Vincent Aleven
ABSTRACT
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.
- Aleven and Ashley, 1992.Vincent Aleven and Kevin D. Ashley. Automated Generation of Examples for a Tutorial in Case-Based Argumentation. In C. Frasson, G. Gauthier, and G.I. McCalla (eds.), Proceedings of the Second international Conference on Intelligent Tutoring Systems, 576-584. Montreal, 1992. Google Scholar
Digital Library
- Ashley, 1990.Kevin D. Ashley. Modeling Legal Argument: Reasoning with Cases and Hypotheticals. MIT Press, Cambridge, 1990. Google ScholarDigital Library
- Ashley and Aleven, 1991.Kevin D. Ashley and Vincent Aleven. Toward an Intelligent Tutoring System for Teaching Law Students to Argue with Cases. In Proceedings of the Third International Conference on Articial Intelligence and Law, 42-52. Oxford, England, 1991. Google ScholarDigital Library
- Ashley and Aleven, 1992.Kevin D. Ashley and Vincent Aleven. Generating Dialectical Examples Automatically. In Proceedings AAAI-92, 654-660. San Jose, CA, 1992.Google Scholar
- Berman and Hafner, 1991.Donald H. Berman and Carole D. Hafner. incorporating Procedural Context into a Model of Case-Based Legal Reasoning. In Proceedings of the Third International Conference on Articial Intelligence and Law, 12-20. Oxford, England, 1991. Google ScholarDigital Library
- Branting, 1991.L. Karl Branting. Building Explanations from Rules and Structured Cases. International Journal of Man-Machine Studies 34(6):797-837, 1991. Google ScholarDigital Library
- Burton, 1985.Steven J. Burton. An Introduction to Law and Legal Reasoning. Little, Brown, Boston, 1985.Google Scholar
- Croft and Turtle, 1992.W. Bruce Croft, and Howard R. Turtle. Text Retrieval and Inference. In P. Jacobs (ed.), Text-Based Intelligent Systems, 127-155. L. Erlbaum, Hillsdale, NJ, 1992. Google ScholarDigital Library
- MacGregor, 1988.Robert M. MacGregor. A Deductive Pattern Matcher. In Proceedings AAAI-88, 403-408.Saint Paul, MN, 1988.Google Scholar
- Skalak and Rissland, 1992.David B. Skalak and Edwina L. Rissland. Arguments and Cases: An Inevitable Intertwining. Artificial Intelligence and Law 1(1):3-44, 1992.Google ScholarDigital Library
Index Terms
- What law students need to know to WIN
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