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Evaluating Student Behaviour on the MathE Platform - Clustering Algorithms Approaches

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Learning and Intelligent Optimization (LION 2022)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 13621))

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Abstract

The MathE platform is an online educational platform that aims to help students who struggle to learn college mathematics as well as students who wish to deepen their knowledge on subjects that rely on a strong mathematical background, at their own pace. The MathE platform is currently being used by a significant number of users, from all over the world, as a tool to support and engage students, ensuring new and creative ways to encourage them to improve their mathematical skills. This paper is addressed to evaluate the students’ performance on the Linear Algebra topic, which is a specific topic of the MathE platform. In order to achieve this goal, four clustering algorithms were considered; three of them based on different bio-inspired techniques and the k-means algorithm. The results showed that most students choose to answer only basic level questions, and even within that subset, they make a lot of mistakes. When students take the risk of answering advanced questions, they make even more mistakes, which causes them to return to the basic level questions. Considering these results, it is now necessary to carry out an in-depth study to reorganize the available questions according to other levels of difficulty, and not just between basic and advanced levels as it is.

This work has been supported by FCT Fundação para a Ciência e Tecnologia within the R &D Units Project Scope UIDB/00319/2020, UIDB/05757/2020, UIDP/05757/2020 and Erasmus Plus KA2 within the project 2021-1-PT01-KA220-HED-000023288. Beatriz Flamia Azevedo is supported by FCT Grant Reference SFRH/BD/07427/2021.

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Authors and Affiliations

  1. Research Centre in Digitalization and Intelligent Robotics (CeDRI), Instituto Politécnico de Bragança, Bragança, 5300-253, Portugal

    Beatriz Flamia Azevedo, Florbela P. Fernandes, Maria F. Pacheco & Ana I. Pereira

  2. Algoritmi Research Centre, University of Minho, Campus Azurém, Guimarães, 4800-058, Portugal

    Beatriz Flamia Azevedo, Ana Maria A. C. Rocha & Ana I. Pereira

  3. Center for Research and Development in Mathematics and Applications CIDMA, University of Aveiro, Aveiro, Portugal

    Maria F. Pacheco

Authors
  1. Beatriz Flamia Azevedo
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  2. Ana Maria A. C. Rocha
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  3. Florbela P. Fernandes
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  4. Maria F. Pacheco
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  5. Ana I. Pereira
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Corresponding author

Correspondence to Beatriz Flamia Azevedo .

Editor information

Editors and Affiliations

  1. SBA Research, Vienna, Austria

    Dimitris E. Simos

  2. Moscow Aviation Institute (National Research University), Moscow, Russia

    Varvara A. Rasskazova

  3. Università degli Studi di Milano-Bicocca, Milan, Italy

    Francesco Archetti

  4. Wilfrid Laurier University, Waterloo, ON, Canada

    Ilias S. Kotsireas

  5. University of Florida, Gainesville, FL, USA

    Panos M. Pardalos

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Flamia Azevedo, B., Rocha, A.M.A.C., Fernandes, F.P., Pacheco, M.F., Pereira, A.I. (2022). Evaluating Student Behaviour on the MathE Platform - Clustering Algorithms Approaches. In: Simos, D.E., Rasskazova, V.A., Archetti, F., Kotsireas, I.S., Pardalos, P.M. (eds) Learning and Intelligent Optimization. LION 2022. Lecture Notes in Computer Science, vol 13621. Springer, Cham. https://doi.org/10.1007/978-3-031-24866-5_24

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  • DOI: https://doi.org/10.1007/978-3-031-24866-5_24

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