The Impact of Generative Artificial Intelligence on Self-Regulated Learning Skills: Academic Motivation as a Mediating Variable
Keywords:
Generative Artificial Intelligence (GenAI), Academic Motivation, Self-Regulated Learning
Abstract
This study aimed to investigate the impact of using Generative Artificial Intelligence (GenAI) on enhancing academic motivation and self-regulated learning skills among higher education students, in addition to examining the mediating role of academic motivation in the relationship between Generative Artificial Intelligence and self-regulated learning. The study adopted a predictive correlational descriptive approach. The study sample consisted of (800) male and female students from King Abdulaziz University enrolled in bachelor’s, master’s, and doctoral programs. A questionnaire was used as the data collection instrument. The findings revealed that the level of Generative Artificial Intelligence usage was very high, with a mean score of (4.42). Self-regulated learning skills were also found to be high, with a mean score of (4.11), while the level of academic motivation was high, with a mean score of (4.19). The results further indicated statistically significant positive correlations at the (0.01) level among the study variables. The correlation coefficient between Generative Artificial Intelligence and academic motivation reached (0.750), between academic motivation and self-regulated learning (0.751), and between Generative Artificial Intelligence and self-regulated learning (0.720). Regression analysis showed that Generative Artificial Intelligence and academic motivation together explained (62.0%) of the variance in self-regulated learning skills. Path analysis results also demonstrated a significant direct effect of Generative Artificial Intelligence on academic motivation, a significant direct effect of academic motivation on self-regulated learning, and a significant direct effect of Generative Artificial Intelligence on self-regulated learning, in addition to a significant indirect effect through academic motivation. These findings indicate that academic motivation plays a partial mediating role in this relationship.
References
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26. Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of educational psychology, 106(1), 121. https://doi.org/10.1037/a0033546
27. Nguyen, H., & Nguyen, A. (2025). Reflective Practices and Self-Regulated Learning in Designing with Generative Artificial Intelligence: An Ordered Network Analysis. Journal of science education and technology, 34(5), 1178-1192. https://doi.org/10.1007/s10956-024-10175-z
28. Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192. https://doi.org/10.1126/science.adh2586
29. Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422
30. Pataranutaporn, P., Leong, J., Danry, V., Lawson, A. P., Maes, P., & Sra, M. (2022). AI-generated virtual instructors based on liked or admired people can improve motivation and foster positive emotions for learning. 2022 IEEE Frontiers in Education Conference (FIE), https://doi.org/10.1109/fie56618.2022.9962478
31. Qu, K., & Wu, X. (2024). ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments. Education and Information Technologies, 29(15), 19471-19503. https://doi.org/10.1007/s10639-024-12598-y
32. Renfeng, J., Gang, Y., & Qi, S. (2025). The Motivational Impact of GenAI Tools in Language Learning: a Quasi‐Experiment Study. International Journal of Applied Linguistics. https://doi.org/10.1111/ijal.12701
33. Saadati, Z., Perkan, C., & Barenji, R. (2021). On the development of blockchain-based learning management system as a metacognitive tool to support self-regulation learning in online higher education. Interactive Learning Environments, 31. https://doi.org/10.1080/10494820.2021.1920429
34. Saleem, R. Y., Zaki, M. Z., & Alhalafawy, W. S. (2024). Improving awareness of foreign domestic workers during the COVID-19 pandemic using infographics: An experience during the crisis. Journal of Infrastructure, Policy and Development, 8(5), 4157. https://doi.org/10.24294/jipd.v8i5.4157
35. Sumilong, M. J. (2025). Instructional affect and learner motivation in generative AI-restrictive and permissive classrooms [Brief Research Report]. Frontiers in Education, Volume 10 - 2025. https://doi.org/10.3389/feduc.2025.1626802
36. Wang, C., Li, X., & Zou, B. (2025). Revisiting Integrated Model of Technology Acceptance Among the Generative AI‐Powered Foreign Language Speaking Practice: Through the Lens of Positive Psychology and Intrinsic Motivation. European Journal of Education, 60(1), e70054. https://doi.org/10.1111/ejed.70054
37. Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955
38. Weng, X., Xia, Q., Ahmad, Z., & Chiu, T. K. (2024). Personality traits for self-regulated learning with generative artificial intelligence: The case of ChatGPT. Computers and Education: Artificial Intelligence, 7, 100315. https://doi.org/10.1016/j.caeai.2024.100315
39. Wong, J., & Viberg, O. (2024). Supporting self-regulated learning with generative AI: a case of two empirical studies. 14th International Conference on Learning Analytics and Knowledge (LAK24), Kyoto, Japan.
40. Yuan, L., & Liu, X. (2025). The effect of artificial intelligence tools on EFL learners' engagement, enjoyment, and motivation. Computers in Human Behavior, 162, 108474. https://doi.org/10.1016/j.chb.2024.108474
2. الكفيري، وداد محمد (2021). مستوى ممارسة طلبة كلية التربية في جامعة حائل لاستراتيجيات التعلم المنظم ذاتيا وعلاقته بالدافعية للإنجاز الأكاديمي لديهم. المجلة العربية لضمان جودة التعليم الجامعي، 14(49)، 51-71. https://doi.org/10.20428/AJQAHE.14.49.3
3. بودالي، وحميدة (2018). العلاقة بين استراتيجيات التعلم المنظم ذاتيا والدافعية للإنجاز الدراسي لدى الطالب الجامعي: دراسة ميدانية. مجلة البحوث التربوية والتعليمية، 7(1)، 137-164.
4. رافع، محمود؛ والعقون، كمال الدين (2023). استراتيجيات التعلم المنظم ذاتيا في ضوء نموذج بينتريش وعلاقتها بالدافعية للانجاز لدى الطلبة الجامعيين. مجلة البحوث التربوية والتعليمية،12(1)، 797-822.
5. كسي، سامية، ومباركي، زاكية. (2018). التعلم المنظم ذاتيًا وعلاقته بمستوى الدافعية للتعلم لدى المتعلمين عن بعد [مذكرة ماجستير، جامعة مولود معمري-تيزي وزو].
6. Abbas, M., & Khouidmi, D. (2024). Self-Regulated Learning and its Relation to Achievement Motivation among University Students in the Context of Online Learning After the COVID-19. أطراس, 5(3), 97-114. https://doi.org/10.70091/atras/ai.6
7. Al-Hafdi, F. S., & Alhalafawy, W. S. (2026). Learning analytics for reducing student dropout in digital video platforms. PeerJ Computer Science, 12, e3532. https://doi.org/10.7717/peerj-cs.3532
8. Alharbi, T. S., Al-Hafdi, F. S., & Alhalafawy, W. S. (2025). Exploring the Framework for Intelligent Operations (FiOps) for Teachers in the Era of Generative AI (GenAI). International Journal of Learning, Teaching and Educational Research, 24(8), 942-964. https://doi.org/10.26803/ijlter.24.8.42
9. Alsayed, W. O., Al-Hafdi, F. S., & Alhalafawy, W. S. (2024). Chatbots in Education. In S. Papadakis & M. Kalogiannakis (Eds.), Empowering STEM Educators With Digital Tools (1 ed., pp. 137-154). IGI Global Scientific Publishing, Hershey, USA. https://doi.org/10.4018/979-8-3693-9806-7.ch006
10. Alzahrani, F. K. J., Alhalafawy, W. S., & Alshammary, F. M. (2023). Teachers’ Perceptions of Madrasati Learning Management System (LMS) at Public Schools in Jeddah. Journal of Arts, Literature, Humanities and Social Sciences(97), 345-363. https://doi.org/DOI: https://doi.org/10.33193/JALHSS.97.2023.941
11. Bower, M., Torrington, J., Lai, J. W. M., Petocz, P., & Alfano, M. (2024). How should we change teaching and assessment in response to increasingly powerful generative Artificial Intelligence? Outcomes of the ChatGPT teacher survey. Education and Information Technologies, 29(12), 15403-15439. https://doi.org/10.1007/s10639-023-12405-0
12. Chan, C. K. Y., & Hu, W. J. (2023). Students' voices on generative AI: perceptions, benefits, and challenges in higher education [Article]. International journal of educational technology in higher education, 20(1), 18, Article 43. https://doi.org/10.1186/s41239-023-00411-8
13. Chang, D. H., Lin, M. P.-C., Hajian, S., & Wang, Q. Q. (2023). Educational design principles of using AI chatbot that supports self-regulated learning in education: Goal setting, feedback, and personalization. Sustainability, 15(17), 12921. https://doi.org/10.3390/su151712921
14. Chen, C.-H., & Chang, C.-L. (2024). Effectiveness of AI-assisted game-based learning on science learning outcomes, intrinsic motivation, cognitive load, and learning behavior. Education and Information Technologies, 29(14), 18621-18642.
15. Chen, Z., Wei, W., & Zou, D. (2026). Generative AI technology and language learning: global language learners’ responses to ChatGPT videos in social media. Interactive learning environments, 34(2), 907-920. https://doi.org/10.1080/10494820.2025.2511248
16. Chiu, T. K. F. (2023). The impact of Generative AI (GenAI) on practices, policies and research direction in education: a case of ChatGPT and Midjourney [; Early Access]. Interactive Learning Environments, 17. https://doi.org/10.1080/10494820.2023.2253861
17. Dwivedi, Y. K., Kshetri, N., Hughes, L., Slade, E. L., Jeyaraj, A., Kar, A. K., Baabdullah, A. M., Koohang, A., Raghavan, V., & Ahuja, M. (2023). Opinion Paper:“So what if ChatGPT wrote it?” Multidisciplinary perspectives on opportunities, challenges and implications of generative conversational AI for research, practice and policy. International Journal of Information Management, 71, 102642. https://doi.org/10.1016/j.ijinfomgt.2023.102642
18. Hmoud, M., Swaity, H., Hamad, N., Karram, O., & Daher, W. (2024). Higher education students’ task motivation in the generative artificial intelligence context: the case of chatgpt. Information, 15(1), 33. https://doi.org/10.3390/info15010033
19. Ibrahim, H. O., Al-Hafdi, F. S., & Alhalafawy, W. S. (2024). Ethnographic Insights of Educational Digital Life Behaviours: A Study of Affluent Schools. Journal of Ecohumanism, 3(7), 4413-4428. https://doi.org/10.62754/joe.v3i7.4556
20. Jin, Im, K., Yoo, M., Roll, I., & Seo, K. (2023). Supporting students’ self-regulated learning in online learning using artificial intelligence applications. International Journal of Educational Technology in Higher Education, 20(1), 37. https://doi.org/10.1186/s41239-023-00406-5
21. Kong, S.-C., & Yang, Y. (2024). A Human-Centred Learning and Teaching Framework Using Generative Artificial Intelligence for Self-Regulated Learning Development through Domain Knowledge Learning in K–12 Settings. IEEE Transactions on Learning Technologies . https://doi.org/10.1109/tlt.2024.3392830
22. Lai, J. W. (2024). Adapting Self-Regulated Learning in an Age of Generative Artificial Intelligence Chatbots. Future Internet, 16(6), 218. https://doi.org/10.3390/fi16060218
23. Lee, Y.-F., Hwang, G.-J., & Chen, P.-Y. (2022). Impacts of an AI-based cha bot on college students’ after-class review, academic performance, self-efficacy, learning attitude, and motivation. Educational technology research and development, 70(5), 1843-1865. https://doi.org/10.1007/s11423-022-10142-8
24. Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarok or reformation? A paradoxical perspective from management educators. International Journal of Management Education, 21(2), 13, Article 100790. https://doi.org/10.1016/j.ijme.2023.100790
25. Lim, W. M., Gunasekara, A., Pallant, J. L., Pallant, J. I., & Pechenkina, E. (2023). Generative AI and the future of education: Ragnarök or reformation? A paradoxical perspective from management educators. The international journal of management education, 21(2), 100790. https://doi.org/10.1016/j.ijme.2023.100790
26. Mega, C., Ronconi, L., & De Beni, R. (2014). What makes a good student? How emotions, self-regulated learning, and motivation contribute to academic achievement. Journal of educational psychology, 106(1), 121. https://doi.org/10.1037/a0033546
27. Nguyen, H., & Nguyen, A. (2025). Reflective Practices and Self-Regulated Learning in Designing with Generative Artificial Intelligence: An Ordered Network Analysis. Journal of science education and technology, 34(5), 1178-1192. https://doi.org/10.1007/s10956-024-10175-z
28. Noy, S., & Zhang, W. (2023). Experimental evidence on the productivity effects of generative artificial intelligence. Science, 381(6654), 187-192. https://doi.org/10.1126/science.adh2586
29. Panadero, E. (2017). A review of self-regulated learning: Six models and four directions for research. Frontiers in psychology, 8, 422. https://doi.org/10.3389/fpsyg.2017.00422
30. Pataranutaporn, P., Leong, J., Danry, V., Lawson, A. P., Maes, P., & Sra, M. (2022). AI-generated virtual instructors based on liked or admired people can improve motivation and foster positive emotions for learning. 2022 IEEE Frontiers in Education Conference (FIE), https://doi.org/10.1109/fie56618.2022.9962478
31. Qu, K., & Wu, X. (2024). ChatGPT as a CALL tool in language education: A study of hedonic motivation adoption models in English learning environments. Education and Information Technologies, 29(15), 19471-19503. https://doi.org/10.1007/s10639-024-12598-y
32. Renfeng, J., Gang, Y., & Qi, S. (2025). The Motivational Impact of GenAI Tools in Language Learning: a Quasi‐Experiment Study. International Journal of Applied Linguistics. https://doi.org/10.1111/ijal.12701
33. Saadati, Z., Perkan, C., & Barenji, R. (2021). On the development of blockchain-based learning management system as a metacognitive tool to support self-regulation learning in online higher education. Interactive Learning Environments, 31. https://doi.org/10.1080/10494820.2021.1920429
34. Saleem, R. Y., Zaki, M. Z., & Alhalafawy, W. S. (2024). Improving awareness of foreign domestic workers during the COVID-19 pandemic using infographics: An experience during the crisis. Journal of Infrastructure, Policy and Development, 8(5), 4157. https://doi.org/10.24294/jipd.v8i5.4157
35. Sumilong, M. J. (2025). Instructional affect and learner motivation in generative AI-restrictive and permissive classrooms [Brief Research Report]. Frontiers in Education, Volume 10 - 2025. https://doi.org/10.3389/feduc.2025.1626802
36. Wang, C., Li, X., & Zou, B. (2025). Revisiting Integrated Model of Technology Acceptance Among the Generative AI‐Powered Foreign Language Speaking Practice: Through the Lens of Positive Psychology and Intrinsic Motivation. European Journal of Education, 60(1), e70054. https://doi.org/10.1111/ejed.70054
37. Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1261955. https://doi.org/10.3389/fpsyg.2023.1261955
38. Weng, X., Xia, Q., Ahmad, Z., & Chiu, T. K. (2024). Personality traits for self-regulated learning with generative artificial intelligence: The case of ChatGPT. Computers and Education: Artificial Intelligence, 7, 100315. https://doi.org/10.1016/j.caeai.2024.100315
39. Wong, J., & Viberg, O. (2024). Supporting self-regulated learning with generative AI: a case of two empirical studies. 14th International Conference on Learning Analytics and Knowledge (LAK24), Kyoto, Japan.
40. Yuan, L., & Liu, X. (2025). The effect of artificial intelligence tools on EFL learners' engagement, enjoyment, and motivation. Computers in Human Behavior, 162, 108474. https://doi.org/10.1016/j.chb.2024.108474
Published
2026-06-12
How to Cite
Alhassan Abdulrahman Alhassan Alamri, Dr. Ahmed bin Ibrahim Flattah, & Prof. Waleed Salim Alhalafawy. (2026). The Impact of Generative Artificial Intelligence on Self-Regulated Learning Skills: Academic Motivation as a Mediating Variable. Journal of Arts, Literature, Humanities and Social Sciences, (131), 330-354. https://doi.org/10.33193/JALHSS.131.2026.1683
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Copyright (c) 2026 الحسن عبدالرحمن الحسن العامري , د. أحمد بن إبراهيم فلاته , أ.د. وليد سالم الحلفاوي
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