LITES, an intelligent tutoring system for legal problem solving in the domain of Dutch Civil law
ICAIL '93 Proceedings of the 4th international conference on Artificial intelligence and law
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Arguing with the Devil: teaching in Controversial Domains
ITS '96 Proceedings of the Third International Conference on Intelligent Tutoring Systems
Teaching case-based argumentation through a model and examples
Teaching case-based argumentation through a model and examples
Further Results from the Evaluation of an Intelligent Computer Tutor to Coach Self-Explanation
ITS '00 Proceedings of the 5th International Conference on Intelligent Tutoring Systems
Law, learning and representation
Artificial Intelligence - Special issue on AI and law
Artificial Intelligence - Special issue on AI and law
A comparison of tutor and student behavior in speech versus text based tutoring
HLT-NAACL-EDUC '03 Proceedings of the HLT-NAACL 03 workshop on Building educational applications using natural language processing - Volume 2
An Evaluation of a Hybrid Language Understanding Approach for Robust Selection of Tutoring Goals
International Journal of Artificial Intelligence in Education
Spoken Versus Typed Human and Computer Dialogue Tutoring
International Journal of Artificial Intelligence in Education
Toward supporting hypothesis formation and testing in an interpretive domain
Proceedings of the 2005 conference on Artificial Intelligence in Education: Supporting Learning through Intelligent and Socially Informed Technology
AIED Applications in Ill-Defined Domains
Proceedings of the 2007 conference on Artificial Intelligence in Education: Building Technology Rich Learning Contexts That Work
Artificial Intelligence in Medicine
Interactivity and expectation: eliciting learning oriented behavior with tutorial dialogue systems
INTERACT'05 Proceedings of the 2005 IFIP TC13 international conference on Human-Computer Interaction
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We compared two automated approaches to teaching distinguishing, a fundamental skill of case-based reasoning that involves assessing the relevant differences among cases in a context-sensitive way. The approaches are implemented in two versions of CATO, an ITS designed to teach law students basic skills of case-based legal argument. The original version of CATO employed a didactic explanatory dialogue. The newer version, CATO-Dial, teaches the same skill with a simulated dialectic argument in a courtroom setting. Our hypothesis was that students would learn better by engaging in the simulated argument than by receiving interactive explanation. We showed that students in the dialectic argument simulation group performed significantly better on certain sections of the post-test aimed at assessing transfer of their skills of distinguishing.