1. Set an equity commitment:
- Set an intention to mitigate bias during your data analysis. Which type of bias do you want to actively work to mitigate? What will you do to self-monitor?
- Who might you be able to invite into the data analysis process? Is there a colleague(s) that can participate to add perspective?
2. Look for strengths, growth areas and patterns/trends/noticings
Strengths/Bright Spots
- Where are there bright spots in the data? Where is there evidence of student growth? What reason(s)/action(s) led to these strengths?
Opportunities for Growths/Areas of Improvement
- Where did students struggle/need more support? Where are there opportunities for growth? What reason(s)/action(s) led to these growth areas?
Noticings/patterns/trends
- Based on the data, how did students perform based on subgroups? Are there patterns of misconceptions or gaps in conceptual understandings? Are there any disparities in the data (consider factors within your locus of control)?
3. Develop an Action plan.
- Based on the data, what are the most appropriate next steps needed to support students in meeting their potential? (Examples might include: a tool or support that you will teach students to use, an instructional routine that you will emphasize, a re-teach lesson that you will design or an activity you will incorporate to address prerequisite standards from previous grades)
4. Engage in an equity pause (to ensure inclusive support)
Pause to reflect on the following:
- Will the action plan serve all kids? Who may be left out?
- What additional support may be needed (consider UDL aligned scaffolds)?
- What evidence will you collect to determine the effectiveness of your method?
- Based on the equity pause, revise your action plan. What are the most important next steps needed to support all students in meeting their potential?
- If additional support is needed, who else is available to support?
Adapted from Responding to Data Equitably. Professional Education, Relay GSE
