Karen WebberAssociate Professor,

The Institute of Higher Education, UGAPresentation for HEISEE, June 6, 2013

kwebber@uga.edu

Using National Data for Decision Support in US Colleges and Universities

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• Institutional Research• Institutional Effectiveness• Quality Assurance• Planning and Research

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Institutional Research

A focus on:

the collection, analysis, and reporting of information that leads to improved understanding, planning, and operating of institutions of higher education

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Data Collection and Use of Data

• Very helpful for institutional planning, quality assurance

• Can be used for benchmarking• May start small, informal• As more institutions get involved, grows larger, may

take on formal procedures

• Critical to have good infrastructure/technology• Critical to have definitions to ensure consistency

Institutional or System Database(s)

Student Data

• Addresses, enrolment qualifying scores, course grades, etc

HR Data • Address, phone, faculties group, etc

Finance • Tuition & fees, • E&G expenditures,

salary & benefits

Facilities•# buildings, sq ft figures, equipment,

Central data repository or Data Warehouse

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KWebber HEISEE 2013

Who Uses National/Regional Data and Why?• Many with Inquiring Minds:

– Institutional Research/academic planning officials– Educational researchers– Graduate students– Legislators– Policy Analysts

• Why?– Academic/administrative planning within an institution– Assessment; evidence of meeting goals, strategic plans– Scholarly inquiry– Policy, budget planning– Generalizable; reliable, good for policy considerations

Some data systems for higher education

• Australia – Higher Education Statistics Collectionhttp://www.innovation.gov.au/HigherEducation/HigherEducationStatistics/Pages/OverviewOfHigherEducationStatisticsCollections.aspx

– HERDC http://www.innovation.gov.au/Research/ResearchBlockGrants/Pages/HigherEducationResearchDataCollection.aspx

• South Africa – CHE and HEMIS– http://www.che.ac.za/about/

• EUMIDA– http://datahub.io/dataset/eumida

• UK – HESA– http://www.hesa.ac.uk/– http://www.ukcisa.org.uk/about/statistics_he.php

• Middle East, Latin America – beginning

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Data Systems for Higher Education

• EU – OECD Statistics and Data Lab– http://www.oecd.org/statistics/

• Eurostats– http://epp.eurostat.ec.europa.eu/portal/page/portal/education/introduction

• The World Bank data– http://data.worldbank.org/data-catalog/ed-stats

• World Higher Education Database Online – http://www.whed-online.com/about.aspx

• Croatia –– Croatian Bureau of Statistics, IDIZ, IED, CEP, ? Institutions, others

• US – IPEDS, NCES, NSF

KWebber HEISEE 2013

KWebber HEISEE 2013

U.S. Department of Education

Mission – to ensure equal access to education and to promote educational excellence throughout the nation.

Supplements and complements the efforts of states, local school systems and other instrumentalities of states, private sector, public and private nonprofit educational research institutions, community-based organizations, parents, and students to improve the quality of education.

http://ed.gov

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U.S. Department of Education

• Establishes policies on federal financial aid (distributes and monitors those funds)

• Collects data on America's schools and distributes research via reports and in some cases, datasets

• Focuses national attention on key educational issues

• Prohibits discrimination and ensures equal access to education

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National Center for Education Statistics (NCES)

NCES is the primary Federal agency responsible for the collection, analysis, and the reporting of data related to education in the United States

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National Center for Education Statistics (NCES)

On the web…• Monitoring Programs• Publications• Collecting Data

http://nces.ed.gov

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• Educational Level– Early childhood – Primary/secondary – Postsecondary

• Type of Data– Cross-sectional – Longitudinal

• Unit of Analysis– Individual Student or Faculty member– School (institution)

Types of Surveys and Data

NCES Data Sets

• IPEDS (Integrated Postsecondary Education Data System)

• Baccalaureate & Beyond (B&B)• Beginning Postsecondary Students Longitudinal Study (BPS)• Career/Technical Education Statistics (CTES)• High School & Beyond (HS&B)• National Longitudinal Study of 1972 (NLS)• National Postsecondary Study of Financial Aid (NPSAS)• National Study of Postsecondary Faculty (NSOPF)• Postsecondary Education Transcript Collection (PETS)

• Interagency Expanded Measures Enrollment & Attainment (GEMEnA) • Statewide Longitudinal Data Systems Grant Program (SLDS)

• Postsecondary Education Descriptive Analysis Rpts (PEDAR)• Postsecondary Education Quick Information System (PEQIS)

http://nces.ed.gov/surveys/SurveyGroups.asp?group=2KWebber HEISEE 2013

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Data Access

• Both NCES and NSF have some publicly-available data

• And some restricted access files

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Data Tools from NCES

• Executive Peer Tool (ExPT)• Peer Analysis System (PAS)• Powerstats and Data Analysis System

(DAS)

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Short Demonstration

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National Science Foundation – Nat Center for Science & Engineering Statistics (NCSES)• The responsibilities of NCSES have been broadened from those of the former Division of

Science Resources Statistics. Data collections related to U.S. competitiveness and STEM education are part of these new responsibilities. NCSES is responsible for statistical data on the following:– Research and development– The science and engineering workforce– U.S. competitiveness in science, engineering, technology, and R&D– The condition and progress of STEM education in the United States

• Core Activities. As one of 13 federal statistical agencies, NCSES designs, supports, and directs periodic national surveys and performs a variety of other data collections and research. The America COMPETES Reauthorization Act codifies the role of NCSES in supporting research using the data that it collects and its role in research methodologies related to its work. The legislation specifies the responsibilities of NCSES in supporting the education and training of researchers who use large-scale data sets, such as the ones NCSES now collects. The following activities form the core of NCSES work:

• The collection, acquisition, analysis, reporting, and dissemination of statistical data related to the United States and other nations

• Support of research that uses NCSES data• Methodological research in areas related to its work• Education and training of researchers in the use of large-scale nationally representative

data sets

http://nsf.gov/statistics/about.cfm

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NSF - NCSES• Each year produces about 30 publications, which can be

roughly divided into the following categories:

• InfoBriefs highlighting results from recent surveys and analyses;

• Detailed Statistical Tables (DSTs) containing extensive tabulated data from a particular survey;

• Periodic "overview" reports, such as Science and Engineering Indicators and Women, Minorities, and Persons With Disabilities in Science and Engineering; and

• Special reports, such as Interstate Migration Patterns of Recent Recipients of Bachelor's and Master's Degrees in Science and Engineering and Gender Differences in the Careers of Academic Scientists and Engineers.

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NSF Data Tools WebCASPAR and SESTAT

• provides easy access to a large body of statistical data resources for science and engineering (S&E) at U.S. academic institutions.

• emphasizes S&E, but its data resources also provide some information on non-S&E fields and higher education in general.

• https://webcaspar.nsf.gov/• http://www.nsf.gov/statistics/sestat/

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These Data Are Useful

• Intra- and inter-institutional data comparisons

• Monitor institutional progress, help with decisions

• Help national leaders monitor US higher education broadly– Reports and other information to the

public

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Data Used on Campus

• Ad hoc or regular, on-going reports to senior administrators

(e.g., deans, rectors, vice rectors)

• Institution Fact Book

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Also used for analytic studies

• Almost endless number of good research questions can be generated

• Examples:– Student access to higher education,

graduate school• Student demographics, location, type institution

– Effects of financial aid on student completion– Where/what do degree recipients go/do

after graduation?– What is relationship between financial

allocations and institutional outcomes

In US- a current focus on student financial aid

Example Research Studies

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Study on graduate student financial aid debt (Belasco, Trivette, & Webber, 2013)

• NPSAS data 2000 and 2008• About 49% all graduate students borrowed

for school in 2008; increased to 59% in 2008

• Mean debt $42,000 in 2008• Higher for doctoral and professional

students, but more master’s• More debt incurred by Black and Hispanic,

less for Asian than white students

Also a focus on degree completion

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Study on benefits of the earned doctorate (Webber et al, 2013)

Using NSF’s Survey of Doctorate Recipients:• What individual economic benefits accrue for

doctoral degree recipients from the time of doctorate graduation (1998-99) to the present time (2008)?

• Are there differences in the economic benefits resulting from debt assumed and sources of financial support during degree enrollment?

• What effect does time to degree completion have on the economic benefits obtained by doctoral degree recipients?

1999

2001

2003

2006

2008

$0 $20,000 $40,000 $60,000 $80,000 $100,000 $120,000 $140,00062051

71738

80893

90175

104336

72189

81560

90055

99309

112799

86999

99846

107503

117001

130464

Average Annual Salary of Doctorate Recipients by Job Sector

Business & Industry

Government

Education

Source: Survey of Doctorate Recipients, National Science Foundation

KW study on benefits of the earned doctorate

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Interest in faculty work and faculty productivity

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Study on Postsecondary Faculty (Webber, 2012)

Using 2004 National Study of Postsecondary Faculty:

• What factors contribute to a faculty member’s research productivity

• Are there differences in productivity for US- vs. Foreign-Born faculty/academic staff

Recent Scholarly Works by US- V. Foreign-Born Status

Born in US N=2990*

Foreign-Born N=1190

Mean SD Mean SD p Refereed articles 3.81 4.846 5.56 5.862 **

Non-refereed articles 1.40 2.885 1.86 3.840 **

Book revw, chptrs, creative wrks 1.23 2.180 1.20 2.063

Books, textbooks .61 1.525 .66 1.496 **

Presentations 5.84 6.792 7.22 7.177 **

Exhibitions, performances 1.23 6.453 .36 3.067 **

Patents .15 .683 .24 .830 **

Total Recent Written Works 7.07 9.491 9.29 9.355 **

** p <.01

* all Ns are weighted and rounded

Results from NSOPF study

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KWebber HEISEE 2013

Results from NSOPF:04

Born in USN=2990*

Foreign-BornN=1190

Mean SD Mean SD  p

% Time on Research 32.83 22.205 39.43 21.926 **

% Time on UG Instruction 30.96 26.839 24.47 23.163 **

% Time on Graduate Instruct 22.37 19.834 23.56 17.183  

% Time Other Activities 13.85 12.880 12.55 12.437 **

Student Credit Hours Generated 227.76 269.761 184.70 206.012 **

           

Annual Salary          

Base salary $78,277 $34,453 $79,936 $33,677  

Total annual income $95,726 $46,423 $94,540 $43,154  

Time Allocations and Salary by US- V. Foreign-Born Status

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Growing Discussions About Postdoctoral Researchers

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Study on postdoctoral researchers (Yang & Webber, 2013)

• Does the choice to take a postdoctorate research experience affect career path?

• Does taking a postodoctorate research experience affect productivity or salary a decade later?

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Results on postdoc study

• Taking one or more postdoc appointments significantly increased likelihood of going to education sector and earning a tenure-track faculty appointment

• Take one postdoc increases productivity, but two or more does not add more

• Taking postdoc does not affect salary 10 years later

Questions, Discussion

• Questions on IPEDS?

• What are the most pressing questions that you have that would be better answered with data similar to IPEDS?

• What are the obstacles to inter-institution data collection in Croatia?

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Critical Elements

• Good data infrastructure

• Data definitions to ensure consistency

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This may be of interest

Principles and Practices for a Federal Statistical AgencyConstance F. Citro and Miron L. Straf, Editors

Committee on National Statistics; Division on Behavioral and Social Sciences and Education; National Research Council , 2013.

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Principles for a federal statistical agency (Citro & Straf, Eds., 2013)

• Relevance to policy issues• Credibility among data users• Trust among data providers• Independence from political and other

undue external influence