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Computational Intelligence in Security for Information Systems Conference

International Conference on EUropean Transnational Education

CISIS 2019, ICEUTE 2019: International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019) pp 302–311Cite as

Automatic Categorization of Introductory Programming Students

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 951))

Abstract

Learning to program can be quite difficult for CS1 students. They must master language syntax, programming theory and problem-solving techniques in a short period of time. Consequently, a significant percentage of students struggle to successfully complete CS1.

Several studies have shown that students that do poorly the first weeks tend to fail at the end of the course. We would be able to help these students if we could automatically infer their learning stages during the course. One powerful tool that we can use to this end is cluster analysis: a class of computational methods that has been proved effective in analyzing complex datasets, including novice programmers’ learning trajectories.

Our aim in this study is to explore the feasibility of using exercises based on the neo-Piagetian model together with cluster analysis to infer the learning stage of the novice programmer. We have been able to automatically classify students at the end of an introductory programming course obtaining highly stable clusters compatible with Neo-Piagetian theory.

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Acknowledgments

This work was partially supported by the University of Granada and by the MINECO under its Competitive Research Programme (DPI2015-69585-R).

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Authors and Affiliations

  1. University of Granada, Granada, Spain

    Miguel A. Rubio

Authors
  1. Miguel A. Rubio
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Corresponding author

Correspondence to Miguel A. Rubio .

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Editors and Affiliations

  1. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Francisco Martínez Álvarez

  2. Data Science and Big Data Lab, Pablo de Olavide University, Seville, Spain

    Alicia Troncoso Lora

  3. University of Salamanca, Salamanca, Spain

    José António Sáez Muñoz

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

    Héctor Quintián

  5. University of Salamanca, Salamanca, Spain

    Emilio Corchado

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Rubio, M.A. (2020). Automatic Categorization of Introductory Programming Students. In: Martínez Álvarez, F., Troncoso Lora, A., Sáez Muñoz, J., Quintián, H., Corchado, E. (eds) International Joint Conference: 12th International Conference on Computational Intelligence in Security for Information Systems (CISIS 2019) and 10th International Conference on EUropean Transnational Education (ICEUTE 2019). CISIS ICEUTE 2019 2019. Advances in Intelligent Systems and Computing, vol 951. Springer, Cham. https://doi.org/10.1007/978-3-030-20005-3_31

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