The Role and Impact of AI-Driven Feedback Models and Applications in EFL Vocabulary Learning and Retention: A Systemic Review
Keywords:
Artificial Intelligence, EFL, Feedback, vocabularyAbstract
Vocabulary learning is an essential part of language learning. Vocabulary Instruction Feedback is essential in achieving learning objectives, mainly in language education. Vocabulary retention in one of the key issues in developing various language skills. Vocabulary instruction feedback is essential in achieving learning objectives, mainly in language education. The present study purposes to determine the role and impact of AI-driven feedback in EFL vocabulary instruction in Islamic countries educational institution. The study used systematic review method to gather data for the present study. For this, the study reviews the various AI-driven models that can be integrated with E-learning and act a source of feedback. The findings of the review assert that AI-driven mechanisms can be integrated to enhance the vocabulary learning and retention. The analysis suggest that AI-driven feedback models can useful if they are effectively incorporated in enhancing EFL vocabulary learning. By leveraging these technologies, instructors can produce more personalized feedback and operative learning experiences that help students in their vocabulary learning and retention.
References
Akmalovna, X. A. (2024). Improving Vocabulary Effectively. ANALYSIS OF MODERN SCIENCE AND INNOVATION, 1(2), 229-233.
Al-Badi, A., & Khan, A. (2022). Perceptions of learners and instructors towards artificial intelligence in personalized learning. Procedia computer science, 201, 445-451.
Al Arif, T. Z. Z., & Handayani, R. (2022). Factors influencing the use of ICT for English language learning of Indonesian EFL university students. Elsya: Journal of English Language Studies, 4(1), 24-33.
Alatrash, R., Priyadarshini, R., Ezaldeen, H., & Alhinnawi, A. (2022). Augmented language model with deep learning adaptation on sentiment analysis for E-learning recommendation. Cognitive Systems Research, 75, 53-69.
Alharbi, K., & Khalil, L. (2023). Artificial intelligence (AI) in ESL vocabulary learning: An exploratory study on students and teachers’ perspectives. Migration Letters, 20(S12), 1030-1045.
Alharbi, W. (2023). AI in the foreign language classroom: A pedagogical overview of automated writing assistance tools. Education Research International, 2023(1), 4253331.
Ali, & Faisal, B. (2024). The Effectiveness of Two Feedback Strategies for Teaching Vocabulary Among EFL Students. journal of Language Studies, 8(10), 184-202.
Ali, A., Khan, R. M. I., & Al-Awadhi, A. A. (2022). The adoption of mobile learning among university students. International Journal of Computer Science and Network Security, 531-538.
Ali, A., Khan, R. M. I., & Alouraini, A. (2023). A comparative study on the impact of online and blended learning. SAGE Open, 13(1), 21582440231154417.
Barclay, S. C. (2021). Examining the learning burden and decay of second language vocabulary knowledge. UCL (University College London).
Chiu, T. K., Meng, H., Chai, C.-S., King, I., Wong, S., & Yam, Y. (2021). Creation and evaluation of a pretertiary artificial intelligence (AI) curriculum. IEEE Transactions on Education, 65(1), 30-39.
Chiu, T. K., Moorhouse, B. L., Chai, C. S., & Ismailov, M. (2023). Teacher support and student motivation to learn with Artificial Intelligence (AI) based chatbot. Interactive Learning Environments, 1-17.
Chowdhury, K. (2024). Impediments of Speaking English in EFL Classroom: A case study on Undergraduate level in Bangladesh. International Journal of English Language Teaching, 12(2), 66-81.
Enayat, M. J., & Derakhshan, A. (2021). Vocabulary size and depth as predictors of second language speaking ability. System, 99, 102521.
Etaat, F. (2024). The Effect of AI-Based Applications on EFL Writing Skill Development: An Inquiry into Integration of AI into Language Learning. UiT Norges arktiske universitet.
Feng, Alsager, H. N., Azizi, Z., & Sarabani, L. (2023). Impact of mind-mapping technique on EFL learners' vocabulary recall and retention, learning motivation, and willingness to communicate. Heliyon, 9(6).
Feng, Y., & Webb, S. (2020). Learning vocabulary through reading, listening, and viewing: Which mode of input is most effective? Studies in Second Language Acquisition, 42(3), 499-523.
Ghalebi, R., Sadighi, F., & Bagheri, M. S. (2020). Vocabulary learning strategies: A comparative study of EFL learners. Cogent Psychology, 7(1), 1824306.
Guo, L. (2021). Effects of the initial test interval and feedback timing on L2 vocabulary retention. The Language Learning Journal, 49(3), 382-398.
Hashimoto, B. J. (2021). Is frequency enough?: The frequency model in vocabulary size testing. Language Assessment Quarterly, 18(2), 171-187.
Hestiana, M., & Anita, A. (2022). THE ROLE OF MOVIE SUBTITLES TO IMPROVE STUDENTS'VOCABULARY. Journal of English Language Teaching and Learning, 3(1), 46-53.
Huang, L. (2023). Ethics of artificial intelligence in education: Student privacy and data protection. Science Insights Education Frontiers, 16(2), 2577-2587.
Hwang, W.-Y., Nurtantyana, R., Purba, S. W. D., Hariyanti, U., Indrihapsari, Y., & Surjono, H. D. (2023). AI and recognition technologies to facilitate English as foreign language writing for supporting personalization and contextualization in authentic contexts. Journal of Educational Computing Research, 61(5), 1008-1035.
Jomaa, N., Attamimi, R., & Al Mahri, M. (2025). The Use of Artificial Intelligence (AI) in Teaching English Vocabulary in Oman: Perspectives, Teaching Practices, and Challenges. World, 15(3).
Khan, R. M. I. (2022). The use of flashcards in teaching EFL vocabulary in online learning. Register Journal, 15(1), 109-125.
Khan, R. M. I., Alahmadi, A., Radzuan, N. R. M., & Shahbaz, M. (2024). A Qualitative Analysis of WhatsApp Integration on Speaking Vocabulary Development. Register Journal, 17(1), 146-163.
Khan, R. M. I., Radzuan, N. R. M., Farooqi, S.-u.-H., Shahbaz, M., & Khan, M. S. (2021). Learners' Perceptions on WhatsApp Integration as a Learning Tool to Develop EFL Vocabulary for Speaking Skill. International Journal of Language Education, 5(2), 1-14.
Kibuku, R. N., Ochieng, D. O., & Wausi, A. N. (2020). e‑Learning Challenges Faced by Universities in Kenya: A Literature Review. Electronic Journal of E-learning, 18(2), pp150‑161-pp150‑161.
Kuddus, K. (2022). Artificial intelligence in language learning: Practices and prospects. Advanced Analytics and Deep Learning Models, 1-17.
Kuo, F.-R., Hsu, C.-C., Fang, W.-C., & Chen, N.-S. (2014). The effects of Embodiment-based TPR approach on student English vocabulary learning achievement, retention and acceptance. Journal of King Saud University-Computer and Information Sciences, 26(1), 63-70.
Li, R. (2023). Investigating effects of computer-mediated feedback on L2 vocabulary learning. Computers & Education, 198, 104763.
Mohamed, M. S. P. (2024). Exploring ethical dimensions of AI-enhanced language education: A literature perspective. Technology in Language Teaching & Learning, 6(3), 1813-1813.
Mousavi, S., Ghafoori, N., & Saeidi, M. (2020). The effect of noticing, retrieval, and generation on vocabulary learning and retention among high School students. Journal of School Psychology, 9(1), 189-207.
Nakata, T. (2015). Effects of feedback timing on second language vocabulary learning: Does delaying feedback increase learning? Language Teaching Research, 19(4), 416-434.
Nation, P. (2024). Re-thinking the principles of (vocabulary) learning and their applications. Languages, 9(5), 160.
Ngo, K. T. (2024). The Use of ChatGPT for Vocabulary Acquisition: A Literature Review. International Journal of AI in Language Education, 1(2), 1-17.
Nykyporets, S., Pradivlyanny, M., Boiko, Y. V., Chopliak, V., & Kukharchuk, H. (2024). Innovative techniques in vocabulary acquisition for foreign language learning: the impact of artificial intelligence. Суспільство та національні інтереси№ 5 (5): 113-127.
Paiva, J. C., Leal, J. P., & Figueira, Á. (2022). Automated assessment in computer science education: A state-of-the-art review. ACM Transactions on Computing Education (TOCE), 22(3), 1-40.
Qizi, T. F. R. (2023). Bias in AI-based L2 learning tools. Paper presented at the Interdisciplinary Conference of Young Scholars in Social Sciences (USA).
Schmidt, T., & Strasser, T. (2022). Artificial intelligence in foreign language learning and teaching: a CALL for intelligent practice. Anglistik: International Journal of English Studies, 33(1), 165-184.
Schmitt, N., & Schmitt, D. (2020). Vocabulary in language teaching: Cambridge university press.
Von Rueden, L., Mayer, S., Beckh, K., Georgiev, B., Giesselbach, S., Heese, R., . . . Ramamurthy, R. (2021). Informed machine learning–a taxonomy and survey of integrating prior knowledge into learning systems. IEEE Transactions on Knowledge and Data Engineering, 35(1), 614-633.
Wei, W. (2023). Understanding and supporting the use of feedback from mobile applications in the learning of vocabulary among young adolescent learners. Studies in Educational Evaluation, 78, 101264.
Wen, Y., Chiu, M., Guo, X., & Wang, Z. (2024). AI‐powered vocabulary learning for lower primary school students. British Journal of Educational Technology.
Yablonsky, S. A. (2020). AI-driven digital platform innovation. Technology Innovation Management Review, 10(10).
Zhang, R., Zou, D., & Xie, H. (2022). Spaced repetition for authentic mobile-assisted word learning: Nature, learner perceptions, and factors leading to positive perceptions. Computer Assisted Language Learning, 35(9), 2593-2626.
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Dr. Raja Muhammad Ishtiaq Khan, Muhammad Shahbaz, Raja Zahid Farid, Nouman Hamid

This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
COPYRIGHT NOTICE
REGISTER JOURNAL: https://ejournal.uinsalatiga.ac.id/index.php/register/index is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License
Copyright Notice
An author who publishes in REGISTER JOURNAL agrees to the following terms:
- The author retains the copyright and grants the journal the right of first publication of the work simultaneously licensed under the Creative Commons Attribution-ShareAlike 4.0 License that allows others to share the work with an acknowledgment of the work's authorship and initial publication in this journal
- The author can enter into separate, additional contractual arrangements for the non-exclusive distribution of the journal's published version of the work (e.g., post it to an institutional repository or publish it in a book) with the acknowledgment of its initial publication in this journal.
- The author is permitted and encouraged to post his/her work online (e.g., in institutional repositories or on their website) before and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of the published work (See The Effect of Open Access).
Read more about the Creative Commons Attribution-ShareAlike 4.0 Licence here: https://creativecommons.org/licenses/by-sa/4.0/.
Privacy Statement
The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal. They will not be made available for any other purpose or to any other party.