Guide to Using Data in School Improvement Efforts

Author: North Central Regional Educational Laboratory (NCREL), Sargent, J., Shively, J.
Publisher: Learning Point Associates
Publication Date: 2004, December
Publication City: Naperville
Publication State: IL
Full text available online at: http://www.ncrel.org/datause/howto/guidebook.pdf

Abstract (written by WestEd)

This guide, designed for educators learning to more effectively use data, provides the fundamentals for understanding data-driven decision making that can help guide instruction, curriculum, and programming. After a brief introduction to prerequisite concepts — the school improvement cycle and the characteristics of data-driven decision making — the guide goes through eight steps to data-driven decision making:

1. Develop a Leadership Team
   
2. Collect various types of data
   
3. Analyze data patterns
   
4. Generate hypotheses
   
5. Develop goal-setting guidelines
   
6. Design specific strategies
   
7. Define evaluation criteria
   
8. Make the commitment

The guide focuses on the different types of data and what they are useful for: achievement data, demographic data, program data, and perception data. It delves deeper into the three tiers of achievement data: annual, large-scale assessment data; periodic assessment data; and ongoing classroom assessment data.