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How the Entry Profiles and Early Study Habits Are Related to First-Year Academic Performance in Engineering Programs

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Listed:
  • Osvaldo Aquines Gutiérrez

    (Department of Physics and Mathematics, Universidad de Monterrey, Avenida Morones Prieto 4500, San Pedro Garza García 66238, NL, Mexico)

  • Diana Margarita Hernández Taylor

    (Department of Physics and Mathematics, Universidad de Monterrey, Avenida Morones Prieto 4500, San Pedro Garza García 66238, NL, Mexico)

  • Ayax Santos-Guevara

    (Department of Physics and Mathematics, Universidad de Monterrey, Avenida Morones Prieto 4500, San Pedro Garza García 66238, NL, Mexico)

  • Wendy Xiomara Chavarría-Garza

    (Department of Physics and Mathematics, Universidad de Monterrey, Avenida Morones Prieto 4500, San Pedro Garza García 66238, NL, Mexico
    CICFIM Facultad de Ciencias Físico Matemáticas, Universidad Autónoma de Nuevo León, San Nicolás de los Garza 66450, NL, Mexico)

  • Humberto Martínez-Huerta

    (Department of Physics and Mathematics, Universidad de Monterrey, Avenida Morones Prieto 4500, San Pedro Garza García 66238, NL, Mexico)

  • Ross K. Galloway

    (School of Physics & Astronomy, The University of Edinburgh, James Clerk Maxwell Building, King’s Buildings, Peter Guthrie Tait Road, Edinburgh EH9 3FD, UK)

Abstract

This paper explores how the entry profiles of engineering students are related to their academic performance during the first year of university in a sample of 255 first-year engineering students (77 females and 178 males) at a university in Northeast Mexico. The predictors used were the high school grade point average (HSGPA), Scholastic Aptitude Test (SAT) results, the first admission test, and a Spanish adaptation of the Survey of Study Habits and Attitudes Test (SSHA) from Brown and Holtzman. The SSHA adaptation was tested for internal consistency reliabilities via Cronbach’s alpha globally (0.92) and for the following categories: delay avoidance (DA: 0.79), work methods (WM: 0.81), teacher approval (TA: 0.89), and educational acceptance (EA: 0.74). The results were compared with those of other studies to validate their consistency. To assess the different entry profiles between high- and low-achieving students, we performed a Kruskal–Wallis test and found significant differences ( p < 0.001) between both profiles for all variables. We then measured the relationships between the variables and academic success by constructing a correlation table, where HSGPA, SAT, and DA showed the highest correlations: 0.61, 0.40, and 0.36, respectively. With these outcomes, a predictive model via a logistic regression ( R 2 = 0.52 ) was built to forecast first year academic performance in the specific context.

Suggested Citation

  • Osvaldo Aquines Gutiérrez & Diana Margarita Hernández Taylor & Ayax Santos-Guevara & Wendy Xiomara Chavarría-Garza & Humberto Martínez-Huerta & Ross K. Galloway, 2022. "How the Entry Profiles and Early Study Habits Are Related to First-Year Academic Performance in Engineering Programs," Sustainability, MDPI, vol. 14(22), pages 1-19, November.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:22:p:15400-:d:977884
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    References listed on IDEAS

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    1. Cohn, Elchanan & Cohn, Sharon & Balch, Donald C. & Bradley, James Jr., 2004. "Determinants of undergraduate GPAs: SAT scores, high-school GPA and high-school rank," Economics of Education Review, Elsevier, vol. 23(6), pages 577-586, December.
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