Theses and Dissertations

Date of Award

2007

Document Type

Dissertation - NSU Access Only

Degree Name

Doctor of Education (EdD)

Department

Abraham S. Fischler College of Education and School of Criminal Justice

Advisor

Stan Hannah

Committee Member

Anita Barrett

Committee Member

Maryellen Maher

Keywords

Professional Education/Medical Education/Medical Schools/ Medical Students/Educational Testing

Abstract

Successful performance in medical school and passing the licensure examinations by students are critical outcomes for all medical education programs. The percentage rate of students who pass or fail the licensure examinations from each medical education program is frequently used to evaluate the quality of the program and as a standard uniform measure.

This study was designed to explore the ability of selected academic and demographic variables to predict the pass/fail performance of osteopathic medical students on the Comprehensive Osteopathic Medical Licensing Exam (COMLEX) Level I exam. The researcher sought to determine if there was a regression equation that could be used to predict academic difficulty during the first 2 years of medical school.

The sample of medical students selected for this study consisted of 458 students starting medical school from Fall 2000 through Fall 2003 who completed the first 2 years of didactic instruction and took the COMLEX Level I exam. Data were obtained from the students' admission files and the institution's student information system.

The purpose of this study was to use gender, age, undergraduate GPA, selectivity of undergraduate institution, undergraduate major, and first-time Medical College Admission Test scores plus the postmatriculation variable course performance in Mechanism of Disease to develop a model that could be used to predict which students would fail a course in the first 2 years of the curriculum, meet criteria to repeat an academic year, or fail to pass COMLEX Level I on the first attempt.

The findings in this study lacked strong predictive value by statistical standards. Further studies are needed to identify other cognitive or noncognitive factors that can help predict which students are at-risk and then develop interventional strategies for those students.

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