Generative Artificial Intelligence and Professional Development for University Faculty: A Systematic Review
DOI:
https://doi.org/10.5281/zenodo.24120289Keywords:
generative artificial intelligence, teacher professional development, higher educationAbstract
The objective of this systematic review was to analyze the scientific evidence on the role of generative artificial intelligence in the professional development of higher education faculty. To this end, the PRISMA 2020 statement was followed as a reporting guide, structuring the process in four phases: identification, screening, eligibility, and inclusion. The search was conducted on September 29, 2026, in Scopus, ScienceDirect, and Redalyc, using descriptors combined with Boolean operators. After applying inclusion and exclusion criteria, the final corpus consisted of 35 studies. The findings show that generative AI is primarily used for planning, content generation, feedback, and evaluation, always under human supervision. Five interrelated dimensions were identified: faculty perceptions and practices, AI skills and literacy, assessment and academic integrity, trust and ethics, and curriculum and workload. Adoption depends not only on perceived usefulness but also on motivational, pedagogical, and institutional conditions. It is concluded that the effective integration of generative AI into teacher professional development is a multidimensional process that requires continuous, differentiated, and progressive training.
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