Diagnostic Classification Models for Analyzing Examinees' Responses to a Large Number of Small and Similar Tasks

• In Event: Measurement and Statistical Modeling

Abstract

Assessments with a large amount of small, similar or often repetitive tasks are being used in both educational, neurocognitive, and psychological contexts. For example, respondents are asked to recognize numbers or letters from a large pool of those and the number of correct answers is a count variable. In 1960, George Rasch developed the Rasch Poisson Counts Model (RPCM) to handle that type of assessment. This paper extends the RPCM into the world of diagnostic classification models (DCMs) where a framework of Poisson DCMs and a framework of Negative Binomial DCMs are proposed and demonstrated through an operational dataset.

Authors

• Ren Liu, University of California - Merced

• Haiyan Liu, University of California - Merced

• Dexin Shi, University of South Carolina

• Zhehan Jiang, Peking University