The Effectiveness of AI-Assisted Reading Tools on EFL Students’ Reading Comprehension and Engagement
DOI:
https://doi.org/10.24256/ideas.v13i2.8715Keywords:
AI assisted reading tools, reading comprehension, student engagementAbstract
This study investigates the effectiveness of a ChatGPT-based Reading Assistant in enhancing EFL students’ reading comprehension and learning engagement. Employing a quasi-experimental design, the study involved two groups of third-semester undergraduate students during the 2024/2025 academic year. Over a six-week instructional period, the experimental group received reading instruction supported by the ChatGPT Reading Assistant, while the control group followed conventional reading practices. Data were collected using a standardized reading comprehension test and an engagement questionnaire. An independent samples t-test revealed no statistically significant difference between the groups’ pretest scores (p > .05), indicating comparable initial proficiency. Post-intervention analysis showed that the experimental group outperformed the control group in reading comprehension, with a statistically significant difference (p < .05). Engagement levels were also significantly higher in the experimental group compared to the control group (p < .05). These findings suggest that AI-assisted reading tools can effectively support EFL reading instruction by improving comprehension outcomes and fostering greater student engagement. Further research is recommended to investigate long-term instructional impacts and to explore learners’ qualitative experiences with AI-supported reading activities.
References
Alazemi, A. F. T. (2024). Formative Assessment in Artificial Integrated Instruction: Delving into the Effects On Reading Comprehension Progress, Online Academic Enjoyment, Personal Best Goals, and Academic Mindfulness. Language Testing in Asia, 14(1). https://doi.org/10.1186/s40468-024-00319-8
Andhika, Aldila, A. S., Supriyono, L. A., Previana, C. N., & Habibie, D. R. (2024). The Effectiveness of Adaptive Learning Systems Integrated with LMS in Higher Education. Jurnal KomtekInfo, 49–56. https://doi.org/10.35134/komtekinfo.v11i2.505
Chea, P., & Xiao, Y. (2024). Artificial Intelligence in Higher Education: The Power and Damage of AI-assisted Tools on Academic English Reading Skills. Journal of General Education and Humanities, 3(3), 287–306. https://doi.org/10.58421/gehu.v3i3.242
Contrino, M. F., Reyes-Millán, M., Vázquez-Villegas, P., & Membrillo-Hernández, J. (2024). Using an Adaptive Learning Tool to Improve Student Performance And Satisfaction in Online and Face-to-Face Education for a More Personalized Approach. Smart Learning Environments, 11(1). https://doi.org/10.1186/s40561-024-00292-y
Diprossimo, L., Ushakova, A., Zoski, J., Gamble, H., Irey, R., & Cain, K. (2023). The Associations between Child and Item Characteristics, Use of Vocabulary Scaffolds, and Reading Comprehension in a Digital Environment: Insights from a Big Data Approach. Contemporary Educational Psychology, 102165. https://doi.org/10.1016/j.cedpsych.2023.102165
Fan, K. (2025). Enhancing Cognitive Reading Strategy Use for L2 Learners with Lower Working Memory through AI-Based Scaffolding. Journal of English Language Teaching and Applied Linguistics, 7(3), 143–151. https://doi.org/10.32996/jeltal.2025.7.3.14
Güner, H., & Er, E. (2025). AI in the classroom: Exploring students’ interaction with ChatGPT in programming learning. Education and Information Technologies. https://doi.org/10.1007/s10639-025-13337-7
Herdiana, & Munir, S. (2023). The Effect of Teacher Scaffolding and Peer-Scaffolding on Reading Comprehension and Vocabulary Ability. JPI (Jurnal Pendidikan Indonesia), 12(3), 451–460. https://doi.org/10.23887/jpiundiksha.v12i3.61213
Jin, F., Maheshi, B., Lai, W., Li, Y., Gašević, D., Chen, G., Charwat, N., Chan, P. W. K., Martinez-Maldonado, R., Gašević, D., & Tsai, Y.-S. (2025). Students’ Perceptions of GenAI-powered Learning Analytics in the Feedback Process: Journal of Learning Analytics, 1–17. https://doi.org/10.18608/jla.2025.8609
Lim, S., & Lee, S.-K. (2025). How do Text Type, Prior Vocabulary Knowledge, and Working Memory Capacity Affect Second Language Incidental Vocabulary Learning through Reading? Studies in Second Language Learning and Teaching. https://doi.org/10.14746/ssllt.33236
Liu, C.-C., Chen, W.-J., Lo, F., Chang, C.-H., & Lin, H.-M. (2024). Teachable Q&A agent: The Effect of Chatbot Training by Students on Reading Interest and Engagement. Journal of Educational Computing Research. https://doi.org/10.1177/07356331241236467
Ozigagun, O. O., Ololade, J., Eyo-Udo, L., & Ogundipe, O. (2024). Revolutionizing Education through Ai: A Comprehensive Review of Enhancing Learning Experiences. International Journal of Applied Research in Social Sciences, 6(4), 589–607. https://doi.org/10.51594/ijarss.v6i4.1011
Pellicer-Sánchez, A. (2020). Expanding English Vocabulary Knowledge through Reading: Insights from Eye-tracking Studies. RELC Journal, 51(1), 003368822090690. https://doi.org/10.1177/0033688220906904
Rad, H. S. (2025). Reinforcing L2 Reading Comprehension through Artificial Intelligence Intervention: Refining Engagement to Foster Self-Regulated Learning. Smart Learning Environments, 12(1). https://doi.org/10.1186/s40561-025-00377-2
Ramadan, A., & Jember, B. (2024). A Step toward Effective Language Learning: An Insight into the Impacts of Feedback-Supported Tasks and Peer-Work Activities on Learners’ Engagement, Self-Esteem, and Language Growth. Asian-Pacific Journal of Second and Foreign Language Education, 9(1). https://doi.org/10.1186/s40862-024-00261-5
Salameh, W. A. K. (2025). Exploring the Impact of AI-Driven Real-Time Feedback Systems on Learner Engagement and Adaptive Content Delivery in Education. International Journal of Science and Research Archive, 14(2), 098-104. https://doi.org/10.30574/ijsra.2025.14.2.0299
Uzun, Y., Suraworachet, W., Zhou, Q., Gauthier, A., & Cukurova, M. (2025). Engagement with Analytics Feedback and its Relationship to Self-Regulated Learning Competence and Course Performance. International Journal of Educational Technology in Higher Education, 22(1). https://doi.org/10.1186/s41239-025-00515-3
Wahyu, Hasanah, U., Muhammad, & Purwati, D. (2025). Student Attitudes Toward AI-Assisted Thesis Writing and Critical Reading: A Case Study from Indonesian English Programs. LETS Journal of Linguistics and English Teaching Studies, 6(2), 129–140. https://doi.org/10.46870/lets.v6i2.1462
Wang, L., & Li, W. (2024). The Impact of AI Usage on University Students’ Willingness for Autonomous Learning. Behavioral Sciences, 14(10), 956–956. https://doi.org/10.3390/bs14100956
Wang, Y., Wu, J., Chen, F., Wang, Z., Li, J., & Wang, L. (2024). Empirical Assessment of AI-Powered Tools for Vocabulary Acquisition in EFL Instruction. IEEE Access, 1–1. https://doi.org/10.1109/access.2024.3446657
Wangdi, T., & Shimray, R. (2025). AI-Powered ReadTheory as a Self-Access Learning Platform to Enhance EFL Learners’ Reading Enjoyment and Comprehension Skills: A Posthumanist Perspective. Studies in Self-Access Learning Journal, 16(2), 437–460. https://doi.org/10.37237/160209
Wu, J., Wang, Y., Chen, F., Yin, X., & He, Y. (2025). Impact of AI-Powered Adaptive Learning Platforms on English Reading Proficiency: Evidence From Structural Equation Modeling. IEEE Access, 13, 88230–88242. https://doi.org/10.1109/access.2025.3571055
Wu, D., & Zhang, J. (2025). Generative artificial intelligence in secondary education: Applications and effects on students’ innovation skills and digital literacy. PLOS One, 20(5), e0323349. https://doi.org/10.1371/journal.pone.0323349
Yaseen, H., Mohammad, A. S., Najwa Ashal, Hesham Abusaimeh, Ali, A., & Abdel-Aziz Ahmad Sharabati. (2025). The Impact of Adaptive Learning Technologies, Personalized Feedback, and Interactive AI Tools on Student Engagement: The Moderating Role of Digital Literacy. Sustainability, 17(3), 1133–1133. https://doi.org/10.3390/su17031133
Yılmaz, Ö. K., & Aydın, S. (2025). The Impact of the Use of Artificial Intelligence–Generated Materials on Reading Motivation among EFL Learners. Reading Research Quarterly, 60(3). https://doi.org/10.1002/rrq.70016
Yin, J., Xu, H., Pan, Y., & Hu, Y. (2025). Effects of different AI-driven Chatbot feedback on learning outcomes and brain activity. Npj Science of Learning, 10(1). https://doi.org/10.1038/s41539-025-00311-8
Yuan, L., & Liu, X. (2024). The Effect of Artificial Intelligence Tools on EFL Learners’ Engagement, Enjoyment, and Motivation. Computers in Human Behavior, 162, 108474–108474. https://doi.org/10.1016/j.chb.2024.108474
Zhang, N. H., & Kaur, C. (2025). Scaffolding and Reading Comprehension: A Literature Review. International Journal of Modern Languages and Applied Linguistics, 9(2), 89–109. https://doi.org/10.24191/ijmal.v9i2.4671
Downloads
Published
Issue
Section
Citation Check
License
Copyright (c) 2026 Nasmah Riyani riyan
This work is licensed under a Creative Commons Attribution-ShareAlike 4.0 International License.
Authors retain copyright and grant the journal right of first publication with the work simultaneously licensed under an Attribution-ShareAlike 4.0 International (CC BY-SA 4.0) that allows others to share the work with an acknowledgement of the work's authorship and initial publication in this journal.
Authors are able to 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 an acknowledgement of its initial publication in this journal.
Authors are permitted and encouraged to post their work online (e.g., in institutional repositories or on their website) prior to and during the submission process, as it can lead to productive exchanges, as well as earlier and greater citation of published work (See the Effect of Open Access)
