Probing Faculty Cognitions: A Systematic Review of AI Integration, Perceived Benefits, and Ethical Challenges in Chinese Primary Teacher Education
List of Authors
Dai Ziying, Syeda Rabia Tahir
Keyword
AI Integration; Teacher Education; Faculty Cognition; Perceived Benefits; Systematic Review; Sustainable Development Goal 4 (SDG 4)
Abstract
The integration of Artificial Intelligence (AI) into teacher education has emerged as a pivotal yet contested domain within Chinese higher education. This systematic literature review examines the multifaceted perceptions of AI integration among primary education faculty, with particular emphasis on the tripartite dimensions of teacher cognition, perceived benefits, and implementation challenges. Drawing upon empirical studies published between 2020 and 2024, this review synthesizes evidence regarding educators' cognitive appraisals encompassing perceived usefulness, ease of use, ethical acceptability, and emotional responses toward AI-assisted instruction. While findings reveal substantial perceived benefits including enhanced teaching efficiency, personalized learning facilitation, improved feedback mechanisms, and professional innovation identity significant challenges persist regarding algorithmic transparency, data privacy concerns, academic integrity risks, and potential threats to professional identity. The analysis highlights that teachers' cognitive frameworks serve as critical mediators, wherein positive perceptions catalyse technology adoption while ethical ambivalence and techno-stress may impede integration depth. This review contributes to the theoretical advancement of AI-mediated pedagogy in teacher education and provides evidence-based implications for curriculum reform, institutional policy development, and preservice teacher preparation in the Chinese context.