Completing the Remedial Sequence and College-Level Credit-Bearing Math

Abstract

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.

Keywords

student persistence remedial math binary logistic regression cumulative logistic regression ordered logit models continuation ratio model policy grades developmental math

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