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Early Warning Data System (EWDS) The EWDS tool designed to help Texas districts/charters identify students who are at risk of dropping out by collecting data on key indicators and through use of a systemic process, implement interventions, verify success, and adjust interventions if necessary to reduce dropout rates and improve graduation rates. This tool is freely available. 2

Key Indicators of Potential Dropouts The EWDS tool tracks key indicators related to HS dropout 1. *Attendance 2. *Course performance  Course failures  Low grade point average (GPA)  F’s in core courses and credits earned in 9 th grade 3. Behavior *High Yield Attributed to the National High School Center’s resources: Developing Early Warning Systems to Identify Potential High School Dropouts (2008; retrieved from and Approaches to Dropout Prevention: Heeding Early Warning Signs With Appropriate Interventions (2007; retrieved from 3

Customized Application EWDS provides pre-defined indicators (attendance, academic performance, & behavior), and allows you to develop up to 5 additional custom indicators. Reports are also available on individuals and groups for those who are below the benchmark for each indicator. Reports are based on school data regarding academic performance, attendance and behavior. Data can be imported or entered manually. Reports can be viewed, printed or shared via Microsoft Excel.

Reducing Dropouts by Using an Early Warning Data System Ariel 5

First Quarter Ariel Chavez – First Quarter Data 6

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8 Ariel Chavez Student Details

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10 Ariel Chavez Student Details

Planning and Implementing Successful Dropout Prevention Interventions Remember the DIVA: Data Interventions Verify Adjust 11

DIVA 1 st — Collect student data: Attendance* Course performance* Behavior 12 *High yield

Consider the reasons... If, for example, attendance is the most prevalent indicator at the school... one would need to determine why students are absent from their high school. Think about what the reasons might be... 13

After determining the leading dropout indicator by collecting data... 1 st – Collect Data 2 nd — Identify appropriate Interventions -Consider one indicator at a time until interventions are well implemented. -Consider 2 to 3 interventions for each indicator. DIVA 14

Make the difference between an effective and ineffective intervention... DIVA 3 rd – Verify the intervention’s implementation and impact 4 th – Adjust the intervention based on the data 15

Examples of verifying implementation for tutoring Verify enrollment and demographics. Verify attendance and demographics. Verify the extent of alignment for curriculum and instruction between tutoring and course teachers. 16

Examples of verifying impact for tutoring Verify students’ grades. Verify the student and staff perceptions of the tutoring program through surveys. 17

Targeting Interventions For individual students For groups of students For the entire school 18

Region 20 Education Service Center Contacts Gina Christenson Cheri Hendrick (technical assistance) Larry Rodriguez