Research Article

Mathematical Models in Predicting Retention of STEM Students in Pre-Calculus

Norman Cuello Barroso 1 *
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1 Tanza National Comprehensive High School, PHILIPPINES* Corresponding Author
International Journal of Pedagogical Development and Lifelong Learning, 1(1), 2020, ep2004, https://doi.org/10.30935/ijpdll/8342
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ABSTRACT

This study aimed to determine the mathematical models in predicting retention of STEM students in Pre-Calculus. The study utilized a non-experimental research specifically a cross-sectional predictive design. The independent variables in the study are the Grade Point Average (GPA) in Mathematics 10, General Weighted Average (GWA) in grade 10, National Career Assessment Examination (NCAE) - mathematical ability, NCAE - STEM results, gender and family monthly income. The dependent variable is the retention of STEM students in Pre-Calculus. The instruments in the study are Pre-Calculus Retention Test (PRT), interview and documentary analysis. The PRT was validated by five experts and underwent reliability testing with a Cronbach alpha value of 0.524. Percentage, mean, standard deviation, Pearson Product Moment Coefficient of Correlation and Multiple Regression Analysis were applied in the study. The researcher used IBM SPSS version 20 in analyzing the data gathered. The study developed two mathematical models that can predict retention of STEM students in Pre-Calculus. Using the standardized coefficients, the formula in predicting retention of STEM students in Pre-Calculus are y = 0.035x1 + 0.632x2 - 31.462 and y = 0.033x1 + 0.599x3 - 28.370 where y is PRT scores of the STEM students, x1 is NCAE-Mathematical Ability scores, x2 is GPA in Mathematics 10 and x3 is GWA in grade 10. . It can be gleaned on the mathematical models that the best predictor of the retention of STEM students in Pre-Calculus are GPA in Mathematics 10 and GWA in grade 10.
Keywords: pre-calculus retention test, mathematical models, multiple regression analysis, NCAE

CITATION (APA)

Barroso, N. C. (2020). Mathematical Models in Predicting Retention of STEM Students in Pre-Calculus. International Journal of Pedagogical Development and Lifelong Learning, 1(1), ep2004. https://doi.org/10.30935/ijpdll/8342

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