This paper conducts a comparative analysis of mentoring and metacognition in education, unveiling their intricate connections. Both concepts, though seemingly disparate, prove to be interdependent within the educational landscape. The analysis showcases the dynamic interplay between mentoring and metacognition, emphasizing their reciprocal influence. Metacognition, often perceived as self-awareness and introspection, is found to complement the relational and supportive nature of mentoring. Within this context, metacognitive education within mentoring emerges as a vital component. Practical recommendations are offered for effective metacognitive training, highlighting its role in enhancing cognitive and metacognitive skills. Moreover, the paper introduces the concept of a “mentoring scaffolding system.” This system emphasizes mentor-led gradual independence for mentees, facilitating their professional and personal growth. The necessity of fostering a metacognition culture in education is a central theme. Such a culture promotes improved performance and lifelong learning. The paper suggests integrating metacognition into curricula and empowering learners as essential steps toward achieving this culture. In conclusion, this paper advocates for the integration of metacognition into mentoring and education, fostering self-awareness, independence, and adaptability. These attributes are deemed crucial for individuals navigating the challenges of the information age.

With the deep integration of artificial intelligence technology in education, the development of AI integration capabilities among pre-service teachers—as the core of future educational human resources—has become crucial for enhancing educational quality and driving digital transformation in education. Based on the AI-TPACK (Artificial Intelligence-Technological Pedagogical Content Knowledge) theoretical framework, this study employs questionnaire surveys and structural equation modeling to explore the structural characteristics, influencing factors, and formation mechanisms of AI-TPACK competencies among pre-service teachers in Chinese universities. Findings indicate that while pre-service teachers demonstrate moderately high overall AI-TPACK levels, their technical knowledge (AI-TK) and technological integration competencies (e.g., AI-TPK, AI-TCK) remain relatively weak. School technical support, technological attitudes, and technological competence significantly influence their AI-TPACK capabilities, with institutional level and teaching experience serving as important external moderating factors. Building on these findings, this paper proposes a systematic framework for developing pre-service teachers' AI integration capabilities from a human resource development perspective. This framework encompasses four dimensions: curriculum optimization, practice enhancement, resource support, and policy guidance. It aims to provide theoretical foundations and practical pathways for pre-service teacher training and teacher human resource development in higher education institutions.