A Study on Teachers’ Willingness to Use Generative AI Technology and Its Influencing Factors: Based on an Integrated Model

Haili Lu, Lin He (), Hao Yu, Tao Pan () and Kefeng Fu
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Haili Lu: Faculty of Education, Shaanxi Normal University, Xi’an 710062, China
Lin He: Faculty of Education, Shaanxi Normal University, Xi’an 710062, China
Hao Yu: Faculty of Education, Beijing Normal University, Beijing 100875, China
Tao Pan: Youth League Committee, Weinan Normal University, Weinan 714099, China
Kefeng Fu: Faculty of Education, Shaanxi Normal University, Xi’an 710062, China

Sustainability, 2024, vol. 16, issue 16, 1-18

Abstract: The development of new artificial intelligence-generated content (AIGC) technology creates new opportunities for the digital transformation of education. Teachers’ willingness to adopt AIGC technology for collaborative teaching is key to its successful implementation. This study employs the TAM and TPB to construct a model analyzing teachers’ acceptance of AIGC technology, focusing on the influencing factors and differences across various educational stages. The study finds that teachers’ behavioral intentions to use AIGC technology are primarily influenced by perceived usefulness, perceived ease of use, behavioral attitudes, and perceived behavioral control. Perceived ease of use affects teachers’ willingness both directly and indirectly across different groups. However, perceived behavioral control and behavioral attitudes only directly influence university teachers’ willingness to use AIGC technology, with the impact of behavioral attitudes being stronger than that of perceived behavioral control. The empirical findings of this study promote the rational use of AIGC technology by teachers, providing guidance for encouraging teachers to actively explore the use of information technology in building new forms of digital education.

Keywords: AIGC technology; influencing factors; willingness to use; TAM TPB model (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2024
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