Authoring problem-solving ITS with ASTUS: An interactive event

Luc Paquette, Jean François Lebeau, André Mayers

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

Abstract

ASTUS: Problem-solving or step-based ITS have been proven successful for well-defined domains, particularly in well-defined tasks, but their success is mitigated by their cost. Typically, the main factor behind the cost is the efforts needed to model the task domain. Different approaches have been investigated to reduce these efforts: Model-Tracing Tutors (e.g. Cognitive Tutors [1], Andes [2]), Constraint-Based Tutors (e.g. SQL-Tutor [3], ASPIRE [4]) and Example-Tracing Tutors (e.g. CTAT [5], ASSISTment [6]).

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education - 16th International Conference, AIED 2013, Proceedings
EditorsH Chad Lane, Kalina Yacef, Jack Mostow, Philip Irvin Pavlik
PublisherSpringer
Pages934-935
Number of pages2
ISBN (Print)9783642391118
DOIs
StatePublished - 2013
Externally publishedYes
Event16th International Conference on Artificial Intelligence in Education, AIED 2013 - Memphis, TN, United States
Duration: Jul 9 2013Jul 13 2013

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7926 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other16th International Conference on Artificial Intelligence in Education, AIED 2013
Country/TerritoryUnited States
CityMemphis, TN
Period7/9/137/13/13

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science

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