Cognitive Dependency in Artificial Intelligence–Based Learning: Its Impact on Students' Learning Autonomy
DOI:
https://doi.org/10.55927/marcopolo.v4i2.11Keywords:
Cognitive Dependency, Learning Autonomy, Artificial Intelligence, Higher EducationAbstract
The use of artificial intelligence (AI) in learning in higher education is increasingly widespread and affects student learning patterns. Although AI improves learning efficiency, overuse has the potential to lead to cognitive dependency that weakens learning autonomy. This study aims to analyze cognitive dependence in AI-based learning and its impact on student learning autonomy. The study used a quantitative approach with a cross-sectional survey design of 312 undergraduate students in semesters IV–VIII of the Education and Social Sciences study program at state universities in Central Java Province, Indonesia, who were selected through purposive sampling. Data were collected using a Likert scale questionnaire and analyzed descriptively and inferentially. The results showed that high levels of cognitive dependence were negatively associated with critical thinking skills, metacognitive regulation, and learning independence, while moderate and reflective use of AI tended to favor learning autonomy. This research emphasizes the importance of learning design and educational policies that encourage the critical use of AI without replacing student learning autonomy.
References
Amin, R., & Ningsih, D. (2024). Pengaruh teknologi digital terhadap kemandirian belajar mahasiswa pada masa pascapandemi. Jurnal Teknologi Pendidikan Indonesia, 9(1), 45–58.
Baker, L. (2023). Self-regulated learning in higher education: Theory, research, and practice. Educational Psychology Review, 35(2), 1–21. https://doi.org/10.1007/s10648-023-09702-1
Buchanan, R., Sainter, P., & Saunders, G. (2022). Factors affecting faculty use of artificial intelligence in higher education. Teaching in Higher Education, 27(7), 1–16. https://doi.org/10.1080/13562517.2021.1989581
Cahyanto, H. N., Pamungkas, P., & Zulkarnain, O. (2024). Pengaruh penggunaan ChatGPT terhadap kemandirian mahasiswa dalam menyelesaikan tugas akademik. PREPOTIF: Jurnal Kesehatan Masyarakat, 8(1), 1–10. https://doi.org/10.31004/prepotif.v8i1.25582
Creswell, J. W., & Creswell, J. D. (2021). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). Sage Publications.
Etikan, I., Musa, S. A., & Alkassim, R. S. (2020). Comparison of convenience sampling and purposive sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1–4. https://doi.org/10.11648/j.ajtas.20160501.11
Eunike, P., Wardhani, P. A. P., & Wulansari, O. D. (2024). Pengaruh ChatGPT dan literasi digital terhadap motivasi belajar mahasiswa. Jurnal Penelitian Pendidikan, Psikologi dan Kesehatan (J-P3K), 5(3), 831–840.
Field, A. (2022). Discovering statistics using IBM SPSS statistics (6th ed.). Sage Publications.
Gerlich, M. (2025). Exploring how AI literacy and self-regulated learning relate to student writing performance and well-being in generative AI-supported higher education. Behavioral Sciences, 15(5), 705. https://doi.org/10.3390/bs15050705
Hair, J. F., Hult, G. T. M., Ringle, C. M., & Sarstedt, M. (2022). A primer on partial least squares structural equation modeling (PLS-SEM) (3rd ed.). Sage Publications.
Heryanto, A., & Rachmawati, F. (2023). Strategi penguatan otonomi belajar mahasiswa di perguruan tinggi. Jurnal Pendidikan dan Kebijakan, 14(2), 112–130.
Holmes, W., Bialik, M., & Fadel, C. (2022). Artificial intelligence in education: Promises and implications for teaching and learning. Center for Curriculum Redesign.
Israel, M., & Hay, I. (2020). Research ethics for social scientists (2nd ed.). Sage Publications.
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., Gasser, U., Groh, G., Günnemann, S., Hüllermeier, E., Krusche, S., Kutyniok, G., Michaeli, T., Nerdel, C., Pfeffer, J., Poquet, O., Sailer, M., Schmidt, A., Seidel, T., … Kasneci, G. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274
Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? The International Journal of Management Education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
Malik, A. R., Pratiwi, Y., Andajani, K., Numertayasa, I. W., Suharti, S., Darwis, A., & Marzuki. (2023). Exploring artificial intelligence in academic essay writing: Higher education students’ perspectives. International Journal of Educational Research Open, 5, 100296. https://doi.org/10.1016/j.ijedro.2023.100296
Ministry of Education and Culture. (2022). Guidelines for strengthening learning autonomy in higher education. Ministry of Education, Culture, Research, and Technology of the Republic of Indonesia.
Oliveira, L., Tavares, C., Strzelecki, A., & Silva, M. (2025). Prompting minds: Evaluating how students perceive generative AI’s critical thinking dispositions. The Electronic Journal of e-Learning, 23(2), 1–18. https://doi.org/10.34190/ejel.23.2.3986
Panadero, E. (2023). A review of self-regulated learning: Six models and four directions for research. Frontiers in Psychology, 14, 1133440. https://doi.org/10.3389/fpsyg.2023.1133440
Prasetyo, A. D., & Wijaya, S. (2021). Literasi digital dan independensi belajar mahasiswa. Jurnal Pendidikan Humaniora, 6(4), 325–338.
Rahman, A., Suryadi, B., & Nugroho, R. (2023). Artificial intelligence adoption in Indonesian higher education: Opportunities and ethical challenges. Journal of Educational Technology Systems, 52(1), 45–63. https://doi.org/10.1177/00472395231174015
Sagita, R. N., & Miyarso, E. (2025). ChatGPT sebagai inovasi pembelajaran untuk meningkatkan motivasi belajar mandiri mahasiswa. Jurnal Teknologi Pendidikan.
Sari, M., & Nugroho, P. (2023). Dampak penggunaan platform digital terhadap strategi belajar mahasiswa. Jurnal Ilmu Pendidikan Indonesia, 8(2), 87–101.
Shin, D. (2021). The effects of explainability and causability on trust in artificial intelligence. Computers in Human Behavior, 113, 106635. https://doi.org/10.1016/j.chb.2020.106635
Smutny, P., & Schreiberova, P. (2023). ChatGPT in education: Opportunities and risks. Innovations in Education and Teaching International, 60(6), 1–11. https://doi.org/10.1080/14703297.2023.2208941
Suryani, R., & Prasetyo, Y. (2022). Potensi dan tantangan pembelajaran digital di perguruan tinggi Indonesia. Jurnal Teknologi dan Pendidikan, 7(1), 15–29.
Tian, J., & Zhang, R. (2025). Learners’ AI dependence and critical thinking: The psychological mechanism of fatigue and the social buffering role of AI literacy. Acta Psychologica, 260, 105725. https://doi.org/10.1016/j.actpsy.2025.105725
Tlili, A., et al. (2023). Towards responsible use of generative AI in education. Smart Learning Environments, 10(1), 1–15. https://doi.org/10.1186/s40561-023-00245-8
Zawacki-Richter, O., Marín, V. I., Bond, M., & Gouverneur, F. (2023). Systematic review of research on artificial intelligence applications in higher education. International Journal of Educational Technology in Higher Education, 20(1), 1–27. https://doi.org/10.1186/s41239-023-00392-8
Zhai, C., Wibowo, S., & Li, L. D. (2024). The effects of over-reliance on AI dialogue systems on students’ cognitive abilities: A systematic review. Smart Learning Environments, 11, 28. https://doi.org/10.1186/s40561-024-00316-7
Zhang, L., & Xu, J. (2025). The paradox of self-efficacy and technological dependence: Unraveling generative AI’s impact on university students’ task completion. The Internet and Higher Education, 65, 100978. https://doi.org/10.1016/j.iheduc.2024.100978
Zimmerman, B. J. (2020). Becoming a self-regulated learner: An overview. Theory Into Practice, 59(2), 1–11. https://doi.org/10.1080/00405841.2019.1702395
