Use longitudinal student-level data systems to diagnose dropout scope and identify at-risk students before key transitions¶

Strategy · All strategies
Evidence · no claims cited

Description¶

The guide's first recommendation directs schools to build comprehensive, longitudinal, student-level databases with unique IDs covering absences, grade retention, and low achievement, and to review data regularly with emphasis on transitions. The panel states that 'Regularly analyzing student data is the critical first step both for determining the scope of the dropout problem and for identifying the specific students who are at risk of dropping out.' Schools should designate staff to monitor incoming, current, and departed students and follow up as needed.

Design Implications¶

Context¶

Requirements¶

• Longitudinal student-level databases with unique statewide identifiers
• A designated staff member or team to regularly monitor data and follow up with students
• Accurate withdrawal and transfer documentation with verified enrollment

Constraints¶

• No studies directly evaluate the effect of using data systems on staying in school, progressing in school, or completing school, so the evidence level is low

Target Learners¶

• Middle and high school students at risk of dropping out

Target Learning Goals¶

• Accurate diagnosis of dropout risk and timely identification of students needing targeted support

Related Strategies¶

• Use school-level data systems to identify which students need which types of support for dropout prevention
• Build early-warning indicators and leverage online-learning-system process data to support students before gaps widen in Grade 3
• Use an early warning system based on linked school and human services data to target resources and lessen risks before they become more serious
• Provide rigorous and relevant instruction connecting academics to postsecondary options
• Prioritize more studies of direct dropout behavior, including objective enrollment data, before drawing firm retention conclusions

Examples¶

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Key Sources¶

• Dynarski, M., Clarke, L., Cobb, B., Finn, J., Rumberger, R., and Smink, J. (2008). Dropout Prevention: A Practice Guide (NCEE 2008-4025). Washington, DC: National Center for Education Evaluation and Regional Assistance, Institute of Education Sciences, U.S. Department of Education. Retrieved from https://ies.ed.gov/ncee/WWC/PracticeGuide/9.