Work

The Impact of Educational LLM Agent Use on Teachers’ Curriculum Content Creation: The Chain Mediating Role of School Support and Teacher Self-Efficacy

Year: 2026

Type: article

Abstract: The application of social cognitive theory has expanded to the boundaries of human-computer interaction research. However, existing research has scarcely addressed mutual cognitive facilitation between humans and personalized educational large language model (LLM) agents. This study explored how educational LLM agents influence teachers' curriculum design and content creation, based on a sample of 464 teachers from coastal regions of China, along with semi-structured interviews with 23 participants. Quantitative analysis of the survey data revealed that the involvement of educational LLM agents positively predicts teachers' ability to create content in curriculum design. Additionally, teachers' self-efficacy mediated this relationship, while both school support and self-efficacy together created a chain mediation effect. Qualitative findings from the interviews supported the quantitative results and further highlighted individual differences and contextual nuances in teachers' use of educational LLM agents. In summary, the findings indicated that educational LLM agents positively impact teachers' curriculum design and content creation, with school support and teachers' self-efficacy acting as a chain mediator in this process.

Source: Behavioral Sciences

DOI: 10.3390/bs16010124

Authors: Huifen Xu, Minjing Chen, Minjuan Wang, Jijian Lu

Institutions: Hangzhou Normal University, Nanyang Technological University, National Institute of Education, Education University of Hong Kong

Language: English

Topic: Artificial Intelligence in Education

Subfield: Information Systems

Field: Computer Science

Domain: Physical Sciences

SDG: Quality education

Open Access status: gold

Estimated APC paid: $2,654