The purpose of conducting Data Reviews is to analyze school benchmark assessment data at the student level in reading, mathematics, and other content areas and to analyze how performance relates to the state standards/Oklahoma Academic Standards. Other data to be reviewed may include student behavior and professional activities.
Key Principles for Leading Data Reviews
- Let the data do the talking.
- Let the teacher do the talking. (If necessary, push the teacher to do so!)
- Always go back to specific questions on the test.
- Do not fight the battles on ideological lines.
- You should know the data yourself to lead a data review effectively.
- Make sure the analysis is connected to a concrete action plan you can verify.
Four Steps for Data-Driven Analysis Meetings
1. Praise - Highlight a clear accomplishment for the teacher.
2. Probe on Analysis
- Begin with the ideal student answer.
- Ask the question: “What did students need to be able to do to get that question right?
- Deep dive on the assessment item and patterns that emerge.
- Ask the question: “What pattern do you see in the errors students made?”
3. Plan Your Actions
- Start by naming the student actions that you need to teach.
- Ask the question: “What should students do when they have difficulty with an item like this next time?”
- Add interim assessment and/or check for understand.
- Ask the question: “How will you check for understanding and assess mastery?”
- Make sure teachers write it down.
- Say, “Let’s write down these action steps and add them to your plan.”
- Set follow-up time to analyze evidence of improved student learning.
- Say, “For next meeting on ___, please bring __.” Or schedule a way to see the plan in action.
Oklahoma Data Review (ODR) Model
REAC3H Summit Data Review Power Point (19 Feb 2014)
Results Meeting Protocol
Data-Driven Analysis Meeting
Data Lunch Meeting Agenda
Data-Driven Implementation Rubric
Student Progress on Benchmark by Standard (example)
Student Progress on Benchmark by Standard (blank form)