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Predicting grade 3 reading assessment performance in North Carolina: Risk prediction and instructional implications

Region:
Southeast
Abstract:

Description: North Carolina educators have routinely administered screening and monitoring assessments statewide in the primary grades over the past six years, yet the percentage of students reaching grade-level performance at the end of grade 3 has largely remained unchanged. The lack of improvement in student results prompted state-level policymakers to further understand the relationship between the screening and progress monitoring assessments administered in each grade and the grade 3 end-of-grade assessment, and to use these relationships to identify decision rules for identifying students who are at risk of poor performance. This study will examine these relationships using a longitudinal sample of students who participated in the grade-level assessments from kindergarten through the end of grade 3, and generate, if possible, decision rules for identifying students at risk of poor performance in reading.

Research Questions: The study will be guided by the following research questions:

  1. How can educators use students' scores on interim assessments in the middle of the year in kindergarten to predict reading proficiency at the end of grade 3?
  2. How do these results change if educators use interim assessments taken at the beginning of the year and middle of the year in grade 1 in place of the kindergarten scores?
  3. How do these results change if educators use interim assessments taken at the beginning of the year in grade 2?
  4. How do these results change if educators use interim assessments taken at the beginning of the year in grade 3?

Study Design: Associations between student performance on grade-level interim assessment measures and proficiency on the grade 3 end-of-grade assessment in reading will be modeled using classification and regression tree (CART) analyses. The statistical package rpart will be used for the CART analyses. The classification rules resulting from the CART analyses will be judged by traditional measures of classification accuracy, including the sensitivity and specificity indices.

Projected Release Date: Winter 2019/2020

Partnership or Research Alliance: REL Southeast Improving Literacy Alliance

Related Products: Descriptive Study

Principal Investigators & Affiliation:
Sharon Koon, Ph.D.
Senior Research Associate
Florida State University