Predictive Relationship Between Mathematics Pathways and Success Indicators at a Community College
Date of Conferral
Doctor of Education (Ed.D.)
College algebra, a gateway course, has had the lowest passing rate for students of any freshman course. While research exists on the implementation of quantitative reasoning at 4-year institutions, little understanding exists on whether different mathematical pathways predict non-Science, Technology, Engineering, and Mathematics (non-STEM) student mathematics success indicators. This study’s purpose was to determine if mathematics pathways (college algebra or quantitative reasoning) predict non-STEM student mathematics success indicators such as course retention, course passage, continuation to one semester after mathematics course passage, graduation within 1 year, and transfer-out within one semester after mathematics course completion while controlling for preexisting knowledge. Holland’s personal-environment fit theory was the framework for this study. One research question with 5 hypotheses determined if mathematics pathways predicted the 5 non-STEM success indicators controlling for ACCUPLACER Elementary Algebra test scores. A quantitative predictive design was employed using a census of 138 records on non-STEM students enrolled in one of the pathway courses and who took the ACCUPLACER Elementary Algebra test during the Fall 2018 and Spring 2019 semesters. Binary logistic regression analysis was conducted for each criterion variable. The results indicated that mathematics pathways did not predict the five success indicators. Findings were not consistent with the literature nor with Holland’s theory. This study offers implications for positive social change by offering evidence to institutions of higher education that students should be allowed to enroll in the mathematics pathway that best prepares them for their intended programs of study.
Wilkinson, Anthony Raynard, "Predictive Relationship Between Mathematics Pathways and Success Indicators at a Community College" (2020). Walden Dissertations and Doctoral Studies. 9012.