一种智慧课堂交互行为数据的标准分数常模计算方法研究——基于改进型弗兰德斯互动分析系统iFIAS

Research on the Method of Calculating Standard Score Norm for Smart Classroom Interaction Behavior Data:Based on Improved Flanders Interaction Analysis System

国家教育数字化战略转型带动了智慧课堂交互行为数据大规模、系统化的采集,当前在采集的数据基础上所进行的分析依据是统计性的经验性分析方法。如何根据课堂交互行为数据建立标准分数常模,并对相关维度数据进行分级应用,是目前国家教育数字化亟待探索的数据驱动智慧课堂交互分析方法。为此,从课堂交互行为数据基础出发,基于改进型弗兰德斯互动分析系统(iFIAS),选取iFIAS系统平台的358节有效课堂和292380条有效数据,形成了课堂交互行为分析标准分数常模的计算方法,并构建了“1个总体,4个主维度,14个子维度”的标准分数常模分级应用框架,得出iFIAS课堂交互行为数据标准分数常模计算结果。最后,应用该方法对一堂小学四年级数学课“认识三角形和四边形”和一堂初中一年级英语课“Do You Think You Will Have Your Own Robot?”进行课堂交互行为量化分析,通过比较发现数据驱动的智慧课堂的特点及其内在关联,并从“标准分数常模、三值内在逻辑关系、课堂特点、无学科限定、常模漂移”五个方面讨论了常模分析结果。

The strategic transformation of national education digitization has driven the large-scale and systematic collection of smart classroom interaction behavior data,and the current analysis based on the collected data is based on statistical and empirical analysis methods.Therefore,how to establish a standard score norm model based on classroom interaction behavior data and hierarchical application of related dimensional data is a data-driven smart classroom interaction analysis method that needs to be explored urgently for the digitalization of national education.With the data basis of classroom interaction behavior,based on the Improved Flanders Interaction Analysis System(iFIAS),358 lessons and 2,923,380 pieces of data from the iFIAS platform were selected to form the calculation method of the standard score norm model for classroom interaction analysis.Besides,a hierarchical application framework of“one overall,four main dimensions,and fourteen sub-dimensions”for the standard score norm was constructed,which resulted in the calculation results of the standard score norm for the classroom interaction behavior data of iFIAS.Finally,this method was applied to the quantitative analysis of classroom interaction behaviors of the fourth-grade math class“Recognize Triangles and Quadrangles”and the Seventh-grade English class“Do You Think You Will Have Your Own Robot?”The analysis compares the characteristics of the data-driven smart classrooms of the two cases and their intrinsic correlations,and discusses the results of norm analysis in five aspects:standard score norm,three-valued intrinsic logical relation,classroom characteristics,non-subject limitations,and norm drift.