Cognitive Diagnosis Models: Theory and Applications in R

Full day short course (9:00am – 5:00pm)

Short Course #2

This workshop aims to equip participants with practical skills and theoretical foundations for applying Cognitive Diagnosis Models (CDMs) in real-world contexts. Participants will analyze assessment data with the R package and shiny app developed by the presenters and learn how to perform some key CDM analyses, such as model calibration, model fit evaluation, and Q-matrix validation. Recent developments on model identifiability will be discussed too. To ensure participants develop a well-rounded understanding, the workshop will also delve into the key theoretical principles that underpin CDM analysis. 

The course will feature a combination of slide presentations and hands-on exercises in R. Participants are expected to bring their own laptops with R installed (RStudio is optional but recommended). During the exercises, instructors will circulate to provide individual assistance, ensuring participants can effectively engage with the material on their own devices.

Intended Audience

This workshop is tailored for researchers, practitioners, and graduate students with a basic knowledge of Item Response Theory (IRT) and some familiarity with R programming. While prior experience with CDMs is not required, a general understanding of psychometric modeling will be beneficial. By the end of the workshop, participants will have both the theoretical knowledge and practical skills needed to conduct various CDM analyses independently, leveraging the GDINA package and Shiny app for their diagnostic modeling projects.

About the instructors

Wenchao Ma (University of Minnesota), Jimmy de la Torre (University of Hong Kong), & Sangbeak Ye (Florida Atlantic University)

	Wenchao Ma, PhD
	Jimmy de la Torre, PhD
	Sangbeak Ye, PhD