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Setting a standard for low reading proficiency: A comparison of the bookmark procedure and constrained mixture Rasch model
In order to draw pertinent conclusions about persons with low reading skills, it is essential to use validated standard-setting procedures by which they can be assigned to their appropriate level of proficiency. Since there is no standard-setting procedure without weaknesses, external validity studi...
Autores principales: | , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8629253/ https://www.ncbi.nlm.nih.gov/pubmed/34843482 http://dx.doi.org/10.1371/journal.pone.0257871 |
Sumario: | In order to draw pertinent conclusions about persons with low reading skills, it is essential to use validated standard-setting procedures by which they can be assigned to their appropriate level of proficiency. Since there is no standard-setting procedure without weaknesses, external validity studies are essential. Traditionally, studies have assessed validity by comparing different judgement-based standard-setting procedures. Only a few studies have used model-based approaches for validating judgement-based procedures. The present study addressed this shortcoming and compared agreement of the cut score placement between a judgement-based approach (i.e., Bookmark procedure) and a model-based one (i.e., constrained mixture Rasch model). This was performed by differentiating between individuals with low reading proficiency and those with a functional level of reading proficiency in three independent samples of the German National Educational Panel Study that included students from the ninth grade (N = 13,897) as well as adults (Ns = 5,335 and 3,145). The analyses showed quite similar mean cut scores for the two standard-setting procedures in two of the samples, whereas the third sample showed more pronounced differences. Importantly, these findings demonstrate that model-based approaches provide a valid and resource-efficient alternative for external validation, although they can be sensitive to the ability distribution within a sample. |
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