Generative Artificial Intelligence Self-Efficacy and Learning Engagement Among Special Education Teacher Trainees: A Moderated Mediation Model
Year: 2026
Type: article
Study design: Observational Study
Abstract: 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.
Source: Behavioral Sciences
DOI: 10.3390/bs16040488
Authors: Xiage Liu, Juan Yang, Wei Zhao, Tingzhao Wang
Institutions: Xianyang Polytechnic Institute, Shaanxi Normal University
Language: English
Subfield: Information Systems
Field: Computer Science
Domain: Physical Sciences
SDG: Quality education
Open Access status: gold
Estimated APC paid: $2,654
OpenAlex ID: W7140714430
