ArticleBMC medical education2025
How well do admission criteria predict student performance in one medical course?
Article in BMC medical education, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
backgroundAdmission criteria for medical schools in Saudi Arabia-such as the General Aptitude Test (GAT), Scholastic Achievement Admission Test (SAAT), and English proficiency-are intended to predict student success. Yet, their effectiveness in forecasting performance in core medical courses taught in English remains uncertain.
methodsThis cross-sectional study examined 210 Saudi medical students at a single institution, analyzing how GAT, SAAT, and English proficiency measures (English course average, reading test, and communication test) predicted grades in a medical biology course. Data were analyzed using simple and multivariate regression models, with additional correlation and diagnostic checks.
resultsIndividually, GAT and SAAT explained only 5.0% and 5.3% of the variance in biology grades, respectively. English proficiency was a stronger predictor: English average (12.2%), reading test (19.0%), and communication test (18.1%). Combined, these variables accounted for 26.6% of variance, with the communication test emerging as the strongest predictor (p < 0.01), followed by the reading test (p < 0.05).
conclusionStandardized admission tests such as GAT and SAAT show limited predictive value for biology performance in an English-medium curriculum, while English proficiency demonstrates stronger associations. These findings, though based on a single course at one institution, highlight the importance of language skills in early medical education. The study offers preliminary, hypothesis-generating evidence that can inform broader investigations and future admission reforms aligned with Saudi Vision 2030.
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