Acceptance of artificial intelligence among pre-service teachers: a multigroup analysis

作者：Chengming Zhang, Jessica Schießl, Lea Plößl, F. Hofmann, Michaela Gläser‐Zikuda · 发表于：International Journal of Educational Technology in Higher Education · 年份：2023 · DOI：10.1186/s41239-023-00420-7 · 被引用次数：392 · 研究领域：Technology Adoption and User Behaviour、Motivation and Self-Concept in Sports、Gender and Technology in Education

Abstract Over the past few years, there has been a significant increase in the utilization of artificial intelligence (AI)-based educational applications in education. As pre-service teachers’ attitudes towards educational technology that utilizes AI have a potential impact on the learning outcomes of their future students, it is essential to know more about pre-service teachers’ acceptance of AI. The aims of this study are (1) to discover what factors determine pre-service teachers’ intentions to utilize AI-based educational applications and (2) to determine whether gender differences exist within determinants that affect those behavioral intentions. A sample of 452 pre-service teachers (325 female) participated in a survey at one German university. Based on a prominent technology acceptance model, structural equation modeling, measurement invariance, and multigroup analysis were carried out. The results demonstrated that eight out of nine hypotheses were supported; perceived ease of use ( β = 0.297***) and perceived usefulness ( β = 0.501***) were identified as primary factors predicting pre-service teachers’ intention to use AI. Furthermore, the latent mean differences results indicated that two constructs, AI anxiety (z = − 3.217**) and perceived enjoyment (z = 2.556*), were significantly different by gender. In addition, it is noteworthy that the paths from AI anxiety to perceived ease of use ( p = 0.018*) and from perceived ease of use to perceived usefulness ( p = 0.00...