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 1 CUNY Institutional Data for Research and Policy Analysis

2. 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

3. The Institutions of CUNY 3 24 colleges and professional schools  11 senior colleges  7 baccalaureate +  3 “comprehensive” colleges  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

4. Undergraduate Student Profile 4 Senior CollegesCommunity CollegesTotal Undergraduates Total Undergraduate EnrollmentN137,220 91,264228,484 Female% 58.6 Race/Ethnicity American Indian/ Alaskan Native% 0.2 0.3 Asian% 19.3 15.4 17.7 Black% 25.7 29.0 27.0 Hispanic% 24.0 36.6 29.0 White% 30.7 18.8 26.0 AgeMean 24.0 25 Years and Older% 28.5 28.2 28.4 Attend Part Time% 30.3 39.4 33.9 Born outside of U.S. Mainland% 42.9 43.7 43.3 Countries of AncestryN 206 190 210 Native Language Other than English% 41.8 46.3 43.6 Languages SpokenN165 189 Pell Grant Recipients 2 %52.864.557.3 Household Income Less than $20,000 3 %32.846.238.1 First Generation in College 3 %41.548.444.2 Married 3 %13.413.713.6 Supporting Children 3 %13.215.614.2 Work For Pay more than 20 hours per week 3 %33.229.831.8

5. What is institutional research? 5 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

6. Institutional Research at CUNY 6 Provides support for…  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

7. Who we study 7 Students  Applicants  Enrolled Students – undergraduates and graduate students  Degree recipients Faculty  Profiles  Workload

8. Institutional Data Sources Freshman and Transfer Application Processing Data System Student Information System Basic Skills Tests Financial Aid Packaging Financial Aid Disbursement 8

9. Institutional Data Student Data  Applications/High School Background  Enrollments/Registrations  Basic Skills Test Scores  Financial Aid  Degrees granted Employee Data  Work History  Teaching and other activities 9

10. Organization of Institutional Data 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  Cross section/Trend reporting  Longitudinal tracking  Oracle Database, data organized into:  Fact tables  Dimension tables  Lookup tables  End-user layer developed to make data more accessible 10

11. How are data moved from operational systems into a data warehouse? 11 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 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 semester- based fact and dimension tables.

12. 12 CUNY IRDB Data Flow Diagram CAS (freshman admissions) Special Reports Standardized Files Joins from Multiple Tables across Multiple Terms Group by Selected Columns (SQL) Oracle Discoverer Crosstabs Ad-Hoc Queries Migrate Data into Oracle9i Environment (SQL*Loader) Normalize Data (PL/SQL) Oracle Forms CUNY Data Book on Institutional Research Web Site Extract Files Oracle Discoverer Tables ASTA (transfer admissions) SHOW (enrollment) SKAT (skills tests) PERF (grades) GRAD (degrees) NCES (job survey) SFA (financial aid) Clearinghouse (transfers to non-CUNY colleges) Reformat and Clean Input Files (SPSS) Create Fact and Dimension Tables (SQL) Migrate Data into Oracle 9i Environment (SQL*Loader) Type or Cut and Paste SPSS for Windows Crystal Reports and Oracle Portal Institutional Researchers University Administrators Public Users Oracle Discoverer Crosstabs Staging Tables Code Descriptions from File Layouts PC Files Operational Data Store (normalized student-level data) Lookup Tables (metadata) Flash Enrollment Summary Tables (denormalized aggregate-level data) Data Warehhouse (denormalized student-level data) Longitudinal Cohorts (denormalized student-level data) Ad-Hoc Queries Spread sheets

13. CUNY OIRA Reports http://www.cuny.edu/ir http://www.cuny.edu/opr 13

14. Overview: NYCDOE–CUNY Data Exchange 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? 14

15. Gates_NLC_Using Data as Information to Drive Change_1_24_2012_cuny.pptx Gates_NLC_Using Data as Information to Drive Change_1_24_2012_cuny.pptx 15

16. LTDB – Longitudinal Tracking Database DOE and CUNY matched student records  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 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 16