ChatGPT in Higher Education: Does Acceptance Lead to Self-Directed Learning?
The rapid development of artificial intelligence (AI) in education has introduced new learning tools, one of which is ChatGPT—a language model capable of supporting academic tasks interactively. However, the effectiveness of such tools in fostering student independence remains under-explored. This study investigates whether students’ acceptance of ChatGPT contributes to their self-directed learning (SDL) in a higher education context. The aim of this study is to examine the relationship between students’ acceptance of ChatGPT—conceptualized through perceived usefulness and perceived ease of use—and their level of SDL, with frequency of use tested as a mediating variable. The scope of the study focuses on undergraduate students who have used ChatGPT in academic settings. This research employed a quantitative approach using a survey method. A total of 242 students from various faculties participated in the study. The data were analyzed through multiple regression and Sobel test to assess both direct and indirect effects within the proposed mediation model. The results showed that acceptance of ChatGPT significantly influenced both the frequency of its usage and students' self-directed learning. Although the direct effect of frequency of use on SDL was not statistically significant, the Sobel test revealed a significant indirect effect, indicating that frequency of use acts as a mediator between acceptance and SDL. In other words, students who perceive ChatGPT as useful and easy to use tend to use it more frequently, and this usage contributes—indirectly and significantly—to the development of self-directed learning behaviors. These findings suggest that integrating AI tools like ChatGPT into higher education requires not only technical access but also fostering positive perceptions and habits of use, to truly enhance student autonomy in learning.
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Achmad, W. K. S., & Utami, U. (2023). Sense-making of digital literacy for future education era: a literature review. Jurnal Prima Edukasia, 11(1), 47–53. https://doi.org/https://doi.org/10.21831/jpe.v11i1.52911
Al-Zahrani, A. M., & Alasmari, T. M. (2024). Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanities and Social Sciences Communications, 11(1), 1–12.
Alshammari, S. H., & Babu, E. (2025). The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT. Scientific Reports, 15(1), 7169. https://doi.org/10.1038/s41598-025-91634-4
Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96(3), 523.
Börekci, C., & Çelik, Ö. (2024). Exploring The Role of Digital Literacy in University Students’ Engagement with AI through the Technology Acceptance Model. Sakarya University Journal of Education, 14(Special Issue-AI in Education), 228–249. https://doi.org/10.19126/suje.1468866
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13.
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8
Charokar, K., & Dulloo, P. (2022). Self-directed learning theory to practice: a footstep towards the path of being a life-long learne. Journal of Advances in Medical Education & Professionalism, 10(3), 135.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., … Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Grande, R. A. N., Berdida, D. J. E., Cruz, J. P., Cometa‐Manalo, R. J., Balace, A. B., & Ramirez, S. H. (2022). Academic motivation and self‐directed learning readiness of nursing students during the COVID‐19 pandemic in three countries: A cross‐sectional study. Nursing Forum, 57(3), 382–392. https://doi.org/10.1111/nuf.12698
Hadi, N. A. A., Mohamad, F., Johar, E. M., & Kadir, Z. A. (2024). Exploring the Acceptance of ChatGPT as an Assisting Tool in Academic Writing among ESL Undergraduate Students. International Journal of Research and Innovation in Social Science, VIII(X), 2886–2901. https://doi.org/10.47772/IJRISS.2024.8100242
Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., & Wallach, H. (2019). Improving Fairness in Machine Learning Systems. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–16. New York, NY, USA: ACM. https://doi.org/10.1145/3290605.3300830
Huang, Y., & Huang, J. X. (2024). Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges. Web Intelligence, 22(1), 31–44. https://doi.org/10.3233/WEB-230363
Ibrahim, A., & Shiring, E. (2022). The Relationship between Educators’ Attitudes, Perceived Usefulness, and Perceived Ease of Use of Instructional and Web-Based Technologies: Implications from Technology Acceptance Model (TAM). International Journal of Technology in Education, 5(4), 535–551. https://doi.org/10.46328/ijte.285
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Imran, M., & Almusharraf, N. (2023). Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature. Contemporary Educational Technology, 15(4), ep464. https://doi.org/10.30935/cedtech/13605
Jin, M., & Ji, C. (2021). The correlation of metacognitive ability, self‐directed learning ability and critical thinking in nursing students: A cross‐sectional study. Nursing Open, 8(2), 936–945. https://doi.org/10.1002/nop2.702
Juuti, K., Kervinen, A., & Loukomies, A. (2022a). Quality over frequency in using digital technology: Measuring the experienced functional use. Computers & Education, 176, 104361. Achmad, W. K. S., & Utami, U. (2023). Sense-making of digital literacy for future education era: a literature review. Jurnal Prima Edukasia, 11(1), 47–53. https://doi.org/https://doi.org/10.21831/jpe.v11i1.52911
Al-Zahrani, A. M., & Alasmari, T. M. (2024). Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanities and Social Sciences Communications, 11(1), 1–12.
Alshammari, S. H., & Babu, E. (2025). The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT. Scientific Reports, 15(1), 7169. https://doi.org/10.1038/s41598-025-91634-4
Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96(3), 523.
Börekci, C., & Çelik, Ö. (2024). Exploring The Role of Digital Literacy in University Students’ Engagement with AI through the Technology Acceptance Model. Sakarya University Journal of Education, 14(Special Issue-AI in Education), 228–249. https://doi.org/10.19126/suje.1468866
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13.
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8
Charokar, K., & Dulloo, P. (2022). Self-directed learning theory to practice: a footstep towards the path of being a life-long learne. Journal of Advances in Medical Education & Professionalism, 10(3), 135.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., … Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Grande, R. A. N., Berdida, D. J. E., Cruz, J. P., Cometa‐Manalo, R. J., Balace, A. B., & Ramirez, S. H. (2022). Academic motivation and self‐directed learning readiness of nursing students during the COVID‐19 pandemic in three countries: A cross‐sectional study. Nursing Forum, 57(3), 382–392. https://doi.org/10.1111/nuf.12698
Hadi, N. A. A., Mohamad, F., Johar, E. M., & Kadir, Z. A. (2024). Exploring the Acceptance of ChatGPT as an Assisting Tool in Academic Writing among ESL Undergraduate Students. International Journal of Research and Innovation in Social Science, VIII(X), 2886–2901. https://doi.org/10.47772/IJRISS.2024.8100242
Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., & Wallach, H. (2019). Improving Fairness in Machine Learning Systems. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–16. New York, NY, USA: ACM. https://doi.org/10.1145/3290605.3300830
Huang, Y., & Huang, J. X. (2024). Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges. Web Intelligence, 22(1), 31–44. https://doi.org/10.3233/WEB-230363
Ibrahim, A., & Shiring, E. (2022). The Relationship between Educators’ Attitudes, Perceived Usefulness, and Perceived Ease of Use of Instructional and Web-Based Technologies: Implications from Technology Acceptance Model (TAM). International Journal of Technology in Education, 5(4), 535–551. https://doi.org/10.46328/ijte.285
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Imran, M., & Almusharraf, N. (2023). Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature. Contemporary Educational Technology, 15(4), ep464. https://doi.org/10.30935/cedtech/13605
Jin, M., & Ji, C. (2021). The correlation of metacognitive ability, self‐directed learning ability and critical thinking in nursing students: A cross‐sectional study. Nursing Open, 8(2), 936–945. https://doi.org/10.1002/nop2.702
Juuti, K., Kervinen, A., & Loukomies, A. (2022a). Quality over frequency in using digital technology: Measuring the experienced functional use. Computers & Education, 176, 104361. https://doi.org/10.1016/j.compedu.2021.104361
Juuti, K., Kervinen, A., & Loukomies, A. (2022b). Quality over frequency in using digital technology: Measuring the experienced functional use. Computers & Education, 176, 104361. https://doi.org/10.1016/j.compedu.2021.104361
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023a). 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
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023b). 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
Kharroubi, S., & ElMediouni, A. (2024). Conceptual Review: Cultivating Learner Autonomy Through Self-Directed Learning & Self-Regulated Learning: A Socio-Constructivist Exploration. International Journal of Language and Literary Studies, 6(2), 276–296. https://doi.org/10.36892/ijlls.v6i2.1649
Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142.
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. Cambridge Adult Education.
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2025). Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective. International Journal of Human–Computer Interaction, 41(2), 1431–1445. https://doi.org/10.1080/10447318.2024.2314358
Marquardson, J. (2024). Embracing Artificial Intelligence to Improve Self-Directed Learning: A Cybersecurity Classroom Study. Information Systems Education Journal, 22(1), 4–13. https://doi.org/10.62273/WZBY3952
Nehra, S. S., & Bansode, S. Y. (2024). Exploring the Prospects and Perils of Integrating Artificial Intelligence and ChatGPT in Academic and Research Libraries (ARL): Challenges and Opportunity. Journal of Web Librarianship, 18(3), 111–132. https://doi.org/10.1080/19322909.2024.2390413
Nguyen, T. N. T., Van Lai, N., & Nguyen, Q. T. (2024). Artificial Intelligence (AI) in Education: A Case Study on ChatGPT’s Influence on Student Learning Behaviors. Educational Process: International Journal, 13(2), 105–121.
Okwuduba, E. N., Nwosu, K. C., Okigbo, E. C., Samuel, N. N., & Achugbu, C. (2021). Impact of intrapersonal and interpersonal emotional intelligence and self-directed learning on academic performance among pre-university science students. Heliyon, 7(3), e06611. https://doi.org/10.1016/j.heliyon.2021.e06611
Ouyang, F., Zheng, L., & Jiao, P. (2022). Artificial intelligence in online higher education: A systematic review of empirical research from 2011 to 2020. Education and Information Technologies, 27(6), 7893–7925.
Prastika, B. A., Senen, A., & Cahya, R. D. (2023). Immersive Pop-Up Books: Enhancing Disaster Awareness in the Merdeka Curriculum. Jurnal Prima Edukasia, 11(2), 186–196. https://doi.org/https://doi.org/10.21831/jpe.v11i2.57723
Sobel, M. E. (1982). Asymptotic Confidence Intervals for Indirect Effects in Structural Equation Models. Sociological Methodology, 13, 290. https://doi.org/10.2307/270723
Susnjak, T., & McIntosh, T. (2024a). ChatGPT: The End of Online Exam Integrity? Education Sciences, 14(6), 656. https://doi.org/10.3390/educsci14060656
Achmad, W. K. S., & Utami, U. (2023). Sense-making of digital literacy for future education era: a literature review. Jurnal Prima Edukasia, 11(1), 47–53. https://doi.org/https://doi.org/10.21831/jpe.v11i1.52911
Al-Zahrani, A. M., & Alasmari, T. M. (2024). Exploring the impact of artificial intelligence on higher education: The dynamics of ethical, social, and educational implications. Humanities and Social Sciences Communications, 11(1), 1–12.
Alshammari, S. H., & Babu, E. (2025). The mediating role of satisfaction in the relationship between perceived usefulness, perceived ease of use and students’ behavioural intention to use ChatGPT. Scientific Reports, 15(1), 7169. https://doi.org/10.1038/s41598-025-91634-4
Azevedo, R., & Cromley, J. G. (2004). Does training on self-regulated learning facilitate students’ learning with hypermedia? Journal of Educational Psychology, 96(3), 523.
Börekci, C., & Çelik, Ö. (2024). Exploring The Role of Digital Literacy in University Students’ Engagement with AI through the Technology Acceptance Model. Sakarya University Journal of Education, 14(Special Issue-AI in Education), 228–249. https://doi.org/10.19126/suje.1468866
Broadbent, J., & Poon, W. L. (2015). Self-regulated learning strategies & academic achievement in online higher education learning environments: A systematic review. The Internet and Higher Education, 27, 1–13.
Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: perceptions, benefits, and challenges in higher education. International Journal of Educational Technology in Higher Education, 20(1). https://doi.org/10.1186/s41239-023-00411-8
Charokar, K., & Dulloo, P. (2022). Self-directed learning theory to practice: a footstep towards the path of being a life-long learne. Journal of Advances in Medical Education & Professionalism, 10(3), 135.
Davis, F. D. (1989). Perceived Usefulness, Perceived Ease of Use, and User Acceptance of Information Technology. MIS Quarterly, 13(3), 319. https://doi.org/10.2307/249008
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., … Eirug, A. (2021). Artificial Intelligence (AI): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57, 101994.
Grande, R. A. N., Berdida, D. J. E., Cruz, J. P., Cometa‐Manalo, R. J., Balace, A. B., & Ramirez, S. H. (2022). Academic motivation and self‐directed learning readiness of nursing students during the COVID‐19 pandemic in three countries: A cross‐sectional study. Nursing Forum, 57(3), 382–392. https://doi.org/10.1111/nuf.12698
Hadi, N. A. A., Mohamad, F., Johar, E. M., & Kadir, Z. A. (2024). Exploring the Acceptance of ChatGPT as an Assisting Tool in Academic Writing among ESL Undergraduate Students. International Journal of Research and Innovation in Social Science, VIII(X), 2886–2901. https://doi.org/10.47772/IJRISS.2024.8100242
Holstein, K., Wortman Vaughan, J., Daumé, H., Dudik, M., & Wallach, H. (2019). Improving Fairness in Machine Learning Systems. Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems, 1–16. New York, NY, USA: ACM. https://doi.org/10.1145/3290605.3300830
Huang, Y., & Huang, J. X. (2024). Exploring ChatGPT for next-generation information retrieval: Opportunities and challenges. Web Intelligence, 22(1), 31–44. https://doi.org/10.3233/WEB-230363
Ibrahim, A., & Shiring, E. (2022). The Relationship between Educators’ Attitudes, Perceived Usefulness, and Perceived Ease of Use of Instructional and Web-Based Technologies: Implications from Technology Acceptance Model (TAM). International Journal of Technology in Education, 5(4), 535–551. https://doi.org/10.46328/ijte.285
Ifenthaler, D., & Yau, J. Y.-K. (2020). Utilising learning analytics to support study success in higher education: a systematic review. Educational Technology Research and Development, 68(4), 1961–1990. https://doi.org/10.1007/s11423-020-09788-z
Imran, M., & Almusharraf, N. (2023). Analyzing the role of ChatGPT as a writing assistant at higher education level: A systematic review of the literature. Contemporary Educational Technology, 15(4), ep464. https://doi.org/10.30935/cedtech/13605
Jin, M., & Ji, C. (2021). The correlation of metacognitive ability, self‐directed learning ability and critical thinking in nursing students: A cross‐sectional study. Nursing Open, 8(2), 936–945. https://doi.org/10.1002/nop2.702
Juuti, K., Kervinen, A., & Loukomies, A. (2022a). Quality over frequency in using digital technology: Measuring the experienced functional use. Computers & Education, 176, 104361. https://doi.org/10.1016/j.compedu.2021.104361
Juuti, K., Kervinen, A., & Loukomies, A. (2022b). Quality over frequency in using digital technology: Measuring the experienced functional use. Computers & Education, 176, 104361. https://doi.org/10.1016/j.compedu.2021.104361
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023a). 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
Kasneci, E., Sessler, K., Küchemann, S., Bannert, M., Dementieva, D., Fischer, F., … Kasneci, G. (2023b). 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
Kharroubi, S., & ElMediouni, A. (2024). Conceptual Review: Cultivating Learner Autonomy Through Self-Directed Learning & Self-Regulated Learning: A Socio-Constructivist Exploration. International Journal of Language and Literary Studies, 6(2), 276–296. https://doi.org/10.36892/ijlls.v6i2.1649
Kirschner, P. A., & De Bruyckere, P. (2017). The myths of the digital native and the multitasker. Teaching and Teacher Education, 67, 135–142.
Knowles, M. S. (1975). Self-directed learning: A guide for learners and teachers. Cambridge Adult Education.
Ma, J., Wang, P., Li, B., Wang, T., Pang, X. S., & Wang, D. (2025). Exploring User Adoption of ChatGPT: A Technology Acceptance Model Perspective. International Journal of Human–Computer Interaction, 41(2), 1431–1445. https://doi.org/10.1080/10447318.2024.2314358
Marquardson, J. (2024). Embracing Artificial Intelligence to Improve Self-Directed Learning: A Cybersecurity Classroom Study. Information Systems Education Journal, 22(1), 4–13. https://doi.org/10.62273/WZBY3952
Nehra, S. S., & Bansode, S. Y. (2024). Exploring the Prospects and Perils of Integrating Artificial Intelligence and ChatGPT in Academic and Research Libraries (ARL): Challenges and Opportunity. Journal of Web Librarianship, 18(3), 111–132. https://doi.org/10.1080/19322909.2024.2390413
Nguyen, T. N. T., Van Lai, N., & Nguyen, Q. T. (2024). Artificial Intelligence (AI) in Education: A Case Study on ChatGPT’s Influence on Student Learning Behaviors. Educational Process: International Journal, 13(2), 105–121.
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