Tracing Emerging Complexity of Scientific Reasoning Actions During Game-Based Learning

Scientific reasoning is a critical foundational skill learners need to practice and know for increased science learning outcomes. Game-based learning environments (GBLEs) provide learners a platform for developing and practicing scientific reasoning skills but little is known about how learners should engage in scientific reasoning during game-based learning. As such, this paper aimed to understand if and how learners engaged in effective scientific reasoning activities during learning with a GBLE. This paper used analytical techniques from Complex Systems Theory to quantify learners’ scientific reasoning actions during game-based learning. High-school students (N = 170) played Crystal Island, a microbiology GBLE requiring learners to engage in scientific reasoning to successfully identify an illness infecting residents of a virtual island. Categorical auto-Recurrence Quantification Analysis was run on participants’ log files as they deployed scientific reasoning actions. This analysis revealed several metrics of complexity, including recurrence rate which is the proportion of repetitive to novel scientific reasoning actions. Results found that as time progressed, recurrence rates decreased. Successful learners (i.e., those who solved the mystery) demonstrated less repetition in their scientific reasoning activities where their recurrence rates decreased at a slower rate over time than learners who were unsuccessful in solving the mystery. Findings provide implications for adaptively scaffolding learners’ emerging complexities in their scientific reasoning processes during game-based learning to increase learners’ GBLE success. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.