Yan Watequlis Syaifudin; Nobuo Funabiki; Andi Baso Kaswar; Asep Sunandar; Suryani Dyah Astuti; Triana Fatmawati; Mustika Mentari; Alfiandi Aulia Rahmadani

Empowering Self-Learning: Automated Assistance and Grading Mechanisms in Android Application Development

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Author(s)

Yan Watequlis Syaifudin ^1,* Nobuo Funabiki ² Andi Baso Kaswar ³ Asep Sunandar ⁴ Suryani Dyah Astuti ⁵ Triana Fatmawati ¹ Mustika Mentari ² Alfiandi Aulia Rahmadani ¹

1. Department of Information Technology, State Polytechnic of Malang, Malang, Indonesia

2. Department of Electrical and Communication Engineering, Okayama University, Okayama, Japan

3. Department of Informatics and Computer Education, State University of Makassar, Makassar, Indonesia

4. Department of Education Administration, State University of Malang, Malang, Indonesia

5. Department of Biomedical Engineering, Surabaya, Indonesia

* Corresponding author.

DOI: https://doi.org/10.5815/ijmecs.2026.04.07

Received: 7 Jan. 2025 / Revised: 24 May 2025 / Accepted: 26 Oct. 2025 / Published: 8 Aug. 2026

Index Terms

Android Application, Self-Learning, Learning Assistance, Assignment Grading, Automated Testing

Abstract

The increasing dominance of Android devices has driven a surge in demand for skilled mobile programmers, prompting educational institutions to incorporate mobile programming courses into their curricula. This trend, combined with the rise of self-learning platforms, highlights the need for innovative educational technologies that enhance programming instruction. While automated assessment systems have improved the grading process in programming education, there remains a gap in mobile programming education, particularly due to the complexities of assessing Android applications. To address this, an innovative framework for Android application development is proposed, leveraging automated grading and assistance mechanisms. The framework employs a Test-Driven Development (TDD) approach, providing structured guidance and immediate feedback through automated testing tools including JUnit and Robolectric. A study involving 125 students revealed high engagement and success in basic topics, though challenges persisted in more complex areas, indicating a need for ongoing refinement and additional instructional support to elevate the learning experience in mobile application development.

Cite This Paper

Yan Watequlis Syaifudin, Nobuo Funabiki, Andi Baso Kaswar, Asep Sunandar, Suryani Dyah Astuti, Triana Fatmawati, Mustika Mentari, Alfiandi Aulia Rahmadani, "Empowering Self-Learning: Automated Assistance and Grading Mechanisms in Android Application Development", International Journal of Modern Education and Computer Science(IJMECS), Vol.18, No.4, pp. 99-121, 2026. DOI:10.5815/ijmecs.2026.04.07

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International Journal of Modern Education and Computer Science (IJMECS)