High school graduation and dropout rates have long been used as a key indicator of the effectiveness of a school system, but how best to calculate these rates is controversial for both educators and policymakers.
HIGH SCHOOL DROPOUT, GRADUATION, AND COMPLETION RATES: BETTER DATA, BETTER MEASURES, BETTER DECISIONS, a new report from the National Research Council and the National Academy of Education, offers guidance to the federal government, states, and schools on measuring dropout rates and collecting data to help them achieve better outcomes for students.
Among the report’s recommendations:
- When choosing among different ways to calculate a graduation or dropout rate, analysts should keep in mind the purpose of the rate. If the purpose is to characterize the education level of the U.S. population, for example, it may not matter whether people received a traditional diploma or a GED, or how long it took them to earn it; however, those factors are critical in evaluating a particular school’s effectiveness in graduating students in four years.
- Some rates are calculated by comparing the total number of seniors graduating in a given year with the number of students who entered ninth grade four years earlier. Rates calculated in this way are useful as rough approximations but are too imprecise to make fine distinctions, such as comparisons across states, districts, or schools, or over time. The most accurate rates are those based on longitudinal data, which track students over the course of their schooling. Dropout and completion rates should be based on individual student-level data whenever possible.
- Accountability policies should require schools and districts to set and meet realistic and meaningful goals for improving their graduation rates. Rates that are used for accountability should minimize the bias that results from students who transfer between schools and from the ways that subgroups — such as English language learners, students with disabilities, or disadvantaged students — are defined.
- To help identify students at risk of dropping out, state data systems should incorporate established early indicators of risk, such as frequent absences, poor behavior, being older than the average age for grade, and having a record of frequent transfers.
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