Framework for understanding the critical properties of data that matter for student achievement¶

Theory · All theories
Evidence · 2 claims (2 for) · 2 studies (1 review, 1 associational), q1–q2 · 0 of 2 report an effect size · 2 claims rest on one study

Description¶

The article describes a framework offered by Elaine Allensworth for understanding "the critical properties of data" and the tools educators need to focus on the metrics most relevant to student achievement. It is positioned as bridging theory and practice, rooted in two decades of research on educational policy and practice and real-world success stories from Chicago Public Schools, and is intended to help educators build a culture of data-driven collaboration.

Design Implications¶

Context¶

Requirements¶

• Educators need tools to focus on the metrics that matter most for student achievement, per the article's framing of the framework's purpose

Constraints¶

Target Learners¶

• school educators and leaders

Target Learning Objectives¶

• using data to improve student achievement outcomes such as attendance, test scores, and graduation rates

Claims¶

• The article claims schools can improve attendance, test scores, and graduation rates by identifying high-impact metrics and fostering a collaborative culture of improvement [+W]
• Higher absence rates are the most important factor explaining why students with disabilities fail more courses and earn lower GPAs than students without identified disabilities [+W]

Related Theories¶

• Four-property framework for effective school improvement data: timely, clear, malleable, and predictive

Examples¶

• Use Early Warning Indicator (EWI) and Multi-Tiered Systems of Support (MTSS) for continuous improvement

Key Sources¶

• Elaine Allensworth. (2025). Using Data to Improve Schools. Corwin. https://consortium.uchicago.edu/publications/using-data-to-improve-schools