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Academic Behavior Analysis in Virtual Courses Using a Data Mining Approach

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Applied Informatics (ICAI 2019)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 1051))

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Abstract

Virtual education is one of the educational trends of the 21st century; however knowing the perception of students is a new challenge. This article presents a proposal to define the essential components for the construction of a model for the analysis of the records given by the students enrolled in courses in a virtual learning platform (VLE). The article after a review of the use of data analytics in VLE presents a strategy to characterize the data generated by the student according to the frequency and the slice of the day and week that access the material. With these metrics, clustering analysis is performed and visualized through a map of self-organized Neural Networks. The results presented correspond to five courses of a postgraduate career, where was found that students have greater participation in the forums in the daytime than in the nighttime. Also, they participate more during the week than weekends. These results open the possibility to identify possible early behaviors, which let to implement tools to prevent future desertions or possible low academic performance.

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Author information

Authors and Affiliations

  1. Universidad Nacional Abierta y a Distancia, Bogota, Colombia

    Dario Delgado-Quintero, Diego Aranda-Lozano & Pablo Munevar-Garcia

  2. Universidad de Bogota Jorge Tadeo Lozano, Bogota, Colombia

    Olmer Garcia-Bedoya

  3. OCOX AI, Bogota, Colombia

    Cesar O. Diaz

Authors
  1. Dario Delgado-Quintero
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  2. Olmer Garcia-Bedoya
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  3. Diego Aranda-Lozano
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  4. Pablo Munevar-Garcia
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  5. Cesar O. Diaz
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Corresponding author

Correspondence to Olmer Garcia-Bedoya .

Editor information

Editors and Affiliations

  1. Universidad Distrital Francisco Jose de Caldas, Bogota, Colombia

    Hector Florez

  2. Universidad Nacional de Loja, Loja, Ecuador

    Marcelo Leon

  3. Universidad a Distancia de Madrid, Madrid, Spain

    Jose Maria Diaz-Nafria

  4. Universidad Complutense de Madrid, Madrid, Spain

    Simone Belli

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Delgado-Quintero, D., Garcia-Bedoya, O., Aranda-Lozano, D., Munevar-Garcia, P., Diaz, C.O. (2019). Academic Behavior Analysis in Virtual Courses Using a Data Mining Approach. In: Florez, H., Leon, M., Diaz-Nafria, J., Belli, S. (eds) Applied Informatics. ICAI 2019. Communications in Computer and Information Science, vol 1051. Springer, Cham. https://doi.org/10.1007/978-3-030-32475-9_2

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  • DOI: https://doi.org/10.1007/978-3-030-32475-9_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-32474-2

  • Online ISBN: 978-3-030-32475-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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