Community graph elicitation from students’ interactions in virtual learning environments

Paolo Mengoni*, Alfredo Milani, Yuanxi Li

*Corresponding author for this work

Research output: Chapter in book/report/conference proceedingConference contributionpeer-review

5 Citations (Scopus)

Abstract

In this work we introduce a novel graph-based approach to elicit students’ communities. Teaching, in the blended learning environment, is delivered as a mixture of online and offline activities. While the online activities can be tracked and analysed in the Virtual Learning Environment, the offline activities fall out of the educators’ control scope. In this educational setting, communications take place using side channels, such as the instant messaging applications and social network platform. Using our approach, the students’ groupings and social interactions can be elicited by analysing the student-system interactions. The co-occurrence of interactions among the students give information about their social connections. This conveys information useful to elicit the students’ interaction graph and the student communities contained in it. Students’ leader-follower community structure can be elicited starting from the interaction network. This can empower teachers to plan and revise their Learning Designs as well as to identify situations that need teacher’s intervention, e.g. students at risk of failing the exam and/or dropping the studies.

Original languageEnglish
Title of host publication18th International Conference on Computational Science and Its Applications (ICCSA 2018)
EditorsOsvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Elena Stankova, Carmelo M. Torre, Ana Maria A.C. Rocha, David Taniar, Bernady O. Apduhan, Eufemia Tarantino, Yeonseung Ryu
PublisherSpringer Verlag
Pages414-425
Number of pages12
ISBN (Print)9783319951676
DOIs
Publication statusPublished - 2018
Event18th International Conference on Computational Science and Its Applications, ICCSA 2018 - Melbourne, Australia
Duration: 2 Jul 20185 Jul 2018

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume10962 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference18th International Conference on Computational Science and Its Applications, ICCSA 2018
Country/TerritoryAustralia
CityMelbourne
Period2/07/185/07/18

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Community detection
  • Graph analysis
  • Modularity maximization
  • Student interactions

Fingerprint

Dive into the research topics of 'Community graph elicitation from students’ interactions in virtual learning environments'. Together they form a unique fingerprint.

Cite this