Arab World English Journal (AWEJ) Volume 17. Number 3, September 2026 Pp.274-295

Artificial Intelligence in Supporting Self-Regulated Reading among English as a Second Language Learners: A Systematic Review

Ruba Salim Abdulaziz Al Rawas

Education Department, Faculty of Social Sciences and Humanities, University Kebangsaan Malaysia, Bangi, Malaysia

Corresponding Author: P153145@siswa.ukm.edu.my

Education Department, Faculty of Social Sciences and Humanities, University Kebangsaan Malaysia, Bangi, Malaysia

Education Department, Faculty of Social Sciences and Humanities, University Kebangsaan Malaysia, Bangi, Malaysia

Abstract:

Artificial intelligence (AI) has become increasingly prominent in English language education, offering new possibilities for supporting reading instruction and independent learning among English as a second language (ESL) learner. This study aims to examine the existing body of empirical research concerning the use of AI to improve reading skills and encourage self-regulated learning (SRL). The significance of this study lies in its synthesis of fragmented data to provide a unified framework for future technology-mediated reading instruction. Using a systematic literature review approach that strictly followed the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) framework, 19 empirical studies were extracted from major academic databases including Scopus, ERIC, and Google Scholar and analyzed through thematic analysis. The synthesized results reveal that AI applications, particularly adaptive learning platforms and conversational agents, effectively support reading development by giving feedback, personal learning experiences, and opportunities for learners to monitor their own progress. Concurrently, the results highlight several concerns, including excessive dependence on technological support and limited development of higher-order reading skills. Overall, AI can make a valuable contribution to reading instruction when integrated with pedagogical practices that encourage learner independence. Future research should investigate the influence of AI on reading comprehension through longitudinal studies conducted in authentic educational settings.

Cite as:

Al Rawas, R. S.A., Mohammed, M., & Kamsin, I. F. (2026). Artificial Intelligence in Supporting Self-Regulated Reading among English as a Second Language Learners: A Systematic Review. Arab World English Journal, 17(3): 274-295.

References:

Afzaal, M., Zia, A., Nouri, J., & Fors, U. (2024). Informative feedback and explainable AI-based recommendations to support students’ self-regulation. Technology, Knowledge and Learning, 29(1), 331–354. https://doi.org/10.1007/s10758-023-09653-2

Al-Ahdal, A. A. M. H. (2023). Integrating Artificial Intelligence in English language classrooms: A review of pedagogical shifts and learner autonomy. Arab World English Journal, 14(2), 43–56. https://doi.org/10.24093/awej/vol14no2.3

Al Seyabi, F. A., & Al Amri, K. S. (2016). Omani students’ attitudes towards EFL reading between school and university foundation programs: A bridge or a gap? Journal of Educational and Psychological Studies – Sultan Qaboos University, 10(2), 205–220. https://doi.org/10.24200/jeps.vol10iss2pp205-220

Alkhateeb, A., Hezam, A. M. M., & Almuraikhi, A. A. (2025). Assessing the use of AI tools for EFL exam preparation at Saudi universities: Efficiency, benefits, and challenges. Cogent Education, 12(1), Article 2507553. https://doi.org/10.1080/2331186X.2025.2507553

AL-Maktoumi, H. A. S. (2024). The impact of artificial intelligence on the future of English language teaching and learning at Omani universities. Journal of Propulsion Technology, 45(3), 321–335. https://doi.org/10.52783/tjjpt.v45.i03.7359

Alreshoud, A. A., & Abdelhalim, S. M. (2022). The impact of self-regulated strategy development on enhancing Saudi female English majors’ reading comprehension skills and self-efficacy. Arab World English Journal, 13(2), 312–327. https://doi.org/10.24093/awej/vol13no2.21

Azevedo, R., & Cromley, J. G. (2004). Does training learners of challenging science topics with self-regulated learning scaffolds improve deep understanding? Cognition and Instruction, 22(4), 523–583. https://doi.org/10.1207/s1532690xci2204_2

Azmuddin, R. A., Nor, N. F. M., & Hamat, A. (2020). Facilitating online reading comprehension in enhanced learning environment using digital annotation tools. IAFOR Journal of Education, 8(2), 7–27. https://doi.org/10.22492/ije.8.2.01

Behforouz, B., & Al Ghaithi, A. (2025). AI meets education: How ChatGPT transforms reading skills in Omani EFL learners. Training, Language and Culture, 9(3), 10–21. https://doi.org/10.22363/2521-442X-2025-9-3-10-21

Butler, D. L. (2002). Qualitative approaches to investigating self-regulated learning: Contributions and challenges. Educational Psychologist, 37(1), 59–63. https://doi.org/10.1207/S15326985EP3701_7

Darwin, Rusdin, D., Mukminatien, N., Suryati, N., Laksmi, E. D., & Marzuki. (2024). Critical thinking in the AI era: An exploration of EFL students’ perceptions, benefits, and limitations. Cogent Education, 11(1), Article 2290342. https://doi.org/10.1080/2331186X.2023.2290342

Davis, F. D. (1989). Perceived usefulness, perceived ease of use, and user acceptance of information technology. MIS Quarterly, 13(3), 319–340. https://doi.org/10.2307/249008

Diamond, A. (2013). Executive functions. Annual Review of Psychology, 64(1), 135–168. https://doi.org/10.1146/annurev-psych-113011-143750

Fadhil, M. A., & Rahman, S. A. (2024). AI-mediated reading environments and ESL literacy development: Current trends and challenges. Arab World English Journal, 15(1), 110–124. https://doi.org/10.24093/awej/vol15no1.8

Gehlot, L., Al-Khalaf, H. A., & Gehlot, H. (2020). Evaluation of the reading habits of Indian students (reading aloud and reading silently) from low, middle and high class schools. Educational Research and Reviews, 15(2), 41–51. https://doi.org/10.5897/ERR2019.3760

Habók, A., Oo, T. Z., & Magyar, A. (2024). The effect of reading strategy uses on online reading comprehension. Heliyon, 10(3), e24281. https://doi.org/10.1016/j.heliyon.2024.e24281

Jin, Y., 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), 45–62. https://doi.org/10.1186/s41239-023-00406-5

Jose, J. (2024). The impact of integrating Microsoft Teams Reading Progress as an artificial intelligence (AI) platform for promoting learners’ reading aloud skills. Education and Information Technologies, 29(8), 9411–9435. https://doi.org/10.1007/s10639-023-12104-1

Li, S., & Kim, J. (2025). AI to support self-regulated English language learning. NPJ Science of Learning, 10(1), 5–18. https://doi.org/10.1038/s41539-025-00211-9

Lin, L., & Chang, M. (2023). CHAT-ACTS: A pedagogical framework for personalized chatbot to enhance active learning and self-regulated learning. Computers and Education: Artificial Intelligence, 4, Article 100122. https://doi.org/10.1016/j.caeai.2023.100122

Lo, C. K., Tlili, A., Huang, X., & Chen, G. (2024). Exploring the application of ChatGPT in ESL/EFL education and related research issues: A systematic review of empirical studies. Discover Education, 3(1), 12–34. https://doi.org/10.1007/s44217-024-00085-3

Maimaiti, G., & Hew, K. F. (2025). Gamified self-regulated learning improves EFL reading comprehension, motivation, self-regulation skills and process patterns: Quasi-experiment with process mining. The Internet and Higher Education, 67, Article 101042. https://doi.org/10.1016/j.iheduc.2025.101042

Mirzaeian, V. R. (2023). A Google Neural Machine Translation GNMT model for foreign language education. International Journal of Computer-Assisted Language Learning and Teaching, 13(1), 1–19. https://doi.org/10.4018/IJCALLT.316492

Mohammadi, M., Saeidi, M., & Ahangari, S. (2020). Self-regulated learning instruction and the relationships among self-regulation, reading comprehension and reading problem solving: PLS-SEM approach. Cogent Education, 7(1), Article 1757393. https://doi.org/10.1080/2331186X.2020.1757393

Ng, D. T. K., Tan, J. K. L., & Leung, J. K. W. (2024). Empowering student self-regulated learning and science education through ChatGPT: A pioneering pilot study. British Journal of Educational Technology, 55(4), 1254–1273. https://doi.org/10.1111/bjet.13412

Page, M. J., McKenzie, J. E., 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., McGuinness, L. A., Stewart, L. A., Tonia, T., White, I. R., Whittington, C., Jenkins, P., & Moher, D. (2021). The PRISMA 2020 statement: An updated guideline for reporting systematic reviews. BMJ, 372(n71). https://doi.org/10.1136/bmj.n71

Paris, S. G., & Paris, A. H. (2001). Classroom applications of research on self-regulated learning. Educational Psychologist, 36(2), 89–101. https://doi.org/10.1207/S15326985EP3602_4

Pintrich, P. R. (2004). A conceptual framework for assessing motivation and self-regulated learning in college students. Educational Psychology Review, 16(4), 385–407. https://doi.org/10.1007/s10648-004-0006-x

Rakhmetov, M., Sadvakassova, A., Saltanova, G., Kuanbayeva, B., & Zhusupkalieva, G. (2025). Evaluation of an AI-based feedback system for enhancing self-regulated learning in digital education platforms. Electronic Journal of e-Learning, 23(4), 412–427. https://doi.org/10.34190/ejel.23.4.3120

Schunk, D. H., & Greene, J. A. (Eds.). (2018). Handbook of self-regulation of learning and performance (2nd ed.). Routledge. https://doi.org/10.4324/9781315638416

Teich, K., Reinders, H., Stebner, F., & Leutner, D. (2024). Meeting challenges of continuing education online courses: Can we promote SRL strategies with adaptive support? British Journal of Educational Technology, 55(2), 621–640. https://doi.org/10.1111/bjet.13382

Theobald, M. (2021). Self-regulated learning training programs enhance university students’ academic performance, self-regulated learning strategies, and motivation: A meta-analysis. Contemporary Educational Psychology, 66, Article 101976. https://doi.org/10.1016/j.cedpsych.2021.101976

Wolters, C. A., & Brady, A. C. (2021). A self-regulated learning perspective on college students’ time management. Educational Psychology Review, 33(4), 1319–1351. https://doi.org/10.1007/s10648-020-09519-w

Zhang, Z., Zhou, S., & Bai, B. (2026). A systematic scoping review of self-regulated learning with AI in language education. International Journal of Applied Linguistics. Advance online publication. https://doi.org/10.1111/ijal.70030

Zimmerman, B. J. (2000). Attaining self-regulation: A social cognitive perspective. In M. Boekaerts, P. R. Pintrich, & M. Zeidner (Eds.), Handbook of self-regulation (pp. 13–39). Academic Press. https://doi.org/10.1016/B978-012109890-2/50031-7

Zimmerman, B. J., & Schunk, D. H. (Eds.). (2011). Handbook of self-regulation of learning and performance. Routledge. https://doi.org/10.4324/9780203839010

Facebook
Twitter
LinkedIn
Tumblr
Reddit
Email
StumbleUpon
Digg

Ruba Salim Abdulaziz Al Rawas was born in Oman. She is a researcher at the Education Department, Faculty of Social Sciences and Humanities, Universiti Kebangsaan Malaysia, focusing on AI applications, self-regulated reading strategies among Omani ESL/EFL undergraduates.  ORCID: https://orcid.org/0009-0000-5275-0987

 Maslawati Mohamad was born in Malaysia. She is currently a senior lecturer at the Faculty of Education, Universiti Kebangsaan Malaysia. Her research areas are Teaching English as a Second Language and English for Specific Purposes. ORCID: https://orcid.org/0000-0002-8979-5895

 Intan Farahana Kamsin was born in Malaysia. She is a senior lecturer at the Faculty of Education, Universiti Kebangsaan Malaysia. Her research focuses on the Internet of Things, education among marginalized communities, instructional design, e-learning, and technology for teaching and learning. Her interests include students’ well-being and performance. ORCID: https://orcid.org/0009-0006-0435-6743