spectrum disorder (ASD) show atypical patterns of learning and generalization. We explored the possible impacts of autism-related neural abnormalities on perceptual category learning using a neural network model of visual cortical processing. When applied to experiments in which children or adults were trained to classify complex two-dimensional images, the model can account for atypical patterns of perceptual generalization. This is only possible, however, when individual differences in learning are taken into account. In particular, analyses performed with a self-organizing map suggested that individuals with high-functioning ASD show two distinct generalization patterns: one that is comparable to typical patterns, and a second in which there is almost no generalization. The model leads to novel predictions about how individuals will generalize when trained with simplified input sets and can explain why some researchers have failed to detect learning or generalization deficits in prior studies of category learning by individuals with autism. On the basis of these simulations, we propose that deficits in basic neural plasticity mechanisms may be sufficient to account for the atypical patterns of perceptual category learning and generalization associated with autism, but they do not account for why only a subset of individuals with autism would show such deficits. If variations in performance across subgroups reflect heterogeneous neural abnormalities, then future behavioral and neuroimaging studies of individuals with ASD will need to account for such disparities.

Rule-based and information-integration perceptual category learning in children with attention-deficit/hyperactivity disorder.

PubMed

Huang-Pollock, Cynthia L; Maddox, W Todd; Tam, Helen

2014-07-01

Suboptimal functioning of the basal ganglia is implicated in attention-deficit/hyperactivity disorder (ADHD). These structures are important to the acquisition of associative knowledge, leading some to theorize that associative learning deficits might be expected, despite the fact that most extant research in ADHD has focused on effortful control. We present 2 studies that examined the acquisition of explicit rule-based (RB) and associative information integration (II) category learning among school-age children with ADHD. In Study 1, we found deficits in both RB and II category learning tasks among children with ADHD (n = 81) versus controls (n = 42). Children with ADHD tended to sort by the more salient but irrelevant dimension (in the RB paradigm) and were unable to acquire a consistent sorting strategy (in the II paradigm). To disentangle whether the deficit was localized to II category learning versus a generalized inability to consider more than 1 stimulus dimension, in Study 2 children completed a conjunctive RB paradigm that required consideration of 2 stimulus dimensions. Children with ADHD (n = 50) continued to underperform controls (n = 33). Results provide partial support for neurocognitive developmental theories of ADHD that suggest that associative learning deficits should be found, and highlight the importance of using analytic approaches that go beyond asking whether an ADHD-related deficit exists to why such deficits exist.

Finding faults: analogical comparison supports spatial concept learning in geoscience.

PubMed

Jee, Benjamin D; Uttal, David H; Gentner, Dedre; Manduca, Cathy; Shipley, Thomas F; Sageman, Bradley

2013-05-01

A central issue in education is how to support the spatial thinking involved in learning science, technology, engineering, and mathematics (STEM). We investigated whether and how the cognitive process of analogical comparison supports learning of a basic spatial concept in geoscience, fault. Because of the high variability in the appearance of faults, it may be difficult for students to learn the category-relevant spatial structure. There is abundant evidence that comparing analogous examples can help students gain insight into important category-defining features (Gentner in Cogn Sci 34(5):752-775, 2010). Further, comparing high-similarity pairs can be especially effective at revealing key differences (Sagi et al. 2012). Across three experiments, we tested whether comparison of visually similar contrasting examples would help students learn the fault concept. Our main findings were that participants performed better at identifying faults when they (1) compared contrasting (fault/no fault) cases versus viewing each case separately (Experiment 1), (2) compared similar as opposed to dissimilar contrasting cases early in learning (Experiment 2), and (3) viewed a contrasting pair of schematic block diagrams as opposed to a single block diagram of a fault as part of an instructional text (Experiment 3). These results suggest that comparison of visually similar contrasting cases helped distinguish category-relevant from category-irrelevant features for participants. When such comparisons occurred early in learning, participants were more likely to form an accurate conceptual representation. Thus, analogical comparison of images may provide one powerful way to enhance spatial learning in geoscience and other STEM disciplines.

Pigeons can discriminate "good" and "bad" paintings by children.

PubMed

Watanabe, Shigeru

2010-01-01

Humans have the unique ability to create art, but non-human animals may be able to discriminate "good" art from "bad" art. In this study, I investigated whether pigeons could be trained to discriminate between paintings that had been judged by humans as either "bad" or "good". To do this, adult human observers first classified several children's paintings as either "good" (beautiful) or "bad" (ugly). Using operant conditioning procedures, pigeons were then reinforced for pecking at "good" paintings. After the pigeons learned the discrimination task, they were presented with novel pictures of both "good" and "bad" children's paintings to test whether they had successfully learned to discriminate between these two stimulus categories. The results showed that pigeons could discriminate novel "good" and "bad" paintings. Then, to determine which cues the subjects used for the discrimination, I conducted tests of the stimuli when the paintings were of reduced size or grayscale. In addition, I tested their ability to discriminate when the painting stimuli were mosaic and partial occluded. The pigeons maintained discrimination performance when the paintings were reduced in size. However, discrimination performance decreased when stimuli were presented as grayscale images or when a mosaic effect was applied to the original stimuli in order to disrupt spatial frequency. Thus, the pigeons used both color and pattern cues for their discrimination. The partial occlusion did not disrupt the discriminative behavior suggesting that the pigeons did not attend to particular parts, namely upper, lower, left or right half, of the paintings. These results suggest that the pigeons are capable of learning the concept of a stimulus class that humans name "good" pictures. The second experiment showed that pigeons learned to discriminate watercolor paintings from pastel paintings. The subjects showed generalization to novel paintings. Then, as the first experiment, size reduction test, grayscale test, mosaic processing test and partial occlusion test were carried out. The results suggest that the pigeons used both color and pattern cues for the discrimination and show that non-human animals, such as pigeons, can be trained to discriminate abstract visual stimuli, such as pictures and may also have the ability to learn the concept of "beauty" as defined by humans.

40 CFR 156.62 - Toxicity Category.

Code of Federal Regulations, 2010 CFR

2010-07-01

... being the highest toxicity category. Most human hazard, precautionary statements, and human personal protective equipment statements are based upon the Toxicity Category of the pesticide product as sold or...

40 CFR 156.62 - Toxicity Category.

Code of Federal Regulations, 2011 CFR

2011-07-01

... being the highest toxicity category. Most human hazard, precautionary statements, and human personal protective equipment statements are based upon the Toxicity Category of the pesticide product as sold or...

Rule-Based Category Learning in Children: The Role of Age and Executive Functioning

PubMed Central

Rabi, Rahel; Minda, John Paul

2014-01-01

Rule-based category learning was examined in 4–11 year-olds and adults. Participants were asked to learn a set of novel perceptual categories in a classification learning task. Categorization performance improved with age, with younger children showing the strongest rule-based deficit relative to older children and adults. Model-based analyses provided insight regarding the type of strategy being used to solve the categorization task, demonstrating that the use of the task appropriate strategy increased with age. When children and adults who identified the correct categorization rule were compared, the performance deficit was no longer evident. Executive functions were also measured. While both working memory and inhibitory control were related to rule-based categorization and improved with age, working memory specifically was found to marginally mediate the age-related improvements in categorization. When analyses focused only on the sample of children, results showed that working memory ability and inhibitory control were associated with categorization performance and strategy use. The current findings track changes in categorization performance across childhood, demonstrating at which points performance begins to mature and resemble that of adults. Additionally, findings highlight the potential role that working memory and inhibitory control may play in rule-based category learning. PMID:24489658

Multi-level discriminative dictionary learning with application to large scale image classification.

PubMed

Shen, Li; Sun, Gang; Huang, Qingming; Wang, Shuhui; Lin, Zhouchen; Wu, Enhua

2015-10-01

The sparse coding technique has shown flexibility and capability in image representation and analysis. It is a powerful tool in many visual applications. Some recent work has shown that incorporating the properties of task (such as discrimination for classification task) into dictionary learning is effective for improving the accuracy. However, the traditional supervised dictionary learning methods suffer from high computation complexity when dealing with large number of categories, making them less satisfactory in large scale applications. In this paper, we propose a novel multi-level discriminative dictionary learning method and apply it to large scale image classification. Our method takes advantage of hierarchical category correlation to encode multi-level discriminative information. Each internal node of the category hierarchy is associated with a discriminative dictionary and a classification model. The dictionaries at different layers are learnt to capture the information of different scales. Moreover, each node at lower layers also inherits the dictionary of its parent, so that the categories at lower layers can be described with multi-scale information. The learning of dictionaries and associated classification models is jointly conducted by minimizing an overall tree loss. The experimental results on challenging data sets demonstrate that our approach achieves excellent accuracy and competitive computation cost compared with other sparse coding methods for large scale image classification.

Structure Mapping and Relational Language Support Children's Learning of Relational Categories

ERIC Educational Resources Information Center

Gentner, Dedre; Anggoro, Florencia K.; Klibanoff, Raquel S.

2011-01-01

Learning relational categories--whose membership is defined not by intrinsic properties but by extrinsic relations with other entities--poses a challenge to young children. The current work showed 3-, 4- to 5-, and 6-year-olds pairs of cards exemplifying familiar relations (e.g., a nest and a bird exemplifying "home for") and then tested whether…

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

ERIC Educational Resources Information Center

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and…

Due Process in Dual Process: Model-Recovery Simulations of Decision-Bound Strategy Analysis in Category Learning

ERIC Educational Resources Information Center

Edmunds, Charlotte E. R.; Milton, Fraser; Wills, Andy J.

2018-01-01

Behavioral evidence for the COVIS dual-process model of category learning has been widely reported in over a hundred publications (Ashby & Valentin, 2016). It is generally accepted that the validity of such evidence depends on the accurate identification of individual participants' categorization strategies, a task that usually falls to…

Visual Imagery, Lifecourse Structure and Lifelong Learning

ERIC Educational Resources Information Center

Schuller, Tom

2004-01-01

Imagery could add an extra dimension to analyses of lifelong learning, which need to draw on diverse sources and techniques. This article has two principal components. First I suggest that the use of images might be divided into three categories: as illustration; as evidence; and as heuristic. I go on to explore the latter two categories, first by…

Perceptual Learning of Intonation Contour Categories in Adults and 9- to 11-Year-Old Children: Adults Are More Narrow-Minded

ERIC Educational Resources Information Center

Kapatsinski, Vsevolod; Olejarczuk, Paul; Redford, Melissa A.

2017-01-01

We report on rapid perceptual learning of intonation contour categories in adults and 9- to 11-year-old children. Intonation contours are temporally extended patterns, whose perception requires temporal integration and therefore poses significant working memory challenges. Both children and adults form relatively abstract representations of…

The Effect of Zipfian Frequency Variations on Category Formation in Adult Artificial Language Learning

ERIC Educational Resources Information Center

Schuler, Kathryn D.; Reeder, Patricia A.; Newport, Elissa L.; Aslin, Richard N.

2017-01-01

Successful language acquisition hinges on organizing individual words into grammatical categories and learning the relationships between them, but the method by which children accomplish this task has been debated in the literature. One proposal is that learners use the shared distributional contexts in which words appear as a cue to their…

Long-term care planning study: strengths and learning needs of nursing staff.

PubMed

Cruttenden, Kathleen E

2006-01-01

This planning study was designed and conducted in a predominantly rural Canadian province to examine the strengths and learning needs of four categories of nursing staff practising in New Brunswick nursing homes. Participants included directors of care, registered nurses, licensed practical nurses, and resident attendants. The nursing homes ranged in size from 38 to 196 beds and were located throughout the province. In health and planning studies, ethnography conveys a coherent statement of peoples' local knowledge as culture-sharing groups (Muecke, 1994). The study derived information from the Nursing Home Act, reports, the literature, key informants, and direct observations of and interviews with participants. Leadership strengths defined the roles for categories of staff and supported the capacity of each category to identify their learning needs. In conclusion, nurses practising in nursing homes can and must take an active role in decision making for their learning.

Amnesic patients show superior generalization in category learning.

PubMed

O'Connell, Garret; Myers, Catherine E; Hopkins, Ramona O; McLaren, R P; Gluck, Mark A; Wills, Andy J

2016-11-01

Generalization is the application of existing knowledge to novel situations. Questions remain about the precise role of the hippocampus in this facet of learning, but a connectionist model by Gluck and Myers (1993) predicts that generalization should be enhanced following hippocampal damage. In a two-category learning task, a group of amnesic patients (n = 9) learned the training items to a similar level of accuracy as matched controls (n = 9). Both groups then classified new items at various levels of distortion. The amnesic group showed significantly more accurate generalization to high-distortion novel items, a difference also present compared to a larger group of unmatched controls (n = 33). The model prediction of a broadening of generalization gradients in amnesia, at least for items near category boundaries, was supported by the results. Our study shows for the first time that amnesia can sometimes improve generalization. (PsycINFO Database Record (c) 2016 APA, all rights reserved).

Strong systematicity through sensorimotor conceptual grounding: an unsupervised, developmental approach to connectionist sentence processing

NASA Astrophysics Data System (ADS)

Jansen, Peter A.; Watter, Scott

2012-03-01

Connectionist language modelling typically has difficulty with syntactic systematicity, or the ability to generalise language learning to untrained sentences. This work develops an unsupervised connectionist model of infant grammar learning. Following the semantic boostrapping hypothesis, the network distils word category using a developmentally plausible infant-scale database of grounded sensorimotor conceptual representations, as well as a biologically plausible semantic co-occurrence activation function. The network then uses this knowledge to acquire an early benchmark clausal grammar using correlational learning, and further acquires separate conceptual and grammatical category representations. The network displays strongly systematic behaviour indicative of the general acquisition of the combinatorial systematicity present in the grounded infant-scale language stream, outperforms previous contemporary models that contain primarily noun and verb word categories, and successfully generalises broadly to novel untrained sensorimotor grounded sentences composed of unfamiliar nouns and verbs. Limitations as well as implications to later grammar learning are discussed.

Fragrances Categorized According to Relative Human Skin Sensitization Potency

PubMed Central

Api, Anne Marie; Parakhia, Rahul; O'Brien, Devin; Basketter, David A.

2017-01-01

Background The development of non-animal alternatives for skin sensitization potency prediction is dependent upon the availability of a sufficient dataset whose human potency is well characterized. Previously, establishment of basic categorization criteria for 6 defined potency categories, allowed 131 substances to be allocated into them entirely on the basis of human information. Objectives To supplement the original dataset with an extended range of fragrance substances. Methods A more fully described version of the original criteria was used to assess 89 fragrance chemicals, allowing their allocation into one of the 6 potency categories. Results None of the fragrance substances were assigned to the most potent group, category 1, whereas 11 were category 2, 22 were category 3, 37 were category 4, and 19 were category 5. Although none were identified as non-sensitizing, note that substances in category 5 also do not pass the threshold for regulatory classification. Conclusions The combined datasets of >200 substances placed into potency categories solely on the basis of human data provides an essential resource for the elaboration and evaluation of predictive non-animal methods. PMID:28691948

[Problem based learning: achievement of educational goals in the information and comprehension sub-categories of Bloom cognitive domain].

PubMed

Montecinos, P; Rodewald, A M

1994-06-01

The aim this work was to assess and compare the achievements of medical students, subjected to problem based learning methodology. The information and comprehension categories of Bloom were tested in 17 medical students in four different occasions during the physiopathology course, using a multiple choice knowledge test. There was a significant improvement in the number of correct answers towards the end of the course. It is concluded that these medical students obtained adequate learning achievements in the information subcategory of Bloom using problem based learning methodology, during the physiopathology course.

Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment

EPA Science Inventory

Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

Sleep Benefits Memory for Semantic Category Structure While Preserving Exemplar-Specific Information.

PubMed

Schapiro, Anna C; McDevitt, Elizabeth A; Chen, Lang; Norman, Kenneth A; Mednick, Sara C; Rogers, Timothy T

2017-11-01

Semantic memory encompasses knowledge about both the properties that typify concepts (e.g. robins, like all birds, have wings) as well as the properties that individuate conceptually related items (e.g. robins, in particular, have red breasts). We investigate the impact of sleep on new semantic learning using a property inference task in which both kinds of information are initially acquired equally well. Participants learned about three categories of novel objects possessing some properties that were shared among category exemplars and others that were unique to an exemplar, with exposure frequency varying across categories. In Experiment 1, memory for shared properties improved and memory for unique properties was preserved across a night of sleep, while memory for both feature types declined over a day awake. In Experiment 2, memory for shared properties improved across a nap, but only for the lower-frequency category, suggesting a prioritization of weakly learned information early in a sleep period. The increase was significantly correlated with amount of REM, but was also observed in participants who did not enter REM, suggesting involvement of both REM and NREM sleep. The results provide the first evidence that sleep improves memory for the shared structure of object categories, while simultaneously preserving object-unique information.

Methods for detecting long-term CNS dysfunction after prenatal exposure to neurotoxins.

PubMed

Vorhees, C V

1997-11-01

Current U.S. Environmental Protection Agency regulatory guidelines for developmental neurotoxicity emphasize functional categories such as motor activity, auditory startle, and learning and memory. A single test of some simple form of learning and memory is accepted to meet the latter category. The rationale for this emphasis has been that sensitive and reliable methods for assessing complex learning and memory are either not available or are too burdensome, and that insufficient data exist to endorse one approach over another. There has been little discussion of the fact that learning and memory is not a single identifiable functional category and no single test can assess all types of learning and memory. Three methods for assessing complex learning and memory are presented that assess two different types of learning and memory, are relatively efficient to conduct, and are sensitive to several known neurobehavioral teratogens. The tests are a 9-unit multiple-T swimming maze, and the Morris and Barnes mazes. The first of these assesses sequential learning, while the latter two assess spatial learning. A description of each test is provided, along with procedures for their use, and data exemplifying effects obtained using developmental exposure to phenytoin, methamphetamine, and MDMA. It is argued that multiple tests of learning and memory are required to ascertain cognitive deficits; something no single method can accomplish. Methods for acoustic startle are also presented.

Practice guidelines in the context of primary care, learning and usability in the physicians' decision-making process--a qualitative study.

PubMed

Ingemansson, Maria; Bastholm-Rahmner, Pia; Kiessling, Anna

2014-08-20

Decision-making is central for general practitioners (GP). Practice guidelines are important tools in this process but implementation of them in the complex context of primary care is a challenge. The purpose of this study was to explore how GPs approach, learn from and use practice guidelines in their day-to-day decision-making process in primary care. A qualitative approach using focus-group interviews was chosen in order to provide in-depth information. The participants were 22 GPs with a median of seven years of experience in primary care, representing seven primary healthcare centres in Stockholm, Sweden in 2011. The interviews focused on how the GPs use guidelines in their decision-making, factors that influence their decision how to approach these guidelines, and how they could encourage the learning process in routine practice.Data were analysed by qualitative content analysis. Meaning units were condensed and grouped in categories. After interpreting the content in the categories, themes were created. Three themes were conceptualized. The first theme emphasized to use guidelines by interactive contextualized dialogues. The categories underpinning this theme: 1. Feedback by peer-learning 2. Feedback by collaboration, mutual learning, and equality between specialties, identified important ways to achieve this learning dialogue. Confidence was central in the second theme, learning that establishes confidence to provide high quality care. Three aspects of confidence were identified in the categories of this theme: 1. Confidence by confirmation, 2. Confidence by reliability and 3. Confidence by evaluation of own results. In the third theme, learning by use of relevant evidence in the decision-making process, we identified two categories: 1. Design and lay-out visualizing the evidence 2. Accessibility adapted to the clinical decision-making process as prerequisites for using the practice guidelines. Decision-making in primary care is a dual process that involves use of intuitive and analytic thinking in a balanced way in order to provide high quality care. Key aspects of effective learning in this clinical decision-making process were: contextualized dialogue, which was based on the GPs' own experiences, feedback on own results and easy access to short guidelines perceived as trustworthy.

The Neural Correlates of Desire

PubMed Central

Kawabata, Hideaki; Zeki, Semir

2008-01-01

In an event-related fMRI study, we scanned eighteen normal human subjects while they viewed three categories of pictures (events, objects and persons) which they classified according to desirability (desirable, indifferent or undesirable). Each category produced activity in a distinct part of the visual brain, thus reflecting its functional specialization. We used conjunction analysis to learn whether there is a brain area which is always active when a desirable picture is viewed, regardless of the category to which it belongs. The conjunction analysis of the contrast desirable > undesirable revealed activity in the superior orbito-frontal cortex. This activity bore a positive linear relationship to the declared level of desirability. The conjunction analysis of desirable > indifferent revealed activity in the mid-cingulate cortex and in the anterior cingulate cortex. In the former, activity was greater for desirable and undesirable stimuli than for stimuli classed as indifferent. Other conjunction analyses produced no significant effects. These results show that categorizing any stimulus according to its desirability activates three different brain areas: the superior orbito-frontal, the mid-cingulate, and the anterior cingulate cortices. PMID:18728753

The Human Likeness Dimension of the “Uncanny Valley Hypothesis”: Behavioral and Functional MRI Findings

PubMed Central

Cheetham, Marcus; Suter, Pascal; Jäncke, Lutz

2011-01-01

The uncanny valley hypothesis (Mori, 1970) predicts differential experience of negative and positive affect as a function of human likeness. Affective experience of humanlike robots and computer-generated characters (avatars) dominates “uncanny” research, but findings are inconsistent. Importantly, it is unknown how objects are actually perceived along the hypothesis’ dimension of human likeness (DOH), defined in terms of human physical similarity. To examine whether the DOH can also be defined in terms of effects of categorical perception (CP), stimuli from morph continua with controlled differences in physical human likeness between avatar and human faces as endpoints were presented. Two behavioral studies found a sharp category boundary along the DOH and enhanced visual discrimination (i.e., CP) of fine-grained differences between pairs of faces at the category boundary. Discrimination was better for face pairs presenting category change in the human-to-avatar than avatar-to-human direction along the DOH. To investigate brain representation of physical change and category change along the DOH, an event-related functional magnetic resonance imaging study used the same stimuli in a pair-repetition priming paradigm. Bilateral mid-fusiform areas and a different right mid-fusiform area were sensitive to physical change within the human and avatar categories, respectively, whereas entirely different regions were sensitive to the human-to-avatar (caudate head, putamen, thalamus, red nucleus) and avatar-to-human (hippocampus, amygdala, mid-insula) direction of category change. These findings show that Mori’s DOH definition does not reflect subjective perception of human likeness and suggest that future “uncanny” studies consider CP and the DOH’s category structure in guiding experience of non-human objects. PMID:22131970

Familiarity with a Vocal Category Biases the Compartmental Expression of "Arc/Arg3.1" in Core Auditory Cortex

ERIC Educational Resources Information Center

Ivanova, Tamara N.; Gross, Christina; Mappus, Rudolph C.; Kwon, Yong Jun; Bassell, Gary J.; Liu, Robert C.

2017-01-01

Learning to recognize a stimulus category requires experience with its many natural variations. However, the mechanisms that allow a category's sensorineural representation to be updated after experiencing new exemplars are not well understood, particularly at the molecular level. Here we investigate how a natural vocal category induces expression…

Testing the Efficiency of Markov Chain Monte Carlo with People Using Facial Affect Categories

ERIC Educational Resources Information Center

Martin, Jay B.; Griffiths, Thomas L.; Sanborn, Adam N.

2012-01-01

Exploring how people represent natural categories is a key step toward developing a better understanding of how people learn, form memories, and make decisions. Much research on categorization has focused on artificial categories that are created in the laboratory, since studying natural categories defined on high-dimensional stimuli such as…

The Development of Categorization: Effects of Classification and Inference Training on Category Representation

ERIC Educational Resources Information Center

Deng, Wei; Sloutsky, Vladimir M.

2015-01-01

Does category representation change in the course of development? And if so, how and why? The current study attempted to answer these questions by examining category learning and category representation. In Experiment 1, 4-year-olds, 6-year-olds, and adults were trained with either a classification task or an inference task and their…

Dimension-Based Statistical Learning Affects Both Speech Perception and Production

ERIC Educational Resources Information Center

Lehet, Matthew; Holt, Lori L.

2017-01-01

Multiple acoustic dimensions signal speech categories. However, dimensions vary in their informativeness; some are more diagnostic of category membership than others. Speech categorization reflects these dimensional regularities such that diagnostic dimensions carry more "perceptual weight" and more effectively signal category membership…

Comparing Product Category Rules from Different Programs: Learned Outcomes Towards Global Alignment (Presentation)

EPA Science Inventory

Purpose Product category rules (PCRs) provide category-specific guidance for estimating and reporting product life cycle environmental impacts, typically in the form of environmental product declarations and product carbon footprints. Lack of global harmonization between PCRs or ...

Differences in students' perceptions of learning compulsory foundation biochemistry in the health sciences professions.

PubMed

Minasian-Batmanian, Laura C; Lingard, Jennifer; Prosser, Michael

2005-11-01

Student approaches to learning vary from surface approaches to meaningful, deep learning practices. Differences in approach may be related to students' conceptions of the subject, perceptions of the learning environment, prior study experiences and performance on assessment. This study aims to explore entering students' conceptions of the unit they are about to study and how they intend to approach their studies. It involved a survey of 203 (of 250) first year students in a cross disciplinary unit in the Faculty of Health Sciences. They were asked to complete an open-ended response survey, including questions on what they thought they needed to do to learn biochemistry and what they thought the study of biochemistry was about. A phenomenographic methodology was used to identify categories of description for the questions. The paper will describe the categories in detail, the structural relationship between the categories and the distribution of responses within categories. The study reports a relationship between conception of the topic and approaches to learning. Students with more complex and coherent conceptions of the topic report that they were more likely to adopt deeper approaches to study than those with more fragmented conceptions. However, compared to previous studies, a surprisingly high proportion of students with more cohesive conceptions still intended to adopt more surface approaches. This may reflect the particular context of their learning, namely in a compulsory unit involving material for which most students have minimal background and difficulty seeing its relevance. Implications for teaching such foundation material are discussed.

The Use of Category Information by 2- and 3-Year-Olds.

ERIC Educational Resources Information Center

Dunn, Lynne Anne

This study examined the ability of preschool children to process and use conceptual category information in a disrcimination learning task. A total of 60 boys and girls between the ages of 2 1/2 and 4 years completed a 3-choice discrimination learning task. On each of 12 trials, a child was presented with three magazine photographs: one of an…

Interest in School and Learning: Quality Education Program Study. Booklet 4 (Description) and Booklet 4-A (Needs Assessment).

ERIC Educational Resources Information Center

Bucks County Public Schools, Doylestown, PA.

Categories of effective and ineffective behavior in regard to Goal Four of the Quality Education Program (regarding interest in school and learning) are listed. Both the rationales for areas of effective student behavior and the categories of teacher strategies are also included. (See TM 001 375 for project description.) (MS)

Brief Report: Simulations Suggest Heterogeneous Category Learning and Generalization in Children with Autism Is a Result of Idiosyncratic Perceptual Transformations

ERIC Educational Resources Information Center

Mercado, Eduardo, III; Church, Barbara A.

2016-01-01

Children with autism spectrum disorder (ASD) sometimes have difficulties learning categories. Past computational work suggests that such deficits may result from atypical representations in cortical maps. Here we use neural networks to show that idiosyncratic transformations of inputs can result in the formation of feature maps that impair…

Do Development and Learning Really Decrease Memory? On Similarity and Category-Based Induction in Adults and Children

ERIC Educational Resources Information Center

Wilburn, Catherine; Feeney, Aidan

2008-01-01

In a recently published study, Sloutsky and Fisher [Sloutsky, V. M., & Fisher, A.V. (2004a). When development and learning decrease memory: Evidence against category-based induction in children. "Psychological Science", 15, 553-558; Sloutsky, V. M., & Fisher, A. V. (2004b). Induction and categorization in young children: A similarity-based model.…

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database.

PubMed

Choi, Joon Yul; Yoo, Tae Keun; Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen's kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals.

Framework for Conducting Empirical Observations of Learning Processes.

ERIC Educational Resources Information Center

Fischer, Hans Ernst; von Aufschnaiter, Stephan

1993-01-01

Reviews four hypotheses about learning: Comenius's transmission-reception theory, information processing theory, Gestalt theory, and Piagetian theory. Uses the categories preunderstanding, conceptual change, and learning processes to classify and assess investigations on learning processes. (PR)

Learning in Mental Retardation: A Comprehensive Bibliography.

ERIC Educational Resources Information Center

Gardner, James M.; And Others

The bibliography on learning in mentally handicapped persons is divided into the following topic categories: applied behavior change, classical conditioning, discrimination, generalization, motor learning, reinforcement, verbal learning, and miscellaneous. An author index is included. (KW)

Abstract memory representations in the ventromedial prefrontal cortex and hippocampus support concept generalization.

PubMed

Bowman, Caitlin R; Zeithamova, Dagmar

2018-02-07

Memory function involves both the ability to remember details of individual experiences and the ability to link information across events to create new knowledge. Prior research has identified the ventromedial prefrontal cortex (VMPFC) and the hippocampus as important for integrating across events in service of generalization in episodic memory. The degree to which these memory integration mechanisms contribute to other forms of generalization, such as concept learning, is unclear. The present study used a concept-learning task in humans (both sexes) coupled with model-based fMRI to test whether VMPFC and hippocampus contribute to concept generalization, and whether they do so by maintaining specific category exemplars or abstract category representations. Two formal categorization models were fit to individual subject data: a prototype model that posits abstract category representations and an exemplar model that posits category representations based on individual category members. Latent variables from each of these models were entered into neuroimaging analyses to determine whether VMPFC and the hippocampus track prototype or exemplar information during concept generalization. Behavioral model fits indicated that almost three quarters of the subjects relied on prototype information when making judgments about new category members. Paralleling prototype dominance in behavior, correlates of the prototype model were identified in VMPFC and the anterior hippocampus with no significant exemplar correlates. These results indicate that the VMPFC and portions of the hippocampus play a broad role in memory generalization and that they do so by representing abstract information integrated from multiple events. SIGNIFICANCE STATEMENT Whether people represent concepts as a set of individual category members or by deriving generalized concept representations abstracted across exemplars has been debated. In episodic memory, generalized memory representations have been shown to arise through integration across events supported by the ventromedial prefrontal cortex (VMPFC) and hippocampus. The current study combined formal categorization models with fMRI data analysis to show that the VMPFC and anterior hippocampus represent abstract prototype information during concept generalization, contributing novel evidence of generalized concept representations in the brain. Results indicate that VMPFC-hippocampal memory integration mechanisms contribute to knowledge generalization across multiple cognitive domains, with the degree of abstraction of memory representations varying along the long axis of the hippocampus. Copyright © 2018 the authors.

Category Learning in the Brain

PubMed Central

Seger, Carol A.; Miller, Earl K.

2013-01-01

The ability to group items and events into functional categories is a fundamental characteristic of sophisticated thought. It is subserved by plasticity in many neural systems, including neocortical regions (sensory, prefrontal, parietal, and motor cortex), the medial temporal lobe, the basal ganglia, and midbrain dopaminergic systems. These systems interact during category learning. Corticostriatal loops may mediate recursive, bootstrapping interactions between fast reward-gated plasticity in the basal ganglia and slow reward-shaded plasticity in the cortex. This can provide a balance between acquisition of details of experiences and generalization across them. Interactions between the corticostriatal loops can integrate perceptual, response, and feedback-related aspects of the task and mediate the shift from novice to skilled performance. The basal ganglia and medial temporal lobe interact competitively or cooperatively, depending on the demands of the learning task. PMID:20572771

Teaching children with autism spectrum disorder to tact olfactory stimuli.

PubMed

Dass, Tina K; Kisamore, April N; Vladescu, Jason C; Reeve, Kenneth F; Reeve, Sharon A; Taylor-Santa, Catherine

2018-05-28

Research on tact acquisition by children with autism spectrum disorder (ASD) has often focused on teaching participants to tact visual stimuli. It is important to evaluate procedures for teaching tacts of nonvisual stimuli (e.g., olfactory, tactile). The purpose of the current study was to extend the literature on secondary target instruction and tact training by evaluating the effects of a discrete-trial instruction procedure involving (a) echoic prompts, a constant prompt delay, and error correction for primary targets; (b) inclusion of secondary target stimuli in the consequent portion of learning trials; and (c) multiple exemplar training on the acquisition of item tacts of olfactory stimuli, emergence of category tacts of olfactory stimuli, generalization of category tacts, and emergence of category matching, with three children diagnosed with ASD. Results showed that all participants learned the item and category tacts following teaching, participants demonstrated generalization across category tacts, and category matching emerged for all participants. © 2018 Society for the Experimental Analysis of Behavior.

The home care teaching and learning process in undergraduate health care degree courses.

PubMed

Hermann, Ana Paula; Lacerda, Maria Ribeiro; Maftum, Mariluci Alves; Bernardino, Elizabeth; Mello, Ana Lúcia Schaefer Ferreira de

2017-07-01

Home care, one of the services provided by the health system, requires health practitioners who are capable of understanding its specificities. This study aimed to build a substantive theory that describes experiences of home care teaching and learning during undergraduate degree courses in nursing, pharmacy, medicine, nutrition, dentistry and occupational therapy. A qualitative analysis was performed using the grounded theory approach based on the results of 63 semistructured interviews conducted with final year students, professors who taught subjects related to home care, and recent graduates working with home care, all participants in the above courses. The data was analyzed in three stages - open coding, axial coding and selective coding - resulting in the phenomenon Experiences of home care teaching and learning during the undergraduate health care degree courses. Its causes were described in the category Articulating knowledge of home care, strategies in the category Experiencing the unique nature of home care, intervening conditions in the category Understanding the multidimensional characteristics of home care, consequences in the category Changing thinking about home care training, and context in the category Understanding home care in the health system. Home care contributes towards the decentralization of hospital care.

Deficits in Category Learning in Older Adults: Rule-Based Versus Clustering Accounts

PubMed Central

2017-01-01

Memory research has long been one of the key areas of investigation for cognitive aging researchers but only in the last decade or so has categorization been used to understand age differences in cognition. Categorization tasks focus more heavily on the grouping and organization of items in memory, and often on the process of learning relationships through trial and error. Categorization studies allow researchers to more accurately characterize age differences in cognition: whether older adults show declines in the way in which they represent categories with simple rules or declines in representing categories by similarity to past examples. In the current study, young and older adults participated in a set of classic category learning problems, which allowed us to distinguish between three hypotheses: (a) rule-complexity: categories were represented exclusively with rules and older adults had differential difficulty when more complex rules were required, (b) rule-specific: categories could be represented either by rules or by similarity, and there were age deficits in using rules, and (c) clustering: similarity was mainly used and older adults constructed a less-detailed representation by lumping more items into fewer clusters. The ordinal levels of performance across different conditions argued against rule-complexity, as older adults showed greater deficits on less complex categories. The data also provided evidence against rule-specificity, as single-dimensional rules could not explain age declines. Instead, computational modeling of the data indicated that older adults utilized fewer conceptual clusters of items in memory than did young adults. PMID:28816474

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

PubMed

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.

Ventral striatum and the evaluation of memory retrieval strategies.

PubMed

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M; Scimeca, Jason M

2014-09-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant's subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies.

Learning to Detect Triggers of Airway Symptoms: The Role of Illness Beliefs, Conceptual Categories and Actual Experience with Allergic Symptoms

PubMed Central

Janssens, Thomas; Caris, Eva; Van Diest, Ilse; Van den Bergh, Omer

2017-01-01

Background: In asthma and allergic rhinitis, beliefs about what triggers allergic reactions often do not match objective allergy tests. This may be due to insensitivity for expectancy violations as a result of holding trigger beliefs based on conceptual relationships among triggers. In this laboratory experiment, we aimed to investigate how pre-existing beliefs and conceptual relationships among triggers interact with actual experience when learning differential symptom expectations. Methods: Healthy participants (N = 48) received information that allergic reactions were a result of specific sensitivities versus general allergic vulnerability. Next, they performed a trigger learning task using a differential conditioning paradigm: brief inhalation of CO2 enriched air was used to induce symptoms, while participants were led to believe that the symptoms came about as a result of inhaled allergens (conditioned stimuli, CS’s; CS+ followed by symptoms, CS- not followed by symptoms). CS+ and CS- stimuli either shared (e.g., birds-mammals) or did not share (e.g. birds-fungi) category membership. During Acquisition, participants reported symptom expectancy and symptom intensity for all triggers. During a Test 1 day later, participants rated symptom expectancies for old CS+/CS- triggers, for novel triggers within categories, and for exemplars of novel trigger categories. Data were analyzed using multilevel models. Findings: Only a subgroup of participants (n = 22) showed differences between CO2 and room air symptoms. In this group of responders, analysis of symptom expectancies during acquisition did not result in significant differential symptom CS+/CS- acquisition. A retention test 1 day later showed differential CS+/CS- symptom expectancies: When CS categories did not share category membership, specific sensitivity beliefs improved retention of CS+/CS- differentiation. However, when CS categories shared category membership, general vulnerability beliefs improved retention of CS+/CS- differentiation. Furthermore, participants showed some selectivity in generalization of symptom expectancies to novel categories, as symptom expectancies did not generalize to novel categories that were unrelated to CS+ or CS- categories. Generalization to novel categories was not affected by information about general vulnerability or specific sensitivities. Discussion: Pre-existing vulnerability beliefs and conceptual relationships between trigger categories influence differential symptom expectancies to allergic triggers. PMID:28638358

Same Items, Different Order: Effects of Temporal Variability on Infant Categorization

ERIC Educational Resources Information Center

Mather, Emily; Plunkett, Kim

2011-01-01

How does variability between members of a category influence infants' category learning? We explore the impact of the order in which different items are sampled on category formation. Two groups of 10-months-olds were presented with a series of exemplars to be organized into a single category. In a low distance group, the order of presentation…

Unsupervised active learning based on hierarchical graph-theoretic clustering.

PubMed

Hu, Weiming; Hu, Wei; Xie, Nianhua; Maybank, Steve

2009-10-01

Most existing active learning approaches are supervised. Supervised active learning has the following problems: inefficiency in dealing with the semantic gap between the distribution of samples in the feature space and their labels, lack of ability in selecting new samples that belong to new categories that have not yet appeared in the training samples, and lack of adaptability to changes in the semantic interpretation of sample categories. To tackle these problems, we propose an unsupervised active learning framework based on hierarchical graph-theoretic clustering. In the framework, two promising graph-theoretic clustering algorithms, namely, dominant-set clustering and spectral clustering, are combined in a hierarchical fashion. Our framework has some advantages, such as ease of implementation, flexibility in architecture, and adaptability to changes in the labeling. Evaluations on data sets for network intrusion detection, image classification, and video classification have demonstrated that our active learning framework can effectively reduce the workload of manual classification while maintaining a high accuracy of automatic classification. It is shown that, overall, our framework outperforms the support-vector-machine-based supervised active learning, particularly in terms of dealing much more efficiently with new samples whose categories have not yet appeared in the training samples.

Ways of dealing with science learning: a study based on Swedish early childhood education practice

NASA Astrophysics Data System (ADS)

Gustavsson, Laila; Jonsson, Agneta; Ljung-Djärf, Agneta; Thulin, Susanne

2016-07-01

The Swedish school system offers curriculum-based early childhood education (ECE) organised as preschool (for 0-5-year-olds) and preschool class (for 6-year-olds). The intention to create a playful and educational environment based on children's perspectives, interests, and questions is strongly based on historical and cultural traditions. This article develops knowledge of ECE teachers' approaches to science-learning situations. The study applies a phenomenographic approach. The analysis is based on approximately 9.5 hours of video documentation of teacher-led and child-initiated Swedish ECE science activities. We identified two descriptive categories and four subcategories dealing with science-learning situations: (A) making anything visible, containing the three subcategories (Aa) addressing everyone, (Ab) addressing everything, and (Ac) addressing play and fantasy; and (B) creating a shared space for learning (Ba) addressing common content. These categories are related to how efforts to take advantage of children's perspectives are interpreted and addressed in educational practice. The article discusses and exemplifies the use of various categories and their potential implications for ECE learning practice.

Valuable human capital: the aging health care worker.

PubMed

Collins, Sandra K; Collins, Kevin S

2006-01-01

With the workforce growing older and the supply of younger workers diminishing, it is critical for health care managers to understand the factors necessary to capitalize on their vintage employees. Retaining this segment of the workforce has a multitude of benefits including the preservation of valuable intellectual capital, which is necessary to ensure that health care organizations maintain their competitive advantage in the consumer-driven market. Retaining the aging employee is possible if health care managers learn the motivators and training differences associated with this category of the workforce. These employees should be considered a valuable resource of human capital because without their extensive expertise, intense loyalty and work ethic, and superior customer service skills, health care organizations could suffer severe economic repercussions in the near future.

Categories and Music Transmission

ERIC Educational Resources Information Center

Gatien, Greg

2009-01-01

Lucy Green's (2008) "Music, Informal Learning, and the School: A New Classroom Pedagogy" gives rise to an interesting corollary. Does the manner of music's transmission inform one's understanding of a musical category? While categories of music can be difficult to define according to strict musical characteristics, a better understanding of…

Phoenix Violence Prevention Initiative.

ERIC Educational Resources Information Center

Waits, Mary Jo; Johnson, Ryan; Silverstein, Rustin

This report describes seven categories of violent crime in Phoenix, Arizona, and provides causes, facts, preventative programs, and lessons learned pertaining to each category of violence. The categories are: (1) prenatal and early childhood; (2) families; (3) individual youth; (4) schools; (5) neighborhood and community; (6) workplace; and (7)…

Effects of Reflection Category and Reflection Quality on Learning Outcomes during Web-Based Portfolio Assessment Process: A Case Study of High School Students in Computer Application Course

ERIC Educational Resources Information Center

Chou, Pao-Nan; Chang, Chi-Cheng

2011-01-01

This study examines the effects of reflection category and reflection quality on learning outcomes during Web-based portfolio assessment process. Experimental subjects consist of forty-five eight-grade students in a "Computer Application" course. Through the Web-based portfolio assessment system, these students write reflection, and join…

The Use and Ranking of Different English Language Learning Strategies by English Major Iranian Female University Level Learners

ERIC Educational Resources Information Center

Fazeli, Seyed Hossein

2012-01-01

This study aims to rank types of English language learning strategies that are used by Iranian female university level learners of English language as a university major. The results show that except for the Metacognitive Strategies category, the mean score for each of the five categories fell in the range of medium strategy use.

A History of Space Toxicology Mishaps: Lessons Learned and Risk Management

NASA Technical Reports Server (NTRS)

James, John T.

2009-01-01

After several decades of human spaceflight, the community of space-faring nations has accumulated a diverse and sometimes harrowing history of toxicological events that have plagued human space endeavors almost from the very beginning. Lessons have been learned in ground-based test beds and others were discovered the hard way - when human lives were at stake in space. From such lessons one can build a risk-management framework for toxicological events to minimize the probability of a harmful exposure, while recognizing that we cannot foresee all events. Space toxicologists have learned that relatively harmless compounds can be converted by air revitalization systems into compounds that cause serious harm to the crew. Our toxic risk management strategy now includes an assessment of the fate of any compound that might be released into the atmosphere. Propellants are highly toxic compounds, yet we have not always been able to thoroughly isolate the crew from exposure to these toxicants. Leakage of fluids from systems has resulted in hazardous conditions at times, and the behavior of such compounds inside a spacecraft has taught us how to manage potentially harmful escapes should they occur. Potential combustion events are an ever-present threat to the wellbeing of the crew. Such events have been sufficiently common that we have learned that one cannot judge the health threat of a given fire by the magnitude of the event. Management of such risks demands monitoring of combustion products. In the category of unpredictable toxic events, if one assumes that fires are predictable, we can place experience with toxic microbial metabolites, upsets during repair operations, and discharges from filters that have accumulated a substantial load of pollutants in their absorption beds. Management of such events requires a broad-spectrum, real-time analytical capability to discern the identity and concentrations of pollutants if they enter the atmosphere. Adverse events are an integral part of any human activity, and the spacefaring community must learn as much as possible from mistakes and near misses.

Systematicity and a Categorical Theory of Cognitive Architecture: Universal Construction in Context

PubMed Central

Phillips, Steven; Wilson, William H.

2016-01-01

Why does the capacity to think certain thoughts imply the capacity to think certain other, structurally related, thoughts? Despite decades of intensive debate, cognitive scientists have yet to reach a consensus on an explanation for this property of cognitive architecture—the basic processes and modes of composition that together afford cognitive capacity—called systematicity. Systematicity is generally considered to involve a capacity to represent/process common structural relations among the equivalently cognizable entities. However, the predominant theoretical approaches to the systematicity problem, i.e., classical (symbolic) and connectionist (subsymbolic), require arbitrary (ad hoc) assumptions to derive systematicity. That is, their core principles and assumptions do not provide the necessary and sufficient conditions from which systematicity follows, as required of a causal theory. Hence, these approaches fail to fully explain why systematicity is a (near) universal property of human cognition, albeit in restricted contexts. We review an alternative, category theory approach to the systematicity problem. As a mathematical theory of structure, category theory provides necessary and sufficient conditions for systematicity in the form of universal construction: each systematically related cognitive capacity is composed of a common component and a unique component. Moreover, every universal construction can be viewed as the optimal construction in the given context (category). From this view, universal constructions are derived from learning, as an optimization. The ultimate challenge, then, is to explain the determination of context. If context is a category, then a natural extension toward addressing this question is higher-order category theory, where categories themselves are the objects of construction. PMID:27524975

Systematicity and a Categorical Theory of Cognitive Architecture: Universal Construction in Context.

PubMed

Phillips, Steven; Wilson, William H

2016-01-01

Why does the capacity to think certain thoughts imply the capacity to think certain other, structurally related, thoughts? Despite decades of intensive debate, cognitive scientists have yet to reach a consensus on an explanation for this property of cognitive architecture-the basic processes and modes of composition that together afford cognitive capacity-called systematicity. Systematicity is generally considered to involve a capacity to represent/process common structural relations among the equivalently cognizable entities. However, the predominant theoretical approaches to the systematicity problem, i.e., classical (symbolic) and connectionist (subsymbolic), require arbitrary (ad hoc) assumptions to derive systematicity. That is, their core principles and assumptions do not provide the necessary and sufficient conditions from which systematicity follows, as required of a causal theory. Hence, these approaches fail to fully explain why systematicity is a (near) universal property of human cognition, albeit in restricted contexts. We review an alternative, category theory approach to the systematicity problem. As a mathematical theory of structure, category theory provides necessary and sufficient conditions for systematicity in the form of universal construction: each systematically related cognitive capacity is composed of a common component and a unique component. Moreover, every universal construction can be viewed as the optimal construction in the given context (category). From this view, universal constructions are derived from learning, as an optimization. The ultimate challenge, then, is to explain the determination of context. If context is a category, then a natural extension toward addressing this question is higher-order category theory, where categories themselves are the objects of construction.

The Science of Home Automation

NASA Astrophysics Data System (ADS)

Thomas, Brian Louis

Smart home technologies and the concept of home automation have become more popular in recent years. This popularity has been accompanied by social acceptance of passive sensors installed throughout the home. The subsequent increase in smart homes facilitates the creation of home automation strategies. We believe that home automation strategies can be generated intelligently by utilizing smart home sensors and activity learning. In this dissertation, we hypothesize that home automation can benefit from activity awareness. To test this, we develop our activity-aware smart automation system, CARL (CASAS Activity-aware Resource Learning). CARL learns the associations between activities and device usage from historical data and utilizes the activity-aware capabilities to control the devices. To help validate CARL we deploy and test three different versions of the automation system in a real-world smart environment. To provide a foundation of activity learning, we integrate existing activity recognition and activity forecasting into CARL home automation. We also explore two alternatives to using human-labeled data to train the activity learning models. The first unsupervised method is Activity Detection, and the second is a modified DBSCAN algorithm that utilizes Dynamic Time Warping (DTW) as a distance metric. We compare the performance of activity learning with human-defined labels and with automatically-discovered activity categories. To provide evidence in support of our hypothesis, we evaluate CARL automation in a smart home testbed. Our results indicate that home automation can be boosted through activity awareness. We also find that the resulting automation has a high degree of usability and comfort for the smart home resident.

Collaborative project-based learning: an integrative science and technological education project

NASA Astrophysics Data System (ADS)

Baser, Derya; Ozden, M. Yasar; Karaarslan, Hasan

2017-04-01

Background: Blending collaborative learning and project-based learning (PBL) based on Wolff (2003) design categories, students interacted in a learning environment where they developed their technology integration practices as well as their technological and collaborative skills.

"What is relevant in a text document?": An interpretable machine learning approach

PubMed Central

Arras, Leila; Horn, Franziska; Montavon, Grégoire; Müller, Klaus-Robert

2017-01-01

Text documents can be described by a number of abstract concepts such as semantic category, writing style, or sentiment. Machine learning (ML) models have been trained to automatically map documents to these abstract concepts, allowing to annotate very large text collections, more than could be processed by a human in a lifetime. Besides predicting the text’s category very accurately, it is also highly desirable to understand how and why the categorization process takes place. In this paper, we demonstrate that such understanding can be achieved by tracing the classification decision back to individual words using layer-wise relevance propagation (LRP), a recently developed technique for explaining predictions of complex non-linear classifiers. We train two word-based ML models, a convolutional neural network (CNN) and a bag-of-words SVM classifier, on a topic categorization task and adapt the LRP method to decompose the predictions of these models onto words. Resulting scores indicate how much individual words contribute to the overall classification decision. This enables one to distill relevant information from text documents without an explicit semantic information extraction step. We further use the word-wise relevance scores for generating novel vector-based document representations which capture semantic information. Based on these document vectors, we introduce a measure of model explanatory power and show that, although the SVM and CNN models perform similarly in terms of classification accuracy, the latter exhibits a higher level of explainability which makes it more comprehensible for humans and potentially more useful for other applications. PMID:28800619

Deep Learning with Convolutional Neural Network for Differentiation of Liver Masses at Dynamic Contrast-enhanced CT: A Preliminary Study.

PubMed

Yasaka, Koichiro; Akai, Hiroyuki; Abe, Osamu; Kiryu, Shigeru

2018-03-01

Purpose To investigate diagnostic performance by using a deep learning method with a convolutional neural network (CNN) for the differentiation of liver masses at dynamic contrast agent-enhanced computed tomography (CT). Materials and Methods This clinical retrospective study used CT image sets of liver masses over three phases (noncontrast-agent enhanced, arterial, and delayed). Masses were diagnosed according to five categories (category A, classic hepatocellular carcinomas [HCCs]; category B, malignant liver tumors other than classic and early HCCs; category C, indeterminate masses or mass-like lesions [including early HCCs and dysplastic nodules] and rare benign liver masses other than hemangiomas and cysts; category D, hemangiomas; and category E, cysts). Supervised training was performed by using 55 536 image sets obtained in 2013 (from 460 patients, 1068 sets were obtained and they were augmented by a factor of 52 [rotated, parallel-shifted, strongly enlarged, and noise-added images were generated from the original images]). The CNN was composed of six convolutional, three maximum pooling, and three fully connected layers. The CNN was tested with 100 liver mass image sets obtained in 2016 (74 men and 26 women; mean age, 66.4 years ± 10.6 [standard deviation]; mean mass size, 26.9 mm ± 25.9; 21, nine, 35, 20, and 15 liver masses for categories A, B, C, D, and E, respectively). Training and testing were performed five times. Accuracy for categorizing liver masses with CNN model and the area under receiver operating characteristic curve for differentiating categories A-B versus categories C-E were calculated. Results Median accuracy of differential diagnosis of liver masses for test data were 0.84. Median area under the receiver operating characteristic curve for differentiating categories A-B from C-E was 0.92. Conclusion Deep learning with CNN showed high diagnostic performance in differentiation of liver masses at dynamic CT. © RSNA, 2017 Online supplemental material is available for this article.

Naming and Categorization in Young Children: IV: Listener Behavior Training and Transfer of Function

PubMed Central

Horne, Pauline J; Hughes, J. Carl; Lowe, C. Fergus

2006-01-01

Following pretraining with everyday objects, 14 children aged from 1 to 4 years were trained, for each of three pairs of different arbitrary wooden shapes (Set 1), to select one stimulus in response to the spoken word /zog/, and the other to /vek/. When given a test for the corresponding tacts (“zog” and “vek”), 10 children passed, showing that they had learned common names for the stimuli, and 4 failed. All children were trained to clap to one stimulus of Pair 1 and wave to the other. All those who named showed either transfer of the novel functions to the remaining two pairs of stimuli in Test 1, or novel function comprehension for all three pairs in Test 2, or both. Three of these children next participated in, and passed, category match-to-sample tests. In contrast, all 4 children who had learned only listener behavior failed both the category transfer and category match-to-sample tests. When 3 of them were next trained to name the stimuli, they passed the category transfer and (for the 2 subjects tested) category match-to-sample tests. Three children were next trained on the common listener relations with another set of arbitrary stimuli (Set 2); all succeeded on the tact and category tests with the Set 2 stimuli. Taken together with the findings from the other studies in the series, the present experiment shows that (a) common listener training also establishes the corresponding names in some but not all children, and (b) only children who learn common names categorize; all those who learn only listener behavior fail. This is good evidence in support of the naming account of categorization. PMID:16673828

Development of Category-based Induction and Semantic Knowledge

ERIC Educational Resources Information Center

Fisher, Anna V.; Godwin, Karrie E.; Matlen, Bryan J.; Unger, Layla

2015-01-01

Category-based induction is a hallmark of mature cognition; however, little is known about its origins. This study evaluated the hypothesis that category-based induction is related to semantic development. Computational studies suggest that early on there is little differentiation among concepts, but learning and development lead to increased…

How do People Solve the “Weather Prediction” Task?: Individual Variability in Strategies for Probabilistic Category Learning

PubMed Central

Gluck, Mark A.; Shohamy, Daphna; Myers, Catherine

2002-01-01

Probabilistic category learning is often assumed to be an incrementally learned cognitive skill, dependent on nondeclarative memory systems. One paradigm in particular, the weather prediction task, has been used in over half a dozen neuropsychological and neuroimaging studies to date. Because of the growing interest in using this task and others like it as behavioral tools for studying the cognitive neuroscience of cognitive skill learning, it becomes especially important to understand how subjects solve this kind of task and whether all subjects learn it in the same way. We present here new experimental and theoretical analyses of the weather prediction task that indicate that there are at least three different strategies that describe how subjects learn this task. (1) An optimal multi-cue strategy, in which they respond to each pattern on the basis of associations of all four cues with each outcome; (2) a one-cue strategy, in which they respond on the basis of presence or absence of a single cue, disregarding all other cues; or (3) a singleton strategy, in which they learn only about the four patterns that have only one cue present and all others absent. This variability in how subjects approach this task may have important implications for interpreting how different brain regions are involved in probabilistic category learning. PMID:12464701

Non-linguistic learning and aphasia: Evidence from a paired associate and feedback-based task

PubMed Central

Vallila-Rohter, Sofia; Kiran, Swathi

2013-01-01

Though aphasia is primarily characterized by impairments in the comprehension and/or expression of language, research has shown that patients with aphasia also show deficits in cognitive-linguistic domains such as attention, executive function, concept knowledge and memory (Helm-Estabrooks, 2002 for review). Research in aphasia suggests that cognitive impairments can impact the online construction of language, new verbal learning, and transactional success (Freedman & Martin, 2001; Hula & McNeil, 2008; Ramsberger, 2005). In our research, we extend this hypothesis to suggest that general cognitive deficits influence progress with therapy. The aim of our study is to explore learning, a cognitive process that is integral to relearning language, yet underexplored in the field of aphasia rehabilitation. We examine non-linguistic category learning in patients with aphasia (n=19) and in healthy controls (n=12), comparing feedback and non-feedback based instruction. Participants complete two computer-based learning tasks that require them to categorize novel animals based on the percentage of features shared with one of two prototypes. As hypothesized, healthy controls showed successful category learning following both methods of instruction. In contrast, only 60% of our patient population demonstrated successful non-linguistic category learning. Patient performance was not predictable by standardized measures of cognitive ability. Results suggest that general learning is affected in aphasia and is a unique, important factor to consider in the field of aphasia rehabilitation. PMID:23127795

Predicting the Valence of a Scene from Observers’ Eye Movements

PubMed Central

R.-Tavakoli, Hamed; Atyabi, Adham; Rantanen, Antti; Laukka, Seppo J.; Nefti-Meziani, Samia; Heikkilä, Janne

2015-01-01

Multimedia analysis benefits from understanding the emotional content of a scene in a variety of tasks such as video genre classification and content-based image retrieval. Recently, there has been an increasing interest in applying human bio-signals, particularly eye movements, to recognize the emotional gist of a scene such as its valence. In order to determine the emotional category of images using eye movements, the existing methods often learn a classifier using several features that are extracted from eye movements. Although it has been shown that eye movement is potentially useful for recognition of scene valence, the contribution of each feature is not well-studied. To address the issue, we study the contribution of features extracted from eye movements in the classification of images into pleasant, neutral, and unpleasant categories. We assess ten features and their fusion. The features are histogram of saccade orientation, histogram of saccade slope, histogram of saccade length, histogram of saccade duration, histogram of saccade velocity, histogram of fixation duration, fixation histogram, top-ten salient coordinates, and saliency map. We utilize machine learning approach to analyze the performance of features by learning a support vector machine and exploiting various feature fusion schemes. The experiments reveal that ‘saliency map’, ‘fixation histogram’, ‘histogram of fixation duration’, and ‘histogram of saccade slope’ are the most contributing features. The selected features signify the influence of fixation information and angular behavior of eye movements in the recognition of the valence of images. PMID:26407322

Mild Perceptual Categorization Deficits Follow Bilateral Removal of Anterior Inferior Temporal Cortex in Rhesus Monkeys.

PubMed

Matsumoto, Narihisa; Eldridge, Mark A G; Saunders, Richard C; Reoli, Rachel; Richmond, Barry J

2016-01-06

In primates, visual recognition of complex objects depends on the inferior temporal lobe. By extension, categorizing visual stimuli based on similarity ought to depend on the integrity of the same area. We tested three monkeys before and after bilateral anterior inferior temporal cortex (area TE) removal. Although mildly impaired after the removals, they retained the ability to assign stimuli to previously learned categories, e.g., cats versus dogs, and human versus monkey faces, even with trial-unique exemplars. After the TE removals, they learned in one session to classify members from a new pair of categories, cars versus trucks, as quickly as they had learned the cats versus dogs before the removals. As with the dogs and cats, they generalized across trial-unique exemplars of cars and trucks. However, as seen in earlier studies, these monkeys with TE removals had difficulty learning to discriminate between two simple black and white stimuli. These results raise the possibility that TE is needed for memory of simple conjunctions of basic features, but that it plays only a small role in generalizing overall configural similarity across a large set of stimuli, such as would be needed for perceptual categorical assignment. The process of seeing and recognizing objects is attributed to a set of sequentially connected brain regions stretching forward from the primary visual cortex through the temporal lobe to the anterior inferior temporal cortex, a region designated area TE. Area TE is considered the final stage for recognizing complex visual objects, e.g., faces. It has been assumed, but not tested directly, that this area would be critical for visual generalization, i.e., the ability to place objects such as cats and dogs into their correct categories. Here, we demonstrate that monkeys rapidly and seemingly effortlessly categorize large sets of complex images (cats vs dogs, cars vs trucks), surprisingly, even after removal of area TE, leaving a puzzle about how this generalization is done. Copyright © 2016 the authors 0270-6474/16/360043-11$15.00/0.

Dissociating hippocampal and basal ganglia contributions to category learning using stimulus novelty and subjective judgments

PubMed Central

Seger, Carol A.; Dennison, Christina S.; Lopez-Paniagua, Dan; Peterson, Erik J.; Roark, Aubrey A.

2011-01-01

We identified factors leading to hippocampal and basal ganglia recruitment during categorization learning. Subjects alternated between blocks of a standard trial and error category learning task and a subjective judgment task. In the subjective judgments task subjects categorized the stimulus and then instead of receiving feedback they indicated the basis of their response using 4 options: Remember: Conscious episodic memory of previous trials. Know-Automatic: Automatic, rapid response accompanied by conscious awareness of category membership. Know-Intuition: A “gut feeling” without fully conscious knowledge of category membership. Guess: Guessing. In addition, new stimuli were introduced throughout the experiment to examine effects of novelty. Categorization overall recruited both the basal ganglia and posterior hippocampus. However, basal ganglia activity was found during Know judgments (both Automatic and Intuition), whereas posterior hippocampus activity was found during Remember judgments. Granger causality mapping indicated interactions between the basal ganglia and hippocampus, with the putamen exerting directed influence on the posterior hippocampus, which in turn exerted directed influence on the posterior caudate nucleus. We also found a region of anterior hippocampus that showed decreased activity relative to baseline during categorization overall, and showed a strong novelty effect. Our results indicate that subjective measures may be effective in dissociating basal ganglia from hippocampal dependent learning, and that the basal ganglia are involved in both conscious and unconscious learning. They also indicate a dissociation within the hippocampus, in which the anterior regions are sensitive to novelty, and the posterior regions are involved in memory based categorization learning. PMID:21255655

Smartphone-Based Patients' Activity Recognition by Using a Self-Learning Scheme for Medical Monitoring.

PubMed

Guo, Junqi; Zhou, Xi; Sun, Yunchuan; Ping, Gong; Zhao, Guoxing; Li, Zhuorong

2016-06-01

Smartphone based activity recognition has recently received remarkable attention in various applications of mobile health such as safety monitoring, fitness tracking, and disease prediction. To achieve more accurate and simplified medical monitoring, this paper proposes a self-learning scheme for patients' activity recognition, in which a patient only needs to carry an ordinary smartphone that contains common motion sensors. After the real-time data collection though this smartphone, we preprocess the data using coordinate system transformation to eliminate phone orientation influence. A set of robust and effective features are then extracted from the preprocessed data. Because a patient may inevitably perform various unpredictable activities that have no apriori knowledge in the training dataset, we propose a self-learning activity recognition scheme. The scheme determines whether there are apriori training samples and labeled categories in training pools that well match with unpredictable activity data. If not, it automatically assembles these unpredictable samples into different clusters and gives them new category labels. These clustered samples combined with the acquired new category labels are then merged into the training dataset to reinforce recognition ability of the self-learning model. In experiments, we evaluate our scheme using the data collected from two postoperative patient volunteers, including six labeled daily activities as the initial apriori categories in the training pool. Experimental results demonstrate that the proposed self-learning scheme for activity recognition works very well for most cases. When there exist several types of unseen activities without any apriori information, the accuracy reaches above 80 % after the self-learning process converges.

Informal Learning after Organizational Change

ERIC Educational Resources Information Center

Reardon, Robert F.

2004-01-01

This inductive, qualitative study investigates how learning took place among nine experienced engineers in an industrial setting after a major reorganization. A thematic analysis of the transcripts revealed that the learning was informal and that it fell into three distinct categories: learning new workflows, learning about the chemical process,…

Repeated imitation makes human vocalizations more word-like.

PubMed

Edmiston, Pierce; Perlman, Marcus; Lupyan, Gary

2018-03-14

People have long pondered the evolution of language and the origin of words. Here, we investigate how conventional spoken words might emerge from imitations of environmental sounds. Does the repeated imitation of an environmental sound gradually give rise to more word-like forms? In what ways do these forms resemble the original sounds that motivated them (i.e. exhibit iconicity)? Participants played a version of the children's game 'Telephone'. The first generation of participants imitated recognizable environmental sounds (e.g. glass breaking, water splashing). Subsequent generations imitated the previous generation of imitations for a maximum of eight generations. The results showed that the imitations became more stable and word-like, and later imitations were easier to learn as category labels. At the same time, even after eight generations, both spoken imitations and their written transcriptions could be matched above chance to the category of environmental sound that motivated them. These results show how repeated imitation can create progressively more word-like forms while continuing to retain a resemblance to the original sound that motivated them, and speak to the possible role of human vocal imitation in explaining the origins of at least some spoken words. © 2018 The Author(s).

The impact of CmapTools utilization towards students' conceptual change on optics topic

NASA Astrophysics Data System (ADS)

Rofiuddin, Muhammad Rifqi; Feranie, Selly

2017-05-01

Science teachers need to help students identify their prior ideas and modify them based on scientific knowledge. This process is called as conceptual change. One of essential tools to analyze students' conceptual change is by using concept map. Concept Maps are graphical representations of knowledge that are comprised of concepts and the relationships between them. Constructing concept map is implemented by adapting the role of technology to support learning process, as it is suitable with Educational Ministry Regulation No.68 year 2013. Institute for Human and Machine Cognition (IHMC) has developed CmapTools, a client-server software for easily construct and visualize concept maps. This research aims to investigate secondary students' conceptual change after experiencing five-stage conceptual teaching model by utilizing CmapTools in learning Optics. Weak experimental method through one group pretest-posttest design is implemented in this study to collect preliminary and post concept map as qualitative data. Sample was taken purposively of 8th grade students (n= 22) at one of private schools Bandung, West Java. Conceptual change based on comparison of preliminary and post concept map construction is assessed based on rubric of concept map scoring and structure. Results shows significance conceptual change differences at 50.92 % that is elaborated into concept map element such as prepositions and hierarchical level in high category, cross links in medium category and specific examples in low category. All of the results are supported with the students' positive response towards CmapTools utilization that indicates improvement of motivation, interest, and behavior aspect towards Physics lesson.

Search for Patterns of Functional Specificity in the Brain: A Nonparametric Hierarchical Bayesian Model for Group fMRI Data

PubMed Central

Sridharan, Ramesh; Vul, Edward; Hsieh, Po-Jang; Kanwisher, Nancy; Golland, Polina

2012-01-01

Functional MRI studies have uncovered a number of brain areas that demonstrate highly specific functional patterns. In the case of visual object recognition, small, focal regions have been characterized with selectivity for visual categories such as human faces. In this paper, we develop an algorithm that automatically learns patterns of functional specificity from fMRI data in a group of subjects. The method does not require spatial alignment of functional images from different subjects. The algorithm is based on a generative model that comprises two main layers. At the lower level, we express the functional brain response to each stimulus as a binary activation variable. At the next level, we define a prior over sets of activation variables in all subjects. We use a Hierarchical Dirichlet Process as the prior in order to learn the patterns of functional specificity shared across the group, which we call functional systems, and estimate the number of these systems. Inference based on our model enables automatic discovery and characterization of dominant and consistent functional systems. We apply the method to data from a visual fMRI study comprised of 69 distinct stimulus images. The discovered system activation profiles correspond to selectivity for a number of image categories such as faces, bodies, and scenes. Among systems found by our method, we identify new areas that are deactivated by face stimuli. In empirical comparisons with perviously proposed exploratory methods, our results appear superior in capturing the structure in the space of visual categories of stimuli. PMID:21884803

The competency of internists in holistic global care to support healthy Indonesia 2010.

PubMed

Rudijanto, Achmad

2006-01-01

All patients are entitled to good standards of practice and care from their doctors. The improved health of all peoples is the main goal of medical education, including for the education of internal medicine registrars. The future development of the direction and goal of education, the level of competence of internal medicine specialists, and the process of learning will be related to preparing the internal medicine specialist to have global competitive advantage. Identification of general competencies is the first step in a long-term effort designed to emphasize educational outcome, for assessment in residency programs, and in the accreditation process. To achieve that competence, a variety of learning opportunities need to be provided in order that the resident can achieve the necessary knowledge, skills, attitude, and behaviors. Identification of the role and function of internal medicine specialists is needed prior to the development of the general competencies. As educational objectives, the competencies fall into two main categories: knowledge-based and performance-based. Knowledge-based competency has two components, medical knowledge (bio-science and clinical medicine) and contextual knowledge (epidemiology, health service organization, and human behavior). The performance base has two components, intellectual skills and the interpersonal skills. Besides the two main categories of educational objectives, there are behavioral objectives that residents must achieve through the educational program, to ensure that residents are able to deal with a range of prescribed clinical situations effectively, safely, humanely, and economically. The achievement of behavioral objectives will ensure, at least in part, that the doctor will implement good medical practice. The index clinical/community situations (ICS) on which the educational objectives will be based are taken from diseases and illnesses that occur in clinical and community settings. No resident can master all medicine there is to know, as there are no limits to what can be known about medicine. It is important to make choices in selecting what residents should learn by analyzing the ICS.

A Continuum of Learning: From Rote Memorization to Meaningful Learning in Organic Chemistry

ERIC Educational Resources Information Center

Grove, Nathaniel P.; Bretz, Stacey Lowery

2012-01-01

The Assimilation Theory of Ausubel and Novak has typically been used in the research literature to describe two extremes to learning chemistry: meaningful learning "versus" rote memorization. It is unlikely, however, that such discrete categories of learning exist. Rote and meaningful learning, rather, are endpoints along a continuum of…

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features

PubMed Central

Liu, Zhiya; Song, Xiaohong; Seger, Carol A.

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting. PMID:26274332

An Eye-Tracking Study of Multiple Feature Value Category Structure Learning: The Role of Unique Features.

PubMed

Liu, Zhiya; Song, Xiaohong; Seger, Carol A

2015-01-01

We examined whether the degree to which a feature is uniquely characteristic of a category can affect categorization above and beyond the typicality of the feature. We developed a multiple feature value category structure with different dimensions within which feature uniqueness and typicality could be manipulated independently. Using eye tracking, we found that the highest attentional weighting (operationalized as number of fixations, mean fixation time, and the first fixation of the trial) was given to a dimension that included a feature that was both unique and highly typical of the category. Dimensions that included features that were highly typical but not unique, or were unique but not highly typical, received less attention. A dimension with neither a unique nor a highly typical feature received least attention. On the basis of these results we hypothesized that subjects categorized via a rule learning procedure in which they performed an ordered evaluation of dimensions, beginning with unique and strongly typical dimensions, and in which earlier dimensions received higher weighting in the decision. This hypothesis accounted for performance on transfer stimuli better than simple implementations of two other common theories of category learning, exemplar models and prototype models, in which all dimensions were evaluated in parallel and received equal weighting.

Teacher Professional Learning: Developing with the Aid of Technology

ERIC Educational Resources Information Center

Kyprianou, Marianna; Nikiforou, Eleni

2016-01-01

Education is a field that constantly changes, which dictates the need for continuing teacher professional learning and development. Teacher professional learning and development can be divided into two categories: formal learning/ development and informal learning/development. This paper focuses on the experience of the presenters as coordinators…

What is automatized during perceptual categorization?

PubMed Central

Roeder, Jessica L.; Ashby, F. Gregory

2016-01-01

An experiment is described that tested whether stimulus-response associations or an abstract rule are automatized during extensive practice at perceptual categorization. Twenty-seven participants each completed 12,300 trials of perceptual categorization, either on rule-based (RB) categories that could be learned explicitly or information-integration (II) categories that required procedural learning. Each participant practiced predominantly on a primary category structure, but every third session they switched to a secondary structure that used the same stimuli and responses. Half the stimuli retained their same response on the primary and secondary categories (the congruent stimuli) and half switched responses (the incongruent stimuli). Several results stood out. First, performance on the primary categories met the standard criteria of automaticity by the end of training. Second, for the primary categories in the RB condition, accuracy and response time (RT) were identical on congruent and incongruent stimuli. In contrast, for the primary II categories, accuracy was higher and RT was lower for congruent than for incongruent stimuli. These results are consistent with the hypothesis that rules are automatized in RB tasks, whereas stimulus-response associations are automatized in II tasks. A cognitive neuroscience theory is proposed that accounts for these results. PMID:27232521

Managerial Skills Teaching: Ten Questions and Answers.

ERIC Educational Resources Information Center

McEnrue, Mary Pat

2002-01-01

Presents considerations for design and delivery of management skills courses as sets of questions in three categories: (1) preteaching (understanding and teaching skills, teacher qualities); (2) class (skills learning, learning barriers, cultural elements, learning assessment); and application/evaluation (lifelong learning, course evaluation,…

The interaction of short-term and long-term memory in phonetic category formation

NASA Astrophysics Data System (ADS)

Harnsberger, James D.

2002-05-01

This study examined the role that short-term memory capacity plays in the relationship between novel stimuli (e.g., non-native speech sounds, native nonsense words) and phonetic categories in long-term memory. Thirty native speakers of American English were administered five tests: categorial AXB discrimination using nasal consonants from Malayalam; categorial identification, also using Malayalam nasals, which measured the influence of phonetic categories in long-term memory; digit span; nonword span, a short-term memory measure mediated by phonetic categories in long-term memory; and paired-associate word learning (word-word and word-nonword pairs). The results showed that almost all measures were significantly correlated with one another. The strongest predictor for the discrimination and word-nonword learning results was nonword (r=+0.62) and digit span (r=+0.51), respectively. When the identification test results were partialed out, only nonword span significantly correlated with discrimination. The results show a strong influence of short-term memory capacity on the encoding of phonetic detail within phonetic categories and suggest that long-term memory representations regulate the capacity of short-term memory to preserve information for subsequent encoding. The results of this study will also be discussed with regards to resolving the tension between episodic and abstract models of phonetic category structure.

Property content guides children's memory for social learning episodes.

PubMed

Riggs, Anne E; Kalish, Charles W; Alibali, Martha W

2014-05-01

How do children's interpretations of the generality of learning episodes affect what they encode? In the present studies, we investigated the hypothesis that children encode distinct aspects of learning episodes containing generalizable and non-generalizable properties. Two studies with preschool (N=50) and young school-aged children (N=49) reveal that their encoding is contingent on the generalizability of the property they are learning. Children remembered generalizable properties (e.g., morphological or normative properties) more than non-generalizable properties (e.g., historical events or preferences). Conversely, they remembered category exemplars associated with non-generalizable properties more than category exemplars associated with generalizable properties. The findings highlight the utility of remembering distinct aspects of social learning episodes for children's future generalization. Copyright © 2014 Elsevier B.V. All rights reserved.

Learning words and learning sounds: Advances in language development.

PubMed

Vihman, Marilyn M

2017-02-01

Phonological development is sometimes seen as a process of learning sounds, or forming phonological categories, and then combining sounds to build words, with the evidence taken largely from studies demonstrating 'perceptual narrowing' in infant speech perception over the first year of life. In contrast, studies of early word production have long provided evidence that holistic word learning may precede the formation of phonological categories. In that account, children begin by matching their existing vocal patterns to adult words, with knowledge of the phonological system emerging from the network of related word forms. Here I review evidence from production and then consider how the implicit and explicit learning mechanisms assumed by the complementary memory systems model might be understood as reconciling the two approaches. © 2016 The British Psychological Society.

Behavioral and anatomical consequences of early versus late symbol training in macaques.

PubMed

Srihasam, Krishna; Mandeville, Joseph B; Morocz, Istvan A; Sullivan, Kevin J; Livingstone, Margaret S

2012-02-09

Distinct brain regions, reproducible from one person to the next, are specialized for processing different kinds of human expertise, such as face recognition and reading. Here, we explore the relationship between age of learning, learning ability, and specialized brain structures. Specifically, we ask whether the existence of reproducible cortical domains necessarily means that certain abilities are innate, or innately easily learned, or whether reproducible domains can be formed, or refined, by interactions between genetic programs and common early experience. Functional MRI showed that intensive early, but not late, experience caused the formation of category-selective regions in macaque temporal lobe for stimuli never naturally encountered by monkeys. And behaviorally, early training produced more fluent processing of these stimuli than the same training in adults. One explanation for these results is that in higher cortical areas, as in early sensory areas, experience drives functional clustering and functional clustering determines how that information is processed. Copyright © 2012 Elsevier Inc. All rights reserved.

A grounded theory of faculty's use of humanization to create online course climate.

PubMed

Cox-Davenport, Rebecca A

2014-03-01

The purpose of this research was to study the way faculty establish course social presence in an online course. The community of inquiry model by Garrison, Anderson, and Archer distinguished the area of social presence as an important component of online learning, and this study sought to understand how faculty perceive and create social presence in their online classroom. By employing a grounded theory approach, a substantive theory was developed to explain the way in which faculty create and maintain an online course climate. The sample consisted of 10 nursing faculty teaching various master's in nursing courses. Through a rigorous qualitative process using nursing faculty interviews and online course analysis, humanization was found to be the core category in setting online course climate. Faculty's efforts to humanize the climate lead each member of the community to view the other members as real, thereby enabling the establishment of online social presence.

Human Factors Checklist: Think Human Factors - Focus on the People

NASA Technical Reports Server (NTRS)

Miller, Darcy; Stelges, Katrine; Barth, Timothy; Stambolian, Damon; Henderson, Gena; Dischinger, Charles; Kanki, Barbara; Kramer, Ian

2016-01-01

A quick-look Human Factors (HF) Checklist condenses industry and NASA Agency standards consisting of thousands of requirements into 14 main categories. With support from contractor HF and Safety Practitioners, NASA developed a means to share key HF messages with Design, Engineering, Safety, Project Management, and others. It is often difficult to complete timely assessments due to the large volume of HF information. The HF Checklist evolved over time into a simple way to consider the most important concepts. A wide audience can apply the checklist early in design or through planning phases, even before hardware or processes are finalized or implemented. The checklist is a good place to start to supplement formal HF evaluation. The HF Checklist was based on many Space Shuttle processing experiences and lessons learned. It is now being applied to ground processing of new space vehicles and adjusted for new facilities and systems.

[Cognitive enrichment in farm animals--the impact of social rank and social environment on learning behaviour of dwarf goats].

PubMed

Baymann, Ulrike; Langbein, Jan; Siebert, Katrin; Nürnberg, Gerd; Manteuffel, Gerhard; Mohr, Elmar

2007-01-01

The influence of social rank and social environment on visual discrimination learning of small groups of Nigerian dwarf goats (Capra hircus, n = 79) was studied using a computer-controlled learning device integrated in the animals' home pen. The experiment was divided into three sections (LE1, LE1 u, LE2; each 14d). In LE1 the goats learned a discrimination task in a socially stable environment. In LE1u animals were mixed and relocated to another pen and given the same task as in LE1. In LE2 the animals were mixed and relocated again and given a new discrimination task. We used drinking water as a primary reinforcer. The rank category of the goats were analysed as alpha, omega or middle ranking for each section of the experiment. The rank category had an influence on daily learning success (percentage of successful trials per day) only in LE1 u. Daily learning success decreased after mixing and relocation of the animals in LE1 u and LE2 compared to LE1. That resulted in an undersupply of drinking water on the first day of both these tasks. We discuss social stress induced by agonistic interactions after mixing as a reason for that decline. The absolute learning performance (trials to reach the learning criterion) of the omega animals was lower in LE2 compared to the other rank categories. Furthermore, their absolute learning performance was lower in LE2 compared to LE1. For future application of similar automated learning devices in animal husbandry, we recommend against the combination of management routines like mixing and relocation with changes in the learning task because of the negative effects on learning performance, particularly of the omega animals.

Age distribution patterns of human gene families: divergent for Gene Ontology categories and concordant between different subcellular localizations.

PubMed

Liu, Gangbiao; Zou, Yangyun; Cheng, Qiqun; Zeng, Yanwu; Gu, Xun; Su, Zhixi

2014-04-01

The age distribution of gene duplication events within the human genome exhibits two waves of duplications along with an ancient component. However, because of functional constraint differences, genes in different functional categories might show dissimilar retention patterns after duplication. It is known that genes in some functional categories are highly duplicated in the early stage of vertebrate evolution. However, the correlations of the age distribution pattern of gene duplication between the different functional categories are still unknown. To investigate this issue, we developed a robust pipeline to date the gene duplication events in the human genome. We successfully estimated about three-quarters of the duplication events within the human genome, along with the age distribution pattern in each Gene Ontology (GO) slim category. We found that some GO slim categories show different distribution patterns when compared to the whole genome. Further hierarchical clustering of the GO slim functional categories enabled grouping into two main clusters. We found that human genes located in the duplicated copy number variant regions, whose duplicate genes have not been fixed in the human population, were mainly enriched in the groups with a high proportion of recently duplicated genes. Moreover, we used a phylogenetic tree-based method to date the age of duplications in three signaling-related gene superfamilies: transcription factors, protein kinases and G-protein coupled receptors. These superfamilies were expressed in different subcellular localizations. They showed a similar age distribution as the signaling-related GO slim categories. We also compared the differences between the age distributions of gene duplications in multiple subcellular localizations. We found that the distribution patterns of the major subcellular localizations were similar to that of the whole genome. This study revealed the whole picture of the evolution patterns of gene functional categories in the human genome.

Continual improvement: A bibliography with indexes, 1992-1993

NASA Technical Reports Server (NTRS)

1994-01-01

This bibliography lists 606 references to reports and journal articles entered into the NASA Scientific and Technical Information Database during 1992 to 1993. Topics cover the philosophy and history of Continual Improvement (CI), basic approaches and strategies for implementation, and lessons learned from public and private sector models. Entries are arranged according to the following categories: Leadership for Quality, Information and Analysis, Strategic Planning for CI, Human Resources Utilization, Management of Process Quality, Supplier Quality, Assessing Results, Customer Focus and Satisfaction, TQM Tools and Philosophies, and Applications. Indexes include subject, personal author, corporate source, contract number, report number, and accession number.

Rapid Categorization of Human and Ape Faces in 9-Month-Old Infants Revealed by Fast Periodic Visual Stimulation.

PubMed

Peykarjou, Stefanie; Hoehl, Stefanie; Pauen, Sabina; Rossion, Bruno

2017-10-02

This study investigates categorization of human and ape faces in 9-month-olds using a Fast Periodic Visual Stimulation (FPVS) paradigm while measuring EEG. Categorization responses are elicited only if infants discriminate between different categories and generalize across exemplars within each category. In study 1, human or ape faces were presented as standard and deviant stimuli in upright and inverted trials. Upright ape faces presented among humans elicited strong categorization responses, whereas responses for upright human faces and for inverted ape faces were smaller. Deviant inverted human faces did not elicit categorization. Data were best explained by a model with main effects of species and orientation. However, variance of low-level image characteristics was higher for the ape than the human category. Variance was matched to replicate this finding in an independent sample (study 2). Both human and ape faces elicited categorization in upright and inverted conditions, but upright ape faces elicited the strongest responses. Again, data were best explained by a model of two main effects. These experiments demonstrate that 9-month-olds rapidly categorize faces, and unfamiliar faces presented among human faces elicit increased categorization responses. This likely reflects habituation for the familiar standard category, and stronger release for the unfamiliar category deviants.

Picture-Word Differences in Discrimination Learning: 11. Effects of Conceptual Categories

ERIC Educational Resources Information Center

Bourne, Lyle E.; And Others

1976-01-01

Investigates the prediction that the usual superiority of pictures over words for repetitions of the same items would disappear for items that were different instances of repeated categories. (Author/RK)

Multi-categorical deep learning neural network to classify retinal images: A pilot study employing small database

PubMed Central

Seo, Jeong Gi; Kwak, Jiyong; Um, Terry Taewoong; Rim, Tyler Hyungtaek

2017-01-01

Deep learning emerges as a powerful tool for analyzing medical images. Retinal disease detection by using computer-aided diagnosis from fundus image has emerged as a new method. We applied deep learning convolutional neural network by using MatConvNet for an automated detection of multiple retinal diseases with fundus photographs involved in STructured Analysis of the REtina (STARE) database. Dataset was built by expanding data on 10 categories, including normal retina and nine retinal diseases. The optimal outcomes were acquired by using a random forest transfer learning based on VGG-19 architecture. The classification results depended greatly on the number of categories. As the number of categories increased, the performance of deep learning models was diminished. When all 10 categories were included, we obtained results with an accuracy of 30.5%, relative classifier information (RCI) of 0.052, and Cohen’s kappa of 0.224. Considering three integrated normal, background diabetic retinopathy, and dry age-related macular degeneration, the multi-categorical classifier showed accuracy of 72.8%, 0.283 RCI, and 0.577 kappa. In addition, several ensemble classifiers enhanced the multi-categorical classification performance. The transfer learning incorporated with ensemble classifier of clustering and voting approach presented the best performance with accuracy of 36.7%, 0.053 RCI, and 0.225 kappa in the 10 retinal diseases classification problem. First, due to the small size of datasets, the deep learning techniques in this study were ineffective to be applied in clinics where numerous patients suffering from various types of retinal disorders visit for diagnosis and treatment. Second, we found that the transfer learning incorporated with ensemble classifiers can improve the classification performance in order to detect multi-categorical retinal diseases. Further studies should confirm the effectiveness of algorithms with large datasets obtained from hospitals. PMID:29095872

Conditions for excellence in teaching in medical education: The Frankfurt Model to ensure quality in teaching and learning.

PubMed

Giesler, Marianne; Karsten, Gudrun; Ochsendorf, Falk; Breckwoldt, Jan

2017-01-01

Background: There is general consensus that the organizational and administrative aspects of academic study programs exert an important influence on teaching and learning. Despite this, no comprehensive framework currently exists to describe the conditions that affect the quality of teaching and learning in medical education. The aim of this paper is to systematically and comprehensively identify these factors to offer academic administrators and decision makers interested in improving teaching a theory-based and, to an extent, empirically founded framework on the basis of which improvements in teaching quality can be identified and implemented. Method: Primarily, the issue was addressed by combining a theory-driven deductive approach with an experience based, "best evidence" one during the course of two workshops held by the GMA Committee on Personnel and Organizational Development in Academic Teaching (POiL) in Munich (2013) and Frankfurt (2014). Two models describing the conditions relevant to teaching and learning (Euler/Hahn and Rindermann) were critically appraised and synthesized into a new third model. Practical examples of teaching strategies that promote or hinder learning were compiled and added to the categories of this model and, to the extent possible, supported with empirical evidence. Based on this, a checklist with recommendations for optimizing general academic conditions was formulated. Results: The Frankfurt Model of conditions to ensure Quality in Teaching and Learning covers six categories: organizational structure/medical school culture, regulatory frameworks, curricular requirements, time constraints, material and personnel resources, and qualification of teaching staff. These categories have been supplemented by the interests, motives and abilities of the actual teachers and students in this particular setting. The categories of this model provide the structure for a checklist in which recommendations for optimizing teaching are given. Conclusions: The checklist derived from the Frankfurt Model for ensuring quality in teaching and learning can be used for quality assurance and to improve the conditions under which teaching and learning take place in medical schools.

Triangular model integrating clinical teaching and assessment

PubMed Central

Abdelaziz, Adel; Koshak, Emad

2014-01-01

Structuring clinical teaching is a challenge facing medical education curriculum designers. A variety of instructional methods on different domains of learning are indicated to accommodate different learning styles. Conventional methods of clinical teaching, like training in ambulatory care settings, are prone to the factor of coincidence in having varieties of patient presentations. Accordingly, alternative methods of instruction are indicated to compensate for the deficiencies of these conventional methods. This paper presents an initiative that can be used to design a checklist as a blueprint to guide appropriate selection and implementation of teaching/learning and assessment methods in each of the educational courses and modules based on educational objectives. Three categories of instructional methods were identified, and within each a variety of methods were included. These categories are classroom-type settings, health services-based settings, and community service-based settings. Such categories have framed our triangular model of clinical teaching and assessment. PMID:24624002

Triangular model integrating clinical teaching and assessment.

PubMed

Abdelaziz, Adel; Koshak, Emad

2014-01-01

Structuring clinical teaching is a challenge facing medical education curriculum designers. A variety of instructional methods on different domains of learning are indicated to accommodate different learning styles. Conventional methods of clinical teaching, like training in ambulatory care settings, are prone to the factor of coincidence in having varieties of patient presentations. Accordingly, alternative methods of instruction are indicated to compensate for the deficiencies of these conventional methods. This paper presents an initiative that can be used to design a checklist as a blueprint to guide appropriate selection and implementation of teaching/learning and assessment methods in each of the educational courses and modules based on educational objectives. Three categories of instructional methods were identified, and within each a variety of methods were included. These categories are classroom-type settings, health services-based settings, and community service-based settings. Such categories have framed our triangular model of clinical teaching and assessment.

Learning Scene Categories from High Resolution Satellite Image for Aerial Video Analysis

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

Cheriyadat, Anil M

2011-01-01

Automatic scene categorization can benefit various aerial video processing applications. This paper addresses the problem of predicting the scene category from aerial video frames using a prior model learned from satellite imagery. We show that local and global features in the form of line statistics and 2-D power spectrum parameters respectively can characterize the aerial scene well. The line feature statistics and spatial frequency parameters are useful cues to distinguish between different urban scene categories. We learn the scene prediction model from highresolution satellite imagery to test the model on the Columbus Surrogate Unmanned Aerial Vehicle (CSUAV) dataset ollected bymore » high-altitude wide area UAV sensor platform. e compare the proposed features with the popular Scale nvariant Feature Transform (SIFT) features. Our experimental results show that proposed approach outperforms te SIFT model when the training and testing are conducted n disparate data sources.« less

Implicit Statistical Learning in Real-World Environments Leads to Ecologically Rational Decision Making.

PubMed

Perkovic, Sonja; Orquin, Jacob Lund

2018-01-01

Ecological rationality results from matching decision strategies to appropriate environmental structures, but how does the matching happen? We propose that people learn the statistical structure of the environment through observation and use this learned structure to guide ecologically rational behavior. We tested this hypothesis in the context of organic foods. In Study 1, we found that products from healthful food categories are more likely to be organic than products from nonhealthful food categories. In Study 2, we found that consumers' perceptions of the healthfulness and prevalence of organic products in many food categories are accurate. Finally, in Study 3, we found that people perceive organic products as more healthful than nonorganic products when the statistical structure justifies this inference. Our findings suggest that people believe organic foods are more healthful than nonorganic foods and use an organic-food cue to guide their behavior because organic foods are, on average, 30% more healthful.

Learning grammatical categories from distributional cues: flexible frames for language acquisition.

PubMed

St Clair, Michelle C; Monaghan, Padraic; Christiansen, Morten H

2010-09-01

Numerous distributional cues in the child's environment may potentially assist in language learning, but what cues are useful to the child and when are these cues utilised? We propose that the most useful source of distributional cue is a flexible frame surrounding the word, where the language learner integrates information from the preceding and the succeeding word for grammatical categorisation. In corpus analyses of child-directed speech together with computational models of category acquisition, we show that these flexible frames are computationally advantageous for language learning, as they benefit from the coverage of bigram information across a large proportion of the language environment as well as exploiting the enhanced accuracy of trigram information. Flexible frames are also consistent with the developmental trajectory of children's sensitivity to different sources of distributional information, and they are therefore a useful and usable information source for supporting the acquisition of grammatical categories. 2010 Elsevier B.V. All rights reserved.

Rapid visual perception of interracial crowds: Racial category learning from emotional segregation.

PubMed

Lamer, Sarah Ariel; Sweeny, Timothy D; Dyer, Michael Louis; Weisbuch, Max

2018-05-01

Drawing from research on social identity and ensemble coding, we theorize that crowd perception provides a powerful mechanism for social category learning. Crowds include allegiances that may be distinguished by visual cues to shared behavior and mental states, providing perceivers with direct information about social groups and thus a basis for learning social categories. Here, emotion expressions signaled group membership: to the extent that a crowd exhibited emotional segregation (i.e., was segregated into emotional subgroups), a visible characteristic (race) that incidentally distinguished emotional subgroups was expected to support categorical distinctions. Participants were randomly assigned to view interracial crowds in which emotion differences between (black vs. white) subgroups were either small (control condition) or large (emotional segregation condition). On each trial, participants saw crowds of 12 faces (6 black, 6 white) for roughly 300 ms and were asked to estimate the average emotion of the entire crowd. After all trials, participants completed a racial categorization task and self-report measure of race essentialism. As predicted, participants exposed to emotional segregation (vs. control) exhibited stronger racial category boundaries and stronger race essentialism. Furthermore, such effects accrued via ensemble coding, a visual mechanism that summarizes perceptual information: emotional segregation strengthened participants' racial category boundaries to the extent that segregation limited participants' abilities to integrate emotion across racial subgroups. Together with evidence that people observe emotional segregation in natural environments, these findings suggest that crowd perception mechanisms support racial category boundaries and race essentialism. (PsycINFO Database Record (c) 2018 APA, all rights reserved).

Advancing clinical reasoning in virtual patients - development and application of a conceptual framework.

PubMed

Hege, Inga; Kononowicz, Andrzej A; Berman, Norman B; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty.

Advancing clinical reasoning in virtual patients – development and application of a conceptual framework

PubMed Central

Hege, Inga; Kononowicz, Andrzej A.; Berman, Norman B.; Lenzer, Benedikt; Kiesewetter, Jan

2018-01-01

Background: Clinical reasoning is a complex skill students have to acquire during their education. For educators it is difficult to explain their reasoning to students, because it is partly an automatic and unconscious process. Virtual Patients (VPs) are used to support the acquisition of clinical reasoning skills in healthcare education. However, until now it remains unclear which features or settings of VPs optimally foster clinical reasoning. Therefore, our aims were to identify key concepts of the clinical reasoning process in a qualitative approach and draw conclusions on how each concept can be enhanced to advance the learning of clinical reasoning with virtual patients. Methods: We chose a grounded theory approach to identify key categories and concepts of learning clinical reasoning and develop a framework. Throughout this process, the emerging codes were discussed with a panel of interdisciplinary experts. In a second step we applied the framework to virtual patients. Results: Based on the data we identified the core category as the "multifactorial nature of learning clinical reasoning". This category is reflected in the following five main categories: Psychological Theories, Patient-centeredness, Context, Learner-centeredness, and Teaching/Assessment. Each category encompasses between four and six related concepts. Conclusions: With our approach we were able to elaborate how key categories and concepts of clinical reasoning can be applied to virtual patients. This includes aspects such as allowing learners to access a large number of VPs with adaptable levels of complexity and feedback or emphasizing dual processing, errors, and uncertainty. PMID:29497697

Local inhibition modulates learning-dependent song encoding in the songbird auditory cortex

PubMed Central

Thompson, Jason V.; Jeanne, James M.

2013-01-01

Changes in inhibition during development are well documented, but the role of inhibition in adult learning-related plasticity is not understood. In songbirds, vocal recognition learning alters the neural representation of songs across the auditory forebrain, including the caudomedial nidopallium (NCM), a region analogous to mammalian secondary auditory cortices. Here, we block local inhibition with the iontophoretic application of gabazine, while simultaneously measuring song-evoked spiking activity in NCM of European starlings trained to recognize sets of conspecific songs. We find that local inhibition differentially suppresses the responses to learned and unfamiliar songs and enhances spike-rate differences between learned categories of songs. These learning-dependent response patterns emerge, in part, through inhibitory modulation of selectivity for song components and the masking of responses to specific acoustic features without altering spectrotemporal tuning. The results describe a novel form of inhibitory modulation of the encoding of learned categories and demonstrate that inhibition plays a central role in shaping the responses of neurons to learned, natural signals. PMID:23155175

Problem based learning: the effect of real time data on the website to student independence

NASA Astrophysics Data System (ADS)

Setyowidodo, I.; Pramesti, Y. S.; Handayani, A. D.

2018-05-01

Learning science developed as an integrative science rather than disciplinary education, the reality of the nation character development has not been able to form a more creative and independent Indonesian man. Problem Based Learning based on real time data in the website is a learning method focuses on developing high-level thinking skills in problem-oriented situations by integrating technology in learning. The essence of this study is the presentation of authentic problems in the real time data situation in the website. The purpose of this research is to develop student independence through Problem Based Learning based on real time data in website. The type of this research is development research with implementation using purposive sampling technique. Based on the study there is an increase in student self-reliance, where the students in very high category is 47% and in the high category is 53%. This learning method can be said to be effective in improving students learning independence in problem-oriented situations.

District nurses' knowledge development in wound management: ongoing learning without organizational support.

PubMed

Friman, Anne; Wahlberg, Anna Carin; Mattiasson, Anne-Cathrine; Ebbeskog, Britt

2014-10-01

The aim of this study was to describe district nurses' (DNs') experiences of their knowledge development in wound management when treating patients with different types of wounds at healthcare centers. In primary healthcare, DNs are mainly responsible for wound management. Previous research has focused on DNs' level of expertise regarding wound management, mostly based on quantitative studies. An unanswered question concerns DNs' knowledge development in wound management. The present study therefore intends to broaden understanding and to provide deeper knowledge in regard to the DNs' experiences of their knowledge development when treating patients with wounds. A qualitative descriptive design was used. Subjects were a purposeful sample of 16 DNs from eight healthcare centers in a metropolitan area in Stockholm, Sweden. The study was conducted with qualitative interviews and qualitative content analysis was used to analyze the data. The content analysis resulted in three categories and 11 sub-categories. The first category, 'ongoing learning by experience,' was based on experiences of learning alongside clinical practice. The second category 'searching for information,' consisted of various channels for obtaining information. The third category, 'lacking organizational support,' consisted of experiences related to the DNs' work organization, which hindered their development in wound care knowledge. The DNs experienced that they were in a constant state of learning and obtained their wound care knowledge to a great extent through practical work, from their colleagues as well as from various companies. A lack of organizational structures and support from staff management made it difficult for DNs to develop their knowledge and skills in wound management, which can lead to inadequate wound management.

Innovative learning model for improving students’ argumentation skill and concept understanding on science

NASA Astrophysics Data System (ADS)

Nafsiati Astuti, Rini

2018-04-01

Argumentation skill is the ability to compose and maintain arguments consisting of claims, supports for evidence, and strengthened-reasons. Argumentation is an important skill student needs to face the challenges of globalization in the 21st century. It is not an ability that can be developed by itself along with the physical development of human, but it must be developed under nerve like process, giving stimulus so as to require a person to be able to argue. Therefore, teachers should develop students’ skill of arguing in science learning in the classroom. The purpose of this study is to obtain an innovative learning model that are valid in terms of content and construct in improving the skills of argumentation and concept understanding of junior high school students. The assessment of content validity and construct validity was done through Focus Group Discussion (FGD), using the content and construct validation sheet, book model, learning video, and a set of learning aids for one meeting. Assessment results from 3 (three) experts showed that the learning model developed in the category was valid. The validity itself shows that the developed learning model has met the content requirement, the student needs, state of the art, strong theoretical and empirical foundation and construct validity, which has a connection of syntax stages and components of learning model so that it can be applied in the classroom activities

Empowering Students with Language Learning Strategies: A Critical Review of Current Issues

ERIC Educational Resources Information Center

Rivera-Mills, Susanna V.; Plonsky, Luke

2007-01-01

This article analyzes the body of research literature that has brought us to the state of our current knowledge regarding learning strategies in general and learning strategies Instruction as they relate to second language acquisition (SLA). Three categories are discussed: (1) types of learning strategies, (2) learning autonomy and strategy…

Memory Errors Reveal a Bias to Spontaneously Generalize to Categories

PubMed Central

Sutherland, Shelbie L.; Cimpian, Andrei; Leslie, Sarah-Jane; Gelman, Susan A.

2014-01-01

Much evidence suggests that, from a young age, humans are able to generalize information learned about a subset of a category to the category itself. Here, we propose that—beyond simply being able to perform such generalizations—people are biased to generalize to categories, such that they routinely make spontaneous, implicit category generalizations from information that licenses such generalizations. To demonstrate the existence of this bias, we asked participants to perform a task in which category generalizations would distract from the main goal of the task, leading to a characteristic pattern of errors. Specifically, participants were asked to memorize two types of novel facts: quantified facts about sets of kind members (e.g., facts about all or many stups) and generic facts about entire kinds (e.g., facts about zorbs as a kind). Moreover, half of the facts concerned properties that are typically generalizable to an animal kind (e.g., eating fruits and vegetables), and half concerned properties that are typically more idiosyncratic (e.g., getting mud in their hair). We predicted that—because of the hypothesized bias—participants would spontaneously generalize the quantified facts to the corresponding kinds, and would do so more frequently for the facts about generalizable (rather than idiosyncratic) properties. In turn, these generalizations would lead to a higher rate of quantified-to-generic memory errors for the generalizable properties. The results of four experiments (N = 449) supported this prediction. Moreover, the same generalizable-versus-idiosyncratic difference in memory errors occurred even under cognitive load, which suggests that the hypothesized bias operates unnoticed in the background, requiring few cognitive resources. In sum, this evidence suggests the presence of a powerful bias to draw generalizations about kinds. PMID:25327964

The effect of science learning integrated with local potential to improve science process skills

NASA Astrophysics Data System (ADS)

Rahardini, Riris Riezqia Budy; Suryadarma, I. Gusti Putu; Wilujeng, Insih

2017-08-01

This research was aimed to know the effectiveness of science learning that integrated with local potential to improve student`s science process skill. The research was quasi experiment using non-equivalent control group design. The research involved all student of Muhammadiyah Imogiri Junior High School on grade VII as a population. The sample in this research was selected through cluster random sampling, namely VII B (experiment group) and VII C (control group). Instrument that used in this research is a nontest instrument (science process skill observation's form) adapted Desak Megawati's research (2016). The aspect of science process skills were making observation and communication. The data were using univariat (ANOVA) analyzed at 0,05 significance level and normalized gain score for science process skill increase's category. The result is science learning that integrated with local potential was effective to improve science process skills of student (Sig. 0,00). This learning can increase science process skill, shown by a normalized gain score value at 0,63 (medium category) in experiment group and 0,29 (low category) in control group.

Rule Based Category Learning in Patients with Parkinson’s Disease

PubMed Central

Price, Amanda; Filoteo, J. Vincent; Maddox, W. Todd

2009-01-01

Measures of explicit rule-based category learning are commonly used in neuropsychological evaluation of individuals with Parkinson’s disease (PD) and the pattern of PD performance on these measures tends to be highly varied. We review the neuropsychological literature to clarify the manner in which PD affects the component processes of rule-based category learning and work to identify and resolve discrepancies within this literature. In particular, we address the manner in which PD and its common treatments affect the processes of rule generation, maintenance, shifting and selection. We then integrate the neuropsychological research with relevant neuroimaging and computational modeling evidence to clarify the neurobiological impact of PD on each process. Current evidence indicates that neurochemical changes associated with PD primarily disrupt rule shifting, and may disturb feedback-mediated learning processes that guide rule selection. Although surgical and pharmacological therapies remediate this deficit, it appears that the same treatments may contribute to impaired rule generation, maintenance and selection processes. These data emphasize the importance of distinguishing between the impact of PD and its common treatments when considering the neuropsychological profile of the disease. PMID:19428385

The Design and Validation of the Colorado Learning Attitudes about Science Survey

NASA Astrophysics Data System (ADS)

Adams, W. K.; Perkins, K. K.; Dubson, M.; Finkelstein, N. D.; Wieman, C. E.

2005-09-01

The Colorado Learning Attitudes about Science Survey (CLASS) is a new instrument designed to measure various facets of student attitudes and beliefs about learning physics. This instrument extends previous work by probing additional facets of student attitudes and beliefs. It has been written to be suitably worded for students in a variety of different courses. This paper introduces the CLASS and its design and validation studies, which include analyzing results from over 2400 students, interviews and factor analyses. Methodology used to determine categories and how to analyze the robustness of categories for probing various facets of student learning are also described. This paper serves as the foundation for the results and conclusions from the analysis of our survey data.

Human simulations of vocabulary learning.

PubMed

Gillette, J; Gleitman, H; Gleitman, L; Lederer, A

1999-12-07

The work reported here experimentally investigates a striking generalization about vocabulary acquisition: Noun learning is superior to verb learning in the earliest moments of child language development. The dominant explanation of this phenomenon in the literature invokes differing conceptual requirements for items in these lexical categories: Verbs are cognitively more complex than nouns and so their acquisition must await certain mental developments in the infant. In the present work, we investigate an alternative hypothesis; namely, that it is the information requirements of verb learning, not the conceptual requirements, that crucially determine the acquisition order. Efficient verb learning requires access to structural features of the exposure language and thus cannot take place until a scaffolding of noun knowledge enables the acquisition of clause-level syntax. More generally, we experimentally investigate the hypothesis that vocabulary acquisition takes place via an incremental constraint-satisfaction procedure that bootstraps itself into successively more sophisticated linguistic representations which, in turn, enable new kinds of vocabulary learning. If the experimental subjects were young children, it would be difficult to distinguish between this information-centered hypothesis and the conceptual change hypothesis. Therefore the experimental "learners" are adults. The items to be "acquired" in the experiments were the 24 most frequent nouns and 24 most frequent verbs from a sample of maternal speech to 18-24-month-old infants. The various experiments ask about the kinds of information that will support identification of these words as they occur in mother-to-child discourse. Both the proportion correctly identified and the type of word that is identifiable changes significantly as a function of information type. We discuss these results as consistent with the incremental construction of a highly lexicalized grammar by cognitively and pragmatically sophisticated human infants, but inconsistent with a procedure in which lexical acquisition is independent of and antecedent to syntax acquisition.

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

DTIC Science & Technology

2014-01-01

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

Classifying injury narratives of large administrative databases for surveillance-A practical approach combining machine learning ensembles and human review.

PubMed

Marucci-Wellman, Helen R; Corns, Helen L; Lehto, Mark R

2017-01-01

Injury narratives are now available real time and include useful information for injury surveillance and prevention. However, manual classification of the cause or events leading to injury found in large batches of narratives, such as workers compensation claims databases, can be prohibitive. In this study we compare the utility of four machine learning algorithms (Naïve Bayes, Single word and Bi-gram models, Support Vector Machine and Logistic Regression) for classifying narratives into Bureau of Labor Statistics Occupational Injury and Illness event leading to injury classifications for a large workers compensation database. These algorithms are known to do well classifying narrative text and are fairly easy to implement with off-the-shelf software packages such as Python. We propose human-machine learning ensemble approaches which maximize the power and accuracy of the algorithms for machine-assigned codes and allow for strategic filtering of rare, emerging or ambiguous narratives for manual review. We compare human-machine approaches based on filtering on the prediction strength of the classifier vs. agreement between algorithms. Regularized Logistic Regression (LR) was the best performing algorithm alone. Using this algorithm and filtering out the bottom 30% of predictions for manual review resulted in high accuracy (overall sensitivity/positive predictive value of 0.89) of the final machine-human coded dataset. The best pairings of algorithms included Naïve Bayes with Support Vector Machine whereby the triple ensemble NB SW =NB BI-GRAM =SVM had very high performance (0.93 overall sensitivity/positive predictive value and high accuracy (i.e. high sensitivity and positive predictive values)) across both large and small categories leaving 41% of the narratives for manual review. Integrating LR into this ensemble mix improved performance only slightly. For large administrative datasets we propose incorporation of methods based on human-machine pairings such as we have done here, utilizing readily-available off-the-shelf machine learning techniques and resulting in only a fraction of narratives that require manual review. Human-machine ensemble methods are likely to improve performance over total manual coding. Copyright © 2016 The Authors. Published by Elsevier Ltd.. All rights reserved.

Affordance Analysis--Matching Learning Tasks with Learning Technologies

ERIC Educational Resources Information Center

Bower, Matt

2008-01-01

This article presents a design methodology for matching learning tasks with learning technologies. First a working definition of "affordances" is provided based on the need to describe the action potentials of the technologies (utility). Categories of affordances are then proposed to provide a framework for analysis. Following this, a…

Collaborative Project-Based Learning: An Integrative Science and Technological Education Project

ERIC Educational Resources Information Center

Baser, Derya; Ozden, M. Yasar; Karaarslan, Hasan

2017-01-01

Background: Blending collaborative learning and project-based learning (PBL) based on Wolff (2003) design categories, students interacted in a learning environment where they developed their technology integration practices as well as their technological and collaborative skills. Purpose: The study aims to understand how seventh grade students…

On the Role of Concepts in Learning and Instructional Design

ERIC Educational Resources Information Center

Jonassen, David H.

2006-01-01

The field of instructional design has traditionally treated concepts as discrete learning outcomes. Theoretically, learning concepts requires correctly isolating and applying attributes of specific objects into their correct categories. Similarity views of concept learning are unable to account for all of the rules governing concept formation,…

[Problem based learning from the perspective of tutors].

PubMed

Navarro Hernández, Nancy; Illesca P, Mónica; Cabezas G, Mirtha

2009-02-01

Problem based learning is a student centered learning technique that develops deductive, constructive and reasoning capacities among the students. Teachers must adapt to this paradigm of constructing rather than transmitting knowledge. To interpret the importance of tutors in problem based learning during a module of Health research and management given to medical, nursing, physical therapy, midwifery, technology and nutrition students. Eight teachers that participated in a module using problem based learning accepted to participate in an in depth interview. The qualitative analysis of the textual information recorded, was performed using the ATLAS software. We identified 662 meaning units, grouped in 29 descriptive categories, with eight emerging meta categories. The sequential and cross-generated qualitative analysis generated four domains: competence among students, competence of teachers, student-centered learning and evaluation process. Multiprofessional problem based learning contributes to the development of generic competences among future health professionals, such as multidisciplinary work, critical capacity and social skills. Teachers must shelter the students in the context of their problems and social situation.

Human motion tracking by temporal-spatial local gaussian process experts.

PubMed

Zhao, Xu; Fu, Yun; Liu, Yuncai

2011-04-01

Human pose estimation via motion tracking systems can be considered as a regression problem within a discriminative framework. It is always a challenging task to model the mapping from observation space to state space because of the high-dimensional characteristic in the multimodal conditional distribution. In order to build the mapping, existing techniques usually involve a large set of training samples in the learning process which are limited in their capability to deal with multimodality. We propose, in this work, a novel online sparse Gaussian Process (GP) regression model to recover 3-D human motion in monocular videos. Particularly, we investigate the fact that for a given test input, its output is mainly determined by the training samples potentially residing in its local neighborhood and defined in the unified input-output space. This leads to a local mixture GP experts system composed of different local GP experts, each of which dominates a mapping behavior with the specific covariance function adapting to a local region. To handle the multimodality, we combine both temporal and spatial information therefore to obtain two categories of local experts. The temporal and spatial experts are integrated into a seamless hybrid system, which is automatically self-initialized and robust for visual tracking of nonlinear human motion. Learning and inference are extremely efficient as all the local experts are defined online within very small neighborhoods. Extensive experiments on two real-world databases, HumanEva and PEAR, demonstrate the effectiveness of our proposed model, which significantly improve the performance of existing models.

From bird to sparrow: Learning-induced modulations in fine-grained semantic discrimination.

PubMed

De Meo, Rosanna; Bourquin, Nathalie M-P; Knebel, Jean-François; Murray, Micah M; Clarke, Stephanie

2015-09-01

Recognition of environmental sounds is believed to proceed through discrimination steps from broad to more narrow categories. Very little is known about the neural processes that underlie fine-grained discrimination within narrow categories or about their plasticity in relation to newly acquired expertise. We investigated how the cortical representation of birdsongs is modulated by brief training to recognize individual species. During a 60-minute session, participants learned to recognize a set of birdsongs; they improved significantly their performance for trained (T) but not control species (C), which were counterbalanced across participants. Auditory evoked potentials (AEPs) were recorded during pre- and post-training sessions. Pre vs. post changes in AEPs were significantly different between T and C i) at 206-232ms post stimulus onset within a cluster on the anterior part of the left superior temporal gyrus; ii) at 246-291ms in the left middle frontal gyrus; and iii) 512-545ms in the left middle temporal gyrus as well as bilaterally in the cingulate cortex. All effects were driven by weaker activity for T than C species. Thus, expertise in discriminating T species modulated early stages of semantic processing, during and immediately after the time window that sustains the discrimination between human vs. animal vocalizations. Moreover, the training-induced plasticity is reflected by the sharpening of a left lateralized semantic network, including the anterior part of the temporal convexity and the frontal cortex. Training to identify birdsongs influenced, however, also the processing of C species, but at a much later stage. Correct discrimination of untrained sounds seems to require an additional step which results from lower-level features analysis such as apperception. We therefore suggest that the access to objects within an auditory semantic category is different and depends on subject's level of expertise. More specifically, correct intra-categorical auditory discrimination for untrained items follows the temporal hierarchy and transpires in a late stage of semantic processing. On the other hand, correct categorization of individually trained stimuli occurs earlier, during a period contemporaneous with human vs. animal vocalization discrimination, and involves a parallel semantic pathway requiring expertise. Copyright © 2015 Elsevier Inc. All rights reserved.

Prototype learning and dissociable categorization systems in Alzheimer's disease.

PubMed

Heindel, William C; Festa, Elena K; Ott, Brian R; Landy, Kelly M; Salmon, David P

2013-08-01

Recent neuroimaging studies suggest that prototype learning may be mediated by at least two dissociable memory systems depending on the mode of acquisition, with A/Not-A prototype learning dependent upon a perceptual representation system located within posterior visual cortex and A/B prototype learning dependent upon a declarative memory system associated with medial temporal and frontal regions. The degree to which patients with Alzheimer's disease (AD) can acquire new categorical information may therefore critically depend upon the mode of acquisition. The present study examined A/Not-A and A/B prototype learning in AD patients using procedures that allowed direct comparison of learning across tasks. Despite impaired explicit recall of category features in all tasks, patients showed differential patterns of category acquisition across tasks. First, AD patients demonstrated impaired prototype induction along with intact exemplar classification under incidental A/Not-A conditions, suggesting that the loss of functional connectivity within visual cortical areas disrupted the integration processes supporting prototype induction within the perceptual representation system. Second, AD patients demonstrated intact prototype induction but impaired exemplar classification during A/B learning under observational conditions, suggesting that this form of prototype learning is dependent on a declarative memory system that is disrupted in AD. Third, the surprisingly intact classification of both prototypes and exemplars during A/B learning under trial-and-error feedback conditions suggests that AD patients shifted control from their deficient declarative memory system to a feedback-dependent procedural memory system when training conditions allowed. Taken together, these findings serve to not only increase our understanding of category learning in AD, but to also provide new insights into the ways in which different memory systems interact to support the acquisition of categorical knowledge. Copyright © 2013 Elsevier Ltd. All rights reserved.

Prototype Learning and Dissociable Categorization Systems in Alzheimer’s Disease

PubMed Central

Heindel, William C.; Festa, Elena K.; Ott, Brian R.; Landy, Kelly M.; Salmon, David P.

2015-01-01

Recent neuroimaging studies suggest that prototype learning may be mediated by at least two dissociable memory systems depending on the mode of acquisition, with A/Not-A prototype learning dependent upon a perceptual representation system located within posterior visual cortex and A/B prototype learning dependent upon a declarative memory system associated with medial temporal and frontal regions. The degree to which patients with Alzheimer’s disease (AD) can acquire new categorical information may therefore critically depend upon the mode of acquisition. The present study examined A/Not-A and A/B prototype learning in AD patients using procedures that allowed direct comparison of learning across tasks. Despite impaired explicit recall of category features in all tasks, patients showed differential patterns of category acquisition across tasks. First, AD patients demonstrated impaired prototype induction along with intact exemplar classification under incidental A/Not-A conditions, suggesting that the loss of functional connectivity within visual cortical areas disrupted the integration processes supporting prototype induction within the perceptual representation system. Second, AD patients demonstrated intact prototype induction but impaired exemplar classification during A/B learning under observational conditions, suggesting that this form of prototype learning is dependent on a declarative memory system that is disrupted in AD. Third, the surprisingly intact classification of both prototypes and exemplars during A/B learning under trial-and-error feedback conditions suggests that AD patients shifted control from their deficient declarative memory system to a feedback-dependent procedural memory system when training conditions allowed. Taken together, these findings serve to not only increase our understanding of category learning in AD, but to also provide new insights into the ways in which different memory systems interact to support the acquisition of categorical knowledge. PMID:23751172

Striatal and Hippocampal Entropy and Recognition Signals in Category Learning: Simultaneous Processes Revealed by Model-Based fMRI

PubMed Central

Davis, Tyler; Love, Bradley C.; Preston, Alison R.

2012-01-01

Category learning is a complex phenomenon that engages multiple cognitive processes, many of which occur simultaneously and unfold dynamically over time. For example, as people encounter objects in the world, they simultaneously engage processes to determine their fit with current knowledge structures, gather new information about the objects, and adjust their representations to support behavior in future encounters. Many techniques that are available to understand the neural basis of category learning assume that the multiple processes that subserve it can be neatly separated between different trials of an experiment. Model-based functional magnetic resonance imaging offers a promising tool to separate multiple, simultaneously occurring processes and bring the analysis of neuroimaging data more in line with category learning’s dynamic and multifaceted nature. We use model-based imaging to explore the neural basis of recognition and entropy signals in the medial temporal lobe and striatum that are engaged while participants learn to categorize novel stimuli. Consistent with theories suggesting a role for the anterior hippocampus and ventral striatum in motivated learning in response to uncertainty, we find that activation in both regions correlates with a model-based measure of entropy. Simultaneously, separate subregions of the hippocampus and striatum exhibit activation correlated with a model-based recognition strength measure. Our results suggest that model-based analyses are exceptionally useful for extracting information about cognitive processes from neuroimaging data. Models provide a basis for identifying the multiple neural processes that contribute to behavior, and neuroimaging data can provide a powerful test bed for constraining and testing model predictions. PMID:22746951

The experiment of cooperative learning model type team assisted individualization (TAI) on three-dimensional space subject viewed from spatial intelligence

NASA Astrophysics Data System (ADS)

Manapa, I. Y. H.; Budiyono; Subanti, S.

2018-03-01

The aim of this research is to determine the effect of TAI or direct learning (DL) on student’s mathematics achievement viewed from spatial intelligence. This research was quasi experiment. The population was 10th grade senior high school students in Alor Regency on academic year of 2015/2016 chosen by stratified cluster random sampling. The data were collected through achievement and spatial intelligence test. The data were analyzed by two ways, ANOVA with unequal cell and scheffe test. This research showed that student’s mathematics achievement used in TAI had better results than DL models one. In spatial intelligence category, student’s mathematics achievement with high spatial intelligence has better result than the other spatial intelligence category and students with high spatial intelligence have better results than those with middle spatial intelligence category. At TAI, student’s mathematics achievement with high spatial intelligence has better result than those with the other spatial intelligence category and students with middle spatial intelligence have better results than students with low spatial intelligence. In DL model, student’s mathematics achievement with high and middle spatial intelligence has better result than those with low spatial intelligence, but students with high spatial intelligence and middle spatial intelligence have no significant difference. In each category of spatial intelligence and learning model, mathematics achievement has no significant difference.

Analysis of senior high school students’ creative thinking skills profile in Klaten regency

NASA Astrophysics Data System (ADS)

Sugiyanto, F. N.; Masykuri, M.; Muzzazinah

2018-04-01

The aim of this research is to analyze the initial profile of creative thinking skills in Senior High School students on biology learning. This research was a quantitative descriptive research using test method. Analysis was conducted by giving tests containing creative thinking skills. The research subject was grade 11 students of Senior High School that categorized by its accreditation as category A (high grade) and category B (low grade). These schools are placed in Klaten Regency, Central Java. Based on the analysis, it showed that the percentage of creative thinking skill achievement in category A school is: fluency (46.35%), flexibility (13.54%), originality (20%), and elaboration (34.76%); meanwhile, category B school is fluency (30.39%), flexibility (2.45%), originality (9.11 %) and elaboration (12.87%). The lowest percentage of that result in both school categories was found on flexibility and originality indicator. Based on the result, the average of creative thinking skills in category A school was 28.66%, and category B school was 13.71%. The conclusion of this research is the initial profile of students’ creative thinking skills in biology learning was relatively in low grade. The result indicates that creative thinking skills of Senior High School students should become a serious attention considering the low percentage on each indicator.

Non-Formal Learning: Clarification of the Concept and Its Application in Music Learning

ERIC Educational Resources Information Center

Mok, On Nei Annie

2011-01-01

The concept of non-formal learning, which falls outside the categories of informal and formal learning, has not been as widely discussed, especially in the music education literature. In order to bridge this gap and to provide supplementary framework to the discussion of informal and formal learning, therefore, this paper will first summarize…

Increasing Dopamine Levels in the Brain Improves Feedback-Based Procedural Learning in Healthy Participants: An Artificial-Grammar-Learning Experiment

ERIC Educational Resources Information Center

de Vries, Meinou H.; Ulte, Catrin; Zwitserlood, Pienie; Szymanski, Barbara; Knecht, Stefan

2010-01-01

Recently, an increasing number of studies have suggested a role for the basal ganglia and related dopamine inputs in procedural learning, specifically when learning occurs through trial-by-trial feedback (Shohamy, Myers, Kalanithi, & Gluck. (2008). "Basal ganglia and dopamine contributions to probabilistic category learning." "Neuroscience and…

Designing a Semantic Bliki System to Support Different Types of Knowledge and Adaptive Learning

ERIC Educational Resources Information Center

Huang, Shiu-Li; Yang, Chia-Wei

2009-01-01

Though blogs and wikis have been used to support knowledge management and e-learning, existing blogs and wikis cannot support different types of knowledge and adaptive learning. A case in point, types of knowledge vary greatly in category and viewpoints. Additionally, adaptive learning is crucial to improving one's learning performance. This study…

College Students' Conceptions of Learning Management: The Difference between Traditional (Face-to-Face) Instruction and Web-Based Learning Environments

ERIC Educational Resources Information Center

Lin, Hung-Ming; Tsai, Chin-Chung

2011-01-01

This study investigates the differences between students' conceptions of learning management via traditional instruction and Web-based learning environments. The Conceptions of Learning Management Inventory (COLM) was administered to 259 Taiwanese college students majoring in Business Administration. The COLM has six factors (categories), namely,…

From Young Children's Ideas about Germs to Ideas Shaping a Learning Environment

NASA Astrophysics Data System (ADS)

Ergazaki, Marida; Saltapida, Konstantina; Zogza, Vassiliki

2010-11-01

This paper is concerned with highlighting young children’s ideas about the nature, location and appearance of germs, as well as their reasoning strands about germs’ ontological category and biological functions. Moreover, it is concerned with exploring how all these could be taken into account for shaping a potentially fruitful learning environment. Conducting individual, semi-structured interviews with 35 preschoolers (age 4.5-5.5) of public kindergartens in the broader area of Patras, we attempted to trace their ideas about what germs are, where they may be found, whether they are good or bad and living or non-living and how they might look like in a drawing. Moreover, children were required to attribute a series of biological functions to dogs, chairs and germs, and finally to create a story with germs holding a key-role. The analysis of our qualitative data within the “NVivo” software showed that the informants make a strong association of germs with health and hygiene issues, locate germs mostly in our body and the external environment, are not familiar with the ‘good germs’-idea, and draw germs as ‘human-like’, ‘animal-like’ or ‘abstract’ entities. Moreover, they have significant difficulties not only in employing biological functions as criteria for classifying germs in the category of ‘living’, but also in just attributing such functions to germs using a warrant. Finally, the shift from our findings to a 3-part learning environment aiming at supporting preschoolers in refining their initial conceptualization of germs is thoroughly discussed in the paper.

Multivariate sensitivity to voice during auditory categorization.

PubMed

Lee, Yune Sang; Peelle, Jonathan E; Kraemer, David; Lloyd, Samuel; Granger, Richard

2015-09-01

Past neuroimaging studies have documented discrete regions of human temporal cortex that are more strongly activated by conspecific voice sounds than by nonvoice sounds. However, the mechanisms underlying this voice sensitivity remain unclear. In the present functional MRI study, we took a novel approach to examining voice sensitivity, in which we applied a signal detection paradigm to the assessment of multivariate pattern classification among several living and nonliving categories of auditory stimuli. Within this framework, voice sensitivity can be interpreted as a distinct neural representation of brain activity that correctly distinguishes human vocalizations from other auditory object categories. Across a series of auditory categorization tests, we found that bilateral superior and middle temporal cortex consistently exhibited robust sensitivity to human vocal sounds. Although the strongest categorization was in distinguishing human voice from other categories, subsets of these regions were also able to distinguish reliably between nonhuman categories, suggesting a general role in auditory object categorization. Our findings complement the current evidence of cortical sensitivity to human vocal sounds by revealing that the greatest sensitivity during categorization tasks is devoted to distinguishing voice from nonvoice categories within human temporal cortex. Copyright © 2015 the American Physiological Society.

Is the asymmetry in young infants' categorization of humans versus nonhuman animals based on head, body, or global gestalt information?

PubMed

Quinn, Paul C

2004-02-01

Quinn and Eimas (1998) reported an asymmetry in the exclusivity of the category representations that young infants form for humans and nonhuman animals: category representations for nonhuman animal species were found to exclude humans, whereas a category representation for humans was found to include nonhuman animal species (i.e., cats, horses). The present experiment utilized the familiarization/novelty-preference procedure with 3- and 4-month-olds to determine the perceptual cues (i.e., whole stimulus, head alone, body alone) that provided the basis for this asymmetry. The data revealed the asymmetry to be observable only with the whole animal stimuli and not when infants were provided with information from just the head or the body of the exemplars. The results indicate that the incorporation of nonhuman animal species into a category representation for humans is based on holistic information.

Individual differences in cortical face selectivity predict behavioral performance in face recognition

PubMed Central

Huang, Lijie; Song, Yiying; Li, Jingguang; Zhen, Zonglei; Yang, Zetian; Liu, Jia

2014-01-01

In functional magnetic resonance imaging studies, object selectivity is defined as a higher neural response to an object category than other object categories. Importantly, object selectivity is widely considered as a neural signature of a functionally-specialized area in processing its preferred object category in the human brain. However, the behavioral significance of the object selectivity remains unclear. In the present study, we used the individual differences approach to correlate participants' face selectivity in the face-selective regions with their behavioral performance in face recognition measured outside the scanner in a large sample of healthy adults. Face selectivity was defined as the z score of activation with the contrast of faces vs. non-face objects, and the face recognition ability was indexed as the normalized residual of the accuracy in recognizing previously-learned faces after regressing out that for non-face objects in an old/new memory task. We found that the participants with higher face selectivity in the fusiform face area (FFA) and the occipital face area (OFA), but not in the posterior part of the superior temporal sulcus (pSTS), possessed higher face recognition ability. Importantly, the association of face selectivity in the FFA and face recognition ability cannot be accounted for by FFA response to objects or behavioral performance in object recognition, suggesting that the association is domain-specific. Finally, the association is reliable, confirmed by the replication from another independent participant group. In sum, our finding provides empirical evidence on the validity of using object selectivity as a neural signature in defining object-selective regions in the human brain. PMID:25071513

Exploring the spatio-temporal neural basis of face learning

PubMed Central

Yang, Ying; Xu, Yang; Jew, Carol A.; Pyles, John A.; Kass, Robert E.; Tarr, Michael J.

2017-01-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150–250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150–250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces. PMID:28570739

Exploring the spatio-temporal neural basis of face learning.

PubMed

Yang, Ying; Xu, Yang; Jew, Carol A; Pyles, John A; Kass, Robert E; Tarr, Michael J

2017-06-01

Humans are experts at face individuation. Although previous work has identified a network of face-sensitive regions and some of the temporal signatures of face processing, as yet, we do not have a clear understanding of how such face-sensitive regions support learning at different time points. To study the joint spatio-temporal neural basis of face learning, we trained subjects to categorize two groups of novel faces and recorded their neural responses using magnetoencephalography (MEG) throughout learning. A regression analysis of neural responses in face-sensitive regions against behavioral learning curves revealed significant correlations with learning in the majority of the face-sensitive regions in the face network, mostly between 150-250 ms, but also after 300 ms. However, the effect was smaller in nonventral regions (within the superior temporal areas and prefrontal cortex) than that in the ventral regions (within the inferior occipital gyri (IOG), midfusiform gyri (mFUS) and anterior temporal lobes). A multivariate discriminant analysis also revealed that IOG and mFUS, which showed strong correlation effects with learning, exhibited significant discriminability between the two face categories at different time points both between 150-250 ms and after 300 ms. In contrast, the nonventral face-sensitive regions, where correlation effects with learning were smaller, did exhibit some significant discriminability, but mainly after 300 ms. In sum, our findings indicate that early and recurring temporal components arising from ventral face-sensitive regions are critically involved in learning new faces.

Ventral Striatum and the Evaluation of Memory Retrieval Strategies

PubMed Central

Badre, David; Lebrecht, Sophie; Pagliaccio, David; Long, Nicole M.; Scimeca, Jason M.

2015-01-01

Adaptive memory retrieval requires mechanisms of cognitive control that facilitate the recovery of goal-relevant information. Frontoparietal systems are known to support control of memory retrieval. However, the mechanisms by which the brain acquires, evaluates, and adapts retrieval strategies remain unknown. Here, we provide evidence that ventral striatal activation tracks the success of a retrieval strategy and correlates with subsequent reliance on that strategy. Human participants were scanned with fMRI while performing a lexical decision task. A rule was provided that indicated the likely semantic category of a target word given the category of a preceding prime. Reliance on the rule improved decision-making, as estimated within a drift diffusion framework. Ventral striatal activation tracked the benefit that relying on the rule had on decision-making. Moreover, activation in ventral striatum correlated with a participant’s subsequent reliance on the rule. Taken together, these results support a role for ventral striatum in learning and evaluating declarative retrieval strategies. PMID:24564466

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

PubMed

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 the ADHD dopaminergic dysfunction model and recent findings implicating procedural learning impairments in those with ADHD. Copyright © 2017 Elsevier Inc. All rights reserved.

Field Learning as a powerful tool of Education for geoscience, environment and disaster prevention.

NASA Astrophysics Data System (ADS)

Matsumoto, I.; LI, W.

2015-12-01

Field learning in through elementary school to University is very important for cultivation of science, environment and disaster prevention literacy. In Japan, we have various natural disasters such as earthquakes and volcanoes based on its geological settings ( Island-arc with subduction zone settings). And, it is a challenge environmental problem such as global warming prevention and energy problem to be solved by a human. For the above problem solving, it said that science education plays very important role. Especially learning with direct experience in the field is not only to get the only knowledge, we believe that greater development of science literacy, environmental literacy and disaster prevention literacy. In this presentation, we propose the new teaching method of field learning not only provided by school but also provided by outside school. We show following four studies that are (1) function of running water and origin of the land (science education and disaster prevention), (2) environmental consciousness of student (environmental education), (3) radiation education (scientific technology and its utilization) and (4) astronomical observation (acquisition of time and space concept). We were led to the preliminary conclusion of above four categories in practice research in and out of school. That is, the teacher is teaching the essence and phenomena of science to focus on science learning of school, in addition to environmental awareness, disaster prevention awareness, use of scientific technology are also important to teach at the same time. To do this, it is to make effective use of field learning. It can be said that the field study is a perfect and power place to perform learning such simultaneity. Because, natural field is originally the place can learn along with the feeling through the five senses of human. It is important especially for the growth stage of the student.

Multi-agents and learning: Implications for Webusage mining.

PubMed

Lotfy, Hewayda M S; Khamis, Soheir M S; Aboghazalah, Maie M

2016-03-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user's current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user's visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user's profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F 1-measure.

Multi-agents and learning: Implications for Webusage mining

PubMed Central

Lotfy, Hewayda M.S.; Khamis, Soheir M.S.; Aboghazalah, Maie M.

2015-01-01

Characterization of user activities is an important issue in the design and maintenance of websites. Server weblog files have abundant information about the user’s current interests. This information can be mined and analyzed therefore the administrators may be able to guide the users in their browsing activity so they may obtain relevant information in a shorter span of time to obtain user satisfaction. Web-based technology facilitates the creation of personally meaningful and socially useful knowledge through supportive interactions, communication and collaboration among educators, learners and information. This paper suggests a new methodology based on learning techniques for a Web-based Multiagent-based application to discover the hidden patterns in the user’s visited links. It presents a new approach that involves unsupervised, reinforcement learning, and cooperation between agents. It is utilized to discover patterns that represent the user’s profiles in a sample website into specific categories of materials using significance percentages. These profiles are used to make recommendations of interesting links and categories to the user. The experimental results of the approach showed successful user pattern recognition, and cooperative learning among agents to obtain user profiles. It indicates that combining different learning algorithms is capable of improving user satisfaction indicated by the percentage of precision, recall, the progressive category weight and F1-measure. PMID:26966569

Toward a tactile language for human-robot interaction: two studies of tacton learning and performance.

PubMed

Barber, Daniel J; Reinerman-Jones, Lauren E; Matthews, Gerald

2015-05-01

Two experiments were performed to investigate the feasibility for robot-to-human communication of a tactile language using a lexicon of standardized tactons (tactile icons) within a sentence. Improvements in autonomous systems technology and a growing demand within military operations are spurring interest in communication via vibrotactile displays. Tactile communication may become an important element of human-robot interaction (HRI), but it requires the development of messaging capabilities approaching the communication power of the speech and visual signals used in the military. In Experiment 1 (N = 38), we trained participants to identify sets of directional, dynamic, and static tactons and tested performance and workload following training. In Experiment 2 (N = 76), we introduced an extended training procedure and tested participants' ability to correctly identify two-tacton phrases. We also investigated the impact of multitasking on performance and workload. Individual difference factors were assessed. Experiment 1 showed that participants found dynamic and static tactons difficult to learn, but the enhanced training procedure in Experiment 2 produced competency in performance for all tacton categories. Participants in the latter study also performed well on two-tacton phrases and when multitasking. However, some deficits in performance and elevation of workload were observed. Spatial ability predicted some aspects of performance in both studies. Participants may be trained to identify both single tactons and tacton phrases, demonstrating the feasibility of developing a tactile language for HRI. Tactile communication may be incorporated into multi-modal communication systems for HRI. It also has potential for human-human communication in challenging environments. © 2014, Human Factors and Ergonomics Society.

Human Factors Process Task Analysis Liquid Oxygen Pump Acceptance Test Procedure for the Advanced Technology Development Center

NASA Technical Reports Server (NTRS)

Diorio, Kimberly A.

2002-01-01

A process task analysis effort was undertaken by Dynacs Inc. commencing in June 2002 under contract from NASA YA-D6. Funding was provided through NASA's Ames Research Center (ARC), Code M/HQ, and Industrial Engineering and Safety (IES). The John F. Kennedy Space Center (KSC) Engineering Development Contract (EDC) Task Order was 5SMA768. The scope of the effort was to conduct a Human Factors Process Failure Modes and Effects Analysis (HF PFMEA) of a hazardous activity and provide recommendations to eliminate or reduce the effects of errors caused by human factors. The Liquid Oxygen (LOX) Pump Acceptance Test Procedure (ATP) was selected for this analysis. The HF PFMEA table (see appendix A) provides an analysis of six major categories evaluated for this study. These categories include Personnel Certification, Test Procedure Format, Test Procedure Safety Controls, Test Article Data, Instrumentation, and Voice Communication. For each specific requirement listed in appendix A, the following topics were addressed: Requirement, Potential Human Error, Performance-Shaping Factors, Potential Effects of the Error, Barriers and Controls, Risk Priority Numbers, and Recommended Actions. This report summarizes findings and gives recommendations as determined by the data contained in appendix A. It also includes a discussion of technology barriers and challenges to performing task analyses, as well as lessons learned. The HF PFMEA table in appendix A recommends the use of accepted and required safety criteria in order to reduce the risk of human error. The items with the highest risk priority numbers should receive the greatest amount of consideration. Implementation of the recommendations will result in a safer operation for all personnel.

Holistic processing from learned attention to parts.

PubMed

Chua, Kao-Wei; Richler, Jennifer J; Gauthier, Isabel

2015-08-01

Attention helps us focus on what is most relevant to our goals, and prior work has shown that aspects of attention can be learned. Learned inattention to parts can abolish holistic processing of faces, but it is unknown whether learned attention to parts is sufficient to cause a change from part-based to holistic processing with objects. We trained subjects to individuate nonface objects (Greebles) from 2 categories: Ploks and Glips. Diagnostic information was in complementary halves for the 2 categories. Holistic processing was then tested with Plok-Glip composites that combined the kind of part that was diagnostic or nondiagnostic during training. Exposure to Greeble parts resulted in general failures of selective attention for nondiagnostic composites, but face-like holistic processing was only observed for diagnostic composites. These results demonstrated a novel link between learned attentional control and the acquisition of holistic processing. (c) 2015 APA, all rights reserved).

Semantic Coherence Facilitates Distributional Learning.

PubMed

Ouyang, Long; Boroditsky, Lera; Frank, Michael C

2017-04-01

Computational models have shown that purely statistical knowledge about words' linguistic contexts is sufficient to learn many properties of words, including syntactic and semantic category. For example, models can infer that "postman" and "mailman" are semantically similar because they have quantitatively similar patterns of association with other words (e.g., they both tend to occur with words like "deliver," "truck," "package"). In contrast to these computational results, artificial language learning experiments suggest that distributional statistics alone do not facilitate learning of linguistic categories. However, experiments in this paradigm expose participants to entirely novel words, whereas real language learners encounter input that contains some known words that are semantically organized. In three experiments, we show that (a) the presence of familiar semantic reference points facilitates distributional learning and (b) this effect crucially depends both on the presence of known words and the adherence of these known words to some semantic organization. Copyright © 2016 Cognitive Science Society, Inc.

A Model Driven Framework to Address Challenges in a Mobile Learning Environment

ERIC Educational Resources Information Center

Khaddage, Ferial; Christensen, Rhonda; Lai, Wing; Knezek, Gerald; Norris, Cathie; Soloway, Elliot

2015-01-01

In this paper a review of the pedagogical, technological, policy and research challenges and concepts underlying mobile learning is presented, followed by a brief description of categories of implementations. A model Mobile learning framework and dynamic criteria for mobile learning implementations are proposed, along with a case study of one site…

Mobile Learning Projects--A Critical Analysis of the State of the Art

ERIC Educational Resources Information Center

Frohberg, D.; Goth, C.; Schwabe, G.

2009-01-01

This paper provides a critical analysis of Mobile Learning projects published before the end of 2007. The review uses a Mobile Learning framework to evaluate and categorize 102 Mobile Learning projects, and to briefly introduce exemplary projects for each category. All projects were analysed with the criteria: context, tools, control,…

Work-Based Learning: A Resource Guide for Change. Test Draft.

ERIC Educational Resources Information Center

Hudson River Center for Program Development, Glenmont, NY.

This resource guide is intended to provide New York schools, business/industry, and others with resources to develop work-based learning strategies and components. Section 1 examines the scope, foundation, categories, and operation of work-based learning. Section 2 presents detailed information about the following forms of work-based learning:…

Using Learning Analytics to Assess Student Learning in Online Courses

ERIC Educational Resources Information Center

Martin, Florence; Ndoye, Abdou

2016-01-01

Learning analytics can be used to enhance student engagement and performance in online courses. Using learning analytics, instructors can collect and analyze data about students and improve the design and delivery of instruction to make it more meaningful for them. In this paper, the authors review different categories of online assessments and…

Some Aspects of Mathematical Model of Collaborative Learning

ERIC Educational Resources Information Center

Nakamura, Yasuyuki; Yasutake, Koichi; Yamakawa, Osamu

2012-01-01

There are some mathematical learning models of collaborative learning, with which we can learn how students obtain knowledge and we expect to design effective education. We put together those models and classify into three categories; model by differential equations, so-called Ising spin and a stochastic process equation. Some of the models do not…

A Teacher-Friendly Instrument in Identifying Learning Styles in the Classroom.

ERIC Educational Resources Information Center

Pitts, Joseph I.

This report describes a reliability and validity study on a learning styles instrument that was developed based on the Dunn, Dunn, & Price model. That model included 104 Likert five-point scale items for investigating 24 scales grouped into five categories considered likely to affect learning. The Learning Style Preference Inventory (LSPI)…

Learning while Babbling: Prelinguistic Object-Directed Vocalizations Indicate a Readiness to Learn

ERIC Educational Resources Information Center

Goldstein, Michael H.; Schwade, Jennifer; Briesch, Jacquelyn; Syal, Supriya

2010-01-01

Two studies illustrate the functional significance of a new category of prelinguistic vocalizing--object-directed vocalizations (ODVs)--and show that these sounds are connected to learning about words and objects. Experiment 1 tested 12-month-old infants' perceptual learning of objects that elicited ODVs. Fourteen infants' vocalizations were…

The Costs of Supervised Classification: The Effect of Learning Task on Conceptual Flexibility

ERIC Educational Resources Information Center

Hoffman, Aaron B.; Rehder, Bob

2010-01-01

Research has shown that learning a concept via standard supervised classification leads to a focus on diagnostic features, whereas learning by inferring missing features promotes the acquisition of within-category information. Accordingly, we predicted that classification learning would produce a deficit in people's ability to draw "novel…

A developmental examination of the conceptual structure of animal, artifact, and human social categories across two cultural contexts

PubMed Central

Rhodes, Marjorie; Gelman, Susan A.

2009-01-01

Previous research indicates that the ontological status that adults attribute to categories varies systematically by domain. For example, adults view distinctions between different animal species as natural and objective, but view distinctions between different kinds of furniture as more conventionalized and subjective. The present work (N = 435; ages 5-18) examined the effects of domain, age, and cultural context on beliefs about the naturalness vs. conventionality of categories. Results demonstrate that young children, like adults, view animal categories as natural kinds, but artifact categories as more conventionalized. For human social categories (gender and race), beliefs about naturalness and conventionality were predicted by interactions between cultural context and age. Implications for the origins of social categories and theories of conceptual development will be discussed. PMID:19524886