# Study Overview for Schools and Districts

Purpose of the Study

One in four students in the United States fails to graduate from high school and graduation rates are significantly lower for students who are racial or ethnic minorities, economically disadvantaged, migrant and/or limited

English proficient, and receiving special education services. However, strong foundational research highlights critical indicators in ninth and tenth grade that powerfully predict whether students are “on track” for high school graduation. These indicators, which typically focus on student engagement measures (attendance) and course performance (grades, credits earned), can be used as part of an early warning system to flag at

- risk students early, assign ap propriate interventions, and get students back on track for graduation. As part of Ohio’s Comprehensive Continuous Improvement Plan, the state has committed, through adoption of the Ohio Improvement Process, to promoting student success through data

- driven decision making, targeted programming, ongoing student monitoring, and evaluation of improvement process effectiveness. Use of an early warning system is one strategy that schools can use to address the Ohio Improvement Process. One such early warning sys tem is the early warning and intervention monitoring system (EWIMS) developed by the National High School Center. The EWIMS model encourages educators to use data to consider and provide appropriate interventions to students, and provides a means for monit oring student progress over time. At the core of EWIMS is the use of simple tools that encourage educators to routinely examine indicators that identify students as “off track” and take action. Despite increasingly widespread implementation of early warni ng systems by states, districts, and schools, there have been no rigorous studies testing the impact of using an early warning system to improve student outcomes such as staying in school, progressing in school, and probability of graduating. There is also little research examining how using an early warning system can shape a school’s culture for data use including how schools allocate their limited dropout prevention resources. To address this gap, this study will provide the first rigorous test of the im pact of an early warning system. This study, funded by the U.S. Department of Education’s Institutes of Educational Sciences, is being conducted by the Midwest Regional Educational Laboratory at the American Institutes for Research. The planned study will examine the impact of EWIMS on (1) student outcomes including student risk status for dropout, scores on graduation tests, persistence and progress in school and likelihood of on

- time graduation; and (2) school outcomes including how schools allocate drop out prevention interventions for students and their data

- use culture. Participating in this high

- profile, large

scale study will give your school and district an opportunity to access these innovative resources at no
cost and help inform educational policy in Ohio and at the federal level. 

# Study Design

The study will take place in approximately 70 high schools in Ohio during the 2013

– 14 and 2014

– 15 school years. All schools that participate in the study will receive the early warning system at no cost. Par ticipating schools will be assigned by lottery to receive access to the EWIMS model (including the tool and technical support for implementation) in the 2013

- 2014 school year or the fall of 2015 (following the completion of the study). Schools assigned to receive the EWIMS model in the fall of 2015 will continue “business as usual” practices to identify at

- risk students and allocate dropout prevention resources through 2014

- 15. The study will examine student outcomes for all students in grades 9 and 10 dur ing the 2013

– 14 school year and all students in grades 9 through 11 during the 2014

– 15 school year for schools that implement EWIMS in 2013

- 2014 and those that do not implement EWIMS during the study period. All student outcome data will be collected from school or district administrative data, the EWS tool or the Ohio Department of Education; therefore there will be no primary student data collection for this study. To understand how EWIMS may impact schools, all participating schools will be asked to comp lete an annual Web

- based survey about data use practices and schools implementing EWIMS during the two

- year study period may be asked to participate in interviews about their experiences using the tool.

# EWIMS Intervention

The EWIMS process is designed to i dentify students who are at risk of dropping out of school and s upport and monitor at

- risk students through school

- wide strategies and targeted interventions. EWIMS is currently in use in 67 districts in six states, and the tool has been downloaded mor e than 20,000 times from the National High School Center’s website.

EWS tool. At the heart of the EWIMS model is an early warning data tool used to flag students as “at risk” based on attendance, course performance (grades, credits, GPA), and behavior ind icators. The tool enables users to identify students who are at risk of dropping out of school, record assignments to available interventions, and monitor students’ response to those interventions. The Excel based tool provides a number of reports accessib le to users, including:

 School

- Level Reports: Graphical reports that show trends in student risk status across the school

 Student

- Level Reports: Lists of students, grouped by indicators of risk and/or assigned intervention programs, that include summary information

 Detailed Student Reports: Simple reports that can be generated for each individual student and show student information, indicators of risk status, and any assigned interventions

 Student

- Level Intervention Summary Reports: Lists of students, th eir indicators of risk (flagged or not flagged), and the number and types of interventions to which each student was assigned EWIMS Implementation Process. In addition to the tool, the National High School Center has devised a

seven

- step EWIMS implementation process to support implementation. The process guides users to make informed decisions about how to use data to support at

risk students and how to continue to monitor their progress over time. In addition to focusing on individual students, the process guides users to examine the success of specific supports or interventions and to examine possible systemic issues (school climate) that may relate to dropout trends. EWIMS Seven

- Step Implementation Cycle



# Initial Criteria for Participation

The study will include approximately 70 high schools in Ohio. To qualify, schools must (1) have at least 150 ninth

grade students; (2) a graduation rate between 25 and 95 percent and (3) not already be implementing an early warning system tool for using da ta to flag at

- risk students. 

# Study Timeline

Through January 2014, the study team will discuss participation with districts and schools that meet the initial criteria and conduct on

- site or virtual meetings with school principals, guidance counselors and dropout prevention coordinators. Participating schools will sign memoranda of understanding in January 2014 and be assigned by lottery to receive access to the EWIMS model in January 2014 (treatment group) or the 2015

- 2016 school year (“business as usual” control group). Training for EWIMS implementat ion in treatment schools will begin in January 2014. Data collection activities will continue through but not beyond the 2014

– 15school year.


# For Additional Information

For more information about the study, or to begin a conversation about partner ing on this project, contact Dr. Nicholas Sorensen (nsorensen@air.org or 312

- 283

- 2318) or Dr. Mindee O’Cummings (mocum mings@air.org or 202

- 403

- 5254). STEP 1

— Establish Roles & Process

STEP 2

— Use the EWS tool

STEP 3

— Analyze EWS data

STEP 4

— Interpret EWS data STEP 5

— Assign & Provide Interventions STEP 6

— Monitor Students STEP 7

— Evaluate & Refine EWIMS