无处不在和上下文感知移动学习模型:一种移动虚拟社区方法

Mohammad M. Alnabhan
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引用次数: 2

摘要

本文提出了一种新的自适应移动学习模型,支持协作和上下文感知学习。学习者的位置信息与一组相关的学习上下文维度之间的无缝集成用于促进提供无处不在的学习服务。该模型采用最近搜索算法,对空间相关的移动学习者进行分组,构建面向学习的虚拟社区,实现协同学习体验。该模型实现了基于客户端的协作模式和基于服务器的协作模式两种虚拟社区构建模式。采用初步评估方法,衡量所提出的新模型的成功实施,并在考虑一组学习情境维度后确认虚拟社区的建立;例如学习协作类型、学习风格和学习者的位置信息。结果表明,这两种协作模式都能成功地建立移动学习者之间的虚拟社区。然而,在处理移动对等体数量增加时,基于服务器的模式比基于客户端的模式更具可扩展性,响应时间更短,形成的学习网格区域更小。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Ubiquity and Context-Aware M-Learning Model: A Mobile Virtual Community Approach
This paper presents a new adaptive m-learning model supporting collaborative and context-aware learning. A seamless integration between learners' location information and a set of associated learning context dimensions is used to facilitate the provision of pervasive and ubiquitous learning services. The new model adopts nearest search algorithm in order to group spatially related mobile learners, constructing learning-oriented virtual communities and achieving a collaborative learning experience. The presented model implements two virtual community construction modes, described as client-based and server-based collaboration modes. A preliminary evaluation methodology was conducted, measuring the successful implementation of the proposed new model, and confirming the establishment of the virtual community after considering a set of learning context dimensions; such as learning collaboration type, learning style and learners' location information. Results have confirmed that both collaboration modes were successful in establishing the virtual communities between mobile learners. However, the server-based mode was more scalable than client-based mode while handling the increased number of mobile peers, in which less response time was experienced and a smaller learning grid area was formed.
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