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Jessica Heppen, Ph.D. Susan Bowles Therriault, Ed.D. National High School Center

Identifying Students At-Risk for Dropping Out of High School: Overview of a Tool for Developing Early Warning Systems April 10, 2009 Governor Lynch’s Dropout Prevention Summit Concord, New Hampshire. Jessica Heppen, Ph.D. Susan Bowles Therriault, Ed.D. National High School Center.

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Jessica Heppen, Ph.D. Susan Bowles Therriault, Ed.D. National High School Center

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  1. Identifying Students At-Risk for Dropping Out of High School: Overview of a Tool for Developing Early Warning SystemsApril 10, 2009Governor Lynch’s Dropout Prevention SummitConcord, New Hampshire Jessica Heppen, Ph.D. Susan Bowles Therriault, Ed.D. National High School Center

  2. National High School Center Mission • Serve as the central source of research and information on high school improvement for the Regional Comprehensive Centers • Identify, summarize and disseminate information on: • latest research and innovations • useful programs, tools, and products • high-quality technical assistance relating to high schools and their diverse student populations • Build capacity of RCCs to promote and support high school improvement at all levels

  3. True/ False Quiz

  4. This Presentation • Overview of early warning systems to identify potential high school dropouts • Background on academic indicators of high school dropout • Lessons from research on “high yield” academic indicators • Demonstration of data tool - Building EWS in schools • Building EWS at the district level • Resources for information on research-based dropout prevention interventions

  5. Ninth Grade is a Critical Year • Ninth grade is a “make or break year” • More students fail 9th grade than any other grade in high school • A disproportionate number of students who are held back in 9th grade subsequently drop out • By the end of 9th grade or even during the first semester, powerful indicators exist that can predict whether students will complete high school • Engagement • Course performance • “On-Track” Indicator Herlihy, C. (2007). State and district-level supports for successful transition into high school. Washington, DC: National High School Center. Allensworth, E., & Easton, J.Q. (2007). What matters for staying on-track and graduating in Chicago Public High Schools: A close look at course grades, failures and attendance in the freshman year. Chicago: Consortium on Chicago School Research.

  6. What are the Key 9th Grade Indicators? Engagement • Attendance/ absenteeism Course Performance • Course grades • Number of credits earned “On-track” Indicator • Core course performance & accumulated credits Research from several U.S. school districts provides a strong foundation for defining 9th grade warning signs that students might drop out, but local adaptation is key

  7. “High-Yield” Academic Indicators: Attendance

  8. “High-Yield” Academic Indicators: Course Failures

  9. “High-Yield” Academic Indicators: GPA

  10. “High Yield” 9th Grade Indicators

  11. On-Track Indicator Source: Allensworth & Easton (2005)

  12. “High Yield” 9th Grade Indicators

  13. Building Early Warning Systems in High Schools • Demonstration of simple tool designed to help high schools use data they already have for dropout prevention • http://www.betterhighschools.org/pubs/ews_guide.asp • http://www.betterhighschools.org/pubs/EWStool.xls

  14. The District Rolein Developing Early Warning Systems to Identify Potential Dropouts • Readiness • Identification • Local Adaptation

  15. The District Role: Readiness • Taking inventory of readily available data and data elements collected • Developing tools for use by district and school to support the key elements of the warning system • Data Collection • Data elements • Data systems • Accessibility of data • Training staff • Data analysis for identifying key indicators • Using the early warning systems tool

  16. The District Role: Identification • Identifying areas of need (e.g., schools, student subgroups) • Targeting resources to support schools • intervention strategies for at-risk students • collaboration among high schools across the district or region

  17. The District Role: Targeting Resources • Identifying critical areas, districts, high schools in need • Allocating resources based on district/school need • Using aggregate on-track rates from high schools or a promoting power index (Balfanz & Legters, 2004) to identify “drop-out factories” (http://www.msnbc.msn.com/id/21532193)

  18. The District Role: Local Adaptation • Conducting data analysis for the local context • Vertical analysis • Historical analysis • Persistent problems • Continuous analysis • Resource: Jerald, C. (2006). Identifying potential dropouts: Key lessons for building an early warning data system. Washington, DC: Achieve, Inc. (http://www.achieve.org/files/FINAL-dropouts_0.pdf)

  19. Local Adaptation Questions for Analysis What percentage of students with each risk factor (or combination)… • Dropped Out? • Graduated (in 4 or 5 years)? What percentage of students without each risk factor (or combination)… • Dropped out? • Graduated (in 4 or 5 years)?

  20. Local Adaptation

  21. Dropout Prevention Strategies

  22. Dropout Prevention Strategies http://www.betterhighschools.org/docs/NHSC_ApproachestoDropoutPrevention.pdf

  23. Attendance and Behavior Monitoring • Focus on Achievement in Core Courses • Tutoring as an Academic Support • Counseling and Mentoring • Small Learning Communities • Content Recovery Courses (Catch-up courses) • Advisories and Team Teaching • Ninth Grade Transition Programs • Partnerships between High Schools and Feeder Middle Schools • Support for Students with Disabilities Outside of School • Tiered Approaches • Career and College Awareness • Community Engagement • Family Engagement Dropout Prevention Strategies Example Programs that Incorporate Attendance and Behavior Monitoring: • ALAS • Check and Connect • Coca-Cola Valued Youth Program • Positive Behavioral Interventions & Supports (PBIS) • Talent Development High School • Teen Outreach Program (TOP)

  24. Discussion Questions • What are the ways that you use data in your schools to identify at-risk students? • What challenges have you experienced or do you anticipate with integrating data systems for reporting, accountability, and intervention/prevention? • What systems do you currently use to allocate resources for dropout prevention in your school? • Are there other indicators that you suspect are as powerful or more powerful than those we’ve highlighted?

  25. For more information from the National High School Center on Dropout Prevention and Early Warning Systems: http://www.betterhighschools.org/topics/DropoutWarningSigns.asp

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