In Flanders, matriculation to medical education is made dependent upon a centrally organized admission test assessing competences in sciences (mathematics, physics, chemistry, and biology), interpersonal skills, and scientific text comprehension using multiple-choice items that are scored using the so-called “correction for guessing”. Admission is granted to a fixed number of examinees who are ranked highest among those examinees that obtained a passing score on the different subtests. In 2023, the acceptance rate equaled .53 for male examinees who just finished high school while being only .38 for their female peers. Similar gender differences were found among the group of older examinees and examinees coming from abroad. Two factors can explain these gender differences. Firstly, due to self-selection male applicants may on average be stronger in the assessed skills than female applicants. Secondly, awarding a negative score to wrong answers may incentive participants to omit response to items when they do not know or are not sure of the answer, which could impact women more than men (e.g., Kelly & Dennick, 2009). To disentangle both factors, a tree-based Item Response Theory model (De Beer, Janssen, De Boeck, 2017) is applied to the results of the 2021, 2022, and 2023 science tests of the Flemish medical entrance examination. By modeling the correctness of given responses and response omission jointly, a separate estimate of examinees’ science proficiency and skipping propensity is obtained. Gender differences are observed on both measures. Moreover, by simulating responses on the skipped items based on examinees’ science proficiency, the effect of the gender differences in skipping propensity on the ranking of examinees is illustrated. Hence, the present study shows that both factors contribute to the gender difference in acceptance rates for all three investigated years of administration. The study therefore argues to monitor the quality of high-stakes examination in several respects in order to avoid gender bias, especially with numerus fixus (ranking of candidates). Moreover, exam committees should consider alternative instructions for negative marking in high-stakes multiple-choice exams, such as elimination scoring in which students can show their partial knowledge on exam questions (Vanderoost et al., 2019).

De Beer, D., Janssen, R., & De Boeck, P. (2017). Modeling skipped and notreached items using IRTrees. Journal of Educational Measurement, 54(3), 333–363. https://doi.org/10.1111/jedm.12147 Kelly, S., & Dennick, R. (2009). Evidence of gender bias in True-False-Abstain medical examinations. BMC Medical Education, 7, 9-32. doi: 10.1186/1472-6920-9-32. Vanderoost, J., Janssen, R., Callens, R., Eggermont, J., De Laet, T. with De Laet, T. (corresp. author) (2018). Elimination testing with adapted scoring reduces guessing and anxiety in multiple-choice assessments, but does not increase grade average with respect to traditional negative marking. PLoS One, 13 (10). doi: 10.1371/journal.pone.0203931