The purpose of this correlational study was twofold: to examine the relationship of students' reading performance on six different diagnostic reading assessments and the third grade Ohio Reading Achievement Test; and to assist educators in choosing the diagnostic assessments that best identify students at risk of failing the third grade Ohio Reading Achievement Test so early reading intervention can be implemented. The six diagnostic reading assessments analyzed were (1) kindergarten KRA-L (Kindergarten Readiness Assessment-Literacy); (2) first grade Ohio Reading Diagnostic Test; (3) first grade DIBELS (Dynamic Indicators for Basic Early Literacy Skills) Oral Fluency subtest (ORF); (4) second grade Ohio Reading Diagnostic Test; (5) second grade DIBELS ORF; and (6) third grade DIBELS ORF. The sample included 49 third grade students in a rural Ohio public elementary school.
Four research questions and Chall's (1983) theoretical literacy framework guided the examination of student literacy data. Pearson Correlation Coefficient revealed that the second grade Ohio Reading Diagnostic Test and second grade DIBELS ORF had the strongest correlations with the third grade Ohio Reading Achievement Test. The correlations of third grade DIBELS fluency assessment and first grade DIBELS ORF with the third grade Ohio Reading Achievement Test were weak and had no predicative ability or value.
The strongest significant predictive models were the third grade DIBELS ORF and second grade Ohio Reading Diagnostic Test. The strongest early assessment predictive model was the KRA-L. The second grade DIBELS ORF was a significant predictive model for male and middle/high socioeconomic participants. The second grade Ohio Reading Diagnostic Test was a significant predictive model for female and low socioeconomic participants. Finally, significant regression equations were created for the KRA-L, first grade and second grade Ohio Reading Diagnostic Test, and second grade DIBELS ORF.
The six diagnostic assessments better served different populations of students. There was great variability in predictive ability and correlations. Schools should select the most appropriate diagnostic assessments to monitor literacy progress based upon the unique student population. To become more precise, different diagnostic assessments should be administered on an individualized basis, dependent upon student subgroups of SES, gender, and students with IEPs.