Document Type

Dissertation

Degree

Doctor of Education (EdD)

Department

Higher Education

First Advisor's Name

Kingsley Banya

First Advisor's Committee Title

Committee Chair

Second Advisor's Name

Janice Sandiford

Third Advisor's Name

Martha Pelaez

Fourth Advisor's Name

Victoria Menzies

Fifth Advisor's Name

Kathleen Blais

Date of Defense

2-26-2009

Abstract

This study examined the predictive merits of selected cognitive and noncognitive variables on the national Registry exam pass rate using 2008 graduates (n = 175) from community college radiography programs in Florida. The independent variables included two GPAs, final grades in five radiography courses, self-efficacy, and social support. The dependent variable was the first-attempt results on the national Registry exam. The design was a retrospective predictive study that relied on academic data collected from participants using the self-report method and on perceptions of students' success on the national Registry exam collected through a questionnaire developed and piloted in the study. All independent variables except self-efficacy and social support correlated with success on vii the national Registry exam (p < .01) using the Pearson Product-Moment Correlation analysis. The strongest predictor of the national Registry exam success was the end-of-program GPA, r = .550, p < .001. The GPAs and scores for self-efficacy and social support were entered into a logistic regression analysis to produce a prediction model. The end-of-program GPA (p = .015) emerged as a significant variable. This model predicted 44% of the students who failed the national Registry exam and 97.3% of those who passed, explaining 45.8% of the variance.

A second model included the final grades for the radiography courses, self efficacy, and social support. Three courses significantly predicted national Registry exam success; Radiographic Exposures, p < .001; Radiologic Physics, p = .014; and Radiation Safety & Protection, p = .044, explaining 56.8% of the variance. This model predicted 64% of the students who failed the national Registry exam and 96% of those who passed. The findings support the use of in-program data as accurate predictors of success on the national Registry exam.

Identifier

FI15101363

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