A comparison of decision-theoretic, fixed-policy and random tutorial action selection

R. Charles Murray, Kurt VanLehn

Research output: Chapter in Book/Report/Conference proceedingConference contribution

23 Scopus citations

Abstract

DT Tutor (DT), an ITS that uses decision theory to select tutorial actions, was compared with both a Fixed-Policy Tutor (FT) and a Random Tutor (RT). The tutors were identical except for the method they used to select tutorial actions: FT employed a common fixed policy while RT selected randomly from relevant actions. This was the first comparison of a decision-theoretic tutor with a non-trivial competitor (FT). In a two-phase study, first DT's probabilities were learned from a training set of student interactions with RT. Then a panel of judges rated the actions that RT took along with the actions that DT and FT would have taken in identical situations. DT was rated higher than RT and also higher than FT both overall and for all subsets of scenarios except help requests, for which DT's and FT's ratings were equivalent.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 8th International Conference, ITS 2006, Proceedings
PublisherSpringer Verlag
Pages114-123
Number of pages10
ISBN (Print)3540351590, 9783540351597
DOIs
StatePublished - 2006
Externally publishedYes
Event8th International Conference on Intelligent Tutoring Systems, ITS 2006 - Jhongli, Taiwan, Province of China
Duration: Jun 26 2006Jun 30 2006

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume4053 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other8th International Conference on Intelligent Tutoring Systems, ITS 2006
Country/TerritoryTaiwan, Province of China
CityJhongli
Period6/26/066/30/06

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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