Lincoln Ritter's Idea

During a recorded tutoring session, the student generates strings of events representing his/her path through the problem/solution space. Further, a "correct" solution can be expressed as a particular subset of all the possible strings over the alphabet of recordable events. To effectively extract useful information from student generated event logs, two things must be known. First, some knowledge of a correct path from problem to goal must be developed. Regardless of the approach taken to analyze student data, an idea of when a student has veered off a productive path must be had if effective interactive tutoring is to take place. Second, some way of comparing paths to, at minimum, determine some notion of distance between correct paths (paths that will more likely lead to a correct solution) and less correct paths.

To this end, I propose that expert users be elisted to solve problems so that "correct" paths through the space can be recorded. Then using existing student data, we can perform gapped alignment algorithms to compare student paths with expert paths. presumably, students who wandered insearch of a solution will generate event strings that are more dissimilar to the expert paths than students who who navigate to the solution succinctly. Insights gained from these experiments could then be used directly, or as a starting point for other data mining methods.