Understanding Gaming the System by Analyzing Self-Regulated Learning in Think-Aloud Protocols

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Authors: Jiayi Zhang, Conrad Borchers, Canwen Wang, Vishal Kumar, Leah Teffera, Bruce M. McLaren, Ryan S. Baker
Cited by: 2
References: 50

Abstract

In digital learning systems, gaming the system refers to occasions when students attempt to succeed in an educational task by systematically taking advantage of system features rather than engaging meaningfully with the content. Often viewed as a form of behavioral disengagement, gaming the system is negatively associated with short- and long-term learning outcomes. However, little research has explored this phenomenon beyond its behavioral representation, leaving questions such as whether students are cognitively disengaged or whether they engage in different self-regulated learning (SRL) strategies when gaming largely unanswered. This study employs a mixed-methods approach to examine students’ cognitive engagement and SRL processes during gaming versus non-gaming periods, using utterance length and SRL codes inferred from think-aloud protocols collected while students interacted with an intelligent tutoring system for chemistry. We found that gaming does not simply reflect a lack of cognitive effort; during gaming, students often produced longer utterances, were more likely to engage in processing information and realizing errors, but less likely to engage in planning, and exhibited reactive rather than proactive self-regulatory strategies. These findings provide empirical evidence supporting the interpretation that gaming may represent a maladaptive form of SRL. With this understanding, future work can address gaming and its negative impacts by designing systems that target maladaptive self-regulation to promote better learning.

Fields of Study & Subjects

Innovative Teaching and Learning Methods Visual and Cognitive Learning Processes Educational Games and Gamification

Publication details

Journal / source
Proceedings of the LAK26: 16th International Learning Analytics and Knowledge Conference
Publisher
ACM
Pages
22–31
Publication date
25 April 2026