We propose FairCollab, an AI-driven analytics extension designed to promote fairness and transparency in teamwork. FairCollab collects log data from Learning Management Systems (LMS) and collaboration platforms such as Google Docs, Sheets, and Slides, and visualizes key teamwork indicators, engagement levels, activity consistency, task completion, communication balance, and contribution distribution, within an integrated LMS dashboard. The main objectives of FairCollab are to ensure fair participation, strengthen accountability, motivate less active members, and support reflective learning in collaborative settings. Students can request AI generated feedback, reflect on their individual and group contributions, and engage in constructive discussions to enhance collaboration and learning outcomes. Educators gain a clear, data-driven overview that helps them identify group dynamics and provide timely support. By promoting transparency, self-awareness, and equitable participation, FairCollab directly enhances active learning in digital higher education, helping students organize, monitor, and improve teamwork processes. Success can be evaluated through increased engagement metrics, balanced contribution patterns, and positive feedback in self-reported satisfaction surveys. Over time, adoption of the extension for multiple courses would demonstrate scalability, sustained impact, and the value of FairCollab as a transformative tool for collaborative learning analytic.
https://www.figma.com/design/wgFkPK8LPhPLfCumcW0am9/Eduhack?node-id=0-1&p=f