Applying learning analytics to collaborative learning

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review


This study applies learning analytics to measure learners’ interaction, collaboration, and engagement during the process of collaborative learning in a MOOCs enabled course. The learning analytics provide instructors with visualized analysis of learners’ engagement for better understanding of learners’ collaboration with co-learners and interaction with course context. In addition, the learning analytics enable instructors to identify at-risk learners who have difficulties in collaboration and then trigger early intervention strategy. Our study shows that the learning analytics can successfully identify 85 % of students who were at-risk in collaboration, and over 60 % of the identified at-risk learners can improve their collaboration with early interventions.

Original languageEnglish
Title of host publicationCollaboration and Technology - 22nd International Conference, CRIWG 2016, Proceedings
EditorsTakaya Yuizono, Julita Vassileva, Hiroaki Ogata, Ulrich Hoppe
PublisherSpringer Verlag
ISBN (Print)9783319447988
StatePublished - 2016
Event22nd International Conference on Collaboration and Technology, CRIWG 2016 - Kanazawa, Japan
Duration: 14 Sep 201616 Sep 2016

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9848 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference22nd International Conference on Collaboration and Technology, CRIWG 2016


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