ERIC Number: EJ1106069
Record Type: Journal
Publication Date: 2016-Aug
Pages: 29
Abstractor: As Provided
ISBN: N/A
ISSN: ISSN-1521-0251
EISSN: N/A
Available Date: N/A
Completing the Remedial Sequence and College-Level Credit-Bearing Math: Comparing Binary, Cumulative, and Continuation Ratio Logistic Regression Models
Davidson, J. Cody
Journal of College Student Retention: Research, Theory & Practice, v18 n2 p138-166 Aug 2016
Mathematics is the most common subject area of remedial need and the majority of remedial math students never pass a college-level credit-bearing math class. The majorities of studies that investigate this phenomenon are conducted at community colleges and use some type of regression model; however, none have used a continuation ratio model. The purpose of this study was to assess student persistence through the remedial math sequence and successfully passing a college-level credit-bearing math course using binary, cumulative, and continuation ratio logistic regression models at 2- and 4-year public institutions. Findings showed the pre-algebra grade was the strongest predictor of completing each course in the remedial sequence and passing a college-level credit-bearing math class. Also, continuation ratio logistic regression provided methodological advantages over binary and cumulative logistic regression.
Descriptors: Regression (Statistics), Remedial Mathematics, Academic Persistence, Remedial Instruction, Algebra, Two Year College Students, College Students, Predictor Variables, Higher Education, Community Colleges, Dual Enrollment, Student Characteristics, College Mathematics
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Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education; Two Year Colleges
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Identifiers - Location: Kentucky
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