教育大数据分析与应用正如火如荼地展开,并不断向课堂的教与学聚焦.围绕智慧课堂的常态化应用,对基于智慧课堂的教育大数据分析进行实证性研究,具有现实意义.智慧课堂的教学互动可以用"STM三角模型"来描述,包括教师与媒介互动、学生与媒介互动、教师对学生互动、学生对教师互动、学生与学生互动等互动行为及数据关系.智慧课堂数据建模与分析,总体上采取基于学习者行为建模与分析的"1+3模式"以及基于学习内容和结果建模与分析的"3+1模式"两种方式.智慧课堂的数据挖掘流程,分为目标理解、数据清洗、数据分析、数据展现等步骤,常用的挖掘算法和技术有多元回归分析、分类聚类、关联规则挖掘、文本分析、图挖掘技术等方法.基于某中学智慧课堂常态化应用的真实数据,通过构建师生互动指数分析模型并进行实证分析,为教育大数据的分析和应用,提供了一个应用参考实例.%Recent years have witnessed the increased development and popularity of big data in education, and the research contents are constantly focused on class teaching and learning. Therefore, around the normalization application of the smart class, it is of practical significance to do empirical research on the big data analysis of education in the smart class.The interaction of teaching in the smart class can be described by the"STM triangle model", which includes five types of interaction and data relationship be-tween teacher and media interaction, student and media interaction, teacher to student interaction, student to teacher interaction, student interaction with student. The smart class data mining process including object understanding, data cleaning, data analysis, data visualization. The common algorithms and techniques are multiple regression analysis, classification, clustering and association rule mining,text analysis and graph mining technique.Based on the real data of smart class in a middle school,this paper constructs a teacher-student interaction index analysis model of data mining in smart class, and makes an empirical analysis, which provides an application example.
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