Selection, assessment & performance


Worldwide the number of students applying for Medical School is much larger than the available positions. Therefore the selection and admission of medical students is a high stakes process for both students and medical schools. Therefore, the methods of student selection, their validity and their underlying mechanisms are of great interest. In this line of research we study the validity of the methods of student selection which have been used by Erasmus MC since 2001. As a by-product of the peculiar Dutch system of medical school selection, a cohort of control students exists who have been admitted to medical school through a lottery system. Our studies include the predictive validity of our selection instrument for preclinical and clinical academic performance and the exploration of additional selection instruments.

Ongoing research concerns the comparison of several non-academic and academic selection instruments in their predictive value for performance during medical school. These instruments include cognitive tests of study skills, IQ tests, measurements of learning style, personality, etc. In addition, we are developing Situational Judgement Tests to determine several competences relevant for the medical profession, such as professionalism, communication and collaboration.

A more challenging line of research aims at the identification of characteristics of students during clerkships and residency, who are considered successful by their instructors and supervisors. The aim is to distinguish and validate behavioural characteristics of excellent residents in several specialties, which are amenable to quantitative determination and fit in the concept of deliberate practice. Subsequently, the findings will be applied in a selection tool for first year medical students.

Recently a pilot project has been started in the Netherlands to investigate whether it is possible to pre-select sixth year clerkship students for a limited set of residency programmes. One of the challenges is to use validated methods to select the right students that go beyond the classical application letter and interview paradigm. One of the studies will focus on the development of a Situational Judgement Test to determine the level of competencies such as professionalism, collaboration and communication.



Recent work conducted at Erasmus MC showed that strong ethnicity-related disparities exist in medical school performance even after adjustments for age, gender, pre-university GPA and socio-demographic variables. A more subjective grading process cannot be ruled out as a cause of the lower grades in clinical training achieved by students from ethnic minority groups, but other explanations require further investigation.

A first question we aim to answer is whether non-Dutch students are less well prepared for clinical training, despite receiving the same pre-clinical training and if so, why this is the case. In addition, we aim to conduct more detailed experimental studies to understand the processes underlying judgement and decision making in clinical assessments. Finally, we are considering, designing, implementing and evaluating interventions for improvement, such as attempts to make assessment in clinical training less subjective and to create awareness of cultural bias by both students and assessors.



In this line of research we aim to identify factors that predict performance throughout medical school. Several issues are studied: the evaluation of educational management decisions such as the introduction of an academic dismissal policy, the development of a model to identify students at risk for failure, further characterisation of such students at risk and the effects of the development of a remedial programme for these students, and the development of self-regulated learning skills during medical school.


Meet the researchers

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Chantal van Andel PhD candidate
Vera Broks PhD candidate
Suzanne Fikrat-Wevers PhD candidate
Inge Otto PhD candidate
Karen Stegers-Jager Assistant Professor
Andrea Woltman Associate Professor