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The Philosophical Aspects of IRT Equating: Modeling Drift to Evaluate Cohort Growth in Large-Scale Assessments

Authors


Husein Taherbhai, Principal Research Scientist, Pearson, 1265 Earlford Dr., Pittsburgh, PA 15227; husein.taherbhai@pearson.com. Daeryong Seo, Senior Research Scientist, Pearson, 19500 Bulverde Road, San Antonio, TX 78259; daeryong.seo@pearson.com.

Abstract

Calibration and equating is the quintessential necessity for most large-scale educational assessments. However, there are instances when no consideration is given to the equating process in terms of context and substantive realization, and the methods used in its execution.

In the view of the authors, equating is not merely an exhibit of the statistical methodology, but it is also a reflection of the thought process undertaken in its execution. For example, there is hardly any discussion in literature of the ideological differences in the selection of an equating method. Furthermore, there is little evidence of modeling cohort growth through an identification and use of construct-relevant linking items’ drift, using the common item nonequivalent group equating design. In this article, the authors philosophically justify the use of Huynh's statistical method for the identification of construct-relevant outliers in the linking pool. The article also dispels the perception of scale instability associated with the inclusion of construct-relevant outliers in the linking item pool and concludes that an appreciation of the rationale used in the selection of the equating method, together with the use of linking items in modeling cohort growth, can be beneficial to the practitioners.

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