Enhancing academic English instruction through pedagogically integrated GenAI: Effects on students’ AI literacy and engagement

The rise of generative AI (GenAI) has made AI literacy and academic literacy critical competencies for students in higher education (HE). While the capabilities and risks of GenAI tools are widely debated, the pedagogical impact of their structured integration into the classroom remains underexplored. This study addresses this gap by investigating how GenAI-integrated topics within English for Academic Purposes (EAP) courses affect students' AI literacy and their cognitive, behavioral, and social engagement. We designed and incorporated 10 GenAI-integrated topics based on a theoretical framework encompassing AI literacy, principled communicative language teaching approach, an engagement model and self-determination theory. Employing a mixed-methods design across four universities in Hong Kong (H.K.), we collected pre- and post-questionnaires by convenience sampling from over 200 students enrolled in EAP courses and conducted semi-structured interviews with 19 participants. Results from t tests and thematic analysis of interview data revealed higher perceptions of students' self-reported AI literacy and all three forms of engagement in the post-intervention group compared to the pre-group. These findings offer practical insights for educators and researchers, providing a model for designing effective GenAI-integrated topics in EAP courses that enhance students’ autonomy and self-efficacy in learning academic English.