Predictors of Postsecondary Success: An Analysis of First Year College Remediation Page: 60
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With this study, the researcher investigated the predictive relationships between high
school campus-level characteristics and the percentages of high school campus graduates
enrolled in at least one student credit hour of remedial education during their first year of
college. The sample included first-year college students enrolled in the Central Texas two-year
college during the fall semester of 2013. All 5,036 students in the sample were spring 2013
Texas public high school graduates that represented 296 Texas public high school campuses.
Within this chapter are the findings related to this study. The researcher utilized descriptive
statistics, Pearson correlations, and multiple regression analysis to examine the data.
This study was guided by the hypothesis that high school campus factors could be used to
successfully predict a first-year college students' enrollment into postsecondary remedial
education coursework. Research questions related to the predictive relationships between
campus-level variables and enrollment in remedial college coursework. In this chapter, the
researcher reported the results of the investigation in regards to the two 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
In order to answer each of the study's research questions effectively, descriptive statistics and a
predictive regression model were utilized to identify the level of relationship between the
independent and dependent variables.
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Reference the current page of this Dissertation.
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/m1/68/: accessed April 26, 2019), University of North Texas Libraries, Digital Library, https://digital.library.unt.edu; .