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PubMed2004

Learning categories by making predictions: an investigation of indirect category learning.

Categories are learned in many ways, but studies of category learning have generally focused on classification learning. This focus may limit the understanding of categorization processes. Two experiments were conducted in which participants learned categories of animals by predicting how much food each animal would eat. We refer to this as indirect category learning, because the task andthe feedback were not directly related to category membership, yet category learning was necessary for good performance in the task. In the first experiment, we compared the performance of participants who learned the categories indirectly with the performance of participants who first learned to classify the objects. In the second experiment, we replicated the basic findings and examined attention to different features during the learning task. In both experiments, participants who learned in the prediction-only condition displayed a broader distribution of attention than participants who learned in the classification-and-prediction condition did. Some participants in the prediction-only group learned the family resemblance structure of the categories, even when a perfect criterial attribute was present. In contrast, participants who first learned to classify the objects tended to learn the criterial attribute.

Forecasting↗
PubMed2005

Dyslexics are impaired on implicit higher-order sequence learning, but not on implicit spatial context learning.

Developmental dyslexia is characterized by poor reading ability and impairments on a range of tasks including phonological processing and processing of sensory information. Some recent studies have found deficits in implicit sequence learning using the serial reaction time task, but others have not. Other skills, such as global visuo-spatial processing may even be enhanced in dyslexics, although deficits have also been noted. The present study compared dyslexic and non-dyslexic college students on two implicit learning tasks, an alternating serial response time task in which sequential dependencies exist across non-adjacent elements and a spatial context learning task in which the global configuration of a display cues the location of a search target. Previous evidence indicates that these implicit learning tasks are based on different underlying brain systems, fronto-striatal-cerebellar circuits for sequence learning and medial temporal lobe for spatial context learning. Results revealed a double dissociation: dyslexics showed impaired sequence learning, but superior spatial context learning. Consistent with this group difference, there was a significant positive correlation between reading ability (single real and non-word reading) and sequence learning, but a significant negative correlation between these measures and spatial context learning. Tests of explicit knowledge confirmed that learning was implicit for both groups on both tasks. These findings indicate that dyslexic college students are impaired on some kinds of implicit learning, but not on others. The specific nature of their learning deficit is consistent with reports of physiological and anatomical differences for individuals with dyslexia in frontal and cerebellar structures.

Adolescent↗
PubMed2003

Learning a single limb multijoint coordination pattern: the impact of a mechanical constraint on the coordination dynamics of learning and transfer.

The coordination dynamics of learning and transfer were studied in a single limb multijoint task requiring rhythmic elbow and wrist motions. Participants were required to learn a continuous 90 degrees relative phase pattern between the elbow and wrist such that an angle-angle plot of elbow and wrist motion produced a circle with a diameter of 80 degrees. Joint motion was restricted to elbow and wrist flexion-extension on the sagittal plane and the to-be-learned 90 degrees relative phase pattern was always practiced with the learning arm supine. Cycling frequency was controlled by a pacing metronome set at 0.75 Hz. Issues regarding effector-independent and effector-specific transfer were addressed with three transfer conditions: (1). learning arm prone (LP), (2). non-learning arm supine (NS), and (3). non-learning arm prone (NP). Four subjects learned the required relative phase (90 degrees ) and amplitude (80 degrees ) pattern with their dominant arm and four with their non-dominant arm. The experiment produced three main findings with regard to elbow-wrist control processes: First, seven of eight participants spontaneously produced a wrist-lagging coordination pattern (wrist motion lagged elbow motion) in learning to produce a continuous relative phase pattern of 90 degrees between the elbow and wrist. The wrist-lagging pattern may emerge as a result of the central nervous system exploiting the transfer of angular momentum from the elbow to the wrist as the elbow rotates up and down. The influence of interactive torque on elbow-wrist coordination represents an important mechanical constraint on the selection of intralimb coordination strategies during learning. The transfer conditions revealed that this mechanical constraint was effector-independent with regard to ipsilateral limb transfer (LP) and contralateral limb transfer (NS and NP). Second, consistent transfer of the learned relative phase pattern across ipsilateral and contralateral conditions demonstrates an effector-independent representation for this control variable. The effector-independent and effector-specific nature of joint amplitude transfer was dependent to some degree on learning arm, dominant or non-dominant, and the amount of practice, 1 day versus 5 days. Third, learning of the required 90 degrees relative phase pattern may be characterized as a phase transition leading to the formation of a stable attractor in the elbow-wrist coordination landscape. The above findings are discussed with respect to motor programming and coordination dynamic viewpoints on effector-independent and effector-specific aspects of motor equivalence.

Adult↗
PubMed2004

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

This article proposes a connectionist model of the social learning theory developed by Bandura (1977). The theory posits that an individual in an interactive situation is capable of learning new behaviours merely by observing them in others. Such learning is acquired through an initial phase in which the individual memorizes what he has observed (observation phase), followed by a second phase where he puts the recorded observations to use as a guide for adjusting his own behaviour (reproduction phase). We shall refer to the two above-mentioned phases to demonstrate that it is conceivable to simulate learning by observation otherwise than through the recording of perceived information using symbolic representation. To this end we shall rely on the formalism of ecological neuron networks (Parisi, Cecconi, & Nolfi, 1990) to implement an agent provided with the major processes identified as essential to learning through observation. The connectionist model so designed shall implement an agent capable of recording perceptive information and producing motor behaviours. The learning situation we selected associates an agent demonstrating goal-achievement behaviour and an observer agent learning the same behaviour by observation. Throughout the acquisition phase, the demonstrator supervises the observer's learning process based on association between spatial information (input) and behavioural information (output). Representation thus constructed then serves as an adjustment guide during the production phase, involving production by the observer of a sequence of actions which he compares to the representation stored in distributed form as constructed through observation. An initial simulation validates model architecture by confirming the requirement for both phases identified in the literature (Bandura, 1977) to simulate learning through observation. The representation constructed over the observation phase evidences acquisition of observed behaviours, although this phase alone is not sufficient to ensure accurate reproduction and must be made functional through the production phase (Deakin & Proteau, 2000). Results obtained through a second simulation replicate those produced by Bandura & Jeffery (1973), who observed that the individual tested following the retention phase recalled recorded information better than he realized in the production phase. The outcome of a third simulation shows that, when performing the transfer task, agents performed the task all the more effectively when they were required to learn a simple path which facilitated knowledge transfer to an adjacent situation. New explanatory assumptions of the mechanics of learning through observation may be produced through OLEANNet. Thus, observed deterioration between memorization and production is caused by successive approximations which occur in the acquisition phase then in the production phase. Further, depending on the type of learning undergone by agents, use of representation as a production guide induces a more or less stringent constraint in the approximation of actual behaviour. This results, during the transfer task, in the ability to effectively generalize acquired knowledge where such knowledge is not specifically related to the task at hand. In conclusion, connectionist model architecture appears valid for modeling learning through observation as defined by Bandura (1977). However, certain limitations appear during implementation, especially in terms of the observed behaviour's availability and the planning of produced behaviours that future developments are liable to counter.

Humans↗
PubMed1999

Pupils' reasons for learning and behaving and for not learning and behaving in English and maths lessons in a secondary school.

BACKGROUND: There is renewed interest in motivation and school learning, though there has been relatively little theory-linked research in English schools. AIMS: In the first stage, to explore pupils' reasons for learning and behaving and for not learning and behaving in English, maths and other subjects. In the second stage, to examine differences in reasons across subjects, for learning and behaving and for not learning and behaving for boys and girls in two year groups in one secondary school. SAMPLE: Stage 1, 16 pupils in years 7, 8 and 9 in two London secondary schools; Stage 2, 267 pupils in years 7 and 9 in one of these schools. METHODS: Stage 1--semi-structured interviews were conducted to elicit different kinds of reasons conceptualised in terms of the Deci & Ryan's (1985) framework of self-determination. From these elicited reasons, an inventory 'Why I Learn' was designed. Stage 2--the inventory was administered to identify reasons for learning and behaving and for not learning and behaving in English and maths. RESULTS: Parent introjected reasons were the highest for learning and behaving while teacher introjected and intrinsic reasons were the lowest. Intrinsic reasons were highest for not learning and behaving. Year group differences in reason levels were more significant than gender or subject differences. Reasons for learning and behaving were more differentiated from each other than reasons for not learning and behaving. DISCUSSION: The results are discussed in terms of their significance for self-determination theory, research into the conditions promoting greater self-determination in school learning and further development of the inventory for programme evaluation.

Adolescent↗
PubMed1998

Teachers' experiential learning about learning.

OBJECTIVE: An experiential model of learning suggests that changing a learner's understanding will lead to the learner choosing to change behavior. A workshop was designed for medical educators to examine their understanding of learning in order to change their behavior as teachers. This article describes that workshop which was presented as part of a conference on successful techniques for education of primary care practitioners. METHOD: Eighteen medical educators participated in the workshop. The educators were instructed to reflect on a recent personal learning experience. Group discussion led to production of a list of components of effective learning. These learning components were then applied in small groups to three hypothetical tasks related to mental health education. RESULTS: Essential characteristics of three generic features of learning were identified: characteristics of the teacher, learner, and learning experience. When these characteristics were then applied to the hypothetical tasks, a major theme that emerged was a focus on the importance of learner motivation. CONCLUSIONS: The essential components of learning and their application demonstrate the importance of adult learning theory in which it is more important for the learner than for the teacher to determine what, when, and how to learn. This is in contrast to traditional medical education in which the teacher decides what to learn and if it has been learned. To improve education for practicing primary care providers, a shift from a teaching paradigm to a learning paradigm is indicated.

Adult↗
PubMed1992

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

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

Algorithms↗
PubMed2006

Implicit learning is intact in adult developmental dyslexic readers: evidence from the serial reaction time task and artificial grammar learning.

Previous research yielded equivocal results concerning implicit learning abilities of developmental dyslexic readers. These studies employed a sequence learning task that requires a motor response to each stimulus. However, implicit learning has been often studied using non-motor tasks. Thus, we investigated implicit learning capabilities of adult developmental dyslexic readers in two standard implicit learning paradigms differing in the involvement of the motor system, namely the serial response time task (SRTT) and artificial grammar learning (AGL).Twelve adult developmental dyslexic and twelve age- and sex- matched normal readers were tested. In the serial response time task (SRTT), participants are exposed to a structured display. Learning is measured by comparing response time (RT) to the structured sequence with RT to a random display. In the artificial grammar learning task (AGL), letter strings following a markovian finite state grammar are presented. In a subsequent test phase subjects have to judge new letter strings according to their grammaticality. Learning of the stimulus regularities was found in both tasks and for both groups of subjects. Furthermore, participants were unaware of the underlying stimulus construction principles. Dyslexic readers were unimpaired in SRTT as well as artificial grammar learning relative to normal readers. These findings show that implicit learning is intact in dyslexia. Intact implicit learning capabilities should be taken into account when designing training programs for developmental dyslexic readers.

Adult↗
PubMedDate not supplied

Word-learning skills of deaf preschoolers: the development of novel mapping and rapid word-learning strategies.

Word-learning skills of 19 deaf/hard-of-hearing preschoolers were assessed by observing their ability to learn new words in two contexts. The first context required the use of a novel mapping strategy (i.e., making the inference that a novel word refers to a novel object) to learn the new words. The second context assessed the ability to learn new words after minimal exposure when reference was explicitly established. The children displayed three levels of word-learning skills. Eleven children learned words in both contexts. Five were able to learn new words rapidly only when reference was explicitly established. Two children did not learn new words rapidly in either context. The latter seven children were followed longitudinally. All children eventually acquired the ability to learn new words in both contexts. The deaf children's word-learning abilities were related to the size of their vocabularies. The present study suggests that word-learning strategies are acquired even when children are severely delayed in their language development and they learn language in an atypical environment.

Association Learning↗
PubMed1999

Intact learning of artificial grammars and intact category learning by patients with Parkinson's disease.

Patients with Parkinson's disease (PD) have been shown to be impaired on some nondeclarative memory tasks that require cognitive skill learning (perceptual-motor sequence learning, probabilistic classification). To determine what other skill-based tasks are impaired, 13 patients with PD were tested on artificial grammar learning, artificial grammar learning with transfer to novel lettersets, and prototype learning. Patients with PD performed similarly to controls on all 3 tests. The intact learning exhibited by PD patients on these tests suggests that nondeclarative cognitive skill learning is not a single entity supported by the neostriatum. If learning the regularities among visual stimuli is the principal feature of artificial grammar learning and prototype learning, then these forms of skill learning may be examples of perceptual learning, and they may occur in early visual cortical processing areas.

Aged↗
PubMedDate not supplied

How does the severity of a learning disability affect working memory performance?

Working memory performance was examined in children aged 11-12 years who had borderline, mild, and moderate learning disabilities. Comparisons with children of average abilities were used to determine whether those with more severe learning disabilities had greater impairments in working memory. Seven measures of working memory span were used to assess temporary phonological short-term storage (digit span, word span), temporary visuo-spatial short-term storage (pattern span, spatial span), and temporary short-term storage with additional processing, or central executive, demands (listening span. odd one out span, reverse digit span). Children with mild and moderate learning disabilities were impaired on all measures of working memory compared to children of average abilities. Children with borderline learning disabilities were just as good as children with average abilities on visuo-spatial and complex span tasks, but showed an impairment on phonological span tasks. Children with moderate learning disabilities were indistinguishable from children with mild learning disabilities on simple span tasks, but were significantly poorer than the mild group on the more demanding complex span tasks. For the group as a whole, working memory was strongly related to mental age.

Case-Control Studies↗
PubMed1996

A fuzzy adaptive learning control network with on-line structure and parameter learning.

This paper addresses a general connectionist model, called Fuzzy Adaptive Learning Control Network (FALCON), for the realization of a fuzzy logic control system. An on-line supervised structure/parameter learning algorithm is proposed for constructing the FALCON dynamically. It combines the backpropagation learning scheme for parameter learning and the fuzzy ART algorithm for structure learning. The supervised learning algorithm has some important features. First of all, it partitions the input state space and output control space using irregular fuzzy hyperboxes according to the distribution of training data. In many existing fuzzy or neural fuzzy control systems, the input and output spaces are always partitioned into "grids". As the number of input/output variables increase, the number of partitioned grids will grow combinatorially. To avoid the problem of combinatorial growing of partitioned grids in some complex systems, the proposed learning algorithm partitions the input/output spaces in a flexible way based on the distribution of training data. Second, the proposed learning algorithm can create and train the FALCON in a highly autonomous way. In its initial form, there is no membership function, fuzzy partition, and fuzzy logic rule. They are created and begin to grow as the first training pattern arrives. The users thus need not give it any a priori knowledge or even any initial information on these. In some real-time applications, exact training data may be expensive or even impossible to obtain. To solve this problem, a Reinforcement Fuzzy Adaptive Learning Control Network (RFALCON) is further proposed. The proposed RFALCON is constructed by integrating two FALCONs, one FALCON as a critic network, and the other as an action network. By combining temporal difference techniques, stochastic exploration, and a proposed on-line supervised structure/parameter learning algorithm, a reinforcement structure/parameter learning algorithm is proposed, which can construct a RFALCON dynamically through a reward/penalty signal. The ball and beam balancing system is presented to illustrate the performance and applicability of the proposed models and learning algorithms.

Algorithms↗
PubMed2002

Spatial generalization of learning in smooth pursuit eye movements: implications for the coordinate frame and sites of learning.

We have examined the underlying coordinate frame for pursuit learning by testing how broadly learning generalizes to different retinal loci and directions of target motion. Learned changes in pursuit were induced using double steps of target speed. Monkeys tracked a target that stepped obliquely away from the point of fixation, then moved smoothly either leftward or rightward. In each experimental session, we adapted the response to targets moving in one direction across one locus of the visual field by changing target speed during the initial catch-up saccade. Learning occurred in both presaccadic and postsaccadic eye velocity. The changes were specific to the adapted direction and did not generalize to the opposite direction of pursuit. To test the spatial scale of learning, we examined the responses to targets that moved across different parts of the visual field at the same velocity as the learning targets. Learning generalized partially to motion presented at untrained locations in the visual field, even those across the vertical meridian. Experiments with two sets of learning trials showed interference between learning at different sites in the visual field, suggesting that pursuit learning is not capable of spatial specificity. Our findings are consistent with the previous suggestions that pursuit learning is encoded in an intermediate representation that is neither strictly sensory nor strictly motor. Our data add the constraint that the site or sites of pursuit learning must process visual information on a fairly large spatial scale that extends across the horizontal and vertical meridians.

Animals↗
PubMed2003

Student use and perceptions of different learning aids in a problem-based learning (PBL) dentistry course.

First-year dental students in a new problem-based learning (PBL) course, the Bachelor of Dentistry (BDent) Program at the University of Sydney, Australia, completed the Study Process Questionnaire and two other questionnaires in this study. The study aimed to identify student perceptions of a written formative assessment and the helpfulness of various learning aids used to prepare for this assessment and preparing to be a dental clinician. Correlations between approach to learning and perceptions of assessment and learning aids showed theoretically expected associations. Surface learning was associated with students' concerns regarding whether assessment items reflected curriculum content, a valuing of lectures as a learning aid, and low scores for theme sessions. Deep learning was associated with a perception that the assessment tested application of basic and clinical sciences and a valuing of both independent study groups and learning topics as learning aids. An achievement orientation to learning was associated with a valuing of formative assessment as a learning aid and an intention to modify study habits as a result of participating in formative assessment. The findings provide insight into student learning in a PBL context that will help teachers and curriculum developers better understand the value of teaching aids provided in the program and the impact assessment has on study styles.

Achievement↗