Joining the Conversation: Predictors of Success on the United States Medical Licensing Examinations (USMLE)
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| Title: | Joining the Conversation: Predictors of Success on the United States Medical Licensing Examinations (USMLE) |
|---|---|
| Language: | English |
| Authors: | Gohara, Sabry, Shapiro, Joseph I., Jacob, Adam N., Khuder, Sadik A., Gandy, Robyn A., Metting, Patricia J., Gold, Jeffrey, Kleshinski, James, James Kleshinski |
| Source: | Learning Assistance Review. Spr 2011 16(1):11-20. |
| Availability: | National College Learning Center Association. Web site: http://www.nclca.org/tlar.htm |
| Peer Reviewed: | Y |
| Page Count: | 10 |
| Publication Date: | 2011 |
| Document Type: | Journal Articles Reports - Research |
| Descriptors: | Medical Education, Medical Students, Required Courses, Medical Schools, Licensing Examinations (Professions), Regression (Statistics), Certification, College Admission, Models, Scores, Evaluation, Academic Achievement, Predictor Variables, Colleges |
| Geographic Terms: | United States |
| Assessment and Survey Identifiers: | Medical College Admission Test, United States Medical Licensing Examination |
| ISSN: | 1087-0059 |
| Abstract: | The purpose of this study was to evaluate whether models based on pre-admission testing, including performance on the Medical College Admission Test (MCAT), performance on required courses in the medical school curriculum, or a combination of both could accurately predict performance of medical students on the United States Medical Licensing Examination (USMLE) Steps 1 and 2. Models were produced using stepwise linear regression and feed forward neural networks. Notable accuracy in predicting Step 1 and Step 2 scores were achieved from models integrating pre-admission variables with medical school coursework grades. Of interest, the coursework grades contributed far greater to these models than the pre-admission variables except the MCAT. (Contains 2 tables.) |
| Abstractor: | As Provided |
| Number of References: | 13 |
| Entry Date: | 2011 |
| Access URL: | https://www.nclca.org/tlar.html |
| Accession Number: | EJ919575 |
| Database: | ERIC |
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