Exploring English Education Students’ Experiences in AI-Supported Reading Tasks for HOTS Development
Authors
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Rizky Sangaji
Universitas Kuningan
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Gadis Pujawiyanti
Universitas Kuningan
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Nani Ronsani Thamrin
Universitas Kuningan
https://orcid.org/0000-0002-6130-4206
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Wulan Rahmatunnisa
Universitas Kuningan
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Erlan Darmawan
Universitas Kuningan
https://orcid.org/0000-0002-8939-3394
DOI:
https://doi.org/10.36312/jolls.v6i2.4650Keywords:
Artificial intelligence, EFL reading, Higher order thingking, Cognitive scaffoldingAbstract
This study addresses the limited engagement of EFL students in Higher-Order Thinking Skills (HOTS) during reading activites, particularly their difficulty in moving beyond literal comprehension toward analysis, evaluation, and creation. At the same time, the growing use of Artificial Intelligence (AI) in language learning offers potential as a cognitive scaffold; however, its pedagogical role in fostering HOTS in EFL reading remains underexplored, especially in contexts where AI is often used merely as an answer provider. Therefore, this study aims to explore English Education students’ experiences in developing HOTS through AI-supported reading activities at Universitas Kuningan. Using a qualitative case study design, the study involved 31 students enrolled in an intensive reading course. Data were collected through reading tasks conducted with and without AI assistance, classroom observations, and semi-structured interviews, and were analyzed using reflexive thematic analysis. The findings show that without AI support, students predominantly demonstrated literal comprehension and relied on copying textual information. In contrast, when AI was used as a reflective tool, students actively compared responses, evaluated arguments, and reconstructed their understanding, indicating the development of analyzing (C4), evaluating (C5), and creating (C6) processes. AI functioned as a cognitive scaffold that promoted deeper cognitive engagement; however, challenges such as overreliance on AI and concerns about response validity were also identified. The study concludes that AI can support HOTS development in EFL reading only when it is integrated reflectively and pedagogically, rather than used as an instant answer generator, and highlights implications for designing more effective AI-supported reading instruction in higher education contexts.
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