Final Agreement Form (District MOU)

District Roles and Responsibilities: 

Early Warning and Intervention Monitoring System Study

Dear <superintendent>,

On behalf of American Institutes for Research (AIR) (www.air.org) and its partners, we welcome 

you to the Early Warning and Intervention Monitoring System (EWIMS) study. We are excited 

about this project. Its purpose is to examine the impact of EWIMS on (1) student outcomes 

including student risk status for dropout, scores on state assessments, persistence and progress in 

school and likelihood of on-time graduation; and (2) school outcomes including how schools 

allocate dropout prevention interventions for students and their data-use culture. This document 

contains an overview of the study and a brief description of the intervention, followed by a 

description of the roles and responsibilities for your district and for the study team, including the 

benefits of participation, and the project timeline. Please review the contents of this document 

and sign the last page to indicate your agreement to participate. Return the signed last page to Dr. 

Nicholas Sorensen (nsorensen@air.org, fax 312-288-7601).

Overview

The primary goal of the EWIMS study is to evaluate whether implementing an early warning and 

intervention monitoring system for identifying students at-risk of dropping out and using this 

system to assign students to dropout prevention interventions will improve student outcomes 

including student risk status for dropout, scores on graduation tests, persistence and progress in 

school and likelihood of on-time graduation. In addition, this study will also examine the impact 

of implementing EWIMS on school outcomes including how schools allocate dropout prevention 

resources for students and their data-use culture. Study results will yield valuable information for 

the state of <state name> and for districts and schools across the country about the viability and 

benefits of using an early warning system to prevent high school dropout and help struggling 

students get back on track for eventual graduation. The study is being funded by the U.S. 

Department of Education, Institute of Education Sciences, and will run from January 2014 

through the spring of 2016.

We look forward to working with <district name> as a partner in this project! 
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

The EWIMS Model

The EWIMS model, developed by the National High School Center at AIR, is a multistep 

process intended to encourage systematic and comprehensive implementation within schools. 

The process is based on a combination of research on data use in schools and National High 

School Center’s experience working with states, districts, and schools implementing early 

warning systems. 

At the heart of the EWIMS process is an early warning data tool used to flag students as “at risk” 

based on attendance, course performance (grades, credits, grade point average [GPA]), and 

behavior indicators. The tool enables schools to identify students who are at risk of dropping out 

of school, record assignments to available interventions, and monitor students’ response to those 

interventions.

Beyond the development of the data tools, the National High School Center has devised a sevenstep 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 (e.g., school climate) that may relate to dropout trends.

Figure A-2. Early Warning Intervention Monitoring System Implementation Process

As shown in Figure 1, the steps are intended to be cyclical. At the core of this data-driven 

decision-making process, the steps focus users on key indicators that identify which students are 

showing signs of risk of dropping out of high school and guide users to go beyond the indicator 

data and other relevant information to connect at-risk students to dropout prevention or academic 

support interventions. The EWIMS model does not prescribe specific interventions for schools to 

implement. Instead, the model is designed to allow schools flexibility to decide which 

interventions they believe are most effective for their students’ needs. Ideally, the EWIMS model 

allows users to identify students with accuracy and provide supports and intervention of the 
schools’ choosing to at-risk students, resulting in improved outcomes for students, including 

higher attendance rates and improvement in academic performance leading toward successful 

graduation. 

This Study

Despite increasingly widespread implementation of early warning 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 

graduating. There is also little research examining how using an early warning system can shape 

a school’s culture for data use—increased data-driven decision making (assigning interventions 

to students) and processes and professional development to support using data to improve 

teaching and learning. This study will address these gaps and provide the first rigorous test of the 

impact of an early warning system. The study will:

 Identify a sample of eligible and interested schools in <state name>. The study team 

will conduct outreach to schools that meet initial eligibility criteria to confirm eligibility 

and discuss interest in participating in the EWIMS study. The study will include 

approximately 70 high schools in the Midwest. 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 data to flag at-risk 

students.

 Use a lottery to randomly assign half of the participating schools to implement 

EWIMS in February 2014 and the other half to implement in fall of 2015. Half of 

participating schools will be randomly assigned to receive access to the EWIMS model in 

Feburary 2014 (including the tool and technical support for implementation) and the 

other half of participating schools will be randomly assigned to conduct “business as 

usual” for identifying at-risk students until the fall of 2015 when they will receive the 

same resources and supports for implementing EWIMS.

 Implement EWIMS. All schools will implement the seven-step EWIMS process either 

in February 2014 or the fall of 2015 (depending on random assignment by lottery). The 

seven steps for implementation are as follows:

o Step 1—Establish Roles and Process. In this step, the composition of the EWIMS 

team is established;1team members then determine frequency and duration of 

meetings and develop a shared vision or focus of the team’s work.

o Step 2—Use the EWS tool. In this step, the school-based EWIMS teams are 

trained on the use and purpose of the tool itself. This step also includes first 

customizing the tool settings and importing the student demographic and initial 

administrative data and also ongoing refreshing of the administrative data in the 

tool and the running of automated and custom lists and reports available within 

the tool. 

 

1

The goal is not to create yet another “team” with functions that may or may not overlap with functions of other 

already existing teams. Rather, integration with existing team structures (if functionally operational) is optimal.
o Step 3—Analyze EWS data. In Step 3, EWIMS teams focus their attention on 

student- and school-level data, based on the indicators available in the tool. This 

data review process is intended to identify areas of focus and further 

investigation. 

o Step 4—Interpret EWS data. Step 4 guides teams to bring in additional data 

(external to the tool) to provide more context and a fuller picture to inform the 

EWIMS team’s consideration of specific needs of individuals or groups of 

flagged students. Unlike Step 3, which is focused on the indicator flags 

themselves (i.e., the data in the tool), this step addresses root causes of why 

students might be identified as at risk for one or more indicators. The 

implementation team will provide training to identify root causes that focus on 

acquiring additional formal (e.g., administrative records) and informal (e.g., from 

teacher, family, and student) input. This training will occur face to face and will 

last for one hour. 

o Step 5—Assign and Provide Interventions. In this step, EWIMS team members 

make informed decisions about the allocation of available resources and strategies 

to support students identified as at risk of dropping out of high school. The 

EWIMS team matches individual students to specific interventions after having 

gathered information about (1) potential root causes for individual flagged 

students (Step 4) and (2) the available dropout prevention and academic and 

behavioral support programs in the school, district, and community, which are 

locally determined.

o Step 6—Monitor Students. In this step, EWIMS teams continue to examine 

student indicators at regular intervals to continually identify students who show 

signs of being at risk. The teams will use the same indicators to closely monitor 

already-identified students who were assigned to interventions for progress in 

school and risk status. This step provides critical ongoing feedback about 

additional student- and school-level needs and apparent successes. 

o Step 7—Evaluate and Refine the EWIMS. Through active and structured 

reflection, EWIMS team members assess whether students are responding to 

assigned interventions, revise their specific strategies or general approach as 

needed, and determine how resources are allocated to improve support for 

students. This step encourages EWIMS teams to make course corrections to all 

parts of the EWIMS implementation. As implied by the cyclical depiction of the 

seven-step process, this step (as well as the other six) reflects an ongoing process 

of continual improvement. 

 Evaluate the effects of EWIMS on student and school outcomes. The study will 

examine student outcomes for all students in grades 9 and 10 during the 2013–14 school 

year and all students in grades 9 through 11 during the 2014–15 school year. All student 

outcome data will be collected from school or district administrative data, the EWS tool 

or the <State Department of Education>. In addition, all participating schools will be 

asked to complete an annual Web-based survey about data use practices and schools 

randomly assigned to implement EWIMS in February 2014 may be asked to participate 

in interviews about their experiences using the tool.
District Roles and Responsibilities

We look forward to partnering with <District Name> for this exciting project! More detailed 

information on the responsibilities of participating schools follows. 

 Maintain a sustained commitment to participate in the study. To evaluate the impact 

of EWIMS, it is critical that participating districts agree to adhere to the study guidelines 

and timelines associated with random assignment by lottery to implement EWIMS in 

February 2014 fall of 2015. 

 Support school recruitment. Participating districts should actively support the study 

team’s efforts to recruit high schools by communicating with school leadership and 

endorsing district participation and encourage school-level participation. 

 Support the use of random assignment. It is essential that the district support the use of 

random assignment of schools to receive access to and implement EWIMS in February 

2014 or the fall of 2015. All schools will receive access to EWIMS including the tool and 

training and technical support for implementation; random assignment will only 

determine whether schools receive the “treatment” in February 2014 or a “delayed 

treatment” in the fall of 2015. Schools assigned by lottery to implement the EWIMS 

model in February 2014 will serve as the treatment group. Their counterparts assigned to 

implement EWIMS in fall of 2015 will serve as a control group from February 2014 

through the spring of 2015. Schools randomly assigned to the control group must

continue with “business as usual” practices for identifying at-risk students and assigning 

dropout prevention interventions until EWIMS implementation begins in the fall of 2015. 

Students in control schools should continue to receive any services that would be offered 

to them in the absence of the study. As for students in the “treatment” group, no “typical” 

services should be withheld. 

 Provide access to student-level administrative records. Administrative student-level 

data collection in participating schools will focus on all students in grades 9 and 10 

during the 2013–14 school year and all students in grades 9, 10 and 11 during the 2014–

15 school year. The study team will obtain as much administrative data as possible from 

the <State Department of Education (DOE)>. However, all participating schools should 

provide the study team access to the following student-level administrative data should 

this data be unavailable from <DOE>:

o Demographic information (e.g., race/ethnicity, gender, free or reduced-price lunch 

[FRPL], individualized education program [IEP], and English language learner 

[ELL] status, and parents’ education)

o Grade point average (GPA)

o State test scores 

o Attendance rates

o Course grades in core academic courses by semester

o Credits earned by semester
o Disciplinary information (e.g., suspensions)

o Enrollment information (e.g. whether students are enrolled or have left school for 

reasons other than transfer to another district, including dropping out)

o Grade promotion

Study Team Role and Responsibilities 

The project team is composed of researchers from the Midwest Regional Educational Laboratory 

at AIR. The major responsibilities for the study team are as follows: 

 Obtain necessary approvals from review boards (federal, district, and organizational 

Internal Review Boards) and comply with the research protocols in place.

 Provide access to the EWS tool and training and technical support for implementation to 

participating schools.

 Collect data for the study. The majority of the data for this study will be administrative 

records transmitted from the district, thus minimizing the data collection burden on 

participating schools. The study team will provide a detailed data request to participating 

districts in a pre-determined format that will minimize burden on district staff.

 The study team will conduct an annual Web-based survey of all participating schools and 

collect all implementation data from schools assigned to the treatment group (EWS tool 

data, interviews with EWIMS team members).

 Assure confidentiality. The study team will collect data only for the purposes of this 

study and will not use or allow the use of the data for evaluating individual participants, 

schools, or districts.

 Each participant will be assigned a study-specific identification number, in place of 

their names. A data file that links each participant with their identification number 

will be kept in a password-protected file that only the study team can access.

 The published analysis of the results will aggregate results across all schools and will 

not include results that have been disaggregated by school.

 All members of the study team are required to complete a comprehensive training 

course that addresses current federal government standards and sign federal data 

confidentiality agreements.

 Analyze data and produce reports. The study team will be responsible for aggregating 

information about the effectiveness of EWIMS on student and school outcomes. The 

study team expects that the final report will be released in 2016, pending the federal 

review process, and will ensure that participating schools receive this report.
Timeline 

Table A-3 presents the major tasks of the project as they were described previously.

Table A-3. Major Tasks of the Project

Tasks Dates

EWIMS Implementation

Treatment schools implement EWIMS with Grades 9 and 10 February 2014–June 2014

Treatment schools implement EWIMS with Grades 9, 10, and 11 August 2014–June 2015

Control schools implement EWIMS August 2015–June 2016

Data Collection

Collect administrative records from the state and district Jan 2014–June 2015

Collect EWS tool data from treatment schools Jan 2014–June 2015

Conduct annual Web-based survey May 2014 and May 2015

Conduct interviews with EWIMS team members in treatment schools June 2014 and June 2015

Analysis and Reporting 

Draft and submit final report. December 2015

Benefits to Participation

There are many benefits of participation for districts in <state name>. Critical indicators in ninth 

and tenth grade that powerfully predict whether students are “on track” for high school graduation 

can be used as part of an early warning system to flag at-risk students early, assign appropriate 

interventions, and get students back on track. Participating in this high-profile, large-scale study 

will give your district an opportunity to access the Early Warning and Intervention Monitoring 

System (developed by the National High School Center at AIR) at no cost. The EWIMS model, 

currently in use in 67 districts in six states, includes both an excel-based tool and training and 

technical support for implementation. Your participation in this study will also play an important 

role in informing educational policy focused on dropout prevention in <state name> and at the 

federal level.

Questions or Comments

If you have any questions or comments about the study or the opportunity it provides for your 

district, please feel free to contact Dr. Nicholas Sorensen (nsorensen@air.org or 312-283-2318) 

or Dr. Mindee O’Cummings (mocummings@air.org or 202-403-5254).
Signatures of Commitment

Return via fax (312-288-7601) or e-mail (nsorensen@air.org)

The following people have read this document detailing the study and agree to the roles, responsibilities, 

and conditions of participation on behalf of <District Name> and the study team.

<insert name> <insert title>

District Representative Signature Printed Name Title Date

Jessica Heppen Co-Principal Investigator

Principal-Investigator Printed Name Title Date

Mindee O’Cummings Co-Principal Investigator

Principal-Investigator Printed Name Title Date

Ann-Marie Faria Project Director 

Project Director Printed Name Title Date

Nicholas Sorensen Deputy Project Director 

Project Director Printed Name Title Date

Per the policies and procedures required by the Education Sciences Reform Act of 2002, 

Title I, Part E, Section 183, responses to this data collection will be used only for 

statistical purposes. The reports prepared for this study will summarize findings across 

the sample and will not associate responses with a specific district or individual. Any 

willful disclosure of such information for nonstatistical purposes, except as required by 

law, is a class E felony.

The below <District Name> staff person has agreed to serve as the primary point of contact for school 

recruitment and data collection during the course of the study.

Name:

Position:

Telephone Number:

E-Mail: