The study examined factors that will predict Grade 11 STEM students' academic achievement in Mathematics in the Division of Quirino with the ultimate view of enhancing the learning of Mathematics of STEM students. Two hundred and twenty-eight Grade 11 STEM students were randomly selected from five secondary schools offering STEM strands in Quirino Province. This study focused on descriptive correlational research design. Descriptive statistics such as frequency count was utilized to describe the different selected independent variables. In addition, the data collected were analyzed using multiple linear regression analysis. This study has established that among the selected independent variables, there are five statistically significant predictor variables in Grade 11 STEM students' academic performance in Mathematics. The results showed that the five predictor variables have 77.80% of the total variance observed in achievement accounted for by the independent variables. By implication, significant relationships existed between academic performance in Mathematics and the student's Grade 10 general weighted average and Mathematics final grade, libraries' functionality, teachers' educational attainment and length of service. The relative effects of the predictor variables revealed that teachers' educational attainment to Mathematics achievement had the greatest, followed by libraries" functionality, Grade 10 general weighted average, Grade 10 Mathematics final grade, and lastly by the teachers' length of service. However, the latter gives a negative relationship with the students' academic achievement in Mathematics. Furthermore, the study came upwith a proposed intervention plan to help improve the students' academic performance in Mathematics.

Keywords: Multiple Linear Regression, STEM Students, Mathematics Academic Performance, Intervention Plan

Thesis (Master of Science in Teaching- Mathematics)

Includes appendices and bibliographical references.