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作 者:曾宁 张宝辉[1] 范逸洲 ZENG Ning;ZHANG Baohui;FAN Yizhou(School of Education,Shaanxi Normal University,Xi’an,China 710062;The University of Edinburgh,Edinburgh,UK,999020)
机构地区:[1]陕西师范大学,陕西西安710062 [2]英国爱丁堡大学,英国爱丁堡999020
出 处:《现代远距离教育》2019年第6期87-96,共10页Modern Distance Education
基 金:2015年度教育部全国教育规划国家重点课题“中国终身教育体系构建的路径与机制研究”(编号:AKA150013)
摘 要:课程论坛是慕课师生交互和生生交互最主要的发生场所,面对其中不断生成的数据,如何选择合适的方法分析和了解论坛的教学和交互活动并优化论坛环境,是慕课研究者们关注的重要问题。以Web of Science Core Collection和ScienceDirect为文献来源数据库,选取2014-2018年与慕课论坛(MOOC forum)数据分析最相关的30篇英文文献,结合实例详细阐述网络志、内容分析、数理统计、聚类分析、网络分析、文本挖掘等6类方法的具体分析过程。在此基础上,探讨以上方法及现有数据分析的局限,并为未来研究者分析慕课论坛数据提出建议:将数据分析结果服务于慕课利益相关者;加强对慕课论坛的动态分析;探讨相关背景,逐步扩大研究的推广范围。Discussion forum is the main venue for learner interaction in MOOCs,which directly affects the effectiveness of MOOC courses.When having big data of MOOC discussion forums,how to select appropriate analysis methods to discover how discussion forums work,optimize teaching and student interaction level is a critical issue for researchers.This study selected 30 English journal papers that were highly relevant to data analysis of internationally renowned MOOC discussion forums dated from 2014 to 2018.The high quality English papers were from Web of Science Core Collection and ScienceDirect journal databases.We summarized interaction data methods of six forums that included examples including nethnography,content analysis,statistics,clustering,network analysis and text mining.We analyzed the limitations of each of the methods and provided suggestions on improving the MOOC discussion forums:1)to provide analysis results for MOOC stakeholders;2)to strengthen the dynamic of MOOC discussion forum;3)to discuss the context of data analysis methods,gradually expand the scope of research.
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