The iGEM TIES project (Team IntEraction Study) explores how iGEM team interactions, collaborations, diversity and transdisciplinarity impact their global performance and the learning experience of the students. For this study, we collect self-reported team collaborations from the CoSo app , along with answers to an in-depth questionnaire about team dynamics and individual backgrounds .
Below you can find some visualisations from the CoSo data collected during the summer of the 2020 competition on a set of pilot teams. This year was very special, with the pandemic creating extraordinary conditions for such a study to take place. Here we show some preliminary insights into some of the data, with the hope to extend this study further in future competition.
First we wonder how do team members participate to various tasks in their team. We collected self-reported data about which team member did which task, and how many times. This bubble graph represents for each team the proportion of work invested in each task (size of the task bubble), and their repartition between team members (size of the team member bubble). We can see for example that some tasks involve a lot of team members (team meetings, meetups, brainstorming), while other tasks are more specialized (analysing results, hardware development), showing the importance of planning and synchronizing as a whoel team, and delegating subtasks to subgroups. Note that individual team member names have been anonymised.
Next we show what are the tasks that are most mentionned in the self-reports. We ordered tasks in the barplot by decreasing number of mentions across all teams. This shows the importance of team-wide synchronisations (team meetings, task planning, meetups) during the summer period!
Now that we have seen what the important tasks are, we wonder how team members interacted across these tasks. In the self-reports, each team member could nominate other team members that they worked on a given task. This allows to get finer insights on team collaborations across tasks, and eventually build team interaction networks.
For each team we build a network (we do not show teams with only one team member self-reporting, limitting here to 5 teams). In these team networks, each link is weighted by the number of tasks done in collaboration between any two members (you can zoom in to better see the weights). You can use the filters below to highlight strong collaborations only, or to select only the network corresponding to a single task. For example, selecting a weight threshold of 7 allows to see some subteam structure in the densest team network. Note that this is only based on self-reports, and as such is not fully representative of all team interactions. Further insights can be gained from the questionnaire, make sure to have a look!
Finally, we examine how task importance evolves during this period . For this we compute for each week the proportion of tasks done across teams. Note that small amount of data in September limits the interpretation. We see that brainstorming and team meetings are important before the summer time intense period of work. We also see specific dates corresponding to team-specific events (such as education event). Further insights would be gained by extending the data collection to the early stages (March/April) as well as later stages (Sept/Oct).