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International Conference on Computational Science and Its Applications

ICCSA 2018: Computational Science and Its Applications – ICCSA 2018 pp 398–413Cite as

Clustering Students Interactions in eLearning Systems for Group Elicitation

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10962))

Abstract

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.

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Author information

Authors and Affiliations

  1. Department of Mathematics and Computer Science, University of Florence, Florence, Italy

    Paolo Mengoni

  2. Department of Mathematics and Computer Science, University of Perugia, Perugia, Italy

    Alfredo Milani

  3. Department of Computer Science, Hong Kong Baptist University, Kowloon Tong, Hong Kong

    Alfredo Milani & Yuanxi Li

Authors
  1. Paolo Mengoni
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  2. Alfredo Milani
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  3. Yuanxi Li
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Corresponding author

Correspondence to Paolo Mengoni .

Editor information

Editors and Affiliations

  1. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  2. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  3. Covenant University, Ota, Nigeria

    Sanjay Misra

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Polytechnic University of Bari, Bari, Italy

    Carmelo M. Torre

  6. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  7. Monash University, Clayton, Victoria, Australia

    David Taniar

  8. Kyushu Sangyo University, Fukuoka shi, Fukuoka, Japan

    Bernady O. Apduhan

  9. Politecnico di Bari, Bari, Italy

    Eufemia Tarantino

  10. Myongji University, Yongin, Korea (Republic of)

    Yeonseung Ryu

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Mengoni, P., Milani, A., Li, Y. (2018). Clustering Students Interactions in eLearning Systems for Group Elicitation. In: Gervasi, O., et al. Computational Science and Its Applications – ICCSA 2018. ICCSA 2018. Lecture Notes in Computer Science(), vol 10962. Springer, Cham. https://doi.org/10.1007/978-3-319-95168-3_27

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  • DOI: https://doi.org/10.1007/978-3-319-95168-3_27

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