Coupling Admissions and Curricular Data to Predict Medical Student Outcomes
Autor: | Kadian McIntosh, Jeffrey F. Milem, Diana B. Sesate, W. Patrick Bryan |
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Rok vydání: | 2016 |
Předmět: |
Predictive validity
medicine.medical_specialty 020205 medical informatics Higher education business.industry education Counterintuitive Graduate medical education Medical school 02 engineering and technology Explained variation Education Test (assessment) 03 medical and health sciences 0302 clinical medicine Family medicine Pedagogy 0202 electrical engineering electronic engineering information engineering medicine 030212 general & internal medicine business Psychology Inclusion (education) |
Zdroj: | Research in Higher Education. 58:295-312 |
ISSN: | 1573-188X 0361-0365 |
Popis: | The relative impact of admissions factors and curricular measures on the first medical licensing exam (United States Medical Licensing Exam [USMLE] Step 1) scores is examined. The inclusion of first-year and second-year curricular measures nearly doubled the variance explained in Step 1 scores from the amount explained by the combination of preadmission demographic characteristics and admissions factors. In addition, the relationship between the Medical College Admissions Test (MCAT) and Step 1 scores becomes counterintuitive in models that include curricular measures, where students with the lowest combined admissions metrics (MCAT, grade-point average) score higher, on average, than those with some of the highest admissions metrics. Overreliance on traditional metrics in admissions decisions can exclude students from medical school who have the ability to succeed. |
Databáze: | OpenAIRE |
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