PREDICTING MATHEMATICS PERFORMANCE AMONG GRADE 11 STUDENTS IN THE PHILIPPINES: EVIDENCE FROM REGRESSION MODELING AND MULTICOLLINEARITY ANALYSIS

Mathematics performance is important for academic success and future opportunities among senior high school students in the Philippines. This study aimed to predict Mathematics performance among Grade 11 students using regression modeling and multicollinearity analysis. A quantitative research design was employed using secondary data from prior studies involving Grade 11 learners. The predictor variables included students’ attitudes toward Mathematics, academic strand, sex, monthly family income, and parental educational attainment. Data were analyzed using correlation analysis, collinearity diagnostics, and multiple linear regression with stepwise procedures. Results showed that students’ attitudes toward Mathematics were the most frequently identified influential factor. Regression analysis further revealed that High School Strand (STEM) and low monthly family income were significant predictors of Mathematics performance (p < 0.05), while sex and father’s educational attainment showed marginal significance. Multicollinearity diagnostics indicated interrelationships among several predictors, particularly those related to socioeconomic and parental factors. The final regression model identified High School Strand (STEM), low family income, and sex as the most stable predictors of Mathematics performance. These findings highlight the combined influence of academic preparation and socioeconomic context in shaping student achievement. The study underscores the importance of addressing both cognitive and contextual factors in improving Mathematics outcomes in Philippine senior high schools.