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A systematical approach for learner group composition by utilizing u-learning portfolio

机译:利用U学习组合的学习者组组合的系统方法

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Context-aware ubiquitous learning environment, which embeds various ubiquitous computing technologies, allows applications to acquire diverse learning behaviors of each u-learner. Those behaviors that were collected and recorded by the u-learning system can be quite useful to enhance the analysis of learner characteristics which can be utilized to distinguish and group learners for further instruction strategy design, for instance, a ubiquitous collaborative learning strategy. This needs a systematical method to analyze learner behaviors and utilize learner characteristics for the group composition. This paper attempts to propose an effective learner grouping scheme which contains processes of the transformation from u-portfolio to our proposed Portfolio Grid, the creation of learner similarity matrix, and the group composition. The aim of this paper is to propose a systematical manner of dividing learners into groups based on the analysis of previously collected u-learning portfolios. The analysis outcome, which has implied the similarity of various behaviors of learners, will facilitate obtaining an expected grouping result for the use of further learning activities such as ubiquitous collaborative learning and team working.
机译:背景感知无处不在的学习环境嵌入各种无处不在的计算技术,允许应用程序获取每个U-Learner的各种学习行为。由U学习系统收集和记录的这些行为对于提高学习者特征的分析,可以用于区分和集团学习者以获得进一步的指导策略设计,例如普遍存在的协作学习策略。这需要一个系统的方法来分析学习者行为并利用组组成的学习者特征。本文试图提出一个有效的学习者分组计划,其中包含从U-POSTFOLIO转换到我们所提出的投资组合网格的过程,创建学习者相似性矩阵和组组成。本文的目的是基于对先前收集的U-Creation组合的分析,提出将学习者分成群体的系统。暗示了学习者各种行为的相似性的分析结果将有助于获得使用进一步学习活动的预期分组结果,例如无处不在的协作学习和团队工作。

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