The impact of pedagogical beliefs on the adoption of generative AI in higher education: predictive model from UTAUT2

Artificial Intelligence in Education (AIEd) offers advanced tools that can personalize learning experiences and enhance teachers’ research capabilities. This paper explores the beliefs of 425 university teachers regarding the integration of generative AI in educational settings, utilizing the UTAUT2...

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Detalles Bibliográficos
Autores: Cabero Almenara, Julio, Palacios Rodríguez, Antonio de Padua, Loaiza Aguirre, María Isabel, Andrade Abarca, Paola Salomé
Tipo de recurso: artículo
Estado:Versión aceptada para publicación
Fecha de publicación:2024
País:España
Institución:Universidad de Sevilla (US)
Repositorio:idUS. Depósito de Investigación de la Universidad de Sevilla
OAI Identifier:oai:idus.us.es:11441/163784
Acceso en línea:https://hdl.handle.net/11441/163784
https://doi.org/10.3389/frai.2024.1497705
Access Level:acceso abierto
Palabra clave:Artificial intelligence
Higher education
Professor
Educational technology
UTAUT
Descripción
Sumario:Artificial Intelligence in Education (AIEd) offers advanced tools that can personalize learning experiences and enhance teachers’ research capabilities. This paper explores the beliefs of 425 university teachers regarding the integration of generative AI in educational settings, utilizing the UTAUT2 model to predict their acceptance and usage patterns through the Partial Least Squares (PLS) method. The findings indicate that performance expectations, effort expectancy, social influence, facilitating conditions, and hedonic motivation all positively impact the intention and behavior related to the use of AIEd. Notably, the study reveals that teachers with constructivist pedagogical beliefs are more inclined to adopt AIEd, underscoring the significance of considering teachers’ attitudes and motivations for the effective integration of technology in education. This research provides valuable insights into the factors influencing teachers’ decisions to embrace AIEd, thereby contributing to a deeper understanding of technology integration in educational contexts. Moreover, the study’s results emphasize the critical role of teachers’ pedagogical orientations in their acceptance and utilization of AI technologies. Constructivist educators, who emphasize student-centered learning and active engagement, are shown to be more receptive to incorporating AIEd tools compared to their transmissive counterparts, who focus on direct instruction and information dissemination. This distinction highlights the need for tailored professional development programs that address the specific beliefs and needs of different teaching philosophies. Furthermore, the study’s comprehensive approach, considering various dimensions of the UTAUT2 model, offers a robust framework for analyzing technology acceptance in education.