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Early Dropout Prediction Model: A Case Study of University Leveling Course Students

Author

Listed:
  • Iván Sandoval-Palis

    (Departamento de Formación Básica, Escuela Politécnica Nacional, Quito 17-01-2759, Ecuador)

  • David Naranjo

    (Departamento de Formación Básica, Escuela Politécnica Nacional, Quito 17-01-2759, Ecuador)

  • Jack Vidal

    (Department of Developmental Psychology and Didactics, University of Alicante, 03690 Alicante, Spain)

  • Raquel Gilar-Corbi

    (Department of Developmental Psychology and Didactics, University of Alicante, 03690 Alicante, Spain)

Abstract

The school-dropout problem is a serious issue that affects both a country’s education system and its economy, given the substantial investment in education made by national governments. One strategy for counteracting the problem at an early stage is to identify students at risk of dropping out. The present study introduces a model to predict student dropout rates in the Escuela Politécnica Nacional leveling course. Data related to 2097 higher education students were analyzed; a logistic regression model and an artificial neural network model were trained using four variables, which incorporated student academic and socio-economic information. After comparing the two models, the neural network, with an experimentally defined architecture of 4–7–1 architecture and a logistic activation function, was selected as the model that should be applied to early predict dropout in the leveling course. The study findings show that students with the highest risk of dropping out are those in vulnerable situations, with low application grades, from the Costa regime, who are enrolled in the leveling course for technical degrees. This model can be used by the university authorities to identify possible dropout cases, as well as to establish policies to reduce university dropout and failure rates.

Suggested Citation

  • Iván Sandoval-Palis & David Naranjo & Jack Vidal & Raquel Gilar-Corbi, 2020. "Early Dropout Prediction Model: A Case Study of University Leveling Course Students," Sustainability, MDPI, vol. 12(22), pages 1-17, November.
    • Handle: RePEc:gam:jsusta:v:12:y:2020:i:22:p:9314-:d:442527
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    References listed on IDEAS

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    1. Cindi Mason & Janet Twomey & David Wright & Lawrence Whitman, 2018. "Predicting Engineering Student Attrition Risk Using a Probabilistic Neural Network and Comparing Results with a Backpropagation Neural Network and Logistic Regression," Research in Higher Education, Springer;Association for Institutional Research, vol. 59(3), pages 382-400, May.
    2. Donggeun Kim & Seoyong Kim, 2018. "Sustainable Education: Analyzing the Determinants of University Student Dropout by Nonlinear Panel Data Models," Sustainability, MDPI, vol. 10(4), pages 1-18, March.
    3. John M. Braxton & Jeffrey F. Milem & Anna Shaw Sullivan, 2000. "The Influence of Active Learning on the College Student Departure Process," The Journal of Higher Education, Taylor & Francis Journals, vol. 71(5), pages 569-590, September.
    4. Rong Chen & Stephen L. DesJardins, 2010. "Investigating the Impact of Financial Aid on Student Dropout Risks: Racial and Ethnic Differences," The Journal of Higher Education, Taylor & Francis Journals, vol. 81(2), pages 179-208, March.
    5. Camelia Truta & Luminita Parv & Ioana Topala, 2018. "Academic Engagement and Intention to Drop Out: Levers for Sustainability in Higher Education," Sustainability, MDPI, vol. 10(12), pages 1-11, December.
    6. Tin-Chun Lin & William Wei-Choun Yu & Yi-Chi Chen, 2012. "Determinants and probability prediction of college student retention: new evidence from the Probit model," International Journal of Education Economics and Development, Inderscience Enterprises Ltd, vol. 3(3), pages 217-236.
    7. J. -P. Vandamme & N. Meskens & J. -F. Superby, 2007. "Predicting Academic Performance by Data Mining Methods," Education Economics, Taylor & Francis Journals, vol. 15(4), pages 405-419.
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    Cited by:

    1. Inmaculada Sureda-García & Rafael Jiménez-López & Olaya Álvarez-García & Elena Quintana-Murci, 2021. "Emotional and Behavioural Engagement among Spanish Students in Vocational Education and Training," Sustainability, MDPI, vol. 13(7), pages 1-15, April.
    2. Raquel Gilar-Corbi & Teresa Pozo-Rico & Juan-Luis Castejón & Tarquino Sánchez & Ivan Sandoval-Palis & Jack Vidal, 2020. "Academic Achievement and Failure in University Studies: Motivational and Emotional Factors," Sustainability, MDPI, vol. 12(23), pages 1-14, November.

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