摘要
核心素养时代,课堂教学评价体系的建构需要对我国课堂教学评价的研究现状、聚类主题与发展趋势有整体性的认识。文本以中国知网中的CSSCI数据库为数据来源,借助知识图谱分析软件CiteSpace对233篇文献进行可视化分析,发现:我国课堂教学评价领域研究成果丰硕,但核心作者群以及研究机构分布较为零散,尚未形成学术共同体;关键词聚类的核心主题随技术的发展而发生缓慢变化,以应然化的理论研究为主,缺乏实然化的实证研究;演绎路径遵循教学价值与教学技术的双重取向。基于此,建议我国课堂教学评价研究应构建多维主体的协作研究共同体、加强基于实践逻辑的理论研究与实证研究、兼顾教学价值与教学技术的双重建构,以进一步推动核心素养时代课堂教学评价实施。
The construction of classroom teaching evaluation system in the era of core literacy requires a comprehensive understanding of the current research status and trends of classroom teaching evaluation in China.With the help of knowledge map software CiteSpace,233 documents in CNKI CSSCI database are visually analyzed.The results show that:there are rich research achievements in the field of classroom teaching evaluation in China,but the distribution of core author groups and research institutions is relatively scattered,and an academic community for research has not yet formed;The core theme of keyword clustering undergoes slow changes with the development of technology,with a focus on theoretical research that should be implemented and a lack of empirical research that should be implemented;The deductive path follows the dual orientation of teaching value and teaching technology,and its cutting-edge hot topics are related to“core competencies,smart classrooms,student development,and intelligent evaluation”.Therefore,the study suggests that research on classroom teaching evaluation in China should“build a multi-dimensional collaborative research community,strengthen theoretical and empirical research based on practical logic,and balance the dual construction of teaching value and teaching technology.”This is of great significance for deepening the implementation of classroom teaching evaluation in the era of core literacy.
作者
徐恩伟
王媛媛
XU En-wei;WANG Yuan-yuan(School of Education Science,Xinjiang Normal University,Urumqi Xinjiang 830017;No.23 Middle School,Urumqi Xinjiang 830002)
出处
《语言与教育研究》
2023年第4期58-67,F0002,共11页
LANGUAGE AND EDUCATION STUDIES
关键词
课堂教学评价
聚类主题
发展趋势
知识图谱
实证分析
Classroom Teaching Evaluation
Clustering Topics
Cutting Edge Trends
Knowledge Map
Empirical Analysis
