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首页> 外文期刊>SIAM journal on applied dynamical systems >A Method to Analyze Computer Science Students' Teamwork in Online Collaborative Learning Environments
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A Method to Analyze Computer Science Students' Teamwork in Online Collaborative Learning Environments

机译:一种分析计算机科学学生团队合作在线协同学习环境的方法

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摘要

Although teamwork has been identified as an essential skill for Computer Science (CS) graduates, these skills are identified as lacking by industry employers, which suggests a need for more proactive measures to teach and assess teamwork. In one CS course, students worked in teams to create a wiki solution to problem-based questions. Through a case-study approach, we test a developed teamwork framework, using manual content analysis and sentiment analysis, to determine if the framework can provide insight into students' teamwork behavior and to determine if the wiki task encouraged students to collaborate, share knowledge, and self-adopt teamwork roles. Analysis revealed the identification of both active and cohesive teams, disengaged students, and particular roles and behaviors that were lacking. Furthermore, sentiment analysis revealed that teamsmoved through positive and negative emotions over the course of developing their solution, toward satisfaction. The findings demonstrate the value of the detailed analysis of online teamwork. However, we propose the need for automated measures that provide real-time feedback to assist educators in the fair and efficient assessment of teamwork. We present a prototype system and recommendations, based on our analysis, for automated teamwork analysis tools.
机译:虽然团队合作已被确定为计算机科学(CS)毕业生的基本技能,但这些技能被确定为雇主缺乏,这表明需要更多主动措施教授和评估团队合作。在一个CS课程中,学生在团队中致力于为基于问题的问题创建Wiki解决方案。通过一个案例研究方法,我们使用手动内容分析和情感分析来测试开发的团队合作框架,以确定框架是否可以提供对学生的团队合作行为的洞察,并确定Wiki任务是否鼓励学生合作,分享知识,分享知识而自我采用团队合作。分析揭示了识别活跃和凝聚力的团队,脱离的学生,以及缺乏的特殊角色和行为。此外,情绪分析显示,在发展他们的解决方案的过程中,通过积极和负面情绪,朝着满意度来努力。调查结果展示了在线团队合作的详细分析的价值。但是,我们建议需要提供实时反馈的自动措施,以协助教育工作者在公平和高效的配合评估中。我们根据我们的分析提供了一种原型系统和建议,适用于自动团队合作分析工具。

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