Evaluation of the Early Warning and Intervention Monitoring System (EWIMS)

Final Agreement Form (District MOU)

District Roles and Responsibilities:
Early Warning and Intervention Monitoring System Study
Dear ,
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 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 as a partner in this project!

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
STEP 1 – Establish
Roles & Process

STEP 7 – Evaluate
& Refine EWIMS

STEP 2 – Use the
EWS tool

STEP 3 – Analyze
EWS data

STEP 6 – Monitor
Students

STEP 5 – Assign &
Provide
Interventions

STEP 4 – Interpret
EWS data

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 . 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 March 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
March 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 March 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;1 team 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.

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.
1

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 . 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 March 2014 may be asked to participate in
interviews about their experiences using the tool.

District Roles and Responsibilities
We look forward to partnering with for this exciting project! More detailed
information on the responsibilities of participating schools follows. Please note that your
district’s participation in this project is voluntary. You will not be penalized in any way for not
participating and you may discontinue participation at any time without penalty.


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
March 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 March
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 March 2014 or a “delayed
treatment” in the fall of 2015. Schools assigned by lottery to implement the EWIMS
model in March 2014 will serve as the treatment group. Their counterparts assigned to
implement EWIMS in fall of 2015 will serve as a control group from March 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 . However, all participating schools should
provide the study team access to the following student-level administrative data should
this data be unavailable from :
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

March 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

March 2014–June 2015

Collect EWS tool data from treatment schools

March 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 . 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 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
The below 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:

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 and the study team.

District Representative Signature

Principal-Investigator

Principal-Investigator

Printed Name Title

Jessica Heppen

Co-Principal Investigator

Printed Name

Title

Mindee O’Cummings

Co-Principal Investigator

Printed Name

Title

Ann-Marie Faria
Project Director

Project Director

Date

Date

Date
Project Director

Printed Name

Title

Nicholas Sorensen

Deputy Project Director

Printed Name

Title

Date

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.