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Educational Data Mining: A Profile Analysis of Brazilian Students

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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 11619))

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Abstract

This paper presents an analysis of data referring to the profile of Brazilian students in the year 2016, according to the Higher Education Census. The information provided by this census is used to carry out various analyses related to the current situation of Brazilian education, as well as the profile of students and institutions. In this work, we analyze the modality of courses offered by educational institutions, investigating the profile and the quantitative of students who have scholarship, and how they enter the courses. We also investigate the distribution of students according to the informed skin color/race. The method used to conduct this research involved the application of the steps proposed by the CRISP-DM Reference Model and the use of the Apriori association algorithm to identify and analyze the data set. The results show that 30% of students choose not to report their skin color; Of those who reported, 37.4% are white and 6% are black. Approximately 82% of the students entered higher education through the traditional method (entrance examination), and 82.3% of the male and 77.2% of the female opted for face-to-face courses.

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Acknowledgment

This research work has the support of the Research Support Foundation of the Federal District (FAPDF).

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Authors and Affiliations

  1. University of Brasília (UnB), Brasília, DF, 70910-900, Brazil

    Edna Dias Canedo, Rhandy Rafhael de Carvalho, Ruyther Parente da Costa, Giovanni Almeida Santos & Marcio Vinicius Okimoto

  2. Lutheran University Center of Palmas (CEULP), Palmas, TO, Brazil

    Heloise Acco Tives Leão

Authors
  1. Edna Dias Canedo
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  2. Heloise Acco Tives Leão
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  3. Rhandy Rafhael de Carvalho
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  4. Ruyther Parente da Costa
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  5. Giovanni Almeida Santos
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  6. Marcio Vinicius Okimoto
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Corresponding author

Correspondence to Edna Dias Canedo .

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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Canedo, E.D., Leão, H.A.T., de Carvalho, R.R., da Costa, R.P., Santos, G.A., Okimoto, M.V. (2019). Educational Data Mining: A Profile Analysis of Brazilian Students. In: Misra, S., et al. Computational Science and Its Applications – ICCSA 2019. ICCSA 2019. Lecture Notes in Computer Science(), vol 11619. Springer, Cham. https://doi.org/10.1007/978-3-030-24289-3_35

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  • DOI: https://doi.org/10.1007/978-3-030-24289-3_35

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-24288-6

  • Online ISBN: 978-3-030-24289-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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