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1 Reconstructing Institutional Research for 21 st Century Needs: A Case Study of Stony Brook University Braden J. Hosch, Ph.D. Asst. Vice President for.

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Presentation on theme: "1 Reconstructing Institutional Research for 21 st Century Needs: A Case Study of Stony Brook University Braden J. Hosch, Ph.D. Asst. Vice President for."— Presentation transcript:

1 1 Reconstructing Institutional Research for 21 st Century Needs: A Case Study of Stony Brook University Braden J. Hosch, Ph.D. Asst. Vice President for Institutional Research, Planning & Effectiveness Stony Brook University International Conference on Higher Education and Innovation February 5, 2015

2 2 The importance of context University Profile Context History Mission and Goals Office Profile Measurement Data Management IR Fundamentals Internal External Tools and Methods OVERVIEW

3 3 STONY BROOK UNIVERSITY PROFILE

4 4 Source: Office of Institutional Research, Planning & Effectiveness STONY BROOK UNIVERSITY

5 5 UNIVERSITY PROFILE Part of State University of New York System Co-Manager of Brookhaven National Lab SUNY Korea (Songdo) Highly Ranked – U.S. News & World Report: #88 National, #131 Global

6 6 (225 Degree & Certificate Programs) ORGANIZATION West Campus Colleges/Schools Arts & Sciences Business Engineering & Applied Sciences Journalism Marine & Atmospheric Sciences Professional Development Schools in Health Sciences Ctr Dental Medicine Health Tech & Mgt Medicine Nursing Social Welfare

7 7 Source: Office of Institutional Research, Planning & Effectiveness STUDENT AND DEGREE PROFILE

8 8 Source: Office of Institutional Research, Planning & Effectiveness OTHER HIGHLIGHTS

9 9 OFFICE OF INSTITUTIONAL RESEARCH, PLANNING & EFFECTIVENESS

10 10 * FTE = Full-Time Equivalent Office of Institutional Research 5 FTE* Employees – Director, Assoc. Director, 3 Analysts Primary tools: SPSS, SAS Data storage: SPSS files Primary functions: Compliance reporting Ranking surveys Presidential support HISTORY OF IR TO 2010 “We deal with numbers without the dollar sign”

11 11 TRANSFORMATION 2010 Budget cuts Staff departures Interim leadership / Receivership 2013 Reorganization Office of Institutional Research, Planning & Effectiveness 2014 New mission Staff restoration Data Governance Expanded Scope

12 12 *FY 2016: 5 FTE, plus 1 requested INSTITUTIONAL RESEARCH FULL-TIME STAFF

13 13 ORGANIZATION CHART: INSTITUTIONAL RESEARCH, PLANNING & EFFECTIVENESS

14 14 MISSION AND VISION Mission To collect, analyze, organize and communicate data and information to provide a valid, consistent, and accurate understanding of how the institution is advancing its mission in support of its vision to become a top-ranked public research university. Vision To establish a world-class institutional research operation and institutional effectiveness system in support of the University’s mission.

15 15 GOALS 6. Strategic Planning Support5. Institutional Effectiveness4. Research3. Decision Support & Internal Data Requests2. External Reporting & Accountability1. Data Management

16 16 INSTITUTIONAL RESEARCH FUNDAMENTALS

17 17 VALUES FOR PROJECTS AccurateResponsiveTimelyReproducibleContextualized

18 18 MEASUREMENT CONCEPTS DefinitionTime period Measurement Point Documentation

19 19 DATA MANAGEMENT

20 20 PRINCIPAL DATA TYPES Administrative Enterprise Data (PeopleSoft) Survey Data (NSSE, student opinion, alumni) Environmental Data (IPEDS, rankings, data exchanges Administrative Ancillary Data (Blackboard, Social Media)

21 21 EXTERNAL REPORTING/ACCOUNTABILITY FederalStateSystemRankings Summary Stats Enrollment Completions Financial Aid Graduation Rates Human Resources Summary Stats Enrollment Completions Financial Aid Unit Records Enrollment Courses Completions Financial Aid Summary Stats Applied Learning Non-Credit Student Surveys Summary Stats Common Data Set Research Various

22 22 INTERNAL TOOLS AND METHODS

23 23 Data Warehouse Internal Reporting & Analytics Web site Internal & External Communication Static & Dynamic Pages Dashboards Compact Communication / Monitoring INTERNAL TOOLS

24 24 SOFTWARE Basic Tools MS Excel MS Office Google Drive Adobe Acrobat Statistical SPSS (base) AMOS Decision Trees Missing Data SAS Specialized Tableau Visual Analysis QGIS Circos, Google Charts

25 25 Managed by Unit in Information Technology Campus Support with Emphasis on Finance Daily Updates from PeopleSoft Internal Decision Support Current Limitations Not aligned with external data standards Important data does not freeze Data governance DATA WAREHOUSE PeopleSoft (ERP) Static Reporting Data Warehouse Business Intelligence / Dynamic Reporting

26 26 Source: Pyramid Analytics PYRAMID ANALYTICS

27 27 Cross-functional task force in 2015 to recommend institutional policies and structures STRENGTHENING DATA INFRASTRUCTURE Communication Data Quality Data Governance

28 28 WEB SITE Areas for: About Data Reports Dashboards Resources

29 29 STATIC WEB PAGESWEB PAGES

30 30 INTERACTIVE WEB PAGESWEB PAGES

31 31 INTERACTIVE VISUALIZATIONSVISUALIZATIONS Major Migration, Freshmen Entering in Fall 2010 Degree Outcomes by Initial Major Freshmen Entering in Fall 2007

32 32 Source: Stony Brook Executive Dashboard EXECUTIVE DASHBOARD

33 33 Source: Stony Brook Executive Dashboard

34 34 Research reports and briefs support institutional needs and priorities RESEARCH Analysis of general education course success to forecast policy impact Stony Brook Univ. as 1 st, 2 nd 3 rd choice of admitted students, year graduation rates by initial major and limitations

35 35 EXTERNAL TOOLS AND METHODS

36 36 STUDENT SUCCESS COLLABORATIVE Source: Educational Advisory Board Proprietary Tool

37 37 Source: Educational Advisory Board Proprietary Tool STUDENT-LEVEL ANALYTICS Student Success Collaborative Screenshot

38 38 -Private social network for admitted students within Facebook, hosted by Uversity -Students build their own communities around shared interests -Native mobile apps and multichannel announcements SOCIAL MEDIA ANALYSIS

39 39 App provides rank and probability to enroll Categorizes students for outreach ENROLLMENT PROBABILITIES

40 40 Source: Academic Analytics ACADEMIC ANALYTICS Dept. of Computer Science

41 41 Extensive use of transactional data means results are not replicable Third party algorithms prevent easy validation; some models do not follow generally accepted data mining practices (training, validation, test) Difficulty of data cleaning in external databases LIMITATIONS

42 42 EVOLVING ROLE OF IR IN BIG/NEW DATA Identify data that matter Translate into actionable information Sort/translate Ground analyses in integrity & ethics Assure quality Validate Attach new data to traditional data Extend archiving protocols Collect Develop skill sets Apply new methods Learn

43 43 BUILDING A STRONG IR FUNCTION Build a firm foundation Definitions Data Governance Data Management Master the regular communication of quality descriptive statistics Develop capacity for inferential statistics, forecasting, modeling, and data mining

44 44 Contact Information: Dr. Braden J. Hosch Stony Brook University +1 (631) QUESTIONS?

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