Data-use cycle: collect and prepare data, interpret and hypothesize, modify instruction¶

Theory · All theories
Evidence · 1 claim (1 for) · 1 study (1 review), q2 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The guide frames using data to improve instruction as a cyclical process with three steps: "Collect and prepare a variety of data about student learning", "Interpret data and develop hypotheses about how to improve student learning", and "Modify instruction to test hypotheses and increase student learning". Teachers then restart the cycle with new performance data to evaluate their instructional changes. Because the process is cyclical, teachers can begin at any point, though the guide presents data collection as the first step.

Design Implications¶

Context¶

Requirements¶

• Teachers collect data from a variety of sources, including annual, interim, and classroom assessment data
• Hypotheses must be testable with future assessment data

Constraints¶

• No literature was located that assesses the impact on student achievement of using an inquiry cycle as a framework for data analysis

Target Learners¶

• K-12 teachers

Target Learning Objectives¶

• Using student achievement data to make instructional decisions that raise achievement

Claims¶

• All five of the guide's data-use recommendations are supported by low levels of evidence [+W]

Related Theories¶

Examples¶

• Teach students to examine their own data and set learning goals
• Data Driven Inquiry
• Data Wise Improvement Process

Key Sources¶

• Hamilton, L., Halverson, R., Jackson, S., Mandinach, E., Supovitz, J., & Wayman, J. (2009). Using student achievement data to support instructional decision making (NCEE 2009-4067). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. Retrieved from https://ies.ed.gov/ncee/wwc/PracticeGuide/12