Enhancing motivation in gamified learning: how relatedness moderates the ARCS model

Gamification is widely adopted to enhance student motivation, yet its effectiveness remains context-dependent and theoretically fragmented. This study examines how the ARCS motivational model (Attention, Relevance, Confidence, and Satisfaction) influences motivation in gamified learning environments, and whether Relatedness, drawn from Self-Determination Theory, moderates these relationships. It also investigates the role of control variables (gender, academic major, and institutional affiliation) in predicting motivation. A quantitative survey was administered to 453 business students from two Malaysian universities following gamified activities implemented through the Socrative platform. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM). The findings reveal that Relevance and Satisfaction significantly predicted motivation, whereas Attention and Confidence did not. Relatedness moderated the effects of Satisfaction (positive) and Confidence (negative), suggesting its dual role in shaping social and psychological engagement. Control variables were non-significant. Theoretically, this study extends the ARCS framework by incorporating relatedness as a social moderator, advancing understanding of motivational processes in gamified learning. Empirically, it contributes evidence from a non-Western higher education context. Practically, the results highlight the need for educators to design gamified learning that prioritizes relevance, satisfaction, and social connectedness rather than demographic tailoring. Despite demonstrating moderate explanatory power (R2 = 0.557), the model’s predictive performance was low, indicating limited forecasting ability. This limitation suggests the importance of testing more diverse samples and additional moderators in future research to strengthen predictive generalizability.