Date of Award

1-1-2023

Language

English

Document Type

Dissertation

Degree Name

Doctor of Psychology (PsyD)

College/School/Department

Department of Educational and Counseling Psychology

Content Description

1 online resource (viii, 89 pages) : illustrations (some color)

Dissertation/Thesis Chair

Benjamin G Solomon

Committee Members

David N Miller, Kevin P Quinn

Keywords

Language and languages, Mathematical ability

Subject Categories

Educational Psychology

Abstract

The purpose of the present study was to compare the classification accuracy of a previous year’s end-of-year state assessment, a computer-adaptive diagnostic assessment (i-Ready), and the combination of the previous year’s end-of-year state assessment with the following year’s i-Ready performance to predict the rate of students passing or failing the following year’s end-of-year state assessment in English Language Arts (ELA) and math. This was conducted to determine whether i-Ready as an additional screening measure is necessary to identify students who are at-risk of failing the upcoming end-of-year assessment and are in need of tiered intervention supports, or if the previous year’s end-of-year assessment is sufficient for this purpose. Overall, for the population of students represented in this study, the previous year’s end-of-year state assessment yielded stronger classification accuracy over the use of the fall or winter i-Ready diagnostic assessment. The combination of i-Ready with the previous year’s state test demonstrated minimally greater strength in determining student risk level. Moreover, the previous year’s end-of-year assessment serves as economically advantageous over administering i-Ready as an additional screening assessment to determine risk and inform decisions within a multi-tiered system of supports. Implications of these findings and recommendations for further research are discussed.

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