Applications of Data Mining in Constraint-Based Intelligent Tutoring Systems

This report describes an investigation into the use of data mining processes, with respect to student interaction with Intelligent Tutoring Systems (ITSs). In particular, a framework for the analysis of constraint-based tutors is developed. The framework, which involves three phases (collection, transformation and analysis), is implemented to extract patterns in student interaction with an ITS called SQL-Tutor. This investigation identifies alternative techniques in each of the three phases, and discusses the advantages and disadvantages of each approach. The report also highlights a number of key knowledge areas in which the mining process can be used to find rules, relationships and patterns. A range of typical findings from an existing tutoring system are used to illustrate each of these knowledge areas. It is envisaged that the knowledge that is extracted using these techniques will be used to improve the tutoring systems