Generative Artificial Intelligence Self-Efficacy and Learning Engagement Among Special Education Teacher Trainees: A Moderated Mediation Model
Generative artificial intelligence (GenAI), known for its personalization and intelligence, is gaining traction in special education as a tool to address diverse learner needs. As future key practitioners integrating intelligent technology to promote educational equity, how special education teacher trainees effectively utilize GenAI has become a critical issue. In the context of Chinese higher education, this study employed a cross-sectional design and administered a questionnaire survey to 434 special education teacher trainees. The aim was to examine the association between their GenAI self-efficacy and learning engagement, with particular attention to the potential mediating association of problem-solving ability and the moderating role of critical thinking. The results revealed the following: GenAI self-efficacy was positively associated with learning engagement, and problem-solving ability played a mediating role in the relationship between self-efficacy and learning engagement. Moreover, critical thinking significantly moderated the relationship between self-efficacy and problem-solving ability.
Authors
- Tingzhao Wang (ORCID: https://orcid.org/0000-0002-6049-1978)
- Jin Yang (ORCID: https://orcid.org/0000-0001-6255-7937)
- Xiage Liu
- Wei Zhao
Institutions
- Xianyang Normal University (CN)
- Shaanxi Normal University (CN)
Publication Details
- Journal
- Behavioral Sciences
- Published
- 2026-03-26
- DOI
- https://doi.org/10.3390/bs16040488
- Primary Topic
- Innovative Teaching and Learning Methods
- Type
- article
- Field-Weighted Citation Impact
- 0.00