ANALISIS PEMANFAATAN ARTIFICIAL INTELLIGENCE SEBAGAI MEDIA PEMBELAJARAN ADAPTIF DALAM MENINGKATKAN MOTIVASI DAN KETERLIBATAN BELAJAR MAHASISWA
DOI:
https://doi.org/10.23969/jp.v11i02.55048Keywords:
Artificial Intelligence, adaptive learning, learning motivation, student engagement, higher educationAbstract
This study aims to analyze the use of Artificial Intelligence (AI) as an adaptive learning medium in improving students' motivation and learning engagement. The study employed a descriptive qualitative method with a structured literature review approach. Data were collected from books, journal articles, and policy reports discussing artificial intelligence in education, adaptive learning, learning motivation, and student engagement in higher education. The data were analyzed through reduction, categorization, interpretation, and synthesis of findings based on pedagogical relevance. The results show that AI can support adaptive learning by providing personalized learning paths, immediate feedback, intelligent tutoring, learning analytics, chatbot assistance, and recommendation of learning resources according to students' needs. The use of AI is also related to the fulfillment of students' autonomy, competence, and relatedness, which are important elements in strengthening intrinsic motivation. In terms of learning engagement, AI can encourage behavioral, emotional, and cognitive engagement through interactive activities, timely feedback, and reflective learning support. However, the implementation of AI requires ethical control, lecturer guidance, data protection, digital literacy, and clear academic integrity policies. The study concludes that AI has strong potential as an adaptive learning medium when it is positioned as a pedagogical support tool rather than a substitute for lecturers. Therefore, higher education institutions need to design human-centered AI-based learning that is adaptive, ethical, inclusive, and aligned with learning outcomes.
Downloads
References
Baker, R. S., & Smith, L. (2019). Educ-AI-tion rebooted? Exploring the future of artificial intelligence in schools and colleges. London: Nesta.
Bond, M., Buntins, K., Bedenlier, S., Zawacki-Richter, O., & Kerres, M. (2020). Mapping research in student engagement and educational technology in higher education: A systematic evidence map. International Journal of Educational Technology in Higher Education, 17(2), 1-30. https://doi.org/10.1186/s41239-019-0176-8
Crompton, H., & Burke, D. (2023). Artificial intelligence in higher education: The state of the field. International Journal of Educational Technology in Higher Education, 20(22), 1-22. https://doi.org/10.1186/s41239-023-00392-8
Deci, E. L., & Ryan, R. M. (2000). The what and why of goal pursuits: Human needs and the self-determination of behavior. Psychological Inquiry, 11(4), 227-268. https://doi.org/10.1207/S15327965PLI1104_01
Downloads
Published
Issue
Section
License
Copyright (c) 2026 Pendas : Jurnal Ilmiah Pendidikan Dasar

This work is licensed under a Creative Commons Attribution 4.0 International License.