Purpose This study examines how Generative Artificial Intelligence (GenAI) tools shape students' perceptions and acceptance in fashion product development courses, comparing mentor-supported team-based and individual learning contexts. It aims to inform educators on effective strategies for integrating GenAI to enhance Artificial Intelligence literacy and career readiness in creative disciplines. Design/methodology/approach A quasi-experimental mixed-methods design was implemented across two undergraduate courses. Students used ChatGPT 3.5 (text generation) and Bing Image Creator (visual ideation) in experiential assignments guided by the IDEE framework and social constructivist principles. Quantitative data were analyzed using ANCOVA to compare post-test perceptions between mentor-supported team and individual groups, controlling for pre-test scores. Thematic analysis of student reflections provided qualitative insights into perceptions of GenAI's usefulness, availability, and ethical implications. Findings Students in mentor-supported teams reported higher perceptions of career readiness, learning support, and availability for text-based GenAI compared to those working individually. While image-based GenAI supported ideation, students expressed concerns about reliability and visual fidelity. Qualitative data reinforced that mentorship and collaboration increased confidence and fostered reflective engagement with GenAI. Originality/value Integrating UTAUT, social constructivism, and the IDEE framework, this study offers one of the first empirical examinations of GenAI use in fashion education. It highlights how structured, mentor-supported collaboration promotes meaningful GenAI adoption and provides a model for embedding ethical, experiential learning in creative curricula.
Browning-Samoni et al. (2026) studied this question.