面向知识的教师教学监测评估-清华大学教育研究

文章信息/Info

Author(s):: WANG Zhan-jun¹; ² GE Ming-xing² ZHANG Wei¹; 1.School of Humanities and Social Sciences, Beijing Institute of Technology；2.Institute of Education, Tsinghua University

Keywords:: teaching; monitoring assessment; knowledge engineering; big data; artificial intelligence

摘要:: 本研究以大数据、知识工程与教学监测评估三者之间的逻辑关系为分析框架，通过对教师教学评估理论、方法与实践的革新研究，对教师教学监测评估内涵特征的研究，以及对教学监测评估实施路径的探索，建构了面向知识的教师教学监测评估新模式。大数据驱动的教师教学监测评估是以算法智能体为主导，使教师教学监测评估回归教学本身，由教学管理者、同行专家、学生以及评估智能体相结合，挖掘教学状态大数据以发现新知识，并通过知识管理判断教师教学的优势与不足，进而循证为教师提供教学改进的知识、方法、技能、措施与资源等。

Abstract:: This research takes the logical relationship among big data, knowledge engineering and teaching monitoring assessment as the analytical framework. Through the innovative research on the theory, method and practice of teachers’ teaching assessment, the research on the connotation and characteristics of teaching monitoring assessment, and the exploration of the implementation path of teaching monitoring assessment, this study constructed a new model of knowledge-based teaching monitoring assessment. The Big-data-driven teaching monitoring assessment is dominated by algorithmic agents and brings the focus of assessment back to the essence of teaching. Teaching managers, peer experts, students and evaluation agents should work together to explore the big data in teaching to discover new knowledge and judge the strengths and weaknesses of teachers’ teaching through knowledge management. Furthermore, it provides teachers with knowledge, methods, skills, measures and resources for evidence-based teaching improvement.