Predicting Second-Grade Students' Yearly Standardized Reading Achievement Using a Computer-Adaptive Assessment

The present study investigated the predictability of a computer-adaptive, curriculum-based reading assessment for measuring second-grade students' overall and comprehension reading achievement on a standardized reading achievement test. Specifically, second-grade student scores (N = 428) of the Istation's Indicators of Progress for Early Reading (ISIP-ER) and the Standardized Test for the Assessment of Reading (STAR Reading) in one state were examined. Linear regression analysis was conducted in Mplus to determine the predictability between the ISIP-ER and STAR Reading scores, identifying that both the ISIP-ER overall reading and comprehension scores in December predicted the standardized reading scores in Spring (May). Confidence intervals were estimated to identify the ISIP-ER cut scores that predict STAR Reading scores for all achievement levels. Overall, ISIP-ER shows promise as a universal screening tool for second-grade student yearly reading skills.