Education evaluation and monitoring have been evolving rapidly thanks to the application of artificial intelligence and big data, which have significantly supported learning, teaching, and school management, experts said during a conference in Beijing on Tuesday.
Yang Yu, deputy director of the Office of National Education Inspection at the Ministry of Education, said accurate profiles of assessment subjects, generated through machine learning, have dramatically improved the efficiency and accuracy of grading exam papers.
He made these remarks at the 7th International Conference on Education Evaluation and Monitoring organized by Beijing Normal University and iFLYTEK.
"AI and big data enable a more scientific analysis and interpretation of vast monitoring and evaluation data," Yang said, adding that these technologies help educators identify priorities in the evaluation process.
When combined with visualization tools, big data can present complex analytical results through charts and comparative graphs, allowing education administrators and decision-makers to understand the insights behind the data and implement more targeted actions.
"For evaluation subjects, these technologies can generate personalized reports, accurately identify individual needs, and provide scientific support for adjustments and tailored interventions," Yang said.
Fu Bo, spokeswoman for the China Education Association for International Exchange, said countries worldwide are exploring new education evaluation systems, shifting from solely result-oriented assessments to multidimensional evaluations that focus on the learning process.
AI and big data have been widely applied in education, from personalized learning to teaching management, Fu said. "We need to utilize these emerging technologies to promote digitalized evaluation and monitoring while improving accuracy and efficiency," she said, emphasizing the importance of international cooperation in sharing educational resources.
David Osher, vice-president of the American Institutes for Research, highlighted AI's role in collecting high-quality data and offering actionable insights for educators. Specific applications include tracking classroom interactions and student engagement, as well as providing personalized feedback.
Osher shared a study on the effects of suspension from school on children, using AI to analyze data collected over 10 years among school children in New York. "By using AI, we were able to match students on 80 different variables and thoroughly examine the predictive consequences of suspension," he said.
