An Illustration of Diagnostic Classification Modeling in Student Learning Outcomes Assessment

Abstract

The assessment of higher-education student learning outcomes is an important component in understanding the strengths and weaknesses of academic and general education programs. This study illustrates the application of diagnostic classification models, a burgeoning set of statistical models, in assessing student learning outcomes. To facilitate understanding and future applications of diagnostic modeling, the log-linear cognitive diagnosis model used in this study is presented in a didactic manner. The model is applied in a context where undergraduate students were assessed along four learning outcomes related to psychosocial research across two time points. Results focus on implications and methods to aid stakeholders’ interpretation of the analyses. Contrasts to traditional measurement models and potential future applications are also discussed.

Keywords:

• diagnostic classification models
• log-linear cognitive diagnosis model
• student learning outcomes assessment

Notes

Mplus syntax used to estimate models can be found at http://laineb.myweb.uga.edu/html/research.html.