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Learning to monitor and regulate collective thinking processes
International Journal of Computer-Supported Collaborative Learning ( IF 5.611 ) Pub Date : 2018-03-13 , DOI: 10.1007/s11412-018-9270-5
Marcela Borge , Yann Shiou Ong , Carolyn Penstein Rosé

In this paper, we propose a conceptual framework to guide the design of a computer-supported collaborative learning intervention to help students learn how to improve collaborative knowledge building discourse at the level of the small group. The framework focuses on scripting individual and collective regulatory processes following collaboration. Individuals are required to evaluate their team’s chat transcripts against rubrics to score discussion quality. These theoretically supported rubrics provide individuals with concrete examples of desired communication processes. After this individual assessment, the team is prompted to discuss their individual scores, identify strengths and weaknesses of their collaborative discourse processes, and select strategies to improve the quality of their collaborative discussion in a future discussion session. To evaluate our framework, we created a prototype of an online system and asked students to use it over ten weeks as part of five discussion sessions. Participants included 37 students, divided into 13 teams, from an undergraduate online course in information sciences. We used quantitative and qualitative analysis techniques to examine students’ collaborative processes over time, with teams as the main unit of analysis. All teams followed the same general activities, but there were two different conditions for scripting individual reflections that preceded the collective sense-making activity: one (Future-thinking) focused on pushing individuals to pay attention to advice on how to improve existing processes in future sessions and another (Evidence-Based) pushed individuals to pay closer attention to the chat transcripts to provide evidence for their group process scores. Our results suggest (1) use of the framework can help students’ monitor and regulate collaborative processes and improve collaborative discourse over time and (2) the Evidence-Based condition can help students engage in higher quality reflective analysis.

中文翻译:

学习监控和规范集体思维过程

在本文中,我们提出了一个概念框架来指导计算机支持的协作学习干预的设计,以帮助学生学习如何在小组水平上改进协作知识的构建。该框架着重于在协作之后编写个人和集体监管程序的脚本。要求个人根据规则评估其团队的聊天记录,以评定讨论的质量。这些理论上支持的规则为个人提供了所需沟通过程的具体示例。在进行个人评估之后,团队会被提示讨论他们的个人分数,确定他们的协作性话语过程的优缺点,并在以后的讨论环节中选择提高协作性讨论质量的策略。为了评估我们的框架,我们创建了一个在线系统的原型,并要求学生在十个星期内使用它,这是五个讨论会的一部分。参与者包括来自信息科学本科在线课程的37名学生,分为13个小组。我们使用定量和定性分析技术,以团队为主要分析单元,研究了学生随着时间推移的协作过程。所有团队都遵循相同的一般活动,但是在集体意义形成活动之前,有两个不同的条件来编写个人思考:一个(未来思维)侧重于促使个人注意如何在将来的会议中改进现有流程的建议,另一种(基于证据)则推动个人更密切地关注聊天记录,以为其小组过程分数提供证据。我们的结果表明:(1)使用该框架可以帮助学生监控和规范协作过程,并随着时间的推移改善协作性话语;(2)循证条件可以帮助学生进行更高质量的反思性分析。
更新日期:2018-03-13
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