This Guide offers five recommendations to help educators effectively use data to monitor students' academic progress and evaluate instructional practices. The Guide recommends that schools set a clear vision for schoolwide data use, provide supports to foster a data-driven culture, make data part of an ongoing cycle of instructional improvement, and teach students how to use their own data to set learning goals. The Guide also recommends developing and maintaining a districtwide data system.
Access the Practice Guide on the What Works Clearinghouse website.
Multimedia Overview Transforming Teaching and Learning Through the Effective Use of DataUse this presentation to learn how practices for Using Student Achievement Data to Support Instructional Decision Making can be implemented to improve instruction and learning. Through implementing a cycle of instructional improvement, teaching students to examine their own data, establishing a vision for data use, supporting a data-driven culture, and maintaining a districtwide data system, educators can refine teaching and learning to better meet students' needs. (7:57 min)
Explore these recommended practices:
- <<Cycle of Improvement
Make data part of an ongoing cycle of instructional improvement.
- <<Student Use of Data
Teach students to examine their own data and set learning goals.
- <<Vision for Data Use
Establish a clear vision for schoolwide data use.
- <<Data-Driven Culture
Provide supports that foster a data-driven culture within the school.
- <<Districtwide Data System
Develop and maintain a districtwide data system.
Visual Diagram Using Student Achievement Data to Support Instructional Decision MakingThis diagram serves as a visual reminder of the five interrelated practices that are recommended for using student achievement data effectively to support instructional decision making. A districtwide data system forms the "foundation" for the other recommendations. Establishing a clear vision and supports for data use (on the walls around the schools) set the conditions for data use. Within schools and classrooms, teachers can collaboratively engage in data analysis through cycles of instructional improvement and teach students to understand their own data and set learning goals. Together, these practices are part of a comprehensive and cohesive framework for using data to support instructional decision making.
Data-Driven Instructional Decision MakingLaura Hamilton, Ph.D.
RAND Corporation and University of Pittsburgh's Learning Sciences and Policy Program
Dr. Laura Hamilton, chair of the IES panel that developed the Practice Guide, Using Student Achievement Data to Support Instructional Decision Making, explains the five recommended practices and offers considerations for implementation of the practices. (6:23 min)