Remedial education

Optics

Physics

Mathematics education

Paleontology

Artificial intelligence

Psychology

Power (physics)

Focus (optics)

Data science

Test (biology)

Computer science

Reliability (semiconductor)

Quantum mechanics

Biology

Measurement Interdisciplinary Research and Perspectives

Diagnostic classification models (DCMs) classify examinees based on the skills they have mastered given their test performance. This classification enables targeted feedback that can inform remedial instruction. Unfortunately, applications of DCMs have been criticized (e.g., no validity support). Generally, these evaluations have been brief and not the study’s focus. Thus, the literature of DCM applications was extensively analyzed. Results mostly supported criticisms. For example, most DCM applications lacked strong reliability and validity evidence and were not used to give feedback to examinees. We provide possible explanations for these results and suggest how to advance the application and usage of DCMs.

Applications of Diagnostic Classification Models: A Literature Review and Critical Commentary