Carlson, R., Matsuda, N., Koedinger, K. R., & Rose, C. (2012). Building a Conversational SimStudent. In S. Cerri & W. Clancey (Eds.), Proceedings of International Conference on Intelligent Tutoring Systems (pp. 563-569). Heidelberg, Berlin: Springer-Verlag.
Abstract: SimStudent, an intelligent-agent architecture that generates a cognitive model from worked-out examples, currently interacts with human subjects only in a limited capacity. In our application, SimStu- dent attempts to solve algebra equations, querying the user about the correctness of each step as it solves, and the user explains the step in natural language. Based on that input, SimStudent can choose to ask fur- ther questions that prompt the user to think harder about the problem in an attempt to elicit deeper responses. We show how text classification techniques can be used to train models that can distinguish between dif- ferent categories of student feedback to SimStudent, and how this enables interaction with SimStudent in a pilot study.