...
  • 主题
高级搜索  >
历史搜索 清空历史
首页> 外文期刊>International journal of machine learning and cybernetics >Towards organizing smart collaboration and enhancing teamwork performance: a GA-supported system oriented to mobile learning through cloud-based online course
【24h】

Towards organizing smart collaboration and enhancing teamwork performance: a GA-supported system oriented to mobile learning through cloud-based online course

机译：致力于组织智能协作并提高团队绩效：基于GA的系统支持，通过基于云的在线课程面向移动学习

获取原文
获取原文并翻译 | 示例
           
页面导航
  • 摘要
  • 著录项
  • 相似文献
  • 相关主题

摘要

At present, people's learning styles become diverse, for which mobile learning is a significant trend that enables distributed learners to achieve collaborative learning and allows them to be engaged in virtual teams to work together. In this research, we develop a system to cope with the problem in current mobile learning circumstance, where learners in virtual teams generally lack proper communications, guidance and assistances between each other. Following the theory of Kolb team learning experience, we use our system, Teamwork as a Service (TaaS), to work in conjunction with cloud-based learning management systems. This system targets at organizing a series of learning activities and then forming a learning flow in order to allow learners to participate into smart collaborations. Executing the five web services of TaaS sequentially, learners can have their collaborative learning arranged in a better environment, where they are able to know about one another, be grouped into cloud-based 'Jigsaw Classroom', plan and publish tasks and supervise other learners mutually. In particular, one primary point of enhancing learners' teamwork performance is to offer them computational choice of task allocation. For this reason, we model the social features related to the collaborative learning activities, and introduce a genetic algorithm (GA) approach to group learners into appropriate teams with two different team formation scenarios. The technical details of the operation principle of GA are illustrated thoroughly. Finally, experimental results are presented to prove our approach is workable to facilitate teamwork with considerations of learner's capabilities and preferences. We also demonstrate our implementation details of the newly designed TaaS over the Amazon cloud and discuss the main improvements for collaborative learning brought by TaaS.
机译：当前，人们的学习方式变得多样化，为此，移动学习是一个重要趋势，它使分布式学习者能够实现协作学习，并使他们能够参与虚拟团队合作。在这项研究中，我们开发了一个系统来解决当前移动学习情况下的问题，在这种情况下，虚拟团队中的学习者通常彼此之间缺乏适当的沟通，指导和帮助。遵循Kolb团队学习经验的理论，我们使用团队协作服务（TaaS）系统与基于云的学习管理系统协同工作。该系统旨在组织一系列学习活动，然后形成学习流程，以允许学习者参与智能协作。依次执行TaaS的五个Web服务，学习者可以在一个更好的环境中安排他们的协作学习，在那里他们可以彼此了解，被分组到基于云的“拼图教室”，计划和发布任务以及监督其他学习者相互。特别是，提高学习者团队合作绩效的主要目的是为他们提供任务分配的计算选择。因此，我们对与协作学习活动相关的社会特征进行建模，并引入遗传算法（GA）方法将学习者分为具有两个不同团队形成场景的合适团队。 GA运作原理的技术细节已详细说明。最后，提供实验结果以证明我们的方法在考虑学习者的能力和偏好的情况下可促进团队合作。我们还将在亚马逊云上展示我们新设计的TaaS的实施细节，并讨论TaaS带来的协作学习的主要改进。

著录项

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱：kefu@zhangqiaokeyan.com

京公网安备：11010802029741号 ICP备案号：京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有

  • 客服微信

  • 服务号