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 teams moved 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.

Industry has called upon academia to better prepare Computer Science graduates for teamwork, especially in developing the soft skills necessary for collaborative work. However, the teaching and assessment of teamwork is not easy, with instructors being pressed for time and a lack of tools available to efficiently analyse student teamwork, where large cohorts are involved.We have developed a teamwork dashboard, founded on learning analytics, learning theory and teamwork models that analyses students' online teamwork discussion data and visualises the team mood, role distribution and emotional climate. This tool allows educators to easily monitor teams in real-time. Educators may use the tool to provide students with feedback about team interactions as well as to identify problematic teams. We present a case study, trialing the dashboard on one university Computer Science course and include reflections from the course lecturer to determine its utility in monitoring online student teamwork.

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