Use multiple, diverse data sources selected to offer distinct yet complementary information¶

Strategy · All strategies
Evidence · no claims cited

Description¶

This strategy recommends combining several intentionally chosen data sources rather than relying on a single measure, so that together they give a well-rounded picture of learning. The brief notes that "using multiple, diverse sources of data can provide a more robust picture of learning" and that sources should be "carefully selected to ensure that they offer distinct yet complementary information" to avoid knowledge gaps. It explicitly distinguishes this from examining an overwhelming deluge of data.

Design Implications¶

Context¶

Requirements¶

• Data sources must be analyzed collectively and chosen to be distinct yet complementary rather than redundant

Constraints¶

• Does not require examining a deluge of data that can be hard to untangle and understand

Target Learners¶

• all students whose learning is being understood through data

Target Learning Goals¶

• building a robust, well-rounded picture of student learning

Related Strategies¶

• Align selected data directly to the purpose or problem the data use is meant to serve
• Use data collaboratively through a structured data analysis process among educators
• Keep students' lived experiences at the center of data use and ensure data reflect students' lives
• Use multiple evidence sources alongside benchmark scores when identifying students for intensive intervention
• Examine literacy screening data for intersectional differences not apparent from simple disaggregation and consider student and school characteristics together when targeting supports

Examples¶

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Key Sources¶

• Jessica Arnold, Julie Webb. (2024). 7 Recommendations for Using Education Data to Support Equitable Learning Outcomes. WestEd. https://eric.ed.gov/?id=ED655653