Mathematical Modeling of Student Performance in Mathematics: Exploring the Impact of Attendance, Study Habits, and Teaching Methods

Abstract

This study examined the impact of attendance rate, study hours, and teaching methods on the mathematics performance of students at Pangasinan State University Binmaley Campus. A quantitative design was employed, involving 50 students from four academic programs, selected through stratified random sampling. Data were collected using a structured questionnaire that gathered information on students' attendance records, self-reported study hours, and perceptions of teaching methods. Data analysis included descriptive statistics, correlation, regression, and ANOVA. The regression analysis revealed no statistically significant impact of attendance and study hours on assessment scores, indicating that other unmeasured factors, such as the quality of instruction, student motivation, and prior mathematical proficiency, may play a greater role in performance. The scatterplots supported this by showing substantial variability in scores at similar attendance and study hour levels, suggesting that simply being present in class or dedicating study time does not automatically translate to higher achievement. Among teaching methods, blended learning demonstrated slightly better outcomes compared to traditional and flipped methods, as shown by ANOVA results. However, the variability in scores across methods suggests that the effectiveness of instruction depends on student adaptability and engagement. The findings indicate that attendance and study habits alone are insufficient predictors of academic performance. Instead, factors such as instructional quality, learning environment, and student engagement should be prioritized. Future research should explore these aspects further to develop targeted interventions that enhance mathematics learning.