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GREENWICH BOARD OF EDUCATION

GREENWICH PUBLIC SCHOOLS

Greenwich, CT

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Board of Education Meeting Agenda Document Cover Sheet

Information Only __X_

Action Requested __

Meeting Date: March 22, 2018

Agenda Item Subject: School Start Time Impact Analysis by Westat

Submitted by: Dr. Gildea and Mr. Dunn

Document Summary/Purpose and/or Recommended Action [If applicable]:

Greenwich Public Schools has contracted the services of a premier research organization, Westat, to

analyze the impact of the district’s new school start time policy that began implementation this school

year. Materials enclosed provide details on the evaluation and include the following:

Analysis overview

Analysis framework

Currently available pre-and post- implementation data:

o Semester GPA

o Daily absences

o Period tardiness

o Athletic participation

o Student sleep survey highlights

o Bus timeliness

Analysis team background

Analysis organization background

The District will focus on the following action steps this Spring:

1 - Discussion on Prioritizing Stakeholder Concerns (3/22)

2 - Presentation of Potential Corrective Options and Additional Analysis (April 19)

3 - Plan to Implement Corrective Options for SY19 (May 17)




Overview of Greenwich Public Schools School Start Time Impact Analysis

School Start Time Impact Analysis Page 1

Greenwich Public Schools

GPS School Start Time Evaluation

Overview of Greenwich Public Schools School Start Time Impact Analysis 1

Overview of Greenwich Public Schools School Start Time Analysis

Overview of Greenwich Public Schools School Start

The potential connection between sleep and adolescent health has sparked an interest from

schools and their communities in adjusting school start times at the secondary level. The

schools that have changed school start times have found that there can be many logistical and

political challenges to overcome with such a policy change. These challenges can affect

communities in terms of traffic patterns, family schedules, school transportation, school food

services, athletics and extra-curricular activities, and teacher schedules. For each community,

as is true with Greenwich, there are a unique set of assets and challenges. It is for these

reasons that a thorough and rigorous impact analysis can help Greenwich Public School (GPS)

leaders and their Board of Education (BOE) understand the challenges and benefits of changing

school start times.

The key to this impact analysis is designing an approach that will quantify and explain how the

many interconnected variables associated with implementing the new start time policy impact

the district’s desired outcome—more sleep for secondary students—and help GPS decide if this

new policy supports district goals around the Vision of the Graduate. School flexibility and

innovation rests on the ability of districts and communities to understand how complex logistics

and school operations impact student academics and engagement, and how problems arising

from making significant changes can be mitigated.

The analysis is designed around the student-centered Vision of the Graduate and

acknowledges that students, school operations (which support students and communities), and

communities are all important for student success. The impact analysis began by collaboratively

designing an analysis framework with district leaders to ensure the results will provide useful

and relevant information for GPS and the BOE. Second, we will work with GPS leadership to

analyze and make sense out of the data that has already been collected on the critical

components affected by the start time policy. Wherever possible, we will collect data prior to the

intervention to capture changes prior to and during policy implementation. Finally, we will

conduct a site visit to interview relevant district and community leaders, teachers, and conduct

focus groups with students and parents.

The analysis framework illustrates the basic questions for

the study and sub-topics that we will probe to answer

those questions. Next to the sub-topics is a list of data

that already exists (highlighted in blue) and data to be

collected during the course of the analysis. The next

column, preliminary pre-post measures, provide a pre-

(SY 2016-17) and post- (SY 2017-18) comparison of:

GPA by student population, attendance rates, student

tardies, early dismissals by athletic teams, and the same

aforementioned factors across bus routes. The analysis is described as preliminary as it only

GPS Vision of the

Graduate

Academic Capacities

Personal Capacities

Interpersonal Capacities


captures changes between two discrete points in time and an implementation time-line of less

than a year. Therefore, the research team will use that data as a basis to guide a deeper probe

through the examination of additional data combined with perceptual data gathered through site

visit interviews. A summary of the change analysis between 2016 and 2017 include:

GPA by Cohort Student Population (See Appendix Figure 1):

Repeating 9th graders, show an increase in GPA.

10th, 11th, and 12th graders, non-athletes and athletes all show a decrease in GPA.

None of the GPAs fell below 3.0 except for non-athletes.

The overall average GPA for the entire student group decreased.

Attendance Rate by Cohort Student Population (See Appendix Figure 2):

The average attendance rate of all students in grades 9-12 as well as non-athletes and

athletes increased.

Tardies by Cohort Student Population (See Appendix Figure 3):

Repeat 9th graders, 10th graders, and Non-athletes all showed an average increase in

tardies.

Students in grades 11 and 12 and athletes showed an average decrease in tardies.

The overall average tardy rate increased.

Early Dismissals per Athletic Teams (See Appendix Figure 4)

The number of early dismissals by students increased.

The number of early dismissals by minutes increased.

Change in Academic Outcomes by Bus Routes (See Appendix Figure 5)

The average GPA score has been decreased for students of all bus routes.

Students in a few bus routes, like #13, show a decrease in attendance rates.

Most bus routes show an increase in tardiness.

Pre- (May) and Post- (October) Sleep Survey Results (See Appendix Figure 5 and 6)

The average student sleep time has shifted from 10:06 pm to 11:02 pm.

The average depressed mood scale indicates a higher level of depressed mood from the

May to the October survey.

The average sleepiness scale decreased from May to October.

The number of students who reported feeling that they never or rarely get enough sleep

decreased by 13% in October.

The average number of students reporting they receive enough sleep increased in

October.

The number of students reporting they go to bed once homework is completed increased

in October.

The number of students reporting they go to bed on the weekends when they feel like it

or when finished socializing increased in October.


Analysis

The first step in understanding these preliminary numbers is to weigh the outcomes against a

set of clearly stated goals. To date, those goals have not yet been identified. In addition to

identifying goals, it is up to the system to apply its contextual knowledge to determine the

importance and relevance of: a drop in 10th grade GPA from 3.03 to 2.94; an increase in 12th

grade attendance from .984 to .992; or in increase in average 10th grade tardies from .05 to .13

related to the new school start time. Second, it is important to consider when reviewing these

numbers that they represent less than a year’s implementation and that many initiatives

experience a first-year implementation dip while logistics and other issues are being

addressed. Third, interpreting the impact on transportation, one of the biggest reported pain

points of this policy, is difficult because the data was collected in different formats between fall

2016 and 2017. Finally, the district has done a good job collecting data on this initiative which,

once organized and analyzed against a clear set of goals, will provide more data points for the

system to decide the impact and future of the new start time policy.

Next Steps

The Westat team will next review and collect additional data to address the impact of the new

school start time on student’s personal lives, school operations, and the surrounding

community. Included in those topics will be a focus on previously conducted student sleep

surveys to understand how the data collected can inform this impact analysis and to consider

the possibility of conducting one more rounds of sleep surveys. Additionally, we will examine

transportation data from the district and the office of the Chief of Police, run additional analyses

on grades, attendance, and tardies, and will begin setting up site visits to interview key

stakeholders involved in planning and implementing the new school start time policy.

1

School Start Time Impact Analysis

How does the new school start time impact student life?

Research Question Impact Subtopics Data Sources (*existing data) Preliminary Pre-Post Data Collection timeline

How does the new start time impact athletics and after-school activities?

- Athletic and after-school activitypractice-time

- Athletic performance- Field/venue availability and

lighting- Bus and parent transportation- Scheduling athletics and

activities with other schools inand out of the district

- Coaches, teachers, and students- Classroom schedule and student

release time- Ability for students to complete

homework- Time students go to bed

- *Fall 2016-17 early dismissal reports per team, time missed from classes, length of time traveling

- *Parent, staff, and student satisfaction surveys

- Interviews with coach(es)- Interview(s) with after-school program leaders

- Interviews with teachers- Parent focus group- Student focus group- Interview with SST ad hoc committee leader

- *May & Oct student sleep survey

- The average number of studentsmissing classes by athletic teamsincreased between fall 2016 and fall2017 (Appendix F4).

- The average number of class-timeminutes missed by athletic teamsbetween fall 2016 and fall 2017increased (Appendix F4).

Late March

How does the new start time impact student academics?

- Student attendance and tardies- Students’ ability to complete

classwork and homework- Student grades- Students’ energy levels during

the day

- *Attendance and tardy data- *Early dismissal data- *School early dismissal reports- *First semester grades 2016 &

2017- *Parent, staff, and student

satisfaction surveys- *May & Oct 2017 student sleep

survey- Student focus group

- The average student attendance rateby grade and athletic participationincreased between 2016 and 2017(Appendix F2).

- The average GPA by grade (10-12)and athletic participation decreasedbetween 2016 and 2017 (AppendixF1).

- The Average GPA for grade 9repeaters increased (Appendix F1).

- The average tardy rate by grade andathletic participation had a mixture ofincreases and decreases(Appendix F4).

Late March

STUDENTS

2


How does the new school start time impact student life?—continued


How does the new start time impact students’ personal lives?

- Sleep and restfulness- Free-time at home- Satisfaction with school schedule- School connectedness

- *May & Oct 2017 student sleepsurvey

- *Student satisfaction survey- Student focus group

- Average student sleep time hasshifted from 10:06 pm to 11:02 pm.

- Average depressed mood scaleindicates a higher level of depressedmood from the May to the Octobersurvey.

- Average sleepiness scale decreasedfrom May to October.

- Average number of students whoreported feeling never or rarelygetting enough sleep decreased by13%.

- Average number of students reportingthey receive enough sleep increasedin October.

- Average number of students reportingthey go to bed once homework iscompleted increased in October.

- Average number of students reportinggo to bed on the weekends whenthey feel like it or when finishedsocializing increased in October.

Late March

STUDENTS

3


How does the new school start time impact school operations and student support?


How does the start time impact school transportation?

- Student drop-off and pick-up atschool

- Bus timeliness- Ability for teachers and parents to

get to school at their desired time- Traffic directly around the school- Student safety getting to and

leaving the school- Transportation costs to the

district/schools- Adjustments made by central

office operations to implement thestart time change

- Adjustments made by schoolleaders to implement the starttime change

- *Traffic pattern data (pre-post)- *Bus schedule data (pre-post)- *District/school budget (pre-post)- *Parent, staff, and student

satisfaction surveys- Interview with district

transportation leader- Interview with high school leader- Parent focus group

- There are no reliable baselinedata to analyze school bustimeliness.

- Average GPA score has beendecreased for students of all busroutes. Students in a few busroutes, like #13, show decreaseattendance rate. Few bus routesshow students with averagedecrease in tardiness incidentswhile most routes are showingincrease in tardiness (AppendixF5).

Late March

How does the new start time impact school food services?

- Coordinating breakfast and lunchprograms

- School food services budget- Availability of meals to

Free/Reduced qualifying students

- Interview with school food servicedirector

- # of F/R meals sold in AM 2016 v2017

Late March

SCHOOL OPERATIONS

4


How does the new school start time impact school operations and student support?


How does the new start time impact human resources?

- The district’s ability to recruit,retain, and develop teachers

- District and school professionallearning

- Teachers’ personal schedules- Teachers’ school commute- Teachers’ ability to meet

instructionalexpectations/schedules

- Teachers’ ability to engagestudents and manage behavior

- Teachers’ satisfaction withteaching in their school

- Opportunity cost of the timechange on teachers (personal orotherwise)

- Satisfaction of transportation andfood service staff in their jobs

- *Staff satisfaction survey- Interview with HR director- Interview with Assistant

Superintendent for Curriculum,Instruction, & ProfessionalLearning

- Interview with high schoolprincipal

- Interviews with teachers

Late March

How does the new start time impact district/school budget?

- Cost differences in district andschool budget

- Actions taken by district and schoolto mitigate negative impact on thebudget

- *District and school budget data- Interview with Chief Operating

Officer- Interview with Deputy

Superintendent

Late March

SCHOOL OPERATIONS

5


How does the new school start time impact the immediate and surrounding community?

Research Question Subtopics Data Sources (*existing data) Preliminary Pre-Post Data Collection timeline

How does the start time impact traffic within the community?

What is the impact on the community’s: - Traffic patterns near and around

the school- Transportation cost to the city

- *Traffic pattern data (pre-andpost)

- *City traffic study- Interviews with the Chief of Police- Interview with city transportation

leaders

Late March

How does the new start time impact parents?

What is the impact on: - Parents personal schedules- Parent’s school commute- Parents’ ability to support and

attend in athletics and after-school activities

- Satisfaction with their children’sschool

- *Parent satisfaction survey- Interviews with teachers- Parent focus group

Late March

How does the new start time impact other community resources?

What is the impact on: - Day care and child care centers- Other after school programs

(Boys and Girls Club)

- Interviews with SST ad hoccommittee

- Interviews with after schoolprogram leaders

Late March

COMMUNITY

1

APPENDIX: PRE-POST IMPACT DATA

Figure 1

ANALYSIS OF GPA BY COHORT STUDENT POPULATION

Target Students

2016/17 Mean

2017/18 Mean

Sample Size Difference Directional

Change Favorable

Results

Repeat 9th graders

1.02 1.06 7 .04 ↑

10th graders 3.03 2.94 638 -.03 ↓ ×

11th graders 3.17 3.04 643 -0.09 ↓ ×

12th graders 3.17 3.07 583 -0.14 ↓ ×

Non- Athletes

3.05 2.96 1,154

-0.10 ↓ ×

Athletes 3.21 3.09 717 -0.12 ↓ ×

Overall 3.11 3.0 1878 -0.10 ↓ ×

Average Grade Average Point (GPA) for the first semester of 2016-17 and 2017-18 school year are

represented in this chart, grouped by grades and athletic membership. Student level data has been

provided to Westat team by GPS information system department.

2

Figure 2

ANALYSIS OF ATTENDANCE RATE BY COHORT STUDENT POPULATIONS

Target Students

2016/17 Mean

2017/18 Mean


Change Favorable

Results

9th graders .924 .987 7 0.063 ↑

10th graders .993 .994 638 0.001 ↑

11th graders .989 .994 643 0.005 ↑

12th graders .984 .992 583 0.008 ↑

Non-Athletes

.985 .991 1,154 0.006 ↑

Athletes .994 .996 717 0.002 ↑

Overall .989 .993 1878 0.005 ↑

Average daily attendance rate for the first semester of 2016-17 and 2017-18 school year are represented in

this chart, grouped by grades and athletic membership. Daily attendance rate is calculated as a ratio of

attendance days (number of enrollment days – number of excused and unexcused absence) to number of

enrollment days in the semester. Student level data has been provided to Westat team by GPS information

system department.

3

Figure 3

ANALYSIS OF TARDIES BY COHORT STUDENT POPULATIONS

Target Students

2016/17 Mean

2017/18 Mean


Change Favorable

Results

9th graders 0.00 .1.29 7 1.28 ↑ ×

10th graders 0.05 0.13 638 0.083 ↑ ×

11th graders 0.09 0.08 643 -0.011 ↓

12th graders 0.15 0.12 583 -0.034 ↓

Non-Athletes

0.103 0.144 1,154 0.041 ↑ ×

Athletes 0.08 0.06 717 -0.017 ↓

Overall 0.95 .0.113 1878 0.019 ↑ ×

Average number of tardiness incidents for the first semester of 2016-17 and 2017-18 school year are

represented in this chart, grouped by grades and athletic membership. Student level data has been


4

Figure 4

ANALYSIS OF EARLY DISMISAL PER ATHLETIC TEAMS

Target 2016/17

Mean 2017/18

Mean Sample Size

(Athletic teams) Difference

Directional Change

Favorable Results

By number of students

1.57 3.87 23 2.304 ↑ ×

By number of minutes

51.30 170.87 23 119.565 ↑ ×

Average number of students with early dismissal and average dismissal time for athletes, for the first

semester of 2016-17 and 2017-18 school year are represented in this chart. Data has been provided to

Westat by the Headmaster of GHS for 23 athletic teams. Data has been provided to Westat by the

Headmaster of GHS.

5

Figure 5

ANALYSIS OF SLEEP SURVEY BEFORE AND AFTER BELL TIME CHANGE

Before Mean

Sample Size

After Mean

Sample Size

Difference Range Directional

Change Favorable

Results

Average Bed Time

10:06 1,581 11:02 2,118 56

minutes 8:30 PM - 4:00 AM

↑ ×

Average Depressed Mood Scale

17.34 1,555 18.84 2,078 1.5 2 - 40 ↑ ×

Average Sleepiness Scale

22.42 1,577 15.55 2,083 -6.87 2 - 46 ↓

Sleep/Wake Problems Behavior Scale

26.85 1,565 25.81 2,082 -1.04 5 - 65 ↓

The Superscience Morningness/Eveningness Scale

8.39 1,573 8.38 2,090 -0.01 1 - 13 ↓ ×

The data source for this analysis is the sleep surveys conducted in May 2017 (pre) and October 2017

(post). The average student bed time after the start time change has shifted to almost an hour later. The

average depressed mood scale is a scale indicating the level of depressed mood. The higher the score is

the higher is the level of depressed mood. This scale decreased after the school start time change. For

average sleepiness scale, the higher the scale is, the sleepier is the student. This scale decreased after the

start time change. The superscience morningness/eveningness scale tells us if the person is a morning

person or an evening person. The bigger the number (closer to 13) is the more of a morning person she/he

is. If the number is closer to “1” that person is an evening person. In general students are not absolutely

morning nor evening people but since May they slightly moved to be more evening people. In this table

green arrows are favorable movement while red arrows are not favorable movements. The sleep data

survey has been slightly modified from May to October data collection point and from the original school

sleep survey that is available online. Interpreting and relying on these information must be done with

caution. Westat has not run any validity tests for this survey and the results may be impacted by changes

in season and time of the school year; the May surveys represents near the end of the school year while

October represents the beginning.

6

Figure 6

ANALYSIS OF SLEEP SURVEY BEFORE AND AFTER BELL TIME CHANGE

The data source for this analysis is the sleep surveys conducted in May 2017 (pre) and October 2017

(post). According to this survey the number of respondents who indicated they do not get enough sleep

decreased by almost 13%. In October more students indicated that they usually get enough sleep than in

May. Most students in both surveys indicated that during the school week they go to bed after their

homework is finished, while during weekends they go to be when they feel it is time to sleep or after they

have finished socializing. This bars represent a snapshot of select items in the survey.

50.0%

71.0%

39.0%

41.5%

47.0%

72.0%

30.6%

54.2%

0.0% 10.0% 20.0% 30.0% 40.0% 50.0% 60.0% 70.0% 80.0%

When I finished my home work, I go to bed onweekdays.

Whenever I feel sleepy or finished socializing, Igo to bed on weekends

I feel I usually get enough sleep

I feel I never or rarely get enough sleep duringschool week

May October

7

Figure 7

ANALYSIS OF CHANGE IN ACEDEMIC OUTCOMES BY BUS ROUTES

Bus Route

Number

Change in GPA Change in Daily

Attendance Rate Change in Tardiness

Mean Std. Dev.

Freq. Mean Std. Dev.

Freq. Mean Std. Dev.

Freq.

1 -0.150 0.701 43 0.013 0.033 43 0.000 0.000 43

2 -0.161 0.530 47 0.004 0.023 47 0.255 1.132 47

3 -0.086 0.554 17 0.019 0.073 17 0.000 0.000 17

4 -0.169 0.559 58 -0.010 0.108 58 0.069 3.313 58

5 -0.136 0.540 52 0.018 0.082 52 -0.769 3.154 52

6 -0.033 0.536 46 -0.001 0.022 46 0.043 0.295 46

7 -0.085 0.570 53 0.007 0.036 53 0.000 0.000 53

8 -0.079 0.589 58 0.013 0.055 58 0.500 2.611 58

9 -0.101 0.584 24 0.014 0.035 24 0.000 0.000 24

10 -0.066 0.445 57 0.004 0.019 57 0.140 1.060 57

11 -0.114 0.584 53 0.004 0.064 53 0.208 1.511 53

12 0.074 0.368 45 0.008 0.034 45 -0.089 0.596 45

13 -0.100 0.595 32 -0.007 0.078 32 0.000 0.000 32

14 -0.104 0.754 32 0.025 0.089 32 0.000 0.000 32

15 -0.009 0.571 38 0.009 0.022 38 -0.263 1.329 38

16 -0.151 0.508 51 0.004 0.032 51 -0.078 0.560 51

17 -0.134 0.577 38 -0.002 0.021 38 0.000 0.000 38

18 -0.177 0.506 36 0.001 0.022 36 0.111 0.667 36

19 -0.101 0.380 38 0.006 0.023 38 0.000 0.000 38

20 -0.132 0.405 48 0.008 0.021 48 -0.063 0.976 48

21 -0.044 0.540 62 0.001 0.014 62 0.113 0.889 62

22 -0.178 0.468 56 -0.001 0.026 56 0.000 0.000 56

23 -0.136 0.549 58 0.004 0.027 58 -0.121 1.027 58

24 -0.121 0.427 54 0.001 0.013 54 0.000 0.000 54

25 -0.050 0.362 42 0.009 0.029 42 -0.048 0.697 42

26 -0.077 0.434 68 0.006 0.021 68 0.044 0.656 68

27 -0.044 0.408 59 0.005 0.024 59 -0.136 1.491 59

28 -0.078 0.483 44 0.002 0.015 44 0.000 0.647 44

29 -0.153 0.502 38 0.005 0.030 38 0.000 0.000 38

30 -0.201 0.498 54 -0.001 0.040 54 0.185 1.117 54

31 -0.114 0.545 32 -0.001 0.014 32 -0.063 0.354 32

Total -0.104 0.516 1,433 0.005 0.044 1,433 0.007 1.283 1,433

8

Average change in GPA, daily attendance rate and tardiness, for the first semester of 2016-17 and 2017-

18 school year, grouped by school bus routes, are represented in this chart. Student level data has been


OF



Background on Westat and the Evaluation Team

Westat has more than 50 years of experience, approximately 2,000 current staff, and a long track record of

success providing evaluation services for a wide range of clients, including Federal, state, and local governments,

school districts, institutions of higher education, foundations, and commercial and non-profit entities. We have

abundant, strong experience in areas that are directly relevant to this evaluation, including evaluations of district

programs, research on district systems and their interdependence on district operations and academics, and

areas in education and social science focused on improving outcomes for students to increase their post-

secondary success rates. The proposed team is small but highly experienced:

Dr. Dean Nafziger will serve as the Executive Leader. Dr. Nafziger is a Westat Vice President with more than 40

years’ experience leading complex organizations that house sophisticated technical functions. He has held

executive roles in major organizations. As President and Chief Executive Officer (CEO) of WestEd, he led the

creation of that organization. As Executive Vice President at ETS, he was one of a three-person Office of the

President, with the responsibility of testing programs in 160 countries throughout the world. At Harcourt

Assessment, he was President, responsible for a $250 million budget and 2,000 employees spanning test

development, psychometrics, operations, and sales. He was also an Assistant Superintendent for Planning,

Research, and Evaluation of a large urban district, providing practical experience and knowledge about applied

research needs at the local level. Dr. Nafziger currently directs the Building State Capacity and Productivity

Center (BSCP), funded by the U.S. Department of Education (ED), to provide technical assistance (TA) and

capacity building for state education agencies (SEAs) to implement strong performance management systems in

their states.

Dr. Heather Zavadsky, the project director and site visit leader, will serve as the Principal Investigator and will

take a lead role in designing and conducting the evaluation approach, and she will serve as the prime point of

contact for the GPS team. Dr. Zavadsky is a Senior Evaluator with more than 25 years of experience as a

practitioner and researcher. Her expertise includes research design, data analysis, and report production.

Dr. Zavadsky oversaw mixed-methods studies and provided program support for Educate Texas (Communities

Foundation of Texas) to identify ways to improve supports to Texas districts and worked with the University of

Texas System, school district partners, and state and Federal education policymakers to inform development of

policies related to K-12 and higher education systems. Focus topics covered over her 25 years of research include

systemic district reform and turnaround, effective human capital strategies, district data and accountability

systems, supporting systems to create college and career-based schools and pathways, and special education.

She recently worked with the Houston ISD central office leadership team to implement Linked Learning (career-

based pathways) in eight high-schools. As a project director at the National Center for Educational Accountability

(University of Texas at Austin), she managed The Broad Prize for Urban Education for 6 years. From this and

other work Dr. Zavadsky wrote two books on the district’s critical role in school improvement and turnaround.

She began her career as a special education teacher, student teacher supervisor, and autism and dyslexia

consultant.

Dr. Eric Rolfhus is a Westat Senior Study Director and would serve as a senior methodologist, providing advice

and support to the team by authenticating and confirming the rigor of research designs and outcome results. He

has more than 20 years of experience as a skilled researcher, psychometrician, and WWC-certified group design

reviewer with the ability to communicate research results effectively to diverse audiences. He has statistical

expertise in large-scale data management, exploratory data analysis, factor analysis, hierarchical linear modeling

(HLM), structural equation modeling, regression, multi-level modeling, CART, and predictive modeling. Recently,

Eric has focused extensively on college and career issues, including on-track indicators in K–12 education.

Mr. Sadeq Sohrabie is a research associate with experience establishing, updating, and implementing

procedures for data collection, data analysis, data quality control, and in conducting financial and economic

evaluation and consultation. He has particularly strong skills in explaining and modeling data. At Westat, Sadeq

supports education research by coordinating the treatment, reduction, and analysis of qualitative and

quantitative data. Recent relevant evaluations include: AT&T Aspire programs, the Verizon Innovative Learning

Schools program, the Pre-K for San Antonio program, the Texas Communities In Schools Program Resource

Center and State Office Support, and an evaluation action plan for the Center for Teaching and Learning

Evaluation Project.

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Our Work Westat does work across a wide range of subject areas, including health, education, social policy, transportation, and information systems.

Our Expertise

Data Collections & Management

We apply innovative methods and technologies to data collection and management whether using paper-and-pencil, in-person, or web-based surveys, or implementing touchscreen versions of audio computer-assisted self-interviewing (ACASI) and interactive voice response (IVR). We have an excellent reputation for large-scale data collection, including fielding nationwide surveys and gaining response from hard-to-reach populations.

Our data collections and management expertise includes:• Surveys, Questionnaires & Interviews• Coordinating Centers• Environmental & Biological Specimens• Geospatial Systems• Human Subjects Protections

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Our clinical trial expertise includes:• Clinical Trial Design• Clinical Trial Management• Site Management & Monitoring• Laboratory Support

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Whether the goal is to assess American children’s educational progress, U.S. household travel behaviors, or HIV drug resistance in developing countries, we assist our clients in meeting research goals using the most efficient, unbiased, and innovative survey methods. Westat statisticians and survey methodologists are internationally recognized for their contributions to the theory and practice of statistical research and survey methods.

Our statistical research and survey methods expertise includes:• Survey Design• Methodological Research• Pretesting Methods• Statistical Analysis

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Westat at a GlanceWestat, an employee-owned corporation, has provided research services to Federal and state government agencies and private organizations since 1963. As one of the foremost contract research organizations in the United States, we are recognized for our statistical skills and developing custom research and program evaluation studies across a range of subject areas.

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Our evaluation expertise includes:• Process & Outcome Evaluation• Program Support• Stakeholder Experience• Technical Assistance & Training

Communications & Social Marketing

We provide evidence-based communication services that improve lives. We translate research results; develop compelling concepts, messages, and materials; employ state-of-the-art tools to communicate through multiple channels; translate content into multiple languages; and provide a range of communication research services. Our expertise helps clients educate, motivate, and change public attitudes and behaviors about issues that affect our lives and our world.

Our communications and social marketing expertise includes:• Center for Digital Strategy & Research• Communications Research• Digital & Social Media• Knowledge Transfer• Social Marketing• Web & App Development

www.westat.com43724.0515.101000

WestatAn Employee-Owned Research Corporation®

1600 Research Boulevard

Rockville, MD 20850

www.westat.com

301-251-1500

301-294-2040 (fax)

[email protected]

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