Affiliations: University of Hamburg, Department of Informatics,
Vogt-Kölln-Str. 30, D-22527 Hamburg, Germany. E-mail:
{le,menzel}@informatik.uni-hamburg.de;
http://nats-www.informatik.uni-hamburg.de
Abstract: In this paper, we introduce logic programming as a domain that
exhibits some characteristics of being ill-defined. In order to diagnose
student errors in such a domain, we need a means to hypothesise the student's
intention, that is the strategy underlying her solution. This is achieved by
weighting constraints, so that hypotheses about solution strategies,
programming patterns and error diagnoses can be ranked and selected. Since
diagnostic accuracy becomes an increasingly important issue, we present an
evaluation methodology that measures diagnostic accuracy in terms of (1) the
ability to identify the actual solution strategy, and (2) the reliability of
error diagnoses. The evaluation results confirm that the system is able to
analyse a major share of real student solutions, providing highly informative
and precise feedback.