Latent Structure Analysis of Gamified Learning Ecosystems: Modeling Mediated and Moderated Effects on Learning Motivation through Structural Equation Modeling

Abstract The study investigates the internal makeup of gamified classrooms to find out the ways that motivation to learn is influenced. Self-Determination Theory (SDT), Instructional Design Theory, and the Technology Acceptance Model (TAM) were combined to produce a comprehensive structural equation model (SEM) and study the connections between Perceived Game Elements, the way a game is designed, how useful gamification is, and both Engagement and Learning Motivation. 374 students in secondary schools were involved in a physics curriculum that included games. All the main constructs had a strong level of construct validity, as their composite reliability and average variance extracted values were acceptable. According to the modeling, the presence of Engagement significantly increases the impact of both thinking about educational principles and game features on a student’s likelihood of being motivated to learn. Importantly, the connection between the Usefulness of Gamification and Learning Motivation was not significant, indicating that the impact of Usefulness of Gamification on Learning Motivation took place through another variable. Since CFI is 0.954 and RMSEA is 0.053, the structure of the model provides excellent evidence of fitting the data well. Based on the findings, it is clear that focusing gamification strategies on students’ learning goals encourages them to take an active interest in their studies. The study adds to the evidence used in designing educational activities that benefit from games and aim to improve motivation.