Influence of Pedagogical Beliefs and Perceived Trust on Teachers’ Acceptance of Educational Artificial Intelligence Tools

Abstract

Advancements in artificial intelligence (AI) have stimulated the development of educational AI tools (EAIT). EAITs intelligently assist teachers in formulating better pedagogical decisions or actions for their students. However, teachers are hardly integrating EAITs, and little is known about their perceptions of EAITs. This study seeks to identify human factors that encourage or restrict teachers’ acceptance of EAITs. We propose a revised technology acceptance model incorporating teachers’ pedagogical beliefs and perceived trust in EAITs. Survey data were collected from 215 teachers in South Korea and analyzed using structural equation modeling. The results indicate that teachers with constructivist beliefs are more likely to integrate EAITs than teachers with transmissive orientations. Furthermore, perceived usefulness, perceived ease of use, and perceived trust in EAITs are determinants to be considered when explaining teachers’ acceptance of EAITs. Among them, the most influential determinant of predicting their acceptance was found to be how easily the EAIT is constructed. Significant implications for researchers and stakeholders regarding the development and integration of EAITs are discussed.

Disclosure statement

No potential competing interest was reported by the authors.

Additional information

Funding

This work was supported by the National Research Foundation (NRF), Korea, under the project BK21 FOUR.

Notes on contributors

Seongyune Choi

Seongyune Choi is a Ph.D. student in the Department of Computer Science and Engineering at Korea University in Seoul, South Korea. His research interests include computer science education, educational technologies, and artificial intelligence in education.

Yeonju Jang

Yeonju Jang is a Ph.D. student in the Department of Computer Science and Engineering at Korea University in Seoul, South Korea. Her research interests include machine learning and deep learning applications in the field of education to better understand students and assist their learning.

Hyeoncheol Kim

Hyeonchel Kim is a professor in the Department of Computer Science and Engineering at Korea University in Seoul, South Korea. He received his Ph.D. in CISE from the University of Florida in 1998. His research interests include machine learning algorithms and AI education.