Anticipated Date of Graduation
Master of Science in Mathematical Sciences
The changes in student demographics and course modality led the researcher to examine cognitive and non-cognitive predictors of academic success in undergraduate mathematics courses. Linear regression analyses were used to determine if ACT and mathematics subscore, high school grade point average, GRIT Gauge® score, age and socioeconomic status were significant predictors of academic success in undergraduate mathematics courses. The results indicated that only high school grade point average was a significant predictor of academic success. In addition, independent samples t-tests were used to determine if there was a statistically significant difference in the mean GRIT® score between STEM and non-STEM majors, underclassman and upperclassman as well as between students enrolled in the mathematics course in an online or face to face modality. No statistically significant differences were found between any of the groups. The results of this study indicate that high school grade point average can be used to predict academic success in an initial mathematics course at a university.
Lamb, Amy, "Cognitive and Non-Cognitive Predictors of Academic Success in Undergraduate Mathematics Courses" (2022). Master of Science in Mathematics. 49.