Anticipated Date of Graduation
Summer 2020
Document Type
Thesis
Degree Name
Master of Science in Mathematical Sciences
Department
Mathematics
First Advisor
Douglas Darbro
Abstract
Objectives. To examine the internal consistency and predictive validity of a teacher-made post-test administered to developmental math students at Shawnee State University. Teacher-made tests receive little attention among published research due to the perceived lack of generalizability. However, granting more attention to teacher-made tests could help researchers to uncover broader trend within post-secondary institutions in the United States. Methods. Principal component analysis with the varimax rotation was used to examine the factor structure of 18 test-items completed by 171 students. Then, multiple logistic regression models were calculated to determine if the post-test predicted if a student would earn a C or higher in their gateway math course. Age, race, high school GPA, and ACT math score were used as covariates. Results. Three primary domains emerged during Principal Component Analysis, with the suggested names: Algebra, Arithmetic, Linear Equations. The logistic regression models did not indicate that the test was statistically reliable for predicting which students would earn a C or higher in their gateway math course. Introducing age, race, high school GPA, and ACT math score did not have a meaningful impact on any of the models. Conclusions. The test-items used for PCA align with the intended course objectives. The test-items, and by extension the course objectives, do not adequately predict which student’s will earn a final letter grade of C or higher in their gateway math course. Since the course objectives appear reasonable, further research is suggested to investigate whether other variables could better predict student outcomes.
Recommended Citation
Schweinsberg, Robert Zachary, "Examining the Internal Consistency and Predictive Validity of a Post-Test Administered to Developmental Math Students" (2020). Master of Science in Mathematics. 21.
https://digitalcommons.shawnee.edu/math_etd/21