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Author ORCID Identifier
https://orcid.org/0000-0002-1386-7397
AccessType
Open Access Dissertation
Document Type
dissertation
Degree Name
Doctor of Philosophy (PhD)
Degree Program
Education
Year Degree Awarded
2021
Month Degree Awarded
May
First Advisor
Scott Monroe
Second Advisor
Craig S. Wells
Third Advisor
John Staudenmayer
Subject Categories
Educational Assessment, Evaluation, and Research
Abstract
Large-scale assessments (LSAs), such as the National Assessment of Educational Progress (NAEP) are low-stakes tests for examinees; consequently, they might randomly guess or generate no responses. Such disengaged test-taking behavior can undermine the validity of test score interpretation. To account for such behavior, various methods have been proposed over the years, which can be classified as ad hoc or model-based. For instance, the Programme for the International Assessment of Adult Competencies (PIAAC) uses a common time threshold (e.g., 5 seconds) method for all items: if an examinee spends more than or equal to five seconds on an item, the omitted response is coded as incorrect; otherwise, it is coded as ignored. Recently, the speed-accuracy+omission (i.e., SA+O model) has been proposed for modeling the processes underlying response and nonresponse behavior. The present research aims to investigate the impact of omitted responses on item and person parameter estimates with the ad hoc and the model-based approaches in the context of LSAs. In a simulation study, we examine (a) how ad hoc and model-based approaches for handling omitted responses compare in terms of item and person parameter estimation in IRT and (b) whether there is a practical difference between ad hoc and model-based approaches to handling omitted responses in real data analyses. Finally, we illustrate the practical implications of selecting a certain approach for handling the omitted items in LSAs through an empirical analysis.
DOI
https://doi.org/10.7275/22445398.0
Recommended Citation
Hong, Seong Eun, "Evaluating Approaches for Dealing with Omitted Items in Large-Scale Assessments" (2021). Doctoral Dissertations. 2188.
https://doi.org/10.7275/22445398.0
https://scholarworks.umass.edu/dissertations_2/2188