The benefits of sequential testing: Improved diagnostic accuracy and better outcomes for failing students

Abstract Introduction: In recent decades, there has been a move towards standardized models of assessment where all students sit the same test (e.g. OSCE). By contrast, in a sequential test the examination is in two parts, a “screening” test (S1) that all candidates take, and then a second “test” (S2) which only the weaker candidates sit. This article investigates the diagnostic accuracy of this assessment design, and investigates failing students’ subsequent performance under this model. Methods: Using recent undergraduate knowledge and performance data, we compare S1 “decisions” to S2 overall pass/fail decisions to assess diagnostic accuracy in a sequential model. We also evaluate the longitudinal performance of failing students using changes in percentile ranks over a full repeated year. Findings: We find a small but important improvement in diagnostic accuracy under a sequential model (of the order 2–4% of students misclassified under a traditional model). Further, after a resit year, weaker students’ rankings relative to their peers improve by 20–30 percentile points. Discussion: These findings provide strong empirical support for the theoretical arguments in favor of a sequential testing model of assessment, particularly that diagnostic accuracy and longitudinal assessment outcomes post-remediation for the weakest students are both improved.