Students’ Attitudes and Usage Patterns of Gen-AI in Critical Reading

Abstract

This study investigates how university students use AI tools when engaging in critical reading and how these tools shape their attitudes toward academic literacy. Using a qualitative design with questionnaires, critical reading tasks, and follow-up interviews, the research focuses on 40 EFL undergraduates who completed reading activities both with and without AI assistance. The findings show that students generally perceive AI as helpful for lower-order processes such as summarizing, identifying main ideas, clarifying vocabulary, and structuring arguments, leading to increased confidence and efficiency in navigating complex texts. However, the data also indicate that AI support does not consistently enhance higher-order critical reading skills, particularly in detecting bias, evaluating arguments, and generating original, deeply reasoned interpretations, where students often perform better independently. Students tend to position AI as a supplementary aid rather than an authoritative source, revealing both emerging critical awareness and instances of over-reliance that risk superficial engagement with texts. The study concludes that thoughtfully scaffolded AI integration can strengthen critical reading only if pedagogical designs explicitly foreground metacognitive reflection, ethical awareness, and deliberate practice in advanced critical thinking, while future research should broaden samples and employ mixed methods to generalize and quantify these patterns.