Enhancing Student Understanding in Electrical Engineering: An Android-Based e-Learning Approach

This research developed and evaluated an android-based intelligent learning application for electronics education, utilizing the Analysis, Design, Development, Implementation, Evaluation (ADDIE) framework. The application was designed to enhance students’ understanding of electronics concepts, and the technology acceptance factors influencing its effectiveness were analyzed using the Unified Theory of Acceptance and Use of Technology (UTAUT) model. The evaluation showed that the application achieved a high level of suitability with material experts rating it at 85% and media experts at 82.22%. The analysis of the implementation through Covariance-Based Structural Equation Modeling (CB-SEM) revealed that Perceived Ease of Use (PEU) and App Interactivity (AI) significantly influenced Perceived Usefulness (PU) (R² = 0.684), while PU also positively impacted Learning Outcomes (LO) (R² = 0.248). Furthermore, the results confirmed the reliability and validity of the application with an Root Mean Square Error of Approximation (RMSEA) of 0.071, Standardized Root Mean Square Residual (SRMR) of 0.046, and Comparative Fit Index (CFI) of 0.979, indicating excellent model fit. The contribution