Building explanations from rules and structured cases
International Journal of Man-Machine Studies - AI and legal reasoning. Part 1
Incorporating procedural context into a model of case-based legal reasoning
ICAIL '91 Proceedings of the 3rd international conference on Artificial intelligence and law
Toward an intelligent tutoring system for teaching law students to argue with cases
ICAIL '91 Proceedings of the 3rd international conference on Artificial intelligence and law
Text-based intelligent systems
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Modeling Legal Arguments: Reasoning with Cases and Hypotheticals
Automated Generation of Examples for a Tutorial in Case-Based Argumentation
ITS '92 Proceedings of the Second International Conference on Intelligent Tutoring Systems
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
A hybrid CBR-IR approach to legal information retrieval
ICAIL '95 Proceedings of the 5th international conference on Artificial intelligence and law
The design and development of a tutoring system for legal domain
WBE'06 Proceedings of the 5th IASTED international conference on Web-based education
An ontology in OWL for legal case-based reasoning
Artificial Intelligence and Law
Advancing Development of Intercultural Competence through Supporting Predictions in Narrative Video
International Journal of Artificial Intelligence in Education
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To make legal arguments, one needs certain information about how to use cases effectively - dialectical information. In the broadest sense, dialectical information includes strategies for employing cases to justify legal conclusions (and responding to such justifications) and criteria for finding cases and deciding which cases to use. Making dialectical information explicit is important for teaching case-based argument. It is our experience that typically, law students do not have a very good set of dialectical strategies nor are they aware of the criteria. Even the most sophisticated legal information retrieval tools do not make such dialectical information explicit and assume that users have already learned it.For purposes of instruction, we have identified some useful dialectical information comprising a flexible argument plan, a set of eight argument moves that embody standard ways for using cases as examples in an argument, factors for representing factual strengths and weaknesses in cases, and an annotated Claim Lattice for organizing cases for the purpose of selecting and making argument moves to implement the plan. Our tutorial program CATO makes this dialectical information explicit through a combination of information retrieval tools and graphical display. In this paper, an extended example illustrated the utility, for an expert, of this dialectical information for constructing a sophisticated legal argument from the argument moves. We believe that practice with the CATO program will make students aware of the existence of argumentative strategies and criteria and help them to apply this dialectical information to construct better arguments.