U.S. Department of Education 

Institute of Education Sciences 

NCES 2005–160

Feasibility of a 

Student Unit 

Record System 

Within the 

Integrated 

Postsecondary 

Education Data 

System 

Research and Development 

Report 

March 2005 

Alisa F. Cunningham 

Institute for Higher Education Policy

John Milam 

HigherEd.org, Inc.

Cathy Statham 

Project Officer 

National Center for Education Statistics
U.S. DEPARTMENT OF EDUCATION 

Margaret Spellings 

Secretary 

INSTITUTE OF EDUCATION SCIENCES 

Grover J. Whitehurst 

Director 

NATIONAL CENTER FOR EDUCATION STATISTICS 

Grover J. Whitehurst 

Acting Commissioner 

The National Center for Education Statistics (NCES) is the primary federal entity for collecting, analyzing, and 

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NCES activities are designed to address high priority education data needs; provide consistent, reliable, complete, 

and accurate indicators of education status and trends; and report timely, useful, and high quality data to the U.S. 

Department of Education, the Congress, the states, other education policymakers, practitioners, data users, and the 

general public. 

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audiences. You, as our customer, are the best judge of our success in communicating information effectively. If you 

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Please direct your comments to: 

National Center for Education Statistics 

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March 2005 

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Suggested Citation 

Cunningham, A. F., and Milam, J. (2005). Feasibility of a Student Unit Record System Within the Integrated 

Postsecondary Education Data System (NCES 2005–160). U.S. Department of Education, National Center for 

Education Statistics. Washington, DC: U.S. Government Printing Office. 

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Content Contact: 

Cathy Statham 

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cathy.statham@ed.gov
iii 

Executive Summary 

This report examines the feasibility of 

implementing a student unit record (UR) 

system to replace the student–related 

components of the Integrated 

Postsecondary Education Data System 

(IPEDS). The feasibility study was 

initiated by the National Center for 

Education Statistics (NCES), a part of 

the Institute of Education Sciences (IES) 

within the U.S. Department of Education 

(ED), in response to growing interest 

within the postsecondary education 

community for more accurate measures 

of net price and graduation rates, 

especially measures that take into 

account institutional mission and student 

mobility. This interest parallels a 

growing congressional desire to hold 

postsecondary institutions accountable 

for student outcomes. 

Background 

This discussion of the feasibility of a 

UR system at the federal level is 

occurring within the context of the 

development of other UR systems for 

students attending postsecondary 

institutions. Unit record systems are 

maintained by most colleges and 

universities to track registration for 

courses, academic performance, degree 

and certificate completion, financial aid, 

and other purposes. A number of states 

began to develop UR systems in the 

mid–1980s and use UR data for analysis 

and program evaluation. Today, 39 

states have at least one student UR 

system. A limitation of state UR 

systems, however, is that most do not 

include data on students attending 

private institutions, or students who 

leave an institution and transfer across 

state lines. 

Many governmental and other 

organizations also maintain UR systems 

on specific groups of students. For 

example, the National Student Loan 

Data System (NSLDS) within the office 

of Federal Student Aid (FSA) compiles 

information on all recipients of federal 

student loans, including verification of 

enrollment by academic term. In 

addition, the National Collegiate 

Athletic Association (NCAA) collects 

UR data on 1,800 institutions with 

Division I, II, or III varsity athletic 

programs, and about 2,800 colleges and 

universities currently contract with the 

National Student Clearinghouse to 

perform enrollment verification and 

other services using student UR data 

uploaded from member institutions. 

At IES/NCES, the Integrated 

Postsecondary Education Data System 

(IPEDS) is the core postsecondary 

education data collection program, 

designed and implemented to meet its 

mission to report on the condition of 

postsecondary education in the United 

States. IPEDS is a single, comprehensive 

system that encompasses over 10,000 

institutions whose primary purpose is to 

provide postsecondary education 

(including roughly 6,700 institutions that 

have Program Participation Agreements 

with ED for Title IV federal student 

financial aid programs and are required 

by statute to report to IPEDS). The 

IPEDS system collects institution–level
Executive Summary

iv 

data in the areas of enrollment, program 

completions, graduation rates, faculty, 

staff, finances, institutional prices, and 

student financial aid. The use of 

aggregate data has some limitations in 

comparison with UR data, such as the 

inability to track the academic progress 

and experiences of individual students, 

and therefore to study the longitudinal 

enrollment of different types of students. 

 Despite its comprehensiveness, the 

IPEDS system cannot measure many of 

the evolving trends in postsecondary 

education that are necessary for sound 

policy decisions. The current IPEDS 

framework cannot accurately capture 

changing enrollment and completions 

patterns in the postsecondary education 

sector, especially given increasing 

numbers of nontraditional students, and 

cannot describe the prices various types 

of students face after financial aid is 

taken into account. To do so, it would be 

necessary to collect accurate student–

level information on persistence 

systemwide (i.e., regardless of institution 

and nationwide), multiple enrollment, 

part–time enrollment, transfer, and 

attainment. It would also be necessary to 

collect student–level information on 

prices and financial aid, in order to 

calculate net prices that take into account 

the individual circumstances of each 

student. By its very nature, a UR system 

would enable the collection of data that 

would lead to more accurate estimates of 

these variables. In addition, a UR system 

would allow the development of a whole 

range of new measures, such as net 

prices for specific groups of students, 

graduation rates that take into account 

institutional missions, persistence rates 

that consider student mobility and a 

systemwide perspective, measures of 

enrollment patterns for nontraditional 

students, and time to degree by field of 

study. 

Goals and Design of the 

Feasibility Study 

In exploring the feasibility of a UR 

system, the study attempted to 

investigate whether such a system could

be constructed technically and 

effectively, given the knowledge about 

UR systems already accumulated at the 

state and institutional levels. In addition, 

the feasibility study tried to explore 

whether such a system should be 

developed by the federal government. To 

do so, the study solicited input on 

several dimensions, including privacy 

and confidentiality, institutional burden, 

coordination, technical issues, and 

timing. 

As part of the feasibility study, three 

Technical Review Panels (TRPs) were 

designed to gather feedback and ideas 

from different perspectives related to the 

study, and included representatives from 

the following groups: 1) states, state 

systems, private systems, and private 

associations of colleges and universities; 

2) institutions, particularly institutional 

researchers and registrars; and 3) other 

stakeholders, including the national 

postsecondary education association 

community, federal agencies, units 

within the ED, and vendors such as 

administrative information system 

developers. In addition, the contractor 

developed an architecture and flow of 

operations for a proposed student UR 

system, as well as a list of potential data 
Executive Summary 

v 

elements that might be collected under 

such a system. 

In reading this report, it is important 

to keep in mind that any redesign of 

IPEDS to develop a UR system would 

require legislative authorization through 

amendments to the Higher Education 

Act (HEA) and funds would have to be 

appropriated by Congress to implement 

the system. 

Proposed Redesign of IPEDS 

If authorized and funded, the 

proposed UR system would replace the 

student–related components in the 

current IPEDS collection—Fall 

Enrollment, Completions, Student 

Financial Aid, and Graduate Rates—as 

well as the price of attendance variables 

collected in the Institutional 

Characteristics component. The UR 

system would be designed to include all 

of the variables necessary to replace 

those components and calculate 

institution–level estimates for the Peer 

Analysis System (PAS). The collection 

process for nonstudent–related 

components in IPEDS would remain the 

same. 

It is difficult to describe exactly what 

the UR system would look like before 

the design process is undertaken. Such a 

process would involve numerous 

technical review panels and input from 

campuses, university systems, and state 

coordinators, particularly from states 

with UR systems. Generally, the UR 

collection system would be designed to 

collect individually identifiable data 

through files that are submitted 

electronically by institutions. The files 

would be used to calculate institutional 

summary totals for each school, with 

information about enrollment, 

completions, graduation rates, financial 

aid, and price. Four types of files would 

be submitted. 

• Header files: These data provide 

individually identifiable information 

such as name, Social Security 

Number (SSN), date of birth, 

address, race/ethnicity, and gender 

that are attached to an individual 

student’s record. These files would 

be required at least once for every 

student. New header records would 

be submitted as needed to document 

any changes in these key data. 

• Enrollment/term files: These data 

include program information such as 

number of courses and credits 

attempted, major field of study, start 

and end dates, and attendance status. 

The files would be required three to 

four times a year, and institutions 

would be allowed to upload files 

more frequently if they wished. 

• Completions files: These data 

include information on degree 

completions and the date of 

completion. The files would need to 

be uploaded at least once per year. 

• Financial aid files: These data 

include information on financial aid 

received from federal, state, and 

institutional sources. Information on 

price of attendance would also be 

included with the financial aid file. 

These data also would need to be 

uploaded at least once a year. 
Executive Summary

vi 

In addition, in the first year of an 

IPEDS UR collection, additional files 

would need to be submitted in order for 

NCES to complete the historical 

calculations that are part of the 

Graduation Rate Survey. Depending on 

program length, these could include up 

to six years of data for key pieces of 

information. 

For each submission of data, the 

IPEDS keyholder at an institution or 

coordinating agency would submit data 

electronically through the IPEDS 

collection system, similar to the process 

that exists currently. After submission, 

NCES would review the data to make 

sure they are consistent within the file 

and with prior submissions. Schools 

would work with the IPEDS Help Desk 

to match all records, and any that do not 

match would have to be resolved. The 

UR data would then be summarized in 

online institutional reports, which would 

also be checked for consistency, before 

the keyholder “locks” or finalizes the 

submission. 

The UR data would then be moved 

from the collection system to the 

permanent database storage system. The 

full UR database would only exist in this 

permanent storage area, which would not 

be accessible via the Internet and would 

be subject to high IES/NCES levels of 

protection for confidentiality and 

security. Ultimately, aggregate estimates 

would be calculated from the full UR 

database and moved to the PAS, where 

they would be stored as institution–level 

data. 

Individually identifiable data would 

remain within the permanent storage 

system. The only allowable redisclosures 

of individually identifiable data would 

have to be specifically authorized in the 

HEA legislation, including. 

• Enrollment verification for the 

National Student Loan Data System 

(NSLDS): The UR system would be 

used to verify enrollment for 

students who are receiving federal 

student loans. Currently, this 

verification is being done either by 

institutions themselves, or by 

organizations such as the National 

Student Clearinghouse. 

• Verification of subsequent 

enrollment to the IPEDS keyholder: 

The UR system would be used to 

redisclose individually identifiable 

data back to the initial keyholders 

and to state/system coordinators, in 

order to give something back to 

institutions. Data on the subsequent 

enrollment of students who left the 

first institution in the previous year 

would be redisclosed to the 

keyholder, including the institution 

of subsequent enrollment, date, 

attendance status, attainment, and 

date of attainment.1

 

• Record mismatches: During the 

process of data collection for the UR 

system, mismatches between data 

records and other types of edit 

failures would have to be resolved. 

This would involve sending 

individually identifiable information 

back to the IPEDS keyholder. These 

 

1

 Redisclosure of student information to the 

original institutions could take place over a 

longer time period if this was decided by a future 

design Technical Review Panels and NCES. 
Executive Summary 

vii 

types of edit failure resolutions 

would be essential to the data 

integrity of the database. 

Other uses of the data would not 

involve the disclosure of individually 

identifiable student information. For 

example, while ensuring the 

confidentiality of the data, NCES could 

generate aggregate reports for the Office 

of Postsecondary Education (OPE) using 

the UR data (e.g., to generate aggregate 

measures of persistence, transfer, and 

attainment for various types of federal 

student aid recipients, such as those 

attending on a part–time basis). It would 

also be possible to add new derived 

variables to the PAS, used by 

institutional researchers and other 

analysts. Each of these derived variables 

would be reviewed for potential 

disclosure risks prior to their release on 

the PAS. Such variables could include 

new definitions of net price; new 

measures of graduation rates that better 

take into account the missions of 

postsecondary institutions and the 

mobility of students across institutions; 

new definitions of time to degree, 

including transfer calculated for various 

fields of study; variables that describe 

enrollment by field of study and program 

length; and completions by field of 

study. 

Challenges to Implementing a 

UR System 

Technically, UR could be done at 

most institutions in the long term, after 

investment of time and financial 

resources. This can be inferred from the 

fact that 39 states have compiled UR 

systems in some form; thousands of 

postsecondary institutions already 

submit UR data electronically to private 

organizations; and postsecondary 

institutions that are Title IV participants 

are required to upload information on 

federal aid recipients to the FSA. 

Nonetheless, in feedback from 

institutions, states, associations, and 

other stakeholders, it is clear if a UR 

system is legislatively authorized, 

certain concerns must be dealt with and 

resolved in the design phase of 

implementation. 

Privacy and confidentiality 

Concerns have been raised about 

student privacy and the confidentiality of 

individually identifiable student data 

under a federal UR system. ED, IES, and 

NCES have always taken seriously the 

importance of safeguarding student data, 

but a UR system raises questions about 

students’ rights to withhold or control 

personal information. This is particularly 

the case for students who do not receive 

federal student aid. However, these 

students benefit indirectly2

 from federal 

student aid funds, which support all 

programs, and benefit directly from state 

appropriations at public institutions and 

the tax–exempt status of private, not–

for–profit institutions. Additionally, data 

on nonaided students are a critical 

element to compute graduation rates, 

retention measures, and other indicators. 

Information on nonaided students would 

be necessary in order to compare these 

measures with information on students 

receiving student aid. 

 

2

 Tuition at these schools is probably lower than 

it would be if they were not the beneficiaries of 

tax–exempt status and state appropriations. 
Executive Summary

viii 

In addition to misgivings about 

student privacy, there are practical, 

technical concerns about unauthorized 

access to the data by hackers and 

identity theft. This is particularly true 

given the proposal to use SSNs as one of 

several personal identifiers that are 

necessary for matching student records. 

The use of SSNs would be essential to a 

UR system to accurately link together 

student information on financial aid, 

enrollment, and completions, as well as 

records from various institutions. 

Enrollment verification for the FSA 

already includes the use of SSNs as a 

student identifier. An additional measure 

of enrollment intensity at the start of 

each term (such as full– or part–time) 

would also be collected to satisfy FSA 

requirements. 

Despite these concerns, IES/NCES is 

well suited to protect the data, given the 

strict limits of the legislation regarding 

data confidentiality under which it 

operates. IES/NCES legislation protects 

the privacy of individuals, making 

wrongful disclosure a Class E felony 

punishable by up to five years in jail and 

a $250,000 fine. NCES has experience in 

working with individually identifiable 

data through its various sample surveys, 

and has created the structures and 

procedures necessary to prevent 

unauthorized disclosure of such data. In 

fact, there are no cases where 

individually identifiable data collected 

by NCES have been wrongfully 

disclosed by an employee, a contractor, 

or a restricted licensee, or of cases in 

which hackers have breached IES/NCES 

firewalls. If collected, the data would be 

technologically protected and secure, 

and would not leave NCES unless 

allowed by law. Under the Patriot Act, 

the Attorney General and the 

Department of Justice could conceivably 

obtain access to UR data in order to fight 

terrorism. Students on whom data are 

held would be able to “opt out” of the 

redisclosure of subsequent enrollment 

information. 

Institutional burden 

The additional burden of a UR system 

can be divided into two categories: 

initial implementation and subsequent 

operations. The burden of initial 

implementation is expected to be higher 

than the costs of subsequent operations. 

A field test would be necessary in order 

to make sure the system works, to 

anticipate and address problems that 

would be encountered, and to develop all 

necessary features in the system prior to 

implementation. About 1,200 to 1,500 

institutions would be required to 

participate in the field test and report 

using both the old and new IPEDS 

collection system. Although NCES 

would make every effort to notify 

selected institutions early, participating 

institutions would need to make changes 

in their reporting systems within a 

relatively short time frame, depending 

upon the desire of Congress for an 

implementation schedule. 

In the full–scale implementation, 

many institutions would need to upgrade 

information technologies and assign staff 

to comply with new reporting 

requirements. Staff would need to be 

trained in the use of these systems and 

the details of reporting procedures. Some 

institutions would need to rely on 

vendors to provide upgrades to existing 
Executive Summary 

ix 

software, build their UR extracts, or pay 

for changes to legacy information 

systems. These additional activities 

would likely increase software costs. 

Obtaining historical GRS files for all 

cohorts in the first year would present a 

burden (although these same files are 

needed now to calculate the GRS 

locally). The initial burden on small 

institutions is likely to be relatively high, 

unless the institutions are part of a larger 

system or state association. 

The additional costs of subsequent 

operations under a UR reporting system 

are expected to be lower than the costs 

of initial implementation. Keyholders 

would need to coordinate with offices on 

campus to gather data, run internal 

checks to make sure data make sense, 

submit data to NCES several times per 

year, and work with the IPEDS Help 

Desk to reconcile record mismatches and 

discrepancies in data. Some mismatches 

of records could be difficult to resolve, 

especially if there are numerous records. 

It is very difficult, at the conceptual 

stage, to make cost estimates with any 

degree of precision. Costs would differ 

widely among postsecondary 

institutions, depending on whether they 

are in state UR systems, whether they 

currently upload to organizations such as 

the National Student Clearinghouse, 

whether they use local or proprietary 

administrative information systems, and 

the extent of their IT and institutional 

research capability. There would be a 

decrease in burden after the initial 

implementation of a UR system, as 

postsecondary institutions would no 

longer need to track and maintain 

records on GRS cohorts for six years or 

fill out the current IPEDS student–

related components. 

If a UR system were implemented, it 

would be important to take into account 

these various issues during the design 

phase of implementation so as to 

minimize institutional burden. There are 

different ways to offset the cost and 

burden of a UR system. One funding 

mechanism, Administrative Cost 

Allowances (ACAs), is used to help 

defray the cost of administering federal 

student aid programs.3

 A similar funding 

mechanism could be put in place for a 

UR system. 

Technical issues 

Technical issues were also raised as a 

potential challenge to the 

implementation of a federal UR system. 

The proposed system would include the 

creation and maintenance of a database 

of millions of student records, with new 

records added every year. In addition, 

the system would require the uploading 

of large files from postsecondary 

institutions to NCES, using multiple 

forms of security to protect against 

unauthorized disclosures of data. NCES 

currently has most of the hardware and 

software necessary to implement a UR 

system, including current equipment 

used in the web–based IPEDS collection 

as well as servers capable of storing 

large amounts of student data. One 

necessary addition would be database 

storage, to be located offline in a secure 

 

3

 Institutions currently receive over $150 million 

in Administrative Cost Allowances (ACAs), 

which is provided to help cover the cost of 

administration of federal programs such as Pell 

Grants and campus–based aid. 
Executive Summary

x 

site and protected by physical and 

software firewalls. 

There would likely be greater 

technical challenges for postsecondary 

institutions, with the extent varying 

among the registrar, institutional 

research, and financial aid offices, which 

sometimes utilize different and 

incompatible information systems. 

Institutions using both legacy and 

proprietary student information systems 

would need to make software 

conversions or updates. For the smallest 

schools, an Excel template could be 

provided to collect data and generate the 

data file needed for submission. 

Although the technical issues could 

present a problem, these schools 

currently find a way to do uniform 

reporting for FSA financial aid 

eligibility and NSLDS loan deferment. 

The proposed UR system would also 

use XML4

 technology for the submission 

of data files to NCES, although it is 

likely that ASCII files would be 

accepted in the early years of 

implementation. Some postsecondary 

institutions have already adopted XML 

and are using it in their exchange of data 

with other organizations. On the other 

hand, many institutions do not currently 

use XML and training would be required 

on the use of this technology. 

Nonetheless, the FSA has already 

mandated that institutions begin 

 

4

 XML is a “markup language,” or mechanism 

for identifying structures within a document or 

data file. It employs tags to identify data 

elements, thereby facilitating the seamless 

exchange of data. In other words, it allows users 

to describe data and deliver it across a network, 

through the creation of common records across 

disparate databases. 

submitting data to the office using XML 

by 2005–06. 

Coordination 

Coordination of the flow of 

information presents a multitude of 

challenges in implementing a UR 

system. For example, a UR system might 

not work well within the existing IPEDS 

structures in some states. Most state UR 

systems are based on specific census 

dates. If multiple header and/or 

enrollment files need to be submitted at 

different points in time to capture total 

enrollment, this would involve a change 

in workload for both institutions and 

systems. Special TRP meetings should 

be held during the UR design phase in 

order to leverage existing UR systems 

whenever possible in order to meet both 

federal and state/system requirements 

and needs. This will prevent unnecessary 

duplication of effort and reporting, and 

ensure that any federal UR system 

maximizes the lessons that have been 

learned through years of state UR 

reporting. 

Timing 

In implementing a UR system, the 

timing of data collections would have to 

be addressed. If a UR system were 

authorized in 2005, a field test would 

then be administered in 2006–07, 

followed by full–scale implementation in 

2007–08. The project timetable is 

designed to yield data relatively quickly 

while avoiding potential problems 

associated with an expedited timeframe. 

A phased implementation could also be 

considered to provide additional time to 

address problems during 
Executive Summary 

xi 

implementation. To respond adequately 

as part of the field test, it might be 

necessary for institutions to examine the 

utility of their administrative information 

systems for the purposes of producing 

UR extracts and to address some of the 

burden issues mentioned above such as 

training and staffing. Early notification 

for the selected institutions would be 

crucial for the institution’s ability to 

respond in a timely and accurate fashion. 

It is possible that NCES could draw the 

sample of institutions immediately after 

legislative authorization to allow 

selected institutions almost a year to 

prepare. 

Since the UR system is based on 

individually identifiable records, it must 

comply with the Office of Management 

and Budget (OMB) requirement for 

collecting race/ethnicity data with a 

two–question format. A by–product of 

the UR system is that schools that have 

not yet implemented this change will 

need to do so to meet OMB Statistical 

Policy Directive No. 15, Race and 

Ethnic Standards for Federal Statistics 

and Administrative Reporting. 

Another important issue is 

operational—how to time data collection 

schedules, while minimizing conflicts 

with other reporting schedules. The 

proposed UR system likely would 

collect enrollment records once per term. 

However, some institutions do not have 

standard terms; for example, courses 

may be offered on a rolling basis or on 

six–week terms. Institutions could 

choose to upload data more frequently, 

especially for the purpose of enrollment 

verification for student loan programs. It 

would be necessary to find a method of 

specifying a whole range of flexible term 

reporting options, perhaps by asking 

institutions to document all possible 

term sequences using the IPEDS 

Institutional Characteristics component. 

Degree and certificate completions 

would likely be collected with only one 

file per year, although institutions with 

several commencement periods might 

wish to submit multiple files over the 

year. In some cases, awards are recorded 

months after the relevant students have 

stopped attending institutions; degree 

dates then reflect the date the degree was 

awarded rather than when the degree 

was finished. In designing the timing of 

data collections and the periods of 

reference for the data, it would be useful 

to align the completions data with the 

enrollment data necessary to calculate 

graduation rates so that completions 

records can be matched to comparable 

enrollment records. 

Student financial aid information also 

would likely be collected in only one file 

per year. Data submitted in an academic 

year would be from the previous year’s 

award cycle. It would be important to 

time the collection of financial aid data 

so that it does not conflict with the 

institution’s aid packaging period, which 

is the busiest time of year for financial 

aid offices. In addition, the treatment of 

summer sessions varies by institution, 

especially regarding whether summer 

sessions would follow or lead the 

submission of an annual data file. 

All of these timing issues would be 

addressed during the design phase of UR 

implementation, should a UR system be 

authorized. In the proposed UR system, 
Executive Summary

xii 

collection schedules would not need to 

be on a uniform schedule, but rather 

could be geared to a schedule that works 

best for individual institutions. In other 

words, institutions with different 

calendars or financial aid packaging 

schedules could submit data to NCES on 

different cycles. 

Conclusions 

As this report has outlined, a central 

question for a UR system is “Could it be 

done?” Have the information 

technologies and infrastructures at the 

campus and state levels matured, could 

the current IPEDS web–based reporting 

system be adapted to a UR system, and 

would there be adequate technical and 

legal protections in place at IES/NCES? 

The report has addressed some of the 

technical and system problems 

associated with the design and 

development of a new IPEDS UR 

system. At the technical level, a UR 

system could be done at most institutions 

given time for implementation. 

The feasibility study also addressed 

the “Should it be done?” question, 

providing a framework for the 

discussion of issues inherent in this 

question. These issues constellate in 

several areas of concern—privacy, 

burden, coordination, technology, and 

timing—which would need to be 

addressed and resolved in the design 

phase of a UR system should 

policymakers decide to authorize and 

fund such a system. 

Finally, the feasibility study outlined 

areas of federal interest: better 

information for informed consumer 

decisions, including the improved 

calculation of net prices; and more 

accurate measures for institutional 

accountability and program 

effectiveness, including enrollment, 

persistence, transfer, and attainment 

rates by program of study. Policymakers 

would be able to monitor in real–time 

federal student aid programs (such as 

Pell Grants) and variations in aid 

packaging. The study also has attempted 

to highlight some potential benefits to 

institutions, researchers, consumers, and 

other users of NCES data. 

The study did not attempt to address 

every challenge or make 

recommendations about how each aspect 

should be addressed. Nor did the study 

document specific organizational 

positions regarding the obstacles a UR 

system might face. Rather, it provided a 

framework for policymakers to 

understand the potential costs and 

benefits of a UR system as they discuss 

whether it should be considered. 

The central defining question of the 

feasibility of a UR system in IPEDS is 

not a “could” question. It is a “should” 

question, asking whether the federal 

government should develop a system 

that is based upon individually 

identifiable information about 

enrollment, financial aid, and attainment. 

This system would, for the first time, 

give policymakers and consumers much 

more accurate and comprehensive 

information about postsecondary 

education in this country. Some of the 

benefits of a UR system include the 

collection of new data that would 

measure the success rates of students at 

institutions to which family and federal 
Executive Summary 

xiii 

student aid monies flow, provide more 

accurate consumer guidance, and 

improve federal programs that support 

those families and students. In addition 

to benefits, the feasibility study found a 

number of significant issues that would 

need to be overcome before a UR system 

could be implemented, including 

objections about student privacy, 

confidentiality of data, new institutional 

burdens, coordination within and outside 

of institutions, and timing issues. 
xiv 

Foreword 

This report examines the feasibility of implementing a student unit record (UR) 

system to replace the student–related components of the Integrated Postsecondary 

Education Data System (IPEDS). These components currently are based on aggregate 

institution–level data collected through IPEDS. The feasibility study was initiated by the 

National Center for Education Statistics (NCES), a part of the Institute for Education 

Sciences (IES) within the U.S. Department of Education, in response to renewed interest 

within the higher education community for improved data. 

The findings in the report are based on several components. Three Technical 

Review Panels (TRPs) were designed to gather feedback and ideas from different 

perspectives related to the study, and included representatives from the following groups: 

1) states, state systems, private systems, and private associations of colleges and 

universities; 2) institutions, particularly institutional researchers and registrars; and 3) 

other stakeholders, including the national postsecondary education association 

community, federal agencies, units within the U.S. Department of Education, and vendors 

such as administrative information system developers. In addition, the experiences and 

architecture of existing UR systems at the state level, other federal agencies, and private 

organizations were compiled. space 
xv 

Acknowledgments 

The authors wish to thank all of those who contributed to this report. We would 

particularly like to thank our colleagues at the Institute for Higher Education Policy and 

at HigherEd.org for their feedback and assistance, including Jamie Merisotis at the 

Institute for Higher Education Policy, and Connie Holohan, Mike Roma, and Andy 

Simpson at HigherEd.org. We would like to thank Michael Lance of Benchmark 

Associates and Tod Massa of the State Council of Higher Education for Virginia. We 

also are grateful for the feedback and support provided by Cathy Statham, Dennis 

Carroll, and Susan Broyles at the National Center for Education Statistics (NCES) 

throughout the project. 

We appreciate the time and effort of the individuals who participated in the three 

Technical Review Panels held as part of this study, as well as the numerous individuals 

who sent personal comments and thoughts about the study. 

We also would like to acknowledge the careful review and thoughtful comments 

provided by the following individuals at various stages of the study: Paula Knepper, Sam 

Barbett, Marilyn Seastrom, and Jan Plotczyk from NCES; David Bergeron and Dan 

Madzelan from the Office of Postsecondary Education; and LeRoy Rooker and Frances 

Moran from the Family Policy Compliance Office (FPCO). 
xvi 

Table of Contents 

 Page 

Executive Summary ....................................................................................................... iii 

Foreword ....................................................................................................................... xiv 

Acknowledgments........................................................................................................... xv 

List of Tables ............................................................................................................... xviii 

List of Figures................................................................................................................ xix 

Chapter 1—Introduction ................................................................................................. 1 

Overview...................................................................................................................... 1 

 Reasons for Feasibility Study..................................................................................... 3 

Background .................................................................................................................. 6 

 Unit Record Systems in Operation............................................................................. 6 

 Current IPEDS Framework...................................................................................... 11 

 Future Data Needs ................................................................................................... 16 

 Context of IES/NCES Operations ............................................................................ 19 

Organization of this Report......................................................................................... 22 

Chapter 2—Proposed Redesign of IPEDS..................................................................... 23 

Brief Description of Unit Record System.................................................................... 23 

 General Architecture................................................................................................ 23 

 Redisclosures........................................................................................................... 26 

 Analysis for OPE..................................................................................................... 27 

 Other Possibilities.................................................................................................... 28 

Alternatives Using IPEDS Aggregate Components..................................................... 29 

Other Alternatives to Unit Records ............................................................................. 30 

Chapter 3—Issues Related to the Development of a Unit Record System ................... 33 

Privacy and Confidentiality ........................................................................................ 34 

Burden........................................................................................................................ 37 

 Initial Implementation ............................................................................................. 38 

 Subsequent Operations ............................................................................................ 39 

Technical Challenges.................................................................................................. 42 

Coordination............................................................................................................... 43 

Timing........................................................................................................................ 44 

Variation Across Institutions ...................................................................................... 47 

Chapter 4—System Architecture................................................................................... 49 

The State Unit Record Collection Model ................................................................... 49 

Assumptions About System Architecture.................................................................... 51 

Collection System....................................................................................................... 52 

Schedule of Data Collection ...................................................................................... 53
Table of Contents 

xvii 

Page 

 File Preparation and Submission.............................................................................. 58 

 Edit Process............................................................................................................. 63

 Movement of Data to Permanent Storage and Aggregates to PAS............................ 64 

 Process of Matching Records................................................................................... 67 

 Issues in the Collection Process ............................................................................... 69 

Redisclosures and Other Data Uses............................................................................. 71 

Training...................................................................................................................... 79 

Help Desk................................................................................................................... 79 

Software..................................................................................................................... 80 

Hardware.................................................................................................................... 80 

Chapter 5—Conclusions ................................................................................................ 83 

References....................................................................................................................... 87 

Appendix A—Technical Review Panels ...................................................................... A-1 

Appendix B— Estimates of Burden............................................................................. B-1 

 

 
xviii 

List of Tables 

Page 

Table 

1 List of proposed variables to be collected in an IPEDS unit record system, by file 

type and IPEDS requirement................................................................................. 54 

2 Schedule of data collection ......................................................................................56 

Appendix B 

B1 Selected comments received from institutions regarding burden associated with 

implementing unit records system, by selected topic .......................................... B-2 
xix 

List of Figures 

Page 

Figure 

1 States with unit record systems ............................................................................... 9 

2 Registration, file preparation and submission, and post–file–lock activity ............. 59 

3 Adjustment of Peer Analysis System for unit record transactions and corrections . 66 

4 Student record match subroutine ........................................................................... 68 

5 Enrollment verification for the National Student Loan Data System...................... 73 

6 Subsequent enrollment disclosure to institutions................................................... 75 

7 Program reports for the Office of Postsecondary Education................................... 77 

8 NCES sample survey files (NPSAS, BPS, and B&B) ........................................... 78 
xx 
1 

Chapter 1—Introduction 

This report examines the feasibility of implementing a student unit record system 

to replace the student–related components that currently are based on aggregate 

institution–level data collected as part of the Integrated Postsecondary Education Data 

System (IPEDS). The feasibility study was initiated by the National Center for Education 

Statistics (NCES), a part of the Institute of Education Sciences (IES) within the 

Department of Education (ED), in response to renewed interest within the higher 

education community for improved data. The feasibility study was conducted between 

October and December 2004. This report describes the findings of the feasibility study. 

Overview 

If a student unit record (UR) system were to be implemented, it would allow the 

collection of high–quality data for student–related information in IPEDS, especially 

related to net prices and graduation rates. By virtue of collecting data at the student level, 

a UR system would lead to more accurate estimates that take into account both 

nationwide trends happening across institutions as well as developments within

institutions. The current IPEDS framework cannot accurately capture changing 

enrollment and completions patterns in the postsecondary education sector, especially 

given increasing numbers of nontraditional students and the mobility of students. It also 

cannot describe the prices various types of students face after financial aid is taken into 

account. In addition to producing the same aggregate estimates that are already collected 

through IPEDS, a UR system would enable a number of additional estimates that would 

capture new dimensions of postsecondary education. These new measures could better 

capture the tracking of students across institutions, unduplicated national headcounts, and 

compute net prices that take into account student characteristics and enrollment patterns. 

In exploring the feasibility of a UR system, this study attempted to investigate 

whether such a system could be constructed technically and effectively, given the 

knowledge about UR systems already in place at the state and institutional levels. In 

addition, the feasibility study tried to explore whether such a system should be developed 
Chapter 1 — Introduction

2 

by the federal government. To do so, the study solicited input from various sources on 

several dimensions of the issue, including privacy and confidentiality, institutional 

burden, coordination, technical issues, and timing. 

Three Technical Review Panels (TRPs) were designed to gather feedback and 

ideas from different perspectives related to the study, and included representatives from 

the following groups: 1) states, state systems, private systems, and private associations of 

colleges and universities; 2) institutions, particularly institutional researchers and 

registrars; and 3) other stakeholders, including the national postsecondary education 

association community, federal agencies, units within the U.S. Department of Education 

(ED), and vendors such as administrative information system developers. (See appendix 

A for agendas and participants.) In addition, the experiences of specific states, private 

organizations, and other entities that have built or maintained existing UR systems were 

compiled. A revision of IPEDS would need to consider the effective practices of already 

existing UR systems and maintain an ongoing dialogue with State Higher Education 

Executive Officers (SHEEOs), systems, and the states. Also as part of the feasibility 

study, the contractor (HigherEd.org, Inc.) developed an architecture and flow of 

operations for a proposed student UR system, as well as a list of potential data elements 

that might be collected under such a system. 

In reading this report, it is important to keep in mind that any redesign of IPEDS 

to develop a UR system would require authorization through the Higher Education Act 

(HEA) and appropriation by Congress. This feasibility study was initiated in order to 

explore whether a UR system could, in fact, be developed, as well as what types of 

challenges existed to the successful implementation of such a system. 

The study did not attempt to address every challenge or make recommendations 

about how each aspect should be addressed, but rather provided a framework for 

policymakers to understand the potential costs and benefits of a UR system as they 

discuss whether it should be considered. 
Chapter 1 — Introduction 

3 

Reasons for Feasibility Study 

The feasibility study, reflecting a renewed interest in a UR system at the federal 

level, is the culmination of several trends in postsecondary education during the 1990s. 

• annual price increases at postsecondary institutions that have exceeded 

increases in inflation indexes such as the Consumer Price Index (CPI); 

• policy concerns about the impact of price increases on consumers and on 

student aid programs; 

• a growing congressional interest in holding institutions accountable for 

outcomes, starting with graduation rates for student athletes and campus 

crime reporting; 

• a demand for better and more timely data to inform policymaking and 

consumer choices; and 

• the desire of many postsecondary institutions for more accurate measures 

of net price and graduation rates, especially measures that take into 

account institutional mission and student mobility. 

Congress has attempted to address these trends in several reauthorizations of the 

Higher Education Act. The 1992 HEA Amendments created a “National Commission on 

College Costs” to study the problem of annual increases in prices at institutions beyond 

increases in the CPI. Such increases in price were an issue both for consumers and for 

Congress, which each year faced increased appropriations for federal student aid 

programs. The commission’s report distinguished between cost and price of attendance, 

recommended more accurate and timely data on costs, prices, and student aid, and looked 

at the relationship of student aid programs to cost increases. The 1992 Amendments also 

included “Student Right–to–Know” legislation, mandating graduation rate information 

for all students. In response, NCES began the Graduation Rates Survey (GRS) 

component of IPEDS collecting data on graduation rates on first–time, full–time students, 

within 150 percent of the nominal time to degree or completion. 

The 1998 HEA amendments instructed NCES to conduct a “Study of College 

Costs,” which included an analysis of whether student aid programs were themselves a 

factor in driving up costs and an analysis of net prices, focusing on the relationship of 
Chapter 1 — Introduction

4 

rising sticker prices and the differential net price paid by students and their families. Net 

prices reflect the prices paid after financial aid is taken into account. Although there is 

substantial debate surrounding the issue of which definition of net price is the best to use 

in examining access or affordability, there is agreement about the fact that it is difficult, if 

not impossible, to measure net prices on an aggregate level. The net price study (Horn et 

al. 2002) showed that prices were flat both for low–income students taking grant aid into 

account and for middle–income students with both grants and loans. 

The 1998 HEA Amendments mandated a redesign of IPEDS, making it a 

significant element in institutional accountability.5

 IPEDS was charged with collecting 

data on institutional prices, changes in prices over a three–year period, and student aid. 

NCES was also tasked with making this consumer information readily available online, 

along with graduation rates. To fulfill this task, NCES created IPEDS College 

Opportunities on Line (COOL), the Department of Education’s provision of information 

on all Title IV institutions. IPEDS itself became a web–based data collection, to insure 

more timely data for policymakers and consumers (see further discussion below). All of 

these changes reflected congressional interest in accountability and having better 

information on college prices and net prices. 

In the context of the current reauthorization of the HEA, price increases, 

particularly in the public sector, led some in Congress to consider an “Affordability 

Index” to reign in price increases. Under the proposal, institutions whose prices had 

increased more than twice the rate of increase in the CPI over a two–year period would 

be required to meet higher standards of accountability. They would have had to report on 

why prices had increased and outline steps to reduce the rate of increase to remain 

eligible for campus–based portions of Title IV of the HEA, where federal student aid 

programs are authorized. Although the Affordability Index proposal has been dropped, 

the interest in outcomes measures such as graduation rates has remained. 

For example, a recent report by the Education Trust (Carey 2004), A Matter of 

Degrees, as well as a congressional oversight hearing, have focused on institutional 

persistence and graduation rates and on the limits of the current IPEDS Graduation Rates 

component in providing accurate information for institutional accountability. In addition, 

 

5

 The mission of and data collected by IPEDS and its predecessor, the Higher Education General 

Information Survey (HEGIS), have shifted over time. See further discussion below. 
Chapter 1 — Introduction 

5 

the postsecondary education community has shown a renewed interest in better 

information on graduation rates, which would include new data on nontraditional students 

who attend part time or otherwise delay their enrollment and have gaps in attendance, as 

well as on students who attend more than one institution, transfer, or coenroll at multiple 

institutions. If Congress were to use graduation rates and time to degree as accountability 

measures for institutions, the consensus is that the GRS in its present form is inadequate. 

Mission–specific measures would take into consideration the goals of the institution, such 

as offering two–year, transfer programs; serving part–time, adult learners; or tailoring 

workforce, noncredit training to the needs of business and industry. Furthermore, the 

current system treats nongraduates as dropouts, when they may have in fact persisted or 

completed their educational program at another institution. 

More accurate data are necessary for more nuanced policy decisionmaking, 

toward the goals of improving student performance and informing students and parents 

about the true costs of college. The American Council of Education (ACE), the 

Association of State Colleges and Universities (AASCU), and the State Higher Education 

Executive Officers (SHEEO) sent letters to congressional leaders, asking that IES/NCES 

conduct a “feasibility study” of a data system, derived from URs, that would provide 

mission–specific data on enrollment patterns of all students and outcome measures such 

as institutional persistence, completion rates, and time to degree, along with detailed 

information on student aid that would make possible accurate calculations of “net price” 

for students. Taking into account individually tailored financial aid packages—including 

the packaging of aid from federal student aid programs—would allow the federal 

government for the first time to assess accurately the relationship of various student aid 

programs to persistence. 

The debate on the feasibility of a UR system at the federal level is occurring 

within the context of the development of other UR systems for students attending 

postsecondary institutions. The following section describes some of these efforts, as well 

as the current IPEDS framework, future data needs, and the context of IES/NCES 

operations related to the protection of individually identifiable data. 
Chapter 1 — Introduction

6 

Background 

Unit Record Systems in Operation 

 It is important to distinguish between the two types of data that are available for 

analysis: (1) summary or aggregate data; and (2) microdata, the raw or unit record (UR) 

data that are summarized or “rolled up” into aggregate data. For example, an aggregate 

report may document the number of bachelor’s degrees awarded by an institution, where 

UR data would document the data that go into the report; in this case, individually 

identifiable information about each degree recipient. A UR system could then document 

students’ demographic, enrollment, attainment, and financial aid information, as 

individually identifiable records if desired. For each type of data collected, schools would 

submit one record per student per term per institutional identifier. 

 For many years, colleges and universities have maintained computerized 

recordkeeping through the use of administrative information systems. Typically, 

specialized admissions software is used to monitor student applications and acceptances, 

in addition to human resources software for hiring and paying employees and registrar 

software to keep track of course enrollments, grades, and awards/degrees. In order to 

submit URs to a federal, state, or other data collection, schools must create electronic 

extracts or snapshots of their recordkeeping data from these different administrative 

information systems. These extracts are created using special software tools and can 

include whatever variables are desired. Extracts represent the selected data and records as 

of a specific point in time when the files are cut. 

 In order to complete aggregate summaries in reporting to governing boards, state 

agencies, or other entities, institutions have two basic choices: (1) run a computer 

program (or query) against the live, administrative information system to produce a 

summary report; or (2) create an extract of the data needed and use these records to 

produce a summary report locally. For both choices, schools must then engage in a 

significant amount of review and clean up of data to ensure that they can be aggregated 

accurately to reflect the institution at the point in time (or census date). 

 In cases in which institutions must submit UR data directly rather than in 

summary reports, schools have two choices about the initial cleanliness of their file 

submissions. They may either (1) submit the raw data they obtain from their 

administrative information systems (which are called transaction files because they 
Chapter 1 — Introduction 

7 

represent ongoing transactions or interactions with the live database); or (2) submit files 

on which they have conducted further editing (in which case they are called analytical 

files because they have been scrutinized from an analytical perspective). The different 

approaches are important to recognize because, if submitted, transaction files may be 

missing some data or include unexpected values, such as invalid Classification of 

Instructional Programs (CIP) codes. The resulting summary report may be different than 

expected for the institution as a whole. However, increased work is necessary to create 

analytical files, resulting in greater burden on institutions. 

The distinction between aggregate and UR data is important because there are 

inherent limitations to using aggregate data, just as there are issues of data integrity for 

transaction versus analytical files. Aggregate data collected at one level of analysis 

cannot be used for lower levels of analysis, such as how the data differ among various 

groups of students or how students move between institutions (unless this is specifically 

included at both levels). With aggregate data, it is difficult (if not impossible) to examine 

relationships among variables or to recompile data for different reporting needs (National 

Postsecondary Education Cooperative 1998). 

Many governmental and other organizations maintain UR systems on specific 

groups of students. For example, in the Department of Education, NCES conducts sample 

surveys of postsecondary students (such as the National Postsecondary Student Aid 

Study, [NPSAS]) in which it collects UR information from the institution for each student 

in the sample. The National Student Loan Data System (NSLDS) within the office of 

Federal Student Aid (FSA) compiles information on all recipients of federal student 

loans, including verification of enrollment by term. FSA also has detailed data on all 

federally aided students, which represent more than half of full–time undergraduates. The 

Office of Postsecondary Education (OPE) collects student–level information on the 

recipients of specific program funds, such as GEAR UP, Upward Bound, and Talent 

Search, for program evaluation. 

Other branches of the federal government also collect student information. For 

example, the National Science Foundation (NSF) conducts its Survey of Earned 

Doctorates annually from all individuals receiving research doctoral degrees from U.S. 

institutions. The Internal Revenue Service (IRS) requires colleges and universities to 

annually submit individually identifiable student data on tuition and related expenses and 
Chapter 1 — Introduction

8 

scholarships/grants, for all enrolled students, in case they or their parents claim a Hope or 

Lifetime Learning tax credit. This same information also is used to send 1098–T forms to 

students for use in preparation of their tax forms. More recently, the Department of 

Homeland Security (DHS) has created the Student and Exchange Visitor Information 

System (SEVIS) in order to maintain information on nonimmigrant students and 

exchange visitors from the time they receive their visa documents until they complete 

their programs. Under SEVIS, colleges are required to provide regular electronic reports 

confirming enrollment in postsecondary institutions to the DHS. 

State and local governments, which are the primary funding sources for public 

colleges and universities, have tied this funding to requirements for collecting increasing 

amounts of data on students attending institutions in their states. A growing number of 

states began to develop UR systems in the mid–1980s, and some states have 30–year 

histories of using UR systems for analysis and program evaluation. In fact, according to a 

recent study (Ewell et al. 2003), 39 states have at least one student UR system; some 

states have more than one, because separate UR systems are maintained for state 

colleges, community colleges, and other system structures. Most of these states collect 

data only on students attending public institutions. However, 12 state UR systems include 

data on students attending at least some private institutions, and the number is growing 

(figure 1). Most of these state–level UR databases are maintained by state higher 

education agencies and multicampus postsecondary education systems. In many cases, 

state UR databases provide extensive support for institutional IPEDS reporting and, in the 

long run, reduce the reporting burden to individual institutions. 

A limitation of state UR systems is that most do not include students attending 

private institutions, or students who leave and cross state lines. In recent years, there has 

been substantial interest in the possibility of linking state UR systems to try to minimize 

these coverage issues. Ewell et al. (2003) noted that in order for existing data in state–

level UR databases to be used to track students on a national basis, they must cover a 

substantial proportion of the nation’s enrollment, the systems must contain roughly 

similar data elements (with similar definitions), and a method must exist to link them 

consistently. The study found that state–level UR databases consistently track 

information on enrollment, degree attainment, program, gender, race/ethnicity, and date 

of birth, and 
Chapter 1 — Introduction 

9 

Figure 1. States with unit record systems 

cover about 73 percent of national headcount enrollment. In addition, definitions and 

structures are compatible enough to allow linkages among databases. Few of these 

systems include information on financial aid. The National Center for Higher Education 

Management Systems (NCHEMS) is currently conducting a follow–up pilot program, 

funded by the Lumina Foundation, to test the feasibility of voluntary, interstate data 

sharing that would link 10 state UR databases. 

Another experimental study is being funded by the Lumina Foundation to collect 

UR data from a number of community colleges (JBL Associates 2004). Thirty 

community colleges are submitting data each term for six student cohorts. Data include 

student contact information, demographics, transfer credits, current courses, credits, 

grade point average, student aid, and information on college intervention programs. 

Lumina and the American Association of Community Colleges (AACC) plan to create a 

database linking the data together longitudinally and create reports for each participating 

SOURCE: Ewell, P., Schild, P.R., and Paulson, K. (2003). Following the Mobile Student: Can We 

Develop the Capacity for a Comprehensive Database to Assess Student Progression? New

Agenda Series. Bloomington, IN: Lumina Foundation for Education. 
Chapter 1 — Introduction

10 

college.6 A similar exchange of UR data by community colleges is being done by Jeffrey 

Seybert at Johnson County Community College with the League for Innovation in the 

Community College, as part of the Community College Benchmarking Project. Statewide 

associations of private colleges and universities in Minnesota and Tennessee have 

initiated their own collections of UR data recently. 

Private organizations also are involved in collecting student–level data. The 

National Collegiate Athletic Association (NCAA) is experimenting with the use of UR 

data for student athletes from its member colleges and universities.7 NCAA collects UR 

data on 1,800 institutions with Division I, II, or III varsity athletic programs, due in large 

part to the limits of the current GRS. In addition, many colleges and universities 

participate in the National Student Clearinghouse, which performs enrollment verification 

and other services for them using student UR data. The clearinghouse, a nonprofit 

organization begun in 1993 to facilitate the student record verification process, asks 

participating colleges to periodically provide them with student UR data electronically. 

The clearinghouse then provides guaranty agencies and FSA with status and deferment 

information on student financial aid recipients on behalf of those institutions. The 

clearinghouse currently is used by about 2,800 colleges and universities (out of the 6,700 

Title IV institutions in IPEDS). Many institutions also pay the clearinghouse for 

information about students’ enrollment and attainment after they leave the requesting 

institutions. 

The National Postsecondary Education Cooperative (NPEC) has conducted 

several studies of UR systems, including the final report of its Working Group on Unit 

Record Data Versus Aggregate Data (National Postsecondary Education Cooperative 

1998), which compared aggregate and UR approaches to data collection. In 2001, another 

working group examined student transition data systems, including exchange of records 

across postsecondary institutions (National Postsecondary Education Cooperative 2001). 

Work on K–16 UR systems was analyzed as part of a recent publication by the State 

Higher Education Executive Officers (Voorhees and Barnes 2003), which reported that 

exemplary state data and accountability systems help establish standards, track the 

 

6

 With the assistance of JBL Associates. 

7

 NCAA used the IPEDS Graduation Rates Survey figures for its annual collection of graduation rate data 

between 1998 and 2003. See the NCAA website for more information: http://www2.ncaa.org/. 
Chapter 1 — Introduction 

11 

performance of individuals throughout their educational careers, and increase 

stakeholders’ commitment to gathering and using data on student performance. 

It is important for NCES to utilize the extensive experience of the states and 

others, as well as the known benefits of UR systems, to improve upon its data collection 

capacity, as part of its ongoing process to improve the analytic capability of IPEDS. 

Current IPEDS Framework 

NCES has been charged by Congress to report on the condition of postsecondary 

education in the United States, including changes in its size, participants, providers, and 

other characteristics. To do this, NCES established the IPEDS as its core postsecondary 

education data collection program in 1986.8

 Prior to IPEDS some of the same information 

was collected by the Higher Education General Information Survey (HEGIS). Between 

1966 and 1985, HEGIS collected information from higher education institutions that 

offered courses creditable toward a bachelor’s degree. IPEDS is a single, comprehensive 

system that encompasses over 10,000 institutions whose primary purpose is to provide 

postsecondary education, thereby expanding the universe of institutions. IPEDS includes 

about 6,700 institutions that have Program Participation Agreements with ED for Title IV 

federal student financial aid programs, for which reporting is mandatory. 

The IPEDS system is built around a series of interrelated components that collect 

institution–level data in the areas of enrollment, program completions, graduation rates, 

faculty, staff, finances, institutional prices, and student financial aid. For example, 

researchers can use IPEDS to analyze information on enrollments of first–time freshmen 

by race/ethnicity and gender; institutional revenue patterns by source of income; degrees 

and certificates awarded by type of program, level of award, and race/ethnicity and 

gender of recipient; and the characteristics of postsecondary institutions, including 

tuition, room and board charges, calendar system, accreditation, and price of attendance. 

Racial and ethnic data collected through IPEDS are used as part of each postsecondary 

institution’s Compliance Report for the Office of Civil Rights (OCR). 

 

8

 Most of the description of IPEDS was taken from U.S. Department of Education, National Center for 

Education Statistics 2004. More detail can be found at the IPEDS homepage: 

http://nces.ed.gov/ipeds/AboutIPEDS.asp. 
Chapter 1 — Introduction

12 

The IPEDS survey data collection occurs at three points during the year (fall, 

winter, and spring), involving multiple web–based components. Several of these 

components are student related, in that they request information from the institutions 

about the activities or characteristics of their students. These student–related components 

include the following: 

• Enrollment (EF). This component collects data annually on the number of 

full– and part–time students enrolled in the fall in postsecondary 

institutions in the United States and the other jurisdictions by level 

(undergraduate, graduate, first–professional) and by race/ethnicity and 

gender of student. The component has requested the total number of 

undergraduates in the entering class (including first–time, transfer, and 

nondegree students) since 2001, to form the basis of the Graduation Rates 

data. Institutions began reporting first–year retention rates for 

undergraduate students by attendance status in fall 2003. Racial/ethnic 

data are collected for the OCR as part of the institution’s Compliance 

Report. Age distributions are collected in odd–numbered years by student 

level. Data on state of residence of first–time freshmen (first–time, first–

year students) and the number that graduated from high school in the past 

12 months are collected in even–numbered years. Four–year institutions 

are also required in even–numbered years to provide fall enrollment data 

by level, race/ethnicity, and gender for nine selected fields of study—

Education; Engineering; Law; Biological and Biomedical Sciences; 

Mathematics; Physical Sciences; Dentistry; Medicine; and Business 

Management, Marketing and Related Support Services. Finally, the 

enrollment component collects the 12–month unduplicated headcount and 

instructional activity data, which are needed to compute a standardized 

full–time–equivalent (FTE) enrollment statistic. 

• Completions (C). This component collects data annually on recognized 

degree completions in postsecondary education programs by level 

(associate’s, bachelor’s, master’s, doctor’s, and first–professional) and on 

other formal awards by length of program. These data are collected by 

race/ethnicity and gender of recipient and by field of study, which is 
Chapter 1 — Introduction 

13 

identified by six–digit Classification of Instructional Programs (CIP) 

codes (National Center for Education Statistics 2002b). Completions data 

on multiple majors are collected by CIP code, award level, race/ethnicity, 

and gender from those schools that award degrees with multiple majors. 

Racial/ethnic data on completers are collected in odd–numbered years for 

the OCR as part of their biennial Compliance Report. 

• Student Financial Aid (SFA). This component collects the number of full–

time, first–time, degree/certificate–seeking students receiving aid 

compared to the total number of full–time, first–time students, as well as 

the number of students receiving each type of financial assistance and the 

average amount received by type. The types of aid included are federal 

grants, state and local government grants, institutional grants, and loans 

from any source. 

• Graduation Rates (GRS). The Student Right–to–Know Act of 1990 (SRK) 

requires Title IV institutions to disclose information about graduation or 

completion rates to current and prospective students. This component 

collects data on the number of students entering the institution as full–

time, first–time, degree/certificate–seeking students in a particular year 

(cohort), by race/ethnicity and gender; and the number completing their 

programs within 150 percent of nominal time to completion. In the GRS, 

if an institution has a transfer mission, transfer–out students in the cohort 

should be reported, if the transfers to other Title IV eligible institutions are 

known to the original institution.9

 The GRS also collects data on the 

number of students receiving athletically–related student aid in the cohort, 

and the number of these students completing within 150 percent of 

nominal time to completion. 

• Prices section of Institutional Characteristics (IC). The core of the IPEDS 

system is the annual Institutional Characteristics component, which acts as 

the control file for the entire IPEDS system and constitutes the sampling 

frame for all other NCES surveys of postsecondary institutions. This 

 

9

 For these institutions, known transfer students are considered completions. 
Chapter 1 — Introduction

14 

component collects the basic institutional data that are necessary to sort 

and analyze not only the IC database, but also all other IPEDS databases. 

One section of the IC component collects information on tuition and 

required fees, room and board charges, books and supplies and other 

expenses charged to various types of students. 

There are also IPEDS components collecting information on institutional 

revenues and expenditures (Finance) as well as faculty and other staff (Salaries, Fall 

Staff, and Employees by Assigned Position). 

IPEDS data collection is conducted using a web–based data collection system. 

Each postsecondary institution designates a keyholder, who is responsible for ensuring 

that data for the institution are submitted as well as editing and “locking” the data.10

Many states or systems also have one or more coordinators who are responsible for 

reviewing the data for a specific group of institutions and applying subsequent locks.11

Together, keyholders and coordinators are referred to as the IPEDS coordination tree. 

The process of IPEDS data collection requires a number of steps. Keyholders first 

enter data through online data entry screens for each IPEDS component, which are 

tailored to each institution based on characteristics such as degree–granting status, 

control, and length of longest program offered. In many cases, data from previous years 

are preloaded on the customized screens for easy reference and comparison purposes. 

Once the current–year data are entered, the keyholders are required to run edit checks and 

resolve all errors before locking their data.12 Once data are locked, they are considered 

“submitted” and IPEDS Help Desk staff conduct a final review. If any additional 

problems are detected, the Help Desk staff contact the institutions to resolve any 

remaining questions. Once data are reviewed and problems resolved, the data are moved 

from the data collection system to the Peer Analysis System (PAS), which is available on 

the IPEDS website.13 At the collection level of the PAS, estimates are available to the 

 

10 Locking occurs when a keyholder has decided that the data are ready to submit to IPEDS; once locked, 

the data become read–only and the keyholder no longer can make changes. 

11 Coordinators may provide different levels of review. For example, some may only view data provided 

by their institutions, while others may upload, review, and lock data. 

12 Edit checks are built into the web–based instrument to detect major reporting errors. The system 

automatically generates percentages and totals on each collection component. Edit checks compare current 

responses to previously reported data and look for consistency within and between components. As edit 

checks are executed, survey respondents are allowed to correct any errors detected by the system. 

13 See: http://nces.ed.gov/ipedspas/. 
Chapter 1 — Introduction 

15 

keyholder; once the estimates are moved to institutional level, they become available to 

other responding institutions for comparison purposes. After the data have been 

adjudicated, estimates are moved to the guest level of the PAS, where they are publicly 

available; these are the “official” estimates. 

Creation of the PAS was prompted by the 1998 HEA Reauthorization, which 

directed the Commissioner of Education Statistics to provide students and families with 

better information about college costs and prices. In response, the NCES Task Force for 

IPEDS Redesign recommended the move from paper forms to the web–based collection 

system (Peng et al. 1999). The task force also recommended the development of a peer 

analysis system, the provision of help desk support for responding institutions, and 

specific changes in data content, such as collection of information on financial aid and 

total price of attendance for first time, full–time degree/certificate–seeking 

undergraduates. These changes, as well as the suggestion to adopt a process of 

continuous improvement for the IPEDS system, added accountability and the provisions 

of information to students and families to the mission of IPEDS. 

Other recommendations of the task force were adopted and implemented in 

subsequent years. NCES developed a searchable website, College Opportunities On–Line 

(COOL), to provide up–to–date statistics on a broad range of postsecondary institutions 

for easy access by consumers. The site presents general information about the institution 

and its mission, as well as data on institution prices, financial aid, enrollment, degrees 

and awards conferred, accreditation, and types of programs that are offered by the 

institution. COOL is designed to help college students, future students, and their parents 

understand the differences among colleges and how much it costs to attend college. The 

site also provides links to each institution’s website, campus crime statistics, and other 

postsecondary education websites.14 In early 2004, graduation rates were added to 

COOL, despite the fact that many colleges perceived them to be an inadequate measure 

of student outcomes. 

The IPEDS Data Analysis System (DAS) was recently released by NCES. This 

online tool allows users to dynamically generate summary tables for one year of IPEDS 

data. These summary tables provide sums, counts, and percentage estimates. The DAS 

 

14 The site is available at http://nces.ed.gov/ipeds/cool/.
Chapter 1 — Introduction

16 

allows users to select and regroup categorical variables to produce estimates and to 

identify ranges of values to form subgroups and estimates. 

Complementing these tools is an ongoing process of revision and improvement to 

the IPEDS collection system, as well as the variables that are calculated for the PAS. To 

effect change within the IPEDS framework, Technical Review Panels (TRPs) are held on 

a specific topic to solicit input from postsecondary institutions, associations, researchers, 

and other stakeholders. The findings of the TRP are summarized and then posted to the 

NCES website for public comment. 

Future Data Needs 

Despite the comprehensiveness of the IPEDS system, there are several important 

items that cannot be calculated accurately from the current data, including net prices, 

graduation rate measures, and other such variables. The current IPEDS framework uses 

institution–level aggregates for purposes that would be better served by student–level, 

longitudinal data collection. These techniques are already being employed by other 

government and nongovernment organizations to look at student behavior using a secure 

data collection mechanism. A federal UR system could make several improvements to 

the data available from IPEDS. 

The calculation of accurate net prices has become more important as published 

tuition and fees (“sticker” prices) have become increasingly unrelated to the price 

students actually pay to attend college (Horn et al. 2002; Cunningham and Merisotis 

forthcoming). Currently, sample surveys such as NPSAS can investigate net prices with 

many different definitions (Horn et al. 2002). Other studies have attempted to measure 

net price on an aggregate level (College Board 2004; Cunningham and Merisotis 

forthcoming), but aggregate figures mask the wide variation in net prices paid by students 

with varying characteristics at different types of institutions. Although a UR system 

would focus on students already enrolled in colleges, it would improve the calculation of 

net prices for different types of students annually from a dataset that includes information 

on all types of financial aid. This would allow the federal government, among others, to 

more accurately measure the relationship of student aid programs to persistence and other 

outcome indicators. 
Chapter 1 — Introduction 

17 

The calculation of outcome measures such as graduation rates, persistence, time 

to degree, and rates of transfer has also become increasingly important, and suffers from 

similar problems with data collection. As mentioned above, the current IPEDS 

framework includes a Graduation Rates component that requests graduation rate data for 

a specific cohort of students—full–time, first–time, degree/certificate–seeking 

undergraduates enrolled in a specific year.15 Student data are reported by gender and 

race/ethnicity, and are separated between those entering bachelor’s degree programs and 

other programs. Institutions then report the number of students in the cohort who 

complete a degree/certificate within 150 percent of the nominal time to award (for 

bachelor’s degrees, this is usually within six years)16 These graduation rates are 

calculated so as to comply with the Student Right to Know Act. 

The graduation rates calculated from these data allow researchers to make 

comparisons between institutions, and within institutions, with regard to gender and 

race/ethnicity. However, these measures are primarily rates of institutional retention, and 

largely do not capture what happens to students who leave an institution and may go on 

to attend another institution and attain a degree. The existing GRS report only counts 

student completers and transfers in a very narrow fashion. It does not include accurate 

information about students who stop out, drop out, graduate at a later date, or transfer out 

unbeknownst to the school. These more complex persistence and attainment data can 

only be documented with a UR–type system that looks longitudinally across schools to 

analyze all possible enrollment behavior. GRS graduation rates also measure the 

educational path of the minority of students who are traditional full–time, degree–seeking 

students. Yet research has shown that 73 percent of postsecondary students are 

nontraditional, with characteristics such as part–time attendance and delayed enrollment 

(Choy 2002). In addition, 40 percent of students now enroll in more than one institution 

at some point during their progress through postsecondary education, including transfer 

to other institutions as well as coenrollment (Berkner et al. 2002). These nontraditional 

paths—along with the increasing price of college—may have encouraged students to 

 

15 Institutions that predominantly use standard academic terms use a fall cohort, whereas other institutions 

use a full–year cohort. 

16 Two–year institutions may count as graduates those students who complete the “equivalent of an 

associate’s degree” (i.e., students who complete, within three years, a two–year transfer preparatory 

program that is acceptable for full credit toward a bachelor’s degree and that qualifies a student for 

admission into the third year of a bachelor’s degree program) (Association for Institutional Research 2000). 
Chapter 1 — Introduction

18 

work while attending college and may have contributed to longer times to degree. These 

issues are especially relevant for colleges that serve large proportions of nontraditional 

students, such as public 2–year institutions. Therefore, the current IPEDS framework 

cannot measure all of the aspects of postsecondary education persistence, attainment, and 

transfer that are necessary for sound policy decisions. To do so, it would be necessary to 

collect accurate student–level information on persistence systemwide (i.e., regardless of 

institution, nationwide), multiple enrollment, part–time enrollment, transfer, and 

attainment, on an annual basis.17 

Additional information on net price, graduation rates, transfer rates, time to 

degree, and enrollment by discipline would provide consumers, policymakers, and others 

with more complete information on which to base decisions. By its very nature, a UR 

system would enable the collection of data that would lead to more accurate estimates of 

variables currently in the PAS, such as fall enrollment and institutional graduation rates. 

Like any data collection instrument, a new UR system would have to recognize some 

degree of error in measurement; however, a UR system would be expected to produce 

estimates superior to the ones created under the current IPEDS framework, which, for 

example, do not capture student transfer in the calculation of graduation rates. Perhaps 

more important, a UR system would allow the development of a whole range of new 

measures that could be added to the PAS, such as net prices for specific groups of 

students, graduation rates that take into account institutional missions, persistence rates 

that consider student mobility and a systemwide perspective, measures of enrollment 

patterns for nontraditional students, time to degree by field of study, and other critical 

data. A variety of factors impact net prices and graduation rates, many of which would 

not be collected by the proposed UR system. However, the level of detail collected 

through a UR system would greatly improve understanding of the issues. 

There are several other important improvements that would be made by a national 

UR system. For example, the UR system would expand upon the current Enrollment 

component to allow unduplicated 12–month enrollment calculations and measures of 

enrollment by field of study, while continuing to comply with Office for Civil Rights 

requirements. The current Enrollment component of IPEDS double counts students who 

 

17 Note that a change in the required calculation of graduation rates would require a change in the Student 

Right–to–Know legislation. 
Chapter 1 — Introduction 

19 

are coenrolled, and does not provide enrollment counts for all programs (enrollment is 

requested in a limited number of programs in even–numbered years). Better estimates of 

full–time–equivalent enrollment (FTE) would also be possible. A national UR system 

would expand upon the current Completions component by enabling the measurement of 

time to degree for each field of study. It also would facilitate the calculation of 

completions for students who attained awards at more than one institution, or attended 

institutions in more than one sector. 

Context of IES/NCES Operations 

The creation of a national UR system would involve the collection of individually 

identifiable student data on a scale that has not yet been accomplished. IES and NCES are 

required by law to protect the confidentiality of these individual respondents. The 

collection, reporting, and publication of data based on student records are overseen by the 

Family Educational Rights and Privacy Act (FERPA). FERPA was enacted in 1974 and 

is administered by the Family Policy Compliance Office (FPCO) of the U.S. Department 

of Education (ED). FERPA requires the protection of student records by educational 

institutions that receive funds from ED, and prohibits the disclosure of individually 

identifiable information from educational records without students’ consent (or their 

parents or guardians). There are exceptions in specific circumstances, including the 

disclosure of directory information,18 disclosure to school officials with legitimate 

educational interests, and disclosure to organizations conducting studies on behalf of 

educational agencies or institutions.19 In addition, FERPA law was amended by the U.S. 

Patriot Act of 2001, so that any data protected by FERPA are available to the Attorney 

General for the purpose of investigating or prosecuting acts of terrorism. 

In addition, IES and NCES operate under a number of other laws and regulations 

governing the confidentiality and security of individually identifiable data. The Privacy 

Act of 1974, as amended, requires federal agencies to collect, maintain, use, or 

 

18 Directory information includes information that would not be considered harmful if it were released, 

such as name, address, telephone number, date of birth, field of study, and degrees awarded (Pfeiffer 2003). 

Also see http://www.ed.gov/policy/gen/guid/fpco/ferpa/index.html. 19 Under the proposed UR system, the original submission of student records by schools to NCES would 

be considered disclosures allowable under FERPA. Redisclosures refer to cases in which UR data that have 

been submitted to the UR system are sent, or “redisclosed,” to the original institution or to another party. 

See chapters 2 and 4 for a more complete explanation.
Chapter 1 — Introduction

20 

disseminate any record of identifiable personal information only for necessary and lawful 

purposes and with adequate safeguards to prevent the misuse of data. A federal agency 

cannot disclose individually identifiable information without the prior written consent of 

the individual, although there are exceptions. The Federal Statistical Confidentiality 

Order of 1997, an order by the Office of Management and Budget (OMB), defines 

relevant terms and provides guidance on the content of confidentiality pledges that 

federal statistical programs should use under two different conditions—when the data 

may only be used for statistical purposes, and when the data are collected for statistical 

purposes but the agency is compelled by law to disclose the data. The second condition is 

relevant under the Patriot Act, which permits the Attorney General to petition a court of 

competent jurisdiction for an ex parte order requiring the Secretary of the Department of 

Education to provide data relevant to an authorized investigation or prosecution of an 

offense concerning national or international terrorism.20 

NCES has had strong confidentiality laws since 1988, where disclosure or 

publication of individually identifiable information is a Class E felony. The Patriot Act 

amended the National Education Statistical Act of 1994, which was adopted and 

amended in the creation of the National Education Sciences Act of 2002. Under the 

Education Sciences Reform Act of 2002 (ESRA 2002), all individually identifiable 

information about students, their families, and their schools shall remain confidential. 

This law requires that no person may use any individually identifiable information for 

any purpose other than the statistical purposes for which it is supplied. In addition, the 

law prohibits publications where the data provided by a particular person could be 

identified, and forbids anyone other than the individuals authorized by the Director of the 

Institution of Education Sciences to examine the individual reports. Employees or other 

individuals who knowingly disclose or publish any individually identifiable information 

are subject to fines of up to $250,000, or up to 5 years in prison, or both. Similarly, the 

E–Government Act of 2002, Title V, Subtitle A, Confidential Information Protection 

(CIP 2002) declares that all individually identifiable information supplied by individuals 

or institutions to a federal agency for statistical purposes must be kept confidential and 

may only be used for statistical purposes; any willful disclosure of the data for 

 

20 This law was incorporated into Education Sciences Reform Act 2002.
Chapter 1 — Introduction 

21 

nonstatistical purposes, without the informed consent of the respondent, is a Class E 

felony. 

As a result of these laws, individually identifiable data must be held confidential 

unless the individual provides written consent, except for specific exceptions (e.g., the 

release of directory information under FERPA, the use of information for statistical 

purposes, and the authorized investigation and prosecution of terrorism). To assist 

IES/NCES staff and data users in meeting the requirements to protect these confidential 

data, IES/NCES has established statistical standards that govern the handling and use of 

confidential data (National Center for Education Statistics 2002).21 For example, all 

IES/NCES staff and relevant contractors are required to pledge (and sign notarized 

affidavits) not to release any individually identifiable data for any purpose, to any person 

not sworn to the preservation of confidentiality. All materials with individually 

identifiable data must be kept secure at all times through the use of passwords and secure 

data handling and storage. In order to prevent the publication of individually identifiable 

data, NCES uses techniques such as range restrictions, collapsing of categories, data 

swapping, and other methods of data perturbation. Qualified external researchers who 

desire access to data files with individually identifiable information must pass through a 

formal application process for a restricted data license, and must follow similar security 

procedures as mentioned for IES/NCES staff and contractors, subject to unannounced 

inspections. The only UR data file that would be made available to licensed researchers is 

the one used to create the NPSAS sample. The complete UR data would not be available 

to licensed researchers. 

NCES has over three decades of experience with individually identifiable data 

files, including the National Postsecondary Study Aid Study and other sample surveys. 

These files have undergone disclosure avoidance procedures prior to release, and 

restricted use licenses have been granted to qualified researchers. To date, IES/NCES has 

experienced no known disclosures of the confidential data entrusted to IES/NCES by the 

many respondents to IES/NCES data collections. 

 

21 NCES recognizes that the use of UR records for FSA enrollment verification is a nonstatistical purpose 

and therefore is not protected by CIPSEA. However, the rest of the UR data uses are protected in this 

manner. 
Chapter 1 — Introduction

22 

Organization of this Report

The remaining sections of this report describe various aspects of a proposed UR 

system. The following chapter provides a brief depiction of what a UR system might look 

like, including the potential redisclosures that might be allowed under such a system as 

well as some proposed alternatives to a UR system. Next, chapter 3 presents a number of 

potential challenges to a national UR system, including privacy and confidentiality 

issues, increased burden to postsecondary institutions, technical problems that might be 

faced, coordination issues, and possible problems with the timing of data collection. 

Chapter 4 describes a potential architecture for a UR system, including the collection 

system, the permanent UR storage database, migration of data to the Peer Analysis 

System (PAS), redisclosures, training, the IPEDS Help Desk, software, and hardware. 

The final chapter summarizes the findings of the feasibility study. 

Several appendixes also are included with this report. Appendix A provides the 

agendas and lists of participants from all three Technical Review Panels. Appendix B 

offers some rough estimates of the potential burden of implementing a UR system. 
23 

Chapter 2—Proposed Redesign of IPEDS

The UR system, as proposed, would replace the student–related components in 

the current IPEDS collection—Fall Enrollment, Completions, Prices, Student Financial 

Aid, Graduate Rates, and the price of attendance component. The UR system would be 

designed to include all of the variables necessary to replace those components and 

calculate institutional–level estimates for the IPEDS Peer Analysis System and other 

required reporting. At the same time, the collection process for nonstudent–related 

components in IPEDS (Institutional Characteristics, Finance, Fall Staff, Salaries, and 

Employees by Assigned Position) would remain the same. 

It is difficult to describe exactly what the UR system would look like before the 

design process is undertaken. In general, however, UR collection may be described as a 

process involving the upload of individual student records to NCES by the IPEDS 

keyholder22 at each institution. The following presents a broad overview of the proposed 

UR system; Chapter 4 describes the system architecture and collection process in more 

detail. Note that the proposed UR system outlined here and in Chapter 4 is presented to 

provide a picture of what a UR system could look like, if authorized, and to help the 

reader understand the challenges to the implementation of such a system as well as 

potential solutions. If a UR system were authorized and funded, various aspects of the 

proposed system could change in the design and implementation phase23. 

Brief Description of Unit Record System 

General Architecture 

 The heart of the proposed UR system involves the collection of individually 

identifiable records about students based on their enrollment, price paid, financial aid, 

and attainment at different points in time. When combined for all students and all 

 

22 The IPEDS keyholder is the person at each institution (or coordinating body) who is responsible for 

compiling data for IPEDS, submitted the data to NCES, and locking the data. 

23 If a UR system were implemented, TRPs would be held to advise on various aspects of the design of the 

system. These TRPs would include input from financial aid officers, institutional researchers, registrars, IT 

staff, and other institutional staff representatives. 
Chapter 2 — Proposed Redesign of IPEDS 

24 

schools, the UR database would allow NCES to complete its IPEDS enrollment, financial 

aid, completions, and price survey components for each institution’s data in the PAS and 

on COOL. In order to collect all of these data, different collection schedules would be 

required with separate file submissions. Details on the proposed collection schedule are 

included in Chapter 4. The working list of variables includes the following: 

• Student identifiers and demographic information: These data provide 

individually identifiable information such as name, Social Security 

Number (SSN) or Individual Taxpayer Identification Number (ITIN), date 

of birth, address, race/ethnicity, and gender that are attached to an 

individual student’s record. Many of these variables allow records to be 

matched with one another to follow a student over time, or to follow a 

student that attends more than one institution. A header file containing 

these variables would be submitted for each student enrolled at each 

institution. 

• Enrollment variables: These data include program information such as 

number of courses and credits attempted, major field of study, start and 

end dates, and attendance status. These data would be required three to 

four times a year (in other words, once per term), while institutions that do 

not use a term system would be allowed to upload files more frequently if 

they wished. The use of multiple files is tied to the FSA enrollment 

verification process and allows for the more accurate calculation of full–

year enrollment. Institutions would identify the type of calendar system 

they use and the way they measure course activity in the Institutional 

Characteristics component during the fall collection schedule. 

• Attainment variables: These data include information on degree 

completions and the date of completion. The file would need to be 

uploaded at least once per year. 

• Financial aid variables: These data include information on students’ 

annual receipt of financial aid from federal, state, and institutional sources 

(i.e., financial aid passing through the institution’s financial aid office). 

These data also would need to be uploaded at least once a year. 
Chapter 2 — Proposed Redesign of IPEDS 

25 

• Price of attendance variables: Information on annual price of attendance 

would be uploaded with the financial aid file. 

In addition, a one–time only collection of historical information on GRS cohorts 

would be required in order to complete the calculations for the GRS. Data would be 

needed for the established GRS cohorts, including basic enrollment and attainment 

information. The full student records for each cohort would not be necessary, such as 

field of study codes and financial aid. 

For each submission of data, the keyholder at an institution or coordinating 

agency would upload a data file using XML,24 although ASCII would likely be accepted 

in the initial years of implementation.25 The data would be submitted through the IPEDS 

collection system, similar to the process that exists currently. At NCES, the data would 

go through internal and external edit checks, and mismatches would be identified and 

sent back to the keyholder for review and resolution. For example, if a student changes 

her name, the record may show up as a mismatch because all other aspects of the 

previous header file are the same, but the name differs. Other mismatches might include 

misspelled names, students identified as first–time students who appear to match records 

of previously enrolled students, and keystroke errors. When edit failures are resolved or 

signed off by the keyholder, aggregate reports would be available onscreen to the 

keyholder to view and correct as needed (see the Chapter 4 for a full description of this 

process). Once the data are satisfactory and pass all edit checks, they would be locked by 

the keyholder (and other members of the IPEDS coordination tree, if applicable). The 

data would then be moved from the collection system to the permanent database storage 

system. The full database would only exist in this permanent storage area, which would 

not be accessible via the Internet and would be subject to NCES’ high levels of protection 

for confidentiality and security. The aggregate estimates that are calculated from the full 

UR database would be moved to the Peer Analysis System, where they would be stored 

and available as institution–level data. 

 

24 XML is a “markup language,” or mechanism for identifying structures within a document or data file. It 

employs tags to identify data elements, thereby facilitating the seamless exchange of data. In other words, it 

allows users to describe data and deliver it across a network, through the creation of common records 

across disparate databases. 

25 Beginning is 2005–06, FSA will require that all Title IV institutions transmit FSA–required data using 

XML tags. Some institutions have already begun the process of converting to XML tags. An Excel 

spreadsheet would be provided for institutions that are not capable of cutting extract files; this would 

include a feature that lets the user automatically export the spreadsheet data in the required format. 
Chapter 2 — Proposed Redesign of IPEDS 

26 

Redisclosures 

As mentioned, the UR system would be heavily protected from unauthorized 

abuse of individually identifiable information. According to FERPA, redisclosures refer 

to cases in which UR data that were submitted to the UR system by institutions would be 

sent, or “redisclosed,” from the UR system to the original institution or to another party. 

The only allowable redisclosures of individually identifiable data would have to be 

specifically authorized in the HEA legislation. Several authorized redisclosures of data 

have been proposed: 

• Enrollment verification for the National Student Loan Data System 

(NSLDS): The UR system would be used to verify enrollment for students 

who are receiving federal student loans. Currently, this verification is 

being done either by institutions themselves, or being outsourced to 

organizations such as the National Student Clearinghouse. 

• Verification of subsequent enrollment to the IPEDS keyholder: The UR 

system would be of significant value to colleges and universities if they 

could gain information on students who left their institutions—i.e., if they 

re–enrolled subsequently or enrolled and obtained a degree from another 

institution. Therefore, a redisclosure of individually identifiable data back 

to the initial institution keyholder and coordinator is proposed. Data on the 

subsequent enrollment of students who left the first institution in the 

previous year would be redisclosed to the keyholder and coordinator, 

including the institution of subsequent enrollment, date, attendance status, 

attainment, and date of attainment.26 This benefit would come in addition 

to potential new aggregate variables on graduation rates, time to degree, 

and student mobility that would be posted to the PAS (see below).27

• Record mismatches: During the process of data collection for the UR 

system, mismatches between data records and other types of edit failures 

would have to be resolved. This would involve sending individually 

 

26 Students would be able to opt out of this redisclosure. This will be discussed in future sections. 

27 Redisclosure of student information to the original institutions could take place over a longer time period 

if this was decided by a future design TRP and NCES. 
Chapter 2 — Proposed Redesign of IPEDS 

27 

identifiable information back to the IPEDS keyholder. These types of edit 

failure resolutions would be essential to the data integrity of the database. 

No other new redisclosures of data would be allowed besides those described 

above and those permitted under the Patriot Act. Individually identifiable data would 

remain within the permanent UR storage system. 

Originally, a proposal was considered to redisclose UR data to the Internal 

Revenue Service (IRS) to verify enrollment for students who claim the Hope or Lifetime 

Learning tax credits. However, after considering feedback from TRP panelists as well as 

discussions with IRS, it was decided not to include the collection of data for the 1098–T 

forms in the proposed UR system framework. Nonetheless, including 1098–T data in the 

UR system, if authorized, might save money for the federal government and may be 

considered in the future. 

Analysis for OPE 

Individually identifiable student information would not leave the UR database for 

any other purposes, such as generating performance measures for federal financial aid 

programs; rather, aggregate reports would be generated by NCES from the data. For 

example, the Office of Postsecondary Education (OPE) is required to assess the success 

of student financial aid programs under the Government Performance and Results Act 

(GPRA). Accurate measures of the persistence and attainment of students who receive 

federal financial aid are important to fulfill these requirements. OMB has developed 

annual program indicators for each federal agency under the Program Assessment Rating 

Tool (PART). For OPE, required program indicators include the percentage of aid 

recipients that persist and attain a degree or certificate, for various groups of students 

broken down by attendance status, gender, race/ethnicity, and other factors. Currently, 

OPE can obtain these types of measures only from the Beginning Postsecondary Students 

(BPS) study, which is administered by NCES once every six to eight years. A UR system, 

on the other hand, would allow the calculation of these measures on an annual basis. 

NPSAS and BPS samples would be drawn from the UR data. NPSAS collects financial 

aid and employment data well beyond the data that would be supplied with the proposed 
Chapter 2 — Proposed Redesign of IPEDS 

28 

UR system. BPS includes a number of variables that are used to predict persistence, 

including information about family formation, health, and employment. 

Under the proposed UR system, NCES could not allow OPE access to the UR 

database. However, NCES could generate aggregate reports for OPE using the UR data. 

In other words, OPE could submit the identifiers of student financial aid recipients to 

NCES, or records could be extracted by NCES from OPE databases. NCES could then 

match those records with the UR database and generate aggregate measures of 

persistence, transfer, and attainment for various types of aid recipients, such as those 

attending on a part–time basis, or those attending institutions in different sectors. Under 

such a scenario, NCES would conduct disclosure risk avoidance analyses of these 

aggregate measures and perturb the data as necessary to ensure confidentiality.28 While 

ensuring that cell sizes were large enough so that no individual could be identified, NCES 

would send reports with these aggregate measures back to OPE. A similar process could 

be performed for program evaluation of other OPE programs, such as GEAR UP, 

Upward Bound, and Talent Search. 

Other Possibilities 

After the full–scale implementation of a UR system, it would be possible to add 

new derived variables to the PAS, COOL, and the Data Analysis System (DAS). These 

new variables could take into account institutional missions, transfers, or the 

characteristics of various groups of students. The procedure for adding or modifying data 

elements under IPEDS involves holding Technical Review Panels to discuss a particular 

topic and posting the findings of the TRP online for public review and comment. 

Several variables of interest were mentioned at the three TRPs. For example, 

panelists were interested in new definitions of net price. A UR system would allow the 

development of net price calculators that could estimate net price for groups of students 

with differing characteristics. After a number of years of implementation of a UR system, 

it would be possible to calculate new measures of graduation rates that better take into 

 

28 In order to preserve the confidentiality of information regarding individuals’ financial aid and graduation 

rates, the student financial aid and graduation rate data files are perturbed in various ways. All aggregate 

student financial aid and graduation rate statistics are based on the perturbed data. NCES would keep a 

copy of the file with flags for perturbed cells for internal documentation purposes. 
Chapter 2 — Proposed Redesign of IPEDS 

29 

account the missions of postsecondary institutions and the mobility of students across 

institutions. New definitions of time to degree, including transfer, calculated separately 

for various fields of study, could also be developed. In addition, variables could be 

created to describe enrollment by field of study and program length, completions by field 

of study, and other factors. 

Alternatives using IPEDS Aggregate Components 

Rather than redesigning IPEDS to create a UR system, the current IPEDS 

framework could be modified by adding additional variables or survey components. 

Additional data elements might lead to improved aggregate measures, although they 

would still suffer from the limitations of aggregate data. 

For example, a Technical Review Panel was held as part of the ongoing IPEDS 

revision process to discuss the calculation of net price and the potential for improved data 

collection. The TRP came up with more than 100 different definitions of net price that 

would be useful to calculate. TRP members also came to the conclusion that in order to 

calculate additional definitions of net price that were useful to the postsecondary 

education community, an entirely new IPEDS net price component would be needed. 

Such a component would require collection and reporting of tuition and fees, housing 

costs, books and supplies, and total price of attendance by such categories as residency 

status, dependency status, attendance intensity, and aid status. Although this option has 

the benefit of fitting within the current parameters of the IPEDS framework, it would 

require substantial additional burden on the part of colleges and universities. 

To calculate graduation rates and variations on persistence, transfer, and time to 

degree, it is possible that NCES could modify the Graduation Rates component in several 

ways. For example, aid categories could be added to the existing matrix of race/ethnicity 

and gender counts. Transfer counts could be made mandatory for all institutions with 

transfer missions, and the time to degree could be extended to 250 percent of normal time 

to degree. Cohorts of part–time students could be established. In addition, a variety of 

derived variables could be defined and added. Like the net price component described 

above, however, these changes would involve increases in institutional burden and would 

not answer many of the questions related to student mobility, multiple enrollment, and 
Chapter 2 — Proposed Redesign of IPEDS 

30 

related issues. Changes also would be necessary to the Student Right–to–Know 

legislation to define new measures of postsecondary outcomes. After legislative change, 

additions would need to be made to the current IPEDS collection schedule to collect the 

new variables required to calculate these measures. 

To gather better data on completions and enrollment, existing IPEDS components 

could be modified with increases in data elements. For example, fall enrollment data 

could be collected by field of study, and age and residence and migration data could be 

collected annually rather than every other year. Unduplicated full–year enrollment, 

including credit activity, could be collected by gender, race/ethnicity, student level, 

attendance intensity, and field of study. Completions data could be collected by field of 

study and the average number of credits earned, including transfer credit. Again, 

however, these changes in aggregate data collection would involve increased costs. A UR 

system would allow the collection of all of these data elements within the framework of 

fewer file submissions and without adverse impact on the schools least able to do 

aggregate IPEDS reporting. 

Other Alternatives to Unit Records 

There are other alternatives to a full UR system that might be able to generate 

variables needed to fill gaps in necessary knowledge. However, each of these alternatives 

has its own costs and/or disadvantages. For example, one suggestion for gathering more 

accurate net price information was to administer the National Postsecondary Student Aid 

Study as an annual sample survey. NPSAS collects information on students’ receipt of 

various forms of financial aid (federal aid as well as state, institutional, and private), 

tuition and fees, total prices of attendance, residency, demographic information, and other 

variables. However, while NPSAS could provide nationally representative net price 

figures, it could not provide net prices by institution. In addition, representation by state 

would likely be far more expensive than a UR system, and would be more burdensome 

for state agencies.29 NPSAS and BPS are necessary, though, to collect additional data 

 

29 It was estimated that administering NPSAS on an annual basis for all 50 states would cost an additional 

$40 million per cycle. 
Chapter 2 — Proposed Redesign of IPEDS 

31 

that are needed to understand student persistence, including income, health, and 

employment. 

Another alternative that would allow more accurate graduation rates is that NCES 

could administer the Beginning Postsecondary Students (BPS) longitudinal study on an 

annual basis.30 BPS captures a national, systemwide perspective of persistence 

systemwide (i.e., regardless of institution), multiple enrollment, part–time enrollment, 

transfer, and attainment using students as the unit of analysis. However, BPS is 

administered only once every six to eight years. In addition, similar to NPSAS, BPS is a 

nationally representative sample of students, and the data cannot be used to make 

generalizations about states or institutions. Finally, the cost of administering BPS is quite 

high, and conducting such a survey on an annual basis would be substantially more 

expensive than a UR system. 

It also has been suggested that since the National Student Clearinghouse already 

collects UR data from 2,800 institutions, perhaps these data could be used for the purpose 

of calculating graduation rates and other measures. Currently, these data cannot be used 

to calculate national estimates because the coverage is not complete (there are about 

6,700 Title IV institutions), with 4–year institutions being more likely to participate than 

2–year institutions or private for–profit institutions. The Clearinghouse currently includes 

only a subset of the data elements that would be required to complete the existing IPEDS 

components. In addition, not all participating institutions currently report degree or 

certificate attainment to the Clearinghouse. This means that students who are enrolled at a 

nonparticipating institution, or whose degree was not reported to the Clearinghouse, 

would show up as stop–outs or drop–outs from postsecondary education. Near 100 

percent participation would be necessary for the Clearinghouse to be used as a viable 

alternative. There also are questions about liability and whether these data are protected 

by FERPA. 

 

30 BPS is a subset of the National Postsecondary Student Aid Study (NPSAS). 
32 
33 

Chapter 3—Issues Related to the Development of a Unit 

Record System

As mentioned in the introduction to this report, it was important to examine two 

separate questions in examining the feasibility of a UR system. First, could a UR system 

be technically and efficiently constructed, or are there insurmountable issues to 

developing such a system? Second, should such a system be developed by the federal 

government? If the barriers to development of the system can be overcome, what are the 

specific issues that must be addressed before moving forward? 

The answer to the first question may be inferred from the fact that 39 states have 

compiled UR systems in some form, and thousands of postsecondary institutions submit 

UR data electronically to private organizations such as the National Student 

Clearinghouse, which collects student UR data for a large proportion of currently 

enrolled students (in addition, for a fee the Clearinghouse will send back to the institution 

selected information on their students). Technically, UR could be done at most 

institutions in the long term, after investment of time and financial resources. NCES 

already collects student UR data through sample surveys such as NPSAS, and 

postsecondary institutions have experience in reporting data on financial aid recipients to 

FSA. 

The answer to the second question is not as clear. This chapter provides a 

framework for the problems associated with the “should” question, including several 

dimensions: privacy and confidentiality; institutional burden; coordination; technical 

issues; and timing. Much of the information in this chapter came out of the three TRPs 

convened as part of the feasibility study, as well as individual comments submitted to the 

contractor in response to the posting of public documents. Some of the concerns raised in 

this chapter are addressed more fully in the following chapter, which presents a detailed 

architecture of a proposed UR system. 

One should note that several design issues were raised during the TRPs, often 

regarding the definition of data elements. These types of questions would be resolved in 
Chapter 3 — Issues Related to the Development of a Unit Record System 

34 

the design phase of a UR system, should a UR system be authorized and funds be 

appropriated. 

Privacy and Confidentiality 

Some of the biggest challenges to a national UR system are concerns about 

student privacy and the confidentiality of individually identifiable student data. Some 

panelists at all three of the TRPs raised the issue of the individual right to withhold or 

control personal information. If NCES collects individually identifiable data in a UR 

database, student data would be in the possession of an external party, but may still be 

within the student’s right to control. ED, IES, and NCES have always taken seriously the 

importance of safeguarding student data, but many in the postsecondary education 

community are concerned that creation of a federal UR database of all students would 

potentially be more dangerous than smaller databases held by states or other 

organizations. Some critics of a federal UR system believe that the simple existence of 

such a database is a violation of privacy. As one TRP member asked, does the need for 

data outweigh individual freedoms? Another way to look at this issue is, if a UR system 

is implemented, can student privacy and the confidentiality of student records be 

protected? 

The goal of the proposal is not to build a system that would endanger students’ 

privacy, but rather to use the experiences of partial collections of student UR data to 

construct a secure system for collecting data on all students. Currently, information about 

federal financial aid recipients, including their SSNs, is collected by FSA to evaluate and 

monitor federal student aid programs. Students who apply for federal student aid or claim 

the Hope and Lifetime Learning tax credits in effect give consent through the Free 

Application for Student Aid (FAFSA) and tax forms submitted. Some panelists, however, 

questioned the need to report data on students who do not receive federal student aid, 

asking what the compelling government interest is in collecting data on nonaided students 

and wondering whether the involuntary inclusion of such students violates their rights of 

refusal. Nonetheless, data on nonaided students would be necessary to compute 

graduation rates, retention measures, and other indicators in order to compare these 

measures to those of aided students. An additional argument made was that students who 
Chapter 3 — Issues Related to the Development of a Unit Record System 

35 

currently do not receive federal student aid are aided indirectly through such forms of 

subsidy as state appropriations to public institutions and deferred tax revenues at private, 

not–for–profit institutions.31 

Another concern raised regarded the redisclosure of individually identifiable 

information for purposes of matching student records and providing information about 

subsequent enrollment of students to IPEDS keyholders. Such redisclosures could 

provide new information going to the original institutions, for which the students did not 

specify their consent. 

Federal privacy laws, such as FERPA, require that individually identifiable 

student information collected by federal agencies be protected and released only with the 

prior consent of the individuals, with certain exceptions. Under FERPA and other privacy 

laws, organizations are required to notify students if their information may be collected 

and used for research studies or other purposes. Students would be able to “opt out” of 

the redisclosure of subsequent enrollment information back to the original keyholder.32

Finally, some postsecondary leaders for private institutions are concerned about 

possible legal liability once they have submitted data to NCES if the data are 

subsequently misused or unlawfully disclosed, because they do not have the sovereign 

immunity protection that exists in the public sector. The Office of General Counsel at the 

Department of Education has agreed that because NCES adds value to submitted data, 

NCES therefore “owns” the data submitted by the institution.33 If a UR system were to be 

legislated and implemented, IES/NCES would work with the FPCO to ensure that 

collection of data and redisclosures are lawful under FERPA. 

TRP panelists also expressed concern over possible unintended uses or 

consequences of the UR data. Other federal agencies might want access to the data for 

noneducation–related purposes. This concern is understandable, although it is the 

purview of Congress to determine legitimate disclosures. If other agencies were to have 

access to the data, this would need to be incorporated into law as appropriate. 

 

31 Tuition at these schools is probably lower than it would be if they were not the beneficiaries of tax–

exempt status and state appropriations. 

32 An “opt out” flag would be included in each student’s header record. Students would not be able to opt 

out of the statistical use of the data. Note that students receiving federal loans have already given their 

consent to enrollment verification. See the Chapter 4 for details. 

33 This agreement was obtained in relation to NPSAS data from the University of Michigan in 2004. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

36 

In addition to misgivings about student privacy, there are more technical concerns 

about unauthorized access to the data by hackers and identity theft. This is particularly 

true given the proposal to use SSN/ITINs as one of several personal identifiers to match 

student records. Many institutions do not require that students provide SSN/ITINs upon 

admission unless they apply for federal student aid or the Hope and Lifelong Learning tax 

credits. In fact, several panelists in the second TRP noted that their institutions are 

moving away from using SSNs to identify student records due to concerns about 

unauthorized access, and that more students are refusing to supply those numbers. TRP 

panelists suggested looking into alternatives to collecting SSNs, such as using 

compression or only the last six digits of the number. Nonetheless, SSN/ITINs are 

currently required by FSA to determine aid eligibility and by NSLDS for loan deferment. 

The use of SSN/ITINs would be essential to a UR system, to accurately link together 

student information on financial aid, enrollment and completions, as well as to link 

records from various institutions. Without SSN/ITINs, mismatch rates would increase 

significantly, which would substantially increase the burden on the Help Desk and 

keyholders to resolve. The practice of obtaining SSN/ITINs from students would have to 

be reinstated if the UR system were authorized. For students without SSN/ITINs or who 

refuse to provide them, a matching process would be used with fuzzy logic and identifiers 

such as name, date of birth, and address. Fuzzy logic involves mathematical algorithms or 

methods for making a decision (in this case a fuzzy match between records) based on 

ambiguous or missing information. 

Certainly there are valid concerns about privacy in a time when increasing 

amounts of information are being gathered on all citizens as well as students. 

Nonetheless, there are assurances IES/NCES can make regarding the confidentiality of 

any data collected through a UR system. IES/NCES is well suited to protect the data, 

given the strict limits of the legislation regarding data confidentiality under which it 

operates. IES/NCES legislation protects the privacy of individuals, making wrongful 

disclosure a Class E felony punishable by up to five years in jail and a $250,000 fine. 

NCES has experience in working with individually identifiable data through its various 

sample surveys, and has created the structures and procedures necessary to prevent 

unauthorized disclosure of such data. In fact, there are no known cases where 

individually identifiable data collected by IES/NCES have been wrongfully disclosed by 
Chapter 3 — Issues Related to the Development of a Unit Record System 

37 

an employee, contractor, or restricted licensee, or of cases in which hackers have 

breached IES/NCES firewalls. In addition, IES/NCES is the only component of ED that 

is separately certified by the Chief Information Officer and the Inspector General for its 

computer operations and system firewalls. Therefore, if collected, the data would be 

technologically protected and secure. 

In the proposed UR system, data would be submitted to NCES but would not ever 

leave NCES unless authorized by legislation. Estimates created from the UR database 

would be reported only as aggregates at the level of institutions or groups within 

institutions. In order to move forward with a UR system, decisions would be necessary 

regarding which redisclosures are valid uses of the UR data and therefore should be 

authorized by law. 

Burden

The potential for additional burden in terms of labor and financial costs is another 

challenge to a federal UR system. Postsecondary institutions believe that they are already 

stretched thin by requirements from federal agencies, state governments, and other 

organizations to submit data electronically throughout the year, as well as the need to 

respond to questions in accordance with the Freedom of Information Act (FOIA). At 

some schools, the need for compliance reporting has used scarce resources that could 

have been spent on other needs, such as policy analysis. At the same time, many small 

colleges do not currently have an institutional research office, and any submission of data 

represents a challenge. Institutions might pass the costs of additional reporting along to 

students and families in the form of price increases. Nonetheless, when examining the 

burden a national UR system would present, it is important to focus on the incremental 

burden of such a system—i.e., the costs produced over and above the costs that would 

have occurred without the UR system, or to what IPEDS might evolve to if UR is not 

used. This needs to measure the burden of UR above what might happen to data 

collection without UR, including the use of XML for transmitting data across computer 

systems. 

The additional burden of a UR system can be divided into two categories: initial 

implementation and subsequent operations. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

38 

Initial Implementation 

The burden of initial implementation is expected to be higher than the costs of 

subsequent operations. The burden may be substantial at some schools that are not 

already part of UR at the state or private system level. Initial implementation would 

involve both a field test and the first and second years of full–scale implementation. 

Generally, there are some challenges that are specific to the initial implementation period, 

including possible hiring of additional staff or shifting of existing staff, training staff 

about the requirements of new IPEDS UR reporting, the purchase or upgrade of software, 

and creating and submitting historical GRS files. 

If a UR system were implemented, a field test would be necessary according to 

IES/NCES standards, in order to make sure that the system works, to anticipate and 

address problems that would be encountered, and to develop all necessary features in the 

system prior to implementation. The data submitted for the field test would not have to be 

complete, but would need to be sufficient to test the system comprehensively. About 

1,200 to 1,500 institutions would be required to participate in the field test, and they 

would have to report using both the old and new IPEDS collection system. NCES would 

make every effort to notify selected institutions as early as possible. Regardless of the 

timeframe, it is recognized that participation in the field test would present an additional 

burden on institutions. 

In the full–scale implementation, many institutions would need to upgrade various 

technologies and assign staff to comply with new reporting requirements. Some 

institutions would rely on vendors for upgrades to existing software, or to build their UR 

extracts, which would increase software costs. Others would need to pay for changes to 

legacy information systems. Staff would need to be trained in the use of these systems 

and the details of reporting procedures. Institutions in the middle of converting or 

upgrading their administrative information systems would have particular constraints 

with implementing these changes during this time. The initial burden on small institutions 

that may not have sophisticated software or that do not have institutional researchers on 

campus is likely to be relatively high, unless the institutions are part of a larger system or 

state association. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

39 

Institutional researchers at one TRP meeting argued that obtaining historical GRS 

files for all cohorts in the first year would present a substantial burden, even though these 

same files are needed now to calculate the GRS locally. The historical files would not 

need to include CIP codes or data for time to degree, financial aid, prices, and other 

information. Required data would include the year of established cohort; first–time, full–

time beginning students in the fall; degrees/awards received; as well as a measure of 

whether students are prepared to transfer. Although institutional researchers attending the 

TRPs stated that they would prefer to submit historical data the old way if UR were 

implemented, it was recognized that this would delay the benefits of UR for six years, 

with no improvement over the current GRS measures. If historical files were submitted, 

then better calculations such as transfer–out rates at community colleges could begin to 

be implemented much sooner. 

Subsequent Operations 

The additional costs of subsequent operations under a UR reporting system are 

expected to be lower than the costs of initial implementation. Keyholders would need to 

coordinate with offices on campus to gather data, run internal checks to make sure the 

data make sense, submit data to NCES several times per year, and work with the IPEDS 

Help Desk to reconcile record mismatches and discrepancies in the data. 

While the data files are being edited, the data would reside in the IPEDS 

collection system where only the keyholder (and his/her proxies) could view the data. 

Only after the data were locked, transported to permanent storage, and later migrated to 

the PAS as aggregate estimates (about a month later) would anyone outside the 

authorized participants in the submitting institution and the authorized participants in the 

NCES data receipt process be able to view the data (see the following chapter for details 

of this process). 

Some mismatches of records found by NCES and sent to the keyholder for 

resolution could be difficult to resolve. For example, NCES would no doubt discover 

cases in which a student reported by an institution as a first–time student has a match at 

another institution, indicating that the student had been previously enrolled. NCES might 

also find a student who matches with other records on all identifiers except last name. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

40 

These student records could be sent back to the keyholder to have the mismatch resolved 

or the identity verified. For these records, the keyholder would then have to check 

institutional records, resubmit the data if appropriate, or send the data back with no 

change. These steps might be minimal for each record, and manageable for a small 

institution. However, the mismatches could add up to a large amount of effort if there are 

numerous records to resolve, as in the case of large public systems, where the chance of 

keystroke error might result in many mismatches. Keyholders would have the opportunity 

to sign off on a mismatch even if they cannot find the student or otherwise resolve the 

issue. Eventually, the institution’s administrative information system would likely be 

improved to ensure that all students with different types of data can be matched—for 

example, all students receiving aid would have enrollment records or all graduates would 

have enrollment records in the system. 

Changes in student records during a semester/term, especially regarding changes 

in attendance status, would require a mechanism for ongoing updates to the UR system. 

For example, if a student changes from full–time to part–time attendance status, this may 

affect his or her eligibility for financial aid or loan deferment. This may be difficult for 

institutions that currently do not store changes in status on their administrative 

information systems. Similarly, institutions might want to resubmit data from the 

previous term or year. For example, some institutions post degree awards retroactively 

during the year after the official degree date, due to incompletes and other issues. This 

process is available only for the previous year under the existing IPEDS system. The 

burden of these types of edit failure resolutions and mid–period adjustments could be 

compounded if institutions are required to keep records of all student data provided to 

NCES indefinitely in order to remain in compliance with FERPA. If a UR system were 

authorized, design TRPs would be necessary to decide on the process for dealing with 

changes in students’ records during a term, whether by including mid–term changes in a 

subsequent file or some other mechanism. 

It is difficult to offer cost estimates with any degree of precision, although some 

rough estimates are presented in Appendix B for purposes of illustration. Costs would 

likely include additional staff, as well as financial resources for hiring and training, and 

the costs of software upgrades. These, and other, costs are likely to differ widely among 

postsecondary institutions, depending on whether they are in state UR systems, whether 
Chapter 3 — Issues Related to the Development of a Unit Record System 

41 

they currently upload data to organizations such as the National Student Clearinghouse, 

whether they use local or proprietary administrative information systems, and whether 

they currently have relatively low levels of IT and institutional research capability. 

At the same time, it is important to keep in mind the labor hours and cost of 

continuing the current student–related IPEDS components, and the additional costs of 

expanded data collections in the context of accountability. It is likely that, without a UR 

system, there would still be increases in the burden of reporting IPEDS aggregate data, 

including new variables for the construction of net price and perhaps revised graduation 

rate variables. There would be a corresponding decrease in burden after the initial 

implementation of a UR system, as postsecondary institutions would no longer need to 

track and maintain records on GRS cohorts for six years. Rather than each institution 

calculating its own estimates, NCES would calculate official fall enrollment, graduation 

rates, financial aid averages, and other measures. 

Some institutional researchers attending the TRP meetings noted that the costs to 

institutions of moving to a UR system would be offset by the benefits of receiving 

information about students at that institution produced by a UR system. In particular, 

TRP attendees felt it would be useful to find out, on a UR level, what happens to the 

students who leave the institution. If such a redisclosure were authorized by the 

legislation creating a UR system, it would be possible to provide student information 

back to the institutional keyholder or coordinator. As noted above, issues regarding 

privacy and the right of students to withhold personal information would need to be 

resolved in the design phase of the UR system. 

TRP panelists noted that if a UR system were implemented, it would be important 

to try to take into account these various issues during the design phase of implementation 

so as to minimize institutional burden. For example, design TRPs could develop 

procedures that minimize the burden of edit failure resolutions and mid–period 

adjustments while allowing accurate data. Institutions would also have the assistance of 

the IPEDS Help Desk and various training sessions. Financial aid officials, registrars, IT 

staff, and institutional researchers would be involved in training and in the project design 

TRPs. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

42 

IPEDS reporting is mandatory for all institutions that participate in the Title IV 

federal student aid programs. Given the administrative burden of this reporting, it is 

possible that some funding could be used to mitigate the burden. There are different ways 

to offset the cost and burden of UR. One funding mechanism, Administrative Cost 

Allowances (ACAs), is used to help defray the cost of administering federal student aid 

programs.34 A similar funding mechanism could be put in place for UR. Another 

possibility would be for a new grant program to be funded to assist in paying for the costs 

of implementing a UR system. 

Technical Challenges 

Technical issues were also raised as a potential challenge to the implementation of 

a national UR system. The proposed system would include the creation and maintenance 

of a database of millions of student records, with new records added every year. In 

addition, the system would require the uploading of large files from postsecondary 

institutions to NCES, using highly secure mechanisms. Multiple forms of security would 

need to be in place to protect against unauthorized disclosures of data. 

NCES currently has most of the hardware and software necessary to implement a 

UR system. Much of the equipment used in the current, web–based IPEDS collection 

would be applicable to a UR collection framework. In addition, ED has servers capable of 

storing large amounts of student data, as seen for example in the data collected on 

financial aid applicants by OPE. One necessary addition would be database storage, to be 

located off–line in a secure site and protected by physical and software firewalls.35 (See 

Chapter 4 for more details on software and hardware needs.) 

There would likely be greater technical challenges for postsecondary institutions. 

The extent of the challenge would differ between the registrar, institutional research, and 

financial aid offices, which sometimes utilize different and incompatible information 

systems that cannot communicate with each other and complicate the exchange and 

compilation of data at a central point at the institution. Institutions using both legacy and 

 

34 Institutions currently receive over $150 million in Administrative Cost Allowances (ACAs), which can 

be used toward the administration of federal programs such as Pell Grants and campus–based aid. 

35 The cost to NCES would depend on the final design and implementation. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

43 

proprietary student information systems would need to make software conversions or 

updates, while institutions that do not have such systems would need to implement the 

UR requirements in another manner. NCES has suggested that it can provide an Excel 

template that could then be used to collect data and generate the data file needed for 

submission. Although the technical issues could present a problem, these schools 

currently find a way to do uniform reporting for FSA financial aid eligibility, NSLDS 

loan deferment, and IRS tax credits. 

The proposed UR system envisions the use of XML technology for the 

submission of data files to NCES, although it is likely that ASCII files would be accepted 

in the early years of implementation. Some postsecondary institutions have already 

adopted XML and are using it in their exchange of data with other organizations. For 

example, in recent years, there has been movement by the Department of Education 

toward using XML as part of its Common Origination and Disbursement Initiative 

(COD).36 FSA has already mandated that institutions begin submitting data to the office 

using XML by 2005–06. Like FSA, IPEDS is moving to register all of its data elements 

and collections with the Postsecondary Electronic Standards Council.37 

Coordination 

Coordination of the flow of information presents a multitude of challenges in 

implementing a UR system. These include the coordination of offices within 

postsecondary institutions and the management of data collection through the IPEDS 

coordination trees. The amount of coordination and interaction will be greater due to the 

increased level of detail that must be matched in the URs. 

TRP panelists noted that coordination between various offices on campuses—

registrars, institutional researchers, admissions, IT, and financial aid offices—might be 

difficult, and becomes even more difficult if those offices are running different 

information systems. Currently, institutions that report data out to states or to 

 

36 For more information, see http://www.ifap.ed.gov/cod/attachments/CODXMLHandout.pdf. Some TRP 

panelists reported problems in sending and receiving large files in their work on COD. 

37 The Postsecondary Electronic Standards Council (PESC) is a non–profit association of colleges and 

universities; professional and commercial organizations; data, software and service providers; and state and 

federal government agencies, whose mission is to lead the establishment and adoption of data exchange 

standards in education. For more information, see: http://www.pesc.org/. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

44 

organizations such as the National Student Clearinghouse often are reporting a narrower 

range of data, such as only enrollment data. Merging financial aid data with enrollment 

and completions data would be especially difficult if an institution does not have an 

integrated system and uses different student identifiers in its various systems. Further, 

some schools have decentralized structures with, for example, multiple registrar and 

financial aid offices. Keyholders would need to coordinate the process of extracting data, 

editing and cleaning data, and running preliminary aggregate reports across these offices. 

The problems of editing are minimized somewhat if schools rely on NCES matching 

subroutines for this first round. 

State and system coordinators that are keyholders in the IPEDS coordination tree 

would have access to collection–level UR data, as they do in the current IPEDS 

collection system. However, several TRP members argued that a UR system might not 

work well within the existing IPEDS coordination tree structures. For example, if state 

coordinators were to continue to submit data to NCES, many would have to expand their 

collections from institutions or expand the type of data they were collecting. Most state 

UR systems are based on census dates and analytical files. Some SHEEOs and system 

offices may not see the benefit of coordinating the submission of multiple streams of 

enrollment files in the IPEDS UR system unless they get something back, such as the 

redisclosure of enrollment and attainment data. Yet there would be a noticeable decrease 

in the requirements for aggregate reporting and a resulting tradeoff in their IPEDS work. 

This could shift more, or all, of the reporting burden to institutions that had previously 

relied on SHEEOs to submit data on their behalf. State coordinators might not know how 

the proposed UR system would affect their role as coordinators until such a system was 

fully implemented and they could assess the nature of collection demands. The various 

scenarios for state roles and coordination would be described and documented as soon as 

possible while the TRP design phase is evolving. 

Timing 

It is possible that if a UR system were authorized in the Higher Education Act 

(which could conceivably be as early as the summer of 2005), a field test would then be 

administered in 2006–07, followed by full–scale implementation in 2007–08. The project 
Chapter 3 — Issues Related to the Development of a Unit Record System 

45 

timetable is designed to yield data relatively quickly while avoiding potential problems 

associated with an expedited timeframe. A phased implementation could also be 

considered to provide additional time to address problems during implementation. 

To respond adequately as part of the field test, it may be necessary for institutions 

to examine the utility of their administrative information systems for the purposes of 

producing UR extracts and to address some of the burden issues mentioned above such as 

training and staffing. Early notification for the selected institutions would be crucial for 

the institution’s ability to respond in a timely and accurate fashion. It is possible that 

NCES could draw the sample of institutions immediately after legislative authorization to 

allow selected institutions almost a year to prepare. 

If a UR system were mandated, institutions that have not already implemented the 

two–question format for race/ethnicity, required by OMB Statistical Policy Directive No. 

15, Race and Ethnic Standards for Federal Statistics and Administrative Reporting on all 

individually identifiable records, would have to do so during initial implementation. 

Another important issue is operational—how to time data collection schedules, 

while minimizing conflicts and taking into account the treatment of transactional files 

compared with analytical files. Transactional files reflect operations at a point in time, 

and usually are used for purposes that require knowing the current status of students, such 

as enrollment verification. These types of records are not used for the fall enrollment 

census report that is used to conduct peer comparisons and therefore may not receive as 

much attention by institutional researchers due to their decreased impact on reporting. 

Analytical files generally are used for official reporting and analysis, and can be files 

with a specified snapshot date such as a census date, or files that accumulate all activity 

during a specified period. The information captured for analytic data reporting may not 

be the same as a transaction record created for the purpose of student status verification. 

As mentioned above, many institutional researchers have expressed concern about the 

burden necessary to clean transactional files before they are submitted. However, it is 

possible for keyholders to submit files without doing significant data cleaning beforehand 

and focus attention on the records that come back from NCES as mismatches, which 

would be resolved by the keyholder before the data were locked and aggregate estimates 

migrated to the PAS. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

46 

To replicate the variables currently collected through IPEDS, the proposed UR 

system likely would collect enrollment records once per term (with the fall collection file 

including a census date flag38 in order to replicate the IPEDS Enrollment component). 

However, some institutions do not have standard terms; for example, courses may be 

offered on a rolling basis, or on six–week terms. Flexible term dates are becoming more 

common with web–based instruction and alternative delivery modes. In addition, some 

institutions offer courses on both standard terms and nontraditional terms. Institutions 

might desire to upload data more frequently, especially for the purpose of enrollment 

verification for student loan programs. The final UR system that is developed through the 

design TRP process will need to allow for various flexible term reporting options. 

Degree and certificate completions would probably be collected with only one file 

per year. Many institutions have several commencement periods, and might wish to 

submit multiple files over the year. A problem that occurs with completions data, 

especially for schools that award degrees only once per year, is that some awards are 

recorded months after the relevant students have stopped attending institutions. In this 

case, degree dates reflect the date the degree was awarded rather then when the degree 

was finished. In designing the timing of data collections and the periods of reference for 

the data, it would be useful to align the completions data with the enrollment data 

necessary to calculate graduation rates so that completions records can be matched to 

comparable enrollment records. 

Student financial aid information also likely would be collected with only one file 

per year. Financial aid data would present some particular challenges in terms of timing, 

given the logistics of the financial aid award cycle. Data submitted in an academic year 

would be from the previous year’s award cycle, for example. It would be important to 

time the data collection of financial aid data so that it does not conflict with the 

institution’s aid packaging period, which is the busiest time of year for financial aid 

offices. In addition, the treatment of summer sessions varies by institution, especially 

regarding whether summer sessions would trail or lead39 the submission of an annual data 

 

38 An alternative to a census flag would be to require a separate census file for enrollment; this option 

would be considered during the design TRP phase if a UR system were implemented. 

39 Problems will be raised if the file schedule splits the summer session in two; these issues would be 

addressed during the design TRP phase of implementation. For example, multiple term files can be 

submitted beyond those that are required. 
Chapter 3 — Issues Related to the Development of a Unit Record System 

47 

file. This is an important difference necessary to state resource allocation models that 

must be considered in a UR system. 

All of these timing issues would be addressed during the design phase of UR 

implementation, should a UR system be authorized. (In addition, a proposed schedule for 

data collection is included in Chapter 4). In the proposed UR system, collection schedules 

would not need to be on a uniform schedule, but rather could be geared to a schedule that 

works best for individual institutions. In other words, institutions with different calendars 

or financial aid packaging schedules could submit data to NCES on different cycles. 

Flags would be used to note collection dates and other timing issues. At the same time, 

the data could all be consistent with the financial aid year, July 1 to June 30. The 

following chapter delves into more detail regarding the proposed data collection, 

including the schedule of submission periods. 

Variation Across Institutions 

All of these challenges are important to the discussion of whether a UR system 

should be implemented. They are also critical to consider if a UR system is legislated and 

moves into the design phase. How institutions would be affected by these various 

challenges depends on their individual circumstances. Institutions that are already 

uploading student data, that are familiar with procedures, and that possess the required 

technology would have the fewest challenges in implementing UR. Institutions with good 

coordination among offices on campus would also be better positioned to implement UR 

relatively rapidly. On the other hand, many small institutions with few resources would 

likely have a more difficult time with reporting, especially those without institutional 

research staff and technological capacity. It will help institutions if they have a good 

vendor relationship that is meeting their compliance needs; many private, for–profit 

institutions, for example, build the cost of compliance into their tuition and fees. Many 

TRP panelists emphasized that if a UR system were to be legislated and implemented, the 

more the design phase of implementation takes into account these challenges, the less 

burden it would place on institutions and others. 
48 

 
49 

Chapter 4—System Architecture 

The proposed IPEDS UR system is, by choice, general in terms of the design of 

the system architecture. It was recognized at the outset of the feasibility study process 

that any such formal design would need to evolve over time, through extensive dialogue 

with and feedback from constituent communities, and that this would involve numerous 

future Technical Review Panel (TRP) meetings if implemented. Nonetheless, for the 

purpose of this feasibility study the nature of the UR proposal needs to be as clear as 

possible, in terms of assumptions about what such a system would provide. 

Policymakers, data users, and institutional representatives want to know as much as 

possible about what the system would require of institutions and of ED to implement and 

operate, and how it might work conceptually. 

This chapter provides a description of the system architecture that is 

conceptualized for the proposed UR data collection system. Since the UR proposal builds 

extensively upon that already in place in many states, a basic description of the state UR 

model is provided first. The underlying assumptions that are inherent in the proposal for a 

federal version of a UR system are then discussed, followed by a discussion of the 

processes for collection and editing for a UR system (illustrated through the use of flow 

charts). Descriptions of other components of a UR system, such as permanent storage, 

migration to the PAS, authorized redisclosures of UR data, training, Help Desk support, 

software, and hardware, are also presented. 

The State Unit Record Collection Model 

The proposed collection of IPEDS student UR data parallels closely that already 

in place at many SHEEO and state system organizations across the country. These offices 

collect individually identifiable enrollment, course, financial aid, completions, human 

resource, room inventory, and finance data for a wide variety of purposes. Any effort to 

build a federal IPEDS UR system would leverage the important lessons and experiences 

of the SHEEO and system offices. The processes and end results are similar, though 

proposed on a larger scale. 
Chapter 4 — System Architecture 

50 

Many institutions are required by their coordinating SHEEO or system offices to 

submit data files with specific variables and census dates. These files are usually 

uploaded via the web, and in earlier years were transferred across computers using file 

transfer protocol (FTP) software. While some of this software is web–based, other offices 

use standard programs written with statistical packages (such as SAS, SPSS, and 

STATA) to merge, edit, and aggregate the data. SHEEOs and system offices provide 

software for schools to run edits against their UR data, looking for outliers and missing 

data. Few of these UR systems look across schools to more accurately classify cohorts 

and types of students or to share UR data on awards, transfers, and persistence with 

participating schools. 

According to recent information gathered by the national SHEEO association, at 

least 23 states and/or state systems use their UR data collections to generate and submit 

aggregate IPEDS reports for member institutions to NCES (L’Orange 2004). Five offices 

in Alaska, California, Minnesota, North Dakota, and Wisconsin produce all four student–

related IPEDS components with their UR systems. Another 13 states/systems reported 

that they produce at least three of the components this way; while only six states/systems 

produce the student financial aid IPEDS component from their UR systems. 

Some SHEEOs require schools to submit both state UR and aggregate IPEDS 

reports about enrollment, financial aid, and completions. In these systems, there is a 

negotiating process that occurs in resolving edits and addressing errors. It is recognized 

that while the SHEEO/state system editing process and collection data elements might 

vary from that proposed for IPEDS, NCES would aim to make the two as seamlessly 

comparable and compatible in definitions, timing, and specifications as possible. If a UR 

system were implemented, NCES would hold TRP meetings specifically to examine and 

build upon the effective practices of SHEEOs and state systems in collecting student UR 

data to produce aggregate IPEDS reports. The relationship between federal and 

state/system reporting and data structures is likely to develop over time, depending on 

which mechanisms work most effectively. 
Chapter 4 — System Architecture 

51 

Assumptions about System Architecture 

The following assumptions about UR system architecture are embedded in the 

proposal as it has evolved through the feasibility study process. These help to clarify 

aspects of the emerging design.

• The UR system would work much the same way IPEDS does now. The 

basic IPEDS collection system would remain the same, involving the 

secure, online submission of data by officially designated IPEDS 

keyholders. 

• The IPEDS coordination tree would remain in place. IPEDS keyholders 

would be appointed by institutional CEOs and could appoint proxies to 

assist in submitting different types of data. For schools that fall under an 

IPEDS coordination tree, two or more levels of review and approval 

would still be in place—once a school locks its data, the coordinator 

would review them and begin either to edit or lock the file. The process 

would work the same for URs as it does for the aggregate IPEDS 

components. 

• Data edits would be customized to each school. As is the case now, 

schools would only submit data for items that pertain to their mission and 

type, as defined through the Institutional Characteristics (IC) component. 

• Editing would be done as before, but expanded. Currently, for example, 

the previous year’s aggregate data are compared with a new submission to 

look for consistency; if data are different than the expected range, the 

keyholder is asked to review the results. This type of edit review would 

continue for URs, but with more levels and types of edits to be resolved 

and passed. 

• Once filed, the UR data would be physically transported to permanent 

storage. After the UR and aggregate level data passed edits and moved 

through the coordination tree, they would be physically moved from the 

collection system to a special UR database. 
Chapter 4 — System Architecture 

52 

• Estimates from the UR database would be used to populate the Peer 

Analysis System (PAS). Currently, when aggregate IPEDS data are moved 

from the collection system, they are stored in the PAS. The PAS data are 

then used to load information into the IPEDS COOL website. Although 

the UR system would not change this general process, data would come 

from the new UR database rather than the collection system. Aggregate 

estimates would be calculated, edited, locked, and if necessary perturbed 

before they were moved to the PAS, per IES/NCES statistical standards 

and requirements to protect confidentiality. (GRS and SFA data would be 

perturbed; enrollment and completions data are not subject to 

perturbation). 

• Permissions and levels of access in the PAS would remain the same. In the 

existing IPEDS collection system, data are migrated to the PAS and are 

made available at what is termed the “collection level” several weeks after 

submission, so that keyholders may immediately begin to compare their 

institution to others using unofficial, preliminary data. After extensive 

cleanup by NCES, the data are made available to other users at what is 

termed the “institution level.” Only after the data are finalized and made 

official through adjudication are the data moved to “guest level,” which is 

available to the general public. These three levels of access are available 

in the PAS. Although the manner of collection would be different if UR 

were implemented, the release of aggregate IPEDS data through the PAS 

would continue under this system of collection, institution, and guest level 

access. 

Collection System 

Generally, the UR collection system would be designed to collect individually 

identifiable, student–related data through files that are submitted electronically by 

institutions. The files would be used to calculate institutional summary totals for each 

school, with information about enrollment, completions, graduation rates, financial aid, 

and price. A list of the data elements that would probably be needed is presented in table 
Chapter 4 — System Architecture 

53 

1. These elements are listed by file type, along with the IPEDS component or other 

federal mandates that require them, and information about their format. 

Institutions would be expected to submit the four types of files: 1) header files, 

which would provide individually identifiable information such as name, Social Security 

Number (SSN), date of birth, address, race/ethnicity, and gender that are attached to an 

individual student’s record; 2) enrollment/term files, which would include program 

information such as number of courses and credits attempted, major field of study, start 

and end dates, and attendance status; 3) completions files, which would include 

information on degree completions and the date of completion; and 4) financial aid files, 

which would include information on financial aid received from federal, state, and 

institutional sources, as well as price of attendance. Each uploaded file would include a 

single record per student, per term/reporting period, per institution. Each of the term, 

completions, and financial aid files would need to include the same header information 

which is needed to match records across files; including fields such as SSN, name, date 

of birth, gender, and address. 

In addition, in the first year of collection, historical enrollment files on Graduation 

Rates (GRS) cohorts would be required in order to complete the required calculations for 

the GRS. Institutions would be expected to submit the four types of files over the course 

of a year, much as they currently submit the aggregate IPEDS components, depending 

upon when the data become available. Some files would be submitted once a year, while 

others would be submitted more frequently (see below). 

Instead of filling out online screens, keyholders would upload files in text or 

AASCII format, eventually in XML. Keyholders would view their aggregate reports for 

the EF, SFA, GRS, C, and IC price components online and review edits. In place of 

submitting corrected reports, however, they would upload corrected UR data, viewing the 

report results until they pass edits and are locked. 

Schedule of Data Collection 

 The dates for file submissions would be set in order to keep enrollment, 

completions, financial aid, and graduation rates in line with the student financial aid year. 

This would ensure that reporting across these components is comparable. This would also 
Chapter 4 — System Architecture 

54 

establish a consistent IPEDS year that would be in conformity with the ED FSA year for 

financial aid, which is July 1 to June 30. As a result, IPEDS—which is mandatory for 

Title IV institutions—would operate on the same cycle as FSA. 

File type Requirement Other comments

Student name Header Matching Full name, not just first and last names

ITIN or SSN Header Matching

Permanent address Header EF (Residence and Migration)

Date of birth Header EF (Age)

State of residence Header EF (Residence and Migration)

Gender Header EF, C, GRS

Race/ethnicity Header EF, C, GRS OMB two-question format

Citizenship Header EF, C

Program Header EF, C CIP 6-digit, including 'undeclared'

Degree plan Header GRS

Program length Header GRS Needed for 'long' programs

Varsity sport Header GRS

High school graduation date Header EF Needed for coenrollment

Institution UNITID Header Internal upload

Transaction date Header Internal upload

Redisclosure flag Header

Start date Term

End date Term

Number of courses Term EF, GRS

Credit hours Term EF, GRS

Attendance intensity Term EF

Level Term EF Including first-time, undergraduate, graduate, first-professional

Census date Term EF Or flag for EF inclusion

Transaction date Term Internal upload

Tuition and fees Aid Prices

Total price of attendance Aid Prices

State residency status Aid Prices In-district, in-state, out-of-state

Campus residency status Aid Prices On campus, off campus, with or without family

Dependency status Aid SFA

Federal grants Aid SFA Including grants from ED as well as other federal agencies

State grants Aid SFA

Institutional grants Aid SFA

Loans Aid SFA Including federal loans and loans from other sources

Assistantships Aid SFA

Transaction date Aid Internal upload

Degree granted Completions C, GRS

Degree date Completions C, GRS

Exclusion flag Completions GRS

Ready for transfer Completions GRS

Transaction date Completions Internal upload

Table 1. List of proposed variables to be collected in an IPEDS unit record system, by file type and IPEDS requirement

NOTE: Term files contain enrollment information. IPEDS components are the following: ITIN = Individual Taxpayer Identification Number; 

SSN = Social Security Number; EF = Enrollment; C = Completions; GRS = Graduation Rates; OMB = Office of Management and Budget; 

CIP = Classification of Instructional Programs; UNITID = Institution Identification Number; SFA = Student Financial Aid; Prices = Price of 

attendance.

IPEDS would use the July 1 to June 30 year for full–year enrollment, credits attempted, 

completions, student financial aid, and graduation rates. The enrollment transaction files 

could be selected as appropriate to accommodate these dates. The student financial aid 

data would be identical in dates to those used for Fiscal Operations Report and 

Application to Participate (FISAP) reporting. It is recognized that the completions and 
Chapter 4 — System Architecture 

55 

graduation rate data might result in slightly different calculations if aggregates were to be 

computed this way, but only for the first reporting period. 

 If this schedule were put in place, it would require modification of the census 

dates currently in use for the Graduation Rates component to match those used for 

financial aid. These dates would be used as the computational year and would not 

necessarily be the same as the academic year used by institutions. The nominal time for 

calculating the attainment of a bachelor's degree is based upon a fall enrollment and a 

spring graduation, not on a late summer graduation. The calculation of a graduation rate 

that is 100 percent of nominal time would be based on completion within three years and 

nine months, not four full years, since most bachelor's degrees are conferred in May. This 

change in GRS calculation dates would require a revision to the Student Right–to–Know 

legislation as part of any Higher Education Act reauthorization. The first year that the 

GRS was calculated with URs, the rates would be slightly different because of this 

shorter time period. This would return to a standard period of time the following year. 

These rates would then be comparable to those calculated for time–to–degree using the 

completions and header data. The change in graduation rate timing would affect trend 

data, and would likely create problems with reporting study abroad and summer 

completers in the first year. 

 Header records would be submitted at least once for every student, so that all 

students have at least one header record in the UR system. These would be replaced only 

when there is a change in the student information. Another option that emerged in the 

feasibility study is for schools to submit these records each term, over and over, replacing 

those previously submitted. Regardless of which option was implemented, it would have 

to ensure that certain key information changes were documented. These files would 

provide the information needed for matching the different types of files and would 

therefore include social security or taxpayer identification number, first and last name, 

gender, date of birth, and permanent address. 

The enrollment/term files would capture intensity of instructional effort for 

purposes of financial aid and loan deferment eligibility. Student level, courses attempted, 

and credit hours attempted would also be documented. Since the enrollment files would 

be used to generate the fall enrollment data, the records for those students that should be 
Chapter 4 — System Architecture 

56 

included in the fall census snapshot would need to be flagged.40 The schedule for 

submitting term enrollment files would vary depending upon the institutional calendar as 

documented in the Institutional Characteristics component. Typically, the data would be 

submitted quarterly for schools on the quarter system and three times a year for those on 

the semester system. All files would be merged into a composite file that documents all 

enrollments for the 12 months between July 1 and June 30. For schools with a quarter 

system, for example, files would be submitted for the enrollment periods July–

September, October–December, January–March, and April–June (see Table 2 below). In 

some cases, the summer term would lead the files for a given year, while in others it 

would trail at the end of the year, and both could possibly be permissible as long as this 

was documented in the IC file. The treatment of the summer term might vary depending 

upon the institution’s financial aid year for the submission of files. Institutions with 

continuous enrollment would need to submit files at least quarterly. 

Table 2. Schedule of data collection

Submission of 

files Data lock

Migration 

to PAS

Submission of

files Data lock

Migration 

to PAS

Submission of 

files Data lock

Migration 

to PAS

July

Submit April–June 

file

August

September X

Submit file (July

to June of 

previous year)

October

Submit 

July–September 

file (including

census flags) X

Submit file (July 

to June of 

previous year)

November X

December X XX

January

Submit October– 

December file 

(including census 

flags) X X

February

March X

April

Submit 

January–March 

file X

May

June X

July X

Enrollment Completions Financial aid

NOTE: PAS = Peer Analysis System.

Regardless of how often they were submitted and for what dates, the files would 

need to capture all activity within their official time period, and include flags that identify 

 

40 An alternative to a census flag would be to require a separate census file for enrollment; this option 

would be considered during the design TRP phase if a UR system were implemented. 
Chapter 4 — System Architecture 

57 

which students should be counted in the fall census and enrollment report.41 The files for 

July–September and October–December would include all students who should be 

counted in the official fall enrollment census date of October 15 that is used for the 

IPEDS EF component.42 These students’ records would be flagged to document that they 

should be included in this aggregate report. The October–December file would have to be 

filed and locked by the end of March at the latest, so that it could be migrated from the 

collection system to the PAS by the end of April. This timeframe would be possible 

because of the extensive editing and matching processes that would be built into the 

submission process. 

 The proposed schedule of file submissions would provide more flexibility in term 

reporting than is the case under the existing IPEDS components, revolving around a 

schedule that works for each institution. With this system, schools would have extended 

time to ensure that their aggregate reports pass edits and that their aggregate EF reports 

are accurate (see details about the edit process below). Data would be provided in the 

PAS at the end of April, whereas enrollment figures are currently being released at the 

institution–level at the end of May. The use of UR would help speed up the production of 

EF data, which are needed by schools to document official IPEDS enrollment figures for 

internal and external purposes. 

Completions file(s) would contain the date, type, and level of degree or 

certification award. In cases where transfer was the measurable outcome, the file would 

include whether the student is ready for transfer. The file would also include any 

exclusion codes that are required for maintaining the correct GRS cohort. Institutions 

would be given two choices for submitting completions data. With the first, they would 

submit one annual file at the end of September for all awards between July 1 and June 30. 

As an alternative, they could upload individual files for each commencement during this 

time period. All files would still be due in September. Once the data are locked in 

November, they would be used to populate aggregate reports. Cleanup would be done 

and the data would be migrated to the PAS at the collection–level in December. 

 

41 It is important, whatever number of files are submitted or schedule is adopted, that the composite result 

include all possible instructional activity within a year’s time, so that aid eligibility and loan deferment 

status could be determined in a timely manner and graduation, transfer, and persistence measures could be 

calculated accurately and with more precision than is currently the case. 

42 The two sets of files would include the records of all students who started a term that would be included 

in the October 15 census data count. 
Chapter 4 — System Architecture 

58 

 Price and financial aid data would be included in the aid file, along with 

dependency status and other fields necessary to accurately calculate the net price paid by 

the individual student. Given a financial aid year from July 1 to June 30, institutions 

would submit one annual file that includes all financial aid awards during this time 

period. The file would be uploaded at the same time that FISAP is due to FSA, on 

October 1. The file would be locked in December, processed with internal NCES edits, 

and net price information would be posted in January. Tables for IPEDS COOL would be 

created and posted in February. Although these data would be one year old, the financial 

aid data are needed in great detail for the calculation of net price. The current year’s 

published price would be collected as part of the Institutional Characteristics component 

in order to maintain more recent figures. 

In addition to the annual schedule of file submissions, there would need to be 

several data submissions as part of the initial year of implementation of a UR system. 

First, institutions would need to supply header records for all students, not just new 

students. Second, historical information on GRS student cohorts would be needed in 

order to perform the multi–year calculations needed for graduation and transfer rates. For 

example, four–year institutions would be required to upload up to six years of historical 

GRS data. Data would be needed for all established GRS cohorts for the different 

program lengths at each institution. The full, historical student enrollment and financial 

aid records for each cohort would not be necessary; only the current header record for 

every student in any active cohort, including those still enrolled, completers, and known 

transfers. The GRS cohort header record would include several fields not in other header 

records, such as first date of attendance, current status (enrolled, completer, or known 

transfer), date of most recent status change, and any exclusion flags that may apply. 

File Preparation and Submission 

A flow chart of the collection system follows that depicts the registration and 

coordination processes for the IPEDS coordination tree; file preparation before 

submission; online file submission; resolution of edit problems; locking of data files by 

the keyholder; and subsequent activities within the IPEDS collection schedule (figure 2). 

These stages are explained below in more detail. 
Chapter 4 — System Architecture 

59 

Figure 2. Registration, file preparation and submission, and post–file–lock activity 

Registration and

coordination

CEO appoints

keyholder

Keyholder appoints

proxies

Keyholder/coordinator reviews

file specifications, plans data

assembly

CEO contacted Coordinators contacted

Coordinator appoints

proxies

Coordination tree

established

File preparation

File preparation

Enrollment, fall

Enrollment,

winter

Enrollment,

spring

Enrollment,

summer

Financial aid

Degrees

conferred

Format data file

(XML or ASCII)

File submission

Execute NCES

edits locally

(optional)

No

Yes

Yes Edits passed?

No

Legend

Help

Desk

Collection

system PAS

UR system External data

source

See notes at end of figure. 
Chapter 4 — System Architecture 

60 

Figure 2. Registration, file preparation and submission, and post–file–lock activity —

 Continued 

File submission

Variable edits

(internal)

Collection estimates

generated

Edit report

No

No

External edits passed

Internal edits

passed

Yes

Yes

A

B

Student record match

subroutine

(SRM)

Help

Desk

Help

Desk

Help

Desk

Help

Desk

Collection

system

Upload to collection system

(UR file processor)

Resolve failures

Rerun edits

A

Keyholder locks

submission

Collection estimates

variable edits (internal

to collection system)

Collection estimates

prior–year edits

Estimates edits

passed

Keyholder resolves edit

problems (estimates)

B

Yes

Submission complete

Coordinator

review passed

No

Coordinator locks

submission

Yes

Post–file–lock

activity

Help

Desk Prior–year estimates

loaded from PAS

Help

Desk

Help

Desk

Help

Desk

Collection

system

Coordinator review

No

Legend

Help

Desk

Collection

system PAS

UR system External data

source

See notes at end of figure. 
Chapter 4 — System Architecture 

61 

Figure 2. Registration, file preparation and submission, and post–file–lock activity —

 Continued

Post–file–lock

activity

Physical migration of

unit record

submission

Delete UR data from

collection system

Migration and

perturbation of

estmates from

collection system to

PAS

Process

reports/queries

Quality control tables

Transfer to PAS

Derived/

composite

variable

processing

Update IPEDS COOL

from PAS

Update IPEDS DAS

from PAS

End IPEDS cycle

Collection

system

PAS

UR system

(collection and institution

levels)

(guest level)

PAS

Legend

Help

Desk

Collection

system PAS

UR system External data

source

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the

details of the system architecture would be decided after several Technical Review Panels as

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS offline

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis

System storage and analysis. The external data source icon refers to nonspecific offline data 

systems. The Help Desk icon refers to the IPEDS Help Desk. IPEDS COOL refers to College

Opportunities Online. IPEDS DAS refers to the IPEDS Data Analysis System. 
Chapter 4 — System Architecture 

62 

The registration process under a UR system would be similar to the current 

IPEDS framework. Registration is begun with a letter from NCES to the school CEO, 

who appoints an official IPEDS keyholder (see figure 2, registration and coordination). 

The keyholder may then appoint proxies to work with or view different data pieces. For 

those institutions that fall under an IPEDS coordination tree, the state or system 

coordinators also are contacted and these persons may in turn designate proxies within 

their organizations. The appointment of institutional keyholders and their proxies and 

coordinators and their proxies constitute the establishment of the “coordination tree.” All 

future IPEDS collections must follow this tree for submission and approval or locking of 

data. 

Under a UR system, in preparation for a new collection year, all keyholders and 

coordinators would review the file specifications and plans for assembling all of the 

IPEDS components. Then the process of preparing files would begin, including the 

student–related files for the UR system (figure 2, file preparation). These files would 

include enrollment, degrees conferred or completions, and financial aid, as well as a 

header file for every student who has one or more of these three types of records. File 

preparation would begin with the creation of a data file that conforms to the requirements 

and specifications from NCES in terms of what data need to be included and how they 

should be formatted. The data would need to be submitted in XML format, though 

AASCII text format might be permissible for some institutions during the implementation 

phase. 

The timing and sequence of data files for enrollment, completions, and financial 

aid would be designed so that institutional researchers and other school staff would have 

as much time and opportunity as possible to clean up the data before they become public. 

Obviously, if schools submit completions files more frequently than once a year, there 

would be additional time spent with these than if one composite file for the entire year 

were produced. 

Excel templates would be provided for schools requiring help in exporting XML 

data. NCES also would provide the source code that documents in Structured Query 

Language (SQL) the many edits that would be conducted at NCES once the data are 

submitted. As a preliminary step, some institutions might want to execute these edits 

locally on their own computer systems, although it would not be required under the UR 
Chapter 4 — System Architecture 

63 

system. If the local program passes edits, then the data would be ready for submission; if 

not, additional file preparation and editing would be needed. Because institutions would 

not have access to the complete database, the final IPEDS numbers would differ slightly 

from those calculated locally. Some institutions would likely choose not to run edits 

locally, preferring to submit the data files and then deal with the mismatches sent back to 

the keyholder. 

Edit Process 

In the next step of the collection process, keyholders would upload a data file to 

the collection system (figure 2, file submission). A wide range of levels and types of edits 

would be put in place for URs, and these would all need to be resolved and passed. Any 

corrections to the aggregate data would be made by submitting new UR files. The focus 

would remain on producing accurate results for the aggregate EF, C, GRS, SFA, and IC 

price components. However, the difference between how IPEDS works now and how it 

would work using URs is that the only way to correct reports under the UR system would 

be through submitting new URs, rather than submitting another summary file. Also, the 

editing process would admittedly be more complex, working at both the UR and the 

aggregate level. 

In the first step, edits for internal consistency would be run on the NCES server, 

resulting in an edit report. The IPEDS Help Desk would work with the keyholder to 

resolve any failures at this stage, until the data pass edits. 

Once the internal edits are passed, the data would proceed into the record–

matching phase. In this phase, the data would be physically transported to the permanent 

UR storage database and matched with other students’ records for discrepancies. For 

example, a school could classify a student as first–time, full–time freshmen, but NCES 

verifications across the entire student population might find that she/he took previous 

course work elsewhere. Discrepancies would need to be resolved and re–run until they 

are passed successfully. The process of matching student records is described below in 

more detail. After records are matched, then the UR collection data would be ready to be 

used to generate institutional, aggregate estimates. 
Chapter 4 — System Architecture 

64 

In the final stage of edits, collection estimates would be generated and compared 

with the previous year’s aggregate estimates from the PAS (figure 2, collection estimates 

variable edits). If the comparison of aggregate reports passed the edit process,43 then the 

keyholder would finalize or lock the submission and the submission would be considered 

complete. If a coordinator were involved as part of the coordination tree, then another 

level of review and approval would be necessary before the submission was considered 

complete. If the keyholder edits did not pass, or the coordinator review found problems, 

then the edit problems would again need to be resolved by the keyholder, requiring the 

resubmission of the data. 

Movement of Data to Permanent Storage and Aggregates to PAS

After the UR data pass edits, move through the coordination tree, and are locked, 

internal NCES processes would occur before the end of the collection schedule (figure 2, 

post file lock activity). The data would be physically transferred from the collection 

system to a special UR database. This would be done separately for each institution, so 

that UR data would reside on the collection server during only the brief time in which 

submissions and edits were being made. All UR data would then be deleted from the 

collection system. The permanent storage database would reside behind all firewalls and 

would not be connected to the Internet; it would not be connected directly to the 

collection server or to the database server that would house the PAS. Data would be 

transferred manually through media by secure NCES staff. No one outside of these 

approved NCES staff and contractors would have access to the permanent storage 

database for UR. 

 As part of the move from the collection system to the UR system, aggregate 

estimates would also be moved to the PAS at the collection level. Aggregate data from 

SFA and GRS would be subject to disclosure risk avoidance analyses and would be 

perturbed where required by IES/NCES policy to maintain confidentiality. At this stage, a 

variety of quality control reports and analyses would be conducted using the migrated 

PAS data to ensure their data integrity. The collection level estimates would be available 

 

43 In the PAS, keyholders would view aggregate data that have gone through the NCES edit process; 

redisclosures of NCES edit changes (including perturbation) would not be made to institutions. 
Chapter 4 — System Architecture 

65 

only to keyholders and their proxies at this point. After passing these quality controls, the 

estimates would be moved to the institutional level of the PAS, where they would be 

available to institutional level users for peer comparisons. 

As multiple UR files are submitted, new data would be made available after they 

go through the editing process (subject to the advice of design TRPs). Different estimates 

of aggregate totals might be calculated for institutional data, requiring adjustments to the 

PAS for UR transactions and corrections during the year (figure 3). These could be 

combined into a full year’s worth of transactions with various corrections for header 

information and other changes. Previous year edits would be run. If edits failed due to 

corrections, then the student records would be put through another student record 

matching process. If they passed edits, then aggregate institutional estimates would be 

recompiled and then transferred to the PAS. As a general rule, no more changes would be 

permitted until the following year, when schools would be able to resubmit prior year 

data to make corrections. This is one proposed model for dealing with mid–term 

adjustments; design TRPs would need to explore this issue to determine which 

mechanism might minimize burden on institutions while allowing necessary adjustments 

such as attendance intensity for enrollment verification. 

 Once the data were finalized through adjudication, the estimates would be moved 

to the guest level of the PAS and would be used to update two additional data tools, 

IPEDS COOL and the IPEDS DAS. Adjudicated, final files would follow per the 

required, standard IES/NCES review and approval process. With the availability of data 

on the IPEDS PAS, COOL, and DAS, the IPEDS cycle would end. Aggregate reports in 

the PAS could be expanded if additional derived variables were to be raised in design 

TRPs and approved by NCES. In this case, the new variables would be available at the 

collection level of the PAS. 

 Institutions would be able to view aggregate reports for each file at each stage of 

the collection process, including after the files were locked. Generally, it would take 

approximately one to two months to do cleanup of the data after they have been locked. It 

would take approximately two months after the end of the collection period for data to be 

moved to the institution–level access in the PAS. This timeframe is comparable to the 

current IPEDS workload for institutions and would need to be reviewed and refined as 
Chapter 4 — System Architecture 

66 

Figure 3. Adjustment of Peer Analysis System for unit record transactions and

dddddddddcorrections 

Adjustment of PAS for UR

transactions/corrections

Process PAS

queries for fullyear transactions/

corrections

Run previous–year

edits

Recompile aggregate

estimates

Student record match

subroutine (SRM)

Are there any edit

failures? Yes

No

Collection

system

Transfer aggregate

estimates to PAS

End PAS adjustments

PAS

UR system

Legend

Help

Desk

Collection

system PAS

UR system External data

source

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the 

details of the system architecture would be decided after several Technical Review Panels as

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS off–line 

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis

System storage and analysis. The external data source icon refers to nonspecific offline data

systems. The Help Desk icon refers to the IPEDS Help Desk. 
Chapter 4 — System Architecture 

67 

part of the TRP design phase if a UR system were implemented. Adjudication would 

continue to take longer to produce guest–level PAS files than many would prefer; 

however, this process is continually being improved to be as quick as possible given the 

levels of approval required. 

Process of Matching Records 

The process of matching student records with the larger UR database might 

happen at various stages of the collection system. First, matching of records would occur 

during the edit process after submission of data files by keyholders. Mismatches would 

be resolved by the school’s keyholder working with the IPEDS Help Desk. Special 

algorithms and “fuzzy matches” would be used to suggest logical, possible matches and 

how best to resolve discrepancies between records, so that time spent on reconciling 

mismatches would be minimized. Figure 4 illustrates that in matching student records, 

data would be physically moved from the collection system to the secure, UR system 

where they would be matched against prior records and submissions. 

When new files entered the system, they would be checked against existing 

records in the UR database; if there were no match, a student would be confirmed as new 

to the system. If there was a match, a student record would be confirmed as continuing, 

unless the previous work was concurrent high school enrollment and the student qualified 

as a first–time freshmen. The record would be flagged and an edit report would be 

created and sent to the keyholder for review in the collection system. With the assistance 

of the Help Desk, the keyholder would either correct a flagged record or verify that a 

student was new. Keyholders would go through various processes, including reviewing 

edit reports; validating, verifying, or correcting records; and submitting the reconciled 

data file. After this, the data would once again be physically transported to the UR 

system, where flagged edits would be resolved and edits cleared. Then, the data would be 

moved back physically to the collection system, where all student matching edits would 

be cleared and the process of matching would be finished as part of this subroutine. 

Other mismatches between record sets would need to be verified by keyholders 

working with the Help Desk, such as a financial aid record for which there was no 

enrollment record (this could occur for several reasons, including the late post–processing 
Chapter 4 — System Architecture 

68 

Figure 4. Student record match subroutine 

Student record match

subroutine (SRM)

Physically

transport

submitted UR

from collection

system to

permanent UR

system

Match newly

submitted records

against prior

submissions

Nonmatching

records are added

to UR as new

students

Record flagged for

keyholder followup

Is there a

match for

processed

record?

Is student

marked as

continuing or as

new?

No

New

Edit report record

developed

Yes

Existing

Collection

system

Physically

transport edit

report from UR

database to

collection system

Keyholder reviews

edit report

Keyholder

validates/verifies

or corrects flagged

records

Keyholder submits

reconciliation file

Physically

transport

reconciliation

from collection

system to

permanent UR

system

Resolve flagged

records, clear

edits

Clear student

matching edits

Physically

transport cleared

edit report to

collection system

End subroutine

Collection

system

Collection

system

UR system

UR system

Collection

system

Help

Desk

Help

Desk

Help

Desk

Help

Desk

Legend

Help

Desk

Collection

system PAS

UR system External data

source

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the

details of the system architecture would be decided after several Technical Review Panels as

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS offline

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis 

System storage and analysis. The external data source icon refers to nonspecific offline data

systems. The Help Desk icon refers to the IPEDS Help Desk. 
Chapter 4 — System Architecture 

69 

of an award amendment, which is done after a student has already graduated). A similar 

process might also occur if the PAS needed to be adjusted for UR corrections. 

 As described previously, NCES has extensive experience in matching URs from 

different sources as part of NPSAS. It is estimated that approximately 4 to 6 percent of 

such file merges result in mismatches in records that must be resolved. For an institution 

with a headcount enrollment of 10,000 students, there could conceivably be 10,000 

header records and 10,000 term enrollment records for a given file submission. At a 4 to 

6 percent mismatch rate, this would result in approximately 400 to 600 records that 

would need to be resolved. However, there would be plenty of time for schools to edit or 

validate the matches for these records within the schedule of file submissions. 

 The actual increase in burden with the implementation of URs would be the time 

necessary for resolving these 400 to 600 records. Some institutions consider estimates of 

the time staff would spend merging records and creating draft summary reports locally to 

be part of the additional burden of a UR system. Many TRP members believed that the 

student matching routine would be time consuming and difficult. However, this burden of 

verifying the outcome and matching records locally would not be designed or required as 

part of the UR system, but rather would be a choice of institutions to conduct as an 

additional process. During the TRP design phase, NCES would work to ensure that there 

is adequate time for editing and matching for submissions. 

 

Issues in the Collection Process 

 In utilizing the experience and knowledge of SHEEOs and state systems, of TRP 

meeting panelists, and of others who have provided comments and feedback as part of the 

feasibility study process, there would be some important data and collection issues to 

address if IPEDS student URs were implemented. Some of these are highlighted below. 

• Working with term dates. The calculation of credit hours/contact hours 

and instructional intensity would be difficult if it must take into account 

different types of terms with different start and stop dates. A methodology 

would need to be developed to allow for some kind of agreed–upon 

weighting scheme, so that measures of output are comparable and could be 

converted across types and time frames.
Chapter 4 — System Architecture 

70 

• Extracting data. Some schools might utilize vendor products to extract the 

data for IPEDS URs about students, financial aid, and completions. Other 

schools might involve different offices and require coordination between 

admissions, financial aid, registrar, bursar, and other functions. Each 

system might have automatic extracting capability, but be designed for 

different purposes that are predominantly operational in nature versus 

geared for federal reporting and analysis. The IPEDS UR extracts would 

need to have identical census dates and business rules for what records to 

include, so that they could be merged appropriately to produce the 

required data.

• Problems in merging IPEDS data files. With this system of data files, 

NCES would need to match records between files for reporting analyses. 

For example, completions records would be matched against header files 

to obtain demographic information. Financial aid and completion records 

would be matched against enrollment files to obtain enrollment eligibility 

and cohort information. If records in one or more merged files were 

missing, the error rate would increase and there would be increased need 

for institutions to work with the IPEDS Help Desk to resolve the 

mismatches. Therefore, at the outset, training would be provided to ensure 

that extracts are designed with the merging of data files in mind. 

Institutions would be given the SQL code with which to do these types of 

merges. For those that rely on vendors to automatically generate these files 

in required IPEDS format, there would be software development involved. 

• Timing of reporting. Institutions responding to IPEDS would have their 

official fall enrollment, graduation rates, persistence and retention, and 

financial aid averages calculated for them by the NCES software. It is 

important that these data be collected and disseminated in a timely manner 

so that this process does not impact important deadlines for other types of 

submissions, such as to SHEEOs or admissions guide publishers. The UR 

system would be designed so that it ensures that reporting is reasonable, 

accurate, timely, and meets other reporting needs besides those of NCES. 
Chapter 4 — System Architecture 

71 

• Change in the locus of reporting. NCES would provide institutions with 

the SQL code and data structures necessary to calculate aggregate IPEDS 

reports locally. Some schools would want to do this before submitting the 

data to IPEDS. However, since some of the data would be revised based 

on redisclosures (such as for the corrected determination of first–time, 

full–time freshmen status), some schools might not be able to replicate this 

calculation entirely locally, because they cannot access UR data for all 

schools. This is not very different from the changes that are made as part 

of data migration from collection to the PAS to preserve confidentiality 

through perturbation. Still, this represents a potential change in the locus 

of control for reporting. 

• The need for different streams of data. In designing a system that brings 

together data from different offices on campus at different times for 

different purposes, one possibility would be to stream these data directly 

from those offices to NCES. In this case, enrollment and completions data 

would be submitted by the registrar, financial aid data from the financial 

aid office, and price data from the bursar. Schools would not have to 

merge record sets locally, but would work with NCES and the IPEDS 

Help Desk after submission to resolve mismatches. Institutions would 

benefit from more sophisticated and peer–reviewed federal edit and 

matching processes, in order to provide much more accurate information 

for consumers and policy makers than they would be capable of doing 

themselves due to staffing and resource constraints. In this model, the 

streaming of data would help build and strengthen colleges’ and 

universities’ capacity for institutional research.

Redisclosures and Other Data Uses 

 As mentioned in previous chapters, the proposed UR system includes several 

redisclosures that would need to be authorized by the legislation creating UR. In addition, 

there are other uses of a UR system that would involve matching or sampling of student 
Chapter 4 — System Architecture 

72 

records. In order to address privacy issues, it is proposed that students would have the 

right to “opt out” of some of these uses. 

One of the proposed redisclosures—the redisclosure of mismatches of student 

records back to the keyholder for follow up—would be necessary for the accurate 

functioning of a UR system. As mentioned above, flagged student records would be sent 

to the keyholder after data submission, and the keyholder would work with the Help Desk 

to resolve the mismatches before the data were locked. 

The second proposed redisclosure would involve periodic enrollment verification 

to NSLDS (figure 5), for which students receiving federal student loans have already 

consented.44 After each collection of enrollment data passed internal and external edits 

and was transferred to the UR permanent storage database, a database coming from an 

external FSA data source would be physically transported to the UR system, where there 

would be an attempt to match records from the external database to the URs. For those 

records that matched, flags would be created and a file of verified enrollments would be 

built. For records that do not match, the data would be moved to the collection system 

where the IPEDS keyholder would be notified by email and asked to resolve the 

mismatches and edit failures. After these were resolved, the data would be replaced in the 

UR system. The records with matches would be flagged and an enrollment verification 

file would be built for these students. Enrollment verification files would be physically 

transferred to FSA for processing and the FSA records in the UR collection system would 

be deleted. 

The redisclosure of subsequent enrollment information back to the IPEDS 

keyholder would provide a benefit to institutions to help mitigate the burden of 

submitting UR data; institutions would be “getting something back” from the process 

besides mandated compliance. This redisclosure would allow institutions to gain 

information about students who leave the institution. 

 

44 The proposal is for enrollment verification once per term, which OPE has said will be acceptable. Some 

institutions may want to report enrollment more often, and they would be allowed to do so. 
Chapter 4 — System Architecture 

73 

Figure 5. Enrollment verification for the National Student Loan Data System 

NSLDS Enrollment

verification

Development of base

file for matching

Physically transport to

UR database

Attempt to match

individual records

Build file of verified

enrollments

Physically transfer to

FSA for processing

Record

matches No

Yes

Physically transport

mismatched records

to collection system

(should only occur for

AKA records)

E–mail to keyholder

Keyholder resolves

mismatch edit failures

Physically transport

result file to UR

database

(create 'AKA' record

for future matches)

Delete UR records from

the collection system

Build file of records

failing to match

Collection

system

Help

Desk

Flag matching records

UR system

UR system

UR system

External data

source

External data

source

Legend

Help

Desk

Collection

system PAS

UR system External data

source

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the

details of the system architecture would be decided after several Technical Review Panels as 

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS offline

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis 

System storage and analysis. The external data source icon refers to nonspecific offline data

systems. The Help Desk icon refers to the IPEDS Help Desk. AKA means ‘Also known as’. 
Chapter 4 — System Architecture 

74 

One possible conceptualization of these subsequent enrollment redisclosures is 

presented in figure 6. The redisclosure would be conducted once a year using the 

previous year’s enrollment and completions data. NCES would identify an institution’s 

previous year enrollment data file in the UR database. For each institution, queries would 

be run for the previous year’s students to check on subsequent enrollment activity. 

Directory level information would be compiled from the UR system, including basic 

information about persistence and completion during this one–year period45— including 

the subsequent school UNITID, the students’ enrollment status, and the date and type of 

any award. The data would be physically transported from the UR system to the 

collection system. IPEDS keyholders would be notified by email that a data file of 

subsequent enrollment information for their students would be available for a limited 

period of time to download. A system would be developed for keyholders to access the 

redisclosed data in a secure environment so that they can then match them to internal 

records, another reason for ensuring that the matching process is as successful as 

possible. The file would be deleted after two weeks from the collection system. The exact 

process would need to be designed at a future TRP meeting, if a UR system were 

authorized and implemented.46 

 The data would be redisclosed back to the original institution only if each 

student’s record does not indicate that she/he has opted out of the redisclosure. If the 

student has opted out, then there would be a flag documenting this response, with no 

additional data.47 Given privacy concerns, institutions would be required to inform 

students about the use of these data for this purpose and establish a campus–wide 

mechanism for students to officially opt out of the redisclosure if they choose to do so. 

This data element would probably need to be stored as part of the header record, which 

could be overwritten with future submissions. 

 

45 Redisclosure of student information to the original institutions could take place over a longer time period 

if this was decided by a future design TRP and NCES. 

46 This process would include any potential restrictions to the use of redisclosed data by institutions and 

state coordinators. 

47 Note that institutions would still benefit from aggregate estimates generated through the UR system (for 

example, the percentage of student who earned a degree at a subsequent institution) that included all 

students, and measured what happened to students over longer periods of time. 
Chapter 4 — System Architecture 

75 

Figure 6. Subsequent enrollment disclosure to institutions 

Subsequent enrollment

Create unit record

match of directory–level

data

Process queries based

on prior–year

enrollment

(one institution at a

time)

Physically transport

data file from UR

system to collection

system

Start countdown clock

Keyholder downloads

file

File deleted after two

weeks

End subsequent enrollment

E–mail keyholder

Identify previous year

data file in UR system

Collection

system

UR system

Legend

Help

Desk

Collection

system PAS

UR system External data

source

 

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the

details of the system architecture would be decided after several Technical Review Panels as 

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS offline

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis 

System storage and analysis. The external data source icon refers to nonspecific offline data

systems. The Help Desk icon refers to the IPEDS Help Desk. 
Chapter 4 — System Architecture 

76 

Other uses of a UR system would include the generation of aggregate program 

reports for the Office of Postsecondary Education (OPE) in order to assess the success of 

student financial aid programs (figure 7). OPE staff would create a program file from the 

COD external data source for aid recipients and specify the comparison groups and 

outcome variables it wished to have reported. After NCES received the records, it would 

physically transport the external data file to the secure UR storage database, where query 

reports would be processed to match the records. NCES would create program reports 

with aggregate measures, after ensuring that cell sizes were large enough so that no 

individual could be identified and if necessary perturbing the data. The reports would be 

physically transported from the UR server to OPE for further analysis and dissemination. 

A similar process could be performed for other OPE programs. 

 Samples of students for NCES sample surveys, such as NPSAS and BPS, could 

be drawn directly from the UR database. The current process for sample surveys involves 

drawing a sample of institutions, which are required to send UR data back for their 

students. The sample surveys would continue to survey students directly and merging in 

data from other ED databases. Figure 8 documents the process of creating NPSAS, BPS, 

and Baccalaureate and Beyond (B&B) sample files from the UR system. A sample size 

would be specified and a sample drawn from the UR system. After drawing the sample, 

perturbing data, and data file, the file would be appended to the sample survey database 

where the survey would be completed. Students would still have the possibility of opting 

out of NCES sample surveys, as they do now. 
Chapter 4 — System Architecture 

77 

Figure 7. Program reports for the Office of Postsecondary Education 

Finish OPE

program reports

OPE creates program

file from COD

Specification of

comparison group

Specification of

outcome variables

Process reports/queries

(create OPE records in

UR database)

Transport program to

UR database

Disclosure analysis for

small cells

Create report

Perturb cells as

necessary

OPE

program reports

Transport perturbed

report to OPE

Store perturbed data

with flags

External data

source

UR system

UR system

Legend

Help

Desk

Collection

system PAS

UR system External data

source

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the

details of the system architecture would be decided after several Technical Review Panels as

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS offline

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis

System storage and analysis. The external data source icon refers to nonspecific offline data 

systems. The Help Desk icon refers to the IPEDS Help Desk. COD refers to Central Processing

System. 
Chapter 4 — System Architecture 

78 

Figure 8. NCES sample survey files (NPSAS, BPS, and B&B) 

NPSAS/BPS/B&B

sampling files

Process sample data/

queries

Sample specifications

Disclosure analysis

Finish NPSAS/BPS/

B&B

Specify sample size

and draw sample

Create analysis record

for each student in

sample

Perturbation

Create

data/queries

(weights)

Physically transport

perturbed sample

survey database

Store original

data/queries

(weights)

UR system

UR system

External data

source

Legend

Help

Desk

Collection

system PAS

UR system External data

source

 

NOTE: Flowchart is for a proposed UR system; if such a system was authorized and funded, the 

details of the system architecture would be decided after several Technical Review Panels as

well as a field test. The collection system icon refers to the IPEDS collection system for

aggregate and unit record data collection. The UR system icon refers to the IPEDS off–line 

database unit record data storage and analysis. The PAS icon refers to the IPEDS Peer Analysis

System storage and analysis. The external data source icon refers to nonspecific offline data

systems. The Help Desk icon refers to the IPEDS Help Desk. 
Chapter 4 — System Architecture 

79 

Training 

Training of IPEDS keyholders and coordinators is important to ensure that the 

data are submitted correctly and meet the parameters of the data collection. Currently, 

numerous training opportunities exist in the postsecondary education community to help 

practitioners learn the skills of using and merging datasets. For example, the Association 

for Institutional Research (AIR) conducts “train the trainer” sessions generally as part of 

state and regional conferences, which allow institution staff to attend one close to their 

institution.48 In addition, web–based tutorials are currently being developed to provide 

instruction for gathering data for IPEDS reporting, entering data into the data collection 

system, using the Peer Analysis System to produce data for analysis, and other functions 

to assist data providers and users. The American Association of Collegiate Registrars and 

Admissions Officers (AACRAO) also hosts IPEDS training sessions to inform members 

of changes to IPEDS and related issues, and EDUCAUSE conducts IT training. The need 

for these types of training would increase substantially if a UR system were to be 

implemented. Training would be extensive and involve multiple levels of institutional 

staff as well as both web–based and in–person delivery models. Other types of 

institutional staff, such as information technology professionals, may require training as 

they may become more involved in the process of IPEDS data submission at the 

institutional level. 

Help Desk 

Under the current IPEDS collection system, institutional keyholders can contact 

the IPEDS Help Desk to help resolve questions about data definitions, procedures, and 

technical problems. The Help Desk would become even more important should a UR 

system be implemented. Help Desk staff would be trained to answer questions from 

keyholders on various aspects of the data collection process. In addition, the Help Desk 

would ask keyholders to resolve mismatches in the URs, working closely with the 

keyholders to assist in this process. The proposed UR system envisions having the Help 

 

48 These sessions are funded through a subcontract with RTI International, which has a contract with 

NCES for this and other purposes. 
Chapter 4 — System Architecture 

80 

Desk open throughout the year, whereas currently it is open around the dates of the three 

collection periods. 

Software 

The existing system for IPEDS collection and dissemination is maintained in a 

Microsoft Windows software environment that incorporates Active Server Page (ASP) 

scripting, the Visual Basic scripting language, and Microsoft SQL Server. In planning for 

the possibility of UR reporting, a number of requirements need to be addressed for 

software and hardware. Specifically, the UR collection software would need an adequate 

database management package capable of holding millions of student records per year; 

security protocols that include Secure Socket Layer (SSL), digital certificates, and 

password protection; and load balancing software that utilizes multiple web and database 

servers to prevent overload and effectively and efficiently handle large data transactions. 

These needs would come in addition to the current PAS environment, which would 

continue to expand with the addition of more years of IPEDS aggregate data files and 

new data elements. 

Hardware 

 For one year of UR data, there would theoretically be four enrollment files, one 

completion file, and one financial aid file for each of the estimated 6,700 Title IV 

institutions. Disk storage space is posited to be approximately 50 GB for the first year. 

This includes room for the historical GRS data files that are needed and header files for 

all students currently in the system. The header file would remain at an estimated 4 GB 

per year with additional new students, with the number of term records growing slightly 

each year for a total of approximately 270 GB of storage needed by the end of seven 

years. In order to accommodate this growth, two database servers would be needed, each 

with 300 GB of capacity. The first server would be used for collecting the data, the 

second for securely storing the URs away from the Internet in final form. 

 The existing IPEDS collection database server does include load balancing. It 

might be necessary to split the UR database across two SQL Servers. The IPEDS 
Chapter 4 — System Architecture 

81 

collection system for the five non–unit record components (S, SA, EAP, Finance, and IC) 

would be given its own database server. It has also been suggested that a separate 

database server be installed to house the IPEDS PAS, which grows annually at more than 

1.5 Gigabytes (GB) per year, and the NCES DASOL applications (which include the 

postsecondary sample surveys and the IPEDS DAS). While the scalability of Microsoft 

SQL Server for handling hundreds of millions of records in the future is worthy of 

discussion, numerous examples of similar enterprise–wide solutions are in place in this 

environment across the country. 

 For the database server that is currently used for the IPEDS collection, the 

collection developer has estimated future growth of 1.5 GB per year. With new reports 

and tables that would be exported to other agencies for redisclosure, approximately 50 

GB of disk space would be needed on this server. The PAS database server would 

continue to grow, with the accretion of larger and more complex files, requiring 

approximately 100 GB over the next seven years. 

 Overall, the implementation of IPEDS URs could require four dedicated database 

servers—one for collecting and another for storing the data separately; one for the 

continued collection of the nonstudent IPEDS components; and a fourth for 

dissemination of IPEDS via the PAS and the DASOL. 
82 
83 

Chapter 5—Conclusions 

 

This report has examined the feasibility of implementing a student UR system to 

replace the student–related components of IPEDS. As part of the feasibility study, an 

architecture and flow of operations for a proposed UR system, as well as a list of 

potential data elements that might be collected under such a system, were developed and 

described. In addition, the feasibility study solicited input from states and state systems; 

private associations of colleges and universities; institutional researchers, registrars, and 

financial aid officers; and other stakeholders such as the postsecondary education 

association community and federal agencies. 

As this report has outlined, a central question for a UR system is “Could it be 

done?” The answer to this question is essentially technical. Have the information 

technologies and infrastructures at the campus and state levels matured, could the current 

IPEDS web–based reporting system be adapted to UR, and would there be adequate 

technical and legal protections in place at IES/NCES? The report has addressed some of 

the technical and system problems associated with the design and development of a new 

IPEDS UR system. At the technical level, a UR system could be done at most institutions 

given time for implementation, and the problems associated with development of such a 

system are manageable. 

The feasibility study also addressed the “Should it be done?” question, providing 

a framework for the discussion of issues inherent in this question. These issues revolve 

around several areas of concern, which would need to be addressed and resolved in the 

design phase of a UR system should policymakers decide to authorize and fund a UR 

system. 

Privacy is the first and more fundamental area of concern. Does the federal 

interest in collecting better data “trump” the right of students to control information about 

their enrollment, attainment, and financial aid? The confidentiality of student data would 

be protected to the extent allowable in the legislation under which IES/NCES operate.

Second, there would be costs and burdens to institutions associated with 

implementation, especially in the initial years. However, over $80 billion in federal 
Chapter 5 — Conclusions 

84 

student financial aid presently flows to postsecondary institutions. A decision would need 

to be reached as to whether these direct federal benefits to institutions are sufficient to 

counterbalance short–term concerns about cost and the burden of implementation, or 

whether additional funds are needed. 

Third, a UR system would require institution–level coordination, involving the 

cooperation of registrars, institutional research, IR, and financial aid offices on campuses; 

with the need to assign or perhaps hire staff. A UR system might bring fundamental 

changes to state coordination structures and the management of the data flow on 

enrollment, completions, and student aid. 

A UR system would also involve issues with technological capacity and the 

timing of data collection and implementation. Although changes in technology could be 

daunting for some institutions, mechanisms would exist to help institutions with 

reporting. The operational timing of data collection could pose complications, but would 

be addressed during the design phase of UR implementation with input from institutions. 

This feasibility study has outlined areas of federal interest: better information for 

informed consumer decisions, including the improved calculation of net prices; and more 

accurate measures for institutional accountability and program effectiveness, including 

enrollment, persistence, transfer, and attainment rates by program of study. Policymakers 

would be able to monitor in real–time federal student aid programs (such as Pell Grants) 

and variations in aid packaging. The study also has attempted to highlight some potential 

benefits to institutions, states, systems, consumers, and other users of NCES data. 

The study did not attempt to address every challenge or make recommendations 

about how each aspect should be addressed. Nor did the report document specific 

organizational positions regarding the obstacles a UR system might face. Rather, it 

provided a framework for policymakers to understand the potential costs and benefits of a 

UR system as they discuss whether it should be considered. 

The central defining question of the feasibility of a UR system in IPEDS is not a 

“could” question. It is a “should” question, asking whether the federal government should 

develop a system that is based upon individually identifiable information about 

enrollment, financial aid, and attainment. This system would, for the first time, give 

policymakers and consumers much more accurate and comprehensive information about 
Chapter 5 — Conclusions 

85 

postsecondary education in this country. Some of the benefits of UR include the 

collection of new data that would measure the success rates of students at institutions to 

which family and federal student aid monies flow, provide more accurate consumer 

guidance, and improve federal programs that support those families and students. In 

addition to benefits, the feasibility study found a number of significant issues that would 

need to be overcome before a UR system could be implemented, including objections 

about student privacy, confidentiality of data, new institutional burdens, coordination 

within and outside of institutions, and timing issues. Whether a UR system should be 

authorized, appropriated, and implemented is left to policymakers to decide, given the 

benefits and constraints examined in this study. 
86 
87 

References 

Association for Institutional Research (AIR). (2000). AIR Alert: Student Right–to–Know 

Act and IPEDS Graduation Rate Survey. November. Available online at: 

http://www.airweb.org/page.asp?page=118. 

________. (2004a). AIR Alert #26: IPEDS Student Unit Record Data Feasibility Study. 

October. Available online at: http://www.airweb.org/page.asp?page=670. 

________. (2004b). AIR Alert #26 Update 1: Proposed IPEDS Student Unit Record Data 

Feasibility Study. November. Available online at: 

http://www.airweb.org/page.asp?page=711. 

Berkner, L., He,S., and Cataldi, E.F. (2002). Student Financing of Undergraduate 

Education: 1999–2000 (NCES 2002–167). U.S. Department of Education, 

National Center for Education Statistics. Washington, DC: U.S. Government 

Printing Office. 

Carey, K. (2004 May). A Matter of Degrees: Improving Graduation Rates in Four–Year 

Colleges and Universities. Washington, DC: The Education Trust. 

Choy, S. (2002). Findings from the Condition of Education 2002: Nontraditional 

Undergraduates. (NCES 2002–012). U.S. Department of Education, National 

Center for Education Statistics. Washington, DC: U.S. Government Printing 

Office. 

College Board. (2004). Trends in College Prices 2004. Washington, DC: College Board. 

Cunningham, A. F. and Merisotis, J.P. (forthcoming). Changes in Patterns of Prices and 

Financial Aid (NCES 2005–153). U.S. Department of Education, National Center 

for Education Statistics. Washington, DC: U.S. Government Printing Office. 

Ewell, P., Schild, P.R., and Paulson, K. (2003). Following the Mobile Student: Can We 

Develop the Capacity for a Comprehensive Database to Assess Student 

Progression? New Agenda Series. Bloomington, IN: Lumina Foundation for 

Education.
References 

88 

Horn, L., Chang–Wei, C., and Berker, A.. (2002). What Students Pay for College: 

Changes in Net Price of College Attendance Between 1999–2000 (NCES 2002–

174). U.S. Department of Education, National Center for Education Statistics. 

Washington, DC: U.S. Government Printing Office. 

JBL Associates. (2004). JBL Associates Achieving the Dream Data Collection Project: 

Reporting System Requirements. Unpublished document, October 6. 

L’Orange, H. (2004). E–mail survey of state SHEEO and system offices in the 

SHEEO/NCES Network, conducted December 17. 

National Center for Education Statistics. (2002a). Statistical Standards. Available online 

at: http://nces.ed.gov/statprog/2002/stdtoc.asp. 

________. (2002b). Classification of Instructional Programs: 2000 Edition. (NCES 

2002–165.) U.S. Department of Education, National Center for Education 

Statistics. Washington, DC: U.S. Government Printing Office. 

National Postsecondary Education Cooperative (NPEC). (2001 April). Student Transition 

Data Systems. Report of the NPEC Working Group. Washington, DC. 

 ________. (1998). Unit Record Versus Aggregate Data: Perspectives on Postsecondary 

Education Data Collection, Retention, and Release. Final Report of the Working 

Group on Unit Record Data Versus Aggregate Data. Washington, DC: NPEC, 

April. 

Peng, S. (1999). Integrated Postsecondary Education Data System (IPEDS): An 

improved system. Final Report of the NCES Taskforce for IPEDS Redesign. U.S. 

Department of Education, Washington, DC: National Center for Education 

Statistics. 

Pfieffer, J. (2003). Overview of Federal Laws Pertaining to Sharing Individually 

Identifiable Educations Records. Tallahassee, FL, May 22: Florida Department of 

Education. 

Seastrom, M. (2004). Confidentiality and Data Access at NCES. Unpublished document. 

Voorhees, R. and Barnes, G. (2003). Data Systems to Enhance Teacher Quality. Denver, 

CO: State Higher Education Executive Officers (SHEEO). 
Appendix A—Technical Review Panels 

 Page 

Technical Review Panel #1, Agenda...................................................................................... A-2 

Technical Review Panel #1, List of Participants.................................................................. A-4 

Technical Review Panel #2, Agenda.................................................................................... A-11 

Technical Review Panel #2, List of Participants................................................................ A-13 

Technical Review Panel #3, Agenda.................................................................................... A-21 

Technical Review Panel #3, List of Participants................................................................ A-23 
Appendix A — Technical Review Panels

A-2

AGENDA 

IPEDS STUDENT UNIT RECORD FEASIBILITY STUDY 

TRP #1 (STATES, SYSTEMS, & PRIVATE ASSOCIATIONS) 

October 28-29, 2004 

Hyatt Arlington 

Arlington, VA 22209-9990 

Thursday, October 28

8:00 a.m. - 8:30 a.m. Continental Breakfast 

8:30 a.m. - 8:45 a.m. Meeting Begins 

8:45 a.m. – 9:00 a.m. Introduction to the Feasibility Study—Dennis Carroll, NCES 

9:00 a.m. – 9:30 a.m. Co-Chair Introductions—Hope Williams, North Carolina 

Independent Colleges and Universities; 

 Tad Perry, South Dakota Board of Regents 

9:30 a.m. – 10:30 a.m. Existing State Unit Record Systems—Tad Perry, South 

Dakota Board of Regents; J. Michael Mullen, West Virginia 

Higher Education Policy Commission; John Porter, SUNY 

System Administration 

10:30 a.m. – 10:45 a.m. Break 

10:45 a.m. – 12:00 p.m. Re-disclosures—Hope Williams 

12:00 p.m. – 1:30 p.m. Working lunch 

1:30 p.m. – 2:30 p.m. Burden—Gary Cox, Association of Independent Kentucky 

Colleges & Universities 

2:30 p.m. – 3:30 p.m. First year Implementation—Dennis Carroll 

Field test—Cathy Statham, NCES 

3:30 p.m. – 3:45 p.m. Break 

3:45 p.m. – 4:45 p.m. Wrap-up discussion 

Friday, October 29

8:00 a.m. – 8:30 a.m. Continental Breakfast 

8:30 a.m. – 8:45 a.m. Meeting Begins 

8:45 a.m. – 10:00 a.m. Review of previous discussion—John Milam, HigherEd.org 
Appendix A — Technical Review Panels 

A-3 

10:00 a.m. – 10:30 a.m. On-going discussion 

10:30 a.m. – 10:45 a.m. Break 

10:45 a.m. – 12:00 p.m. Continued follow-up discussion 

12:00 p.m. – 1:30 p.m. Working lunch and Summary statements—Hope Williams & 

Tad Perry 

2:00 p.m. Adjourn 
Appendix A — Technical Review Panels

A-4

TRP1 Participant List 

 

Frank Balz 

Vice President for Research and Policy 

Analysis 

National Association of Independent 

Colleges and Universities 

1025 Connecticut Ave., NW, Suite 700 

Washington, DC 20036 

202-785-8866 

202-835-0003 

frank@naicu.edu 

Sam Barbett 

Mathematical Statistician 

National Center for Education Statistics 

Postsecondary Institutional Studies Program 

1990 K Street NW, Room 8113B 

Washington, DC 20006 

202-502-7305 

202-502-7460 

Samuel.Barbett@ed.gov 

Gary Barnes 

Independent Contractor 

University of North Carolina System 

217 Weaver Mine Trail 

Chapel Hill, NC 27517 

919-942-8098 

gbarnes1@mac.com 

Charles Benil 

Information Systems Director 

Maryland Higher Education Commission 

Office of Information Systems 

839 Bestgate Rd. Suite 400 

Annapolis, MD 21401 

410-260-4524 

410-260-3203 

cbenil@mhec.state.md.us 

David Bergeron 

Director, Policy and Budget Development 

Staff 

Office of Postsecondary Education 

U.S. Department of Education 

1990 K St. NW 

Washington, DC 20006 

202-502-7815 

202-502-7873 

david.bergeron@ed.gov 

Dan Boehmer 

President 

National Student Clearinghouse 

13454 Sunrise Valley Drive, Suite 300 

Herndon, VA 20171 

703-742-4200 

boehmer@studentclearinghouse.org 

Violet Boyer 

President & CEO 

Independent Colleges of Washington 

600 Stewart St. #600 

Seattle, WA 

206-623-4464 

206-625-9621 

violet@ICWashington.org 

Camille Brown 

M.I.S. Manager 

South Carolina Commission on Higher 

Education 

Finance, Facilities & M.I.S. 

1333 Main St., Suite 200 

Columbia, SC 29201 

803-737-2149 

803-737-2297 

cbrown@che.sc.gov 
Appendix A — Technical Review Panels 

A-5 

Susan Broyles 

Program Director 

National Center for Education Statistics 

1990 K Street, NW, Room 8113C 

Washington, DC 20006 

202-502-7318 

Susan.Broyles@ed.gov 

Ginny Bugg 

President 

Alabama Association of Independent 

Colleges and Universities 

2326 Highland Ave. 

Birmingham, AL 35209 

205-252-6254 

205-252-6256 

gbugg@zebra.net 

Dennis Carroll 

Associate Commissioner 

National Center for Education Statistics 

Postsecondary Studies Division 

1990 K St. NW, Room 8112 

Washington, DC 20006 

202-502-7323 

202-502-7460 

Dennis.Carroll@ed.gov 

Shu-Ling Chen 

Director of Institutional Research 

University of Massachusetts 

President's Office 

One Beacon St., 26th Floor 

Boston, MA 02108 

617-287-7000 

schen@umassp.edu 

John Childers 

President & CEO 

Consortium of Universities of the 

Washington Metro Area 

Office of the President 

One Dupont Circle, NW, Suite 200 

Washington DC 20036 

202-331-8080 

202-331-7925 

childers@consortium.org 

Melanie Corrigan 

Associate Director 

American Council on Education 

Center for Policy Analysis 

1 Dupont Circle, NW 

Washington, DC 20036 

202-939-9554 

202-785-2990 

Melanie_Corrigan@ace.nche.edu 

Gary Cox 

President 

Association of Independent Kentucky 

Colleges and Universities 

(AIKCU) 

484 Chenault Rd. 

Frankfort, KY 40601 

502-695-5007 

502-695-5057 

gary@mail.aikcu.org 

Alisa Cunningham 

Director of Research 

Institute for Higher Education Policy 

1320 19th St, NW, Suite 400 

Washington, DC 20036 

202-861-8223 

202-831-9307 

alisa@ihep.org 
Appendix A — Technical Review Panels

A-6

Kenneth Dalley 

Assistant Director Educational Data Center 

Texas Higher Education Coordinating Board 

Planning and Information Resources 

P.O. Box 12788 

Austin, TX 78711 

512-427-6306 

512-427-6447 

Kenneth.dalley@thecb.state.tx.us 

Gloria Dávila-Casasnovas 

Policy and Planning Director 

Puerto Rico Council on Higher Education 

Policy and Planning Department 

P.O. Box 19900 

San Juan, PR 00910-1900 

787-641-7100 

787-721-6447 

gl_davila@ces.gobierno.pr 

Patricia Duncan 

Director 

Devry 

State and Provincial Licensing 

2149 W. Dunlap Ave 

Phoenix, AZ 85021-2995 

630-706-3100 

630- 571-2389 

pduncan@devry.com 

Peter Ewell 

Vice President 

National Center for Higher Education 

Management Systems 

(NCHEMS) 

P.O. Box 9752 

Boulder, CO 80301 

303-497-0371 

303-497-0338 

peter@nchems.org 

Carol Fuller 

4 Brian Drive 

Carlisle, PA 17013 

717-240-0462 

717-240-0486 

CarolHFuller@earthlink.net 

James Gearity 

Director, Bureau of Postsecondary 

Education 

Pennsylvania Department of Education 

Postsecondary Services 

335 Market St. 

Harrisburg, PA 17126 

717-787-4313 

717-772-3622 

jgearity@state.pa.us 

Susan Hattan 

Senior Consultant 

National Association of Independent 

Colleges and Universities 

(NAICU) 

1025 Connecticut Ave. NW, Suite 700 

Washington, DC 20036 

202-785-8866 

202-835-0003 

susan@naicu.edu 

Carolyn Henrich 

Legislative Director for Education 

University of California 

Office of the President 

1608 Rhode Island Avenue, NW 

Washington, DC 20036 

202-974-6308 

202-974-6330 

carolyn.henrich@ucdc.edu 
Appendix A — Technical Review Panels 

A-7 

Marsha Hirano-Nakanishi 

Assistant Vice Chancellor and Chair of AIR 

HEDPC 

California State University System, 

Chancellor's Office 

Academic Research and Resources 

401 Golden Shore, Sixth Floor 

Long Beach, CA 90802 

562-951-4767 

562-951-4981 

mhirano-nakanishi@calstate.edu

Harold Horton 

Director, Higher Education Information 

Ohio Board of Regents 

Higher Education Information System (HEI) 

30 East Broad St., 36th Floor 

Columbus, OH 43215 

614-644-5796 

614-728-0102 

hhorton@regents.state.oh.us 

Bob Kieran 

Director, Institutional Research 

Oregon University System 

Institutional Research 

P.O Box 3175 

Eugene, OR 97403 

541-346-5758 

541-346-5790 

Bob_Kieran@ous.edu 

Jaci King 

Director 

American Council on Education 

Center for Policy Analysis 

1 Dupont Circle, NW 

Washington, DC 20036 

202-939-9554 

202-785-2990 

Jacqueline_King@ace.nche.edu 

Sandra Kinney 

Coordinator of Information Services 

Georgia Department of Technical & Adult 

Education 

1800 Century Place, Suite 590 

Atlanta, GA 303405 

404-327-6869 

skinney@dtae.org 

David Laird 

President 

Minnesota Private College Council 

445 Minnesota St., Suite 500 

St. Paul, MN 55101 

651-293-6812 

651-228-0379 

dlaird@mnprivatecolleges.org 

Michael Lance 

Consultant 

The Bench Group 

2900 Connecticut Ave. NW 

Washington DC 20008 

202-332-2556 

michael.lance@benchgroup.org 

John Lee 

President 

JBL Associates, Inc. 

6900 Wisconsin Avenue, Suite 606 

Bethesda, MD 20815 

301-654-5154 

301-654-6242 

jbl@jblassoc.com 

Dan Madzelan 

Director, Forecasting and Policy Analysis 

Staff 

Office of Postsecondary Education 

U.S. Department of Education 

1990 K St. NW, Room 8036 

Washington, DC 20006 

202-502-7816 

202-502-7873 

dan.madzelan@ed.gov 

Edith McArthur 

Demographer 

National Center for Education Statistics 

Data Development Program-ECICSD 

1990 K Street, NW, Room 9115 

Washington, DC 20006 

202-502-7393 

202-502-7466 

Edith.Mcarthur@ed.gov 
Appendix A — Technical Review Panels

A-8

Tod Massa 

Director, Policy Research and Data 

Warehousing 

State Council of Higher Education for 

Virginia 

101 N. 14th St. 

Richmond, VA 23219 

804-225-3147 

804-371-2870 

todmassa@schev.edu 

Mari McCarty 

Senior Vice President 

Wisconsin Association of Independent 

Colleges and Universities 

122 West Washington Ave., Suite 700 

Madison, WI 53703-2718 

608-256-7761 ext. 24 

608-256-7065 

mari.mccarty@waicuweb.org 

Sue Ellen Michalek 

Senior Institutional Planner 

University of Wisconsin System 

Policy Analysis and Research 

1220 Linden Dr., 1538 Van Hise Hall 

Madison, WI 53706 

608-262-1751 

608-265-3175 

smichalek@uwsa.edu 

John Milam 

Executive Director 

HigherEd.org., Inc. 

21 South Kent St. 

Winchester, VA 22601 

540-722-6060 

540-722-4225 

jmilam@highered.org 

Ben Passmore 

Director, Policy Research and Analysis 

University System of Maryland 

Administration and Finance 

3300 Mitzerott Road 

Adelphi, MD 20783 

301-445-1913 

301-445-2761 

passmore@usmd.edu 

Jan Plotczyk 

Statistician 

National Center for Education Statistics 

1990 K Street, NW, Room 8122 

Washington, DC 20006 

202- 502-7459 

Janice.Plotczyk@ed.gov 

Robert (Tad) Perry 

Executive Director 

South Dakota Board of Regents 

Executive Department 

306 E. Capitol Ave., Suite 200 

Pierre, SD 57501 

605-773-3455 

605-773-5320 

tadp@ris.sdbor.edu 

Glenwood Rowse 

Coordinator 

New York State Education Department 

Office of Research and Information Systems 

964 EBA 

Albany, NY 12234 

518-474-5091 

518-474-1907 

growse@mail.nysed.gov 
Appendix A — Technical Review Panels 

A-9 

John Porter 

Associate Provost 

SUNY System Administration 

Institutional Research 

353 Broadway 

Albany, NY 12207 

518-443-5646 

518-443-5632 

porterjo@sysadm.suny.edu 

Craig Schoenecker 

System Director for Research 

Minnesota State Colleges and Universities 

System 

Office of the Chancellor 

500 Wells Fargo Place, 30 East Seventh St. 

St. Paul, MN 55101 

651-296-9600 

651-297-1814 

craig.schoenecker@so.mnscu.edu 

Janet Sabri 

Director of Academic Support Services 

Career Education Corporation 

Education 

2895 Greenspoint Parkway 

Hoffman Estates, IL 60195 

847-851-7341 

847-851-7381 

jsabri@careered.com 

Alan Sturtz 

Director of Institutional Research 

Connecticut State University System 

Institutional Research 

39 Woodland St. 

Hartford, CT 06105 

860-493-0012 

860-493-0080 

sturtza@so.ct.edu 

Cathy Statham 

IPEDS Finance Survey Director 

National Center for Education Statistics 

Postsecondary Institutional Studies Program 

1990 K Street, NW, Room 8130 

Washington, DC 20036 

202-502-7383 

Cathy.Statham@ed.gov 

Laura Tyree 

Assistant Director, State System Research 

Oklahoma State Regents for Higher 

Education 

System Research 

655 Research Parkway, Suite 200 

Oklahoma City, OK 73104 

405-225-9100 

ltyree@osrhe.edu 

Judith Thompson 

Research and Accountability Analyst 

Florida Department of Education 

Community College and Technical Center 

MIS 

325 West Gaines St., Suite 1324 

Tallahassee, FL 32399 

850-245-9506 

580-245-9499 

Judith.thompson@fldoe.org 

Hope Williams 

President 

North Carolina Independent Colleges and 

Universities 

879-A Washington St. 

Raleigh, NC 27605 

919-832-5817 

9190829-7358 

williams@ncicu.org 
Appendix A — Technical Review Panels

A-10

Barbara White 

Educational Policy Consultant 

Office of K-20 Education Information and 

Accountability 

Florida Department of Education 

325 West Gaines St., Suite 844 

Tallahassee, FL 32399 

850-245-0429 

850-245-9069 

barbara.white@fldoe.org 

David Wright 

Senior Research Analyst 

SHEEO 

700 Broadway, Suite 1200 

Denver, CO 80203-3460 

303-299-3677 

303-296-9016 

dwright@sheeo.org 

John Wittstruck 

Senior Research Associate 

Department of Higher Education 

Policy, Planning, and Improvement Center 

(EPPIC) 

3515 Amazonas Dr. 

Jefferson City, MO 65109 

573-751-2361 

573-751-6635 

john.wittstruck@dhe.mo.gov 

Carol Yoakum 

Assistant Director 

Illinois Board of Higher Education 

Information Systems 

431 E. Adams 

Springfield, IL 62701-1418 

217-557-7342 

217-782-8548 

yoakum@ibhe.org 

 
Appendix A — Technical Review Panels 

A-11 

AGENDA 

IPEDS STUDENT UNIT RECORD FEASIBILITY STUDY 

TRP #2 (INSTITUTIONAL PERSPECTIVES) 

November 3-4, 2004 

Hyatt Arlington 

Arlington, VA 22209-9990 

Wednesday, November 3

8:00 a.m. – 8:30 a.m. Continental Breakfast 

8:30 a.m. – 8:45 a.m. Meeting Begins 

8:45 a.m. – 9:00 a.m. Introduction to the Feasibility Study: Context for Proposal 

and What will be Learned—Dennis Carroll, NCES 

9:00 a.m. – 9:15 a.m. Co-Chair Introductions—Mike McGuire, Georgetown 

University & Jeffrey von Munkwitz, University of 

Connecticut 

9:15 a.m. – 9:30 a.m. Summary of TRP1 Discussion 

9:30 a.m. – 10:30 a.m. Privacy/Re-disclosures 

10:30 a.m. – 10:45 a.m. Break 

10:45 a.m. – 12:00 p.m. Burden 

12:00 p.m. – 1:30 p.m. Working lunch 

1:30 p.m. – 2:30 p.m. Campus Coordination/System Issues 

2:30 p.m. – 3:30 p.m. Data Flow/Possible Record Formats 

 Transaction vs. Analytical Extracts 

3:30 p.m. – 3:45 p.m. Break 

3:45 p.m. – 4:45 p.m. Timing/Census Dates 

 
Appendix A — Technical Review Panels

A-12

Thursday, November 4

8:00 a.m. – 8:30 a.m. Continental Breakfast 

8:30 a.m. – 8:45 a.m. Meeting begins 

8:45 a.m. – 9:15 a.m. Review of first day’s discussion—John Milam, HigherEd.org 

9:15 a.m. – 10:15 a.m. First year Implementation—Dennis Carroll 

Field test— Cathy Statham, NCES 

10:30 a.m. – 10:45 a.m. Break 

10:45 a.m. – 12:00 p.m. Continued follow-up discussion 

12:00 pm – 1:30 pm Working lunch and Summary statements—Mike McGuire, 

Georgetown University & Jeffrey von Munkwitz, University 

of Connecticut 

 

2:00 p.m. Adjourn 
Appendix A — Technical Review Panels 

A-13 

 

TRP2 Participant List 

 

Frank Balz 

National Association of Independent 

Colleges and Universities 

Suite 200, 1025 Connecticut Ave., NW 

Washington, DC 20036 

Phone: 202-785-8866 

Fax: 202-835-0003 

frank@naicu.edu 

Gordon Babcock 

U.S. Department of Education 

Office of the Chief Information Officer 

550 12th Street, SW 

Washington, DC 20065 

Phone: 202-245-6412 

gordon.babcock@ed.gov 

Sam Barbett 

National Center for Education Statistics 

Postsecondary Institutional Studies Program 

1990 K Street NW, Room 8113B 

Washington, DC 20006 

Phone: 202-502-7305 

Fax: 202-502-7460 

Samuel.Barbett@ed.gov 

Sandy Baum 

The College Board 

1233 20th St., NW 

Washington, DC 20009 

Phone: 518-369-3774 

sbaum@collegeboard.org 

Kathie Beaty 

Bradley University 

1501 W. Bradley Ave. 

Peoria, IL 61625 

Phone: 309-677-3107 

Fax: 309-677-2715 

kbeaty@bradley.edu 

David Bergeron 

Office of Postsecondary Education 

U.S. Department of Education 

1990 K St. NW 

Washington, DC 20006 

Phone: 202-502-7815 

Fax: 202-502-7873 

david.bergeron@ed.gov 

Mary Black 

Michigan State University 

Office of Planning and Budgets 

329 Administration Bldg. 

East Lansing MI 48824 

Phone: 517-353-6463 

Fax: 517-353-3758 

Mary.Black@opb.msu.edu 

M. Christopher Brown 

UNCF Patterson Research Institute 

Frederick D. Patterson Research Institute 

8260 Willow Oaks Corporate Dr. 

Fairfax, VA 22031 

Phone:. 703-205-2011 

Fax: 703-205-2012 

mcb2@uncf.org 

Susan Broyles 

National Center for Education Statistics 

Institute of Education Sciences 

1990 K Street, NW, Room 8113C 

Washington, DC 20006 

Phone: 202-502-7318 

Susan.Broyles@ed.gov 

Dennis Carroll 

National Center for Education Statistics 

Postsecondary Studies Division 

1990 K St. NW, Room 8112 

Washington, DC 20006 

Phone: 202-502-7323 

Fax: 202-502-7460 

Dennis.Carroll@ed.gov 
Appendix A — Technical Review Panels

A-14

Jason Casey 

Higher Education Data Sharing Consortium 

P.O. Box 3003, Franklin & Marshall 

Lancastor, PA 17604 

Phone: 717-358-4448 

Fax: 717-358-4456 

jason.casey@fandm.edu 

Dorothy Cheagle 

Morris College 

Planning & Governmental Relations 

100 West College St. 

Sumter, SC 29150 

Phone: 803-934-3227 

Fax: 803-773-3687 

dcheagle@morris.edu 

David Clawson 

Thomas Jefferson University 

Registrar 

615 Walnut St., Room G-22 

Philidelphia, PA 19107 

Phone: 215-955-5001 

Fax: 215-923-6974 

david.clawson@jefferson.edu 

Peggye Cohen 

George Washington University 

Institutional Research 

2121 I St., NW, Suite 809 

Washington, DC 

Phone: 202-994-6509 

Fax: 202-994-0709 

peggye@gwu.edu 

Melanie Corrigan 

American Council on Education 

Center for Policy Analysis 

1 Dupont Circle, NW 

Washington, DC 20036 

Phone: 202-939-9554 

Fax: 202-785-2990 

Melanie_Corrigan@ace.nche.edu 

Mary Ann Coughlin 

Springfield College/AIR 

Academic Affairs 

Alden St. 

Springfield, MA 01109 

Phone: 413-748-3038 

Mary_Coughlin@spfldcol.edu 

Alisa Cunningham 

Institute for Higher Education Policy 

1320 19th St, NW, Suite 400 

Washington, DC 20036 

Phone: 202-861-8223 

Fax: 202-831-9307 

alisa@ihep.org 

Pat Dewitt 

Shorter College 

Institutional Planning and Research 

315 Shorter Ave. 

Rome, Georgia 30165 

Phone: 706-233-7308 

Fax: 706-233-7458 

patdewitt@shorter.edu 

Celestine Drayton 

The Community College of Baltimore 

County 

Planning, Research, and Evaluation 

7201 Rossville Blvd. 

Baltimore, MD 21234 

Phone: 410-780-6466 

Fax: 410-780-6206 

CDrayton@ccbcmd.edu 

Eileen Driscoll 

Cornell University 

Institutional Planning & Research 

440 Day Hall 

Ithaca, NY 14853 

Phone: 607-255-0876 

Fax: 607-255-2990 

efd2@cornell.edu 
Appendix A — Technical Review Panels 

A-15 

Pam Eliadis 

Federal Student Aid 

U.S. Department of Education 

Union Center Plaza, 830 First St., NE 

Washington, DC 20202 

Phone: 202-377-3554 

Fax: 202-275-0913 

Pam.Eliadis@ed.gov 

William Fendley 

Wayne State University 

Division of Academic Affairs 

656 W. Kirby St., 1309 F/AB 

Detroit, Michigan 48202 

Phone: 313-577-8247 

Fax: 313-577-2198 

bfendley@bama.ua.edu 

Johanna Frost-Johnsen 

St. Joseph's College 

Registrar 

245 Clinton Ave. 

Brooklyn, NY 11205 

Phone: 718-636-6814 

Fax: 718-636-6813 

jfrost@sjcny.edu 

Carol Fuller 

Consultant 

4 Brian Drive 

Carlisle, PA 17013 

Phone: 717-240-0462 

Fax: 717-240-0486 

carol@naicu.edu 

David Futrell 

National Association of Student Financial 

Aid Administrators 

Training and Technical Assistance 

1129 20th St., NW, Suite 400 

Washington, DC 20036 

Phone: 202-785-0453x124 

Fax: 202-785-1487 

futrelld@nasfaa.org 

Tina Gleason 

Union College 

Institutional Studies 

Feigenbaum Hall 

Schenectady, NY 12308 

Phone: 518-388-6607 

Fax: 518-388-6006 

gleasont@union.edu 

David Gray 

Louisville Presbyterian Theological 

Seminary 

1044 Alta Vista Rd. 

Louisville, Kentucky 40205 

Phone: 502-895-3411 

Fax: 502-895-1096 

DGRAY@lpts.edu 

Teresa Hall 

University of Alabama at Birmingham 

Institutional Studies and Services 

1530 3rd Ave. So, AB 420 

Birmingham, AL 35294-0104 

Phone: 205-934-3254 

Fax: 205-934-3179 

hallter@uab.edu 

Dennis Hengstler 

University of California at Berkeley/AAUDE 

Office of Planning and Analysis 

611 University Hall 

Phone: 510-642-5561 

Fax: 510-643-8448 

hengstlr@berkeley.edu 

Anne Horowitz 

University of the Sciences in Philadelphia 

Office of Institutional Research 

600 South 43rd St. 

Philadelphia, PA 19104-4495 

Phone: 215-596-7518 

Fax: 215-596-8726 

a.horowi@usip.edu 
Appendix A — Technical Review Panels

A-16

Marianne Hricay 

Pace University 

Office of Planning Assessment, Research & 

Academic Budgeting 

235 Elm Rd., Dow hall 5103 

Briarcliff Manor NY 10510 

Phone: 914-923-2647 

Fax: 914-923-2679 

MHricay@pace.edu 

Chris Humphrey 

College of Southern Maryland 

Outcomes Assessment and Research 

8730 Mitchell Rd, P.O. Box 910 

La Plata, MD 20646 

Phone: 301-934-7620 

Fax: 301-934-7670 

ChrisH@csmd.edu 

Bob Johnson 

Rhodes Colleges 

2000 N. Parkway 

Memphis, TN 38112-1690 

Phone: 901-843-3745 

johnsonb@rhodes.edu 

Linda Katunich 

Ohio State University 

Registrar 

120 Lincoln Tower, 1800 Cannon Dr. 

Columbus, OH 43210 

Phone: 614-292-0752 

Fax: 614-292-7199 

LKatunich@exchange.ureg.ohio-state.edu 

Marsha Kellman 

University of Texas System 

Institutional Studies and Policy Analysis 

601-Colorada St., O. Henry Hall 111A 

Austin, TX 

Phone: 512-499-4400 

Fax: 512-494-3575 

mkelman@utsystem.edu 

Xiangping Kong 

St. Thomas Aquinas College 

Office of Institutional Research and Program 

Development 

125 Route 340 

Sparkill, NY 10976 

Phone: 845-398-4207 

Fax: 845-398-4224 

xkong@stac.edu 

Pam Lamborne 

Shenandoah University 

Registrars Office 

1460 University Dr. 

Winchester, VA 22601 

Phone: 540-665-4539 

Fax: 540-665-5446 

Plamborn@su.edu 

Michael Lance 

The Bench Group 

2900 Connecticut Ave. NW 

Washington, DC 20008 

Phone: 202-332-2556 

michael.lance@benchgroup.org 

Cathy Lebo 

Johns Hopkins University 

Provost Office 

Garland Hall 210, 3400 N. Charles St. 

Baltimore, MD 21218-2692 

Phone: 410-516-4107 

Fax: 410-516-8035 

clebo1@jhu.edu 

Susan McBride 

Jefferson Davis Community College 

P.O. Box 958 

Brewton, AL 36427 

Phone: 251-809-1551 

Fax: 251-809-0178 

susan.mcbride@jdcc.edu 
Appendix A — Technical Review Panels 

A-17 

Mike McGuire 

Georgetown University 

Planning and Institutional Research 

303 Maguire Hall 

Washington, DC 20057 

Phone: 202-687-3424 

Fax: 202-687-3935 

mcguirmd@georgetown.edu 

Nancy Mendez Velez 

University of Puerto Rico at Mayagüez 

Institutional Research and Planning Office 

PO Box 9000 

Mayaguez, PR 00981-9000 

Phone: 787-265-3877 

Fax: 787-831-3022 

nancy@rectoria.uprm.edu 

Jamie Merisotis 

Institute for Higher Education Policy 

1320 19th St., NW 

Washington, DC 20036 

Phone: 202-861-8223 

Fax: 202-861-9307 

jamie@ihep.org 

John Milam 

HigherEd.org., Inc. 

21 South Kent St 

Winchester, VA 22601 

Phone: 540-722-6060 

Fax: 540-722-4225 

jmilam@highered.org 

Pat Mizak 

Canisius College 

Institutional Research 

2001 Main St. 

Buffalo, NY 14208 

Phone: 716-888-3202 

Fax: 716-888-3743 

mizakp@canisius.edu 

Frances Moran 

Family Policy Compliance Office 

U.S. Department of Education 

400 Maryland Avenue, SW 

Washington, DC 20202 

Phone: 202-260-3887 

Fax: 202-260-9001 

Frances.Moran@ed.gov 

Patty Murphy 

Dickinson College 

Enrollment and College Relations 

P.O. Box 1773 

Carlisle, PA 17013 

Phone: 717-245-1634 

Fax: 717-245-1110 

murphyp@dickinson.edu 

Ben Passmore 

University System of Maryland 

Administration and Finance 

3300 Metzerott Rd 

Adelphi, MD 

Phone: 301-445-1913 

Fax: 301-445-2761 

passmore@usmh.usmd.edu 

Lu Phillips 

Lorain County Community College 

Institutional Research & Planning 

1005 Abbe Rd North 

Elyria, OH 44035 

Phone: 440-366-7789 

Fax: 440-366-4159 

lphillip@lorainccc.edu 

Jan Plotczyk 

National Center for Education Statistics 

1990 K Street, NW, Room 8122 

Washington, DC 20006 

Phone: 202- 502-7459 

Susan.Broyles@ed.gov 
Appendix A — Technical Review Panels

A-18

LeRoy Rooker 

Office of Innovation and Improvement 

Department of Education Organizational 

Structure and Offices 

400 Maryland Ave., SW 

Washington, DC 20202 

Phone: 202-260-3887 

Fax: 202-260-9001 

LeRoy.Rooker@ed.gov 

Karen Roorbach 

Indiana Wesleyan University 

4201 South Washington Street 

Marion, IN 46953 

Phone: 765-677-2131 

Fax: 765-677-2662 

Karen.Roorbach@indwes.edu 

Graziella Saccon 

The College of New Rochelle 

Academic Affairs 

29 Castle Place 

New Rochelle, NY 

Phone: 714-654-5836 

Fax: 914-654-5936 

gsaccon@cnr.edu 

Dixie Sakolosky 

Randolph-Macon Woman's College 

Institutional Research and Assistant to the 

President 

2500 Rivermont Ave. 

Lynchburg, VA 24503 

Phone: 434-947-8131 

Fax: 434-947-8139 

dsakolosky@rmwc.edu 

Mary Sapp 

University of Miami 

Planning & Institutional Research 

1365 Memorial Dr., Unger Bldg. 335 

Coral Gables, FL 33146 

Phone: 305-284-3856 

Fax: 305--284-4020 

msapp@miami.edu 

Tod Schmitz 

Indiana University 

University Reporting & Reporting 

Poplars, Suite 017, 400 E. 7th St. 

Bloomington, IN 47405 

Phone: 812-855-9893 

Fax: 812-856-1209 

schmitz@indiana.edu 

Alice Simpkins 

Paine College 

Institutional Research 

1235 Fifteenth St. 

August, GA 30901 

Phone: 706-821-8283 

Fax: 706-821-8533 

simpkinsa@mail.paine.edu 

Richard Skeel 

University of Oklahoma 

1000 Asp Ave. 

Norman, OK 73071 

Phone: 405-325-6017 

Fax: 405-325-7047 

rskeel@ou.edu 

Brady Sloan 

Teacher's College, Columbia University 

Registrar 

520 West 120th St., Box 311 

New York, NY 10027 

Phone: 212-678-3226 

Fax: 212-678-3005 

bsloan@exchange.tc.columbia.edu 

Barry Smith 

Baptist Bible College 

Information Services 

538 Venard Rd. 

Clarks Summit, PA 18411 

Phone: 570-585-9258 

Fax: 570-586-1753 

bcsmith@bbc.edu 
Appendix A — Technical Review Panels 

A-19 

Cathy Statham 

National Center for Education Statistics 

Postsecondary Institutional Studies Program 

1990 K Street, NW, Room 8130 

Washington, DC 20036 

Phone: 202-502-7383 

Cathy.Statham@ed.gov 

Jeff Tanner 

National Student Clearinghouse 

13454 Sunrise Valley Drive, Suite 300 

Herndon, VA 20171 

Phone: 703-742-4200 

tanner@studentclearinghouse.org 

Deb Teeter 

University of Kansas 

1246 West Campus Rd. 

Lawrence, KS 66045-7505 

Phone: 785-864-4412 

Fax: 785-864-5324 

deb-teeter@ku.edu 

Dawit Teklu 

Anne Arundel Community College 

Planning Research and Institutional 

Assesment 

101 College Parkway 

Arnold, MD 21012 

Phone: 410-777-2766 

Fax: 410-777-2166 

dteklu@aacc.edu 

Mary Rose Tonkin 

Empire Beauty School 

Business Office 

396 Pottsville/St. Clair Hwy 

Pottsville, PA 17901 

Phone: 570-429-1800 

Fax: 570-429-4256 

mrtomkin@empire.edu 

Christopher Van Wyk 

Drew University 

Institutional Research 

36 Madison Ave. 

Madison, NJ 

Phone: 973-408-3502 

Fax: 973-408-3792 

cvanwyk@drew.edu 

Jeffrey von Munkwitz-Smith 

University of Connecticut 

Office of the Registrar 

Unit 4077D 

Storrs, CT 06269-4077 

Phone: 860-486-3903 

Fax: 860-486-0062 

jvon@uconn.edu 

Tim Walsh 

Temple University 

Institutional Research 

1803 N. Broad St. (038-27) 

Philadelphia, PA 19122 

Phone: 215-204-5050 

Fax: 215-204-7487 

timothy.walsh@temple.edu 

Mindy Wang 

Catholic University of America 

Planning & Institutional Research 

200 Leahy Hall 

Washington, DC 20064 

Phone: 202-319-6901 

Fax: 202-319-6690 

WANGM@cua.edu 

Karen Webbs-Bauer 

University of Georgia 

Institutional Research 

110 E. Clayton St., Suite 725 

Athens, GA 30602-5279 

Phone: 706-425-3183 

Fax: 706-425-3200 

kwbauer@uga.edu 
Appendix A — Technical Review Panels

A-20

Gail Wisan 

Goucher College 

Institutional Research 

1021 Dulaney Valley Rd. 

Baltimore, MD 21204 

Phone: 410-337-6144 

Fax: 410-337-6123 

Marjorie Wiseman 

Northeastern University 

Planning and Research 

360 Huntington Ave., Suite 526 CP 

Boston, MA 02115 

Phone: 617-373-5102 

Fax: 617-373-5506 

m.wiseman@neu.edu 

Meihua Zhai 

George Mason University 

Institutional Research and Reporting 

10517 Patriot Square 

Fairfax, Virginia 22030 

Phone: 703-993-8841 

Fax: 703-993-8325 

mzhai@gmu.edu 

Tammy Zimmer 

Career College Association 

Legal 

10 G St., NW, Suite 750 

Washington, DC 20002 

Phone: 202-336-6839 

Fax: 202-336-6828 

tammyz@career.org 
Appendix A — Technical Review Panels 

A-21 

AGENDA 

IPEDS STUDENT UNIT RECORD FEASIBILITY STUDY 

TRP #3 (STAKEHOLDERS) 

November 9-10, 2004 

Hilton Garden Inn 

Washington, DC 20005 

Tuesday, November 9

8:00 a.m. – 8:30 a.m. Continental breakfast 

8:30 a.m. – 9:00 a.m. Meeting begins, Co-Chair introductions—Stan Ikenberry, 

University of Illinois & Chris Nelson, St. John’s College 

9:00 a.m. – 9:30 a.m. Background, Process and framework of the feasibility study—

David Bergeron, ED Office of Postsecondary Education & 

Dennis Carroll, ED National Center for Education Statistics 

9:30 a.m. – 10:15 a.m. Discussion of public policy considerations 

10:15 a.m. – 10:30 a.m. Break 

10:30 a.m. – 11:30 a.m. Privacy, confidentiality, and security—Sarah Flanagan, 

National Association of Independent Colleges and 

Universities & Francis Moran, ED Family Policy Compliance 

Office 

11:30 a.m. - 12:00 p.m. State issues—Paul Lingenfelter, State Higher Education 

Executive Officers & Tod Massa, State Council of Higher 

Education for Virginia 

12:00 p.m. – 1:30 p.m. Working lunch 

1:30 p.m. – 2:30 p.m. Campus issues: Coordination across offices—Melanie 

Corrigan, American Council on Education; Pat Smith, 

American Association of State Colleges and Universities; 

Frank Balz, National Association of Independent Colleges 

and Universities 

2:30 p.m. – 3:30 p.m. Campus issues: Burden and cost—Ken Redd, National 

Association of Student Financial Aid Administrators; Barmak 

Nassirian, American Assoc. of Collegiate Registrars & 

Admissions Officers; Terry Russell, Association for 

Institutional Research 

 

3:30 p.m. – 3:45 p.m. Break 

3:45 p.m. – 4:45 p.m. What next? “If authorized, if funds are appropriated.” 
Appendix A — Technical Review Panels

A-22

Wednesday, November 10

8:00 a.m. – 8:30 a.m. Continental breakfast 

8:30 am. – 8:45 a.m. Meeting begins 

8:45 a.m. – 9:15 a.m. Review of first day’s discussion—John Milam, 

 HigherEd.org 

9:15 a.m. – 10:15 a.m. On-going discussion 

 

10:30 a.m. – 10:45 a.m. Break 

10:45 a.m. – 12:00 p.m. Continued follow-up discussion 

12:00 p.m. – 1:30 p.m. Working lunch and Summary statements 

 

2:00 p.m. Adjourn 
Appendix A — Technical Review Panels 

A-23 

TRP3 Participant List

 

Leslie Atkinson 

Director, Government Affairs 

United Negro College Fund 

1444 I St., NW, Suite 500 

Washington, DC 20005 

Phone: 202-737-8623 

Fax: 202-737-8651 

Leslie.Atkinson@uncf.org 

Daren Bakst

President and General Council 

Council on Law in Higher Education 

111 Coconut Key Court 

Palm Beach Gardens, FL 33418 

Phone: 561-622-5761 

Fax: 561-624-9198 

dbakst@clhe.org 

Frank Balz

Vice President for Research and Policy 

Analysis 

National Association of Independent 

Colleges and Universities 

Suite 200, 1025 Connecticut Ave., NW 

Washington, DC 20036 

Phone: 202-785-8866 

Fax: 202-835-0003 

frank@naicu.edu 

Sam Barbett

Mathematical Statistician 

National Center for Education Statistics 

Postsecondary Institutional Studies Program 

1990 K Street NW, Room 8113B 

Washington, DC 20006 

Phone: 202-502-7305 

Fax: 202-502-7460 

Samuel.Barbett@ed.gov 

Crystal Bennett

Associate Attorney 

United Negro College Fund 

Dean Blakey Attorneys at Law 

1101 Vermont Ave., NW, Suite 400 

Washington, DC 20005 

Phone: 202-289-3900 

Fax: 202-371-0197 

cbennet@deanblakey.com 

David Bergeron

Director, Policy and Budget Development 

Staff 

U.S. Department of Education 

Office of Postsecondary Education 

1990 K St. NW 

Washington, DC 20006 

Phone: 202-502-7815 

Fax: 202-502-7873 

david.bergeron@ed.gov 

Dan Boehmer 

President 

National Student Clearinghouse 

13454 Sunrise Valley Dr., Suite 300 

Herndon, VA 20171 

Phone: 703-742-4201 

boehmer@studentclearinghouse.org 

Susan Broyles 

Program Director 

National Center for Education Statistics 

Institute of Education Sciences 

1990 K Street, NW, Room 8113C 

Washington, DC 20006 

Phone: 202-502-7318 

Susan.Broyles@ed.gov 
Appendix A — Technical Review Panels

A-24

Rosa Cadena 

Product Manager 

Jenzabar, Inc. 

Product Development 

5 Cambridge Center 

Cambridge, Massachusetts 02142 

Phone: 617-492-9099 

Fax: 617-452-9081 

Rosa.Cadena@jenzabar.net 

Kevin Carey 

Director of Policy Research 

National Association of System 

Heads/EdTrust 

1250 H. Street, NW, Suite 700 

Washington, DC 20036 

Phone: 202-293-1217 

Fax: 202-293-2605 

kcarey@edtrust.org 

Dennis Carroll 

Associate Commissioner 

National Center for Education Statistics 

Postsecondary Studies Division 

1990 K St. NW, Room 8112 

Washington, DC 20006 

Phone: 202-502-7323 

Fax: 202-502-7460 

Dennis.Carroll@ed.gov 

Ann Clough 

U.S. Department of Education 

Office of Legislation and Congressional 

Affairs 

400 Maryland Avenue, SW, 6W334 

Washington, DC 20202 

Phone: 202-401-2712 

Fax: 202-401-1438 

ann.clough@ed.gov 

Melanie Corrigan 

Associate Director 

American Council on Education 

Center for Policy Analysis 

1 Dupont Circle, NW 

Washington, DC 20036 

Phone: 202-939-9554 

Fax: 202-785-2990 

Melanie_Corrigan@ace.nche.edu 

Alisa Cunningham 

Director of Research 

Institute for Higher Education Policy 

1320 19th St, NW, Suite 400 

Washington, DC 20036 

Phone: 202-861-8223 

Fax: 202-831-9307 

alisa@ihep.org 

Alex Dreier 

Partner 

Hogan & Hartson 

555 Thirteenth Street, NW 

Washington, DC 20004 

Phone: 202-637-6864 

Fax: 202-637-5910 

AEDreier@HHLaw.com 

Sarah Flanagan 

VP Government Relations and Policy 

Development 

National Association of Independent 

Colleges and Universities 

1025 Connecticut Ave., NW, Suite 700 

Washington, DC 20036 

Phone: 202-785-8866 

Fax: 202-835-0003 

sarah@naicu.edu 
Appendix A — Technical Review Panels 

A-25 

Bernard Fryshman 

Executive Vice President 

Association of Advanced Rabbinical 

Colleges 

11 Broadway, Suite 405 

New York, NY 10004 

Phone: 212-363-1991 

Fax: 212-533-5335 

Sang Han 

Assistant Director for Federal Relations 

National Association of State Universities 

and Land-Grant Colleges 

Federal Relations 

1307 New York Ave, NW #400 

Washington, DC 20005 

Phone: 202-478-6079 

Fax: 202-478-6046 

shan@nasulgc.org 

Susan Hattan 

Senior Consultant 

National Association of Independent 

Colleges and Universities 

1025 Connecticut Ave., NW, Suite 700 

Washington, DC 20036 

Phone: 202-785-8866 

Fax: 202-835-0003 

susan@naicu.edu 

David Hawkins 

Director of Public Policy 

National Association for College Admission 

1631 Prince Court 

Alexandria, VA 22314 

Phone: 703-838-2222 

Fax: 703-636-8015 

dhawkins@NACAC.com 

Carolyn Henrich 

Legislative Director for Education 

University of California 

Office of the President 

1608 Rhode Island Avenue, NW 

Washington, DC 20036 

Phone: 202-974-6308 

Fax: 202-974-6330 

carolyn.henrich@ucdc.edu 

Gregory Henschel 

Program Analyst 

U.S. Department of Education 

Office of Vocational and Adult Education 

550 12th St., SW 

Washington, DC 

Phone: 202-245-7661 

Fax: 202-245-7837 

Gregory.Henschel@ed.gov 

Gillian Holler 

Executive Assistant 

The Fashion Institute of Design & 

Merchandising 

D.C. Office 

305- K St., NW, #165 

Washington, DC 20007 

Phone: 202-822-9633 

Fax: 202-295-5070 

GHollar@fidm.com 

Stan Ikenberry 

Vice President for Academic Affairs 

University of Illinois 

Academic Affairs 

506 S. Wright St. 

Urbana, IL 61801 

Phone: 217-333-3077 

StanIke@uiuc.edu 
Appendix A — Technical Review Panels

A-26

Patrick Kelly 

Senior Associate 

National Center for Higher Education 

Management Systems 

P.O Box 9782 

Boulder, CO 80301-9752 

Phone: 303-497-0307 

Fax: 303-497-0338 

patrick@nchems.org 

Christoph Kunkel 

Assistant to the President 

Council of Independent Colleges 

One Dupont Circle, NW, Suite 320 

Washington, DC 20036 

Phone: 202-466-7230 

Fax: 202-466-7238 

ckunkel@cic.nche.edu 

Michael Lance 

Consultant 

The Bench Group 

2900 Connecticut Ave. NW 

Washington, DC 20008 

Phone: 202-332-2556 

michael.lance@benchgroup.org 

Dr. Robert Lerner 

Commissioner 

U.S. Department of Education 

Institute of Education Sciences 

1990 K St. NW 

Washington, DC 20006 

Phone: 202-502-7432 

robert.lerner@ed.gov 

Paul Lingenfelter 

Executive Director 

State Higher Education Executive Officers 

700 Broadway, Suite 1200 

Denver, CO 80203-3460 

Phone:303-299-3685 

Fax: 303-296-9016 

plingenfelter@SHEEO.org 

Cyndy Littlefield 

Director of Federal Relations 

Association of Jesuit Colleges and 

Universities 

One Dupont Circle, NW, Suite 405 

Washington, DC 20036 

Phone: 202-862-9893 

Fax: 202-812-8523 

cyndylit@aol.com 

Dan Madzelan 

Director, Forecasting and Policy Analysis 

Staff 

U.S. Department of Education 

Office of Postsecondary Education 

1990 K St. NW, Room 8036 

Washington, DC 20006 

Phone: 202-502-7816 

Fax: 202-502-7873 

dan.madzelan@ed.gov 

Geri Malandra 

Associate Vice Chancellor for Accountability 

The University of Texas System 

601 Colorado St. 

Austin, TX, 78701 

Phone: 512-499-4201 

Fax: 512-499-4215 

gmalandra@utsystem.edu 
Appendix A — Technical Review Panels 

A-27 

Luis Maldonaldo 

Executive Director, Legislative Affairs 

Hispanic Association of Colleges and 

Universities 

Government Relations 

One Dupont Circle, NW, Suite 605 

Washington, DC 20036 

Phone: 202-833-8361 

Fax: 202-833-8367 

lmaldonado@hacu.net 

Dallas Martin 

President 

National Association of Student Financial 

Aid Administrators 

Officers of the Corporation and General 

Counsel 

1129 20th Street, NW, Suite 400 

Washington, DC 20036-3489 

Phone: 202-785-0453 

Fax: 202-785-1487 

MartinD@NASFA.org 

Judalyn Martin 

AVP Technology Services and Federal 

Reporting 

National Council of Higher Education Loan 

Program 

1100 Connecticut Ave., NW 

Washington, DC 20036 

Phone: 202-822-2106 

Fax: 202-822-2142 

jmartin@nchelp.org 

Tod Massa 

Director of Policy Research and Data 

Warehousing 

State Council of Higher Education for 

Virginia 

Agency IT Resource 

James Monroe Building, 101 North 

Fourteenth St. 

Richmond, VA 23219 

Phone: 804-225-3147 

Fax: 804-371-2870 

todmassa@schev.edu 

Jamie Merisotis 

President 

Institute for Higher Education Policy 

1320 19th St., NW 

Washington, DC 20036 

Phone: 202-861-8223 

Fax: 202-861-9307 

jamie@ihep.org 

John Milam 

Executive Director 

HigherEd.org, Inc. 

21 South Kent St 

Winchester, VA 22601 

Phone: 540-722-6060 

Fax: 540-722-4225 

jmilam@highered.org 

Frances Moran 

Program Specialist 

U.S. Department of Education 

Family Policy Compliance Office 

400 Maryland Avenue, SW 

Washington, DC 20202 

Phone: 202-260-3887 

Fax: 202-260-9001 

Frances.Moran@ed.gov 

Barmak Nassirian 

Associate Executive Director 

American Association of Collegiate 

Registrars and Admissions Officers 

External Relations 

One Dupont Circle NW 

Washington, DC 20036 

Phone: 202-293-9161 

Fax: 202-872-8857 

nassirianb@aacrao.org 
Appendix A — Technical Review Panels

A-28

Christopher Nelson 

President 

St. John's College 

President's Office - Annapolis 

60 College Avenue 

Annaplois, MD 21401 

Phone: 410-263-2371 

chris.nelson@sjca.edu 

Matt Owens 

Senior Federal Relations Officer 

Association of American Universities 

1200 New York Ave., Suite 550 

Washington, DC 20005 

Phone: 202-408-7500 

Fax: 202-408-8184 

matt_owens@aau.edu 

Basmat Parsad 

Associate Project Director & Data Analyst 

Westat 

Education Studies 

1650 Research Boulevard 

Rockville, MD 20850 

Phone: 301-251-1500 

Fax: 301-294-3992 

PARSADB1@WESTAT.com 

Kent Phillippe 

Senior Research Associate 

American Association of Community 

Colleges 

One Dupont Circle, NW 

Washington, DC 20036 

Phone: 202-728-0200 x 222 

Fax: 202-833-2467 

KPHILLIPPE@aacc.nche.edu 

Jan Plotczyk 

Statistician 

National Center for Education Statistics 

1990 K Street, NW, Room 8122 

Washington, DC 20006 

Phone: 202-502-7459 

Janice.Plotczyk@ed.gov 

Ken Redd 

Director of Research and Policy Analysis 

National Association of Student Financial 

Aid Administrators 

1129 20th St., NW, Suite 400 

Washington, DC 20036-3489 

Phone: 202-785-0453 Ext. 138 

Fax: 202-785-1487 

ReddK@nasfaa.org 

George Reinhart 

Senior Program Officer 

The National Academies 

National Research Council 

500 Fifth St., NW 

Washington, DC 20005 

Phone: 202-334-3162 

Fax: 202-334-2725 

GReinhar@nas.edu 

Terry Russell 

Executive Director 

Association for Institutional Research 

222 Stone Building, Florida State University 

Tallahassee, FL 32306-4462 

Phone: 850-644-4470 

Fax: 850-644-8824 

trussell@mailer.fsu.edu 

Jessica Shedd 

Director, Research and Policy Analysis 

National Association of College and 

Universities Business Officers 

2501 M St., NW, Suite 400 

Washington, DC 20037 

Phone: 202-861-2527 

Fax: 202-449-1244 

JShedd@nacubo.org 

Pat Smith 

Policy Scholar in Residence 

American Association of State Colleges and 

Universities 

Government Relations 

1307 New York Ave., 5th Floor 

Washington, DC 20005 

Phone: 202-554-0349 

smithp@aascu.org 
Appendix A — Technical Review Panels 

A-29 

Janis Somerville 

Senior Associate 

National Association of System 

Heads/EdTrust 

1250 K St., NW, Suite 700 

Washington, DC 20006 

Phone: 202-887-0614 

Fax: 202-293-2605 

jsomerville@edtrust.org 

Cathy Statham 

IPEDS Finance Survey Director 

National Center for Education Statistics 

1990 K Street, NW, Room 8130 

Washington, DC 20036 

Phone: 202-502-7383 

Cathy.Statham@ed.gov 

Assistant Secretary Sally Stroup 

Assistant Secretary 

U.S. Department of Education 

Office of Postsecondary Education 

1990 K St., NW 

Washington, DC 20006 

Phone: 202-502-7714 

sally.stroup@ed.gov 

Luke Swarthout 

Higher Education Associate 

National Association of State PIRGs 

218 D St., SE 

Washington, DC 01002 

Phone: 202-546-9707 

Lswarthout@PIRG.org 

Becky Timmons 

Director of Government Relations 

American Council on Education 

One Dupont Circle 

Washington, DC 20036 

Phone: 202-939-9355 

Fax: 202-833-4762 

becky_timmons@ace.nche.edu 

Ross Weiner 

Principal Partner 

National Assoc of System Heads/The 

Education Trust 

1250 H St. NW, Suite 700 

Washington, DC 20005 

Phone: 202-293-1217 

Fax: 202-293-2605 

rwiener@edtrust.org 

Wesley Wollner 

Developer/Designer 

Datatel, Inc. 

Software Development 

4375 Fair Lakes Court 

Fairfax, VA 22033 

Phone: 703-968-9000 

Fax: 703-802-3965 

fww@datatel.com 

Larry Zaglaniczy 

National Association of Student Financial 

Aid Administrators 

1129 20th Street, NW, Suite 400 

Washington, DC 20036-3489 

Phone: 202-785-0453 

Fax: 202-785-1487 

LarryZ@NASFAA.org 
A-30 
B-1 

Appendix B—Estimates of Burden 

As part of the IPEDS Student Unit Record Feasibility Study, a wide variety of 

information has been collected about the potential costs to institutions of implementing the 

proposed unit record system, including participant comments and discussion as part of three 

Technical Review Panel (TRP) meetings1

. Cost data were not included in the design for the 

study; however, this appendix describes cost estimates that were received from institutions 

and broadly discusses the various types of estimates that were made. In addition, specific 

comments regarding institutional burden are presented. In addition, numerous informal 

comments and feedback from the postsecondary education community were received. As the 

discussion of cost and burden evolved during the process of the feasibility study, one of the 

TRP panelists suggested that any input regarding cost estimates could help in the preparation 

of the report. Subsequently, an AIR Alert email was sent to over 5,000 subscribers by the 

Association for Institutional Research (2004; 2004b), and references to the feasibility study 

were made at presentations before the American Association of Community Colleges 

(AACC), the National Association of Independent Colleges and Universities (NAICU), the 

Southern Association for Institution Research (SAIR), and the Northeast Association for 

Institution Research (NEAIR) national and regional conference sessions. 

Several hundred persons participated in the TRP meetings; their comments are 

integrated into this discussion of cost estimates. Numerous additional comments were 

received by e-mail. Table B1 summarizes these comments and those from the TRP 

discussions that are attributable to an individual. Some of these comments represented groups 

of institutions, specifically the Higher Education Data Sharing consortium of private schools 

and the Association of America Universities Data Exchange. Other respondents included a 

range of schools, including SHEEOs (Maryland and Virginia); large state systems (Indiana 

University and the University of Texas); research universities (Washington University, Johns 

Hopkins, and University of New Mexico); state universities (George Mason University and 

the University of Colorado at Boulder); small private institutions (St. Olaf’s, Shimmer, 

Mount Mary College, and Randolph Macon Woman’s College); and community colleges 

(Pima Community College and Walters State Community College).spacesaversssssssssssssss

 

1

 This section discusses the costs to institutions if a UR system were implemented. The costs to NCES would 

vary depending on the design of such a system; as noted earlier, NCES already uses much of the technology 

required in the current IPEDS collection. 
Appendix B — Estimates of Burden

B-2

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic 

 Comment 

Classification 

James Madison University .... Also IPEDS UR should give serious consideration to maintaining two fields for student status: 

one as submitted by the institution, the other as determined by IPEDS for analysis above 

institutional levels. Accuracy of first-time freshman (FTF) data is given a high priority in this 

proposal and I expect that IPEDS will mandate changes to FTF status based on historical data in 

the IPEDS UR system. An institutional status field, controlled by the institution, could be used for 

IPEDS and institutional GRS calculations. This would drastically reduce the burden on 

institutions and IPEDS, prevent resubmission of data back to state systems (close the fed-state 

edit loop), and allow earlier release of consistent FTF statistics. 

New York Institute of Technology I think consideration needs to be given to how much effort it will take to properly classify 

students. For many years, especially in institutional research (IR), I think institutions have grown 

accustomed to downloading what is in institutional databases and then “working with that data” 

to fit into the IPEDS reports. This person effort may prove to be very difficult to accurately code. 

In fact, in some cases the metadata needed to create the IPEDS reports exists outside the student 

database of record. This could involve dozens of full-time equivalent (FTE) days of effort by both 

programming staff and the staff of IR in conjunction with the functional offices. Some of the 

fields in the proposed upload list would have to be created in this reverse-engineering method so 

that the fields live natively on the database of record from which the uploads ought to occur. 

Coordination 

 Alabama Department of 

 Postsecondary Education 

Institutions will have to implement more elaborate reconciliation processes between the business 

office, Title IV records, and IPEDS, etc. 

Bates College Elements of the data to be requested tend to be scattered among several offices, including the 

registrar, financial aid, admissions, finance, information services, and/or the Dean of Students. 

These offices may report to different members of a college’s senior staff, and they may have 

different priorities, calendars for updating information, and deadlines that conflict with those set 

by IPEDS. The cultural/administrative obstacles to coordinating new forms of sharing across 

independent offices are not insignificant, and will require extensive meetings, as well as buy-in 

from senior staff, to raise the data sharing issue to an institutional priority. The coordination task 

becomes even more difficult as multiple surveys become integrated and have to pass multiple 

edits and cross-checks. Space does not permit us to convey the amount of time and high-level 

negotiations that regularly take place at our institution when “data providers,” “data analysts,” 

and “data consumers” have slightly different interpretations about data definitions, or differing 

levels of understanding of the complex IPEDS instructions. The level of access to data varies 

greatly in small institutions. Some institutional research offices or IPEDS coordinators simply 

compile data prepared by other offices; others have can only run certain “canned” reports or timespecific data extracts; some have to request others to run extracts for them, and a limited number 

have full access to data and the technical ability to obtain it across administrative systems. Few 

small institutions have “data warehouses” that are adequate to handle the types of questions being 

raised in the IPEDS unit record context. Others have written to you about the complexity of 

integrating census data with transactional data, so we will not elaborate... Like it or not, at many 

institutions, key offices at many institutions still have a “stovepipe” mentality, and there will also 

be “territorial” battles to be fought when offices are challenged with new reporting processes. 

Because of the many ways in which the IPEDS data are used, even seemingly minor changes in 

definitions and reporting practices (from IPEDS’ perspective) can require direct decisions and 

intervention at the most senior administrative levels. At some institutions, some reporting 

questions may even require faculty legislation to change definitions or procedures. There are 

internal concerns about security and privacy, since many more staff will probably need to have 

access to certain data elements and will need additional training in how to protect privacy. 

Marian College Some of the information being requested is not readily available the way it is requested. For a 

variety of reasons, the college financial aid, admissions, HR, and receivables are either not 

integrated or only partially integrated with the campus academic information systems, and not at 

all or minimally with each other. Connecting information from these disparate resources, while 

not impossible, requires hand manipulation and resolution of mismatched keys, etc. The IR office, 

which has done all the reporting, does not access some of these records, such as the student 

billing accounts (1098-T). With the merging of files that don’t normally talk to each other, each 

step of this submission will have to be supervised manually, with error resolution of keys or other 

concerns. While this scenario should improve over time as corrected data becomes the norm, the 

need for close intervention and error checking in the process will almost certainly continue 

indefinitely. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-3 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

National Association of Student 

Financial Aid Administrators 

Currently, aid offices at some multi-campus and branch campuses report Pell Grant and campusbased aid data through their larger system offices. These offices may have to reprogram their 

systems in order to get data for individual students at the branch campus level. This may cause 

some additional costs or other burdens. 

Towson University In order to complete the mandatory data cleansing and verification of multiple submissions of 

student unit-record files, additional personnel will be necessary in several service offices; 

institutional research, financial aid, enrollment services, and admissions. 

University of California Different offices working on different issues and reporting through different mechanisms, 

whether it is the bursar versus the financial aid office, or campus-driven data versus system wide 

data, different requirements for data collection and reporting at the state and federal levels, 

competing deadlines, timelines, multiple dates for submission of data, and overall coordination of 

dates in general were all topics discussed at length. 

University of Maryland, Baltimore 

County 

The transactional nature of the proposed system will require a data reconciliation process that 

would involve staff in multiple offices and on a continuous basis. Minor errors or inconsistencies 

could lead to substantial negative affects on the lives of individual students. 

University of Wisconsin – Madison Several different offices at a large institution will be involved in UR IPEDS file development. At 

UW-Madison, those offices include the registrar's office, the bursar, institutional research, 

business services, athletics, and student financial services, information technology, and others. 

University System of Maryland Many institutions in the USM run systems which are functional in one area (financial aid, 

enrollment management, human resources, etc.) but are not cross-compatible. The proposed data 

collection system would require greater compatibility which would require the purchase of 

software and/or substantial programming . . . The use of the unit record data for federal financial 

aid verification demands a higher level of accuracy for each individual record than is currently 

necessary for analytical purposes. Put simply, today a minor error in analytic data might create a 

data anomaly, but in the proposed system it could have a substantial negative impact on the lives 

of individual students. This will require assigning personnel from enrollment management to 

monitor these data. 

Field test 

Association of American 

Universities Data Exchange 

Institutions are concerned about the timetable and their ability to generate the unit-record 

information by 2006-07, if they are selected to be in the pilot program. With regard to the pilot 

program, one responded indicated: “State systems have not been studied sufficiently, goals are 

not clear, and clearly 100 voluntary pilot institutions would provide considerable information. 

Why not do these things first, then go to the mandatory pilot.” 

Columbia College Chicago Some of our deepest concerns surround the proposed timing of this change. The current proposal 

states that the pilot year for this switch will occur during the 2006-2007 academic year. The 

College strongly feels that this does not give our institution enough preparation time. If the 

legislation is passed this year, the pilot year should occur no sooner than the 2007-2008 academic 

year. 

Johns Hopkins University Student records are presently scheduled for implementation in summer 2006, right before the 

planned pilot study for IPEDS unit records in fall 2006. If selected for mandatory participation in 

the pilot, Hopkins would be asked to submit IPEDS in both the current and the new formats. 

Hopkins would be a poor choice for the pilot because it would be attempting both formats for the 

first time on the new system. We would be spending money to develop a new way to replicate the 

old format, never again to be repeated, and the timing of the pilot could bring the entire 

implementation to a halt. 

Financial aid file 

Columbia College Chicago There are also concerns that it will be difficult to reconcile the current financial aid audit 

information to what will be required in the files. It is critical that the deadline of the financial aid 

file must come no sooner than the six months after the end of the academic year, after all other 

federal audits are completed. 

Financial aid administrator: large, 

four-year, private, not-for-profit, 

university in the Mid-Atlantic region 

I notice that "Institutional Grants" are lumped together in one category, without differentiating 

between grants that are funded and those that are unfunded. This might be described as the 

NACUBO approach . . . but it is worrisome in that those who like to impugn institutional aid as 

"tuition discounting" tend to give the impression that all institutional aid is unfunded, and those 

who wish to use institutional aid for enrollment management purposes like to assert that there is 

no difference and behave as all institutional aid is funded, if only, in some cases, by "tuition 

money." 

Financial aid administrator: large, 

public, four-year university in the 

Midwest 

It is not a large task to get the information requested. 

Financial aid administrator: large, 

public, four-year university in the 

Southeast 

We have this information in our database, so I do not know that it would be very cumbersome to 

report. 

Financial aid administrator: small, 

liberal arts college in the Northeast 

While I'm not sure of the impact, once we design the programs and steps in the first year (and 

provided they don't change the requirements every year) it shouldn't be too bad to produce this 

data and send it off. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-4

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Marian College Financial aid data, which seems to be of paramount interest, changes continually and dramatically 

throughout the year. At any point you fix it, it is a partial picture, not settling out until the 

following year. It is probably not useful for the purposes intended unless received early, and isn’t 

stable enough to generate firm conclusions at that time. We do not consider our financial aid data 

final until the next year. 

Maryland Higher Education 

Commission 

The use of multi-submission of IPEDS UR for all types of data is problematic in some areas. The 

collection of student financial aid data over multiple points within a year does not provide an 

accurate picture of the financial aid picture at the end of a yearly period. There are too many 

adjustments (awards adjustments, audit verification corrections) made to student financial aid 

over a year’s period to make any type of collection besides end of year accurate. 

National Association of Student 

Financial Aid Administrators 

Collecting information for graduate/professional student assistantships may be difficult at many 

campuses. These data are usually not kept in the financial aid office. They are kept by deans, who 

are not always willing or able to share these data with the aid office. This is particularly true at 

campuses that have decentralized aid offices. 

University of California at Berkeley The treatment of summer sessions will be another issue, especially with respect to financial aid. 

University of Miami The net price for students for students enrolled in fall/spring is much lower than for those enrolled 

in summer. For example, students who use Pell for fall and spring won't have it in the summer 

because of the annual eligibility limits. No UM gift aid is awarded during the summer. NCES 

needs to decide whether they want net price for a "typical" student (enrolled just fall and spring) 

or for all students. This question also seems to fail to take into account differential pricing offered 

by some programs, so any attempt to look at the whole will not represent the norm. . . . Overall 

budgets are not very accurate. Students living off campus don't pay us for room and board so that 

component of total budget is difficult to estimate for them, and no student pays the University for 

books and supplies, personal expenses or transportation. In addition, if the student changes 

intensity, the costs change but may not be reflected accurately in the database. So you'll never 

really know the net cost for students if the total "budget" is used. You'd have to focus on the 

tuition and fees only, but then you'd only have net tuition and fees, not net cost. Even that won't 

be completely accurate because we award aid on the budget, not on just tuition and fees. 

Furthermore, some students will have a negative net tuition and fees because they receive aid for 

expenses above and beyond just tuition and fees. How would these students be handled? 

University of Miami It sounded as if SFA would continue to be based on the prior-year cohort (either fall or full-year). 

If that's the case SFA data collected during the year associated with the first EF (e.g., Fall 2007) 

would be for the students for the prior year rather than the students included in that UR anyhow 

(e.g., it would be for students enrolled in Fall 2006 not Fall 2007). Delaying UR collection of 

SFA data a year after EF would align the SFA cohort with the EF cohort (e.g., NCES would 

request data for students enrolled in Fall 2007 in 2008-2009). 

General issues 

Agnes Scott College I also have concerns regarding the human power and financial resources necessary to address 

even the most conservative data requirements. Small institutions, such as Agnes Scott College, 

simply do not have the human nor technological resources to comply. 

Alverno College Completing IPEDS is time consuming but the present practices dovetail with institutional reports, 

information to Common Data Set, Petersons, US News & World Report, etc. I am concerned 

about anything that would mean additional work, additional checks and balances on the 

institution's part . . . It seems to me it is the responsibility at the local level to submit the IPEDS 

information for the institution. This feels like someone else taking our numbers, manipulating 

them and drawing conclusions. Also, just letting the computer “do the numbers,” does not provide 

a check and balance. Sometimes when I am completing IPEDS I notice a race code or age or 

state, etc., missing, I can then have that investigated and manually fix the report. 

American Association of 

Community Colleges 

Community colleges represent about half of all undergraduates and they “don’t know what 

happens to their students once they leave their schools.” They don’t know what happens to a lot 

of students in higher education. “AACC is cautiously optimistic and looking forward to the 

results of the study. However, we are concerned about issues related to privacy and the potential 

burden on our institutions, and how these will be addressed as a result of the feasibility study.” 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-5 

 Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

American Council on Education There are “lots of operational issues.” Many of these were raised in the previous two TRPs. 

These are “not insurmountable, but can be magnified or minimized in terms of burden” because 

they can be “very complex in actions.” “We’re prepared to love this a lot unless we hate it. It 

could do us a lot of good, unless it hurts us.” We acknowledge that “most of us are desperate to 

tell the institutional and the student success story in a better way.” While recognizing that future 

TRPs will need to hash a lot of this out if UR moves forward, the concerns they have “are not 

inconsequential.” It is “not so much the intent and design of what it is trying to do, but the whole 

host of attendant issues that it raises.” 

Association of American 

Universities Data Exchange 

Campuses have established numerous reports with a long history of data definitions and 

protocols. Many expressed concern of having to reconcile internal campus reports with NCES 

reports and “correcting” errors in the data files as identified by NCES. One could potentially 

generally three different answers to the same questions based on campus, system/state, or NCES 

data. 

Bates College One of the primary problems with the IPEDS unit record proposal is that it completely ignores the 

practical organizational, cultural, and training obstacles that would have to be overcome. Let me 

try to summarize some of the problems that will be faced by many of the smaller institutions, who 

would find unit-record reporting to be extremely burdensome and expensive. In spite of their 

good intentions, many small institutions will probably end up being forced to pay fines, because 

they will be unable to comply with the new requirements. 

Bucknell University One point, however, needs to be made very clearly: all burdens are not equal. A number of 

college representatives with whom I have spoken would be very willing to complete an additional 

IPEDS report on net cost, an option which entails data collection and reporting of the type with 

which we are familiar from other IPEDS reporting, and which is free of any associated risks. 

Cardinal Stritch University Submitting the data as suggested in the proposed student record layout would not create a 

significant burden for us, as we already have all that information available in our data system . . . 

Institutions will still need to compile all of the same reports that are currently submitted as most 

institutions still need to report these summarized data internally anyway. Institutions are highly 

unlikely to be willing to use the government's summarized data, which will not include small 

values, for their regular internal reports. Most institutional researchers are intent on analyzing 

their own data. I myself won't even use our own system's canned reports as I prefer to work with 

the real data and analyze it in various manners for various needs. Using the government’s version 

of the data will not suffice for these reporting needs, even if the data summaries were available in 

a timely manner. This new process will not reduce the institution's reporting burden, but will 

likely increase it. 

Caspar College This proposed data collection system will require a monumental amount of time and effort at all 

levels to make it work and I am not convinced that we will learn anything new about our students 

in the process. 

Central Wyoming College It would take months to input the data. If a standardized list of variables on each student could be 

agreed upon, the reporting parties could extract this data from their respective databases. 

College of Notre Dame Such a system of data collection would create an immense burden on the College of Notre Dame 

of Maryland. 

College of Southern Maryland In a period of reduced support and funding at the state level for higher education, some degree of

sensitivity to this issue should be displayed by a delay or phased in approach to student unit 

record data collection by the federal government. 

Columbia College Chicago This change will have significant short and long-term impacts on the workload of several offices 

on campus. Most obviously, the IT department would need to develop the reporting mechanisms 

to generate these data files incurring set-up and training costs. 

Concordia University Wisconsin I am very comfortable with the current IPEDS data system, so the idea of making sweeping 

changes is a problem. After reading the descriptions of the proposed changes it appears they 

would require a lot of work and time. 

Council of Independent Colleges There needs to be a way to “help colleges of their size make the transition to UR,” especially with 

the double burden of the pilot. 

DePaul University From the research's perspective there would be many aspects of a federal unit record system that 

would be extremely desirable. 

Eastern Wyoming College In theory, student unit records reporting could probably lead to long-term gains in the amount of 

time we spend responding to surveys and required annual reporting. However, I do not think there 

is anyone optimistic enough to believe this will actually happen. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-6

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Financial aid administrator: large, 

public university in the Mid-Atlantic 

region 

IPEDS needs to consider that this new level of reporting would add considerably to a set of 

institutional reporting responsibilities that include greatly increased state reporting, new and 

intensified grant reporting (the National Science Foundation, the National Institutes of Health, 

etc. all requite far more statistical data and assessment than previously) and an ever-growing 

number of surveys and questions from the public sector that we respond to in accordance with the 

Freedom of Information Act . . . I guess I wonder if more time should be spent assimilating what 

we know and less in new data collection. 

Financial aid administrator: large, 

public, four-year university in the 

Midwest 

We heard NCES folks talk about using the financial aid data to show sample aid packages based 

on a family’s guess of financial need. This puts schools in an extremely difficult position as we 

attempt to explain why the information they saw on the NCES COOL website doesn’t fit their 

situation or represented last year’s approach or any number of other possibilities . . . There is a 

real potential for these data to be naively misunderstood or even intentionally misused. 

Financial aid administrator: large, 

public, four-year university in the 

Northeast 

I agree that more thinking and discussion is needed (in that order) and I agree with the American 

Association of State Colleges and Universities (AASCU) who is supporting the feasibility study . 

. . In general, I think collecting unit record data for IPEDS is a good idea that potentially could 

contribute much to ameliorating the terrible state of IPEDS-based statistics. 

Financial aid administrator: medical 

school in the Southeast 

It would be wonderful to have one central depository but the logistics of it could present some 

significant issues. 

Higher Education Data Sharing 

Consortium, Wake Forest 

University, Haverford College 

We would also like to take exception with the contention that institutions view the burden and 

cost of such a collection of education records as a “tax” for using Title IV financial aid. We 

would remind [NCES] and others that Title IV financial aid is a benefit to individuals and not 

institutions. These individuals have already paid the taxes through their federal income taxes and 

have already fulfilled their responsibilities for provision of information through their applications 

for these benefits. 

Houston Community College System The proposed project seems to me to be too much done too fast . . . It seems to be popular of late 

to place ambitious projects on a fast track for completion. This unfortunately does not ensure 

success or quality. It is certain that the effort will be expensive, with much of the true cost being 

hidden in the budgets of thousands of information services budgets in colleges across the country. 

It is also certain that the effort will provide a veritable bonanza for consultants selling their 

services in support of the project. 

Indiana University The plain truth is that the programs necessary to produce the IPEDS components have already 

been created and leveraged as institutional reports, indicators, and decision support. With all their 

foibles, these surveys have become the currency for those of us that attempt to provide consistent 

metrics to higher education. More importantly, the data that under gird these measures are under 

our control; to be extracted, transformed, manipulated, and presented on our institutional 

schedules. As such, it is pure folly to think that we will no longer be tasked to do these reports but 

rather, simply supply data sets to NCES and wait for our reports to be returned to us. 

James Madison University Overall, the current proposal creates more burden than value. It also mitigates against the 

credibility of IR offices who need to deliver official statistics consistently and in a timely fashion. 

JBL Associates “Once schools get the data and use them internally, they see things about themselves and it helped 

them build a whole new agenda.” The first implementation of UR for this project “came much 

more easily than thought.” 

Jefferson Davis Community College UR will “help validate the role of community colleges in higher education, a role that is 

somewhat overlooked now and does not get the pre-eminence it deserves.” 

Laramie County Community College I see several possible benefits for us, including being able to present a more complete picture of 

how LCCC impacts students. I also think that this proposed student level (unit level) data system 

will give us much more flexibility in terms of research questions. We can ask our own research 

questions and get national average dated data; now we are dependent on the summaries available 

through the current system. I disagree with Northwest's position that the current practices are 

"reasonably acceptable." 

Lewis and Clark College, Juniata 

College 

In moving to transactional data, NCES will put considerable stress on my institution’s ability to 

verify its numbers. Additionally, I am somewhat pessimistic regarding NCES’ ability to do its 

own verification of any statistics derived from such a database, given the lack of context for the 

statistics . . . I have used the recent tools proved by NCES to my institution. They are powerful 

automated tools. They are a testament to the amount of labor invested at NCES and my home 

institution in providing good comparative data for analysis. Unfortunately, the NCES model of 

one-size-fits-all works very poorly in the case of our institution. So, while there are wonderful 

graphs, many of them create misimpressions that take even more work to overcome. When this 

limitation is combined with the IPEDS penchant for “perturbation,” much of the institutional 

benefit is lost. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-7 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Marian College I think it would be feasible for us to generate these files, though I am sure it would be very timeconsuming and even painful at times. I think there are probably a million questions that will come 

up in the first year if they decide to do this—e.g., what to do with 2nd majors. At this point, I 

don’t see how any potential value added to institutions in doing this could possibly match the cost 

and pain involved. 

Maryland Higher Education 

Commission 

There are certain benefits to analysis of UR data nationally, as it would allow tracking of students 

across State boundaries. The downside to this is the loss of individuals’ privacy. This is a 

question that cannot be addressed by the panel. In addition, NCES policies would not allow states 

or institutions to work with the national UR data. This will limit the benefit to the states and the 

institutions while not offsetting the increased burden to them to collect this data. 

Mount Mary College The proposed changes to IPEDS that would require us to submit unit data would be an extreme 

burden for us. 

National Association of Independent 

Colleges and Universities 

Is UR so superior that it justifies the risks, burden, or costs to this than what we know now? We 

know quite a bit. Is this the best way to do it? There are all kinds of other factors that we don’t 

have that much data on with how students get through. 

National Center for Higher 

Education Management Systems 

The proposal for UR “represents a real opportunity to reconceptualize the way enrollments are 

structured and measured. Credit and term are not adequate and institutions are already doing 

things to better define them.” 

National Association of Student 

Financial Aid Administrators 

Despite these points, it is possible that the UR requirement will not be a huge extra burden for 

some campuses. Any problems will probably come from smaller public and private colleges that 

have just one or two aid office staff. These small offices (which tend to have just one or no IR 

office staff) may have additional costs or other burdens. The larger schools that have participated 

in the National Postsecondary Student Aid Study (NPSAS) or other major federal surveys that 

involve unit records probably will not have much difficulty with UR.” 

Northwest College I am writing to state that our college does not support the proposal in any manner. Financial cost, 

time commitments, lack of personnel, technical difficulties, legal issues, regional accreditation 

issues, privacy issues, and reasonably acceptable current practices are the general grounds for our 

decision. 

Northwestern University We are reluctant to comment on the burden of the IPEDS student unit record feasibility study 

because we are fundamentally opposed to it. We believe from a cost/benefit standpoint that the 

costs to institutions far outweigh the benefits or demonstrated value to all stakeholders. We are 

concerned about the many nuances and institutional specific definitions of many of the data 

elements that could potentially be misinterpreted when the data are compiled and reported. 

Occidental College I believe that the unit record proposal is a bad idea, and that its proponents have not realized just 

how bad it is. I think that a few years from now, regardless of whether it gets implemented or not, 

people will look back at this time and ask “What were they thinking?” . . . If enacted, this data 

collection scheme will be a fiasco, initially. The burden on schools will be tremendous, and much 

of the data will not be valid. Eventually, those kinks would get worked out, but at tremendous 

cost in terms of resources—and in terms of the loss of privacy. A bad idea. It is a good idea to 

collect the data, but do so intelligently, by sampling. 

Oglethorpe University We are worried about declining data accuracy were we to move the proposed unit record 

reporting. Since unit record reporting will rely on the submission of transactional data and follow 

a coding scheme that does not fit our institutional system, quality checks on reported data will be 

costly and time consuming at best. 

Oklahoma State Regents for Higher 

Education 

I think there are benefits to the proposed system that outweigh much of the concerns here. The 

ability to actually have data on all students will allow us to really grasp at the real nature of the 

student experience. As Cliff Adelman illustrated in his recent work, students are not tied to 

institutions, nor state borders. If we are to truly know our business then we should seek better 

mechanisms for knowing it. 

Shimer College We are sure we are not alone in finding the proposed requirements: 1) immensely burdensome of 

personnel time and therefore of institutional resources; 2) potentially threatening to privacy and 

other civil guarantees to citizens; and 3) of no compelling value (indeed the opposite) in serving 

the public good. 

St. John's College By collecting one kind of data and not another, this causes policy makers to use those data and 

not others. This is the reason St. John’s doesn’t participate in U.S. News, because the college 

believes that higher education can’t be quantified. “The more counting we do, the less context we 

have.” 

St. Lawrence University The impact of the unit record system on institutional cost and burden will be excessive, with little 

to no additional benefit to the institution itself. 

St. Olaf College Most specifically there was great concern about increased burden—having to both run the 

summary data (as we already do) to check/clean the UR data as well as prepare the UR data in 

proper format 

See notes at end of table. 
Appendix B — Estimates of Burden

B-8

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

State Council of Higher Education 

for Virginia 

There is a “huge, disparate collection of entities” and community colleges make up more than 

half. “There is no good, holistic model of what the benefits of higher ed are. We all think we 

know what higher ed brings to students, states, and the nation, but we cannot prove it.” While the 

UR won’t answer all of these questions, it will allow us to tell different stories about what is 

going on and there are a lot of unanswered questions out there. 

State Higher Education Executive 

Officers 

Current NCES surveys aggregate information from many sources. Despite substantial investments 

in reporting and analysis, these surveys are unable to answer these questions adequately. In fact, 

they lose track entirely of the progress of students who attend different institutions. The only way 

to accurately and completely answer these and other important questions is to collect and analyze 

a handful of data elements on all students over time, even if they attend different institutions. 

Student loan guaranty agency 

representative 

Collecting and maintaining student unit record data is clearly practicable, and such data would no 

doubt yield a wealth of useful facts and figures about higher education. But just because we can 

do this does not mean we should do this. Such a project would no doubt impose a large and 

complex reporting burden on institutions. 

Towson University The NCES proposal to redesign IPEDS to collect student data through individual student unit 

records offers the federal government the potential to provide a more valuable source of 

information than the current aggregate reporting method, particularly in the area of outcome 

assessment and cost of higher education. It is imperative, however, that the cost of implementing 

a system of this magnitude does not outweigh the perceived benefits . . . This initiative will 

impose a heavy financial and resource burden on our institution to create a database of 

information that could jeopardize the privacy of our students. Furthermore, it has the potential to 

seriously compromise the validity of data that institutions are routinely required to report. 

United Negro College Fund "Every year there is more and more reporting,” requiring schools to send more and more data. 

“When will it stop?” “Will the end game be beneficial to some?” 

University of Colorado at Boulder "Full-time enrollment" is the most difficult thing to determine about a student—full-time for

tuition, for financial aid, for this degree program, for residence halls, for . . . . That makes me 

shudder when the goal of analysis is stated as rates of this and that for full-time and part-time 

students, as if they are two separate groups with some qualitative difference between them. 

University of Kansas While schools see the benefits of UR, they have not pursued better numbers because they can’t 

afford to track students this way. In other cases, the cost is greater than the perceived benefits and 

would cut into instructional activities. 

University of Maryland, Baltimore 

County 

This unfunded mandate would be costly and burdensome to the campus and would provide 

questionable data for the uses planned by the federal government. We do not believe that the data 

generated from this project would answer the kinds of questions outlined by NCES. 

University of Maryland Eastern 

Shore 

The impact of the student unit record system may not be fully appreciated prior to implementation 

of the proposed change in data collection. 

University of North Carolina IPEDS UR has the potential to allow us to study the timing of student decisions and the process 

of acquiring credentials. Low-income students and those without enough financial aid are forced 

to drag out going to college. “Timing is a key issue.” One of the central issues is “how to deal 

with non-traditional students.” 

University of Wisconsin System 

Administration 

While we recognize the importance of the issues driving a unit record data collection we have not 

been convinced that this is either the appropriate or adequate vehicle to address these policy 

issues. In addition to policy concerns, we have conceptual, practical and technical considerations. 

. . . At a theoretical level this proposal would seem to address the major policy issues plaguing the 

higher education community at the federal, state and local levels. However, the details, costs and 

implications are serious enough to warrant further discussion prior to advancing the proposal in 

its current form. 

University System of Maryland The current discussion has ignored serious flaws in conceptualization and generally underplayed 

the considerable costs and obstacles to the successful implementation of the system. Most 

importantly, we do not believe that the data generated from this project will be able to answer the 

kinds of questions that NCES has outlined . . . As this system is currently proposed, no outside 

group or agency, including the university or college itself, will be able to validate the accuracy of 

the data analysis and research released about an institution. The IPEDS data set (concerning an 

institution) will exist only with NCES, and will compete directly with institutional and state datasets when any discussion of the institution takes place. This IPEDS data set, for all the reasons 

discussed above, will not be the most accurate. These data will be non-contextualized, 

unconfirmed and not trusted by higher education. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-9 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Villa Julie College The proposed unit record system will impose significant administrative burdens on Villa Julie 

College . . . For an institution of our size, the reporting requirements will generate a massive 

amount of additional work where administrative resources are already stretched thin. The format 

in which data will be requested is likely to be more sophisticated and expensive than the systems 

the college currently uses. The study and implemented program foresees multiple data 

submissions each year. The likelihood that ongoing individual data errors or anomalies will be 

identified and require resolution adds to the burden. The assurances by the Department of 

Education that any additional burden will be initial only, and not ongoing, seems optimistic given 

the multiple submissions each year. Data “cleaning” will be an ongoing effort. One expert on 

higher education data collection advised that it is reasonable to expect at least a 5 percent 

error/anomaly rate each year for unit record data. 

Washington University We could comply with unit record reporting without a significant increase in reporting burden if 

the privacy/SSNs problem is solved. That is no trivial matter. 

GRS data 

Maryland Higher Education 

Commission 

The proposal also identifies the awkward and huge burden that would be required for the 

institutions or States to report back data (as much as 6 years worth) for starting up the unit record 

system to handle the Graduation Rate Survey (GRS). This would also need to be provided the 

first year along with the new UR requirements. A better methodology needs to be developed to 

phase in the GRS based to IPEDS UR. 

Montgomery College The catch-up submission of GRS support data will be a considerable effort. 

Paine College We would have real difficulty due to software conversion projects, especially retrieving data that 

are five or more years old for GRS cohorts. 

Shorter College I could already provide numerous cohort files, as long as they could be uploaded in Excel. 

University of Maryland Eastern 

Shore 

The back fill data for six years will present us a serious challenge in terms of availability of such 

data. Beginning fall of 2003 we changed our database from the Legacy system to PeopleSoft. 

Moreover, the way and the type of data collected over the six year period emphasized freeze data 

to be reported to the Maryland Higher Education Commission that was aggregated and did not 

include course level data. Thus finding appropriate level data will be a major challenge. 

University of Texas system The Technical Review Panel (TRP) for developing these files will have to rethink the alignment 

between the Completions (C) and GRS. The two need to be aligned, since they are based on the 

same data and timing. 

Implementation 

Bates College The desire to accomplish the unit record reporting system all at once, rather than implementing it 

gradually, is very perplexing. The decision to bypass the Office of Management and Budget 

(OMB) clearance process and not do a survey to estimate institutional burden or cost suggests an 

unwillingness from IPEDS to consider institutions’ genuine concerns about a proposal that will 

have far reaching implications for the very nature of student data reporting. It has not been made 

clear what overreaching issues of urgency require such a system to be implemented at once, and 

retroactively, in the case of GRS reporting. 

College of Southern Maryland NCES is moving forward in developing a reporting requirement but a plan for report format, 

fields within the reports, and definitions of the data elements has not been created. Field testing in 

2005 seems impetuous. 

Community College of Baltimore 

County 

Of critical concern is the increased burden given the timetable for implementation. The proposed 

schedule will negatively impact the institutional research, the information technology, and the 

enrollment management departments. Central to this proposal are major changes in the processing 

and handling of student records data. The current timeline does not provide sufficient time to 

adequately plan and implement changes of this magnitude. Allotting additional time between the 

pilot study and the full implementation would allow for the final requirements to be provided to 

the institutions well ahead of implementation. This would provide more time for staffing and 

technology upgrades to be completed before the full implementation. 

Eastern Wyoming College The major challenges would be the workload in the implementation of the new requirements. It 

would require four years of student data (current year plus last three), including all the financial 

aid information, at the start-up phase. The personnel costs and training costs to do this would be 

extensive. 

Financial aid administrator: large, 

public, four-year university in the 

Midwest 

We believe that it significantly increases the institutional reporting burden, especially in the first 

few years of implementation. We’ve yet to see any new initiative put in place without lots of back 

and forth work between the contractor agency and [the university]. Having one of the larger 

populations in the country, this is not trivial. 

Houston Community College System If implemented, I would suggest that a more gradually phased-in model would be preferable with

adequate testing to ensure data security and accuracy. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-10

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Howard Community College We recommend that a secondary review process be considered, one that incorporates further input 

from institutional researchers, admissions officers, and information technology experts from all 

higher education segments, including community colleges. The proposed timeline for 

implementing this initiative needs to be reconsidered as do many of the details of the present 

project design. 

Lewis and Clark College, Whitman 

College, Juniata College 

With the massive potential for bugs, at both the institutional and federal levels, five to seven years 

seems a more reasonable estimate of the period of disruption and unreliability in the aggregates 

rather than two or three. (Just look at the time it’s taken for NCES to streamline the web-based 

IPEDS collection.) 

Maryland Community College 

Research Group 

Structural changes of this nature require more time than the current plan so that appropriate 

resources can be acquired. 

Maryland Higher Education 

Commission 

The proposed implementation schedule is far too tight to allow time to prepare, test and 

implement. Typically unit records systems take three to four years to roll out depending on 

complexity not the one to two year period proposed. Institutions and possibly States will need one 

year of training and preparation time to modify their systems and procedures. One year is spent 

on doing a test or pilot at a few institutions. NCES intends to pilot a 25 percent on the institutions 

in the country and the test will be required of the institutions under current federal law. This could 

be very burdensome to institutions that have weak systems and limited resources. We have found 

this to be true at small independent institutions here in Maryland as we implemented the state UR 

systems. It also constitutes a mandatory shortening to one-year the time for the institution to 

implement. 

Montgomery College Both the implementation and the feasibility study are on a timetable that is entirely too rushed to 

permit adequate review and development—at the institution, state, and NCES levels. At least one 

additional year prior to the feasibility study should be inserted, and universal implementation 

should be postponed an additional year to permit accommodation of the feasibility study’s 

outcomes. 

University of Colorado at Boulder Startup (internal definitions, agreement within system, work on state UR system to match, 

programming, modifying numerous internal processes to match new definitions): an estimated 

100-200 hours of director time plus 200-400 hours of staff time. Maintenance: probably no more 

than now. 

University of Maryland, Baltimore 

County 

The proposed implementation timeline is aggressive, not allowing for careful planning to avoid 

data problems and resolve privacy problems, and it would divert campus resources from other 

planned efforts. 

University of Miami The advantage with the delay for institutions is that they have more time to implement UR 

submission. 

Matching records 

Association of American 

Universities Data Exchange 

Almost all who responded indicated the difficulty of using SSNs to match data files. A 10-25 

percent error rate for mismatches using SSNs is not uncommon. The cleanup associated with 

correcting bad or missing SSNs is very labor intensive and would require additional campus 

resources. 

DePaul University The one that concerns me the most is the second one of having to reconcile "discrepancies" NCES 

finds with the data submitted. This need to clean up data will most likely require we reach back 

into our databases and force us to spend tremendous amounts of resources to match other federal 

records or records from other institutions and to do so in a manner that adds absolutely no value 

to the quality of decision-making at our institution. 

Dickinson College The change process will be difficult, especially at small colleges where there are data integrity 

issues, fiefdoms, and silos of data that make it difficult to match records. It is “hard to get the 

culture changed, but it is part of the burden.” 

Eastern Wyoming College Mismatches on SSN or any other student data would have to be resolved by each institution, 

which will be very time-consuming. A student who does not want to give us a social security 

number is allowed an option here, for example, but then that student may use another option at 

another educational institution. How we match up those student records could be a nightmare. 

Rensselaer Polytechnic Institute Our institutional research office currently consists of one person, the director, and that person is 

currently the IPEDS keyholder. According to the proposal, it is the IPEDS keyholder that must 

resolve all mismatches in the data submissions; this will place a substantial burden on this oneperson office. 

St. John's College St. John’s has never used the Social Security Number as a student identifier and, instead, have 

always elected to use a computer-generated number in order to protect our students’ privacy. The 

proposed collection system would be in direct opposition to our long standing college policy on 

this issue. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-11 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

University of Maryland, Baltimore 

County 

UMBC, like other University System of Maryland campuses, assigns a temporary 

SSN/identification number to international students, until they receive their official SSN. This 

will affect any matching that NCES tries to do for these students. It is possible, and likely, that 

other institutions would assign the same temporary number for some of these students. This will 

be an even greater problem as we move away from using SSN as the student identification code. 

In the new PeopleSoft system, we will be using a different unique code (unique to UMBC only), 

called EMPLID. Only students who apply for federal financial aid will be required to submit their 

SSN. 

University of New Mexico When I report aid to students I match a census file against the aid file to see what they were 

awarded—but this is always different than the total aid awarded, for all the reasons given above. 

We even have the issue of students being enrolled at more than one of our campuses, and 

receiving aid from only one campus—associating the aid with the campus enrollment is tricky, 

and sometimes more of an assumption on my part than actual data. Because we report enrollment 

as of "census" date (even our end-of-semester file captures only students enrolled as of each 

course's census date) there are always awards that don't have a corresponding record on our 

census files. Of course, we have transactional institutional records that show all enrollment, but 

that is very different data than we've reported to IPEDS in the past . . . It simply isn't easy to 

merge financial aid and enrollment data together, especially for campuses like ours where we 

have one financial aid office for all five campuses, but where we report our enrollments, and all 

other IPEDS data, as if we were five separate campuses. 

University of Oklahoma 4-5 percent missing SSNs is still a million students, with a million little research projects that 

NCES and schools would have to do. While there are a lot of good things that could come out of 

the system, it involves passing a lot of SSN work to the schools . . . This burden should not be 

trivialized and that while some of it is due to transposition from data entry errors, there will be 

many other sources of error. 

University of Wisconsin - Madison The UR IPEDS will make use of SSN to track students between institutions. At UW-Madison we 

have moved away from the use of SSN as key identifiers because of a state mandate that the SSN 

not be used as an identifier in higher education. We do not require that students provide a SSN if 

they don't apply for financial aid, so we don't have SSNs for all students. Plus, people change 

their SSN, so those changes have to be accommodated. 

University System of Maryland Our institutions are currently moving away from SSN as an identifier. This process has 

accelerated as new data systems have come online and concerns about identity theft have 

increased. The proposed data collection system will create major problems with student tracking 

and will require dedicated staff time to resolve. 

Washington University The follow-up on un-matched records has the potential to be extremely time-consuming for 

institutions. 

Staffing 

Alabama Department of 

Postsecondary Education 

Institutions will be burdened with additional staff and staff training needs. 

Association of American 

Universities Data Exchange 

Many of the institutional burdens were outlined in your summary of the second TRP meeting. 

Until more details are known, it is difficult to estimate the true institutional burden. Preliminary 

discussions, however, suggest that for IPEDS reporting obligations currently completed by 

system offices would need to be transferred back the campus. Private institutions have also 

reported large burdens to “gear up” for such reporting. Estimates of institutional burden have 

ranged from 600 hours per year to of one or two additional FTEs to “10 times what went into 

SEVIS” reporting obligations. Some have also indicated that unit record reporting would move 

IPEDS responsibility out of IR and into IT and operational departments. 

Bates College In many smaller institutions, student IPEDS reporting tends to be done by the registrar or by the 

person assigned to institutional research. Many institutions do not have full-time institutional 

research staff, or the role may be relegated to a primarily clerical role of coordinating data 

collection as the IPEDS web coordinator. Often the person is a half-time faculty or staff member, 

with many other competing duties. At our institution, we have long had difficulty in hiring and 

retaining the types of people with the skill levels required to do the more sophisticated reporting 

envisioned by IPEDS. (We also have de facto hiring limits, so adding staff to address additional 

reporting burdens is not feasible.) Developing the systems to address an IPEDS unit record 

mandate will force us to shift a significant portion of the resources of our 2.5 FTE staff IR office 

away from other mission-critical efforts in our job description, which include: accreditation 

support; outcomes assessment and institutional effectiveness activities; planning and research 

assignments for college administrators and faculty committees; enrollment planning. We are very 

fortunate that we have more staff than most small institutions, but the extensive task list 

mentioned above is not uncommon for others who coordinate IPEDS reporting . . . Many of the 

staff in the offices that will need to be involved in unit record reporting do not have access to or 

adequate training in the reporting tools that must be used to integrate the data. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-12

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

College of Notre Dame It would be necessary for us to expand the institutional research office, which is currently directed 

by a half-time person, in order to accommodate the additional reporting requirements that would 

occur multiple times during the year. I would find such a shift in resources unacceptable to the 

overall health and future stability of the college, especially since the benefits are questionable. 

College of Southern Maryland Once colleges have a functional description of the system, each institution will need to devote a 

large, and yet unspecified, amount of its resources in the form of programming, analytical 

support, and testing for development. 

Colorado College I am concerned about the financial costs—both computer capacity and staff capacity—to my 

institution to report data in this fashion. 

Columbia College Chicago The Office of Financial Services currently undergoes two major, federally mandated audits during 

the year that require extensive amounts of staff time and energy. This requirement would add to 

the Office of Financial Services reporting burden and repeat the information that is already 

reported to the federal government. In addition, work would need to be done to further integrate 

student accounts and financial aid data with the enrollment files. 

Community College of Baltimore 

County 

It is reasonable to assume that the initial start up costs will include additional personnel, possibly 

additional software, and changes to current processing of student record data. Structural changes 

of this nature require more time so that appropriate and adequate resources can be acquired. 

Financial aid administrator: large, 

private, four-year university in the 

Southwest 

I believe that it would not be difficult to provide this data, since it resides in the student 

information system. A programmer would be needed to write a program to extract the data and 

put it in the required format. It will take time to run the reports and send them to NCES, therefore 

it will require some additional staff hours to complete the task. 

Financial aid administrator: small, 

private college in the Southwest 

The response from our IT department is that this kind of report would be a low-impact project 

from the cost perspective. It would be simply staff time to develop a script to extract this 

information from our system. 

Howard Community College Whether for the pilot or for the official start of the project, the imposition of a substantial increase 

in employee workloads will stretch our current staffing levels to the breaking point. We can 

provide more information, if you need it, about the problematic nature of the integration of cost 

and financial aid data with our current student information system, the major potential 

mismatches with the use of Social Security numbers, and impossibility of applying the new 

race/ethnicity categories to current and former students. Ideally, a full-time staff member in 

admissions, another in information technology, and a third in institutional research would be 

needed to initiate this system. Budgeting for three new positions (a cost of at least $150,000 

annually) to address this initiative is not feasible now or in the foreseeable future for our 

institution. 

Indiana University My estimates of burden were based upon extensive discussions with my programmers regarding 

the potential data elements required, types of files to be created, and the prospect of providing 

verification for SSNs mismatches and data anomalies. The per hour rate ($50) is the current price 

for technology related services, and is a good proxy for this type of work. Since we will be 

responsible for multiple campuses I believe there will be an "economy of scale" in effect but will 

still require additional time, hence the use of the multiplier. Of course, with so many unknowns, 

it's exceptionally difficult to feel comfortable with such estimates but I do believe that these are 

conservative views on the potential burden. 

James Madison University None of our current programs are likely to meet the IPEDS standards and new ones will have to 

be rewritten, tested, and monitored for annual updates. The data keys proposed by IPEDS UR are 

also very different than the current programs, requiring separate programs. I estimate that one 

FTE staff for at least one year will have to be diverted from other important work in order to 

create the new data programs. Again, this estimate is based on my experience with rewriting all of 

the State Council of Higher Education for Virginia (SCHEV) programs during the conversion to 

PeopleSoft systems. The time gained by eliminating web entry into the current IPEDS collection 

is likely to be more than offset by complexities involved with multiple uploads created by IPEDS 

edits. Presently, a graduate assistant can enter the web form data. A higher paid staff person will 

have to manage the more complex UR system uploads, edits and management of edit data 

returned. 

Johns Hopkins University The IPEDS unit record proposal will at least double the current reporting burden because it 

increases the number of file submissions, increases the difficulty of reconciliation, and expands 

the scope of data collection. The time that will be devoted to federal reporting by offices that are 

already stretched too thin will require the addition of full-time, technical staff . . . All available IT 

and functional resources are already committed to the implementation tasks. We would have to 

hire and train new staff, or hire consultants at higher cost, to handle the additional workload. 

Lewis and Clark College, Whitman 

College, Mills College, Juniata 

College 

The amount of human power and financial resources forced on the institution by the system 

currently described are enormous. Our institution does not currently have sufficient computing or 

human resources to address even the most conservative data demands outlined in the current 

proposal. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-13 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

Marian College Costs to the facility to generate these files include: weeks, possibly months of total time from the 

Director of Institutional Research and the System Administrator for college information systems. 

Both offices are very lean in personnel and will have great difficulty in achieving other needed 

work during that time. It has long been a goal to integrate some of the currently separate systems, 

which we might have already begun if we weren’t always behind. We really cannot afford to hire 

another person to help with those duties, but that is what would be needed. 

Maryland Community College 

Research Group 

It is reasonable to assume that the initial start up costs will include additional personnel, possibly 

additional software and changes to current processes. 

McDaniel College Although institutional burden is an issue secondary to student privacy, it is nonetheless a very real 

issue to us and institutions like us. At McDaniel College we have a one-person institutional 

research office (as do 14 of the 18 MICUA member institutions), to complete the ever-increasing 

mandatory reporting, as well as surveys from publishers and the institution’s internal data needs. 

Further, we have only one database administrator for the institution who would have to do any 

programming necessary to meet the requirements of such a collection. The burden to the 

institutions would be great. 

St. John's College It’s a fact that office staffing is thinner in smaller colleges. Institutional researchers very often 

wear other hats and find their time limited by numerous obligations to the college. For these 

reasons, implementing a data collection system on this scale would be especially burdensome for 

small colleges. 

St. Olaf College Although our computer system contains most of the information the proposed plan would require, 

the amount of staff time needed to pull together all the information would be excessive. With 

tight budgets, we simply do not have the staff required to generate the type of detailed report this 

proposal would require. 

State Council of Higher Education 

for Virginia 

“Most edits have to do with making sure financial aid and enrollments are both merged properly.” 

The Association for Institutional Research (AIR) community has had numerous training 

opportunities over the years to try and help practitioners develop these skills in using and merging 

datasets and there are “no secrets on integrating this.” There is a wealth of material on this 

standard in IR and AIR has an IPEDS grant to conduct “train the trainer” sessions. This need will 

only get bigger if UR is implemented. 

Towson University The anticipated increased IT workload related to the proposal is by no means trivial as indicated 

by the resource estimates. Although the technical skills required to write the interface program(s) 

are not expected to be demanding, the real expense will be in the analytical skills required to: (1) 

analyze the mandatory specifications; (2) map and design appropriate translation business rules; 

and (3) test and reconcile invalid interpretations and assumptions. These costs will not only be 

incurred during the initial implementation phase, but will be realized for all succeeding years as 

the IPEDS specifications evolve over time. If modifications are necessary to our Peoplesoft 

student data structure, this will impose a greater burden. Additionally, if personnel and resources 

are redirected from organizational initiatives designed to reduce operating expense and/or 

improve services, those cost savings to the institution will be lost. 

University of Maryland Eastern 

Shore 

It would be difficult to implement a change of this magnitude without additional resources. These 

resources will be in the form of additional personnel both for short term and for ongoing tasks and 

for additional equipment. 

University of Texas system This reporting will be a significant burden to our staff and they are already stretched thin. 

University System of Maryland The transactional nature of the proposed system would require constant “cleaning” and 

reconciling of the data, which can only be accomplished by dedicated personnel. The lack of 

census dates and the proposed flexible reporting calendar changes data reporting from an episodic 

to a continuous activity. This, of course, adds to the cost since most of our institutions would have 

to hire additional staff. 

State/system unit record systems 

Association of Advanced Rabbinical 

Schools 

Where are the good educational outcomes of unit records? Where is the comparison of states 

with and without UR in order to see whether there was a difference relative to achievement? 

Where are the objective pieces of evidence that show how valuable it is on a national basis? 

There is no clear justification for the importance of undertaking this collection of UR . . . Where 

are the examples of wise policies and educational outcomes that they will gain with the national 

UR?” 

Brazosport College Will the state (re: unit record collecting by NCES) be able to do that for us? Our Coordinating 

Board collects unit records already and it would help if we wouldn't have to duplicate this 

process. If more data are needed, the state could simply add it to the list of items we submit—a 

whole lot easier than programming an entire system to satisfy a new requirement for data. 

College of Southern Maryland The requirement to report student unit records on a transactional basis will result in 6 to 10 

submissions each year. This is unrealistic given the existing resources of most colleges. 

Institutions in Maryland must also provide Student Unit Records directly to the Maryland Higher 

Education Commission on a periodic basis, thus increasing, rather than reducing, the amount of 

data flowing between educational entities. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-14

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

DePaul University At a very functional level, also as a researcher, it is obvious that many states including Virginia 

(where we worked . . . to institute the UR system in 1992 have student unit record systems. It 

would seem obvious to me that if in fact the benefits of unit records are real, then these states 

would have better institutions, better educated students, and better state-level educational systems 

with better levels of financial support. I can only wonder why data supporting this advantage over 

those states that do have unit record systems was not brought forth by my colleagues from New 

York, Virginia, and other similar states. Can State Higher Education Executive Officers 

(SHEEOs) from these states show better outcomes from analyses of their data? I am thinking 

about more than them being able to do more complex studies by themselves. But while on the 

topic of states the question does occur for those states that already have unit record systems, will 

the institutions be required to provide data for both record systems or will the states be required to 

use record systems that are consistent with the federal government. 

Financial aid administrator: 

community college in the Midwest 

Our state requires the two-year community colleges to college this data already. I’m uncertain if 

they require the same of the four year regents and the independents. For our Community Colleges 

there would be no additional costs, nor additional staff needed. 

Financial aid administrator: 

community college in the West 

In our state, we already report much of this data to our Chancellor's Office. Our state MIS 

submission is an important IT function that already involves a lot of staff and system time. 

Duplicating this effort to report essentially the same information in a different format to a 

different agency is costly and inefficient. We would request that this information be collected 

from state agencies in states that have already these data elements reported to them. It might also 

be easier for IPEDS. For example, in our state they would be working with just our Chancellor's 

Office rather than our individual colleges. 

Financial aid administrator: large, 

public university in the Mid-Atlantic 

region 

First, in our state, we already do unit record reporting . . .while the edits are onerous, it does 

provide a good, consistent (to the extent possible) database for description, evaluation and 

inference testing. Once you get in the hang of it, other than the edits (and at least in our state, 

they’re bad b/c the database is not quite robust enough to accommodate permutations of student 

enrollment/student financial aid as well as the edits could be more sophisticated) . . .it’s ok. 

James Madison University Because requirements of the state and proposed federal systems are not aligned in this proposal, 

at least two programs will have to be updated instead of one with every change in external 

requirements or internal system changes, thus doubling the maintenance requirements that 

currently exist for the SCHEV data files . . . The proposed system will also make completion of 

official data in state systems a greater burden. Because there is no synchronization between state 

and federal requirements in this proposal and current plans call for edits which state systems 

cannot predict, institutions are likely to increase the amount of time spent revisiting state record 

submissions after federal edits drive data changes. The opposite can occur if institutions submit to 

federal systems first. The prospects of a “federal-state edit loop,” where edits in one system create 

edits in the other, needs to be closely examined for this proposal. 

Maryland Community College 

Research Group, Wor-Wic 

Community College, Maryland 

Association of Community Colleges 

Currently, the Maryland community colleges provide data to the Maryland Higher Education 

Commission and the Commission uploads Completions, Student Financial Aid, Staff, Employee 

by Assigned Position, Enrollment, and GRS data into IPEDS for the community colleges. With 

the proposed unit record changes, individual institutions will report this data separately to the 

state and to NCES. Along with transactional file updates . . . institutional burden will greatly 

increase. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-15 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

Maryland Higher Education 

Commission 

The use of IPEDS UR would probably disrupt the valuable cooperative data process between 

institutions, states and IPEDS. Still more issues will result in increased burden to the institutions 

and even to the States... The burden to the institutions will be enormous. The burden to the states 

will also be very significant and may cause many states to reduce their role in coordination of 

IPEDS. It is highly unlikely that most States will be able to mange the proposed multiple 

submission requirements of IPEDS, modify their systems to accommodate these submissions and 

support the resolution of errors. Many states (Maryland included) would be unable to support the 

new IPEDS UR requirements with their current systems. Most of these systems are designed upon 

well-founded principles to collect statistical data about enrollment, degrees and financial aid. 

These systems are already integrated with IPEDS components and provide a tremendous benefit 

of establishing consistency across state and federal level. This will lead to a problem for the states 

to continue their systems in addition to the new IPEDS UR. It was felt that the loss of these 

systems would have a detrimental impact on the states in meeting their specialized needs and 

reporting such as state accountability or high school graduate performance feedback. Some of 

these needs were established by the legislatures or statutory bodies. This would lead to increased 

burden to institutions to report to both federal and state same data different ways. Most States 

(including Maryland) would also be unable to handle increased burden to process both their 

systems and the new federal IPEDS UR. The federal UR system is an ongoing data collection 

occurring throughout the year not just annually. States would be required to piggy back on the 

multi-submission schedule with their own data elements in order to reduce the double reporting 

burden on institution for separate federal and state UR systems. States will need increased 

resources to modify their systems and process the multiple submissions. It appeared that NCES 

had not factored in the enormous effort and costs to states and institutions to implement an IPEDS 

UR. They were more focused on their technical abilities to implement the system at their end. 

Since they have policies that do not allow outside access to the UR data, the states would not 

achieve the major benefits from such a system. NCES would need to make sure they provide 

adequate resources for special analysis of this repository of data needed by the states. There will 

be only three real choices states could adopt to live with an IPEDS UR system: (1) dual state and 

IPEDS UR—states continue to run their own systems. Institutions will additional burden to report 

both UR systems; (2) combined state/IPEDS UR—states would be required to retool their 

systems to adopt to the multi-submission requirements of IPEDS and integrate their data needs 

into the IPEDS format; and (3) disrupt state systems—states may be pressured into shutting 

down their own time proven systems and lose valuable analysis tools. 

McDaniel College We recently had a similar debate at the state level with the Maryland Higher Education 

Commission (MHEC). We came to a compromise based on three points: 1) MHEC agreed not to 

collect unit record data on students who are not receiving state aid; 2) they don’t use Social 

Security Numbers as a unique identifier on students who are not receiving state aid; and 3) 

MHEC developed a secure way to transfer the data. 

Minnesota Private Colleges 

Commission 

Though fully committed and coming with mandates, the schools “didn’t recognize the benefits 

until they got over the trauma of how to fit it within their regular work and manage it with their 

IR people.” 

Montgomery College Integration with existing state systems (such as in Maryland) needs considerable review and 

assessment to reduce conflicts, overlap, and incompatibility. Also, more time will be needed to 

determine and implement necessary adjustments. 

National Center for Higher 

Education Management Systems 

The states have an enormous amount of wisdom in this” and there is a “lot more commonality in 

these systems than believed” . . . The calculation of graduation rates for states is recognized to be 

flawed, and UR will allow for much better calculations to be made. “The absence of data leads to 

poor policy decisions.” 

Oklahoma State Regents for Higher 

Education 

Many states, including Oklahoma and Georgia, provide extensive support for IPEDS submission 

to institutions, thus the unit record data is not a problem. Unit record data could, in the long run, 

reduce the reporting burden to the institutions. By the way, Oklahoma assists the private 

institutions with IPEDS submissions. States that have state-wide unit record systems have had no 

difficulty in addressing the issues that were outlined in the boilerplate letters. 

St. John's College Regarding institutional burden in order to comply with the proposed collection system, the 

Maryland Higher Education Commission implemented a unit record data system under which the 

Maryland independent colleges submitted data for the first time this fall. MHEC is only tracking 

Maryland students who receive state aid. Submission of this small amount of data required 

several hours of work on my part and our Information Technology office. It required several edits 

and communication back and forth between the college and MHEC. 

State Council of Higher Education 

for Virginia 

Unit records allow us to tell stories and explain the complexity of the system that we couldn’t 

otherwise. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-16

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

State Higher Education Executive 

Officers 

NCES will submit a report to Congress in early 2005, which is expected to recommend steps 

toward the development of a national student unit record collection system. SHEEO supports the 

design and implementation of such a system. 

State University of New York 

System 

“If you can do it in New York, you can do it anywhere.” 

University of Colorado at Boulder Obviously would be far better for a state and its institutions if state UR matched federal UR. 

Some clearly do not. Seems as if these differences might be fruitfully studied. 

University of Texas system If it all plays out, it is important to ensure that “data at the state and national level are consistent 

so they tell the story consistently the same way, or we may end up with more dissatisfaction.” 

University of Wisconsin - Madison Wisconsin is listed by Highered.org as one of the states that already has a unit record data 

collection. Thus, many assume "we are already doing this" and so the transition will be of little 

consequence. That's not a complete picture. The UW System Administration collects the Central 

Data Request (CDR) for analytical—but not transactional—purposes. This CDR is used as the 

basis for UWSA to provide student record IPEDS reports for all UW's. If the UR IPEDS format 

includes enrollment files, completions, and financial aid information similar to the CDR, then the 

administrative burden may be similar to the burden imposed by the current unit record reporting 

requirements to UWSA. In the first few years, a considerable effort would be required to develop 

and program the system. The effort would include people from the registrar's office, student 

financial services, admissions, academic planning and analysis (IR), information technology, and 

perhaps some other offices. In the first year, it would draw staff away from institutional priorities 

directed to serving students. In the long run, the ongoing effort may be somewhat equivalent to 

the CDR; we devote considerable resources to checking, editing and verifying the CDR data, and 

in maintaining the system. However, the current proposal suggests that the UR IPEDS 

submissions will require more information than in our CDR model. UW System has indicated 

they will be unable to support our IPEDS submissions if the tuition information is included and if 

the UR IPEDS has transactional features. 

Wyoming Community College 

Commission 

In general, this proposal will help the Wyoming Community College Commission (WCCC) by 

making new kinds of data available to the state-level agencies. We support the general idea, 

however, we do acknowledge the concerns of the Wyoming community colleges and support 

their points of view. 

Subsequent enrollment redisclosure 

Association of American 

Universities Data Exchange 

Support for the proposal could be increased if institutions saw a value-added component to the 

reporting obligation. That is, if institutions could receive back from NCES information on where 

their students transferred to or enrolled in subsequent colleges upon graduation (e.g., where they 

went to graduate school), there would be greater institutional support for this proposal . . . If the 

proposal is implemented, there is a very strong desire for institutions to receive information back 

from NCES on their former students. For those students who transferred out or graduated from 

our institution, what institution did they go to, did they receive a degree from that institution and 

what type of degree (BA, MS, JD, Ph.D., etc), what degree program (major) were they in, etc. 

Campus would need unit-record data, not aggregate reports produced by NCES. 

Caspar College As I understand the proposal, one of the main goals is to be able to track students across 

institutions and state boundaries. We already know that many students do not graduate from their 

initial college or university—they start and stop, they drop to part-time, they enroll concurrently 

at multiple institutions, etc. I suppose that the tracking information will be interesting, but I don't 

see the real value to decision-makers in documenting known practices. Also, unless changes to 

FERPA are included with the proposed legislation, IPEDS cannot return information about 

individual students to the colleges for our internal use. 

Central Wyoming College It would be extremely useful to see what other higher educational institutions students have 

transferred to, what their program of study is or was, whether they have graduated and with what 

degree. This provides any institution with an excellent evaluation tool for program review 

purposes. 

College of Notre Dame College of Notre Dame already posts very strong graduation rates and this proposed initiative 

would only enhance the rates experienced by students who begin their college career with us. I 

am not concerned about what the “new” data would show. 

Colorado College To be fair, I am attracted to the proposed change for the ability it affords for institutions to track 

former students (both alums and drop-outs) after they leave us. 

DePaul University If participating in this activity of providing student unit records does not help us do our other task 

then it will most likely suffer as do other things which are mandated but seen as worthless to the 

University. It is within recent memory that NCES and IPEDS started providing useful data back 

to the institutions and it is obvious that this support coincided with a major improvement in the 

quality of the data provided by the institutions. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-17 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Eastern Wyoming College The advantages would relate to the increased quality of data related to transfer, graduation rates, 

persistence rates, and college costs. Ed Boenisch is quoted in the 12/7/04 Community College 

Times as supporting the proposal, since it would track every college and university student's 

progress. Currently it is particularly difficult to track students who move from one institution to 

another . . . The catch is that under the current law NCES cannot return record level data back to 

the individual colleges. That means we have the extra burden but receive little in return. 

However, if redisclosure of the information is specifically included in the Higher Education Act 

Reauthorization, then unit record data may be redisclosed to the colleges. It appears that the Dept 

of Education is in favor of giving unit record data back to the colleges and is willing to support 

the necessary wording in the reauthorization act. . . . I think we can safely assume that the 

submittal of the data to NCES in this proposal will be significantly more time consuming than the 

current IPEDS reporting system. However, if we can get detailed unit record level on each of our 

students such as transfer and degree completions at other institutions, then we would have useful 

information that is not currently available to us. I can get some of this information from the 

National Student Clearinghouse, but it is not complete and does not include all of our students. 

However, we will still have the benefit of receiving our graduation rates calculated by NCES. 

They will have access to all transfer and completions at other institutions, so in theory we could 

show a higher graduation rate. 

Financial aid administrator: 

proprietary school in the Midwest 

Our school is very much in favor of creating an industry standard collection instrument that 

institutions can complete as well as draw data from. 

Financial aid administrator: small, 

private college in the Midwest 

We do not have the internal support to provide that kind of data . . . I struggle with doing the 

National Student Clearinghouse submission and that is supported by Datatel. For us to provide all 

of the information requested would require massive programming and we don’t have the internal 

support to do that. 

Goucher College It is important to have this redisclosure of the data and that it is “very important to know.” 

Howard Community College Although a considerable burden will be placed on institutions to provide detailed data to NCES, 

colleges will not receive useable data about their students in return. The one-way flow of data 

may answer some questions about costs and transfer patterns at the national level, but it is at the 

institutional level that the data could be most useful. Without the flow of data back to the schools, 

there will be a sense of a tremendous amount of expended effort for no payoff. 

James Madison University While some transfer and post graduate enrollment data might become a reality, the detail of 

returned information is insufficient to explain “why” a student transferred or “what” a graduate 

could tell us about the value of their JMU degree. Without knowing “why,” the data provide little 

for the institution to effect change. Institutions need detail sufficient to survey their transfers and 

graduates. I am also skeptical that privacy laws will be amended to the degree that any detailed 

information is returned at all. 

Marian College IPEDS asks for things, such as transfers out of our college, that we don’t have and can’t get 

without paying a fee to the National Student Clearinghouse. While we have made submissions to 

the Clearinghouse, our normal data storage does not easily produce the needed file format, so we 

don’t do this on a regular basis. Typically, we haven’t reported those things to IPEDS (such as 

transfers out) that we don’t have a normalized method of capture. Even when we do have time 

and ability to submit to NSC, which is not every year, we don’t maintain it with our student data 

systems and would have to merge it into a new file. 

Montgomery College If the institutions are permitted no access to the additional data obtained about “their” current or 

former students, there is no benefit for the colleges in this process, and no opportunity to 

reconcile potential inconsistencies. 

Springfield College She and other institutional researchers really need to know why students are dropping out, that 

they “have to know that.” 

State Council of Higher Education 

for Virginia 

There is a “lot of legislative support for looking at what happens after they graduate.” The 

legislative money committees and education committees want to know what happens to students, 

inside and outside of the state. 

Temple University NCES should reconsider its stance about sharing UR data with the schools on what happens with 

their students. One of the benefits of using the National Student Clearinghouse is being able to 

evaluate how effective schools are and evaluating student experiences. “Please reconsider doing 

it.” . . . This would be “very good for institutions to have an effective program. If you are going to 

have UR, it is a marvelous opportunity to improve higher education. It impedes that opportunity if 

it is only one-way flow” of data. 

University of Colorado at Boulder I agree with many discussants that getting the data back, in UR form, would be incredibly 

valuable for institutions and for states. No one is going to want to go through all this simply to 

allow one and only one agency to have UR data for analysis. No amount of creative aggregate 

reporting could replace the UR data. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-18

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

University of Miami The more information you can give back to institutions (including institutions to which their 

students transfer and institutions where they eventually enroll in graduate or other higher-level 

schools), the better. It's also imperative that you provide us with information about any changes 

you make to our cohorts based on information you get from the national database (including the 

student's SSN)—otherwise we'll never be able to figure out why our version of IPEDS reports 

differ from yours. 

University of Wisconsin-Madison How will individual institutions get access to tracking information for about their own students? 

What kind of access to unit record or aggregate analysis will be provided? To realize the value 

and power of this data set, some return of information to institutions is essential. 

Wor-Wic Community College Secondly, our college has recently enrolled in the Enrollment Search and Degree Verify services 

of the National Student Clearinghouse in order to receive data about where our students transfer 

and if they earn degrees at other institutions. With the new unit record requirement for IPEDS, we 

would be supplying enrollment data files to the state, NCES and the Clearinghouse. Since NCES 

will not be providing transfer data back to the institutions, participation in the Clearinghouse 

would have to continue in order for us to receive this data. If NCES could provide data similar to 

what the Clearinghouse provides, we could eliminate sending additional data files to the 

Clearinghouse. 

Technical challenges 

Alabama Department of 

Postsecondary Education 

Institutions will be saddled with having to change administrative software systems. Vendors of 

administrative software systems will have to rewrite code and revise systems. The costs of these 

changes will be passed on the buyers, i.e., colleges and universities. 

Alverno College Our administrative software is DATATEL. It would be the company's responsibility to program 

such that any new recording/file transfer could be accomplished. Most likely some of those 

charges would be past on to the colleges. It will also take local programmers and users time to 

document, test, retest etc. any new programs. 

American Association of Collegiate 

Registrars and Admissions Officers 

Many additional variables will be needed, such as citizenship, which can require multiple coding 

of jurisdiction and status such as refugee or provisional enrollee. “By the time it is done, it will be 

a longer list.” . . . with the advent of web functionality, there has been a functional merger 

between financial aid, admissions, and registrar systems that makes the integration of these data 

much more possible than previously thought. While they may not be fully integrated, they are 

enough of a “one stop shop” that they let students register online, with all of the financial 

consequences which this entails. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-19 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

Bates College The technical obstacles to the proposed unit record reporting system are significant, and would 

require devoting excessive staff time and other institutional resources to the problem. Many 

smaller institutions would find the technical challenges to be particularly difficult to meet. We 

think that our institution is in a far better position from the technical standpoint than most small 

colleges, but having collectively over two decades of experience with how small colleges work, 

and how rapidly changes can occur, we have very serious doubts that we could both successfully 

and accurately implement such a change in the timeframe envisioned by IPEDS. Of course, the 

mandated fines would compel institutions to address the issue, albeit to the detriment of other 

programs and research of more immediate concern to the students of our institutions . . . One 

argument has been that most of the development costs would only be a one-time burden. This is 

not necessarily the case. Error-checking and data edits will be a recurring problem, even after the 

programming to prepare a draft report is done. The problem is amplified because resolving 

problems to ensure consistent reporting may now involve multiple offices. Many institutional 

research offices only have “read” access to data, and getting errors and edits resolved usually 

involves contacting one or more other offices who “own” the data and who have access rights and 

the authority to change it. Dealing with even one or two “exceptions” is a very time-consuming 

process, and it usually requires low-tech approaches—phone tag, e-mail, paper files, etc. With 

inflexible IPEDS deadlines, it is most difficult to get rapid turn-around to resolve these 

problems—often we cannot get through to the only person who can resolve the problem 

(sick/vacation, other deadlines, gaining approvals, etc.) in a timely fashion. We are inevitably 

stymied when dealing with certain individuals who won’t answer e-mail, voice mail, meet 

deadlines, etc. At these times, our technical skills must take a back seat to our skills at 

negotiation, diplomacy, and creative nagging. Occasionally, we must enlist a little “coercive 

support” from senior administrators, but in general, we have neither the authority nor the capacity 

to be “data police” across the units of the College. In a small institution, there may be little 

opportunity for cross-training or staffing redundancy, so if the authorized person cannot respond, 

we are at a loss. Because of these factors, we frequently end up in a situation where we can only 

obtain data from others at the very last minute, and this does not give us sufficient time to vet the 

report with others and to take other measures to ensure the accuracy of what we have to submit. 

We are committed to providing most accurate data possible, but if faced with an impending fine, 

we are forced to submit the best we can get by the deadline. We suspect that this will lead to an 

ongoing cycle where we’ll receive the IPEDS “published” data, review it, and recognize that 

we’ll have to revise it . . . We will still need to “pre-process” any unit record submissions to 

verify accuracy and consistency with institutional trends at the summary level prior to locking it. 

We will need to store an accurate copy of the institutional data in our archives, since others will 

only have access to IPEDS’ “perturbed” version that appears in the Peer Analysis System. We 

already have to spend more time than we can afford explaining and defending discrepancies 

between the accurate and the “perturbed” data, and we suspect that these problems will only 

increase. For example, it took us over a week to evaluate, recalculate, and explain some of the 

blatantly “off-target” derived calculations in the recently distributed NPEC IPEDS “Data 

Feedback report.” (IPEDS “one-size-fits-all” approach led to some very inaccurate 

representations of many small liberal arts institutions.) This experience gives us much less 

confidence in IPEDS’ ability to accurately process the unit record data it hopes to collect. Of 

course, as certain definitions or derived calculations change to enforce consistency and matching 

across components, many of our trend analyses will “break” and have to be either re-done or 

heavily annotated. Our own experience with several past changes in definitions is that we are 

required by our superiors to maintain data elements in both the old way (for internal analyses) and 

in the new way. And that leads to more confusion and less confidence in all of the data. 

Cardinal Stritch University How will an institution be able to counter what they believe to be mis-reporting by the 

government? For instance, if we submit enrollment fields, i.e., credits and hours attending, the 

government will calculate full and part-time rates. At our institution, we calculate graduate level 

full- and part-time status based upon whether the student is a part of a cohort. In other words, a 

student who is enrolled for less than seven graduate credit hours is still considered a full-time 

student if they are part of a cohort program. The government would not likely note such 

exceptions. How is the prospective parent or student truly going to be able to accurately interpret 

the government's reported aggregate values? The government would only be able to calculate 

indices with all schools the same. Currently schools submit not only tuition and fees data, but also 

book costs, as well as room and board costs. By only submitting tuition and fees and total price of 

attendance, it could be misperceived by the potential parent or student that an institution is 

inaccurately priced as exorbitantly high. 

College of Southern Maryland There seems to be no method identified to transmit these files. It may seem a small point, but 

wanting to upload the files electronically and bypassing an FTP system seems ill-conceived. 

Whether or not institutions have the electronic capacity to handle these large files is an issue. 

Large file transfers consume large amounts of resources. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-20

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

Community College of Baltimore 

County 

The Community College of Baltimore County is an institution that understands the importance of 

research and that the availability of data can aid in improving current practices. CCBC takes great 

pride in providing accurate and quality data. The submission of unit record data will require 

reporting at its highest level of integrity in order to provide information that can play such a vital 

role in the lives of our students. Suitable time and resources will be necessary to ensure quality 

reporting. 

Eastern Wyoming College I do not have information on how our Datatel Colleague system could/would handle the data 

retrieval requirements. 

Financial aid administrator: large, 

public university in the Southwest 

Our institution runs SIS-PLUS on a mainframe. Running this kind of data on our students would 

require significant programming time. It would not require (I don't think) an additional staff 

person. Of course our hope (as many others I suspect) would be that if this is a required and 

standardized report the mainframe providers (SCT, People Soft, etc) would permanently write the 

program to run as part of a standard maintenance cycle. 

Financial aid administrator: large, 

four-year, public university in the 

Northeast 

Two years ago, motivated by the prospect of a significant tuition increase and some nominal 

support from our IR area, I launched a serious effort to collect limited unit record data on 

financial aid recipients. Each of the issues you mentioned came up in one form or another during 

the discussions with data providers. We struggled, and never really resolved, issues of summer 

school aid (we have both "leader" and "trailer" campuses) and whether to report offered aid, 

accepted aid or disbursed aid. 

Financial aid administrator: large, 

public, four-year university in the 

Midwest 

Tagging onto the size issue, we’ve also seen a series of problems sending and receiving large files 

in our work on COD. The solution has often been to break our large files into a series of smaller 

ones, again causing more work and introducing the opportunity for error. Sending duplicate files 

is just one issue we’ve already seen. This is likely exacerbated by what I expect will be even 

larger file sizes for unit records than for COD records. 

Financial aid administrator: medical 

school in the Southeast 

Medical schools already submit the following data in the Student Record System to the American 

Association of Medical Colleges (AAMC). 

Financial aid administrator: midsize, private college in the Southeast Our data base system (Banner) contains all the proposed data elements, so I don't see that as an 

issue. My opposition is more philosophical than procedural. 

Financial aid administrator: 

optometry school in the West 

We are a small college with limited electronic support. We would probably have to do this 

manually if required. 

Financial aid administrator: 

proprietary school in the Midwest 

My concern is that some of the elements we do not collect and how would that be interpreted by 

the NCES and others. 

Financial aid administrator: Small, 

private college in the Midwest 

Given that caveat, of the data items you have listed, our system does currently contain all except 

possibly the six-digit CIP code for a program of study. It may be that the registrar does have such 

numbers for IPEDS etc and I am just not aware of it. If such a number sequence is not in place, it 

would obviously take some time to set up but would probably be not be overly time consuming or 

expensive. 

Financial aid administrator: small, 

private, liberal arts college in the 

Northeast 

The registration information they are looking for is easy enough to pull from the as/400. From 

everything I've read about this, the issues/concerns regarding the proposal are not based upon how 

hard it is to pull the data or the workload required, but rather the ethics of how the list will 

ultimately be used and/or shared. It is interesting that none of the questions asked were regarding 

that area, just how easy it would be to do. 

Houston Community College 

System 

I believe that the recent acquisition of PeopleSoft by Oracle could also have an affect on this 

proposed project. Oracle has verbally committed to continuing to support the PeopleSoft product 

for the next 10 years, but this is a gratuitous promise and cannot be regarded as a certainty. 

Conversion to another system for college administration would further increase expenses in times 

when resources are scarce. 

Johns Hopkins University Johns Hopkins does not have a university registrar. Some academic divisions, e.g. School of 

Medicine, maintain their own student record systems. The university is in the midst of 

implementing a new student information system. The Matrix system from SUNGARD SCT was 

selected in part because it provided the flexibility to manage student information eight different 

ways, according to the needs of each of the divisions. The university will need to retrieve data 

from satellite systems, the legacy system, and the new student information system. 

Lexington College We have a computer-based system of student unit records, but would have to create a different 

type of unit record system for NCES submissions. This is a big issue for us. We are a small, 

private institution, and changing our technology is not in the current budget. Would we receive 

funding to undertake this task? 

Marian College At a minimum, this would require a comprehensive systems analysis to determine data sources 

and timing, and careful file creation would require several weeks. Given the currently fragmented 

systems that would have to be accessed, it is doubtful that these processes could be even mostly 

automated in the foreseeable future. 

Maryland Higher Education 

Commission 

Lastly the use of a very new technology for data transfer (XML) was being pushed without 

regards to clear benefits to either side. In the meeting IPEDS did suggest they would support 

current ASCII text file transport as a option. This would eliminate state and institution costs to 

implement this technology. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-21 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records

 system, by selected topic—Continued 

 Comment 

Mount Mary College Over the past ten years we have diversified our programs in an effort to maintain a reasonable 

enrollment level; tracking these students in the way proposed would conflict with the ways we 

track them for our own purposes. We would not be in a position to provide these data 

electronically without maintaining a separate data set for our own tracking. Our experience is that 

the way we need to count our students, because it is atypical, never matches what we are asked to 

send to IPEDS. We meet the current expectations by extracting data and manually reconfiguring 

it into the way in which IPEDS asks for it . . . In addition, we already have an outdated system 

that does not provide a shared data base and we do not have the funds to upgrade our system. We 

certainly don't have the funds to comply with the proposed requirements either instead of or in 

addition to what we need to do for our own purposes. At present we are challenged to maintain 

the data that we need to operate our institution and provide the data required by IPEDS. There is 

no way we could meet these new expectations without major changes in our work and a 

significantly higher level of staffing. 

National Student Clearinghouse It will be a challenge for schools to scrape it up and put it together, since most of the data come 

from multiple systems and it will be difficult to integrate the data in the same time period 

depending upon when the reports are cut. The Clearinghouse collects way less than this. 

Occidental College While it is certainly true that finding out what happens to “transfer-outs” and tracking students 

who attend multiple institutions are important goals, requiring every single college in the country 

to report on every single student is a grossly disproportionate response. Virtually every social 

science research or policy question is answered not by bludgeoning the country with a nationwide data collection scheme, but instead by sampling. For several million dollars, a longitudinal 

sample of several tens of thousands of subject could be created to answer these same questions. 

That would be far less costly and intrusive than the proposed national unit record scheme. 

Purdue University There was some discussion about the current difficulty for larger institutions of reporting 

financial aid data in the XML format. Will there be supporting software, training and/or 

assistance for convert to the XML format? 

Rensselaer Polytechnic Institute Pulling the data in the format requested will take a complete re-examination of the computer 

system that Rensselaer uses for student records management. Pulling the data in the specified 

format may require significant modifications to fields, metadata, and reports. 

St. John's College Smaller institutions struggle with the implementation of new data transmission systems. On our 

campus, for example, there are several computer systems in use. Coordinating these systems for a 

reporting requirement of this magnitude would involve not only a great deal of staff time but 

great expense. The IT staffing just isn’t adequate considering the demands on their staff from all 

college offices . . . At St. John’s College, they have five computer systems and don’t have UR for 

a number of reasons—technology, managerial, privacy, and registrar protections. Lots of people 

would like a wall of data from admissions to registration and on through to alumni and 

advancement. St. John’s is playing out in miniature what is happening on a national scale. 

St. Lawrence University We are worried about declining data accuracy if we moved to the proposed UR reporting. For 

each IPEDS reporting cycle, the institution employs a thorough data cleansing process. Data entry 

or extraction errors might be discovered by running special queries and looking at aggregated 

data. Since UR reporting will rely on the submission of transactional data and follow a coding 

scheme that does not fit our institutional system, these quality checks will no longer be able to be 

employed . . . While we have a well-functioning, and well integrated homegrown information 

system, it would need to undergo substantial expansions and modification to accommodate the 

proposed UR reporting. Most significantly, we would need to develop a comprehensive audit 

system to flag record changes, requiring the acquisition of a separate server. Another start-up 

obligation would be the creation of hundreds of crosswalks from our internal coding scheme to 

the numeric format used in IPEDS UR reporting. None of these activities would directly benefit 

the institution! 

Towson University The data we report both internally and to external constituencies may not match the data 

ultimately reported by NCES because of different reporting methodologies. In order to ensure that 

NCES and the institutions are reporting comparable data; it will be imperative that standardized 

methods of analysis be developed and shared. 

University of California at Berkeley It will be difficult to include extension, summer, and assistantships at national labs that are not 

part of existing admin systems 

University of Colorado at Boulder Upload options need to include flat/ASCII files as well as more exotic formats. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-22

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

University of Maryland The feasibility of implementation depends on the cost, timeframe, and planning. While we go to 

great lengths and costs to assure quality of the census data that are currently collected and 

reported, to expand that process would require major changes in the campus infrastructure. Our 

transaction systems are designed to maintain daily operations for the institution. These systems 

do not keep longitudinal data or up-to-date information outside of the needs of the service 

offices. Our census system maintains historical, accurate, reliable information that is auditable 

and verifiable. While we still have data quality issues, we do our best to maintain documentation 

to explain changes in trends that are due to definitional issues. To blend these two systems 

together and maintain accurate and reliable data on a regular basis would require an integrated 

infrastructure that would take away a great deal of resources from the primary mission of our 

institution: to teach students. Data used outside of our census reports would not be deemed 

reliable by our staff and should not be used to characterize our institution. Given that the 

intention of the proposed data collection is to improve the quality of the data provided to NCES, 

this is a critical obstacle in the way of the success of this project. 

University of Maryland, Baltimore 

County 

For UMBC, this proposal comes at a particularly difficult time, as we are beginning a three-year 

effort to implement a new student information system (PeopleSoft). For us, this would mean 

developing the new reporting requirements twice: once for our legacy system and again when the 

PeopleSoft system is implemented. While we will not know the true impact (cost and effort) until 

the final technical specs are developed, we know they will be significant . . . As we interpret the 

data elements being required in this new UR system, there seem to be items that we now do not 

report (total price paid per student; total price charged per student; family flag; dependent status). 

This will require new programming logic and testing. 

University of Maryland Eastern 

Shore 

We shall need the services of a PeopleSoft consultant to determine our needs and help us write 

appropriate programs. 

University of Oklahoma While any systems change will create some real burdens, often ERP package systems may take 

years to catch up, especially if the process in not built into the software package. Changes to these 

vendors’ administrative information systems can be massive projects... XML is a much wordier 

way to store data and some submissions of XML data in California have had to break the file into 

pieces. 

University of Wisconsin - Madison Large institutions like UW-Madison often rely on commercial enterprise data systems. It may 

take years for vendors to provide patches and changes that support UR IPEDS, particularly since 

the software packages were not designed with UR IPEDS reporting in mind. And the application 

of those patches and upgrades can become major projects consuming precious technical and 

budgetary resources. Support from vendors is unlikely to be available during the pilot phase. 

Oracle's recent acquisition of PeopleSoft may complicate and delay any vendor-based support for 

UR IPEDS reporting. 

University System of Maryland Given the amount of data to be collected, the level of poor quality data which enter the system 

will be enormous. This will, for years to come, effectively frustrate any attempt to draw 

meaningful conclusions from the data which are not as likely artifacts of the data quality. 

Problems with tracking, changes in names, confusion about cost, nature of courses and credit 

hours, degree plan designations, and the “backfilling” of data cannot be resolved, in advance, to a 

degree which will address this problem. It will be several years of collection before this system 

could possibly hope to produce an information “signal” discernable through the data error 

“noise.” . . . In-house programming, and in some cases considerable work with consultants, will 

be required to enable current student information systems to produce the data for these reports. 

Beyond the direct costs created by these changes, opportunity costs will be incurred as 

implementation schedules are altered and pushed back to make this federal reporting a priority. 

Some institutions could lose as much as a year in their efforts to bring new PeopleSoft modules 

online. 

Viterbo University One of our biggest objections is the cost of converting to another system—personnel, time, and 

money. (I wonder if some company has been lobbying the government for this so they can "force" 

each institution to purchase their administrative system.) 

Terms 

Career Colleges Association Whatever is implemented needs to be fair and equitable in recording the instructional activity of 

all types of institutions and term structures, including summer. 

Goucher College [I am] jolted by the prospect of keeping up with all these status changes over multiple files over a 

term. 

Johns Hopkins University It will be a considerable challenge both within and across universities to coordinate academic 

calendars and determine the timing of federal submissions. The academic divisions at Hopkins 

operate on both semesters and quarters. Part-time programs offer courses that overlap terms. 

National Center for Higher 

Education Management Systems 

The issue of term structures and the nature of enrollment suggest the need for “radical ways of 

thinking about enrollment,” where higher education may look more like episodes in healthcare. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-23 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

Pima Community College How often should the file be created and transmitted? It must be at least twice a term—we have 

multiple terms. Our terms include fall, spring, summer (can be looked at in two fashions, since 

Summer Session C crosses over the fiscal year—July 1 is the start of the new fiscal year), a term 

for CTD, terms for Gila County enrollment which is reported on IPEDS by Pima Community 

College, and a term for students who are in a full-academic year term. 5. How should credit hours 

be reported—as attempted or as earned? If we send a UR file for our census date (45th day for 

Community Colleges in Arizona), then most credits would be attempted. The end of semester file 

could reflect both attempted and completed. If this reporting is going to be used for financial aid 

tracking, enough data must be submitted to show satisfactory academic progress. It is the 

frequency of creating the UR that is a major concern. We need to definitely send in a fall 

enrollment UR to establish a cohort for later reporting. For data to be comparable to past reports, 

we would need to sent in a census day file and at least an end of the year file to capture 

completions and enrollment that is not picked up on the first census day. 

St. Lawrence University Data integration would be most problematic where net tuition would be linked to enrollment 

activity, for the following reasons: 1) Our academic calendar year operates from fall to summer 

(end of August through beginning of August the following year), while our fiscal year cycle is 

July1 through June30. In aggregate reporting, it is easy to accommodate these adjustments; 

however, for unit record reporting, the two cycles would pose a significant problem; and 2) loan 

charges arrive throughout the year and are not specifically tied to a given semester, making it 

difficult to report charges beyond an entire academic year. 

Thomas Jefferson University Issues were raised about the official semester/term of record for medical students at freestanding 

medical schools such as Thomas Jefferson. Differentiated stop and start dates will be needed by 

student level and some kind of coding structure will need to be in place for these records and 

documented in the Institutional Characteristics (IC) file. 

University of New Mexico Reporting for multiple terms each year is also a major additional reporting burden. We'd still have 

to send reports to our state (since NCES can't release any data back out) and our state needs and 

state definitions are likely to be different than what would work for this proposed IPEDS 

collection. Thus we'd be doing two different files, would have to reconcile between them, etc. 

And the IPEDS burden would be year long, and not just a once-a-year report. 

Washington University I think the notion of unit record reporting does have merit in terms of the enhancement it could 

bring to concurrent enrollment, transfer activity, graduation rate, and time-to-degree issues on a 

national scale. These all address the Congressional issue of accountability by having a 

comprehensive set of data from which to report. The submission of census files several times 

during the academic year would not in my opinion present an excessive burden on schools, 

particularly when considering the trade-off in not having to do IPEDS Enrollment, Completions, 

and Graduation Rates anymore. 

Timing 

Association of American 

Universities Data Exchange 

Another concern was the reconciliation of unit record data against summary figures provided by 

NCES (how long will it take to do this within the current locking process). 

Brewton-Parker College After going over the collection processes necessary for the unit record collection system, the 

administrators from Brewton-Parker College propose that a the deadline for the fall enrollment, 

enrollment transaction update files, and student finance files not be prior to December 1. The 

team members all felt that the information related to the required variables could be gathered and 

input into the database by that time, making a reporting period deadline of early December a goal 

that could be achievable. 

DePaul University Further the timing will cause some of the variables to differ. For example citizenship for an 

international student may be one characteristic in the fall for Entering Fall enrollment and another 

characteristic by the time they complete their program for the Completions report. Of course the 

same is true for degree plan, program length, and many other variables. If this goes forward 

serious consideration should be given to putting information about the degree program into the 

term component of the record which I assume is reoccurring. 

Financial aid administrator: large, 

four-year, private, not-for-profit, 

university in the Mid-Atlantic region 

The admissions and financial aid cycles are anything but coterminous and in fact tend to be about 

a year apart with financial aid behind. This means, for example, when we generate data for the 

Common Data Set, we have to decide whether to submit data that is accurate from the most 

recently closed Award year, but a year behind the equally accurate admissions data, or develop an 

estimate of the current award year's likely result, that will not be completely accurate but will be 

consistent with the admissions submission. Since it seems ineffective, and perhaps unfair, to give 

prospective students inconsistent data and expect them to make the mental adjustment, we wind 

up doing the estimate. We have become relatively good at it and I am confident that we can make 

adequate estimates of current year aggregate data. However, I can think of no way to generate 

"estimated" unit record data. This means that the only way to have consistent and accurate data 

would be to lag the admissions data by a year, something I suspect the Congress will see as not 

responding in timely fashion. 

See notes at end of table. 
Appendix B — Estimates of Burden

B-24

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

George Mason University, Randolph 

Macon Woman’s College, St. Olaf 

College 

Developing transactional databases with records from over 6,700 institutions would create a 

verification quagmire, threatening huge delays in presenting meaningful, useful information such 

as NCES has begun to achieve in recent years. 

James Madison University The IPEDS UR system will degrade the credibility of institutional research across the country if it 

delays institutional ability to respond to data requests. IR is already expected to respond to a host 

of questions from both external and internal sources before data is official. This problem is most 

acute for fall enrollment reports, including data about first-time entering freshmen. Edits that 

might require an institution to change its FTF cohort have to be available so early that an 

institution can complete its fall enrollment no later than October 15th of each year. Also, IR shops 

cannot afford degradation to their credibility associated with changing official numbers or having 

more than one official number on the same subject . . . Again, timing is an issue with respect to 

existing state UR systems. To which system should an institution first submit its data? Will state 

systems still be open for edits after federal mandates force changes to the data? Financial data is 

very organic and synchronization of state and federal systems will help reduce the potential for 

generating different information on the same subjects. 

Mills College The current time-lag between data reporting and availability limits the usefulness of the IPEDS 

aggregates. I believe that NCES has underestimated the potential costs to colleges and 

universities while presenting an overly optimistic picture regarding the period of disruption in 

federal-level aggregates. Requiring more time and resources on my part to comply with NCES 

requirements while providing less timely access to peer data is simply an absurd proposition. 

New York Institute of Technology I believe that the file submission should occur after the traditional Fall semester has ended; in our 

case that means after the end of December (our Fall term ends roughly at the end of December). I 

don’t believe that the current IPEDS requirement of freezing data files in October has kept pace 

with the times. There are several reasons why fall enrollment may not be nearly complete by 

October; some of the big ones I can see are: (1) out of country enrollments where the fall term 

may not precisely coincide with the fall term here in the United States; (2) online colleges 

cropping up as part of traditional universities, which may have rolling admissions where the fall 

term is a moving target and students are continuously enrolling; and (3) Registrations from 

“offsite” locations that come in late for a variety of reasons. I think many colleges and 

universities are still attempting to fit their offerings into a fairly traditional fall term but I think the 

edges of the fall term are being pushed, with enrollments happening all through the entire term. 

For these reasons I think that if there is to be just one upload of record that it ought to occur 

sometime after December for the preceding fall term. However, I think a better solution is to have 

an upload at the end of December with new registration updates to fall enrollment for up to six 

months after the term has ended. 

See notes at end of table. 
Appendix B — Estimates of Burden 

B-25 

Table B1. Selected comments received from institutions regarding burden associated with implementing unit records 

 system, by selected topic—Continued 

 Comment 

University of Miami Creating a separate census file would probably produce less burden for us than trying to 

track/date census versions of these fields on an end-of-semester file (I'd suggest you allow 

institutions an option for how to report Enrollment (EF) data: those institutions for whom a 

snapshot is appropriate because they have a small number of terms could opt to send a census file, 

whereas other institutions for whom cumulative enrollments are more appropriate because they 

have rolling class begin-dates could use the end-of-term transaction file). With that exception, the 

fewer the number of files the better. . . . Transaction files: One problem with end-of-fall-term files 

is that many people take vacation at the end of December and early January, so having a due date 

as late as possible would be helpful. A single summer file, with two records for students enrolled 

both terms would be easiest for us (for one thing, we have classes that run across both summer 

sessions). August is a big vacation month so it would be better to have this due in September. It 

will really help with burden if transaction files can be snapshots that do not require tracking 

changes in status (e.g., for intensity, majors, etc.) since dates when many of these fields change 

(including intensity prior to our census date) are not stored on our homegrown computer system. . 

. . Completions: Degrees awarded over the summer are supposed to be posted by early- to midOctober, but our Registrar said the later this file could be sent, the better. In fact because of 

incompletes and issues related to international students, a number of degrees are retroactively 

posted during the year after the official degree date (I'd estimate our 4-year graduation rate 

increases around one full point when it's recalculated a year later, due to retroactive degrees). If 

you want accurate data you will need to ask institutions to provide an addendum to the prior-year 

Completions report each year to reflect these retroactive degrees, but this will of course increase 

burden (we don't record the date when degrees are recorded so it would require re-running the 

prior-year completions report and merging with the original report to identify discrepancies). . . . 

Financial aid: UM's financial aid year tracks our academic year (i.e., fall/spring/summer 

A/summer B). The SFA data should not be requested until well after the end of the aid year to be 

sure that effect of spring transfers, fall graduates, late applicants, and students who complete the 

verification process late are accurately reflected. Our Director of Financial Assistance Services 

(FAS) indicated the first two weeks of October were the lightest for his office, but our office 

would probably produce the file and those weeks are our busiest since that's when UM 

benchmarks its census file. November would be a better month for us. 

University of Wisconsin - Madison In order for UR IPEDS to satisfy the student loan reporting requirements there would need to be 

timely submissions at critical points in each semester such as: first of term, last drop date, end of 

term, and perhaps additional points. For example, UW-Madison submits six enrollment files per 

spring and fall semester and 5 files during summer to the National Student Clearinghouse in order 

to comply with student loan enrollment reporting. We have access to this system and there are 

clear benefits to the university and our students and alumni, so we can identify clear benefits to 

from our investment in this system. 

Viterbo University I think it would not cut down of the amount of time we currently put into IPEDS. We would need 

to reconfigure our data input/output and our methods of gathering information from students and 

personnel. 

SOURCE: Comments were taken from Technical Review Panel discussions or letters and e-mails send directly to HigherEd.org for the 

feasibility study. In some cases, the language has been modified to meet NCES publication standards. 
Appendix B — Estimates of Burden

B-26

Cost Estimates 

Comments about cost estimates fell into three general types: (1) data-driven—i.e., 

those examining a variety of factors in calculating costs; (2) basic—i.e., those that looked at 

only one or two factors, such as personnel time; and (3) opinion—i.e., those that did not 

appear to be supported with data but only with anecdotal claims or opinions. 

Data-Driven Cost Estimates

Four cost estimates examined a variety of factors and were somewhat data driven, 

including Indiana University (eight campuses), the University of Texas (UT) (nine academic 

campuses, six health science centers), the University of Maryland Eastern Shore (UMES), 

and Towson University. Of the two system offices, the total Indiana estimate is $143,400 for 

implementation and $54,000 annually; where the UT total estimate is $2,275,000 for 

implementation and $1,268,000 annually. Towson University estimates $210,500 for 

implementation and $162,000 annually, and UMES would require $378,000 to implement, 

but did not include an operational estimate. 

The Indiana methodology is “based upon the time it will take to create data 

extractions for a single campus and then modifications of those queries to accommodate the 

other campuses,” including “an estimate to cover hardware to store the data submissions.” 

The UT methodology “did not include any indirect overhead costs, but did include estimates 

for person hours required to reprogram and build new files and for transmission processes, as 

well as an estimate for the data verification process. In a couple of instances, the cost of 

additional hardware was included to archive submitted datasets. Some software costs were 

also included, however, the bulk of these costs are for personnel.” 

The UT estimates are at a more gross level of personnel costs, but average $151,667 

per school for implementation. The Indiana estimates are more refined, with personnel hourly 

estimates for each type of data file, but are less by half for the system as a whole than are 

calculated for UT. This discrepancy illustrates the different perceptions of the personnel costs 

and the inclusion of software upgrades for administrative information system improvements. 

These are more likely a function of these two systems preparedness for extracting and 

manipulating large scale datasets, with Indiana doing this centrally and UT passing the work 

and costs onto the campuses. 
Appendix B — Estimates of Burden 

B-27 

Towson includes the full $2,000 cost of a computer for each of four full- or part-time 

additional staff; while UMES would need to purchase nine $2,000 computers for staff and a 

special $10,000 server. UMES also built in $150,000 to retain a PeopleSoft consultant for six 

months. The President of Towson University reiterates that “this initiative will impose a 

heavy financial and resource burden on our institution.” The “anticipated increased IT 

workload related to the proposal is by no means trivial as indicated by the resource 

estimates.” The UMES estimate, the highest for any one institution that was received as part 

of the project feedback, includes effort by at least eight staff in addition to the PeopleSoft 

consultant. 

Basic Cost Estimates

A wide range of responses were received from schools whose cost estimates were 

less refined. There is little similarity between them. However, at least seven respondents 

suggest that the unit record proposal would require approximately one more full-time 

equivalent (FTE) staff member per year. This is based on their careful reading of the proposal 

and TRP summaries, which contain much more explanation of the specifics of how the 

system would work. James Madison University’s (JMU) institutional research office states 

that after needing one more staff FTE the first year, the cost burden would decrease to onehalf FTE annually. The cost of this one FTE ranges in estimates from $60,000 to $100,000 

per year and would vary based on regional cost of living differentials, among other factors. 

The discrepancy in estimates at even this most basic level is shown in these typical 

responses. The University of Colorado at Boulder suggested that the initial implementation of 

unit records would require 100 to 200 hours of the director’s time and 200 to 400 hours of 

staff time for startup. However, maintenance would not be any more than it is now. A joint 

letter from George Mason University and Randolph Macon Woman’s College that was 

disseminated widely to the institutional research community, and that was mentioned in other 

letters and comments, assumed that it would require “one FTE per institution at a nominal 

average salary of $60,000.” Mount Mary College’s estimate, which was not broken out, totals 

$750,000 for implementation because it has “an outdated system that does not provide a 

shared data base and we do not have the funds to upgrade our system.” The University 

System of Maryland estimates that it would take four to six additional FTE at a cost of 

$400,000 for implementation and $225,000 for subsequent years. The comparability of these 
Appendix B — Estimates of Burden

B-28

estimates is questionable, especially as most of these institutions participate in an existing 

state/system unit record system collection of student data. 

Some schools such as Pima Community College and Shorter College state that they 

can already do this kind of unit record reporting without additional effort, as do some of the 

financial aid administrators surveyed by the National Association of Student Financial Aid 

Administrators (NASFAA). NASFAA comments included statements that: “It is not a large 

task to get the information requested...It will take staff time but it should be minimal.” “It 

wouldn't require additional staff.” “This kind of report would be a low-impact project from 

the cost perspective. It would be simply staff time to develop a script to extract this 

information from our system.” Another financial aid administrator explained that, “Our data 

base system (Banner) contains all the proposed data elements, so I don't see that as an issue.” 

Opinion Estimates

Most of the estimates that were received were based upon anecdotal evidence and 

opinion and did not appear to be data driven. They focus on how the implementation of unit 

records would take staff time away from other projects, would require a major overhaul or 

upgrade of administrative information systems, or would simply “take months to implement.” 

Very often, these estimates are lumped in with other required changes coming from outside 

of NCES, specifically the use of new race/ethnicity categories and the need to submit data in 

XML format. OMB is requiring the new race/ethnicity categories for all unit record data 

collections and FSA is requiring the submission of unit record data using XML. 

Some schools report that their costs would be intertwined with the role of their state 

system or SHEEO offices. If two different unit record systems must be maintained, one for 

NCES and one for the state, then there would be an obvious perceived duplication of effort 

and increased burden. If the SHEEO or system could be modified to include the additional 

data elements needed for IPEDS, as some states do now, then there would be no increased 

burden with unit records, according to some institutions. 

Conclusions

Much of the data in providing estimates of costs for implementing unit records comes 

down to two factors—additional personnel and additional hardware/software. For schools 
Appendix B — Estimates of Burden 

B-29 

that are already well staffed, if priorities are not shifted, then additional work would require 

additional staff. However, this is estimated in the range of one-half to one FTE per school, at 

a cost of $60,000 to $100,000. This would vary with the role of central offices, such as in the 

different estimates of Indiana University and the University of Texas systems and the campus 

estimates of Towson University and the University of Maryland Eastern Shore. 

In preparing any cost estimate, two fundamental challenges will always remain: (1) 

the lack of good staff workload data; and (2) differences in administrative system capability. 

The Indiana University model is based on estimated hours for each of the different unit 

record files. These estimates are likely based on good internal tracking of projects and time 

sheet tracking. Few institutional research offices can afford this level of project management 

documentation, operating instead in a just-in-time production mindset. There are no easy 

comparisons of system capabilities either. For some schools, unit records would require a 

vendor contract in which the school pays someone else to extract and prepare the data for 

NCES, and the bid for this would include profit margins. At many other institutions, system 

offices already do this work and submitting student unit record extracts should involve 

minimal extra effort. Still at others, such as small career colleges, there would be a need to 

document print records in NCES-provided spreadsheets, which are needed already for 

adequate IPEDS reporting. 

Most institutions do not include the full, direct costs for new computers as part of 

their projected costs for implementing UR and this seems appropriate. The cost of additional 

servers and extensive, long-term consulting relationships with vendors for administrative 

software systems also should not be attributed as a full, direct cost of UR, since they would 

benefit and impact other functions at the institution. 

The actual increase in burden with the implementation of unit records would be the 

time necessary for resolving mismatches, which are estimated to be between 4 and 6 percent 

of all records based on NCES experience with NPSAS. Mismatches would be resolved by the 

school’s keyholder working with the IPEDS Help Desk. Special algorithms and “fuzzy logic” 

would be used to suggest possible matches and how best to resolve discrepancies between 

records, so that time spent on reconciling mismatches would be minimized. 

Some schools included in their burden estimates the time they would spend merging 

records and creating draft summary reports locally. This is certainly a choice; however, this 

burden of verifying the outcome and matching records locally would not be designed as part 

of the unit record system and would not be a requirement. The matching and editing 
Appendix B — Estimates of Burden

B-30

processes built into the system would be sufficient to accurately merge records and resolve 

mismatches. 

Without very complex and data-driven estimates, the range of perceived burden in 

terms of cost is very wide. There is some agreement, among a certain type of school, that it 

would require an additional FTE for the first year and probably somewhat less staffing 

annually after implementation. There would need to be a complex survey conducted of staff 

workload to determine true staffing hours. This has been shown to have limited utility unless 

extensive daily logs are in place and the results are tied to some kind of reward system. A cochair of the third Technical Review Panel meeting (at which the issue of cost estimates was 

discussed at length), Stan Ikenberry, replied that “these dollar estimates may not tell us much, 

in part because they would vary widely and aren’t really informative.” 

 The varieties and differences between administrative information systems are 

difficult to track. However, where extracting is already done by vendors or internally by the 

institution, the cutting of a dataset is not the question, so much as the process of handling 

mismatches. It appears that those schools that are most prepared to deal with the mismatches 

place a higher priority on data integrity and are willing to devote the staff time to resolve 

them; whereas other institutions might be more willing to let NCES assist them, using “fuzzy 

logic” and other techniques to tie streams of data together in order to resolve mismatches. 

Overall, perceived cost estimates appear to vary depending upon whether the 

institution desires to replicate and duplicate the NCES procedures locally. While NCES has 

stated that it would give out the SQL code for institutions that desired to calculate aggregate 

reports locally, this is not part of the intended function of the UR system according to the 

proposal and should therefore be separated from its cost estimates. The creation of aggregate 

reports prior to submitting UR data should be considered a quality check on the art of the 

institution, but it is not a required activity in the process as anticipated by NCES.