OMB Supporting Statement Part A: 

Alternative Student Growth Measures for 

Teacher Evaluation: Case Studies of Early 

Adopters

August 6, 2013
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies ii

Table of Contents

Table of Contents ii

SUPPORTING STATEMENT FOR PAPERWORK REDUCTION ACT 1

PART A. JUSTIFICATION 1

1. Circumstances Necessitating the Collection of Information 1

a. Statement of Need to Study Alternative Measures of Student Growth....................................... 1

b. Research Questions ...................................................................................................................... 3

c. Study Overview............................................................................................................................. 3

d. Recruitment of Districts................................................................................................................ 4

e. Data Collection Plan...................................................................................................................... 5

2. Purposes and Uses of Data 9

3. Use of Technology to Reduce Burden 9

4. Efforts to Avoid Duplication 9

5. Methods to Minimize Burden on Small Entities 10

6. Consequences of Not Collecting Data 10

7. Special Circumstances 10

8. Federal Register Announcement and Consultation 11

a. Federal Register Announcement ................................................................................................ 11

b. Consultations Outside the Agency.............................................................................................. 11

9. Payments or Gifts 11

10. Assurances of Confidentiality 11

11. Justification for Sensitive Questions 13

12. Estimates of Burden Hours 13

13. Estimates of Cost Burden to Respondents 14

14. Annualized Cost to the Federal Government 14

15. Reasons for Program Changes or Adjustments 14

16. Plans for Tabulation and Publication of Results 14

a. Tabulation Plans.......................................................................................................................... 15

b. Publication Plans......................................................................................................................... 17
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies iii

17. Approval Not to Display the Expiration Date for OMB Approval 17

18. Exception to the Certification Statement 17

REFERENCES 18
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 1

SUPPORTING STATEMENT FOR PAPERWORK 

REDUCTION ACT

This submission is a request for approval of data collection activities that will be used to support the 

Mid-Atlantic Regional Educational Laboratory (REL) Alternative Student Outcomes for Growth Measures 

Case Studies. The study is being funded by the Institute of Education Sciences (IES), U.S. Department of 

Education (ED), and is being implemented by ICF International and its subcontractor, Mathematica 

Policy Research. 

This study aims to fill the gap in information available to districts and policymakers on measures of 

student growth that do not use state standardized tests via qualitative case studies of up to nine 

districts that are using alternative measures of student achievement growth in teacher performance 

ratings. The case studies will address what alternative outcome measures are used, how the alternative 

growth measures are implemented, challenges and obstacles in implementation, how the measures are 

being used. Where possible, the study team will examine the extent of differentiation produced by the 

measures—specifically, the distribution of teacher performance on the measures, as compared with the 

distribution of teacher performance on conventional value-added measures that are based on state 

assessments. The study team will conduct semi-structured interviews with district administrators 

leading teacher evaluation or effectiveness efforts, teacher representatives (such as union leaders), 

teachers (including both classroom teachers and instructional coaches), and principals. The data 

collected will be summarized and analyzed using a case study approach.

This submission requests approval to recruit districts for the study and conduct in-person and telephone 

interviews with staff in participating districts.

PART A. JUSTIFICATION

1. Circumstances Necessitating the Collection of Information

a. Statement of Need to Study Alternative Measures of Student Growth

The specific legislation authorizing this data collection is specified in Part D, Section 174 (20 U.S.C. 9564) 

of the Education Sciences and Reform Act (ESRA) of 2002. Part D, Section 174 provides for ED to enter 

into five-year contracts with entities to establish a networked system of ten regional laboratories that 

serve the needs of each region of the United States. The Regional Educational Laboratories (RELs) are to 

carry out a range of activities to serve the needs of each region in the United States, including applied 

research, and development, dissemination, training, and technical assistance activities that focus on 

how to use data and analysis. The primary mission of the RELs is to help states and districts 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 2

systematically use data and analysis to answer important issues of policy and practice with the goal of 

improving student outcomes. 

In school districts that have sought to measure the effectiveness of teachers in raising student 

achievement, statistical methods that aim to measure growth or value-added are typically applied to 

students’ scores on statewide standardized tests. These methods are broadly referred to as “growth 

models.” Growth models have attracted considerable interest among educators and policymakers 

nationwide—and have been promoted by the US Department of Education via Race to the Top (RTT)_

and the Elementary and Secondary Education Act (ESEA) waiver process. Indeed, many states are 

beginning to require that some measure of student achievement growth be used as a component of the 

evaluation of teachers and/or principals. All five states in the REL Mid-Atlantic region have secured Race 

to the Top funding, which places a premium on teacher evaluation. Reforms to the teacher evaluation 

systems incorporate student performance, whether it be through a value-added model (e.g., DCPS’s 

IMPACT system; Pennsylvania Value Added Assessment System – PVAAS) or a student growth model 

(e.g., DEDOE, MSDE, and NJDOE). But the utility of value-added models has been limited by the breadth 

and depth of the underlying student assessments. The reliance on statewide standardized tests for 

value-added models limits the grades and subjects that can be evaluated (often only grades 4-8, only in 

math and reading).

To permit evaluation of grades and subjects not tested through state exams, and to derive a more 

comprehensive picture of teacher effectiveness though multiple growth measures, some school districts 

have begun to use alternative student outcome measures in value-added models and other growth 

models. Alternative student achievement measures in use in growth models range from end-of-course 

curriculum-based assessments to commercially available standardized tests such as the Iowa Test of 

Basic Skills and the PSAT. Meanwhile, multiple districts have adopted student learning objectives as 

alternative measures of student achievement growth that are used in teacher evaluation but do not 

involve growth models. Student learning objectives differ from growth models in that they are specific 

growth targets for a teacher’s own particular set of students, and the targets are typically set by 

individual teachers and approved by principals at the beginning of each school year. 

This study, which was requested by the Pennsylvania Department of Education (a member of the 

Teacher Evaluation Research Alliance), will be of interest to officials and policymakers throughout the 

REL Mid-Atlantic region (and the country) who would like to learn more about the characteristics, uses,

and implementation of alternative student growth measures. As noted above, large numbers of states 

and districts are exploring such measures, often as a result of changes in state-level evaluation systems 

inspired by Race to the Top grants or ESEA waivers. Within the region, Delaware is planning on 

extending evaluation of teachers in non-tested grades and subjects to include alternative measures and 

growth goals in the 2012-2013 school year. Pennsylvania, Maryland, and New Jersey are likewise 

working on changes to their teacher evaluation system with the aim of including some measure of 

student growth in the evaluation of teachers within and outside of tested grades and subjects. The 

Pittsburgh Public Schools have pioneered the development and use of value-added models that rely on 

locally developed curriculum-based assessments for courses in secondary grades. The District of 

Columbia Public Schools have already started using student learning objectives (called Teacher-Assessed 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 3

Student Achievement Data) and the district planning to add end-of-course exams to include high school 

teachers in their value-added models in subsequent years (District of Columbia Public Schools 2011). 

Most of these measures are so new that the districts and states developing and using them have had to 

work thus far without much (if any) knowledge about challenges in the implementation of growth 

measures using alternate assessments. The findings of this study therefore have the potential to inform 

states and districts in deciding which measures are promising for use in evaluation systems, which are of 

doubtful value (for example, because they do not distinguish many teachers from each other, or 

because they show indications of rapid inflation from year to year), and the difficulty of effectively 

implementing the measures. Teacher evaluation systems will be works in progress for at least the next 

several years, and policymakers in the Mid-Atlantic region and beyond need information to inform their 

selection of measures, how the measures will be used, and how to minimize implementation costs and 

avoid obstacles.

b. Research Questions

The primary research questions to be addressed in the study are: 

 What student outcome measures other than state standardized test scores are currently being used 

in growth measures to assess teacher performance?

 How have school districts implemented the data collection and analysis necessary for growth 

measures based on alternative student outcomes, and what obstacles have they encountered?

 How are the alternative measures being used for other purposes in addition to teacher evaluation? 

If they are used for other purposes (e.g., for planning instruction), are those purposes compatible 

with maintaining their validity and reliability for evaluation? 

 How much weight does each alternative measure alternative receive in a teacher’s overall 

evaluation, and how does the weight vary by grade and subject? How does the distribution of scores 

on the alternate measure compare to the distribution of scores on growth measures used with state 

assessments (e.g., value-added measures) or other measures of performance? 

 What are the perceived benefits and drawbacks of using growth models (including VAM) based on 

each type of alternative outcome: student learning objectives, end-of-course curriculum-based 

assessments, and nationally normed assessments? What costs (notably in terms of time and effort) 

do they impose on teachers, principals, and districts? What are the estimated monetary costs 

associated with each of the following components: piloting, training, additional data collection, data 

system development, data analysis, and reporting

c. Study Overview

In this study, the study team will examine what alternative outcome measures are used, how the 

alternative growth measures are implemented, challenges and obstacles in implementation, how the 

measures are being used, and, where possible, the distribution of teacher performance on the 

measures, as compared with the distribution of teacher performance on conventional value-added 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 4

measures that are based on state assessments. The study will examine the use of three categories of 

alternative student growth measures: (1) end-of-course curriculum-based assessments to which 

statistical growth models are applied; (2) nationally-normed assessments such as the PSAT or ITBS, to 

which statistical growth models are applied; and (3) student learning objectives, which do not involve 

the application of statistical growth models, and instead are intended to account for growth implicitly, 

because they are selected separately for each teacher’s students. Eight districts have been recruited to 

participate in the study; all three categories of alternative growth models are included among the eight 

districts. 

Data will be collected using semi-structured interviews with district administrators leading teacher 

evaluation or effectiveness efforts, teacher representatives (such as union leaders), teachers (including 

both classroom teachers and instructional coaches), and principals. Prior to the interviews, the study 

team will review documents, available on each of the districts’ websites, which address teacher 

evaluation and effectiveness efforts. The four types of respondents have been selected as the 

stakeholders who are most involved in the decision-making process and most impacted by 

implementation. District administrators and union representatives who played significant roles in 

developing the alternative growth measures will be best equipped to contribute information on the 

district’s decisions related to choosing and implementing the specific measure, and to describe any 

outcomes or lessons learned during the process that can be applied by other districts as best practices. 

Teachers and principals—the respondents most directly affected by the implementation of these 

alternative growth measures—will provide perspectives on the costs and benefits of implementation 

that other districts can anticipate. 

The data collected through interviews and document reviews will be summarized and analyzed using a

qualitative approach. First, a single write-up synthesizing information collected in the interviews will be 

created for each district. Then, a coding system will be developed to characterize the variation across 

key variables or categories of information (e.g., how teacher performance ratings are used). After the 

data have been coded, the study team will use four main categories to examine and summarize the 

data: the type of alternative student outcome and growth model, the applications of the growth 

measure, the differentiation in teacher performance produced by the growth measure, and the 

implementation process, including perceived costs and benefits of the measures. The data will be 

grouped by type of alternative growth measure rather than by district, and the study team will focus on 

examining consistencies and variation both within and across the alternative growth measure 

categories.

d. Recruitment of Districts

The study team has recruited eight school districts to participate in the study. The study team began the 

recruitment effort by mailing districts an introductory package, which will include the following two 

documents:

 Notification letter. The one-page notification letter describes the importance of studying the 

implementation of alternative measures of student growth, provides an overview of the study 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 5

design, summarizes the benefits of participating, and notes that a study team member will follow up 

by telephone to discuss the study in more detail(See Appendix A to Statement B). 

 Study summary. The two-page summary describes the purpose of the study and the benefits of 

participation, identifies the study team, and provides contact information for the project director 

and the ED project officer. It also discusses the activities required of participating districts and 

schools (See Appendix B to Statement B). 

Study team members followed up with phone calls involving one or more relevant district staff, 

describing the study in more detail, answering questions, and securing participation.

e. Data Collection Plan 

The study data collection consists of on-site and in-person interviews with school and district staff who 

are knowledgeable about district implementation of alternative measures of student growth. During 

December 2013 – February 2014, the study team plans to conduct interviews with up to ten individual 

respondents in each district—specifically, at least one district administrator, two principals, three 

classroom teachers, and one union/association representative. In larger districts, the study team will 

conduct additional interviews. In districts with dedicated instructional leaders (e.g., instructional 

coaches and master teachers), one or two additional interviews will be conducted with instructional 

leaders to supplement interviews with classroom teachers and gain a broader perspective on the effects 

on teachers of implementing the measures. The number of instructional leaders interviewed will depend 

on the size of the district. 

The selection of principal and teacher respondents will begin with a purposeful selection of the most 

credible and knowledgeable respondents. Because response bias is a concern and because the study 

team will not be able to select a representative sample of all subjects and grades in a district due to the 

small sample size of respondents, the team’s focus is on selecting teacher and principal respondents 

who will be most credible or accurate in their reports on implementation, application, and effectiveness 

of the alternative measures of student growth. To ensure a range of viewpoints, the study team will 

also solicit suggestions of teachers who actively struggled with implementation. 

Table 1 describes the timeline for data collection.

Table 1. Data Collection Timeline

2013 2014

1 2 3 4 5 6 7 8 9 10 11 12 1 2

Site selection and 

pilot interviews

  

Submission of 

initial OMB 

 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 6

2013 2014

1 2 3 4 5 6 7 8 9 10 11 12 1 2

clearance package 

(60-day public 

comment period)

Analysis of pilot 

interviews

 

Submission of final 

OMB clearance 

package

 

Data collection    

The focus of each interview will vary by respondent type as shown in Table 2. Interviews with district 

administrators will primarily cover the type of student outcome and growth measure used, the 

implementation process, and the extent of differentiation in teacher performance produced by the 

growth measure. Interviews with principals, classroom teachers, and instructional leaders will focus on 

the applications of the growth measure, the perceived costs and benefits of the measure from the 

viewpoint of the respondent, and the respondent’s perception of the success of the district’s 

communication during implementation of the measure. Interviews with teachers’ union/association 

representatives will cover the development and implementation of the alternative measure—

particularly related to the union’s involvement—and the respondent’s perception of the success of the 

district’s communication approach during the process. 

Interview protocols have been devised for each type of interviewee: district administrators, principals, 

teachers and instructional leaders, and union representatives. Those protocols are available in Appendix 

D of Part B.
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 7

Table 2. Interview Topics by Respondent Type

District Administrator Principal Teacher/

Instructional Leader

Union Representative

Type of student 

outcome and growth 

measure used

Design of growth 

measure

Piloting process

Training/PD during 

roll-out 

Involvement of

teacher or union in 

decision-making

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

Applications of 

growth measure

Feedback to 

teachers

Staffing decisions

Union role

√

√

√

√

√

√

√

√

√

√

√

√

Differentiation 

produced by growth 

measure

Relative distribution 

Reliability and 

validity

√

√

√

√

√

√

√

√

√

Implementation 

process

Assessment 

administration/

data collection

Data analysis

Quality control 

processes

Perceived costs 

and benefits of the 

measure

Perceived success 

of the district’s 

communication

and teacher 

response

Changes in the 

district’s approach

External funding

Related district 

changes

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√

√
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 8

The study team also plans to collect contextual information about the districts to describe the types of 

districts implementing alternative growth measures in each of the three categories. Specifically, the 

study team will collect information on district size, region, urbanicity, proportion of disadvantaged 

students, collective bargaining status, adoption of Common Core standards, and receipt of funding 

through RTT, School Improvement Grants (SIG), or the Teacher Incentive Fund (TIF) This information will 

be drawn primarily from the Common Core of Data; a full list of the specific variables and extant data 

sources the study team plans to use is included in Table 3.

Table 3. District Extant Data Collection Protocol

Variable Type of Data Categories Data Source

Size Total student 

enrollment

• Small (<10,000 students)

• Medium (10,000-45,000 

students)

• Large (>45,000 students)

Common Core of Data 

(CCD)

Region Geographic categories • North

• South

• West

• Mid-West

CCD

Urbanicity NCES urban-centric 

locale code

• City

• Suburb

• Town

• Rural

CCD

Poverty Proportion of students 

eligible for FRL

• High poverty (at least 65% 

of students eligible for FRL)

• Low poverty (<65% of 

students eligible for FRL)

CCD

Collective bargaining 

status

State collective 

bargaining requirement 

for school employees 

(binary)

• Collective bargaining 

required

• Collective bargaining not 

required

Department of Labor

Common Core State 

Standard adoption

Common Core State 

Standard adoption 

status (binary)

• In Common Core state

• Not in Common Core state

http://www.corestanda

rds.org/in-the-states

RTT participation by year 

of alternative growth 

measure implementation

RTT participation status 

(binary)

• In RTT state

• Not in RTT state

US Department of 

Education (ED)

SIG funding by year of 

alternative growth 

measure implementation

SIG funding status 

(binary)

• Received SIG funding

• Did not receive SIG funding

State departments of 

education SIG records; 

district interviews

TIF funding by year of 

alternative growth 

measure implementation

TIF funding status 

(binary)

• Received TIF funding

• Did not receive TIF funding

Center for Educator 

Compensation Reform
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 9

2. Purposes and Uses of Data

Mathematica will collect and analyze the data for the REL Mid-Atlantic Regional Educational Laboratory 

(REL) Alternative Student Outcomes for Growth Measures Case Studies under contract number ED-IES12-C-0006 with the Institute of Education Sciences, Department of Education. 

The primary purpose of the study is to document the implementation of alternative measures of student 

growth. The study team will examine what alternative outcome measures are used, how the alternative 

growth measures are implemented, challenges and obstacles in implementation, how the measures are 

being used, and, where possible, the distribution of teacher performance on the measures, as compared 

with the distribution of teacher performance on conventional value-added measures that are based on 

state assessments. The findings of this study will fill a gap in information on the implementation of such 

alternative growth measures and inform states and districts in deciding which measures are promising 

for use in evaluation systems, which are of doubtful value, and the difficulty of effectively implementing 

the measures.

The data to be collected will be obtained from district and school staff interviews. After the data have 

been coded, the study team will use four main categories to examine and summarize the data: the type 

of alternative student outcome and growth model, the applications of the growth measure, the 

differentiation in teacher performance produced by the growth measure, and the implementation 

process, including perceived costs and benefits of the measures. The data will be grouped by type of 

alternative growth measure rather than by district, and the study team will focus on examining 

consistencies and variation both within and across the alternative growth measure categories.

3. Use of Technology to Reduce Burden

Data from the semi-structured interviews cannot be collected through such methods as web surveys or 

computer-assisted telephone interviews. The proposed interviews will be necessary to allow in-depth, 

conversational exchanges with respondents, and to obtain answers to both open-ended and detailed 

questions. Prior to conducting the interviews, the study team will examine district websites to collect 

preliminary details about (a) the implementation of alternative measures of student growth in the 

district and (b) source documents to corroborate information provided during interviews. 

4. Efforts to Avoid Duplication

No comprehensive multi-district study has been conducted or is underway to address the research 

questions presented in this study. Few studies have evaluated the reliability and validity of value-added 

estimates that are based on alternative measures of student achievement, as demonstrated in Gill, 

Bruch, and Booker (2012). Johnson et al. (2012) is a notable exception. This study reports summary 

results for schoolwide value-added models in Pittsburgh that are based on end-of-course exams, PSATs, 

attendance, and the pass rate for core classes. The study finds that all of these measures can be used to 

statistically distinguish above-average and below-average school performance. Papay (2011) finds 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 10

correlations ranging from 0.15 to 0.58 across different model specifications between teacher valueadded estimates based on the two alternative assessments and the state assessment. 

There is also limited evidence on the reliability and validity of student learning objectives and their 

ability to distinguish among teachers. A recent study analyzed four years of data on student learning 

objectives in the context of a pilot program in Denver that tied additional teacher compensation to 

meeting goals set by student learning objectives (Community Training and Assistance Center, 2004). 

Results indicate a positive relationship between meeting student learning objectives and higher student 

achievement, providing some evidence of their predictive validity. The study also found that teachers 

improved the “quality” of their objectives over time, as they received more training and support on 

setting the targets. Ultimately, the pilot schools showed little variability in terms of teachers meeting 

and not meeting their student learning objectives. Goldhaber and Walch (2011) study the effect on 

student achievement of the compensation system that grew out of the pilot program analyzed in 

Community Training and Assistance Center (2004). They found that teacher effectiveness measures 

based on student learning objectives were highly correlated with teacher value-added based on 

standardized tests in math and reading. 

To date, the type of implementation analysis proposed for this study has not been conducted across 

multiple districts and types of alternative student growth measures, and there is no alternative source 

for the information to be collected.

5. Methods to Minimize Burden on Small Entities

The study team has developed an efficient interview protocol that focuses on the data of most interest

to districts and policymakers. Some of respondents, such as schools and small districts, will be small 

entities meaning they have a population of less than 50,000. The study team will also offer to speak with 

respondents via phone interviews rather than in-person visits when preferred by the district.

6. Consequences of Not Collecting Data

The data collection activities described in this submission are necessary for ED to document the 

implementation of alternative measures of student growth and assess their reliability and validity for 

evaluating teacher performance. This is a one-time data collection effort. The study represents a 

significant step in examining how to evaluate teachers using student growth measures in non-statetested grades and subjects. Without the data collected in this study, ED will not be able to provide 

sufficient information to assist states and districts in determining how to implement a teacher 

evaluation system that incorporates alternative measures of student growth.

7. Special Circumstances

There are no special circumstances associated with this data collection.
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 11

8. Federal Register Announcement and Consultation

a. Federal Register Announcement

A 60-day notice to solicit public comments will be published in the Federal Register in early August. We 

will analyze the responses in early October and submit the final package for approval within two weeks 

of the receipt of public comments.

b. Consultations Outside the Agency

The study team has worked with IES to identify five members to serve as the Technical Working Group 

(TWG) for this study. These experts on teacher evaluation and student assessment have provided input 

on the study’s design. For example, TWG members advised the study team to consider respondent bias, 

which led us to seek out some respondents who are unlikely to be advocates for the program. They also 

advised us to consider the relationship between the evaluation uses and instructional uses of student 

learning objectives, which the study team will do. The TWG includes the following individuals:

 Robert Boruch, University of Pennsylvania, 215-898-0409

 Laura Hamilton, RAND, 412-683-2300, x4403

 Christopher Hulleman, University of Virginia, 434-924-6998

 Andrew Porter, University of Pennsylvania, 215-898-7014

 Christopher Rhoads, University of Connecticut, 860-486-3321

9. Payments or Gifts

The study team will not give payments or gifts to districts for completing the interview or providing 

other study data. The study team does not believe it will be necessary to provide incentives for 

participation.

10. Assurances of Confidentiality

The data collection efforts that are the focus of this clearance package will be conducted in accordance 

with all relevant regulations and requirements, including the following:

 The Privacy Act of 1974, P.L. 93-579 (5 U.S.C. 552a).

 The Family Educational and Rights and Privacy Act (FERPA) (20 U.S.C. 1232g; 34 CFR Part 99).

 The Education Sciences Reform Act, P.L. 107-279 (20 U.S.C. 9573).

 The Freedom of Information Act (5 U.S.C. 552).

REL Mid-Atlantic (specifically, Mathematica Policy Research, a subcontractor to ICF International) will

protect the confidentiality of information for the study and will use it for research purposes only and will 

obtain security clearance through NCEE’s security clearance office. The project director will ensure that 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 12

individually identifiable information about study members remains confidential. All data will be kept in 

secured locations and identifiers will be destroyed as soon as they are no longer required. All members 

of the study team having access to the data will be trained and certified on the importance of 

confidentiality and data security. When reporting the results, the study team will present data in 

aggregate form only so that individuals and institutions will not be identified. The study team will also 

include the following statement in the requests to districts for participation in the study (Appendix A): 

 Responses to the data collection activities will be used for research purposes only. The reports 

prepared for the study will summarize findings across the sample and will not associate responses 

with a specific district, school, or individual. The study team will not provide information that 

identifies you or your district to anyone outside the study team, except as required by law. 

 The contractor follows the confidentiality and data protection requirements of the Institute of 

Education Sciences (The Education Sciences Reform Act of 2002, Title I, Part E, Section 183). The 

contractor will protect the confidentiality of all information collected for the study and will use it for 

research purposes only. No information that identifies any study participant will be released. 

Information on respondents will be linked to their institution but not to any individually identifiable 

information. No individually identifiable information will be maintained by the study team. All 

institution-level identifiable information will be kept in secured locations and identifiers will be 

destroyed as soon as they are no longer required.

The following safeguards, which are routinely employed by Mathematica to carry out confidentiality 

assurances, will be applied consistently during the study: 

 All employees sign a confidentiality pledge (Appendix B), which describes both the importance of 

and the employee’s obligation to discretion. 

 Personally identifiable information is maintained on separate forms and files, which are linked by 

sample identification number only.

 Access to hard copy documents is strictly limited. Documents are stored in locked files and cabinets, 

and discarded materials are shredded.

 The study team will submit a list of all people who have access to respondents and data to NCEE and 

will track all staff joining or leaving the study to ensure that signatures are obtained and clearances 

revoked.

 Access to computer data files is protected by secure user names and passwords, which are available 

to specific users only.

 Especially sensitive data is encrypted and stored on removable storage devices that are kept 

physically secure when not in use.

The plan for maintaining confidentiality includes ensuring that all personnel with access to individual 

identifiers sign confidentiality agreements and provide notarized nondisclosure affidavits. Also included 

in the plan is personnel training regarding (1) the meaning of confidentiality, particularly as it relates to 

handling requests for information and providing assurance to respondents about the protection of their 

responses; (2) controlled and protected access to computer files under the control of a single database 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 13

manager; (3) built-in safeguards concerning status monitoring and receipt control systems; and (4) a 

secured and operator-controlled, in-house computing facility.

11.Justification for Sensitive Questions

There are no questions of a sensitive nature in the district interviews.

12. Estimates of Burden Hours

Table 3 shows the estimated burden hours for district staff who will participate in data collection. These 

estimates are based on the study team’s experience collecting such data from district staff for similar 

studies. Please also refer to the IC burden table included as an attachment to this supporting statement.

Table 3. Estimated Response Time for Data Collection

Respondent/Data Request

Number of

Targeted 

Respondents

Expected 

Respons

e Rate 

(%)

Number of 

Respondents

Unit 

Respons

e Time 

(Hours)

Total 

Response 

Time 

(Hours)

Total Cost 

(Based on 

hourly 

wage rate)

District staff

Recruitment by phone 20 100 20 2 40 $1944

Phone interview (up to 2 

staff at each district)

18 100 18 1 18 $875

Principals

Recruitment by phone 27 100 27 1 27 $1181

Phone interview (up to 3 

principals in each district)

27 100 27 1 27 $1181

Teachers

Recruitment by phone 36 100 36 1 36 $980

Phone interview (up to 4 

teachers in each district)

36 100 36 1 36 $980

Instructional Leads/Coaches

Recruitment by phone 12 100 12 1 12 $245

Phone interview (up to 4 

teachers in each district)

12 100 12 1 12 $245

Teachers’ Union/Association 

Representative

Recruitment by phone 9 100 9 1 9 $245

Phone interview (up to 1 

representative in each 

district)

9 100 9 1 9 $245

Total 104 104 226 $8,121

Note: Total cost estimates based on hourly wage rates for the Bureau of Labor Statistics’ May 2012 

National Industry-Specific Occupational Employment and Wage Estimates, NAICS 61100: Educational 

Services (http://www.bls.gov/oes/current/naics3_611000.htm). District staff burden estimates based on a 

mean hourly wage of $48.59 for Human Resources Managers in Elementary and Secondary Schools (11-

3121). Principal burden estimates based on a mean annual salary of $90,980 and 2,080 annual hours for 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 14

Educational Administrators in Elementary and Secondary Schools (11-9032). Teacher, instructional leads,

and union/association representative burden estimates based on a mean annual salary of $56,620 and 

2,080 annual hours for Preschool, Primary, Secondary, and Special Education Teachers (25-2000). Total 

costs rounded to the nearest dollar.

13. Estimates of Cost Burden to Respondents

There are no start-up costs or ongoing operation and maintenance costs for respondents.

14. Annualized Cost to the Federal Government

The estimated cost of the study to the federal government is $345,339 over two years, for an average 

annual cost of $172,670. The estimated total cost of the REL Mid-Atlantic Region five-year contract is 

$32,353,087, of which this study accounts for $345,339. Study costs were estimated using fullyburdened (“loaded”) hourly rates for staff, multiplied by the estimated number of hours of labor, and 

adding travel and other direct costs. Multipliers for indirect rates were applied to travel and other direct 

costs.

15. Reasons for Program Changes or Adjustments

This is a new data collection.

16. Plans for Tabulation and Publication of Results

Table 4. Timeline for Data Collection and Analysis

2013 2014

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8

Site selection 

and pilot

interviews

  

Submission of 

initial OMB 

clearance 

package (60-day 

public comment 

period)

 

Analysis of pilot 

interviews

 

Submission of 

final OMB 

clearance 

package

 

Pilot report 

draft 1 (internal 

 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 15

2013 2014

1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 7 8

and IES review)

Pilot report 

draft 2 (internal 

and IES review)

 

Delivery of pilot

results to 

requestors and 

report public 

release



Data collection   

Data analysis   

Draft 1 of final 

report (internal 

and IES review)

 

Draft 2 of final 

report (internal 

and IES review)

 

Delivery of 

results to 

requestors and 

final report 

public release 



a. Tabulation Plans

The study team will use the information gathered from the district and school staff interviews to 

examine and describe the implementation of alternative measures of student growth in three main 

categories: (1) end-of-course curriculum-based assessments to which statistical growth models are 

applied; (2) nationally-normed assessments such as the PSAT or ITBS, to which statistical growth models 

are applied; and (3) student learning objectives, which do not involve the application of statistical 

growth models, and instead are intended to account for growth implicitly, because they are selected 

separately for each teacher’s students. 

To prepare the interview data for the analysis, the study team will develop a coding system organized 

into four broad categories of information: the type of alternative student outcome and growth model, 

the applications of the growth measure, the differentiation in teacher performance produced by the 

growth measure, and the implementation process, including perceived costs and benefits of the 

measures. The study team will define codes for the variations that they expect to observe based on their

initial literature review and refine the coding system as they collect data. For example, as part of their

coding of applications of alternative growth measures, they will create categories to capture how 

teacher performance ratings based on these measures are used: for evaluating teachers, for targeting 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 16

professional development, for performance-based compensation, and for assigning teachers to 

positions in the district. 

The study team will use the four main categories in the coding system—the type of alternative student 

outcome and growth model, the applications of the growth measure, the effectiveness of the growth 

measure in differentiating teacher performance, and the implementation process (including the 

perceived costs and benefits of the measures)—to summarize key findings across all districts. The 

district will be the primary unit of analysis. The study team plans to address their research questions by 

summarizing and reporting on the following findings by category:

 Type of alternative student outcome and growth model: frequency of each outcome and growth 

model; range and mean years of implementation; range and frequency of subjects and grades 

affected; frequency of application to teachers of ELL and special education students

 Applications of growth measure: frequency of specific uses for alternative measures(evaluation, 

compensation, targeting of professional development, teacher assignment, tenure awards, etc.); 

range and mean frequency of feedback to teachers on alternative growth measure performance 

ratings

 Differentiation of growth measure: characteristics of reliability and validity analysis; range of 

reported reliability and validity for each measure; range and mean number of performance 

categories; range and mean percentage of teachers in highest and lowest performance categories; 

range of weights given to the alternative measures

 Implementation process (including perceived costs and benefits): mean length of piloting period; 

range and mean frequency of data collection; frequency of external vendor contracting; most 

frequently cited quality control measures; most cited obstacles to data collection and analysis; most 

frequently cited benefits (by respondent type); most frequently cited costs (by respondent type); 

range and mean monetary cost (by type of cost cited)

To facilitate cross-site analysis, the data will be grouped by type of alternative growth measure rather 

than by district. Across all districts, the study team will examine findings by key factors of interest to 

stakeholders: type of alternative growth measure and years of experience in implementation. The study 

team will summarize and report information in text and numeric tables to examine cross-site themes 

and the role of district contextual factors. While the study team will strive to provide quantifiable 

information where possible, much of their reporting will focus on themes and detailed descriptions 

rather than on summary statistics to help inform future program design. In particular, the study team

will focus on providing specific details on the implementation process and perceived costs and benefits 

by type of alternative student outcome to help guide policymakers in decision-making and 

implementation. 

The study team plans to examine variation not only across the measures but within the measures as 

well, when possible. In addition to looking at the commonalities of districts using the same alternative 

outcome, the study team will consider the range of experiences within a single category and even within 

a single district. Previous research suggests that districts vary in their approaches to implementing 
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 17

student learning objectives. In addition, there are likely differences in the extent to which assessments 

in a particular outcome category—for example, nationally normed assessments—are aligned with a 

single grade and subject. The PSAT, for example, is designed to reflect multiple years of learning that 

may not be attributable to a particular teacher.

b. Publication Plans

The study team will produce two “What’s Happening” reports during the course of the project. The first 

report, scheduled to be released in September 2013, will be based on document reviews and one pilot

interview with a key staff person in each district, and will present preliminary findings. It will focus 

largely on the design and intended use of the alternative growth measures. The final report, scheduled 

to be released in August 2014, will focus on cross-measure analysis. The study team will present an 

overview of the types of alternative measures on which they collected data, followed by three sections 

on findings: (1) applications of the measures, (2) differentiation produced by the measures (including 

evidence of validity and reliability), and (3) implementation of the measures, including benefits and 

costs. Within each of the three sections the study team will compare findings across the types of 

alternative growth measures to allow readers to make comparisons based on the dimensions of interest. 

Both reports will be aimed at educators and policymakers and will use practitioner-friendly language to 

describe what the team has learned about the implementation of a variety of alternative measures of 

growth/value-added in the case study sites. The reports will be released by the REL and available on the 

REL web page. To avoid the risk of deductive disclosure of district identities, profiles of individual 

districts will not be included in the reports.

17. Approval Not to Display the Expiration Date for OMB 

Approval

The study will display the OMB expiration date.

18. Exception to the Certification Statement

No exceptions are being sought.
OMB Package: Alternative Student Outcomes for Growth Measures Case Studies 18

REFERENCES

Community Training and Assistance Center (2004). Catalyst for Change: Pay for performance in Denver. 

Final Report. Retrieved on May 4th, 2012 from: http://www.ctacusa.com/PDFs/RptCatalystChangeFull-2004.pdf

District of Columbia Public Schools (2011). “IMPACT: The DCPS Effectiveness Assessment System for 

School-Based Personnel, 2011-2012,” Washington, DC: District of Columbia Public Schools, 2011. 

Available at 

[http://dcps.dc.gov/DCPS/Files/downloads/TEACHING%20&%20LEARNING/IMPACT/IMPACT%20Gui

debooks%202010-2011/Impact%202011%20Group%202-Aug11.pdf]. Accesses June 27, 2013. 

Gill, B., J. Bruch, and T.K. Booker. Using alternative student growth measures for evaluating teacher 

performance: what the literature says. (NCEE 2013–4006). Washington, DC: U.S. Department of 

Education, Institute of Education Sciences, National Center for Education Evaluation and Regional 

Assistance, Mid-Atlantic Regional Educational Laboratory, 2013.

Goe, L. and L. Holdheide. “Measuring Teachers’ Contributions to Student Learning Growth for Nontested 

Grades and Subjects.” National Comprehensive Center for Teacher Quality Research & Policy Brief, 

2011.

Goldhaber, D. and J. Walch. “Strategic Pay Reform: A Student Outcomes-Based Evaluation of Denver’s 

ProComp Teacher Pay Initiative”. Center for Education Data & Research Working Paper no. 2011-3.0, 

University of Washington, 2011.

Goldstein, J. and P. Behuniak. “Growth Models in Action: Selected Case Studies.” Practical Research, 

Assessment, & Evaluation, Vol. 10, No. 11, 2005, pp. 1-17.

Johnson, M., S. Lipscomb, B. Gill, K. Booker, and J. Bruch. “Value-Added Models for the Pittsburgh Public 

Schools.” Report to the Pittsburgh Public Schools. Cambridge, MA: Mathematica Policy Research, 

2012.

Kimball, Steven M., Matthew Clifford, Jenni Fetters, Jessica Arigoni, and Kim Bobola. “Evaluating 

Principals’ Work: Design Considerations and Examples for an Evolving Field.” Washington DC: US 

Department of Education, 2012.

Marietta, G. “Multiple Measures of Teacher Effectiveness in Hillsborough County Public Schools: 

Implementing Value-added Measures.” Retrieved on May 4th, 2012 from: 

http://www.fadss.org/_docs/_content/eet/caseStudyHCPS/ImplementingValueaddedMeasuresHCPS.pdf.

Potamites, L., D. Chaplin, E. Isenberg, and K. Booker. “Measuring School Effectiveness in Memphis – Year 

2.” Report to New Leaders for New Schools. Washington, DC: Mathematica Policy Research, 2009.

Zinth, J. D. (2010). “Teacher Evaluation: New Approaches for a New Decade.” Teaching QualityEvaluation and Effectiveness Issue Brief. Denver, CO: Education Commission of the States.