Examining Diagnosis Paths: A Process Mining Approach

Abstract

This paper is motivated by two observations on computer-supported education: First, there has been growing availability, rapid proliferation, and increased diversity of learner-system educational data. Second, advances in learning analytics and data mining have facilitated and spawned a variety of novel investigations using such data. Driven by these complementary trends, the present work is geared towards exploring knowledge-based discovery approaches in understanding learner-system usage data. More specifically, with an eye toward tracing and comprehending learner behaviors in a medical intelligent tutoring system, we explore the utility of Process Mining, in understanding the problem solving trajectories of students in a medical computer-based learning environment.