摘要：Computer multistage adaptive test (MST) combines the advantages of paper and pencil-based test (P&P) and computer-adaptive test (CAT). As CAT, MST is adaptive based on modules; as P&P, MST can meet the need of test developers for test forms managing and keeping them parallel. Cognitive diagnosis (CD) can accurately measure students’ knowledge states (KSs) and provide diagnostic information, which is conducive to students self-learning and teachers targeted teaching. Although MST and CD have a lot of advantage, there are many factors that prevent MST applying to CD. In this study, we firstly attempt to employ automated test assembly (ATA) to achieve the objectives of MST in the application of CD (called CD-MST) via heuristic algorithms. The mean correct response probability of all KSs for each item is used to describe the corresponding item difficulty of CD. The attribute reliability in CD is defined as the test quantitative target. A simulation study with the G-DINA model (generalized deterministic input noisy “and” gate model) was carried out to investigate the proposed CD-MST, and the results showed that the assembled panels of CD-MST were fully satisfied both the statistical and the non-statistical constraints.
