Using growth models to monitor school performance: comparing the effect of the metric and the assessment |
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| Authors: | Pete Goldschmidt Kilchan Choi Felipe Martinez John Novak |
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| Institution: | 1. California State University Northridge , Northridge, CA, USA;2. National Center for Research on Evaluation Standards and Student Testing (CRESST) , University of California , Los Angeles, CA, USA goldschmidt@cse.ucla.edu;4. National Center for Research on Evaluation Standards and Student Testing (CRESST) , University of California , Los Angeles, CA, USA;5. Graduate School of Education and Information Studies , University of California , Los Angeles, CA, USA;6. Long Beach Unified School District , Long Beach, CA, USA |
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| Abstract: | This paper investigates whether inferences about school performance based on longitudinal models are consistent when different assessments and metrics are used as the basis for analysis. Using norm-referenced (NRT) and standards-based (SBT) assessment results from panel data of a large heterogeneous school district, we examine inferences based on vertically equated scale scores, normal curve equivalents (NCEs), and nonvertically equated scale scores. The results indicate that the effect of the metric depends upon the evaluation objective. NCEs significantly underestimate absolute individual growth, but NCEs and scale scores yield highly correlated (r >.90) school-level results based on mean initial status and growth estimates. SBT and NRT results are highly correlated for status but only moderately correlated for growth. We also find that as few as 30 students per school provide consistent results and that mobility tends to affect inferences based on status but not growth – irrespective of the assessment or metric used. |
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| Keywords: | school accountability multilevel longitudinal models test metrics |
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