【作 者】：
张惠丽， 温恒福
【关 键 词 】：
循证教育； 人工智能； 教育证据； 研究范式； 教育决策
【栏 目】：
理论探讨
【中文摘要】：
循证教育是教育科学化的产物。传统循证教育研究范式在证据体系的划分、研究方法的应用等方面一直存在矛盾与争议。随着人工智能等技术的发展，基于古典统计学思想的第一代循证教育也必然随之进化和发展。文章从循证教育内涵、各国实践路径与研究范式出发，通过追溯、推理、反思与技术转换，探讨了智能技术支持下由群体决策到个性化分析的新一代循证教育研究模型，沿着问题发现、群体证据分析、个性化证据分析、循证决策生成的路径，提出利用知识表示和推理技术支持情境性证据生成、基于数据索引技术的群体循证干预、基于学习数据的个性化精准预测与推断、基于机器学习算法辅助生成教育决策的循证教育范式转向。
【英文摘要】：
Evidence-based education is the product of the scientification of education. The traditional paradigm of evidence-based education research has long been plagued by contradictions and controversies in the classification of evidence systems and the application of research methods. With the development of artificial intelligence (AI) and related technologies, the first-generation evidence-based education, rooted in classical statistical thinking, is bound to evolve and develop accordingly. Starting from the connotation of evidence-based education, practice paths and research paradigms of various countries, this paper has explored a new-generation evidence-based education research model through tracing, reasoning, reflection and technology transformation, which changes from the group decision-making to the personalized analysis with the support of intelligent technologies. Following the pathway of problem identification, group evidence analysis, personalized evidence analysis and evidence-based decision generation, this paper proposes the transformation of evidence-based education paradigm, which leverages knowledge representation and reasoning technologies for contextual evidence generation, group evidence-based intervention based on data index technology, personalized accurate prediction and inference based on learning data, and machine learning algorithms to assist the generation of educational decision-making.