Estimation of item parameters and examinees’ mastery probability in each domain of the Korean Medical Licensing Examination using a deterministic inputs noisy and gate (DINA) model

摘要

The deterministic inputs, noisy “and” gate (DINA) model is a promising statistical method for providing useful diagnostic information about students’ level of achievement, as educators often want to receive diagnostic information on how examinees did on each content strand, which is referred to as a diagnostic profile. The purpose of this paper was to classify examinees of the Korean Medical Licensing Examination (KMLE) in different content domains using the DINA model.