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Impact of Time Granularity on Histories Binary Correlation Analysis

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Computational Science and Its Applications – ICCSA 2019 (ICCSA 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11620))

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Abstract

Activities taken by students within a Virtual Learning Environment (VLE) can be represented by using binary student histories. Virtual Learning Environments allow educators to track most of the students’ individual activities that can be used to elicit the students social communities. In this work, we analyse the impact of granularity in the social community elicitation. Granularity can be seen as the resolution of the student history vectors where each time slot is directly dependent from this value. Indeed, the higher is the resolution of the students histories the more precise is the representation of their actions within the VLE. When comparing the histories using various similarity measures to elicit the students’ groups, we find the optimal granularity and demonstrate that there is a resolution limit where the similarity measures will not help to distinguish the social communities.

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Author information

Authors and Affiliations

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

    Paolo Mengoni & Alfredo Milani

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

    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. Covenant University, Ota, Nigeria

    Sanjay Misra

  2. University of Perugia, Perugia, Italy

    Osvaldo Gervasi

  3. University of Basilicata, Potenza, Italy

    Beniamino Murgante

  4. Saint Petersburg State University, Saint Petersburg, Russia

    Elena Stankova

  5. Saint Petersburg State University, Saint Petersburg, Russia

    Vladimir Korkhov

  6. Polytechnic University of Bari, Bari, Italy

    Carmelo Torre

  7. University of Minho, Braga, Portugal

    Ana Maria A.C. Rocha

  8. Monash University, Clayton, VIC, Australia

    David Taniar

  9. Kyushu Sangyo University, Fukuoka, Japan

    Bernady O. Apduhan

  10. Polytechnic University of Bari, Bari, Italy

    Eufemia Tarantino

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Mengoni, P., Milani, A., Li, Y. (2019). Impact of Time Granularity on Histories Binary Correlation Analysis. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11620. Springer, Cham. https://doi.org/10.1007/978-3-030-24296-1_27

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  • DOI: https://doi.org/10.1007/978-3-030-24296-1_27

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