OBJECTIVE: To identify variables that may enhance medical student's preparedness for computer-based administration of the United States Medical Licensing Examination (USMLE). DESIGN: A cross-sectional survey of 301 medical students who completed a self-administered questionnaire. MEASUREMENTS: The questionnaire was designed to obtain information about students' computer resources, personal experience with computers, computer expertise, opinions about computers, experience with computer-based testing, perceived preparedness for the computer-based USMLE, and demographic variables. Variables related to students' perceived preparedness for the computer-based USMLE were identified by ordinal logistic regression. RESULTS: A significant regression model yielded four significant predictors: perceived preparedness for USMLE content (P: < 0.0001), opinions about computers (P: < 0.0012), gender (P: < 0.0001), and a gender by computer-based testing experience interaction (P: < 0. 0004). Computer resources, personal experience with computers, computer expertise, age, race, and year of medical school were not significant predictors. CONCLUSION: Students' perceived preparedness for computer-based administration of high-stakes examinations may be facilitated by preparing them for examination content, by enhancing their opinions about computers, and by increasing their computer-based testing experiences.
OBJECTIVE: To identify variables that may enhance medical student's preparedness for computer-based administration of the United States Medical Licensing Examination (USMLE). DESIGN: A cross-sectional survey of 301 medical students who completed a self-administered questionnaire. MEASUREMENTS: The questionnaire was designed to obtain information about students' computer resources, personal experience with computers, computer expertise, opinions about computers, experience with computer-based testing, perceived preparedness for the computer-based USMLE, and demographic variables. Variables related to students' perceived preparedness for the computer-based USMLE were identified by ordinal logistic regression. RESULTS: A significant regression model yielded four significant predictors: perceived preparedness for USMLE content (P: < 0.0001), opinions about computers (P: < 0.0012), gender (P: < 0.0001), and a gender by computer-based testing experience interaction (P: < 0. 0004). Computer resources, personal experience with computers, computer expertise, age, race, and year of medical school were not significant predictors. CONCLUSION: Students' perceived preparedness for computer-based administration of high-stakes examinations may be facilitated by preparing them for examination content, by enhancing their opinions about computers, and by increasing their computer-based testing experiences.