The constructing and empirical research on primary and secondary school teachers' digital competencies in the age of artificial intelligence

The research employed a mixed-method approach, combining the Analytic Hierarchy Process (AHP) and fuzzy comprehensive evaluation. Data was collected from 30 teachers and a panel of 30 experts to construct and validate a digital competency model. This robust methodology ensured both objective weighting of indicators and a nuanced assessment of teacher performance.

Building upon the TPACK framework, the study constructed a digital competency model tailored for primary and secondary school teachers in the AI era. This model identifies four primary indicators: Digital Technology Application (C1), Innovative Instructional Design (C2), Digital Ethics and Social Responsibility (C3), and Lifelong Learning and Professional Development (C4), each further broken down into secondary indicators. The model emphasizes not just tool mastery but also algorithmic literacy, data-driven decision-making, and digital ethics, reflecting the evolving demands of intelligent education.

The model's primary indicators are C1: Digital Technology Application, C2: Innovative Teaching Design, C3: Digital Ethics and Social Responsibility, and C4: Lifelong Learning and Professional Development. Secondary indicators include mastery of intelligent educational tools (C11), data analysis and feedback mechanisms (C12), technology integration and adaptability (C13), student-centered learning experience design (C21), interdisciplinary integration (C22), virtual and reality-integrated teaching strategies (C23), cultivation of digital citizenship literacy (C31), equity and inclusivity (C32), digital information security management (C33), continuous self-reflection and improvement (C41), updating of cutting-edge knowledge in digital technology (C42), and participation in professional communities and knowledge sharing (C43).

To address identified gaps, the study provides specific recommendations for enhancing teachers' digital competencies. These include structured training, fostering professional learning communities, and integrating digital ethics into curriculum and teacher development programs.

Cultivation of Digital Technology Application Skills

Through project-based learning and practice-oriented training, teachers can apply digital tools in actual teaching contexts. Utilizing Learning Management Systems (LMS) and fostering professional learning communities are crucial for sharing successful experiences and continuously optimizing technical application skills. Schools should establish robust technical support systems and collect feedback to refine training content.

Enhancement of Innovative Teaching Design Capabilities

By introducing Design Thinking and encouraging self-reflection and peer review, teachers can leverage AI for creative instructional practices. Advocating project-based learning stimulates innovative consciousness and promotes interdisciplinary integration, enabling teachers to design diverse tasks and learning environments that increase student engagement and creativity.

Emphasis on Digital Ethics and Social Responsibility

Digital ethics training through case analysis and simulations will equip teachers to make wise choices regarding data privacy, network security, and information accuracy. Clear digital ethics guidelines should be established, and regular education should enhance ethical awareness, cultivating students' digital citizenship. Biannual iteration of ethical scenarios within professional communities will keep content aligned with emerging AI risks.

Support for Lifelong Learning and Professional Development

Schools should foster learning organizations, encouraging continuous on-the-job learning. Online learning platforms, research activities, and workshops can broaden horizons. Educational departments must provide funding and resources to motivate active participation in digital education research and practice, supporting continuous professional growth.