Analyzing learners' behavior and discourse within large online communities: a Social Learning Analytics Dashboard

Rogério F. da Silva, Itana M. S. Gimenes, J. Maldonado
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引用次数: 1

Abstract

Online Learning Communities (OLC) are nowadays one of the most important producers of Big Data in education. However, the investigation of such environments is underrepresented in educational research. There is a lack of methods and tools that characterize the massive learning associated with the student participation in large OLC. This paper presents a Social Learning Analytics Dashboard (SLAD) to analyze temporal trend models that outline the evolution of learners behavior over time. Such models suggest that ongoing collaboration and positive emotion have a fundamental role for knowledge creation and sharing in large scale social learning. These findings can be used to take actions in order to enhance and regulate social interaction within large OLC.
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在大型在线社区中分析学习者的行为和话语:一个社会学习分析仪表板
在线学习社区(OLC)是当今教育领域最重要的大数据生产者之一。然而,对这种环境的调查在教育研究中代表性不足。在大型在线教学中,缺乏与学生参与相关的大规模学习的方法和工具。本文提出了一个社会学习分析仪表板(SLAD)来分析概述学习者行为随时间演变的时间趋势模型。这些模型表明,在大规模社会学习中,持续合作和积极情绪对知识创造和分享起着重要作用。这些发现可以用来采取行动,以加强和规范大型组织内部的社会互动。
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