CUNY Institutional Data for Research and Policy Analysis

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 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 Recipients 2 Household Income Less than $20, 0003 First Generation in College 3 Married 3 Supporting Children 3 Work For Pay more than 20 hours per week 3 Senior Colleges N % 137, 220 58. 6 Community Colleges 91, 264 58. 6 228, 484 58. 6 Total % % % 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 % 206 41. 8 165 52. 8 190 46. 3 165 64. 5 210 43. 6 189 57. 3 % % 32. 8 41. 5 13. 4 13. 2 46. 2 48. 4 13. 7 15. 6 38. 1 44. 2 13. 6 14. 2 % 33. 2 29. 8 31. 8

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

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

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

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

Institutional Data 9 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 10 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 Oracle Database, data organized into: 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? 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 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 Oracle 9 i 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 9 i 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 Oracle Forms Summary Crystal Reports Tables and (denormalized Oracle Portal aggregate-level data) CUNY Data Book on Institutional Research Web Site Special Reports Public Users Flash Enrollment 12

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

Overview: NYCDOE–CUNY Data Exchange 14 • 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?

15 Gates_NLC_Using Data as Information to Drive Change_1_24_2012_cuny. pptx

LTDB – Longitudinal Tracking Database 16 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