Generative Artificial Intelligence Self-Efficacy and Learning Engagement Among Special Education Teacher Trainees: A Moderated Mediation Model

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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.

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Liu, X., Yang, J., Zhao, W., & Wang, T. (2026). Generative Artificial Intelligence Self-Efficacy and Learning Engagement Among Special Education Teacher Trainees: A Moderated Mediation Model. Behavioral Sciences, 16(4). https://doi.org/10.3390/bs16040488

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