Rules of Order: Process Models of Human Learning

Josef Nerb, Frank E. Ritter, Pat Langley

Research output: Chapter in Book/Report/Conference proceedingChapter

1 Scopus citations

Abstract

Science is concerned not only with data, but also with models or theories that explain those data. Because human cognition is dynamic and involves change over time, accounts of cognition often take the form of process models, which are sometimes called cognitive models. This chapter reviews the form such models have taken and their relation to order effects in learning. It begins by discussing the connection between artificial intelligence (AI) systems, including those from machine learning and computational models of human behavior, including some illustrations of the latter. It presents a computational model of order effects on a cognitive task, cast within a particular but simplified theoretical framework. It then explores more broadly the possible sources of order effects within such models and then briefly considers an alternative approach that models human behavior at a more abstract level. The chapter closes with some open problems in the area of modeling order effects and a charge to new modelers.

Original languageEnglish (US)
Title of host publicationIn Order to Learn
Subtitle of host publicationHow the sequence of topics influences learning
PublisherOxford University Press
ISBN (Electronic)9780199893751
ISBN (Print)9780195178845
DOIs
StatePublished - Apr 1 2010

All Science Journal Classification (ASJC) codes

  • General Psychology

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