Abstract
This chapter provides a brief overview of generalizability theory (G theory), a framework for modeling different sources of score variability contributing to measurement inconsistency. First, this chapter introduces basic concepts of G theory in relation to characteristics of classical test theory (CTT), highlighting a notable strength of G theory in allowing for the analysis of selected and constructed item responses for both norm-referenced and criterion-referenced assessments. Then a step-by-step demonstration is provided to illustrate how a dataset could be analyzed using G theory to address specific research questions concerning measurement consistency. Major considerations for determining rating designs are also discussed so as to ensure that a G theory analysis generates meaningful and interpretable results. As an illustrative example, the process of analyzing a language performance assessment dataset by using a univariate G theory analysis software, GENOVA, is described. Results of the analysis are discussed along with key considerations in designing and conducting language assessment studies using G theory.
Original language | English |
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Title of host publication | Quantitative Data Analysis for Language Assessment Volume I |
Subtitle of host publication | Fundamental Techniques |
Publisher | Taylor and Francis |
Pages | 30-53 |
Number of pages | 24 |
ISBN (Electronic) | 9781351741231 |
DOIs | |
Publication status | Published - 2019 Jan 1 |
ASJC Scopus subject areas
- Social Sciences(all)
- Psychology(all)
- Arts and Humanities(all)