摘要
近年来,智慧教育已然成为我国教育教学变革的重要趋势之一。深入探析我国智慧教育研究现状及发展趋势,不仅有利于明晰智慧教育研究热点,也有利于加快我国智慧教育建设。本研究以2010—2017年CNKI核心期刊中智慧教育相关文献为数据源,利用SATI 3.2、UCINET 6等软件进行共词聚类分析和社会网络图谱分析,以明确我国智慧教育研究现状和发展趋向。分析表明,智慧教育研究主题涵盖五大方面:智慧教育基本理论、智慧学习环境研究、智慧教育体系架构与技术支撑研究、智慧教育实践应用研究、智慧教育发展战略与路径研究。未来国内智慧教育研究应把握如下趋势:拓宽研究视角,注重设计、开发、应用、管理、评价的多方位研究;转变研究范式,由"影响"转向"建构";注重从理论向实践的转变,做到政府、社会、学校的协同共建。
Smart education has become one of the crucial research focuses in education and teaching reform in China in recent years.An in-depth analysis of current research topics on smart education and its development trend is not only conducive to the researchers' detailed,clear understanding of the latest development of smart education,but also good to promote the development speed of smart education.In this study,we first searched the studies indexed in the CNKI database from 2010 to 2017 with the term smart education.Then,we analyzed the surveyed studies using knowledge mapping and co-word analysis methods with SATI 3.2 and UCINET 6 to summarize the current status and trends of the research on smart education in China.The results showed that the research topics cover five major areas:the fundamental theories of smart education,the study on smart learning environment,the research on structural framework and technical support of smart education,research on the practical application of smart education,and research on development strategy and path of smart education.In the future,domestic smart education research should grasp the following trends: broaden the research perspective,pay attention to the studies on design, development,application,management and evaluation,change research paradigm from influence to construction,focus on the transition from theory to practice,and achieve the collaborative construction of government,society and schools.
作者
李玥泓
赵可云
LI Yuehong, ZHAO Keyun(School of Media and Communications,Qufu Normal University,Rizhao,Shandong,China 27682)
出处
《数字教育》
2018年第4期29-33,共5页
Digital Education
关键词
智慧教育
词频分析法
共词聚类分析法
研究现状
smart education
word frequency analysis
co-word duster analysis
research shams