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High School Dropout, Graduation, and Completion Rates: Better Data, Better Measures, Better Decisions
such as by identifying the factors associated with dropping out, using these factors to identify at-risk students, and undertaking and evaluating interventions intended to improve outcomes for these students. The approach taken by the California Dropout Research Project provides an example of the ways that states can make use of national data sets to conduct their own research, identify precursors to dropping out, and evaluate the effectiveness of interventions. In addition to identifying individual factors associated with dropping out, this endeavor identified school characteristics associated with lower dropout rates, such as college preparatory programs and vocational education programs. We make two recommendations with regard to the kinds of actions that states should take to improve policy and practice:
RECOMMENDATION 7-2: State governments should develop more robust education data systems that can better measure student progress and institutional improvement efforts.
RECOMMENDATION 7-3: State governments should support reform efforts to demonstrate how districts can develop and effectively use more comprehensive education data systems to improve dropout and graduation rates along with improved student achievement.
To truly help improve outcomes for students, data systems need to incorporate the information needed to enable early identification of at-risk students. The research discussed in this report suggests that indicators such as the following are associated with dropping out: frequent absences, failing grades in reading or mathematics, poor behavior, being over age for grade, having a low grade-point average (GPA) in grade 9, failing grade 9, or having a record of frequent transfers. Moreover, the research shows that some of these factors may become evident as early as grade 6. Although this research provides an important foundation for states, districts, and schools to build on, the findings also suggest that the predictive value of these factors varies across school systems. Thus, we think it is important for states and districts to conduct their own studies to determine the factors associated with dropping out from their school systems. Once they are determined, measures of these factors should be incorporated into the data system so that at-risk students can be identified in time to intervene. We make the following recommendation for specific steps that states and districts should take.
RECOMMENDATION 5-1: States and districts should build data systems that incorporate variables that are documented early indicators of students at risk for dropping out, such as days absent, semester and course grades, credit hours accrued, and indicators of behavior problems. They should use these variables to develop user-friendly systems for monitoring students’