CUNY Institutional Data
for Research and Policy Analysis
1
CITY UNIVERSITY OF NEW YORK
COLIN CHELLMAN, PH.D.
ASSOCIATE DEAN FOR INSTITUTIONAL RESEARCH
CHERYL LITTMAN, PH.D.
DIRECTOR OF THE PERFORMANCE MANAGEMENT PROCESS
The City University of New York
2
 Largest Public Urban Higher Ed System in the US
 23 Institutions, community, senior and graduate
colleges
 Located across all 5 boroughs of New York City and
online
 272,000 degree-seeking students
 250,000 adult and continuing education students
 Racially, ethnically, socioeconomically diverse
 7,300 full-time and 11,000 part-time Faculty
The Institutions of CUNY
3
 24 colleges and professional schools
 11 senior colleges
7 baccalaureate +
 3 “comprehensive” colleges


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7 community colleges
Macaulay Honors College
CUNY Graduate School
CUNY Law School
CUNY Graduate School of Journalism
CUNY School of Professional Studies
CUNY School of Public Health
Undergraduate Student Profile
4
Undergraduates
Total Undergraduate Enrollment
Female
Race/Ethnicity
American Indian/ Alaskan Native
Asian
Black
Hispanic
White
Age
25 Years and Older
Attend Part Time
Born outside of U.S. Mainland
Countries of Ancestry
Native Language Other than English
Languages Spoken
Pell Grant Recipients2
Household Income Less than $20,0003
First Generation in College3
Married3
Supporting Children3
Work For Pay more than 20 hours per week3
Senior Colleges
Community Colleges
Total
N
%
137,220
58.6
91,264
58.6
228,484
58.6
%
%
%
%
%
Mean
%
%
%
0.2
19.3
25.7
24.0
30.7
24.0
28.5
30.3
42.9
0.3
15.4
29.0
36.6
18.8
24.0
28.2
39.4
43.7
0.3
17.7
27.0
29.0
26.0
24.0
28.4
33.9
43.3
N
%
N
%
%
%
%
%
%
206
41.8
165
52.8
32.8
41.5
13.4
13.2
33.2
190
46.3
165
64.5
46.2
48.4
13.7
15.6
29.8
210
43.6
189
57.3
38.1
44.2
13.6
14.2
31.8
What is institutional research?
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Institutional research is a form of “organizational
intelligence,” providing decision makers with information
about an institution, its educational objectives, goals, and
purposes, environmental factors, processes and structures
to more wisely use its resources and more successfully
attain its objectives and goals.
-- Knight (2003). The Primer for Institutional Research
Institutional Research at CUNY
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 Provides support for…
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University accountability
Policy analysis
Outcomes Assessment
Academic program review and accreditation
Program evaluation
Regulatory reporting to federal, state, city government
Press inquiries
Reporting to commercial and inter-institutional
agencies
Marketing
Who we study
 Students

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Applicants
Enrolled Students – undergraduates and graduate
students
Degree recipients
 Faculty

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7
Profiles
Workload
Institutional Data Sources
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 Freshman and Transfer Application
Processing Data System
 Student Information System
 Basic Skills Tests
 Financial Aid Packaging
 Financial Aid Disbursement
Institutional Data
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 Student Data
 Applications/High School Background
 Enrollments/Registrations
 Basic Skills Test Scores
 Financial Aid
 Degrees granted
 Employee Data
 Work History
 Teaching and other activities
Organization of Institutional Data
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 Operational Systems

Transactional data systems, live, changing
 Frozen Extracts


Census data snapshots of operational data systems
Systematic, repeatable
 Relational Databases

Data organized to facilitate analyses

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Oracle Database, data organized into:
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Cross section/Trend reporting
Longitudinal tracking
Fact tables
Dimension tables
Lookup tables
End-user layer developed to make data more accessible
How are data moved from operational systems into a data
warehouse?
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 Step 1. Snapshots are extracted from operational systems.
 Step 2. Extracted files are reformatted and cleaned.
 Step 3. Pre-processed files are loaded into staging tables and
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metadata are loaded into lookup tables in an Oracle relational
database.
Step 4. Data in the staging tables are migrated to normalized tables.
Step 5. Summary tables and other high performance query
structures are created from the normalized tables and lookup tables.
Step 6. Semester-based fact and dimension tables are created from
the normalized tables and lookup tables.
Step 7. Longitudinal fact tables are created from the semesterbased fact and dimension tables.
CAS
(freshman
admissions)
CUNY IRDB
Data Flow Diagram
Longitudinal
Cohorts
(denormalized
student-level
data)
ASTA
(transfer
admissions)
SKAT
(skills tests)
Migrate Data
into Oracle9i
Environment
(SQL*Loader)
SHOW
(enrollment)
Standardized
Files
PERF
(grades)
GRAD
(degrees)
Staging
Tables
Normalize
Data
(PL/SQL)
Operational
Data Store
(normalized
student-level
data)
PC Files
Migrate Data
into Oracle 9i
Environment
(SQL*Loader)
Oracle
Discoverer
Crosstabs
Extract Files
Ad-Hoc
Queries
Institutional
Researchers
Joins from
Multiple Tables
across
Multiple Terms
Oracle
Discoverer
Tables
Create Fact
and Dimension
Tables
(SQL)
Reformat
and Clean
Input Files
(SPSS)
SPSS
for
Windows
Data
Warehhouse
(denormalized
student-level
data)
Oracle
Discoverer
Crosstabs
Spread
sheets
Ad-Hoc
Queries
University
Administrators
Group by
Selected
Columns
(SQL)
Lookup
Tables
(metadata)
NCES
(job survey)
SFA
(financial aid)
Clearinghouse
(transfers to
non-CUNY
colleges)
Type or
Cut and Paste
Code Descriptions
from File Layouts
Summary
Tables
(denormalized
aggregate-level
data)
Oracle
Forms
Crystal Reports
and
Oracle Portal
CUNY Data Book
on Institutional
Research
Web Site
Special Reports
Public Users
Flash Enrollment
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CUNY OIRA Reports
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•
http://www.cuny.edu/ir
•
http://www.cuny.edu/opr
Overview: NYCDOE–CUNY Data Exchange
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•
CUNY/ DOE MOU
 Established in August 2008
 A new two-way data-sharing agreement created an opportunity to
examine the common research goals of both institution.
•
Research designed to support policy for:
 Administration
 Central office staff
 Schools and colleges
•
Shared research agenda with focus on college readiness
 Policy questions informed by data
 What happens to DOE students in their first year at CUNY?
 What are predictors of college success?
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 Gates_NLC_Using Data as Information to Drive
Change_1_24_2012_cuny.pptx
LTDB – Longitudinal Tracking Database
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 DOE and CUNY matched student records
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No reliable common identifier before matching
Matching algorithm developed to ensure a degree of accuracy and reliability
Match process identifies best match between DOE graduates and CUNY
enrollees
Common identifier assigned to individual student records
 Student data – DOE students who applied to or enrolled at
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CUNY
Data from both systems structured to facilitate trends and
tracking over a student’s secondary and post-secondary career
Access for DOE and CUNY institutional researchers
Flexible cohort definitions
Item and row-level security