Illinois Longitudinal Data System Higher Education Consortium Annual Meeting

1. Illinois Longitudinal Data System Higher Education Consortium Annual Meeting July 28, 2011

2. Goals of this Meeting • The primary purpose of today’s meeting is for the participating institutions to elect their sector’s Governing Board members. • After today’s meeting, we will have: • Established the Governing Board • Established the Chair at Large • Collected names of individuals who are interested in serving on a Standing Committees • Discussed the qualifications of the Administrating Institution

3. Agenda • Protocol – Remote Participation • Presentations • Discussion on the duties of the Governing Board/Committee Members – Working Lunch • Election of the Governing Board • Standing Committees/Election of the Governing Board’s Chair Person at Large • Qualifications of the Administrating Unit • Next Steps

4. Activities to Date • October 29, 2010 – ILDS Higher Education Consortium Organizational Meeting • February 25, 2011 – ILDS Governing Board Meeting • June 15, 2011 – Annual Meeting Conference Call

5. Protocol - Remote Participation TO ATTEND THE WEB CONFERENCE WITH AUDIO TEST YOUR BROWSER BEFORE YOU ATTEND YOUR FIRST WEB CONFERENCE Visit https://meetingplace.aces.illinois.edu/test/ to test your web browser for compatibility with the web conference. Meeting ID:    1460 Meeting Password: 7814001. Go to: https://meetingplace.aces.illinois.edu/a/5b8913f139cf41f6011b7e12a81526d7 2. Sign in as a Guest, and click on Attend Meeting. Accept any security warnings you receive and wait for the Meeting Room to initialize. 3. Then call in to the phone number:  Phone Numbers: 800-347-8268 (Toll-free)

6. The audience has a focused view

7. Presentations • IBHE Data Warehouse • IHEC Data Models • ILDS Data Match - ISBE/IHEC • Technical Assistance - DePaul's ILDS Technical Assistance Grant • Disability Advisory Committee

8. IBHE Data Warehouse Update

9. IBHE Data Warehouse • Entering in agreement with NCSA • Archive of ISEG 4 year university data • Building of ILDS Data Warehouse • Operation and support until June 30, 2013 • Portable and can be transferred to the administrating institution

10. Educators and policy makers need accurate, timely, and consistent information about students and schools in order to plan effective learning experiences, improve schools, and reduce costs. In addition, our student population is highly mobile – across districts and states, and between K-12 and postsecondary – thus the need to share high quality data requires that we develop a common vocabulary for a core subset of data elements that exist in multiple data systems. What was the catalyst for Common Education Data Standards?

11. A national collaborative effort to develop voluntary, common data standards for a key set of variables. CEDS elements focus on standard definitions, code sets, and technical specifications of a subset of key data elements. This will increase data interoperability, portability, and comparability across states, districts, and higher education organizations.Voluntary Common Vocabulary What are the standards?

12. CEDS is NOT: Required: Adoption of any or all of the CEDS standards is entirely voluntary. A data collection: CEDS does not collect data. A Federal unit record system: CEDS is a model for data standardization to enable sharing between state systems. Solely a USED undertaking: CEDS is a collaborative effort including SEAs, LEAs, state higher education organizations, institutions of higher education, and national organizations.

13. Version 1 • Released in September, 2010 • 161 elements – focused on K-12 • Student record exchange across districts/States • Student transcripts • High school feedback reports from postsecondary to K-12

14. Where to find CEDS: http://nces.ed.gov/programs/ceds/

15. What to Focus on for Version 2.0? • Overall, focus will be more on postsecondary for Version 2.0 • Postsecondary different from K12 • Most institutions are private (even though most enrollments are in publics) • Not all institutions in state systems • What binds them all together?

16. Why IPEDS? • Good for state systems • Applies to all Title IV institutions regardless of whether in a state data system, but state systems could still adopt them and assist with data-sharing across institutions in their system (as well as with IPEDS reporting) • IPEDS covers topics of most interest: enrollments, transfers, completions (i.e., student mobility) • Good for institutions • NCES can use CEDS to build new tools to assist with data reporting and help ease reporting burden • Institutions can share data, when appropriate, using a common language • Good for project plan • Provides an achievable scope of work for Version 2.0; IPEDS is ultimately a Use Case for CEDS but also keeps work directed and manageable • Good for aggregated data quality • NCES is always interested in improving data quality and comparability in its data collections • IPEDS training can provide more details to data providers and base it on CEDS, ultimately improving data quality

17. Example • What student-level data elements do you need in your data system to report the IPEDS graduation rate for Asian women? • Sex • Race • Hispanic or Latino Ethnicity • GRS indicator • GRS cohort year • Exclusions flag (e.g., death) • Academic award level • Academic award date

18. Additional Possible Use Cases: • How do these elements link to other existing aggregate reporting • Common Education Dataset (CDS) • Voluntary System of Accountability (VSA) • Community college feedback reports • How could these data possibly be used for information exchanges across institutions/state systems?

19. Next Steps/Timeline • July: First draft of elements, definitions and code sets released for public comment • August/September: Comments reviewed and revisions made • October: Second draft released for public comment • November/December: Comments reviewed and revisions made • January: Version 2 released

20. IHEC Data Models The Role of the National Student Clearinghouse and Other Entities

21. What Does the National Student Clearinghouse Do? The Clearinghouse provides status and deferment information, on your behalf, to guaranty agencies, lenders, servicers, and the Department of Education's NSLDS (National Student Loan Data System). The Clearinghouse process identifies borrowers who: • Withdraw from school and need to begin repayment • Transfer from one school to another • Return to school and may be eligible for a deferment • Continue in school and are eligible for deferment extension

22. A Little Recent History • Exploratory conversations at various venues • March 14th– AACRAO Annual Meeting • March 24th – Call with Clearinghouse contact • April 19th – Committee Meeting • June 16th – Conference call with Clearinghouse officers • Capabilities, interests, costs, experiences • Data management, value added, security • June 27th – Clearinghouse conference call debriefing

23. Who are the National Student Clearinghouse Clients? * Registrar, Financial aid, Enrollment Management, Admissions, Institutional Research

24. How Does the Clearinghouse Work? Institutions periodically send the Clearinghouse enrollment or completion data using secure FTP. • Free to institutions for core services (except for local programming) • Costs to aid providers for verifications. http://www.studentclearinghouse.org/colleges/colleges_fees.htm#core

25. What Does the Clearinghouse Track? Core Enroll Elements Core Completion Elements Additional Enroll Elements SSN LAST NAME FIRST NAME MIDDLE INITIAL SFX PREV SSN PREV LAST NAME B-DATE ANTICIPATED GRAD DATE ENROLMENT STATUS START DATE TERM BEG DATE TERM END DATE STREET ADDRESS CITY ST ZIPCODE COUNTRY SSN LAST NAME FIRST NAME MIDDLE INITIAL SFX Prev First Prev Last Birthdate Degree Title (eg Bachelor of Science) College Award Date Major and Minor 1, 2, 3 (Literal) Major and Minor 1, 2, 3 (CIP) Major Option 1, 2 Major Concentration 1, 2, 3 (Sequence) Academic Honors (eg Magna Cum Laude) Honors-Program Other- Honors Attended from, to FERPA Block Financial Block Class Level College Student ID (UID) Current Major and CIP Code Degree Seeking Flag First-Time/ Full-Time Student Gender Good Student Discount High School Code Institutional EMAIL address Middle Name Race/ Ethnicity State Student ID

26. ILDS Data vs. NSC Data Extra ILDS Extra NSC STREET ADDRESS Institutional EMAIL address PrevFirst Name Award College, Major and Minor 1, 2, 3 (Literal) Major and Minor 2, 3 (CIP) Major Option 1, 2 Major Concentration 1, 2, 3 (Sequence) Academic Honors (eg Magna Cum Laude) Honors-Program Other- Honors Attended from, to FERPA Block Financial Block Citizenship Country Citizenship Status Residency Status ACT Composite ACT Subscores Remedial Basic Credits Math Remedial Basic Credits Language Arts Online Indicator Total Cumulative Hours Earned At This Institution GECC-Completed Flag Pell Flag MAP Flag Institution Financial Aid Flag Other Financial Aid Flag Merit Based Financial Aid Flag Need Based Financial Aid Flag

27. Scenario 1 – IHEC Central Data Repository w/ institutions’ current submissions to NSC unchanged Workforce/Early Childhood Data Matches for out-of-state data Current NSC Submissions IHEC Data IBHE and Public Reporting Proprietary Public Independent ICCB/Comm. Coll.

28. Scenario 2 – NSC Central Data Repository on behalf of IHEC w/ institutions directly submitting all IHEC data to NSC Workforce/Early Childhood Data Matches for out-of-state data IHEC Data and Current NSC Submissions IBHE and Public Reporting Proprietary Public Independent ICCB/Comm. Coll.

29. Conclusion • The use of the Clearinghouse can vary from being a data source to the data warehouse. • The Clearinghouse will, however, be a partner in this effort. • The Governing Board will review the various alternatives.

30. Questions and Discussion…

31. ILDS Data Match - ISBE/IHEC

32. External System Matches • Assessment Vendors like ACT • Dept. of Human Services • Temporary Assistance for Needy Families (TANF) • Supplemental Nutrition Assistance Program (SNAP) • ICCB • For last year’s HSFB report • 59,352 records in target selected by age – 74% match • ISEG • Data matched using ACT data

33. Matching Methodology • Multiple passes from highest confidence to lowest • Each pass processed against reduced number • Pass 1 to 5 uses SIS ID • Pass 6 to 10 uses Home School • Pass 11 to 15 uses District code • Pass 16 to 22 uses other combinations • Number of passes established by agreement

34. Potential Matching Data Elements • ISBE Student ID (SIS ID) • Last Name • First Name • Birth Date • Gender • Home School (Graduating HS) from ACT • District • Partial First Name or Last Name • Soundex of name • First 4 characters of name

35. Exact Match Logic • Match on SIS ID plus • Any three or more of: • First Name • Last Name • Birth Date • Gender • Home School

36. How Do I Get the SIS ID • SIS ID is the key moving forward • ISAC contracted with Parchment to provide Docufide – transcript sending/receiving software • Will be distributed to all Illinois secondary and post secondary institutions free of charge • SIS ID will be sent with transcripts • For more accurate matching please collect SIS ID

37. Exact Match without SIS ID • Exact Match • Last Name and Home School • 2 of the following: • First Name • Partial First Name • Birth date • Gender

38. Close Match • Close Match • exact match on last name and • exact match on first name and • exact match on birth date or gender or district • or • Exact match on last name and • Partial (Soundex or 1st 4 characters) match on first name and • exact match on two of the following: • birth date • gender or • district

39. In the Ballpark Matches • Additional Close Match Options • “soundex” match on the last name and • “soundex” match on the first name and • exact match on birth date and • exact match on gender • OR • match first four characters of the last name and • match first four characters of the first name and • exact match on birth date and • exact match on gender • OR • Partial match on the last name and • Partial match on the first name and • exact match on birth date or gender • Used Primarily with Assessment data where LEA validates matches

40. Questions

41. DePaul University’s Technical Assistance Activities and Projects in Support of the Illinois Higher Education Consortium

42. Phase I: Technical Assistance Activity • Survey participants on status and issues • Form Technical Assistance Advisory Committee • Create Technical Assistance Teams • Support Participating Institutions: • to design and develop their data files • to prepare, edit and submit their data files • to maintain security and comply with laws • and agreements

43. Phase I: (cont.) • Compile a Reference Booklet for Participating Institutions’ Executives and Managers – possible content: (suggestions welcome) • Background and Description of the Consortium (IHEC) and the Illinois’ Longitudinal Data System (ILDS) • Considerations on Participation in the Illinois Higher Education Consortium (IHEC) • Process for Participating in IHEC and Potential Uses of the ILDS • Compliance with the FERPA and Other Federal and State Laws

44. Phase II: Technical Assistance Activity • Support Methodologies For Merging External Data Sets With Institutional Data In Support Of Planning And Decision Making • Support the Development of Desktop Analytical/Reporting Tools for Institutional Use • Support the Creation of Standardized Reports to Meet Institutional Needs

45. Suggestions and comments welcome Thank you Gerry McLaughlin (gmclaugh@depaul.edu ) Susan Doyle (sdoyle10@depaul.edu )

46. Including Disability Status in the P-20 Longitudinal Data System IBHE Disability Advisory Committee

47. Background • In 2003, IBHE noted that enrollment percentages reported by members were inconsistent with NCES data • Investigating this disparity, IBHE found: • Variable categorical schemes • Disparate methods of counting students with disabilities • Disparate disability records formatting • Variable disability records archiving procedures

48. Impact of Scant Metrics • Unable to track enrollment across institutions • Unable to report rates of enrollment, retention, graduation or time to degree for students with disabilities • Unable to objectively validate the effectiveness of access services and accommodation practices

49. Developments to Date • Critical stakeholder questions identified • Consensus disability categorization model created • Standardized disability reporting process enacted • Confidentiality concerns related to student-level data addressed • Disability data incorporated into the UGR • Developed and pilot-tested ISEG model

50. Consensus Disability Classification Model BACC CC Blind/Low Vision 100% 100% Deaf/Hard of Hearing 100% 100% Learning Disability 100% 100% Mobility or Physical 100% 100% Psychological Or Psychiatric 100% 100% Atten. Deficit Hyperactivity Dis. 100% 82% Brain Injury 100% 73% Systemic Or Health 88% 86% Other 50% 73%