‘Tis Better to Construct than to Receive? The Effects of Diagram Tools on Causal Reasoning

Matthew W. Easterday, Vincent Aleven, Richard Scheines

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

23 Scopus citations

Abstract

Previous research on the use of diagrams for argumentation instruction has highlighted, but not conclusively demonstrated, their potential benefits. We examine the relative benefits of using diagrams and diagramming tools to teach causal reasoning about public policy. Sixty-three Carnegie Mellon University students were asked to analyze short policy texts using either: 1) text only, 2) text and a pre-made, correct diagram representing the causal claims in the text, or 3) text and a diagramming tool with which to construct their own causal diagram. After a pretest and training, we tested student performance on a new policy text and found that students given a correct diagram (condition 2 above) significantly outperformed the other groups. Finally, we compared learning by testing students on a third policy problem in which we removed all diagram or tool aids and found that students who constructed their own diagrams (condition 3 above) learned the most. We describe these results and interpret them in a way that foreshadows work we now plan for a cognitive-tutor on causal diagram construction.

Original languageEnglish (US)
Title of host publicationArtificial Intelligence in Education
Subtitle of host publicationBuilding Technology Rich Learning Contexts That Work
EditorsRosemary Luckin, Kenneth R. Koedinger, Jim Greer
PublisherIOS Press BV
Pages93-100
Number of pages8
ISBN (Electronic)9781586037642
StatePublished - 2007
Externally publishedYes
Event13th International Conference on Artificial Intelligence in Education, AIED 2007 - Los Angeles, United States
Duration: Jul 9 2007Jul 13 2007

Publication series

NameFrontiers in Artificial Intelligence and Applications
Volume158
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314

Conference

Conference13th International Conference on Artificial Intelligence in Education, AIED 2007
Country/TerritoryUnited States
CityLos Angeles
Period7/9/077/13/07

Keywords

  • Causal reasoning
  • Diagrammatic reasoning
  • External representations

ASJC Scopus subject areas

  • Artificial Intelligence

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