Self-Regulated Language Learning and Generative AI: A Systematic Review

Year 2025, Volume: 42 Issue: 3, 177 - 194, 31.12.2025

Tuba Özturan

https://doi.org/10.52597/buje.1751534

Abstract

This systematic review aims to investigate the integration of generative artificial intelligence tools within foreign and second language (L2) education contexts and their influence on learners' self-regulated learning. Adhering to the PRISMA and PICO protocols, the review encompasses five empirical studies. These studies were systematically coded and analyzed employing a two-cycle coding approach. The findings regarding the research context indicate that most of the included studies adopted an experimental design, primarily involving university-level English as a Foreign Language (EFL) learners. ChatGPT emerged as the most frequently utilized GenAI tool, and English was the dominant target language. Across the studies, self-regulated learning was examined through cognitive, affective, motivational, and metacognitive processes. Key outcomes included learners’ high acceptance of GenAI tools, reports of increased cognitive load while using ChatGPT, and overall positive impacts of GenAI integration on self-regulated learning processes. The paper concludes by offering insights for educators and proposing recommendations for future research.

Keywords

generative artificial intelligence , self-regulated language learning , systematic review

Öz Düzenleme Becerileri ve Üretken Yapay Zeka: Sistematik Bir İnceleme

Abstract

Bu sistematik inceleme, yabancı ve ikinci dil eğitim bağlamlarında üretken yapay zekâ araçlarının entegrasyonunu ve bunların öğrencilerin öz düzenlemeli öğrenmeleri üzerindeki etkisini araştırmayı amaçlamaktadır. PRISMA ve PICO protokollerine bağlı kalınarak, inceleme beş deneysel çalışmayı kapsamaktadır. Bu çalışmalar, iki döngülü bir kodlama yaklaşımı kullanılarak sistematik olarak kodlanmış ve analiz edilmiştir. Araştırma bağlamına ilişkin bulgular, dahil edilen çalışmaların çoğunun deneysel bir tasarım benimsediğini ve öncelikle üniversite düzeyindeki İngilizceyi Yabancı Dil Olarak Öğrenen öğrencileri içerdiğini göstermektedir. ChatGPT, en sık kullanılan üretken yapay zekâ aracı olarak ortaya çıkmış ve İngilizce baskın hedef dil olmuştur. Çalışmalar genelinde, öz düzenlemeli öğrenme bilişsel, duygusal, motivasyonel ve üstbilişsel süreçler aracılığıyla incelenmiştir. Temel sonuçlar arasında öğrencilerin üretken yapay zekâ araçlarını yüksek düzeyde kabul etmesi, ChatGPT kullanırken artan bilişsel yük raporları ve üretken yapay zekâ entegrasyonunun öz düzenlemeli öğrenme süreçleri üzerindeki genel olumlu etkileri yer almaktadır. Makale, eğitimciler için içgörüler sunarak ve gelecekteki araştırmalar için önerilerde bulunarak sona ermektedir.

Keywords

üretken yapay zeka , öz düzenlemeli dil öğrenimi , sistematik inceleme

References

• Alsager, H. (2024). To Look from Another Window in Education: Artificial Intelligence Assisted Language Learning and Its Reflections on Academic Demotivation, Foreign Language Learning Anxiety and Autonomy. Computer-Assisted Language Learning Electronic Journal, 25(4), 124–147. https://callej.org/index.php/journal/article/view/469
• Anggraeni, C. W., Mujiyanto, J., Rustipa, K., & Widhiyanto. (2025). Effects of utilizing self-regulated learning-based instruction on EFL students’ academic writing skills: A mixed-method investigation. Asian-Pacific Journal of Second and Foreign Language Education, 10(15), 1–26. https://doi.org/10.1186/s40862-024-00317-6
• Aryadoust, V., & Zhang, S. (2025). How to Conduct Bibliometric and Scientometric Research in Language Education? Reference Module in Social Sciences. https://doi.org/10.1016/B978-0-323-95504-1.00432-4
• Azevedo, R. (2009). Theoretical, conceptual, methodological, and instructional issues in research on metacognition and self-regulated learning: A discussion. Metacognition and Learning, 4(1), 87–95. https://doi.org/10.1007/s11409-009-9035-7
• Azevedo, R. (2015). Defining and measuring engagement and learning in science: Conceptual, theoretical, methodological, and analytical issues. Educational Psychologist, 50(1), 84–94. https://doi.org/10.1080/00461520.2015.1004069
• Barrot, J. S. (2023). Using ChatGPT for second language writing: Pitfalls and potentials. Assessing Writing, 57, https://doi.org/10.1016/j.asw.2023.100745
• Chang, W.-L., & Sun, J. C.-Y. (2024). Evaluating AI’s impact on self-regulated language learning: A systematic review. System, 126, https://doi.org/10.1016/j.system.2024.103484
• Charmaz, K. (2014). Constructing grounded theory (2. ed). Sage.
• Chong, S. W., & Plonsky, L. (2021). A Primer on Qualitative Research Synthesis in TESOL. TESOL Quarterly, 55(3), 1024–1034. https://doi.org/10.1002/tesq.3030
• De Mooij, S., Lämsä, J., Lim, L., Aksela, O., Athavale, S., Bistolfi, I., Jin, F., Li, T., Azevedo, R., Bannert, M., Gašević, D., Järvelä, S., & Molenaar, I. (2025). A systematic review of self-regulated learning through integration of multimodal data and artificial intelligence. Educational Psychology Review, 37(54), 1–27. https://doi.org/10.1007/s10648-025-10028-0
• De Wilde, V. (2024). Can novice teachers detect AI-generated texts in EFL writing? ELT Journal, 78(4), 414–422. https://doi.org/10.1093/elt/ccae031
• Godwin-Jones, R. (2021). Big data and language learning: Opportunities and challenges. Language Learning & Technology, 25(1), 4–19. http://hdl.handle.net/10125/44747
• Godwin-Jones, R. (2022). Partnering with AI: Intelligent writing assistance and instructed language learning. Language Learning & Technology, 26(2), 5–24. https://doi.org/10125/73474
• Godwin-Jones, R., O’Neill, E., & Ranalli, J. (2024). Integrating AI tools into instructed second language acquisition. In C. Chapelle, G. Beckett, & J. Ranalli (Eds.), Exploring AI in applied linguistics (pp. 9–23). Iowa State University Digital Press. https://doi.org/10.31274/isudp.2024.154.02
• Guo, K., & Wang, D. (2024). To resist it or to embrace it? Examining ChatGPT’s potential to support teacher feedback in EFL writing. Education and Information Technologies, 29(7), 8435–8463. https://doi.org/10.1007/s10639-023-12146-0
• Heck, T., Keller, C., & Rittberger, M. (2024). Coverage and similarity of bibliographic databases to find most relevant literature for systematic reviews in education. International Journal on Digital Libraries, 25(2), 365–376. https://doi.org/10.1007/s00799-023-00364-3
• Ji, Y., Zhong, M., Lyu, S., Li, T., Niu, S., & Zhan, Z. (2025). How does AI literacy affect individual innovative behavior: The mediating role of psychological need satisfaction, creative self-efficacy, and self-regulated learning. Education and Information Technologies, 30, 16133–16162. https://doi.org/10.1007/s10639-025-13437-4
• Karaoglan Yilmaz, F. G., & Yilmaz, R. (2025). Exploring the role of self-regulated learnings skills, cognitive flexibility, and metacognitive awareness on generative artificial intelligence attitude. Innovations in Education and Teaching International, 62(5), 1–16. https://doi.org/10.1080/14703297.2025.2484613
• 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, Article 102274, 1–9. https://doi.org/10.1016/j.lindif.2023.102274
• Koltovskaia, S., Rahmati, P., & Saeli, H. (2024). Graduate students’ use of ChatGPT for academic text revision: Behavioral, cognitive, and affective engagement. Journal of Second Language Writing, 65, Article 101130, 1–15. https://doi.org/10.1016/j.jslw.2024.101130
• Kong, S.-C., Lee, J. C.-K., & Tsang, O. (2024). A pedagogical design for self-regulated learning in academic writing using text-based generative artificial intelligence tools: 6-P pedagogy of plan, prompt, preview, produce, peer-review, portfolio-tracking. Research and Practice in Technology Enhanced Learning, 19(30), 1–18. https://doi.org/10.58459/rptel.2024.19030
• Kong, S.-C., & Yang, Y. (2024). A Human-Centered 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, 17, 1562–1573. https://doi.org/10.1109/TLT.2024.3392830
• Lee, S., Choe, H., Zou, D., & Jeon, J. (2025). Generative AI (GenAI) in the language classroom: A systematic review. Interactive Learning Environments, 1–25. https://doi.org/10.1080/10494820.2025.2498537
• Li, T., Nath, D., Cheng, Y., Fan, Y., Li, X., Raković, M., Khosravi, H., Swiecki, Z., Tsai, Y.-S., & Gašević, D. (2025). Turning real-time analytics into adaptive scaffolds for self-regulated learning using generative artificial intelligence. In Proceedings of the 15th International Learning Analytics and Knowledge Conference, (pp. 667–679). https://doi.org/10.1145/3706468.3706559
• Lin, L., Gong, Y., & Xu, N. (2021). Online self-regulated earning profiles: A study of Chinese as a foreign language learners. Frontiers in Psychology, 12. Article 797786, 1–13. https://doi.org/10.3389/fpsyg.2021.797786
• Liu, C.-C., Hwang, G.-J., Yu, P., Tu, Y.-F., & Wang, Y. (2025). Effects of an automated corrective feedback-based peer assessment approach on students’ learning achievement, motivation, and self-regulated learning conceptions in foreign language pronunciation. Educational Technology Research and Development, 73, 2403–2424. https://doi.org/10.1007/s11423-025-10484-z
• Liu, K., Yao, J., Tao, D., & Yang, T. (2023). Influence of individual-technology-task-environment fit on university students online learning performance: The mediating role of behavioral, emotional, and cognitive engagement. Education and Information Technologies, 28, 15949–15968. https://doi.org/10.1007/s10639-023-11833-2
• Mirriahi, N., Marrone, R., Barthakur, A., Gabriel, F., Colton, J., & Yeung, T. N. (2025). The relationship between students' self-regulated learning skills and technology acceptance of GenAI. Australian Journal of Educational Technology, 41(2), 16–33. https://doi.org/10.14742/ajet.10006
• Mohebbi, A. (2025). Enabling learner independence and self-regulation in language education using AI tools: A systematic review. Cogent Education, 12(1), 1–18. https://doi.org/10.1080/2331186X.2024.2433814
• Molenaar, I., Baten, D., Bárd, I., & Stevens, M. (2025). Artificial intelligence and education: Different perceptions and ethical directions. In N. A. Smuha (Ed.), The Cambridge handbook of the law, ethics and policy of artificial intelligence (1st ed., pp. 261–282). Cambridge University Press. https://doi.org/10.1017/9781009367783.017
• Molenaar, I., Mooij, S. D., Azevedo, R., Bannert, M., Järvelä, S., & Gašević, D. (2023). Measuring self-regulated learning and the role of AI: Five years of research using multimodal multichannel data. Computers in Human Behavior, 139, Article 107540, 1–9. https://doi.org/10.1016/j.chb.2022.107540
• Page, M. J., Moher, D., Bossuyt, P. M., Boutron, I., Hoffmann, T. C., Mulrow, C. D., Shamseer, L., Tetzlaff, J. M., Akl, E. A., Brennan, S. E., Chou, R., Glanville, J., Grimshaw, J. M., Hróbjartsson, A., Lalu, M. M., Li, T., Loder, E. W., Mayo-Wilson, E., McDonald, S.,…, McKenzie, J. E. (2021). PRISMA 2020 explanation and elaboration: Updated guidance and exemplars for reporting systematic reviews. BMJ, 372(160), 1–36. https://doi.org/10.1136/bmj.n160
• Pan, M., Lai, C., & Guo, K. (2025). Effects of GenAI-empowered interactive support on university EFL students’ self-regulated strategy use and engagement in reading. The Internet and Higher Education, 65, Article 100991, 1–15. https://doi.org/10.1016/j.iheduc.2024.100991
• Perifanou, M., & Economides, A. A. (2025). Collaborative Uses of GenAI Tools in Project-Based Learning. Education Sciences, 15(3), 1–23. https://doi.org/10.3390/educsci15030354
• Pintrich, P. R. (2000). The role of goal orientation in self-regulated learning. In M. Boekaerts, M. Zeidner, & P. R. Pintrich (Eds.), Handbook of self-regulation (pp. 451–502). Elsevier. https://doi.org/10.1016/B978-012109890-2/50043-3
• Romero-Rodríguez, J.-M., Ramírez-Montoya, M.-S., Buenestado-Fernández, M., & Lara-Lara, F. (2023). Use of ChatGPT at university as a tool for complex thinking: Students’ perceived usefulness. Journal of New Approaches in Educational Research, 12(2), 323–339. https://doi.org/10.7821/naer.2023.7.1458
• Samadi, F., Jafarigohar, M., Saeedi, M., Ganji, M., & Khodabandeh, F. (2024). Impact of flipped classroom on EFL learners’ self- regulated learning and higher-order thinking skills during the Covid19 pandemic. Asian-Pacific Journal of Second and Foreign Language Education, 9, Article 24, 1–15. https://doi.org/10.1186/s40862-023-00246-w
• Sardi, J., Darmansyah, Candra, O., Yuliana, D. F., Habibullah, Yanto, D. T. P., & Eliza, F. (2025). How generative AI influences students’ self-regulated learning and critical thinking skills? A Systematic Review. International Journal of Engineering Pedagogy (iJEP), 15(1), 94–108. https://doi.org/10.3991/ijep.v15i1.53379
• Shen, R., & Chong, S. W. (2023). Learner engagement with written corrective feedback in ESL and EFL contexts: A qualitative research synthesis using a perception-based framework. Assessment & Evaluation in Higher Education, 48(3), 276–290. https://doi.org/10.1080/02602938.2022.2072468
• Wang, C. (2025). Exploring students’ generative AI-assisted writing processes: Perceptions and experiences from native and nonnative English speakers. Technology, Knowledge and Learning, 30, 1825-1846. https://doi.org/10.1007/s10758-024-09744-3
• Wang, S, & Huang, Y. (2025). Facilitation or Inhibition: The Impact of Generative Artificial Intelligence on College Students’ Creativity. Frontiers of Education in China, 20(2), 38–53. https://doi.org/10.3868/s110-020-025-0003-0
• Wang, Y. (2025). A study on the efficacy of ChatGPT-4 in enhancing students’ English communication skills. Sage Open, 15(1), 1–17. https://doi.org/10.1177/21582440241310644
• Warschauer, M., Tseng, W., Yim, S., Webster, T., Jacob, S., Du, Q., & Tate, T. (2023). The affordances and contradictions of AI-generated text for writers of English as a second or foreign language. Journal of Second Language Writing, 62, Article 101071, 1–7. https://doi.org/10.1016/j.jslw.2023.101071
• Wei, L. (2023). Artificial intelligence in language instruction: Impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, 14, 1–14. https://doi.org/10.3389/fpsyg.2023.1261955
• Winne, P. H. & Hadwin, A. F. (1998). Studying as self-regulated learning. In D. Hacker, J. Dunlosky, & A. Graesser (Eds.), Metacognition in educational theory and practice (pp. 277–304). Erlbaum.
• Woo, D. J., Wang, D., Guo, K., & Susanto, H. (2024). Teaching EFL students to write with ChatGPT: Students’ motivation to learn, cognitive load, and satisfaction with the learning process. Education and Information Technologies, 29(18), 24963–24990. https://doi.org/10.1007/s10639-024-12819-4
• Wu, Y., Wang, X., & Lan, L. (2025). Advancing multilingual education with artificial intelligence: A case study on Spanish language education in Chinese universities. European Journal of Education Science, 1(1), 1–11. https://doi.org/10.71222/9gty4w14
• Xu, J., & Liu, Q. (2025). Uncurtaining windows of motivation, enjoyment, critical thinking, and autonomy in AI-integrated education: Duolingo Vs. ChatGPT. Learning and Motivation, 89, Article 102100. https://doi.org/10.1016/j.lmot.2025.102100
• Xu, Q., Wu, J., & Peng, H. (2022). Chinese EFL university students’ self-efficacy for online self-regulated learning: Dynamic features and influencing factors. Frontiers in Psychology, 13, 1–12. https://doi.org/10.3389/fpsyg.2022.912970
• Xu, X., Qiao, L., Cheng, N., Liu, H., & Zhao, W. (2025). Enhancing self‐regulated learning and learning experience in generative AI environments: The critical role of metacognitive support. British Journal of Educational Technology, 56(5), 1842–1863. https://doi.org/10.1111/bjet.13599
• Yang, L., & Li, R. (2024). ChatGPT for L2 learning: Current status and implications. System, 124, Article 103351. https://doi.org/10.1016/j.system.2024.103351
• Zhang, H., Li, R., & Liao, W. (2024). Unpacking MATESOL students’ self-regulated learning strategy use in an EAP course. System, 124, Article 103364. https://doi.org/10.1016/j.system.2024.103364
• Zhang, W., Liu, B., & Wilson, A. J. (2024). Examining Chinese EFL learners’ online self-regulated learning: A mixed-methods approach. System, 123, Article 103277. https://doi.org/10.1016/j.system.2024.103277
• Zhang, Z., Aubrey, S., Huang, X., & Chiu, T. K. F. (2025). The role of generative AI and hybrid feedback in improving L2 writing skills: A comparative study. Innovation in Language Learning and Teaching, 1–19. https://doi.org/10.1080/17501229.2025.2503890
• Zimmerman, B. J. (2002). Becoming a self-regulated learner: An overview. Theory Into Practice, 41(2), 64–70. https://doi.org/10.1207/s15430421tip4102_2