External cognition: how do graphical representations work?
International Journal of Human-Computer Studies
Causality: models, reasoning, and inference
Causality: models, reasoning, and inference
Visualizing argumentation: software tools for collaborative and educational sense-making
Visualizing argumentation: software tools for collaborative and educational sense-making
Toward legal argument instruction with graph grammars and collaborative filtering techniques
ITS'06 Proceedings of the 8th international conference on Intelligent Tutoring Systems
ITS '08 Proceedings of the 9th international conference on Intelligent Tutoring Systems
Toward assessing law students' argument diagrams
Proceedings of the 12th International Conference on Artificial Intelligence and Law
Assessing Argument Diagrams in an Ill-defined Domain
Proceedings of the 2009 conference on Artificial Intelligence in Education: Building Learning Systems that Care: From Knowledge Representation to Affective Modelling
Argument Diagramming and Diagnostic Reliability
Proceedings of the 2009 conference on Legal Knowledge and Information Systems: JURIX 2009: The Twenty-Second Annual Conference
Evaluating an Intelligent Tutoring System for Making Legal Arguments with Hypotheticals
International Journal of Artificial Intelligence in Education
Constructing Causal Diagrams to Learn Deliberation
International Journal of Artificial Intelligence in Education
LASAD: Flexible representations for computer-based collaborative argumentation
International Journal of Human-Computer Studies
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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.