A comparison of methods to screen middle school students for reading and math difficulties

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.