  We present FullBrain, a social e-learning platform where students share and
track their knowledge. FullBrain users can post notes, ask questions and share
learning resources in dedicated course and concept spaces. We detail two
components of FullBrain: a SIR system equipped with query autocomplete and
query autosuggestion, and a Leaderboard module to improve user experience. We
analyzed the day-to-day users' usage of the SIR system, measuring a
time-to-complete a request below 0.11s, matching or exceeding our UX targets.
Moreover, we performed stress tests which lead the way for more detailed
analysis. Through a preliminary user study and log data analysis, we observe
that 97% of the users' activity is directed to the top 4 positions in the
leaderboard.

Human-Computer Interaction