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This report details the development of a learning progression for the understanding of fractions. The intended use of the learning progression is to support formative assessment practices for children as they receive instruction during elementary school. The validity of the learning progression is evaluated by mapping its levels to vertically scaled test items answered by students taking Curriculum Associates' i-Ready Diagnostic Assessment. It is shown that there is a significant moderate correlation between the levels of the learning progression and the difficulty of the test items associated with each level.

This document presents a set of classroom assessment principles intended as a resource for practitioners, especially school leaders and district and state policymakers. Together these principles articulate a shared vision for effective classroom assessment practices.

Link to Resource: Between-Year Stability of Growth Percentiles : Technical Brief #3Authors: Benjamin R. Shear and Elena Diaz-BilelloThe purpose of this research brief for the Colorado Department of Education

Link to Resource: Growth Percentiles, Achievement & Demographics: Technical Brief #1 - 2019Author: Benjamin R. Shear and Elena Diaz-BilelloThe purpose of this research brief for the Colorado Department of

Link to Resource: Factors Impacting Growth Percentile Variability: Technical Brief #2 - 2019Author: Benjamin R. Shear and Elena Diaz-BilelloThe purpose of this research brief for the Colorado Department of

Link to Resource: Summary of Median Growth Percentile Analyses: Descriptive Statistics, Demographics Correlations, and Stability AnalysesAuthors: Benjamin R. ShearCitation: Shear, B.R. (2019). Summary of median growth percentile analyses:

Keynote address presented by Benjamin Shear at the St John’s University in Queens, New York at the 7th Annual Leadership Symposium on Mar. 16, 2019. In this talk Dr. Shear will discuss the Stanford Education Data Archive (SEDA),

By Benjamin Shear. When contextual features of test-taking environments differentially affect item responding for different test-takers and these features vary across test administrations, they may cause differential item functioning (DIF) that varies across test administrations. Because many common DIF detection methods ignore potential DIF variance, this paper proposes the use of random coefficient hierarchical logistic regression (RC-HLR) models to test for both uniform DIF and DIF variance simultaneously.

Link to Resource:  Considerations for Adopting and Implementing Innovative Assessment SystemsAuthors:  Benjamin Shear, Elena Diaz-Bilello, Rajendra ChattergoonSuggested citation:  Shear, B.R., Diaz-Bilello, E., & Chattergoon