Anticipated Date of Graduation
Master of Science in Mathematical Sciences
This study examines the effectiveness of latent growth models for clustering middle school math students to predict the high school academic outcome, as measured by the number of AP STEM courses passed in high school. Middle school math performance is based on the 6th, 7th, and 8th grade Rhode Island Comprehensive Assessment System (RICAS) scores. The study also examines whether demographic factors can predict student performance clusters. These demographic factors are High-risk status (HAR), eligibility for a free lunch program (FRP), and/or an individualized learning plan (IEP). The study concluded that the students’ growth can be grouped into four clusters. In addition, it demonstrated that cluster membership was associated with demographic predictors consistent with expected historical trends. Furthermore, the study found that the high school performance of students can be predicted by their membership in a growth cluster.
Habach, Sam, "Predicting Students’ Performance Using Growth Models" (2022). Master of Science in Mathematics. 44.