协同推荐:一种个性化学习路径生成的新视角
发布时间：2019-02-24 18:46
【摘要】：以用户需求为中心的个性化学习环境构建是e-Learning未来的发展趋势,也是当前远程教育及智慧教育领域研究的热点。针对个性化e-Learning学习环境的"适应性"问题,从用户认知水平维度切入,利用邻近区用户群(邻居用户)相似性规则提出了一种Web环境下个性化学习路径生成的协同推荐机制,并通过架构设计、系统建模、路径提取及算法设计四个方面重点剖析了自适应学习系统(Adaptive Learning System,ALS)协同推荐机制的技术解决方案,通过系列实验设计、实施以及数据分析对其有效性进行了验证。结果表明,本研究成果在一定程度上能够向目标用户推荐较理想的学习路径,有效改善推荐资源的精准度,进而提高用户学习质量和学习效果。
[Abstract]:The construction of personalized learning environment centered on user needs is the development trend of e-Learning in the future, and it is also a hot spot in the field of distance education and intelligent education. Aiming at the problem of "adaptability" in the personalized e-Learning learning environment, we cut into the dimension of user's cognitive level, This paper proposes a collaborative recommendation mechanism for personalized learning path generation in Web environment by using the similarity rules of adjacent user groups (neighborhood users), and models the system through architecture design. The technical solution of cooperative recommendation mechanism of adaptive learning system (Adaptive Learning System,ALS) is analyzed in four aspects of path extraction and algorithm design, and its validity is verified by a series of experiments, implementation and data analysis. The results show that to some extent, the research results can recommend the ideal learning path to the target users, improve the accuracy of the recommended resources effectively, and then improve the learning quality and learning effect of the users.
【作者单位】： 广西教育学院教育技术与信息管理中心;华南师范大学教育信息技术学院;
【基金】：广西教育教学改革省级重点项目“面向移动终端设备的自适应网络学习平台关键技术研究与实践”(项目编号:2014JGZ151) 广西教育科学“十二五”规划教育信息化专项课题“基于混合式培训模式的广西中小学教师信息技术应用能力培训资源建设与应用研究”(项目编号:2015ZXY22)的研究成果
【分类号】：G434
，
本文编号：2429824
[Abstract]:The construction of personalized learning environment centered on user needs is the development trend of e-Learning in the future, and it is also a hot spot in the field of distance education and intelligent education. Aiming at the problem of "adaptability" in the personalized e-Learning learning environment, we cut into the dimension of user's cognitive level, This paper proposes a collaborative recommendation mechanism for personalized learning path generation in Web environment by using the similarity rules of adjacent user groups (neighborhood users), and models the system through architecture design. The technical solution of cooperative recommendation mechanism of adaptive learning system (Adaptive Learning System,ALS) is analyzed in four aspects of path extraction and algorithm design, and its validity is verified by a series of experiments, implementation and data analysis. The results show that to some extent, the research results can recommend the ideal learning path to the target users, improve the accuracy of the recommended resources effectively, and then improve the learning quality and learning effect of the users.
【作者单位】： 广西教育学院教育技术与信息管理中心;华南师范大学教育信息技术学院;
【基金】：广西教育教学改革省级重点项目“面向移动终端设备的自适应网络学习平台关键技术研究与实践”(项目编号:2014JGZ151) 广西教育科学“十二五”规划教育信息化专项课题“基于混合式培训模式的广西中小学教师信息技术应用能力培训资源建设与应用研究”(项目编号:2015ZXY22)的研究成果
【分类号】：G434
，
本文编号：2429824
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