Does Prior Knowledge Matter? Comparing Gamified and Adaptive Platforms for Introductory Mathematics

Abstract

Basic concepts in introductory mathematics remain a persistent challenge in STEM education, particularly for students entering with heterogeneous levels of prior knowledge. Among technology-enhanced approaches, gamified learning environments and adaptive learning systems have shown promise; however, their differential effectiveness as a function of students’ initial proficiency is not yet well understood. This study examines the impact of these two instructional strategies through a quasi-experimental pre-test–post-test design using intact classroom groups in introductory mathematics courses. A gamified learning platform and an adaptive learning platform were implemented over comparable instructional periods. Learning outcomes were assessed using normalized learning gain, while engagement-related behavior was examined through a normalized dedication metric. Statistical analyses included chi-square tests to examine pre-post performance transitions and one-way ANOVA to evaluate the effect of initial proficiency on learning gain within each instructional condition. Results indicate that both approaches led to improvements in post-test performance; however, distinct learning gain profiles emerged across proficiency levels. Gamified instruction was associated with higher gains among students with low initial proficiency, whereas adaptive learning produced more homogeneous gains across performance groups. Interpreted through an aptitude–treatment interaction framework, these findings suggest that gamified and adaptive learning approaches may serve complementary roles when aligned with learner characteristics. The study contributes empirical evidence to inform the design of personalized instructional strategies in introductory mathematics and motivates future research on integrated, aptitude-sensitive learning models.