A model-building learning environment with explanatory feedback to erroneous models

Tomoya Horiguchi*, Tsukasa Hirashima, Kenneth D Forbus

*Corresponding author for this work

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

2 Scopus citations

Abstract

Many model-building learning environments (MBEs) have been developed to support students in acquiring the ability to build appropriate models of physical systems. However, they can't explain how the simulated behavior of an erroneous model is unnatural. Additionally, they can't create any feedback when the model is unsolvable. We introduce a MBE which overcomes these problems with two technical ideas: (1) robust simulator which analyzes the consistency of a model and relaxes some constraints if necessary, and (2) semantics of constraints which is a systematic description of physical meanings of constraints and provides heuristics for explaining the behavioral unnaturalness.

Original languageEnglish (US)
Title of host publicationIntelligent Tutoring Systems - 11th International Conference, ITS 2012, Proceedings
Pages620-621
Number of pages2
DOIs
StatePublished - 2012
Event11th International Conference on Intelligent Tutoring Systems, ITS 2012 - Chania, Crete, Greece
Duration: Jun 14 2012Jun 18 2012

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume7315 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Other

Other11th International Conference on Intelligent Tutoring Systems, ITS 2012
CountryGreece
CityChania, Crete
Period6/14/126/18/12

Keywords

  • errorawareness/ correction
  • model-building learning environment
  • qualitative reasoning
  • robust simulator
  • semantics of constraints

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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