Evaluation Framework and Descriptors for Teachers’ AI Competence in China

教师人工智能能力评价标准研究

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The rapid integration of artificial intelligence (AI) into educational practice underscores the urgent need for teacher competency frameworks that are both globally informed and locally adaptable. Building on the UNESCO AI Competency Framework for Teachers, this study proposes a China-adapted AI competency framework for primary and middle school teachers that responds to national curriculum standards, policy priorities, and the distinctive characteristics of the Chinese educational technology ecosystem. The framework comprises ten competency dimensions, including core UNESCO-aligned constructs—Human-Centred Mindset, Ethics of AI, AI Knowledge and Application, AI Pedagogy, and AI for Professional Growth—as well as five context-specific extensions: National Curriculum Alignment, Integration with the Chinese EdTech Ecosystem, Managing Academic Integrity, Bridging the Regional Digital Divide, and Moral and Values Education (德育).

To operationalise these competencies, the study develops a weighted evaluation rubric with four proficiency levels and introduces a series of project-based assessment tasks designed to capture authentic teaching practices. These tasks evaluate teachers’ capacity to integrate AI in ethically responsible and pedagogically meaningful ways, design curriculum-aligned lessons and assessments, address learner diversity, mitigate AI-related academic misconduct, and foster students’ digital citizenship and moral development. Particular emphasis is placed on reflective practice, educational equity, and alignment with national initiatives such as the 双减 policy. Overall, the proposed framework offers a systematic, practice-oriented approach to teacher AI competency development in China, while contributing to broader international discussions on contextualising global AI education frameworks.

Thematic analysis of semi-structured interviews with eight teachers identified six themes: practical AI competency, AI-supported learning, ethics and academic integrity, Chinese educational context, professional development, and framework improvement. Teachers prioritised practical AI use, pedagogy, ethical judgement, curriculum alignment, and critical evaluation over advanced technical knowledge. They also highlighted AI’s value for personalised learning alongside concerns about misinformation, privacy, bias, dependency, academic misconduct, and unequal access. The findings support a simplified, differentiated, and context-sensitive framework, reinforced by practical, case-based, and subject-specific professional development.