IJIET 2025 Vol.15(6): 1150-1160
doi: 10.18178/ijiet.2025.15.6.2318
doi: 10.18178/ijiet.2025.15.6.2318
Enhancing Student Understanding in Electrical Engineering: An Android-Based e-Learning Approach
Eko Supraptono1,*, Wagino Wagino2, Ahmad Farid Bin Abidin3, Muhammad Yusro4,
and Rahmat Desman Koto2
1. Department of Electrical Engineering Education, Faculty of Engineering Universitas Negeri Semarang, Semarang, Indonesia
2. Department of Automotive Engineering, Faculty of Engineering Universitas Negeri Padang, Padang, Indonesia
3. Centre of Foundation Studies, Universiti Teknologi MARA, Dengkil, Malaysia
4. Faculty of Engineering, Universitas Negeri Jakarta, Jakarta, Indonesia
Email: ekosupraptono@mail.unnes.ac.id (E.S.); wagino@ft.unp.ac.id (W.W.); ahmad924@uitm.edu.my (A.F.B.A.); myusro@unj.ac.id (M.Y.); rahmatdkoto@student.unp.ac.id (R.D.K.)
*Corresponding author
2. Department of Automotive Engineering, Faculty of Engineering Universitas Negeri Padang, Padang, Indonesia
3. Centre of Foundation Studies, Universiti Teknologi MARA, Dengkil, Malaysia
4. Faculty of Engineering, Universitas Negeri Jakarta, Jakarta, Indonesia
Email: ekosupraptono@mail.unnes.ac.id (E.S.); wagino@ft.unp.ac.id (W.W.); ahmad924@uitm.edu.my (A.F.B.A.); myusro@unj.ac.id (M.Y.); rahmatdkoto@student.unp.ac.id (R.D.K.)
*Corresponding author
Manuscript received January 14, 2025; revised February 7, 2025; accepted March 11, 2025; published June 10, 2025
Abstract—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 of this research lies in demonstrating the effectiveness of a mobile learning application for enhancing electronics education and in highlighting the critical role of user experience factors, such as ease of use and interactivity, in the success of e-learning tools in engineering education.
Keywords—android-based learning, Covariance-Based Structural Equation Modeling (CB-SEM), engineering education, learning outcomes, e-learning
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).
Keywords—android-based learning, Covariance-Based Structural Equation Modeling (CB-SEM), engineering education, learning outcomes, e-learning
Cite: Eko Supraptono, Wagino Wagino, Ahmad Farid Bin Abidin, Muhammad Yusro, and Rahmat Desman Koto, "Enhancing Student Understanding in Electrical Engineering: An Android-Based e-Learning Approach," International Journal of Information and Education Technology, vol. 15, no. 6, pp. 1150-1160, 2025.
Copyright © 2025 by the authors. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited (CC BY 4.0).