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FullBrain: A social E-learning platform

Contributo in Atti di convegno
Data di Pubblicazione:
2021
Abstract:
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 Social Information Retrieval (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.
Tipologia CRIS:
04.01 - Contributo in atti di convegno
Keywords:
E-learning; Gamification; Leaderboards; Social information retrieval; Social networks
Elenco autori:
Biasini, M.; Carmignani, V.; Ferro, N.; Filianos, P.; Maistro, M.; Di Nunzio, G. M.
Autori di Ateneo:
DI NUNZIO GIORGIO MARIA
FERRO NICOLA
Link alla scheda completa:
https://www.research.unipd.it/handle/11577/3386173
Link al Full Text:
https://www.research.unipd.it//retrieve/handle/11577/3386173/1411126/paper3.pdf
Titolo del libro:
Proc. 17th Italian Research Conference on Digital Libraries (IRCDL 2021)
Pubblicato in:
CEUR WORKSHOP PROCEEDINGS
Journal
CEUR WORKSHOP PROCEEDINGS
Series
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