### 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, sc ores 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 o verview 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 con tents 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 scho ols 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 ear ly 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 comprehe nsive 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 d ropping 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 seven

step EWIMS implementation process t o 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 user s 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 d esigned 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 theschools’ cho osing 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 warn ing 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 resear ch 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 le arning. 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 2 014 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 participa ting 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 sev en

- 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 establi shed; 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.

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, b ased 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 cont ext 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 cause s 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, fa mily, 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 sup port 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 o ngoing 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, r evise 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 th e 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 studen ts 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 Ed ucation>. 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 experienc es 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.

 Sup port 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 us e 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 trainin g 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 20 14 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, a ll 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], individu alized 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 semestero Disciplinary information (e.g., suspensions)

o Enrollment information (e.g. w hether 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 te am 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 Board s) 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

re cords 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 th eir 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 proc ess, 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 Feb ruary 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 a ny 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 Sign a ture Printed Name Title Date

Jessica Heppen Co

- Principal Investigator

Principal

- Investigator Printed Name Title Date

Mindee O’Cummings Co

- Principal Investigator

Principal

- Investig ator Printed Name Title Date

Ann

- Marie Faria Project Director

Project Dire ctor Printed Name Title Date

Nicholas Sorensen Deputy Project Director

Project Dire ctor 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

w illful disclosure of such information for nonstatistical purposes, except as required by law, is a class E felon y

. 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: