Cabero-Almenara Julio, Palacios-Rodríguez Antonio, Loaiza-Aguirre María Isabel, Andrade-Abarca Paola Salomé
Department of Didactics and Educational Organisation, University of Seville, Seville, Spain.
Department of Economics and Business Sciences, Private Technical University of Loja, Loja, Ecuador.
Front Artif Intell. 2024 Oct 17;7:1497705. doi: 10.3389/frai.2024.1497705. eCollection 2024.
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.
教育中的人工智能（AIEd）提供了先进的工具，可以使学习体验个性化并增强教师的研究能力。本文探讨了425名大学教师对生成式人工智能在教育环境中整合的看法，利用UTAUT2模型通过偏最小二乘法（PLS）预测他们的接受度和使用模式。研究结果表明，绩效期望、努力期望、社会影响、促进条件和享乐动机都对与使用AIEd相关的意图和行为产生积极影响。值得注意的是，该研究表明，具有建构主义教学信念的教师更倾向于采用AIEd，这突出了考虑教师态度和动机对于在教育中有效整合技术的重要性。这项研究为影响教师接受AIEd的因素提供了有价值的见解，从而有助于更深入地理解教育背景下的技术整合。此外，该研究的结果强调了教师教学取向在其接受和使用人工智能技术方面的关键作用。与注重直接教学和信息传播的传统教育者相比，强调以学生为中心的学习和积极参与的建构主义教育者被证明更愿意采用AIEd工具。这种差异凸显了需要制定量身定制的专业发展计划，以满足不同教学理念的特定信念和需求。此外，该研究的综合方法考虑了UTAUT2模型的各个维度，为分析教育中的技术接受度提供了一个强大的框架。
