Theses and Dissertations

Date of Award

2016

Document Type

Dissertation

Degree Name

Doctor of Education (EdD)

Department

Abraham S. Fischler College of Education

Advisor

David Heflich

Committee Member

Charles Schlosser

Committee Member

Lynn R. Schrum

Abstract

The purpose of this study was to determine if a correlation exists among characteristics common to successful adult career and technical students in the traditional classroom setting, the online mode of instruction, and a hybrid of the traditional and distance mode of instructional delivery. A gap in the literature exists, resulting in a lack of knowledge specific to the reasons for success or failure of these adult career and technical students, specifically in relation to mode of instructional delivery: traditional classroom, online, or a hybrid of both.

This study is a quantitative correlation study of explanatory and predictive design using archival data from a large and diverse school district in the state of Florida. The dependent variables included the level of student success as indicated by the student’s withdrawal codes; achievement as measured by the difference between initial Test of Adult Basic Education pretest score and final post-test score required to gain admittance to career and technical education program of student choice; length of time required for the Adult Basic Education student to achieve his or her highest level of success as determined by the pre- and post-test TABE score; and number of courses repeated before required post-test scores are attained during the duration of the coursework.

The results of the study indicate that a greater number of factors displayed predictive value in distinguishing successful from non-successful face-to-face students. For these students, nine factors could be included in a predictive model that accurately classified approximately 58.5% of the students in terms of success versus non-success. Four factors were found to make unique contributions: age, ethnicity, the number of course attempts, and the difference between the students’ first and last math TABE scores. For the online students, five factors were included in a predictive model that accurately distinguished roughly 64.4% of the students. In the final analysis, only one factor maintained a unique predictor of program success: the number of course attempts.

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