Use prior-years administrative data to forecast school-by-grade enrollment for staffing planning in districts with choice or mobility¶

Strategy · All strategies
Evidence · no claims cited

Description¶

Districts with school choice systems, substantial student mobility, or both can predict incoming fall enrollment at the school-by-grade level using prior-years data to inform staffing plans. The article frames this as addressing an ongoing concern, since inaccurate predictions "can disrupt learning as districts adjust to enrollment fluctuations by reshuffling teachers and students well into the fall semester."

Design Implications¶

Context¶

Requirements¶

• Access to prior-years district administrative data, including cohort sizes, suspension counts, and absence records

Constraints¶

• Predictions differ little in accuracy across methods and leave much student mobility unaccounted for, so reassignment may still be needed in roughly a fifth of incoming grade levels

Target Learners¶

• K-12 students in districts with school choice systems or substantial student mobility

Target Learning Goals¶

• Stable staffing and student assignments across the fall semester

Related Strategies¶

• Adjust transition programs based on family suggestions: longer student sessions, better district-family communication, work-friendly parent sessions, and staffing continuity into fall

Examples¶

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Key Sources¶

• Sean Tanner, Jenna Terrell, Emily Vislosky, Jonathan Gellar, Brian Gill. (2021). Predicting Early Fall Student Enrollment in the School District of Philadelphia. Regional Educational Laboratory Mid-Atlantic, Institute of Education Sciences. https://www.mathematica.org/publications/predicting-early-fall-student-enrollment-in-the-school-district-of-philadelphia