Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs
Year: 2024
Type: article
Abstract: Faculty perspectives on the use of artificial intelligence (AI) in higher education are crucial for AI’s meaningful integration into teaching and learning, yet research is scarce. This paper presents a study designed to gain insight into faculty members’ (N = 122) AI self-efficacy and distinct latent profiles, perceived benefits, challenges, use, and professional development needs related to AI. The respondents saw greater equity in education as AI’s greatest benefit, while students and faculty members’ lack of AI literacy was among the greatest challenges, with the majority interested in professional development. Latent class analysis revealed four distinct faculty member profiles: optimistic, critical, critically reflected, and neutral. The optimistic profile moderates the relationship between self-efficacy and usage. The development of adequate support services is suggested for successful and sustainable digital transformation.
Authors: Mah, Dana-Kristin, Groß, Nele
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: diamond
OpenAlex ID: W7102650455
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