What law students need to know to WIN

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.

REFERENCES

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INDEX TERMS

Primary Classification:
  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.1 Applications and Expert Systems
          Subjects: Law

Additional Classification:
  H. Information Systems
  H.1 MODELS AND PRINCIPLES
      H.1.2 User/Machine Systems
          Subjects: Human factors

  I. Computing Methodologies
  I.2 ARTIFICIAL INTELLIGENCE
      I.2.7 Natural Language Processing
          Subjects: Text analysis

  J. Computer Applications
  J.1 ADMINISTRATIVE DATA PROCESSING
      Subjects: Law

  K. Computing Milieux
  K.3 COMPUTERS AND EDUCATION
      K.3.1 Computer Uses in Education
          Subjects: Computer-assisted instruction (CAI)

General Terms:
Algorithms, Human Factors, Legal Aspects