Enhancing University Students’ Academic Reading Comprehension through ChatGPT-Assisted Instruction in Indonesian Higher Education

M. Iqbal Tawakkal; Sumadi; Djoko Apriono

doi:10.69820/jeltlal.v4i1.533

Authors

M. Iqbal Tawakkal universitas nahdlatul ulama sunan giri
Sumadi Universitas PGRI Ronggolawe, Address, Tuban, Indonesia
Djoko Apriono Universitas PGRI Ronggolawe, Address, Tuban, Indonesia

DOI:

https://doi.org/10.69820/jeltlal.v4i1.533

Keywords:

Academic Reading, AI-Assisted Instruction, Reading Comprehension, Higher Education, Digital Literacy

Abstract

Academic reading comprehension is an essential competency in higher education because students are required to critically understand and evaluate academic texts. However, many university students still experience difficulties in comprehending academic materials due to limited reading strategies and low engagement. This study aimed to investigate the implementation of ChatGPT-assisted instruction and examine its contribution to enhancing students’ academic reading comprehension in higher education. This study employed a mixed-methods approach with a quasi-experimental design involving 60 undergraduate students divided into an experimental group and a control group. The intervention was conducted for eight weeks. The data were collected through reading comprehension tests, classroom observations, and semi-structured interviews and analyzed using quantitative statistical analysis and thematic analysis. The findings revealed that students who participated in AI-assisted instruction achieved significantly higher improvement in reading comprehension compared to those who received conventional instruction. The statistical analysis showed significant improvement in the experimental group (p = 0.001). The qualitative findings also indicated that AI-assisted instruction increased students’ engagement, motivation, and interaction during reading activities. The study concludes that AI-assisted instruction can serve as an effective pedagogical approach to support academic literacy development in higher education.

References

Aldamen, H. A., Almashour, M. A., Al-Deaibes, M. A., & Alsharefeen, R. A. (2026). Comparing AI-assisted and teacher-led reading strategy instruction in an EFL context: A quasi-experimental study. Frontiers in Education, 11. https://doi.org/10.3389/feduc.2026.1828564

Ayala-Pazmiño, M. (2023). Artificial Intelligence in Education: Exploring the Potential Benefits and Risks. 593 Digital Publisher CEIT, 8, 892–899. https://doi.org/10.33386/593dp.2023.3.1827

Braun, V., & Clarke, V. (2021). Can I use TA? Should I use TA? Should I not use TA? Comparing reflexive thematic analysis and other pattern‐based qualitative analytic approaches. Counselling and Psychotherapy Research, 21(1), 37–47.

Chan, C. K. Y., & Hu, W. (2023). Students’ voices on generative AI: Perceptions, benefits, and challenges in higher education. Education and Information Technologies. https://doi.org/10.1007/s10639-023-12217-9

Chen, C., & Leitch, A. (2024). LLMs as academic reading companions: Extending HCI through synthetic personae. ArXiv. https://arxiv.org/abs/2403.19506

Conde, M. Á., García-Pascual, R., & Rodríguez-Sedano, F. J. (2026). Expanding the lens: Multi-institutional evidence on student use of ChatGPT in higher education. Universal Access in the Information Society. https://doi.org/10.1007/s10209-026-01315-w

Creswell, J. W., & Creswell, J. D. (2018). Research design: Qualitative, quantitative, and mixed methods approaches (5th ed.). SAGE Publications.

Creswell, J. W., & Poth, C. N. (2018). Qualitative Inquiry and Research Design: Choosing Among Five Approaches (4th ed.). Sage.

Etikan, I., & Bala, K. (2017). Sampling and sampling methods. Biometrics & Biostatistics International Journal, 5(6), 215–217. https://doi.org/10.15406/bbij.2017.05.00149

Fu, Y., Wester, J., Van Berkel, N., & Hiniker, A. (2026). Self-regulated reading with AI support: An eight-week study with students. ArXiv. https://arxiv.org/abs/2602.09907

Grabe, W., & Stoller, F. L. (2020). Teaching and researching reading (3rd ed.). Routledge.

Kasneci, E., Sessler, K., & Küchemann, S. (2023). ChatGPT for good? On opportunities and challenges of large language models for education. Learning and Individual Differences, 103, 102274. https://doi.org/10.1016/j.lindif.2023.102274

Kim, H.-S., & Cha, Y. (2023). The role of AI translators on reading comprehension. 영어학, 23, 38–58.

Li, S., Noordin, N., & Yang, T. (2026). Critical Thinking as a Bridge Between Reading, Reflection, and Academic Writing: A Mixed-Methods Study of International Doctoral Candidates. Sage Open, 16(1), 21582440261415776. https://doi.org/10.1177/21582440261415778

Pan, M., Guo, K., & Lai, C. (2024). Using Artificial Intelligence Chatbots to Support English-as-a-Foreign Language Students’ Self-Regulated Reading. RELC Journal, 56. https://doi.org/10.1177/00336882241264030

QI, A. I. K. Y., YUNUS, M. M. D., & LUN, C. W. W. E. I. (2025). ENCHANCING ENGLISH READING SKILLS THROUGH AI-BASED TOOLS: A SYSTEMATIC REVIEW. Quantum Journal of Social Sciences and Humanities, 6(6), 373–390.

Rosmiyati, E., Noviati, & Jaya, A. (2025). EXPLORING THE ROLE OF ARTIFICIAL INTELLIGENCE IN ACADEMIC WRITING AMONG STUDENTS. Esteem Journal of English Education Study Programme, 9, 95–106. https://doi.org/10.31851/9zyg6g35

Sanz-Tejeda, A., Domínguez-Oller, J. C., Baldaquí-Escandell, J. M., Gómez-Díaz, R., & García-Rodríguez, A. (2026). The impact of generative AI on academic reading and writing: A synthesis of recent evidence (2023–2025). Frontiers in Education, 10. https://doi.org/10.3389/feduc.2025.1711718

Simbolon, N. E., & Mallo, I. C. (2021). Teacher talk in English classroom interaction. Journal of English Language Teaching and Linguistics, 6(2), 283–298. https://doi.org/10.21462/jeltl.v6i2.567

Valero-Ancco, V. N., Lujano-Ortega, Y., Cariapaza-Mamani, G. J., Gutierrez, F. S., & Pari-Orihuela, M. (2025). Artificial intelligence and reading comprehension in higher education: A bibliometric analysis (2006–2024). Journal of Educational and Social Research, 15(5), 75–89. https://doi.org/10.36941/jesr-2025-0162

Wei, L. (2023). Artificial intelligence in language instruction: impact on English learning achievement, L2 motivation, and self-regulated learning. Frontiers in Psychology, Volume 14-2023. https://doi.org/10.3389/fpsyg.2023.1261955

Wu, R., & Yu, Z. (2024). Do AI chatbots improve students learning outcomes? Evidence from a meta-analysis. British Journal of Educational Technology, 55(1), 10–33. https://doi.org/https://doi.org/10.1111/bjet.13334

Yu, S., Carroll, F., & Bentley, B. L. (2026). Rethinking AI literacy education in higher education: Bridging risk perception and responsible adoption. ArXiv. https://arxiv.org/abs/2603.29935

Zhang, X., Dörig, V., Cui, P., Zouhar, V., Netland, T., & Sachan, M. (2025). Harmonizing assistance: Moderating visual and textual aids in AI-enhanced textbook reading with IRead. International Journal of Artificial Intelligence in Education, 35, 3780–3812. https://doi.org/10.1007/s40593-025-00515-4