Education faculty experiences and interpretations of generative AI's impact on scholarship and higher education: a mixed-methods study

Purpose Research on generative AI (GenAI) in higher education has largely focused on teaching. A gap remains in understanding its impact on teaching and research among education faculty who shape pedagogy and prepare future educators. This study explored how faculty in colleges and schools of education interpret GenAI's influence on their scholarship and the broader higher education landscape. Design/methodology/approach A convergent mixed-method design was employed. Sixty-nine faculty from 15 higher education institutions in Florida completed an online survey, and a sub-sample of eight GenAI users participated in semi-structured interviews. Quantitative and qualitative data were analyzed separately and integrated to identify convergence, divergence and complementarity. Findings Convergence emerged around efficiency gains and ethical concerns, with participants reporting time-saving benefits in lesson planning, assessment design and literature review processes. Qualitative findings complemented these results by revealing selective integration into teaching, research workflows and student support practices not captured in the survey. Partial convergence appeared in innovation, teaching quality and student engagement. Divergence emerged between users and non-users, with users describing more experience-based use and non-users emphasizing potential risks. Participants highlighted concerns about hallucinations, academic integrity and limited institutional guidance. Originality/value Findings suggest that education faculty conceptualized GenAI as a double-edged technology that enhances efficiency while introducing ethical and pedagogical tensions. The study captured a transitional phase in which faculty are moving beyond experimentation toward more intentional integration that is reshaping scholarly workflows and roles. Future research should examine how institutional supports and increasingly agentic AI capabilities may influence practice and teacher–student relationship.