Proceedings of the AAAI Conference on Artificial Intelligence, 5
Cognitive Modeling and Education
A significant portion of tutorial interactions revolve around the bugs a student makes. When a tutor performs an intervention to help a student fix a programming bug, the problem of deciding which intervention to perform requires extensive reasoning. In this paper, we identify five tutorial considerations tutors appear to use when they reason about how to construct tutorial interventions for students’ bugs. Using data collected from human tutors working in the domain of introductory computer programming, we identify the knowledge tutors use when they reason about the five considerations and show that tutors are consistent in the ways that they use the kinds of knowledge to reason about students’ bugs. In this paper we illustrate our findings of tutorial consistency by showing that tutors are consistent in how they reason about bug criticality and bug categories. We suggest some implications of these empirical findings for the construction of intelligent tutoring systems.