Abstract.
The current study explored multiple ways in which middle schools can use and integrate data sources to predict proficiency on future high-stakes state achievement tests. The diagnostic accuracy of (a) prior achievement data, (b) teacher rating scale scores, (c) a composite score combining state test scores and rating scale responses, and (d) two gated screening approaches was compared in a sample of 614 middle school students. Prior state test performance emerged as the strongest single predictor of future state test scores; however, results provide evidence that educators may consider locally derived cut scores or alternative screening procedures that incorporate multiple data sources. Specifically, the combination of prior achievement data and teacher ratings of student competence often resulted in increases in either sensitivity or specificity as a function of how data sources were combined.
Additional information
Notes on contributors
Peter M. Nelson
Peter M. Nelson, PhD, is an assistant professor of school psychology at Penn State University. He is a former high school teacher, and his primary research interests focus on data-based decision making and intervention in the classroom setting. He has published and presented on issues related to effective math intervention, classroom environment assessment, professional development, screening, and progress monitoring.
Ethan R. Van Norman
Ethan R. Van Norman PhD, is an assistant professor of school psychology at Georgia State University. His research interests involve evaluating and improving the technical adequacy of academic and behavioral measures used in schools. Dr. Van Norman is also interested in building the capacity of educators and school psychologists to use data to make sound educational decisions.
Stacey K. Lackner
Stacey K. Lackner, PhD, is the Director of Research and Evaluation for Wayzata Public Schools. Her work focuses on data-based decision making and structuring the school environment to support exceptional learning for all students.