Predictors of Postsecondary Success: An Analysis of First Year College Remediation Page: 76
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Discussion of Results
In this quantitative study, the researcher utilizes a multiple linear regression model to
investigate relationships between high school campus-level variables and remedial education
courses taken by first-year college students in an attempt to answer the research questions:
1. Do high school campus-level variables of incoming freshmen at a Central Texas two-
year college predict a student's enrollment into remedial education?
2. To what extent do high school campus-level variables of incoming freshmen at a
Central Texas two-year college predict a student's enrollment into remedial
Results of this study show statistically significant findings in relationship to the two research
questions. In this section, the researcher provides a discussion of the study's results, presents an
interpretation of the findings, and will make recommendations in regards to college readiness
application and suggestions for future researchers.
Interpretation of the Findings
This study's design was to evaluate the predictive relationship high school campus-level
predictor variables have with first-year college student enrollment into remedial education
coursework. The dependent variable for the study represents the percentage of students from
each Texas public high school campus enrolled into at least one credit hour of remedial
education during their first semester as a freshman at a Central Texas two-year college during the
2013 fall semester.
Multiple regression results regarding Research Question 1 identify relevant campus-level
factors in relationship to first-year college student remediation. The multiple regression model
successfully explained 26.3% (F(8,286) = 12.74, p = 0.05, r2 = 0.263) of the variance between
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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/m1/84/: accessed April 21, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .