Use linked school and child welfare data to flag students at academic risk in the coming quarter or semester¶

Strategy · All strategies
Evidence · no claims cited

Description¶

This strategy combines administrative school records with child welfare data to predict which students will encounter academic problems in the near term. The fact sheet explains that it "describes predictors related to near-term academic problems, meaning academic problems in the next quarter or semester," drawing on a report that developed and assessed a predictive model for this purpose. Education agencies can adopt this approach to build early-warning indicators that operate on a quarter or semester timescale.

Design Implications¶

Context¶

Requirements¶

• A companion report's documented approach for developing the predictive model
• Linked school and child welfare data

Constraints¶

• Predictions address near-term academic problems in the next quarter or semester rather than long-term outcomes

Target Learners¶

• Students in schools served by agencies with access to both school and child welfare administrative data

Target Learning Goals¶

• Timely identification of at-risk students for near-term academic support

Related Strategies¶

• Combine in-school and out-of-school data sources to understand and support students flagged as at risk

Examples¶

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Key Sources¶

• Regional Educational Laboratory Mid-Atlantic. (2020). Using School and Child Welfare Data to Predict Near-Term Academic Risks: Fact Sheet. Regional Educational Laboratory Mid-Atlantic. https://www.mathematica.org/publications/using-school-and-child-welfare-data-to-predict-near-term-academic-risks-fact-sheet