Disaggregate attainment data by student subgroup to locate barriers and target supports¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The researchers' approach of breaking attainment indicators down by student characteristics to understand which students face barriers. The release states that "where possible, researchers disaggregated data by race/ethnicity and gender, disability status, and English Learner (EL) status to understand which students face more barriers to educational attainment and where different strategies and supports are needed." This practice directs improvement efforts toward the students and settings that need them most.

Design Implications¶

Context¶

Requirements¶

• Sufficient data availability, since disaggregation happens only where possible

Constraints¶

• The release does not print the subgroup-specific rates

Target Learners¶

• Chicago Public Schools students, including English Learners and students with disabilities

Target Learning Goals¶

• Identifying barriers to high school graduation, college enrollment, and college completion

Claims¶

Related Strategies¶

• Use disaggregated attainment data with an aspiration benchmark to identify where students face barriers and hold institutions responsible for change
• Examine data across subgroups and account for diversity within subgroup categories before interpreting score differences
• Districts should share sufficient subgroup data with assessment providers to enable multi-subgroup disaggregation
• Use a targeted universalist approach to identify student groups with less positive survey reports and respond with empathy, curiosity, and support

Examples¶

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Key Sources¶

• Mahaffie, S., Usher, A., Nagaoka, J., & McKoy, D. (2025). The Educational Attainment of Chicago Public Schools Students: 2024. To&Through Project and UChicago Consortium on School Research. https://consortium.uchicago.edu/publications/the-educational-attainment-of-Chicago-Public-Schools-students-2024