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Analysis of Students’ Online Interactions in the Covid Era from the Perspective of Anomaly Detection

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14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European Transnational Educational (CISIS 2021 and ICEUTE 2021) (CISIS - ICEUTE 2021)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1400))

Abstract

During the pandemic, most of the teaching has been done online. The lack of face-to-face interaction has many undesirable effects, including students being less focused, not receiving feedback on how they are approaching the current topic/task, and an increased risk of cheating. It is expected that those students with similarly graded assignments/exams would have similar interactions during online teaching sessions. The opposite is an anomaly, for better or worse. It is possible to find out if assignments/exams are legitimate by using anti-plagiarism tools or by carefully examining submissions, but it is time-consuming and only protects against one type of fraud. In this paper, we propose to apply anomaly detection techniques to the students’ interactions to reduce the number of assignments/exams that need to be checked against fraud.

This work has been funded by the Ministry of Science and Innovation of the Government of Spain and by the FEDER funds of the European Community through projects with codes PID2020-112726RB-I00 and TIN2017-84804-R.

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Authors and Affiliations

  1. Oviedo University, Oviedo, Spain

    José Otero, Luciano Sánchez, Luís A. Junco & Inés Couso

Authors
  1. José Otero
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  2. Luciano Sánchez
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  3. Luís A. Junco
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  4. Inés Couso
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Corresponding author

Correspondence to José Otero .

Editor information

Editors and Affiliations

  1. Department of Computing, Electronics and Communication Technologies, University of Deusto, Bilbao, Spain

    Juan José Gude Prego

  2. Department of Computing, Electronics and Communication Technologies, University of Deusto, Bilbao, Spain

    José Gaviria de la Puerta

  3. Department of Mechanics, Design and Industrial Management, University of Deusto, Bilbao, Spain

    Pablo García Bringas

  4. Department of Industrial Engineering, University of A Coruña, Ferrol, Spain

    Héctor Quintián

  5. BISITE Research Group, University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Otero, J., Sánchez, L., Junco, L.A., Couso, I. (2022). Analysis of Students’ Online Interactions in the Covid Era from the Perspective of Anomaly Detection. In: Gude Prego, J.J., de la Puerta, J.G., García Bringas, P., Quintián, H., Corchado, E. (eds) 14th International Conference on Computational Intelligence in Security for Information Systems and 12th International Conference on European Transnational Educational (CISIS 2021 and ICEUTE 2021). CISIS - ICEUTE 2021. Advances in Intelligent Systems and Computing, vol 1400. Springer, Cham. https://doi.org/10.1007/978-3-030-87872-6_30

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