<![CDATA[Artificial intelligence (AI) is becoming increasingly common in academic reading, but its role in supporting students’ critical reading skills remains unclear. This study explored the critical reading performance of 30 pre-service English teachers taking a Critical Academic Reading course at UIN Sunan Gunung Djati Bandung. Using a qualitative exploratory design, the study applied Wallace and Wray’s Elements of Critical Reading to five reading tasks completed with AI available. The tasks focused on identifying the author’s ideology and purpose, recognizing language bias, understanding explicit and implicit meanings, and developing balanced conclusions. Students’ responses were analyzed using the adapted version of Winston-Salem State University’s critical reading criteria and grouped into four performance categories. The findings showed that many students struggled to identify ideological assumptions, evaluate bias, interpret implied meanings, and develop evidence-based, balanced conclusions, even with AI assistance available. These results show that access to AI does not necessarily mean students can use it critically. The study extends Wallace and Wray’s framework to AI-assisted reading and highlights the need to combine AI literacy with critical reading instruction. Students need to learn how to evaluate AI-generated responses, check information against textual evidence, and form their own judgments. These principles also connect with Iqra’, which emphasizes inquiry, reflection, and responsible learning. However, because the study involved only 30 students from one institution and did not include a comparison group or pretest–posttest assessment, the findings describe students’ performance rather than changes caused by AI.]]>
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