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

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.

Publication Details

Journal
PubData
Published
2024-10-17
DOI
https://doi.org/10.48548/pubdata-2463
Primary Topic
Artificial Intelligence in Healthcare and Education
Type
article
Field-Weighted Citation Impact
0.00
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article

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

PubData
Artificial Intelligence in Healthcare and Education
article

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

article en

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.

PubData
Quality Education
Openalex Percentile: Top 58%
Artificial Intelligence in Healthcare and Education
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