Use longitudinal interim assessment data, modeled with seasonal trends, to monitor progress of students, classrooms, and schools within and across school years¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The article recommends a modeling approach for interim assessment data that respects their seasonal structure. It notes that "These tests are often used to monitor the progress of students, classrooms, and schools within and across school years," and argues that models should capture both within-year gains and losses and year-to-year growth rather than ignoring one or the other.

Design Implications¶

Context¶

Requirements¶

• Access to longitudinal interim assessment data collected repeatedly within and across school years

Constraints¶

• The article notes there is little guidance on how to choose among candidate models for such data

Target Learners¶

• K-12 students monitored with interim assessments

Target Learning Goals¶

• Tracking achievement progress for students, classrooms, and schools

Affordances¶

• Seasonal Growth Model Interim Achievement Data

Related Strategies¶

Examples¶

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Key Sources¶

• James Soland, Yeow Meng Thum. (2022). Estimating and comparing growth using longitudinal interim achievement data with seasonal trends. Journal of Research on Educational Effectiveness 15(3) 635-654. https://doi.org/10.1080/19345747.2021.2018744