Academic Choices Influencing Completion Rates for Developmental Math Students: A Logistic Regression Study

Document Type

Dissertation

Degree Name

Doctor of Education (Ed.D)

Department

Curriculum and Instruction

Date of Award

Fall 2025

Abstract

Low success rates in developmental education (DE) are an ongoing concern nationwide. In 2023, Texas House Bill 8 tied funding to completion rates, which increases the emphasis on completion for DE students in Texas. The purpose of this study is to explore how the initial academic choices of first-time-in-college (FTIC) students impact student outcomes. Interventions such as corequisite courses, math pathways, and distance education are designed to increase access and equity for developmental math students. Using the Texas House Bill 8 definition of completion, this research aims to identify which combination of strategies has the most significant impact on student completion rates. Previous research highlights the challenges of DE, emphasizing innovations such as corequisite instruction, which combines credit and developmental coursework, and math pathways, which align math content with students’ academic goals. It also explores the mixed successes of distance education on DE student outcomes. This quantitative study employs Pearson’s chi-square test for independence and logistic regression analysis to examine the relationship between course characteristics and long-term completion and to review the predictive value of course characteristics on long-term completion for DM students while controlling for demographic factors such as age, gender, race, and placement test scores. The population considered in the study is FTIC community college students in Texas who took the Texas Success Initiative Assessment (TSIA) math placement test, scored below the college-ready threshold of 350, and enrolled in a developmental math (DM) course. Archival data on FTIC developmental math students from a large suburban community college in Texas between the fall 2017 and fall 2019 semesters were used as the sample. The findings of this study aim to inform institutional policies and practices by identifying statistically significant predictors of student success. The study aspires to enhance academic advising, course scheduling, and program design so that community colleges in Texas can increase their funding and support completion for underprepared math students.

Advisor

Dimitra Smith

Subject Categories

Education

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