Artificial Intelligence Tools in Personalized Language Learning: A Systematic Thematic Review
DOI:
https://doi.org/10.33394/jollt.v14i2.18187Keywords:
Artificial intelligence, Personalized language learning, Adaptive learning systems, Student autonomy, Natural language processing, ChatGPT mediaAbstract
The integration of artificial intelligence (AI) technologies into language learning has become an essential field of research because it promises to adapt educational experiences to individual learners. With the rapid progress of automatic learning algorithms, adaptive learning systems can now immediately analyze learners' progress and adjust content and delivery methods accordingly. This adaptability improves the personalization of linguistic education, allowing students to engage more deeply with the material at their own pace and skill level. This study aims to explore how AI-driven technologies can improve personalized language learning experiences through autonomous learning. This study focuses on adaptive learning systems powered by AI tools such as ChatGPT, DeepSeek, and Duolingo, developing user engagement strategies, and exploring evolving implications for better results in language acquisition. This research uses a systematic thematic review methodology. Following the guidelines from Braun and Clarke (2006), systematically analyzed 59 peer-reviewed studies thematically. They were identified through academic databases (e.g., Scopus, Google Scholar, ERIC, JSTOR, Education Source) published during 2023-2025. Developed themes included AI for student autonomy, pocket teacher AI: feedback and learning apps, AI for diverse demographics and social inclusion, intelligent conversations: chatbots and language models, personalized learning, limitations, and access inequalities. The study shows that personalized learning helps students learn languages better. Students who use advanced AI tools remember more and manage their learning better than with traditional methods. In the end, the implications of this study highlight the potential of AI tools such as ChatGPT, DeepSeek, and Duolingo to enhance language education by facilitating personalized learning and helping learners achieve better language-learning outcomes.
References
Al-Atrash, A. N. F. (2024). Exploring EFL students’ perspectives of the role of ChatGPT-aided personalized learning in enhancing autonomous learning in Palestinian higher education (Master’s thesis, An-Najah National University). An-Najah National University Repository.
Alhusaiyan, E. (2025). A systematic review of current trends in artificial intelligence in foreign language learning. Saudi Journal of Language Studies, 5(1), 1-16. https://doi.org/10.1108/SJLS-07-2024-0039
Al-Smadi, O. A., Ab Rashid, R., Saad, H., Zrekat, Y. H., Kamal, S. S. L. A., & Uktamovich, G. I. (2024). Artificial intelligence for English language learning and teaching: Advancing sustainable development goals. Journal of Language Teaching and Research, 15(6), 1835-1844. https://doi.org/10.17507/jltr.1506.09
Anis, M. I., & Hasan, M. M. (2025). From Reflection to Practice: A Qualitative Study of Teaching Practicum Experiences. EDUCASIA: Jurnal Pendidikan, Pengajaran, dan Pembelajaran, 10(1), 13-26. https://doi.org/10.21462/educasia.v10i1.295
Arani, S. M. N. (2024). Navigating the future of language learning: A Conceptual review of AI’s role in personalized learning. Computer-Assisted Language Learning Electronic Journal, 25(3), 1-22. https://callej.org/index.php/journal/article/view/78
Alruwaili, A. R., Kianfar, Z., & Azari Noughabi, M. (2025). Exploring EFL Teachers’ Motivation and Influential Factors in Adopting AI for Language Teaching. Language Related Research, 16(5), 93-124. http://lrr.modares.ac.ir/article-14-76622-en.html
Brightwood, S., Olusegun, J., Oluwaseyi, J., & Temitope, O. M. (2024). Intelligent assessment systems: using ai for formative and summative evaluations. https://share.google/oDCJOYkE3pMC8aRvV
Bayly-Castaneda, K., Ramirez-Montoya, M. S., & Morita-Alexander, A. (2024, August). Crafting personalized learning paths with AI for lifelong learning: a systematic literature review. In Frontiers in Education (Vol. 9, p. 1424386). Frontiers. https://doi.org/10.3389/feduc.2024.1424386
Chen, A., Zhang, Y., Jia, J., Liang, M., Cha, Y., & Lim, C. P. (2025). A systematic review and meta‐analysis of AI‐enabled assessment in language learning: Design, implementation, and effectiveness. Journal of Computer Assisted Learning, 41(1), e13064. https://doi.org/10.1111/jcal.13064
Chen, Y. (2025). Transforming English language education with AI-driven deep learning models for scalable adaptive and inclusive assessment. International Journal of Information and Communication Technology, 26(12), 15-31. https://doi.org/10.1504/IJICT.2025.146163
Dekhakhena, A. (2025). AI-Powered Personalized Learning in EFL Acquisition: Exploring Adaptive Instruction and Feedback Systems. Journal of Studies in Language, Culture and Society (JSLCS), 8(1), 111-131. https://asjp.cerist.dz/en/article/266936
Es-Sarghini, A., & Boumahdi, A. (2025). Interactive eAssessment of Writing Competency in French as a Foreign Language: Development and Implementation of an AI-Enhanced Progress Monitoring System. Australian Journal of Applied Linguistics, 8(1), 102495. https://doi.org/10.29140/ajal.v8n1.102495
Erdiana, L., Dziqy, A. N. A., Farouq, A. A., & Slamet, J. (2025). Enhancing Listening Comprehension in Non-English Majors through AI-Integrated Gamified Formative Assessment. Applied Research on English Language. 10.22108/are.2025.144695.2475
Fanning, S. (2024). Parallel Minds: A Thematic Literature Review of Artificial Intelligence in Education (Master's thesis, Washington State University). https://doi.org/10.7273/000007186
Frank, E. (2024). The Influence of artificial intelligence on education: Enhancing personalized learning experiences. EasyChair Preprint, 14675. https://easychair.org/publications/preprint/5Xnl
Haruna, H. H., Iftikhar, S., Isa, S. M., & Hasan, M. M. (2025). Effect of professional development, collaborative learning, and technology integration on teachers’ self-access support competence. Studies in Self-Access Learning Journal, 16(3), 525–565. https://doi.org/10.37237/160304
Hasan, M. M., Islam, M. N., Nirjon, M. I. H., Uddin, M. S., Mamun, M. M., Munna, Z. A., &; Rumman, A. M. (2025). Predicting student performance and identifying learning behaviors using decision trees and K-means clustering. International Journal of Evaluation and Research in Education (IJERE), 14(5), 3872–3881. https://doi.org/10.11591/ijere.v14i5.33815
Hasan, M. M., Islam, M. N., Nirjon, M. I. H., Uddin, M. S., Mamun, M. M., Munna, Z. A., & Rumman, A. M. (2025). Predicting student performance and identifying learning behaviors using decision trees and K-means clustering. International Journal of Evaluation and Research in Education (IJERE), 14(5), 3872–3881. https://doi.org/10.11591/ijere.v14i5.33815
Hasan, M. M., Khanom, S., Rumman, A. M., & Fatema, K. (2024). Blended Supervision of Thesis: Lessons and Future Directions from COVID-19 and Post-Pandemic Situation. Crossings: A Journal of English Studies, 15(1), 196–214. https://doi.org/10.59817/cjes.v15i1.572
Hidayat-ur-Rehman, I. (2024). Examining AI competence, chatbot use and perceived autonomy as drivers of students' engagement in informal digital learning. Journal of Research in Innovative Teaching & Learning, 17(2), 196-212. https://doi.org/10.1108/JRIT-05-2024-0136
Hong, X., & Guo, L. (2025). Effects of AI-enhanced multi-display language teaching systems on learning motivation, cognitive load management, and learner autonomy. Education and Information Technologies, 1-35. http://dx.doi.org/10.1007/s10639-025-13472-1
Huynh, Q. Q. (2024). A Literature Review on EFL Students’ Integration of Al-Based Tools in English Learning and The Perceived Impact on Autonomy. International Journal of AI in Language Education, 1(2), 30-51. https://doi.org/10.54855/ijaile.24123
Igbokwe, I. C. (2023). Application of artificial intelligence (AI) in educational management. International Journal of Scientific and Research Publications, 13(3), 300-307. http://dx.doi.org/10.29322/IJSRP.13.03.2023.p13536
Islam, M., Hasan, M. M., & Mahmud, R. (2024). EFL teachers' perceptions of AI's impact on academic integrity and pedagogy in Bangladeshi universities. Language Literacy: Journal of Linguistics, Literature, and Language Teaching, 8(2), 564–579. https://doi.org/10.30743/ll.v8i2.10082
Jegede, O. O. (2024). Artificial intelligence and English language learning: Exploring the roles of AI-driven tools in personalizing learning and providing instant feedback. Universal Library of Languages and Literatures, 1(2). https://doi.org/10.70315/uloap.ullli.2024.0102002
Jeon, J., Lee, S., & Choi, S. (2024). A systematic review of research on speech-recognition chatbots for language learning: Implications for future directions in the era of large language models. Interactive Learning Environments, 32(8), 4613–4631. https://doi.org/10.1080/10494820.2023.2204343
Jian, M. J. K. O. (2023). Personalized learning through AI. Advances in Engineering Innovation, 5(1), 16-19. https://doi.org/10.54254/2977-3903/5/2023039
Kanchana, S., & Saha, P. R. (2025). Evolving Student Assessment: AI-Driven Rubrics for Personalized and Equitable English Language Learning. Journal of Engineering Education Transformations, 584-590. https://doi.org/10.16920/jeet/2025/v38is2/25072
Kazimova, D., Tazhigulova, G., Shraimanova, G., Zatyneyko, A., & Sharzadin, A. (2025). Transforming University Education with AI: A Systematic Review of Technologies, Applications, and Implications. International Journal of Engineering Pedagogy, 15(1). https://doi.org/10.3991/ijep.v15i1.50773
Kerimbayev, N., Adamova, K., Shadiev, R., & Altinay, Z. (2025). Intelligent educational technologies in individual learning: a systematic literature review. Smart Learning Environments, 12(1), 1. https://doi.org/10.1186/s40561-024-00360-3
Khan, A. L., Hasan, M. M., Islam, M. N., & Uddin, M. S. (2024). Artificial Intelligence Tools in Developing English Writing Skills: Bangladeshi University EFL Students’ Perceptions. English Education: Jurnal Tadris Bahasa Inggris, 17(2), 345-371. https://dx.doi.org/10.24042/ee-jtbi.v17i2.24369
Koç, F. Ş., & Savaş, P. (2025). The use of artificially intelligent chatbots in English language learning: A systematic meta-synthesis study of articles published between 2010 and 2024. ReCALL, 37(1), 4-21. https://doi.org/10.1017/S0958344024000168
Kovalenko, I., & Baranivska, N. (2024). Integrating Artificial Intelligence in English Language Teaching: Exploring the potential and challenges of AI tools in enhancing language learning outcomes and personalized education. Європейські соціо-правові та гуманітарні студії, (1), 86-95. https://doi.org/10.61345/2734-8873.2024.1.9
Κουκαρασ, Χ. (2025). AI-Driven Personalised Language Learning for Refugees and Immigrants: A Study on Adaptive Learning Tools and Their Impact on Migrant and Refugee Integration. https://apothesis.eap.gr/archive/item/219283
Kristiawan, D., Bashar, K., & Pradana, D. A. (2024). Artificial intelligence in English language learning: A systematic review of AI tools, applications, and pedagogical outcomes. The Art of Teaching English as a Foreign Language (TATEFL), 5(2), 207-218. https://doi.org/10.36663/tatefl.v5i2.912
Li, K. C., & Wong, B. T. M. (2023). Artificial intelligence in personalised learning: a bibliometric analysis. Interactive Technology and Smart Education, 20(3), 422-445. https://doi.org/10.1108/ITSE-01-2023-0007
Ma, H., Ismail, L., & Han, W. (2024). A bibliometric analysis of artificial intelligence in language teaching and learning (1990–2023): evolution, trends and future directions. Education and Information Technologies, 29(18), 25211-25235. https://doi.org/10.1007/s10639-024-12848-z
Mahmoud, C. F., & Sørensen, J. T. (2024). Artificial intelligence in personalized learning with a focus on current developments and future prospects. Research and Advances in Education, 3(8), 25-31. http://dx.doi.org/10.56397/RAE.2024.08.04
Mohebbi, A. (2025). Enabling learner independence and self-regulation in language education using AI tools: a systematic review. Cogent Education, 12(1), 2433814. https://doi.org/10.1080/2331186X.2024.2433814
Myrzabek, A., Yersultanova, G., & Jandildinov, M. (2025). Formative Assessment in Kazakhstan’s English Language Classrooms: A Narrative Review of Current Practices and the Role of AI Tools. Педагогика и Методы Обучения, 71(2), 99-113. https://doi.org/10.47344/epbd2d80
Naznin, K., Al Mahmud, A., Nguyen, M. T., & Chua, C. (2025). ChatGPT integration in higher education for personalized learning, academic writing, and coding tasks: a systematic review. Computers, 14(2), 53. https://doi.org/10.3390/computers14020053
Pari, M. (2024). Artificial Intelligence (AI) Presentation Assistants: Current Trends, Experiences, and Future Directions for Language Pedagogy. International Journal of Practical and Pedagogical Issues in English Education, 2(3), 54-66. https://share.google/COfystufBGYBUE9T4
Saeedirad, M. A., & Sabet, M. K. (2024). Planting Seeds of Understanding: Nurturing Listening Comprehension through Formative Assessment and AI-Powered Feedback. Journal of Applied Linguistics Studies, 4(2). https://oiccpress.com/jals/article/view/16545
Saleem, S., Aziz, M. U., Iqbal, M. J., & Abbas, S. (2025). AI in education: Personalized learning systems and their impact on student performance and engagement. The Critical Review of Social Sciences Studies, 3(1), 2445-2459. https://doi.org/10.59075/c35qa453
Sharma, S., Mittal, P., Kumar, M., & Bhardwaj, V. (2025). The role of large language models in personalized learning: a systematic review of educational impact. Discover Sustainability, 6(1), 1-24. https://link.springer.com/article/10.1007/s43621-025-01094-z
Shikina, A. (2025). Artificial intelligence tools effectively developing self-directed learning, increasing students’ autonomy and motivation in uzbekistan. UC Journal: ELT, Linguistics and Literature Journal, 6(1), 1-21. https://share.google/40JARlsrOScslVFYr
Sreen, A. S., & Majid, M. H. M. (2024). Leveraging ChatGPT for personalized learning: A systematic review in educational settings. Amandemen: Journal of Learning, Teaching and Educational Studies, 2(1), 63-78. https://doi.org/10.61166/amd.v2i1.72
Tao, W. (2025). Fostering Inspirational Learning Through AI-Enhanced Formative Assessment: Strategies and Challenges in Higher Education. Educational Assessments in the Age of Generative AI, 207-250. http://dx.doi.org/10.4018/979-8-3693-6351-5.ch008
Vashishth, T. K., Sharma, V., Sharma, K. K., Kumar, B., Panwar, R., & Chaudhary, S. (2024). AI-driven learning analytics for personalized feedback and assessment in higher education. In Using traditional design methods to enhance AI-driven decision making (pp. 206-230). IGI Global Scientific Publishing. http://dx.doi.org/10.4018/979-8-3693-0639-0.ch009
Vorobyeva, K. I., Belous, S., Savchenko, N. V., Smirnova, L. M., Nikitina, S. A., & Zhdanov, S. P. (2025). Personalized Learning through AI: Pedagogical Approaches and Critical Insights. Contemporary Educational Technology, 17(2). https://doi.org/10.30935/cedtech/16108
Wang, X., Xu, X., Zhang, Y., Hao, S., & Jie, W. (2024). Exploring the impact of artificial intelligence application in personalized learning environments: thematic analysis of undergraduates’ perceptions in China. Humanities and Social Sciences Communications, 11(1), 1-10. https://www.nature.com/articles/s41599-024-04168-x
Willis, V. (2024). The role of artificial intelligence (AI) in personalizing online learning. Journal of Online and Distance Learning, 3(1), 1-13. https://doi.org/10.47941/jodl.1689
Yılmaz, Ö. (2024). Personalised learning and artificial intelligence in science education: current state and future perspectives. Educational Technology Quarterly, 2024(3), 255-274. https://doi.org/10.55056/etq.744
Yekollu, R. K., Bhimraj Ghuge, T., Sunil Biradar, S., Haldikar, S. V., & Farook Mohideen Abdul Kader, O. (2024, February). AI-driven personalized learning paths: Enhancing education through adaptive systems. In International Conference on Smart data intelligence (pp. 507-517). Singapore: Springer Nature Singapore. https://doi.org/10.1007/978-981-97-3191-6_38
Yuen, C. L., & Schlote, N. (2024). Learner experiences of mobile apps and artificial Intelligence to support additional language learning in education. Journal of Educational Technology Systems, 52(4), 507-525. https://doi.org/10.1177/00472395241238693
Yu, J. H., & Chauhan, D. (2025). Trends in NLP for personalized learning: LDA and sentiment analysis insights. Education and Information Technologies, 30(4), 4307-4348. http://dx.doi.org/10.1007/s10639-024-12988-2
Zhao, J. (2025). Advancing english language education: A mixed-methods analysis of AI-driven tools' impact on engagement, personalization, and learning outcomes. Education and Information Technologies, 1-41. http://dx.doi.org/10.1007/s10639-025-13560-2
Zhu, M., & Wang, C. (2025). A systematic review of research on AI in language education: Current status and future implications. Language Learning & Technology, 29(1), 1-29. https://doi.org/10.64152/10125/73606
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