Zhang C, Schießl J, Plößl L, Hofmann F, Gläser-Zikuda M (2023)
Publication Language: English
Publication Type: Journal article, Online publication
Publication year: 2023
DOI: 10.1186/s41239-023-00420-7
Open Access Link: https://educationaltechnologyjournal.springeropen.com/articles/10.1186/s41239-023-00420-7
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 = 0.002**) are moderated by gender. This study confirms the determinants influencing the behavioral intention based on the Technology Acceptance Model 3 of German pre-service teachers to use AI-based applications in education. Furthermore, the results demonstrate how essential it is to address gender-specific aspects in teacher education because there is a high percentage of female pre-service teachers, in general. This study contributes to state of the art in AI-powered education and teacher education.
APA:
Zhang, C., Schießl, J., Plößl, L., Hofmann, F., & Gläser-Zikuda, M. (2023). Acceptance of artifcial intelligence among pre-service teachers: a multigroup analysis. International Journal of Educational Technology in Higher Education. https://dx.doi.org/10.1186/s41239-023-00420-7
MLA:
Zhang, Chengming, et al. "Acceptance of artifcial intelligence among pre-service teachers: a multigroup analysis." International Journal of Educational Technology in Higher Education (2023).
BibTeX: Download