title: Preadmission schooling context helps to predict examination performance throughout medical school.
abstract: This study investigates the effects of socioeconomic status and schooling on the academic attainment of a cohort of students at a single medical school (N = 240). Partial least squares structural equation modelling was used to explore how students' summative assessment scores over 4 years of medical school were affected by: attainment in secondary school examinations (GCSEs and A-levels); the Income Deprivation Affecting Children Index (IDACI) rank associated with students' home postcodes; the performance of students' A-level institutions, measured as the percentage of A-level students achieving 3 A-levels at AAB or higher in two or more facilitating subjects. The effects were consistent across time; the final linear regression model used students' cumulative scores (the basis of the medical school's UK Foundation Programme submission) as the dependent variable. The final model fit was quite poor (R2= .184, n = 178). IDACI Rank was non-significant and excluded from the final model. Both GCSE (.340, p < .001) and A-level (.204, p < .005) scores were associated with increasing Cumulative Score; School Performance was associated with decreasing Cumulative Score (-.159, p < .05). This study confirmed the predictive validity of prior academic attainment and found the same inverse relationship between schooling and medical course performance as previous studies. The study found no evidence that socioeconomic background affects course performance; however, students admitted to medicine from poorly performing schools achieve higher academic attainment throughout the course than students admitted from better-performing schools with the same grades. Schooling could be taken into account for admissions purposes.
authors.affiliation: AQA Education's Centre for Education Research and Practice (CERP, AQA Education), Stag Hill House, Guildford, Surrey, GU2 7XJ, UK. nstringer@aqa.org.uk.
authors.forename: Neil
authors.initials: N
authors.lastname: Stringer
authors.affiliation: Barts and The London School of Medicine and Dentistry, London, UK.
authors.forename: Michael
authors.initials: M
authors.lastname: Chan
authors.affiliation: AQA Education's Centre for Education Research and Practice, Surrey, UK.
authors.forename: Yaw
authors.initials: Y
authors.lastname: Bimpeh
authors.affiliation: The Medical School, The University of Sheffield, Sheffield, UK.
authors.forename: Philip
authors.initials: P
authors.lastname: Chan
mesh_terms: D000124:Achievement; D004521:Educational Measurement; D005260:Female; D006801:Humans; D008297:Male; D012577:Schools, Medical / Q000706:statistics & numerical data*; D012959:Socioeconomic Factors; D013337:Students, Medical / Q000706:statistics & numerical data*
keywords: Contextual data; Higher education admissions; Medical school admissions; Predictive validity; Widening participation