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学习云空间中学习路径的情境语义标识及应用
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  • 英文篇名:The Situation Semantic Identification and Applications of the Learning Path in the Learning Cloud Space
  • 作者:韩中美 ; 王希哲 ; 黄昌勤 ; 徐小琪
  • 英文作者:HAN Zhong-mei;WANG Xi-zhe;HUANG Chang-qin;XU Xiao-qi;School of Information Technology in Education, South China Normal University;Beijing Hetian Yuxiang Internet Technology Co., Ltd.;
  • 关键词:学习云空间 ; 情境感知 ; 建构主义 ; 富语义学习路径
  • 英文关键词:learning cloud space;;context aware;;constructivism theory;;rich semantic learning path
  • 中文刊名:XJJS
  • 英文刊名:Modern Educational Technology
  • 机构:华南师范大学教育信息技术学院;北京禾田雨像互联网科技有限公司;
  • 出版日期:2017-11-15
  • 出版单位:现代教育技术
  • 年:2017
  • 期:v.27;No.199
  • 基金:国家科技支撑计划课题“职业教育数字化教学公共服务关键技术研究”(项目编号:2014BAH28F02);; 广东省科技计划项目“网络学习云空间中的教育大数据分析与应用”(项目编号:2015A030401087)的阶段性研究成果;; 华南师范大学研究生创新基金“基于大数据分析的智慧云课堂下教学模式及其应用”(项目编号:2015wkxm33)资助
  • 语种:中文;
  • 页:XJJS201711019
  • 页数:7
  • CN:11
  • ISSN:11-4525/N
  • 分类号:124-130
摘要
学习云空间中学习路径的情境语义标识是为了满足学习者个性化学习的现实需要,也是自适应学习的研究热点之一。文章首先探讨了学习云空间的理想学习环境,提出了基于建构主义理论的学习机制。随后,文章设计了面向学习云空间的情境要素,在此基础上构建了面向富语义学习路径的云空间情境感知模型,揭示了基于情境感知的富语义学习路径生成原理,并对学习路径进行了有效性评估。最后,文章依托世界大学城的学习路径功能模块,对富语义学习路径的应用效果进行检验,展现了良好的学习效果。文章的研究可助力于学习路径的精准推荐和学习云空间的进一步发展。
        The situation semantic identification of the learning path in the learning cloud space is to satisfy the realistic needs of personalized learning, and it is one of the research hotspots of adaptive learning. Firstly, this paper discussed the ideal learning environment of the learning cloud space and proposed the learning mechanism based on the constructivism theory. Then, the situation elements for the learning cloud space was designed, and the situation perceptual model oriented to rich semantic learning path in learning cloud space was further built. In addition, the generation principle of the rich semantic learning path was revealed, and the validity of the learning path was evaluated. Finally, relying on the function module of the learning path in the World University City, this paper examined the application effect of the rich semantic learning path, which showed a good learning effect. The results of this paper could contribute to the accurate recommendation of the learning path and futher development of the learning cloud space.
引文
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