Use this URL to cite or link to this record in EThOS: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.584499
Title: Influence of prior predictiveness on human incidental learning
Author: Beesley, Thomas
ISNI:       0000 0003 5325 6707
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2008
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Abstract:
A common distinction made by theorists examining the mental processes contributing to human learning is that between the automatic formation of associations and controlled reasoning about beliefs. On the other hand, it is widely believed that animal cognition is fundamentally associative in nature. Over the last 25 years, the wealth of data from studies on animal learning has begun to shape our understanding of associative learning in humans. Yet it seems that whether automatic or controlled processes govern human learning is likely to be determined by the context in which learning takes place. Recent research has highlighted cue-predictiveness as an important component modulating the rate of human learning. Findings consistent with those seen in animals have suggested that an interpretation in terms of associative mechanisms is justified. However, the use of explicit learning paradigms - in which participants are encouraged to engage in hypothesis-testing - makes these data open to alternative explanations. In this thesis changes in cue-predictiveness were examined under incidental learning conditions: experimental tasks were used in which there was no instruction to learn, which should minimise the contribution to learning of controlled reasoning processes. In Chapters 2 and 3, a series of experiments provides evidence for a change in cue-associability under these conditions, primarily in a sequence learning task. Chapter 4 describes the application of several models of animal conditioning to the data generated in these experiments, and highlights a need for associative models to incorporate changes in cue-associability. The results of these simulations then provide a basis for modifications to a more complex model of sequence learning, the Simple Recurrent Network. Given the parallel between changes in associability and the allocation of attentional resources, Chapter 5 examines the possibility of changes in attention during sequence learning by measuring eye gaze.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID: uk.bl.ethos.584499  DOI: Not available
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