Automating the modeling of learners' erroneous behaviors in model-tracing tutors

Modeling learners is a fundamental part of intelligent tutoring systems. It allows tutors to provide personalized feedback and to assess the learners' mastery over a task domain. One aspect often overlooked is the modeling of erroneous behaviors that can be used to provide error specific feedback. This is especially true for model-tracing tutors that usually require erroneous procedural knowledge associated to each of the possible error. This process can be automated thanks to a task independent model describing the learners' erroneous behaviors. The model proposed in this paper is inspired by the Sierra theory of procedural error and is developed for ASTUS, an authoring framework for model-tracing tutors.