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Dissertation/Thesis Abstract

Analysis of General Education Mathematics and Quantitative Reasoning Courses at California State University, Long Beach
by Miller, Kirsten Louise, M.S., California State University, Long Beach, 2020, 188; 28028351
Abstract (Summary)

In response to Executive Order 1110 issued by the California State University Chancellor’s Office, California State University, Long Beach redesigned entry level mathematics courses effective Fall 2018. Students whose major does not require a specific mathematics course can satisfy their category B4: Mathematics/Quantitative Reasoning general education requirement by completing one of the following courses: MATH 104 The Power of Mathematics, MATH 112A Essential Algebra A, or STAT 108 Statistics for Everyday Life, all of which were involved in the entry level mathematics redesign process. This study aimed to identify the profile — including both academic and demographic variables — of a student who has the greatest chance of academic success in MATH 104, MATH 112A, and STAT 108. Data was obtained from first time freshmen who took one of the three courses of interest in Fall 2018, Spring 2019, or Fall 2019 and analyzed using a combination of hypothesis testing, conditional probability analyses, failure rate analysis, binary logistic regression, regularized logistic regression, decision tree classifier, random forest classifier, and model stacking. Results indicate, for the population of students without major-specific mathematics requirements, MATH 104 and MATH 112A are the best options for those with less developed academic backgrounds. It is recommended that STAT 108 is reserved for the population of students whose major indicates a need for an approved statistics course or students seeking an academic challenge or an alternative to traditional mathematics when satisfying their B4 course requirement. Additionally, in comparison to STAT 108, students who identify as a racial/ethnic minority tend to perform better in MATH 104 and MATH 112A, and first-generation college students tend to perform better in MATH 112A.

Indexing (document details)
Advisor: Suaray, Kagba
Commitee: Chang, Jen-Mei, AlBawaneh, Mahmoud
School: California State University, Long Beach
Department: Mathematics and Statistics
School Location: United States -- California
Source: MAI 82/6(E), Masters Abstracts International
Source Type: DISSERTATION
Subjects: Statistics, Higher education, Artificial intelligence, Mathematics education, Ethnic studies, Quantitative psychology, Educational administration, Educational leadership, Curriculum development
Keywords: Data science, Logistic regression, Machine learning, Long Beach, California, Algebra courses
Publication Number: 28028351
ISBN: 9798557010344
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