Student academic performance in rural clinical schools: The impact of cohort size and competition

Brendan P. Condon, Paul S. Worley, John R. Condon, David J. Prideaux

Research output: Contribution to journalArticlepeer-review

Abstract

Objectives: The Deakin University School of Medicine commenced in 2008 as a rurally focused medical school in south-eastern Australia. This research was designed to examine the effectiveness of the school’s adoption of small regional clinical school settings.

Methods: A retrospective cohort study of the first two cohorts of students was employed to assess academic performance at each of five geographically dispersed clinical training sites, with varying student cohort sizes. The Dundee Ready Education Environment Measure (DREEM) questionnaire provided quantitative data regarding the students’ perception of their educational environment. The data were analyzed using univariate and multivariate analyses.

Results: The highest examination scores, and greatest satisfaction with educational environment, were associated with the clinical school that had a small-sized group of students and was not co-located with another medical school. These differences remained after adjusting for multiple potential confounding factors.

Conclusion: The smaller sites appear to have provided superior support for student learning in this new medical school. This advantage diminishes when smaller cohorts are co-located with students from other medical schools. Cohort size and co-location of medical school curricula may be important independent variables for researchers to consider when comparing the results of clinical education innovations in different settings.

Original languageEnglish
Pages (from-to)262-268
Number of pages7
JournalMedical Teacher
Volume39
Issue number3
Early online date30 Dec 2016
DOIs
Publication statusPublished - 4 Mar 2017

Fingerprint

Dive into the research topics of 'Student academic performance in rural clinical schools: The impact of cohort size and competition'. Together they form a unique fingerprint.

Cite this