Journal ArticleParallel publicationPublished versionDOI: 10.48548/pubdata-2463

Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs

Chronological data

Date of first publication2024-10-17
Date of publication in PubData 2025-10-30

Language of the resource

English

Related external resources

Variant form of DOI: 10.1186/s41239-024-00490-1
Mah, D., & Groß, N. (2024). Artificial intelligence in higher education: exploring faculty use, self-efficacy, distinct profiles, and professional development needs. International Journal of Educational Technology in Higher Education, 21(1), Article 58
Published in ISSN: 2365-9440
International Journal of Educational Technology in Higher Education

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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.

Keywords

AI Self-efficacy; AI Literacy; Artificial intelligence in Higher Education; Faculty Perspective; Digital Transformation; Latent Class Analysis

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DDC

006 :: Spezielle Computerverfahren
378 :: Hochschulbildung

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Research