Higher Education Longitudinal Data System in New York State 26th Annual Management Information Systems [MIS] Conference February 14,

How many of your state’s high school graduates need to take remedial courses in college? How do your state’s high school graduates perform in their college courses? How do teacher prep program course grades equate with student performance on state tests? 2

Does success on state exams in high school translate to success in college? What college courses/programs lead to successful employment? What are some questions being asked in your state? 3

Charlene Swanson, Program Research Specialist, NYSED Russ Redgate, Product Manager, eScholar Andrew K. Setzer, Project Manger, P-16 Data Warehouse Project The linking of the P-12 and higher education data systems will allow for richer longitudinal analyses and the identification of additional opportunities to improve educational programs and prepare students for college and careers. 4

Background NYS P-12 Data Warehouse New York State Student Identification System (NYSSIS) State University of New York (SUNY) City University of New York (CUNY) Project Funding, Goals, Challenges, Buy- in and Resources needed 5

NYS P-12 Data Warehouse Started in 1999 with public schools grades 4 and 8 students Now contains all P-12 public and charter school students, and most non-public school students Scores, grades, attendance, teacher linkages, enrollments, and more… 6

New York State Student Identification System (NYSSIS) The New York State Student Identification System (NYSSIS) is a key element of New York State Student Information Repository System (SIRS). The New York State Education Department (NYSED) developed NYSSIS to assign a stable, unique student identifier to every pre-kindergarten through grade 12 student in New York State. Unique identifiers enhance student data reporting, improve data quality and ensure that important educational records are associated with the correct students as they transfer between local educational agencies (LEAs). In SIRS, each student record is uniquely identified with a 10-digit number assigned when the student first enters a State public school or participating nonpublic school. 7

State University of New York (SUNY) The State University of New York is the largest comprehensive system of universities, colleges, and community colleges in the United States, with a total enrollment of 480,000 students, spanning 59 campuses across the state. The SUNY system has 88,000 faculty members, 7,660 degree and certificate programs overall, and a $10.7 billion budget. SUNY and CUNY are separate and independent university systems, although both are public institutions that receive funding from New York State. CUNY, however, is additionally funded by the City of New York. 8

City University of New York (CUNY) The City University of New York is the public university system of New York City. It is the largest urban university in the United States, consisting of 24 institutions: 11 senior colleges, seven community colleges, and various other centers. More than 235,000 degree-credit students from 205 countries. The Black, White and Hispanic undergraduate populations each comprise more than a quarter of the student body, and Asian undergraduates make up more than 15 percent. Nearly 60 percent are female, and 29 percent are 25 or older. CUNY graduates include 12 Nobel laureates, a U.S. Secretary of State, a Supreme Court Justice, several mayors, members of Congress, state legislators, scientists and artists. CUNY is the third-largest university system in the United States, in terms of enrollment, behind the State University of New York (SUNY), and the California State University system. 9

Project Funding, Goals, Challenges, and Buy-in RTTT, 2 IES grants, Capital Funds from NYS Legislature FERPA and related privacy concerns Technology and resource challenges Importance of research and data 10

HE LDS Goals Create and Implement a System with Interactive Links to the expanded P-12 system –Expand the Architecture and Functionality of the P-12 Module and Implement a Higher Education LDS –Plan and Implement Standardized Higher Education Course Information –Identify "gatekeeper" and teacher preparation courses with SUNY/CUNY –Standardize course codes with SUNY/CUNY –Implement collection in SUNY/CUNY –Implement collection in private universities –Plan the Linkages to Health/Human Services/Workforce and other Data –Expand comprehensive student identifier system –Implement reporting linkages across four State agencies Create and Implement an Instructional Support System –Design the Reports for a P-16 Comprehensive Instructional Support System 11

Resources Needed to Make HE LDS Happen Funding! SED project manager SED project team –HE staff –IRS staff (including NYSSIS Team) –Researchers (SED and RRF) SUNY and CUNY project teams –IT staff –IR Staff SED hardware, software, data model, and IT Staff eScholar Support 12

eScholar CDW-PS™ What is the value of a data warehouse? -Unlock the value of siloed information -Siloed information becomes integrated -Analyze information across many functional areas -Gain insight into historical patterns, trends, factors affecting operational performance over time -Predict future operational performance -Inform decisions to effect improvement in operational processes and performance 13

eScholar CDW-PS™ eScholar Complete Data Warehouse® for Postsecondary –Enables state education agencies to gather, integrate and manage key postsecondary education-related data from a wide variety of operational systems and data sources –Stand-alone data warehouse platform can be integrated with CDW- PK12™ for a complete P-20 data warehouse solution –Incorporates configurable data collection, data quality, data transformation, data loading, and data error reporting layers –Track critical data such as institution and campus attributes, facts and history, student and staff demographics, qualifications, student educational background, courses, course enrollment, degrees earned, financial aid and transfer information, and more –Enables education agencies to accelerate implementation time and reduce implementation risk and cost 14

Benefits The eScholar CDW integrates data across functional areas, allowing educators and state leaders to analyze the data to investigate critical questions such as: What does the overall flow of students through the educational pipeline look like? What experiences (curricular or environmental) affect student success in making progress through the educational pipeline? What facilitates successful student transitions across specific boundaries—for example from high school to college, from two-year colleges to four-year colleges, or from either of these to and/or from the workplace? How are these transitions different for different types of students? What role does geographic mobility (e.g., transfer) play in inhibiting or enhancing educational credentialing or attainment? Questions taken from the NCHEMS/SHEEO “The Ideal State Postsecondary Data System 15 Essential Characteristics and Required Functionality.” 15

Benefits One of the primary uses of a P-20 unit record data system is to monitor, evaluate, and report education pipeline issues. Pipeline questions might include: How many students are we actually losing at each key transition point? How many students, and what percentage, that graduate from high school actually go on to college and ultimately graduate? How many students decide not to pursue a postsecondary degree immediately following high school but years later decide to enroll in college? What factors help students move successfully through key transition points in the education career, such as enrolling in college, transferring from two- to four-year colleges, or entering the workforce? 16

Original Goals of the NYS HE LDS Project For the school year, SUNY and CUNY will provide end-of-term student-level data to the Department’s P-20 data system. This information will include the student’s institution of higher education enrollment, full/part-time enrollment status, academic program of study, credit hours earned, participation in remedial coursework, and completed degrees. In addition, SUNY and CUNY will begin to integrate the statewide P-12 unique student identifier into their campus systems and processes. At the conclusion of the school year, these higher education data will allow the Department to evaluate career- and college-ready metrics (e.g., students who graduate from high school with a 75 or greater on the English language arts Regents and a 80 or greater on a math Regents) as a predictor of whether a student is required to enroll in a college remediation program across both CUNY and SUNY campuses. Beginning with the school year, NYSED will begin to collect student enrollment and performance in key courses from SUNY and CUNY, including teacher preparation coursework, “gatekeeper” courses (e.g., freshman English and math), and enrollment in courses designed to support the needs of students with disabilities and English language learners. At the conclusion of the school year, NYSED will also be able to evaluate career- and college-ready standards as a predictor of grades earned in key college courses (e.g., freshman English) across both CUNY and SUNY campuses. 17

Our Progress to Date SUNY, CUNY, Level 2, eScholar, NYSED (HE and IRS), Regents Research Fellow and a Project Manager –‘phases’ and timelines –Start with Fall 2011 data Possible future project improvements Your feedback and suggestions 18

NYSSIS Matching Received files for Fall 2011 from CUNY (236,899 records) and SUNY (482,984 records) There is no ‘hold queue’ for manual review Both will also submit Summer 2011 Both will also submit

NYSSIS Matching If there is a P-12 candidate with a match percentage of 90% or greater for a Higher Ed. record, it is automatically matched. Normally records with candidates who have a match percentage less than 90% and greater than 35% would end up in the hold queue. NYSSIS has the business rule coded that will not allow Higher Ed. records to go to the hold queue for a user to resolve. Instead NYSSIS will "try again" to match a P12 record that is reasonable or NYSSIS will assign a new NYSSIS ID. 20

NYSSIS Matching – some stats SUNY file: NYSSIS found a match for about two- thirds of initially submitted records ‘Older’ students, non-NYS residents, and non- public students (~14.3%) may not get NYSSIS IDs Test files (2 campuses) –Focus on students with NYS HS CEEB codes born in 1990 or later –93.62% and 97.90% respectively; 95.25% overall All SUNY = 95.92% 21

NYSSIS Matching – some stats Local HS S to Suffolk CCC – 245/247 = 99.19% Local HS N to Nassau CCC – 383/384 = 99.74% Local HS O to Onondaga CCC – 239/240 = 99.58% Local HS D to Dutchess CCC – 336/338 = 99.41% Local HS B to Broome CCC – 334/337 = 99.11% Local HS S to All SUNY - 509/513 = 99.22% Summary of above*: 1801/1812 = 99.39% Future issues: –Is 99.39% good enough? –Correcting mistakes? –Using a manual hold queue? –Other ? 22

Original P-16 Submission Calendar All campuses will be required to submit data two times per year: March 1 st For data from the Summer and Fall Terms (All terms ending between July 1 and December 31) and Annual Data for the preceding year August 1 st For data from the Winter and Spring Terms (All terms ending between January 1 and June 30) *NYSSIS ID File Submissions can be submitted at any time, but please avoid submitting files from September 1 to November 15. Thank you. 23

Phase 1 (4 templates) PS Student Institution –Name, DOB, ethnicity/race, gender, citizenship, etc. PS Student Enrollment –Information about student enrollment, majors, minors, degree seeking, dual enrollment, graduation, etc. Campus Student Fact Template –Information about remedial enrollment, hours, completion, etc. Campus Student Program Fact Template –Student support services participation 24

Phase 2 (6 templates) PS Student Credit GPA –Term GPA and credits and cumulative GPA and credits PS Student Transfer Fact –Information on transfer students Student Educational Background –High School graduation and GPA info Student Qualification –Exams and scores for entrance, placement, etc. PS Course Campus –Course codes, titles, descriptions, subject, credit, etc. PS Student Class Detail –Student class grades, credits, outcomes, etc. 25

Phase 2 Student Educational Background Student Qualification PS Student Transfer Fact PS Student Credit GPA PS Course Campus PS Student Class Detail 26

Phase 2 Student Educational Background Student Qualification PS Student Transfer Fact PS Student Credit GPA PS Course Campus PS Student Class Detail 27

Phase 3 (planned summer 2013) Student Award –Degrees, diplomas, certificates, etc. Student Campus Expense –Tuition, room and board, books, etc. Student Campus Financial Aid –Federal grants, state loans, etc. 28

Phase 4 (planning not finalized) PS Student Admissions ? 29

Future Project Improvements? Collect other/different/new templates Product enhancements Project Steering Committee Report Writing Getting NYSSIS matching to 100% Adding non-public colleges? NYSSIS ID in TEACH System? What else might we want to do? 30

Andy’s Analogy: Building a data warehouse is like saving for retirement. It is a long-term project. It does require a great deal of time, patience, steady investment, and adjustment. There will be a great payoff. 31

Feedback/Questions Andy Russ Charlene THANK YOU! 32