Evaluating Intervention Effects in a Diagnostic Classification Model Framework: Intervention in a Diagnostic Classification Model

The evaluation of intervention effects is an important objective of educational research. One way to evaluate the effectiveness of an intervention is to conduct an experiment that assigns individuals to control and treatment groups. In the context of pretest/posttest designed studies, this is referred to as a control-group pretest/posttest design. The transition diagnostic classification model (TDCM) was recently developed to assess growth, defined as change in attribute mastery status over time, in a diagnostic classification model framework. The TDCM, however, does not model multiple groups, and therefore is not able to analyze data from a control-group pretest/posttest designed experiment. In this study, we extend the TDCM to model multiple groups, thereby enabling the examination of group-differential growth in attribute mastery and the evaluation of intervention effects. The utility of the multigroup TDCM is demonstrated in the evaluation of an innovative instructional method in mathematics education.