Investigating Epistemic Stances in Game Play Through Learning Analytics

Abstract

The authors apply techniques of statistical computing to data logs to investigate the patterns in students' play of The Fuzzy Chronicles and how these patterns relate to learning outcomes related to Newtonian kinematics. This chapter has two goals. The first goal is to investigate the basic claims of the proposed two-system framework for game-based learning (or 2SM) that may serve as part of a general-use explanatory framework for educational gaming. The second goal is to explore and demonstrate the use of automated log files of student play as evidence of learning through educational data mining techniques. These goals were pursued via two research questions. The first research question examines whether students playing the game showed evidence of dichotomous fast/slow modes of solution. A second research question investigates the connection between conceptual understanding and student performance in conceptually-laden challenges. Implications in terms of game design, learning analytics, and refinement of the 2SM are discussed.