Representing Learning Progression of Unguided Exercise Solving: A Generalization of Wheel-Spinning Detection

Abstract

This study aims at modeling and visualizing students' behavior in a self- regulated and unguided learning environment with a focus on learning progression. Since the modeling approach is process-oriented and does not depend on specific mastery learning criteria, this paper provides a novel way to identify wheel-spinning in self-regulated learning solely based on activity monitoring. The study investigates the free and unsupervised engagement of junior high school students in solving mathematics exercises during summer vacation. During this period, a pool of exercises was provided on the LEAF online learning platform. Additionally, the students receive adaptive exercise recommendations as an add-on. Guided by the basic idea of wheel- spinning as persistent engagement without learning progression, we have designed a mathematical model and a graphical representation to capture and gauge the individual learning progression. Based on an expert questionnaire survey, we considered how this novel representation can serve as a basis to analytically characterize learning progression and specifically to identify wheel-spinning.