Automatic Detection of Concepts from Problem Solving Times

Intelligent tutoring systems need to know a mapping between particular problems and general domain concepts. Such mapping can be constructed manually by an expert, but that is time consuming and error prone. Our aim is to detect concepts automatically from problem solving times. We propose and evaluate two approaches: a model of problem solving times with multidimensional skill and an application of spectral clustering. The results show that it is feasible to construct a problem-concept mapping from solely the problem solving times and that the results of the analysis can bring an interesting insight.