Predictors of Postsecondary Success: An Analysis of First Year College Remediation Page: 69
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significance in relationship to predicting college remediation. Therefore, campus-level non-LEP
percentage did not successfully predict an incoming college freshmen's enrollment into remedial
Campus-Level Non-Economically Disadvantaged
Campus-level non-economically disadvantaged percentage was included in the regression
model as a continuous variable. Non-economically disadvantaged percentage had the strongest
correlation (r = -0.474) to first year college students taking remedial education. In addition, non-
economically disadvantaged percentage had the overall strongest campus-level correlations
among the other predictor variables, showing moderate correlation with college ready ELA (r =
0.716) and non-at-risk (r = 0.780). In addition to its moderate correlations, multiple regression
showed campus-level non-economically disadvantaged to be a statistically significant predictor
of first-year college student remedial coursework (3 = -0.350, t(8) = -3.42, p = 0.01). With a
moderate effect size of r = 0.474 and controlling for the remaining variables, non-economically
disadvantaged percentage produced the highest degree of predictability of first-year college
student remedial education with r2 = 0.224. This suggested a statistically significant relationship
between campus-level non-economically disadvantage percentage and first-year college student
enrollment into remedial education coursework, indicating high school campuses with higher
percentages of economic disadvantaged students were more likely to see larger numbers of their
graduates enrolling in college-level remedial education. Therefore, high school campus-level
non-economically disadvantaged percentage proved to be a statistically significant predictor and
had the overall greatest probability of predicting first-year college student enrollment into
remedial education coursework.
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Baker, Emmett Andrew. Predictors of Postsecondary Success: An Analysis of First Year College Remediation, dissertation, August 2017; Denton, Texas. (https://digital.library.unt.edu/ark:/67531/metadc1011868/m1/77/: accessed April 19, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .