No Schools Left Behind
In this eight-page article, the author describes and illustrates a specific process for using different types of data to improve student outcomes, including achievement. She defines and illustrates four types of data that schools should gather, including demographics, student learning, perception, and school processes data. She also describes different types of questions that may be answered through cross-section analysis of the data. The article concludes with recommendations for data collection, storage, and analysis.