Integrating Media Richness Theory and Technology Acceptance Model to Study the Learning Outcomes of Air Quality Education App

Integrating Media Richness Theory and Technology Acceptance Model to Study the Learning Outcomes of Air Quality Education App

In recent years, the rapid expansion of digital media has revolutionized educational materials by incorporating engaging multimedia elements and gamification principles. These advancements in technology have transformed digital learning into a gamified experience, enhancing the creation and utilization of learning materials. The primary aim of this study was to develop a predictive model for measuring learning outcomes in the Air Quality Education (AQE) app. The study results revealed that the most influential factor affecting learning outcomes was Learning Outcome (R2 = 0.673), followed by Behavioral Intention (R2 = 0.541), Practicability (R2 = 0.456), Use Attitude (R2 = 0.431), and Entertainment (R2 = 0.328). The proposed model accounted for an impressive 67.29.8% of the variability in predicting learning outcomes. These research findings emphasize the significance of Behavioral Intention and Practicability as crucial factors in designing predictive models for learning outcomes within the AQE app. Furthermore, the study highlights the users’ strong emphasis on interface media richness and user experience design elements, indicating the need for their prioritized attention and enhancement. By focusing on these aspects, developers can heighten players’ expectations for interactive media elements and enable them to achieve a more immersive gaming experience through a user-friendly and interactive interface design.