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作 者:赵呈领[1] 李敏[1] 疏凤芳[1] 黄琰[1] ZHAO Chengling;LI Min;SHU Fengfang;HUANG Yan(School of Educational Information Technology,Central China Normal University,Wuhan 430079,China)
机构地区:[1]华中师范大学
出 处:《现代远距离教育》2019年第4期20-27,共8页Modern Distance Education
基 金:教育部-中国移动科研基金2017年度项目“信息技术支持下的区域教研模式研究及试点”(编号:MCM20170502)
摘 要:具有不同的目标、偏好和学习动机的学习者在访问不同类型的网络学习资源时可能会表现出不同的参与水平和行为模式,不同的参与水平和行为模式反过来会影响学习成效。从网络学习资源视角,对观看视频资源、浏览文档资源、参考作业模板以及阅读回复讨论和发布讨论主题所花费的时长这五个变量进行聚类分析,将具有相似访问网络学习资源行为的学习者聚类为三类:“网络学习资源低频率学习者”、“网络学习资源高频率学习者”和“预设性资源密集学习者”,并对三个聚类开展Kruskal-Wallis检验和Mann-Whitney U检验。分析发现,三个聚类的学习者的参与水平存在显著差异;此外,三个聚类学习者的作业评价得分、讨论评价得分和课程总分差异显著,表明访问网络学习资源的行为模式与学习成效相关。从完善网络学习资源多样性建设、满足学习者对网络学习资源的个性化需求和完善评价体系等方面来促进优质网络学习资源和平台的建设,并鼓励学习者在消费网络学习资源的同时,积极参与建设生成性网络学习资源。Learners with different goals,preferences,and motivations may exhibit different levels of participation and behavior when accessing different types of online learning resources.Different levels of participation and behavior patterns may in turn affect learning effectiveness.From the perspective of online learning resources,this study clusters five variables,such as viewing video resources,browsing document resources,reference job templates,and reading responses to discuss and publish discussion topics,to classify learners with similar access to online learning resources into three clusters:“Low-frequency online learning resource learners”,“high-frequency online learning resource learners”and“pre-determined resource-intensive learners”The Kruskal-Wallis test and the Mann-Whitney U test were performed on the three clusters.We found that there were significant differences in the participation levels of the three clusters of learners;in addition,the three evaluation learners’job evaluation scores,discussion evaluation scores and course total scores were significantly different,it indicates that the behavioral patterns of accessing online learning resources are related to learning effectiveness.Promote the promotion of high-quality online learning resources and platform construction by improving the diversity of network learning resources,satisfying learners’individualized needs for online learning resources,and improving the evaluation system.Encourage learners to actively participate in the construction of generative network learning resources while consuming online learning resources.
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