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ORIGINAL RESEARCH article

Front. Artif. Intell.
Sec. AI for Human Learning and Behavior Change
Volume 7 - 2024 | doi: 10.3389/frai.2024.1497705
This article is part of the Research Topic Methodology for Emotion-Aware Education Based on Artificial Intelligence View all 3 articles

The Impact of Pedagogical Beliefs on the Adoption of Generative AI in Higher Education. Predictive model from UTAUT2

Provisionally accepted
Julio C. Almenara Julio C. Almenara 1Antonio Palacios-Rodríguez Antonio Palacios-Rodríguez 1*María I. Loaiza María I. Loaiza 2Paola Salomé Andrade-Abarca Paola Salomé Andrade-Abarca 2
  • 1 Sevilla University, Seville, Andalucia, Spain
  • 2 Universidad Técnica Particular de Loja, Loja, Loja, Ecuador

The final, formatted version of the article will be published soon.

    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. Con formato: Español (España)

    Keywords: artificial intelligence, higher education, professor, Educational Technology, UTAUT2 Alaminos, A., Francés, f.

    Received: 17 Sep 2024; Accepted: 07 Oct 2024.

    Copyright: © 2024 Almenara, Palacios-Rodríguez, Loaiza and Andrade-Abarca. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

    * Correspondence: Antonio Palacios-Rodríguez, Sevilla University, Seville, 41 004, Andalucia, Spain

    Disclaimer: All claims expressed in this article are solely those of the authors and do not necessarily represent those of their affiliated organizations, or those of the publisher, the editors and the reviewers. Any product that may be evaluated in this article or claim that may be made by its manufacturer is not guaranteed or endorsed by the publisher.