A computational model of the role of prior knowledge in learning to operate an interactive device

T.D. Freudenthal

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

This paper describes a computational model that simulates the behaviour of subjects in an experiment where they learn to control an interactive device. The model was specified in the ACT-R cognitive architecture. The amount of foreknowledge that the subjects had was manipulated, and the resulting differences in behaviour were assessed. The model employs a combination of instance learning and difference reduction strategies. Subjects without foreknowledge start out exploring the device in a random fashion, which is replaced by more informed strategies as the number of successful instances increases. For subjects with foreknowledge, strategies are more informed from the outset. The model provides a reasonable fit to the number of actions that both groups of subjects require for later rounds, but is less successful in modelling the behaviour of very early attempts.
Original languageEnglish
Pages (from-to)104-112
Number of pages9
JournalIPO Annual Progress Report
Volume35
Publication statusPublished - 2000

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