大学教师使用人工智能的决定因素:领导的作用、教学关注和建构主义教学信念

IF 4.3 Q1 PSYCHOLOGY, MULTIDISCIPLINARY
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
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引用次数: 0

摘要

本研究探讨了影响大学教师采用人工智能的决定因素及其对教师领导和关注的影响。通过一项涉及秘鲁北部六所公立和私立大学的452名教授的定量横断面研究,该研究测试了关于对人工智能的态度、建构主义教学信念、促进条件和教学方式之间关系的六种假设。通过验证的仪器收集数据,并通过结构方程建模(PLS-SEM)进行分析。结果显示,学生对人工智能的态度(β = 0.529, p <;0.001)和建构主义教学信念(β = 0.253, p <;0.01)显著影响人工智能采用率,而便利条件无显著影响。研究还发现,人工智能的使用对教师领导力有很强的影响(β = 0.711, p <;0.001)和教师关注点(β = 0.597, p <;0.001)。然而,教学方式并没有显著调节态度与人工智能使用之间的关系。该模型显示出强大的解释力,人工智能的使用解释了50.5%的教师领导差异和35.6%的教师关注差异。这些发现有助于理解高等教育中人工智能采用的复杂动态,并为制定有效的教育环境中人工智能整合的制度战略提供有价值的见解。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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, 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.

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来源期刊
Human Behavior and Emerging Technologies
Human Behavior and Emerging Technologies Social Sciences-Social Sciences (all)
CiteScore
17.20
自引率
8.70%
发文量
73
期刊介绍: Human Behavior and Emerging Technologies is an interdisciplinary journal dedicated to publishing high-impact research that enhances understanding of the complex interactions between diverse human behavior and emerging digital technologies.
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