Investigating Hackathons with Collaboration Analytics

Hackathons, collaborative events where individuals form teams to address specific problems, have gained significant traction across various domains since the early 2000s. Due to their time-bound nature, these events present unique challenges, necessitating the rapid establishment of collaboration methods and diverse support from hackathon organizers and mentors. Studying these events offers insights into emerging group work patterns, but tracking all teams during a hackathon is challenging. Traditional methods like surveys and log file analysis provide limited insights into team interactions. To address this, the following paper introduces a comprehensive data collection approach, encompassing detailed observations, speech transcripts, and wearable badges. .Furthermore, it explores using Multimodal Collaboration Analytics (CA) and Sociometric wearable devices (SWDs) to study human behavior in hackathons. The primary research aim is to understand collaboration in absentia, leading to questions about designing technologies to capture collaboration and visualize group interactions. The paper discusses the iterative design approach for a collaboration analytics platform. The paper presents initial findings, challenges, and questions related to the study of collaboration in hackathons and how such tools can support the events and offer insight into collaboration.