DEVELOPING A COGNITIVE RULE-BASED TUTOR FOR THE ASSISTMENT SYSTEM By

The ASSISTment system is a web-based tutor that is currently being used as an eighth and tenth-grade mathematics in both Massachusetts and Pennsylvania. This system represents its tutors as state-based "pseudo-tutors " which mimic a more complex cognitive tutor based on a set of production rules. It has been shown that building pseudo-tutors significantly decreases the time spent authoring content. This is an advantage for authoring systems such as the ASSITment builder, though it sacrifices greater expressive power and flexibility. A cognitive tutor models a student's behavior with general logical rules. Through model-tracing of a cognitive tutor's rule space, a system can find the reasons behind a student action and give better tutoring. In addition, these cognitive rules are general and can be used for many different tutors. It is the goal of this thesis to provide the architecture for using cognitive rule-based tutors in the ASSITment system. A final requirement is that running these computationally intensive model-tracing tutors do not slow down students using the pseudo-tutors, which represents the majority of ASSISTment usage. This can be achieved with remote computation, realized with SOAP web services. The system was further extended to allow the creation and implementation of user-level experiments within the system. These experiments allow the testing of pedagogical choices. We implemented a hint dissuasion experiment to test this experimental framework and provide those results