Cognitive diagnosis modeling: An overview and illustration

Abstract

In conjunction with appropriately designed test, cognitive diagnosis models (CDMs) can be used to identify students’ mastery or nonmastery of skills in a domain. The diagnostic and finer-grained information from CDMs can lead to tailored instruction and remediation. In this chapter, we introduce the generalized deterministic input, noisy “and” gate (G-DINA) model as a general CDM framework. In addition to various CDM formulations, the G-DINA model framework subsumes parameter estimation, model fit evaluation, Q-matrix validation, differential item functioning analysis, and classification accuracy estimation. Using empirically based simulated data, we illustrate how CDM analysis can be performed using the GDINA R package.