|Can scores on an interim high school reading assessment accurately predict low performance on college readiness exams?
|The purpose of this study was to examine the relationship between measures of reading comprehension, decoding, and language with college-ready performance. This research was motivated by leaders in two Florida school districts interested in the extent to which performance on Floridaís interim reading assessment could be used to identify students who may not perform well on the Preliminary SAT/National Merit Scholarship Qualifying Test (PSAT/NMSQT) and ACT Plan. One of the districts primarily administers the PSAT/NMSQT and the other primarily administers the ACT Plan. Data included the 2013/14 PSAT/NMSQT or ACT Plan results for students in grade 10 from these districts, as well as their grade 9 results on the Florida Assessments for Instruction in Reading Ė Florida Standards (FAIR-FS). Classification and regression tree (CART) analyses formed the framework for an early warning system of risk for each PSAT/NMSQT and ACT Plan subject-area assessment. PSAT/NMSQT Critical Reading performance is best predicted in the study sample by a studentís reading comprehension skills, while PSAT/NMSQT Mathematics and Writing performance is best predicted by a studentís syntactic knowledge. Syntactic knowledge is the most important predictor of ACT Plan English, Reading, and Science in the study sample, whereas reading comprehension skills were found to best predict ACT Plan Mathematics results. Sensitivity rates (the percentage of students correctly identified as at risk) ranged from 81 percent to 89 percent correct across all of the CART models. These results provide preliminary evidence that FAIR-FS scores could be used to create an early warning system for performance on both the PSAT/NMSQT and ACT Plan. The potential success of using FAIR-FS scores as an early warning system could enable districts to identify at-risk students without adding additional testing burden, time away from instruction, or additional cost. The analyses should be replicated statewide to verify the stability of the models and the generalizability of the results to the larger Florida student population.
|April 20, 2016
|April 20, 2016
General Ordering Information
|Sharon Koon and Yaacov Petscher: Florida State University
|Type of Product:
For questions about the content of this Making Connections, please contact: