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

Osvaldo Aquines Gutiérrez, Diana Margarita Hernández Taylor, Ayax Santos Guevara, Wendy Xiomara Chavarria-Garza, Humberto Martínez-Huerta, Ross K. Galloway

Research output: Contribution to journalArticlepeer-review

3 Citations (Scopus)


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 ((Formula presented.)) was built to forecast first year academic performance in the specific context.

Original languageEnglish
Article number15400
Issue number22
Publication statusPublished - 19 Nov 2022

Bibliographical note

Publisher Copyright:
© 2022 by the authors.


Dive into the research topics of 'How the Entry Profiles and Early Study Habits Are Related to First-Year Academic Performance in Engineering Programs'. Together they form a unique fingerprint.

Cite this