Demonstration at AEA 2016 in Atlanta
State tests, screening, progress monitoring, summative and formative assessments, and curriculum-based measures all provide data to determine student progress. In fact, we’re drowning in data that is all too often underused. This demonstration shows how to reformat, combine, analyze, and use assessment data to identify students’ needs—beyond those revealed when analyzing tests one by one—and further improve academic opportunities for at-risk students. Combining data across assessments and conducting simple analyses can reveal surprises—and result in more focused individual interventions and systems level changes to help struggling students. Additionally, analyses with combined data can expose misalignment between assessments that suggest interventions which might not be revealed otherwise. Both SPSS and R code to reformat, combine, and analyze multiple data sets will be shared during this session, and examples of surprising findings from several school districts will be shared.