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Regional Educational Laboratory Program


Local Validation of Graduation Indicators in Three Ohio Districts

Region:
Midwest
Abstract:

Description: States, districts, and schools are increasingly using early warning indicator systems in which readily available data on student attendance, academics, and behavior are used to identify students at risk for not graduating from high school on time. Identified students can then be matched with interventions in an attempt to help them get on track for graduation. REL Midwest is working with three Ohio districts to develop a set of locally tailored early warning indicators for each district. Study results will provide information about the strongest indicators of four-year graduation for the students in each district, as well as the indicator thresholds at which students are most accurately identified as graduates or nongraduates.

Research Questions: This study addresses the following research questions:

  1. For each candidate indicator of nongraduation, what is the optimal cutpoint for accurately classifying students as on track or off track to graduate? How do these cutpoints vary across districts and grades?
  2. Which indicators consistently predict failure to graduate on time when their optimal cutpoints are used?
  3. Which of the consistently predictive indicators have the highest correct off-track prediction rates, lowest false alarm rates, and best overall accuracy? How does the accuracy of indicators vary across districts and grades?

Study Design: Each district has provided data on student attendance, academics, and behavior for Grades 8–12 for two cohorts of students. Regression analyses will identify the strongest eighth- and ninth-grade predictors of four-year graduation. These predictors will be converted to binary indicators using receiver operating characteristic curve analysis. A second set of regression analyses will identify the strongest binary indicators of graduation. Descriptive analysis will be used to examine the accuracy with which single and multiple indicators identify graduates and nongraduates. Results will be presented to highlight similarities and differences among the three districts.

Projected Release Date: Summer 2016

Research Alliance: Dropout Prevention Research Alliance

Study Related Products: Making Connections report and Stated Briefly report

Principal Investigators & Affiliation:
Jim Lindsay, American Institutes for Research