Special Topic: Early Childhood Assessment and Intervention
Correspondence regarding this article should be addressed to Nathan Clemens, 603 Harrington Tower, 4225 TAMU, College Station, TX ; e-mail:
Nathan Clemens, PhD, is an assistant professor in the Department of Educational Psychology at Texas A&M University. His research interests include reading development and disability, assessment, and multitiered systems of support.
Shanna Hagan-Burke, PhD, is an associate professor of special education at Texas A&M University. Her interests include functional analyses of problem behavior, positive behavior supports, and relations between problem behaviors and academic achievement.
Wen Luo, PhD, is an associate professor in the Department of Educational Psychology at Texas A&M University. Her research interests include multilevel modeling and structural equation modeling.
Carissa Cerda, MEd, is currently a doctoral candidate in the School Psychology Program at Texas A&M University. Her research interests include learning-related skills, behavioral self-regulation and links to academic achievement, reading intervention, and teacher consultation and coaching methods.
Alane Blakely, MEd, is currently a doctoral candidate in the School Psychology Program at Texas A&M University. Her research interests include academic and behavioral interventions for students with executive functioning deficits and early reading interventions for English language learners.
Jennifer Frosch, MEd, is a former teacher and studied special education at Texas A&M University. Her areas of interest include reading instruction and autism spectrum disorders.
Brenda Gamez-Patience is a doctoral candidate in the School Psychology Program at Texas A&M University and is currently completing her predoctoral internship. Her research interests include reading interventions and the impact of teacher questioning on vocabulary outcomes of dual-language learners.
Meredith Jones, MEd, is a doctoral candidate in the School Psychology Program at Texas A&M University. She is currently completing her predoctoral internship in the Cypress-Fairbanks School District.
Associate Editors: Joseph Betts and Amanda VanDerHeyden
This study examined the predictive validity of a computer-adaptive assessment for measuring kindergarten reading skills using the STAR Early Literacy (SEL) test. The findings showed that the results of SEL assessments administered during the fall, winter, and spring of kindergarten were moderate and statistically significant predictors of year-end reading and reading-related skills, and they explained 35% to 38% of the variance in a latent variable of word-reading skills. Similar results were observed with a subsample of 71 participants who received follow-up assessments in first grade. End-of-kindergarten analyses indicated that, when added as predictors with SEL, paper-based measures of letter naming, letter-sound fluency, and word-reading fluency improved the amount of explained variance in kindergarten and first-grade year-end word-reading skills. Classification-accuracy analyses found that the SEL literacy classifications aligned with word-reading skills measured by paper-based assessments for students with higher SEL scores, but less alignment was found for students with lower SEL scores. In addition, SEL cut scores showed problematic accuracy, especially in predicting outcomes at the end of first grade. The addition of paper-based assessments tended to improve accuracy over using SEL in isolation. Overall, SEL shows promise as a universal screening tool for kindergarten reading skills, although it may not yet be able to completely replace paper-based assessments of early reading.
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