Clustering students interactions in eLearning systems for group elicitation

Paolo Mengoni*, Alfredo Milani, Yuanxi Li

*Corresponding author for this work

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

10 Citations (Scopus)


In this work we introduce a novel Learning Analytics approach to identify students’ communities. The introduction of Learning Management Systems in higher education requires the educators to plan their Learning Design (LD) process with the online scenario in mind. We examined the blended learning environment where this process takes place in the Virtual Learning Environment. This allows the educators to track most of the students’ individual activities, but the communications may be excluded from tracking since the students can use side communications channels, such as face-to-face communication, instant messaging and social network platforms. Our approach, using the student-system interactions histories, helps to discover hidden relationships among the students. The elicited information about students’ groupings and social interactions’ evolution over time can be used by educators to adapt and improve their LD process, to find associations between students’ social interactions and their academic performance, as well as to promote team-based learning.

Original languageEnglish
Title of host publication18th International Conference on Computational Science and Its Applications (ICCSA 2018)
EditorsAna Maria Rocha, David Taniar, Elena Stankova, Carmelo M. Torre, Yeonseung Ryu, Eufemia Tarantino, Osvaldo Gervasi, Beniamino Murgante, Sanjay Misra, Bernady O. Apduhan
PublisherSpringer Verlag
Number of pages16
ISBN (Print)9783319951676
Publication statusPublished - 4 Jul 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


Conference18th International Conference on Computational Science and Its Applications, ICCSA 2018

Scopus Subject Areas

  • Theoretical Computer Science
  • Computer Science(all)

User-Defined Keywords

  • Cluster analysis
  • Hidden relationships identification
  • Learning analytics
  • Student interactions


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