...
首页> 外文期刊>Computers in Human Behavior >Modelling MOOC learners' social behaviours
【24h】

Modelling MOOC learners' social behaviours

机译:建模MooC学习者的社会行为

获取原文
获取原文并翻译 | 示例
           

摘要

MOOCs offer world-widely accessible online content typically including videos, readings, quizzes along with social communication tools on a platform that enables participants to learn at their own pace. The number of learners who sign up and attend the courses are exponentially growing. Consequently, MOOC platforms generate a large amount of data about their learners. Researchers use participants' digital traces to make sense of their engagement in a course and identify their needs to predict future patterns and to make interventions based on these patterns. The research reported here was conducted to further understand learners social engagement on a MOOC platform and the impact of engagement on course completion. The patterns of learners social engagement were modelled by using learning analytics techniques. The findings of this research show that the integrated social features such as commonly known follow features and deeper peer interactions have potential value in tracking, analysing, and generating insightful information related to participants' behaviours.
机译:Moocs提供世界广泛的可访问的在线内容,通常包括视频,读数,在平台上以及社交通信工具以及使参与者以自己的步伐进行学习的平台。注册和参加课程的学习者人数是指数增长的。因此,MoOC平台会产生关于他们学习者的大量数据。研究人员使用参与者的数字痕迹来在课程中进行参与,并确定他们的需要预测未来的模式并根据这些模式进行干预措施。在此报告的研究是为了进一步了解学习者对MoOC平台的社交参与以及参与课程完成的影响。学习者社交参与的模式是通过使用学习分析技术进行建模的。该研究的结果表明,诸如众所周知的遵循特征和更深的同伴互动等综合社交特征在跟踪,分析和生成与参与者行为相关的富有识别信息的潜在价值。

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