Evaluating Behavior-Driven Metrics in Gamified Hybrid Environments: A Structural Analysis Approach
DOI:
https://doi.org/10.26877/asset.v8i3.2499Keywords:
Gamification, blended learning, perceived playfulness, learner analytics, structural modelling, partial least squaresAbstract
Despite the widespread adoption of gamification in higher education, a significant research gap remains regarding the structural pathways through which specific game elements influence psychological drivers and academic success in hybrid settings. This study addresses this by evaluating the impact of badges, points, progress bars, and leaderboards on student motivation and outcomes using a quantitative approach with a sample of 437 university students in Indonesia. Data were analyzed using Partial Least Squares Structural Equation Modeling (PLS-SEM), revealing that the model possesses strong internal consistency and convergent validity, with factor loadings between 0.760–0.956 and Average Variance Extracted (AVE) values ranging from 0.687 to 0.872. The structural analysis confirms that badges act as a primary driver for perceived playfulness and the effectiveness of other elements, while leaderboards and progress bars significantly enhance learning satisfaction; however, points showed no significant impact on playfulness. These findings, evidenced by significant path coefficients (β) and robust R² values, provide an analytical framework for educators to strategically design gamified ecosystems that prioritize high-impact behavioral metrics over simple reward systems, thereby optimizing engagement in blended learning environments.
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