Generative artificial intelligence (GAI) is rapidly transforming higher education, raising pedagogical, ethical, and epistemological challenges. In chemical engineering, concerns have emerged that student over-reliance on GAI may undermine the development of key skills such as problem-solving, creativity, and critical thinking. This mixed-methods study explored staff and student perspectives on the integration of GAI into chemical engineering education. Data were gathered through questionnaires (students n = 115; staff n = 17), two student focus groups, and five semi-structured staff interviews. Quantitative data were statistically analysed, and qualitative data were examined using reflexive thematic analysis. Five themes were identified: ethics, reliability and accuracy, impact on learning, pedagogical disruption, and staff use. Applying the Technological Pedagogical Content Knowledge (TPACK) model highlighted distinct staff–student differences. Students viewed GAI as a beneficial learning support, with limited concern for bias or authorship. Staff raised critical issues around reliability, transparency, and pedagogical alignment, but acknowledged GAI’s potential to streamline routine tasks such as feedback provision. Based on these insights, this study goes beyond reporting perspectives, to also propose curriculum interventions including early AI literacy and critique-based assessment. It also offers policy recommendations addressing equity, sustainability, and the responsible integration of GAI into chemical engineering education.
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