Changes in Teacher Evaluation Standards in the Era of Artificial Intelligence: Emerging Trends and Future Directions

Abstract

Artificial intelligence (AI) and generative AI have developed rapidly in recent years, and now many schools have begun to explore their applications in education. As AI tools are gradually incorporated into teaching and learning activities for design, assessment, feedback and personalisation, the concept of a professional teacher is also evolving. Most of the existing teacher evaluation systems have been developed in educational settings where teachers are the main sources of knowledge and classroom instruction is the focus of evaluation. However, recent developments suggest that such frameworks may no longer be fully in line with the demands of teaching in AI-assisted learning environments. Collect recent research published from 2021 to 2026 around the world on how teachers' evaluation standards are changing in the face of AI-driven changes in education, in conjunction with foreign policy papers and new-era competency systems. Based on thematic reviews of empirical studies, policy reports and conceptual discussions, the five main trends have been identified: a change from digital literacy to AI literacy; the appearance of human-AI collaborative teaching; an increase in the demand for ethical responsibility; a transition from outcome-oriented to process-oriented evaluation; and an expansion in focus on students' AI literacy. Based on the above results, a multi-dimensional system of teacher appraisal has been proposed. The paper proposes that the future evaluation system will move beyond the traditional metrics of teaching effectiveness to consider teachers' abilities in critically using AI technology and making ethical, data-driven choices for students in the era of AI.