EMPOWERING ESL STUDENTS WITH AI: ENHANCING ACADEMIC READING AND AUTONOMY
DOI:
https://doi.org/10.5281/zenodo.21341913Keywords:
Academic Reading, Artificial Intelligence, ESL, Learner Autonomy, Mixed-Methods, Research LiteracyAbstract
Academic reading is a continuous challenge for English as a Second Language (ESL) students in higher education because they need to understand unfamiliar academic language while also acquiring the research-literacy skills necessary to read and work independently with academic texts. The current study conducted an eight-week, classroom-based intervention that involved 64 ESL undergraduate and postgraduate students to four AI-based literature and reading-support tools (Connected Papers, Consensus, Scholarcy, and SciSpace) in a scaffolded task sequence that began with literature discovery and ended with critical synthesis. The research was designed as an explanatory sequential mixed methods design, which included pre–post academic reading test, learner-autonomy questionnaire, research-literacy checklist, semi-structured interviews, and classroom observation. Students' reading scores increased statistically significantly (M = 62.4 to M = 76.1, d ≈ 1.48) and their self-reported autonomy scores increased statistically significantly (t(63) = 6.42, p < .001), with the greatest gains in resource selection and inference. The results indicate that AI tools for discovery and summarization can be a valuable addition to reading instruction and learner autonomy when integrated into an explicit and instructional design. Future studies can provide a transferable task sequence for ESL teachers who want to shift their students from ad hoc use of AI to systematic, autonomy-oriented academic reading instruction.
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Copyright (c) 2026 Muhammad Nadeem Anwar, Seemab Jamil Ghouri, Zainab Abid (Author)
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