Statistical Methods and Artificial Intelligence in Educational Research: An Interview with Professor Ningzhong Shi

In the era of artificial intelligence, the deep integration of statistics, AI, and educational research has become a significant topic worthy of attention for advancing the discipline of education. To address this issue, the author conducted an exclusive interview with Professor Shi Ningzhong, exploring three key areas: the disciplinary logic of education, the application of statistical methods in education, and how AI drives educational reform. Professor Shi Ningzhong emphasized that education belongs to the social sciences. Educational research cannot rely solely on hypothetical reasoning or empirical speculation; it must also reference real-world standards rooted in specific cultural contexts and practical conditions while addressing the actual demands of societal development. Statistics, leveraging mathematical tools to recognize, understand, and express random phenomena, is particularly well-suited for educational research where uncertainty may arise under identical conditions. By modeling and summarizing patterns based on random phenomena in education, statistical methods propel educational research from empirical induction toward theoretical construction, ultimately advancing toward doctrinal innovation. Professor Shi Ningzhong contends that artificial intelligence can address multi-source, dynamic, and contextually complex problems in education through simplified approaches, thereby expanding the application boundaries of statistical methods. Attention should be focused on leveraging statistical methodologies to enhance the efficacy of AI in educational research. Future educational studies must actively respond to the new demands placed on human competency structures in the AI era, prioritizing trends in both foundational and subject-specific education.