摘要
本研究运用CiteSpace对国内外虚拟学习主题相关文献进行分析,结果发现:国内虚拟学习研究的内容不够细化、关联分析较少、研究视角和方法较为单一。具体表现为:在研究内容上,国内关注虚拟学习社区和虚拟学习环境构建等热点主题,国外在关注虚拟学习环境构建的基础上,更加关注学习过程要素、学习者特征、虚拟学习干预、评价和教学促进等热点主题;在研究方法和视角上,国外侧重使用定量与定性结合的方法和运用跨学科视角去剖析问题,国内常从教育学视角进行理论分析或经验总结;在未来的趋势上,国外注重扩展实证研究方法,探究虚拟学习过程机制,国内虚拟现实技术和深度学习将成为研究前沿。建议我国在未来研究上,更加关注微观层面的深入分析,探索交叉学科的整合融入,并着力解决虚拟学习的实际应用问题。
The present study explores Cite Space to make a comparative analysis of literatures on virtual learning between China and other countries.Findings reveal some problems in this respect in China like too broad contents,less relative analyses,narrower perspectives,and less diversified approaches.In terms of hotspot themes,Chinese studies paid much more attention to virtual learning communities and virtual learning environments than their foreign counterparts to learning process factors,learners’characteristics,virtual learning intervention,assessment and promotion.In addition,in respect of research methodology and perspective,foreign scholars tended to adopt an interdisciplinary perspective and explore a comprehensive method integrating both quantitative and qualitative approaches,whereas Chinese researchers relied more on theoretical analyses and empirical studies.Finally,in foreign countries,empirical research methods are expected to be diversified to study the mechanisms governing the virtual learning process.And in China,virtual realization technologies and deep learning are to be its research front.This paper finally proposes that Chinese researchers shall do more and in-depth studies in micro aspects,and explore an interdisciplinary approach to addressing application problems in virtual learning.
作者
陈丽君
林伟婷
CHEN Li-jun;LIN Wei-ting(School of Educational Science and Technology,Guangdong Polytechnic Normal University,Guangzhou 510665)
出处
《广州广播电视大学学报》
2020年第4期6-13,106,共9页
Journal of Guangzhou Open University
基金
教育部人文社会科学研究规划基金项目“虚拟感知整合认知负荷的多维测评与优化控制研究”(项目编号:18YJA880005)。
关键词
虚拟学习
比较研究
可视化分析
研究进展
学习分析
virtual learning
comparative studies
visualized analysis
research development
learning analytics