揭示在线讨论中的社会时间动态:基于事件的方法

Bodong Chen, Oleksandra Poquet
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摘要

在线讨论在高等教育中被广泛采用,以促进学生之间的互动。然而,以往关于在线讨论的研究并没有估算出多种因素共同影响学生在在线讨论活动中互动的效果。在本研究中,我们将一种名为 "关系事件建模 "的动态网络分析方法应用于学生参与每周讨论活动的在线课程数据集。在关系事件模型中,我们纳入了多种因素,包括参与者特征、网络形成机制和即时参与转变。结果表明,讲师更有可能发起互动,但收到回应的可能性较低。在之前的关系事件中建立起来的受欢迎程度、活跃程度和熟悉程度对未来的事件有积极影响。本地受欢迎程度、即时互惠和活动爆发等即时参与转变也起到了积极作用。这项研究强调了在研究在线讨论时考虑多种因素的重要性,证明了关系事件模型在分析在线互动方面的实用性,并为在线讨论中的学生互动提供了经验性见解。对实践或政策的影响: 支持大学课堂中的在线讨论需要教师考虑多方因素,包括教学设计、技术能力、学习者特征和社会动态。教育工作者不能只是简单地计算学生的发帖量,还要关注学生如何在微观层面上进行互动。教育者和教学设计者可以关注在线讨论中的社会时态动态,并评估特定课程中出现的动态是否可取,是否有利于学生的学习。
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Uncovering socio-temporal dynamics in online discussions: An event-based approach
Online discussions are widely adopted in higher education to promote student interaction. However, prior research on online discussions falls short to estimate the effect of multiple factors collectively shape student interaction in online discussion activities. In this study, we applied a dynamic network analysis approach named relational event modelling to a data set from an online course where students participated in weekly discussion activities. In the relational event models, we incorporated multiple factors including participant characteristics, network formation mechanisms and immediate participation shifts. Results indicated that the instructor was more likely to initiate interactions but less likely to receive responses. Popularity, activity and familiarity established in prior relational events positively affected future events. Immediate participation shifts such as local popularity, immediate reciprocation and activity bursts also played a positive role. The study highlights the importance of considering multiple factors when examining online discussions, demonstrates the utility of relational event modelling for analysing online interaction and contributes empirical insights into student interaction in online discussions. Implications for practice or policy: Supporting online discussions in college classrooms requires instructors to consider multiple actors including pedagogical designs, technological affordances, learner characteristics and social dynamics. Educators could go beyond simply counting student posts to paying attention to how students interact at a micro level. Educators and instructional designers could pay attention to socio-temporal dynamics in online discussions and evaluate whether emerging dynamics in a particular course are desirable and conducive to student learning.
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