Intelligent Tutoring System for Teachers' Digital Competence Improvement in China: A Systematic Literature Review

Abstract

This paper conducts a systematic review of quantitative empirical studies from 2020 to 2025 on the integration of teacher digital competence enhancement with intelligent tutoring systems (ITS). A total of 84 high-quality academic articles were selected based on the PRISMA process. The focus is on the mechanisms through which diagnostic-push ITS influence teachers' digital skill development, with analyses grounded in key theories such as DigCompEdu, TPACK, and the Technology Acceptance Model. Central issues including teachers' technological self-efficacy, classroom technology integration, and instructional innovation are explored. The study found that most intelligent tutoring systems enhance teachers' digital adaptability in instructional design and classroom operations by leveraging feedback functions within learning management systems, artificial intelligence recommendations, and personalized intervention strategies. Notably, there was significant improvement in teachers' digital self-efficacy. Additionally, school organizational culture and information and communication technology (ICT) resources emerged as important moderating variables influencing the effectiveness of these systems. This paper constructs a causal model of “platform-capability-performance,” providing theoretical guidance and practical suggestions for cultivating teachers' capabilities in a digital educational environment. It also identifies the design flaws of current intelligent tutoring systems and future research topics, emphasizing the importance of localization adjustments and long-term evaluation.