摘要
教学行为分析是教学研究的一项重要内容,可为教学过程性评价与精准教学服务提供参考与依据。国内外有关教学行为分析的文献样本,从时间分布、研究主题和主题共现等多角度,呈现出教学行为分析的研究现状。在此基础上,面向教学的具体过程,基于数据科学视角,对教学行为的过程性分析框架展开的探讨,可以分析不同情形下教学行为分析方法的合理选择,把握新时期教学行为分析的发展趋向。经研究发现:互联网、大数据和智能技术的发展,对教学行为分析的影响日益凸显;教学主体、教学情境、教学行为与分析方法等方面,是教学行为分析关注的重点。基于此,教学行为分析应以过程性数据为基础,重视多模态数据的采集分析与行为分析方法在不同数据形态下的适切运用,以形成从数据到结论的全链条输出。因此,教学行为分析应立足过程性行为数据,聚焦多模态智能计算,通过“关联”与“因果”探究行为背后的作用机制,不断推动研究结论服务于教学实践和科学决策。
Teaching behavior analysis is an important means of teaching research,which can provide reference for teaching process evaluation and precise teaching service.By the investigating of domestic and foreign literature samples related to teaching behavior analysis,the current situation of teaching behavior analysis is analyzed from the perspectives of time distribution,research topic and theme co-occurrence.Facing the specific process of teaching,combined with the perspective of data science,we explored the practical framework of teaching behavior analysis,analyzed the reasonable choice of behavior analysis methods under different data forms,and grasp its development trend in the new era.The research found that the development of the Internet,big data and intelligent technology has increasingly prominent influence on teaching behavior analysis.Teaching subjects,teaching context,teaching behavior and analysis methods are the focus of teaching behavior analysis.Teaching behavior analysis should be based on the process data,pay attention to the collection and analysis of multi-modal data and the appropriate application of behavior analysis methods in different situations,so as to form the whole chain output from data to conclusions.In the new era,teaching behavior analysis should be based on procedural behavior data,focus on multi-modal intelligent computing,and explore the mechanism behind the behavior through“relation”and“causality”,and promote research conclusions oriented teaching practice and decision-making applications.
作者
张文梅
祁彬斌
范文翔
Zhang Wenmei;Qi Binbin;Fan Wenxiang(Research Center of Distance Education,Faculty of Education,Beijing Normal University,Beijing 100875;Smart Learning Institute,Faculty of Education,Beijing Normal University,Beijing 100875;School of Education,Hangzhou Normal University,Hangzhou Zhejiang 311121)
出处
《远程教育杂志》
CSSCI
北大核心
2021年第1期84-93,共10页
Journal of Distance Education
基金
2020年浙江省哲学社会科学规划课题“基于深度学习的高校智能听评课系统研究”(20NDJC186YB)的研究成果。
关键词
教学行为分析
课堂教学
在线学习
教育大数据
数据驱动
Teaching Behavior Analysis
Classroom Teaching
Online Learning
Educational Big Data
Data Driven
