Improve evaluation fairness by statistically adjusting ratings for classroom characteristics, comparing teachers within similar contexts, and training evaluators on contextual influences¶

Strategy · All strategies
Evidence · 1 claim (1 for) · 1 study (1 associational), q3 · 0 of 1 report an effect size · 1 claim rests on one study

Description¶

The article recommends district-level practices to reduce composition-driven bias in teacher evaluation: "Adjusting ratings statistically for classroom characteristics", "Comparing teachers within similar classroom contexts", and "Training evaluators to recognize contextual influences". These follow from the finding that ratings partly reflect the students assigned rather than teaching quality alone.

Design Implications¶

Context¶

Requirements¶

• Districts need classroom composition data (academic, behavioral, and demographic measures) and multiple years of ratings to implement statistical adjustment or within-context comparison.

Constraints¶

• The adjustment result is demonstrated through simulation on Chicago Public Schools data, not an implemented policy evaluation.

Target Learners¶

• K-12 teachers in urban public school districts

Target Learning Goals¶

• Fair and accurate measurement of teaching quality for tenure, promotion, and dismissal decisions

Claims¶

• Simulated adjustment of ratings for classroom context improves Black teachers' rankings by about 8 percentile points, with the largest gains for teachers serving more disadvantaged students [+W]

Related Strategies¶

Examples¶

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Key Sources¶

• Delgado, W., & Sartain, L. (2026). Classroom composition affects teacher performance ratings. Educational Evaluation and Policy Analysis, 48(2). https://consortium.uchicago.edu/publications/classroom-composition-affects-teacher-performance-ratings