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首页> 外文期刊>Journal of land use science >How social network analysis can be used to monitor online collaborative learning and guide an informed intervention
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How social network analysis can be used to monitor online collaborative learning and guide an informed intervention

机译:社交网络分析如何用于监控在线协同学习并指导知情干预

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To ensure online collaborative learning meets the intended pedagogical goals (is actually collaborative and stimulates learning), mechanisms are needed for monitoring the efficiency of online collaboration. Various studies have indicated that social network analysis can be particularly effective in studying students' interactions in online collaboration. However, research in education has only focused on the theoretical potential of using SNA, not on the actual benefits they achieved. This study investigated how social network analysis can be used to monitor online collaborative learning, find aspects in need of improvement, guide an informed intervention, and assess the efficacy of intervention using an experimental, observational repeated-measurement design in three courses over a full-term duration. Using a combination of SNA-based visual and quantitative analysis, we monitored three SNA constructs for each participant: the level of interactivity, the role, and position in information exchange, and the role played by each participant in the collaboration. On the group level, we monitored interactivity and group cohesion indicators. Our monitoring uncovered a non collaborative teacher-centered pattern of interactions in the three studied courses as well as very few interactions among students, limited information exchange or negotiation, and very limited student networks dominated by the teacher. An intervention based on SNA-generated insights was designed. The intervention was structured into five actions: increasing awareness, promoting collaboration, improving the content, preparing teachers, and finally practicing with feedback. Evaluation of the intervention revealed that it has significantly enhanced student-student interactions and teacher-student interactions, as well as produced a collaborative pattern of interactions among most students and teachers. Since efficient and communicative activities are essential prerequisites for successful content discussion and for realizing the goals of collaboration, we suggest that our SNA-based approach will positively affect teaching and learning in many educational domains. Our study offers a proof-of-concept of what SNA can add to the current tools for monitoring and supporting teaching and learning in higher education.
机译:为确保在线协作学习符合预期的教学目标(实际上是协作和刺激学习),因此需要机制来监控在线合作的效率。各种研究表明,社会网络分析可以特别有效地研究学生在线合作中的互动。然而,教育的研究仅重点关注使用SNA的理论潜力,而不是他们所达成的实际利益。本研究调查了如何使用社交网络分析来监控在线协作学习,找到需要改进的方面,指导知情干预,并在三个课程中使用实验性,观测的重复测量设计进行干预的疗效。持续时间。使用基于SNA的视觉和定量分析的组合,我们监测每个参与者的三个SNA构造:信息交换中的交互,角色和位置等级,以及每个参与者在合作中发挥的作用。在群体水平上,我们监测交互性和组凝聚力指标。我们的监测在三个学习的课程中发现了一个非协同教师中心的互动模式,以及学生之间的互动,有限的信息交流或谈判,以及教师主导的学生网络非常有限。设计了基于SNA-生成的洞察力的干预。干预措施被构建为五项行动:提高意识,促进合作,改善内容,准备教师,最后与反馈练习。对干预的评价显示,它有明显增强了学生 - 学生的互动和教师 - 学生的互动,以及大多数学生和教师之间的合作互动模式。由于高效和交际活动是成功内容讨论的必要条件,并且为了实现合作目标,我们建议我们的SNA的方法将在许多教育领域积极影响教学和学习。我们的研究提供了一个SNA可以添加到当前工具中的概念,以便在高等教育中监控和支持教学和学习。

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