Integrating AI into Teacher Qualification Exams

In April 2026, five departments, including the Ministry of Education, jointly issued the “AI + Education Action Plan,” proposing to include artificial intelligence (AI) in teacher qualification exams and certification.

This initiative clearly signals that future teachers must not only impart knowledge but also adeptly use intelligent tools and engage in human-machine collaborative teaching.

The action plan emphasizes leveraging AI to empower teachers throughout the educational process, from pre-class to post-class. It aims to strengthen the application of intelligent teaching systems, reduce teachers’ workloads, assist in homework management, promote intelligent grading, and provide tutoring. AI will also analyze classroom teaching behaviors to help improve teaching quality.

Experts believe that incorporating AI application theory into teacher qualification exams and certification will systematically enhance teachers’ theoretical literacy regarding AI skills and ethical norms, guiding students to use AI products correctly throughout the educational process. However, the actual integration of AI technology in education and its potential risks will require ongoing observation, evaluation, and optimization in future teaching practices.

Policy Guidance

National Application Norms

In a primary school in Beijing, a fifth-grade math teacher, Mr. Liu, exemplifies the implementation of the action plan. After class each day, he uses an AI learning machine to assess the students’ grasp of the day’s math concepts, generating detailed data analysis reports that highlight each student’s weaknesses without manual grading. For instance, some students struggle with geometry application problems, while others frequently make mistakes in calculation steps.

“Previously, grading assignments and analyzing student performance took at least two hours daily. Now, with AI assistance, I can save that time and focus more on the students,” Mr. Liu stated. He uses the saved time to analyze learning data and address students’ emotional needs. For students who work hard but progress slowly, he writes targeted encouraging comments and rewards them with campus currency to acknowledge their achievements.

“Each of the 40 children in my class is a unique individual. I understand their personalities and experiences, which is a level of emotional care that AI cannot provide,” Mr. Liu clarified, emphasizing the boundaries of AI use—AI handles error correction and data statistics, while teachers focus on guiding values and emotional support.

Notably, in November 2025, the Ministry of Education’s Expert Advisory Committee on Teacher Development released the “Guidelines for the Application of Generative AI by Teachers (Version 1),” marking the first national application norms specifically for teachers regarding generative AI, indicating a systematic entry of generative AI into the education sector.

From a teacher’s perspective, the goal of educational activities in the AI era is human-machine collaboration, promoting deep integration of technology and educational scenarios. Students can engage in personalized learning based on their characteristics, enhancing their learning efficiency and core competencies. Additionally, AI-supported immediate feedback and adaptive learning paths help students transition from passive reception to active exploration, fostering their independent learning abilities.

Reshaping Competencies

Strengthening the Foundation of the Teaching Profession

Cai Hailong, Deputy Dean of the Institute of Education Policy and Law at Capital Normal University, believes that integrating AI into teacher qualification exams is a necessary response to the basic competency requirements for teachers in the intelligent era. The teacher qualification exam essentially serves as a baseline evaluation of teaching ability. In regions where intelligent teaching has become the norm, the focus is not on complex algorithms or programming skills but on whether teachers can appropriately and reasonably apply AI in teaching contexts while possessing basic ethical awareness.

“These components will not increase teachers’ exam preparation burden; instead, they will help teachers master core tools that can alleviate future professional workloads, thereby strengthening the foundation of the teaching profession in the intelligent era,” Cai said.

Yao Jinjun believes that by including AI in teacher qualifications, teachers can enhance their ability to identify ethical risks associated with educational AI products, becoming the first line of defense for students against potential harms such as inappropriate AI use, personal data collection, and algorithmic bias.

“Incorporating AI teaching into the future knowledge structure and qualification certification system for teachers fundamentally reshapes the logic of teacher training, creating an integrated system from initial training to qualification admission and throughout their career. The goal is not merely to train users of AI tools but to cultivate educators who can navigate human-machine collaboration, uphold educational values, and possess ethical judgment capabilities,” Cai stated.

Cai suggests a three-phase approach for training. In the initial training phase, teacher education should reconstruct the curriculum to systematically embed AI literacy into core courses. Topics such as human-machine collaborative teaching design, AI educational ethics, data compliance, and privacy protection should transition from elective to mandatory core courses. It is crucial to establish the fundamental concept of human-machine collaboration early in training, ensuring that technology serves the fundamental task of moral education.

In the admission phase, teacher qualification certification should shift from knowledge memorization to situational competency. The focus should be on assessing the ability to design human-machine collaborative teaching, critically evaluate AI content, and respond to educational ethics through case analysis and situational simulations. This ensures that candidates can identify AI errors and value risks, design suitable teaching plans, and uphold privacy protection and educational responsibilities from the outset.

In the professional development phase, a continuous training and evaluation mechanism should be established throughout the career lifecycle. Human-machine collaboration literacy and technical scrutiny capabilities should be included in induction training, continuing education, and professional title evaluation systems, with assessments centered on educational outcomes to avoid falling into purely technical metrics.

Support Mechanisms

Layered Support and Encouragement of Risk-Taking

Experts emphasize that merely including AI theoretical knowledge in teacher qualification exams does not guarantee effective application in real teaching scenarios. Without ongoing post-training (teacher development), classroom observation assessments, and accountability mechanisms, there may be cases of “passing the exam but not using, fearing to use, or misusing” AI.

“Integrating AI into teacher qualifications requires establishing supportive, layered mechanisms and a tolerance for errors, which is essential for sustainable reform,” Cai believes. Specifically, for newly hired teachers, the focus should be on ensuring proper admission; for in-service teachers, especially those with longer teaching experience or in resource-poor areas, support should be prioritized over simple assessments.

“Additionally, a tolerance mechanism should be established to reduce teachers’ concerns about trying new technologies. Most importantly, we must always uphold the human-centered stance of education. This requires clarifying teachers’ primary status in the system to prevent technology from replacing the leading role in teaching; in evaluations, we should avoid a purely technical perspective and not use frequency of use as the core standard; and ethically, we must reinforce baseline awareness, especially regarding student privacy protection and maintaining genuine teacher-student interactions. Ultimately, technology should empower education, not replace its essence,” Cai stated.

Cai believes that for existing teachers regarding AI use training, the key is to adhere to demand-oriented, layered strategies, prioritize baseline principles, and integrate learning with application, ensuring that teachers can understand, learn, and apply AI effectively. The understanding of generative AI should emphasize demystification, addressing real classroom needs, and embedding AI applications into daily teaching activities. The guidelines should be central to training, clearly defining compliance boundaries and ethical requirements, and combining typical cases for warning education to enhance awareness of privacy protection, copyright, and educational responsibilities.

Journalist’s Note

Having followed the application of AI in education for several years, I have witnessed the gradual integration of AI into every aspect of teaching, from the initial sporadic appearance of intelligent learning devices in schools to its deep involvement in lesson preparation, learning analysis, and assignment grading. This initiative to include AI in teacher qualifications showcases the firm steps and bright prospects of digital transformation in education. It not only standardizes the application of AI in education from the outset but also builds an integrated system encompassing teacher training, qualification admission, and post-career development, enabling every teacher to continuously enhance their AI literacy and ethical judgment.

I envision a future where AI becomes the most reliable assistant for teachers in the classroom: customizing personalized learning paths based on each student’s cognitive characteristics, breaking the “one-size-fits-all” teaching dilemma; overcoming spatial and temporal barriers, allowing students in remote areas to access quality educational resources, and promoting educational equity; and assisting teachers in optimizing teaching strategies, making classes more targeted and dynamic.

In this future, teachers will no longer be mere knowledge transmitters but guides, organizers, and guardians in human-machine collaborative teaching. They will skillfully use AI tools to enhance teaching efficiency while upholding the essence of education, balancing technology and humanity; teaching students to leverage AI to expand their cognitive boundaries while guiding them to maintain independent thinking, sharpening their critical thinking and innovative skills amid the information flood.

In this scenario, the integration of AI and education will not be a mere mechanical overlay but a subtle reshaping of the educational ecosystem—technology empowering education, and teachers nurturing its soul. Together, they will nourish the growth of every child.

The river of education flows endlessly, and the tide of technology never ceases. The integration of AI into education is not the end but a new starting point for high-quality development in the intelligent era of education. My years of tracking educational development have instilled in me a firm belief that as long as we uphold the essence of education, embrace technology with an open and inclusive mindset, and regulate technology with a professional and rigorous attitude, we can truly make AI the “wings” of education. In that future, every teacher will realize their professional value in human-machine collaboration, and every child will grow under the sunlight of the intelligent era, becoming a new generation capable of both adapting to and leading the future.