Bernhardt, V. L. (2003). No schools left behind. Educational Leadership, 60(5), pp. 26-30.
Bernhardt provides information on the kinds of data that are important for continuous school improvement and how educators can most effectively organize these data for easy access and analysis. The author discusses four types of data that are useful for assessing school effectiveness (i.e., demographics, student learning data, perceptions of learning environment, and school processes), how to organize data through data snapshots and intersecting data categories, and the technical support needed to effectively and accurately manage and analyze data. Bernhard concludes with suggestions for getting started with the data analysis process. Overall, she maintains that examining student assessment data in conjunction with school climate and school processes is necessary to develop a complete picture of how students are doing and to determine how to improve learning for all students.
Analysis, Data Integrity, Data Systems, Quality of Assessment Data, Scenarios: School S1