Using the General Diagnostic Model to Measure Learning and Change in a Longitudinal Large-Scale Assessment IRT
- Author(s):
-
von Davier, Matthias;
Xu, Xueli;
Carstensen, Claus H.
- Publication Year:
- 2009
- Report Number:
-
RR-09-28
- Source:
-
ETS Research Report
- Document Type:
- Report
- Page Count:
- 22
- Subject/Key Words:
-
Item Response Theory (IRT),
Growth Models,
Multidimensional Item Response Theory (MIRT),
Longitudinal Models,
Diagnostic Models,
Large-Scale Assessment
Abstract
To illustrate the models presented in this paper, we applied the models to the PISA-I-Plus data for assessing learning and change across multiple subpopulations. The results indicate that (a) the Embretson-type model with multiple-group assumptions fits the data better than the other models investigated, and (b) the higher performing group shows larger improvement at Time Point 2 than the lower performing group.
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