Exploring Social Learning Analytics to Support Teaching and Learning Decisions in Online Learning Environments
Exploring Social Learning Analytics to Support Teaching and Learning Decisions in Online Learning Environments
复制标题
探索社交学习分析以支持在线学习环境中的教学决策
DOI：
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
A. Kluge
中科院分区：
文献类型：
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作者：
Rogers Kaliisa;A. Mørch;A. Kluge
迄今为止，大多数教师都采用总结性评估项目作为衡量学生学习和做出教学决策的基准。然而，这些可能并不一定能为实际的学习过程提供全面的证据，特别是在在线学习环境中，因为它们无法长期监测学生的在线学习模式。在本文中，我们探讨了社会学习分析（SLA）如何被教师用作代理来理解学生的学习过程，并支持他们在课程运行期间做出明智的教学决策。这项研究是在挪威一所大型公立大学的一个学期的本科课程中进行的，并利用了通过大学学习管理系统Canvas提供的每周4次在线讨论的数据。首先，我们使用社交网络分析工具NodeXL来分析和可视化学生的在线学习过程，然后我们使用基于理论的计算语言工具Coh-Metrix来分析学生讨论帖子的话语特征。我们的研究结果表明，SLA提供了对在线学习环境中学生认知和社会学习过程的洞察和概述。这项探索性研究有助于提高对二语习得的概念理解，并详细介绍了二语习得方法在提高在线学习环境中的教与学方面的一些方法含义。
Most teachers to date have adopted summative assessment items as a benchmark to measure students’ learning and for making pedagogical decisions. However, these may not necessarily provide comprehensive evidence for the actual learning process, particularly in online learning environments due to their failure to monitor students’ online learning patterns over time. In this paper, we explore how social learning analytics (SLA) can be used as a proxy by teachers to understand students’ learning processes and to support them in making informed pedagogical decisions during the run of a course. This study was conducted in a semester-long undergraduate course, at a large public university in Norway, and made use of data from 4 weekly online discussions delivered through the university learning management system Canvas. First, we used NodeXL a social network analysis tool to analyze and visualize students’ online learning processes, and then we used Coh-Metrix, a theoretically grounded, computational linguistic tool to analyze the discourse features of students’ discussion posts. Our findings revealed that SLA provides insight and an overview of the students’ cognitive and social learning processes in online learning environments. This exploratory study contributes to an improved conceptual understanding of SLA and details some of the methodological implications of an SLA approach to enhance teaching and learning in online learning environments.
影响因子：
9.9
作者：
Gasevic, Dragan;Joksimovic, Srecko;Shaffer, David Williamson
通讯作者：
Shaffer, David Williamson