Statistical analysis of student performance in redesigned developmental mathematics courses

WCU Author/Contributor (non-WCU co-authors, if there are any, appear on document)
Malgorzata J. Chockla (Creator)
Institution
Western Carolina University (WCU )
Web Site: http://library.wcu.edu/
Advisor
John Wagaman

Abstract: Colleges and universities are focusing their efforts on improving the instruction in developmental mathematics courses. In 2013, community colleges in North Carolina were in the process of implementing the redesigned approach to teaching developmental mathematics with the goal of improving student graduation rates. The purpose of this study is to investigate the differences in academic improvements of developmental mathematics students in order to evaluate the effectiveness of the redesigned MyMathLab (MML) courses. This study investigates the following variables: College Placement Test (CPT) scores in Algebra, Arithmetic, Reading Comprehension, and Sentence Structure, gender, and instructional method. Multiple regression analyses were performed using the statistical computing software, R. In Phase I of this study, two linear regression models were developed to predict student academic improvement in MML and Educo developmental mathematics courses using the standardized CPT scores, gender, and methodological indicator as potential predictors. In Phase II, three linear models were analyzed to predict student academic performance in redesigned MML classes. Using the data from Phase II, three additional regression models were developed with the MML post-test as the response variable and the CPT scores, gender, and the MML pre-test as the set of possible predictors to identify “at-risk” students. An out-of-sample prediction method was used to evaluate the misclassification rate in identifying “at-risk” students. The results of this study suggest that Algebra and Arithmetic CPT scores are significant predictors of student academic improvement. However, for each model, less than 50% of the variability in student improvement is explained by the linear relationship between the variables. Based on the results of this study, students enrolled in module 050 MML classes at Southwestern Community College (SCC) showed greater improvement than Educo students. Furthermore, the predictive models that include CPT scores and gender as the only predictors of learning can be employed to identify “at-risk” students at the beginning of each school semester. In the conclusion of the thesis, the limitations and implications of this study are discussed.

Additional Information

Publication
Dissertation
Language: English
Date: 2013
Keywords
developmental education, multiple regression, redesigned mathematics courses
Subjects
Mathematics -- Remedial teaching -- North Carolina, Western -- Evaluation
Mathematics -- Study and teaching (Higher) -- North Carolina, Western -- Evaluation
Community college students -- North Carolina, Western -- Evaluation

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