中国教育类核心期刊 CSSCI来源期刊 RCCSE中国权威学术期刊

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    基于课堂教学行为大数据的师徒制关系构造模型

    Relational Tectonic Model of Mentoring Based on Big Data of Classroom Teaching Behavior

【作      者】:

王雅慧, 孙 彬, 郭燕巍, 吴永亮


【关 键 词 】:

课堂教学行为; 教师特征; 大数据; 师徒制模型; 师徒关系


【栏      目】:

课程与教学


【中文摘要】:

师徒制作为教师专业发展的重要方式,在教师队伍建设方面占有举足轻重的地位。文章运用访谈法、内容分析法和文献法对当前师徒制存在的问题进行梳理,以课堂教学行为大数据为基础构建了师徒制关系构造模型,该模型共包括四个模块:教师特征大数据采集、教师特征大数据分析、师徒关系匹配大数据分析、师徒绩效大数据分析。同时,提出了三种匹配模式:基于模仿的动态匹配、基于重组的动态匹配和基于创新的动态匹配。通过该模型的构造以期为学校师徒间的构造方式提供参考。


【英文摘要】:

Mentoring is an important way of teacher professional development and plays an important role in the construction of teacher team. This paper uses the interview method, content analysis method and literature research method to sort out the existing problems of the mentoring system, and builds a relational tectonic model of mentoring based on the big data of classroom teaching behavior. The model consists of four modules: big data collection of teachers' characteristics, big data analysis of teachers' characteristics, big data analysis of mentoring relationship matching and big data analysis of mentoring performance. Then, three matching patterns are proposed: dynamic matching based on imitation, dynamic matching based on reorganization and dynamic matching based on innovation. The model is expected to provide a reference for the construction of the mentorship in schools.

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