REHMAN MEDICAL COLLEGE ADMISSION CRITERIA AS AN INDICATOR OF STUDENTS’ PERFORMANCE IN UNIVERSITY PROFESSIONAL EXAMINATIONS - Mufti, Tariq Saeed; ullah, Kifayat; Qayum, Iftikhar (Journal of Ayub Medical College Abbottabad, 2014)
Background: Although admission criteria are standardized by Pakistan Medical & Dental Council (PM&DC), medical colleges can conduct aptitude tests as admission criteria. The present study aimed to determine the correlation of Rehman Medical College’s (RMC) admission criteria with students’ academic performance in the Khyber Medical University (KMU) First Professional Part-1 examinations. Methods: A descriptive study was done at RMC from December 2012 to March 2013 based on computerized records of first and second year MBBS students (years 2010 and 2011; 100 students per year). Students who dropped out or were stricken off from RMC before the university exam were excluded. Pearson’s correlation coefficient was calculated by using SPSS-15. Results: For 2010, highest correlation was observed between combined marks of all admission criteria components and KMU professional examination (r=0.466, p<0.001) followed by RMC aptitude test (r=0.424, p<0.001). For females, combined marks of admission criteria showed highest correlation (r=0.629, p<0.001) while RMC aptitude test showed highest correlation for male students (r=0.361, p=0.004). For 2011, combined marks of admission criteria (r=0.359, p=0.001) showed the highest correlation with KMU professional examination marks followed by Educational Testing & Evaluation Agency (ETEA) marks (r=0.327, p=0.002). ETEA marks showed highest correlation for females (r=0.491, p=0.001) followed by combined marks of admission criteria (r=0.432, p=0.005); for males, combined marks of admission criteria (r=0.385, p=0.006) showed highest correlation followed by ETEA marks (r=0.383, p=0.007). Conclusion: Combined marks of admission criteria correlate with students’ academic performances in university professional examination result. Key words: Association, admission criteria, students, education, medical prediction