Teaching Case-Based Argumentation Through a Model and Examples

286 Pages·2001·1.23 MB·English

Teaching Case-Based Argumentation
Through a Model and Examples
Ph.D. Dissertation
Vincent Aleven
Intelligent Systems Program
University of Pittsburgh
1997

TEACHING CASE-BASED ARGUMENTATION
THROUGH A MODEL AND EXAMPLES
by
Vincent A. W. M. M. Aleven
M.Sc. Computer Science, Delft University of Technology, 1988
M.Sc. Intelligent Systems, University of Pittsburgh, 1992
Submitted to the Graduate Faculty of
the Intelligent Systems Program in partial fulfillment
of the requirements for the degree of
Doctor of Philosophy
University of Pittsburgh
1997

Copyright by Vincent A. W. M. M. Aleven
1997

TEACHING CASE-BASED ARGUMENTATION
THROUGH A MODEL AND EXAMPLES
Vincent Aleven, Ph.D.
University of Pittsburgh, 1997
CATO is an intelligent learning environment designed to help beginning law students
learn basic skills of making arguments with cases. Using CATO, students practice
tasks of induction and analogical argumentation. They practice testing theories against
a body of cases and making written arguments about a problem, comparing and con-
trasting it to past cases.
CATO’s model addresses arguments in which two opponents analogize a problem
to favorable cases, distinguish unfavorable cases, assess the significance of similarities
and differences between cases in light of normative knowledge about the domain, and
use that knowledge to organize multi-case arguments. CATO communicates the model
to students by presenting dynamically-generated argumentation examples and by rei-
fying argument structure based on the model. CATO also provides a case database and
tools based on the model that help make students’ tasks more manageable.
CATO was evaluated in the context of an actual legal writing course, in a study
involving 30 first-year law students. We found that instruction with CATO leads to
statistically significant improvement in students’ basic argumentation skills, compara-
ble to that achieved by an experienced legal writing instructor teaching groups of 4-10
students. However, on a more advanced legal writing assignment, meant to explore the
frontier of the CATO instruction, students taught by the legal writing instructor had
higher grades, suggesting a need for more integrated practice with the CATO model.
CATO contributes to AI research fields modeling educational techniques as well as
case-based and legal reasoning. It is a novel result that students can learn basic argu-
mentation skills by studying computer-generated examples. It means that an instruc-
tional system does not necessarily need to rely on a very sophisticated understanding
of students’ arguments, which would be a significant obstacle to developing such sys-
tems.
Also, CATO presents novel techniques for using background knowledge to support
similarity assessment in case-based reasoning. Drawing on its background knowledge,
CATO characterizes and re-characterizes cases in order to argue that two cases are
similar or different. This is an important skill in the legal domain not previously mod-
eled. CATO’s arguments may help a user in assessing the similarity of cases in a more
discriminatory way.