In this project, we gather extensive organizational and performance data from digital traces (open lab notebooks), and questionnaires questionnaires across 3,000+ interdisciplinary teams participating in the international Genetically Engineered Machine (iGEM) synthetic biology student competition. Using this data we study how team interactions and team diversity impact the performance of iGEM teams and the learning experience of the students. How do students collaborate? How are subgroups formed? What is the frequency of interactions with mentors/PIs? How do these interactions lead to better learning (skill spreading), productivity (BioBricks produced / project size), creativity (project uniqueness) or just success in the competition (medals, prizes, winners)?
To answer these questions, we analyse data and collect surveys from iGEM participants to conduct a quantitative, multi-year, large-scale study. The survey for 2023 can be found here. All this data is anonymised, kept secured on a server, and participation to each data collection is completely voluntary.
You can also check our iGEM resource paper and the publicly available iGEM team dataset that we have collected from wiki pages. Finally, here are some slides about the project.
Interaction Data Lab 