Determinants of AI Use in University Teachers: The Role of Leadership, Teaching Concerns, and Constructivist Pedagogical Beliefs

This study examines the determinant factors influencing artificial intelligence (AI) adoption among university teachers and its impact on teacher leadership and concerns. Through a quantitative cross-sectional study involving 452 professors from six public and private universities in northern Peru,...

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Main Authors: Benicio Gonzalo Acosta-Enriquez, Marco Agustin Arbulu Ballesteros, Maria de los Angeles Guzman Valle, Jahaira Eulalia Morales Angaspilco, Luz Elvira Blanco-García, Giannina Campoverde Ventura, Jhon Dany Castañeda Requejo, Maribel Carranza Torre
Format: Article
Language:English
Published: Wiley 2025-01-01
Series:Human Behavior and Emerging Technologies
Online Access:http://dx.doi.org/10.1155/hbe2/4834893
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Summary:This study examines the determinant factors influencing artificial intelligence (AI) adoption among university teachers and its impact on teacher leadership and concerns. Through a quantitative cross-sectional study involving 452 professors from six public and private universities in northern Peru, the research tested six hypotheses regarding the relationships between attitudes toward AI, constructivist pedagogical beliefs, facilitating conditions, and teaching modality. Data were collected via validated instruments and analyzed via structural equation modeling (PLS-SEM). The results revealed that attitudes toward AI (β=0.529, p<0.001) and constructivist pedagogical beliefs (β=0.253, p<0.01) significantly influence AI adoption, whereas facilitating conditions have no significant effect. The study also revealed that AI use strongly impacts teacher leadership (β=0.711, p<0.001) and teacher concerns (β=0.597, p<0.001). However, teaching modality did not significantly moderate the relationship between attitudes and AI use. The model showed robust explanatory power, with AI use explaining 50.5% of the variance in teacher leadership and 35.6% in teacher concerns. These findings contribute to understanding the complex dynamics of AI adoption in higher education and provide valuable insights for developing effective institutional strategies for AI integration in educational settings.
ISSN:2578-1863