Predicting Reading Problems 6 Years Into the Future: Dynamic Assessment Reduces Bias and Increases Classification Accuracy
Digital Object Identifier (DOI)
Purpose: The purpose of this study was to examine how well a kindergarten dynamic assessment of decoding predicts future reading difficulty at 2nd, 3rd, 4th, and 5th grade and to determine whether the dynamic assessment improves the predictive validity of traditional static kindergarten reading measures. Method: With a small variation in sample size by grade, approximately 370 Caucasian and Hispanic students were administered a 3-min dynamic assessment of decoding and static measures of letter identification and phonemic awareness at the beginning of kindergarten. Oral reading fluency was then assessed at the end of Grades 2–5. In this prospective, longitudinal study, predictive validity was estimated for the Caucasian and Hispanic students by examining the amount of variance the static and dynamic assessments explained and by referring to area under the curve and sensitivity and specificity values.
Results: The dynamic assessment accounted for variance in reading ability over and above the static measures, with fair to good area under the curve values and sensitivity and specificity. Classification accuracy worsened when the static measures were included as predictor measures. The results of this study indicate that a very brief dynamic assessment can predict with approximately 75%–80% accuracy, which kindergarten students will have difficulty in learning to decode up to 6 years into the future.
Conclusion: Dynamic assessment of decoding is a promising approach to identifying future reading difficulty of young kindergarten students, mitigating the cultural and linguistic bias found in traditional static early reading measures.
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Citation / Publisher Attribution
Language, Speech, and Hearing Services in Schools, v. 49, issue 4, p. 875-888
Scholar Commons Citation
Petersen, Douglas B.; Gragg, Shelbi L.; and Spencer, Trina D., "Predicting Reading Problems 6 Years Into the Future: Dynamic Assessment Reduces Bias and Increases Classification Accuracy" (2018). Child and Family Studies Faculty Publications. 31.