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Unveiling Formula Funding Opportunities Through Credit Hour Analysis

Dive into a study on maximizing state funding by analyzing course levels, student combinations and funding formulas. Learn about the IQ project, formula funding factors, and key data for investigation.

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Unveiling Formula Funding Opportunities Through Credit Hour Analysis

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  1. Where Are Your Heavyweights?Identifying Unrealized Formula Funding Opportunities Through Semester Credit Hour Analysis Presentation to TAIR By Kristi D. Fisher The University of Texas at Austin March 4, 2009

  2. Overview • What and why? • David Prior’s work at TAMU – where to look • Employing UT’s B.I. tools • What the cube shows us • Next steps

  3. What and Why We are: • Analyzing student level, course level and discipline combinations by our institution relative to formula matrix weighting factors Because: • More funding mechanisms are being shifted to formulas • Understanding cost study and funding formulas key to maximizing state funding • In tough financial times we need to squeeze out every last drop… not just analyze the big-ticket items

  4. Project Background • Project IQ Course Enrollments (CE) Cube Developed in 2005 Provided SCH by Discipline, etc. • David Prior’s (Texas A&M) Formula Funding Analysis • Created Tables to Hold “Rules” and “Weights” • Modified CE Cube to include Funding Area, Funding Level, Weighted SCH, and Formula Funding Amount • Prototyped for Executive Leadership in May 2008 • Presented completed cube in December 2008

  5. David Prior’s Analysis: Formula Funding Factors • Factor One: Combinations of course/student levels producing SCH • Factor Two: Weight assigned to the resulting SCH level for the funding area • Factor Three: Tenure/Tenure-track teaching supplement – percent of UG SCH (***going away)

  6. THECB Funding Level Rules

  7. THECB Weights Matrix (08-09)

  8. Prior’s Key Data to Investigate • Number and $ of upper division students taking lower division courses • Number and $ of graduate students taking undergraduate courses • Number and $ of PhD students taking masters courses • Funding area weight relative to SCH production trends • Funding area WSCH and $ “difference” trends from year to year • Number WSCH and $ unrealized due to credit hour caps • Number WSCH and $ unrealized due to repeatability limits • Percent undergraduate SCH production taught by Tenured/Tenure-Track faculty

  9. UT Rules Table

  10. UT Weights Table

  11. How Project IQ Works The products of IQ are “cubes” and reports.

  12. Business Intelligence Tools • Transactional Systems: ADABAS/Natural • ETL tools: IBM Data Stage; Treehouse tRelational / DPS • RDBMS: Oracle 9i/10g, SQL-Server • O/S: Sun Solaris RAC, IBM Z/OS, Windows 2003 • BI tools: Cognos Powerplay 7.4, Impromptu 7.4, Cognos 8.2/8.3 (new) • Named User Accounts: 1,250

  13. IQ Data Integrity Legacy Systems (original) • Four – way data validation: • Mainframe to Mainframe • Mainframe to Oracle • Oracle to Cubes • Cubes to Mainframe Legacy Systems (revised) COGNOS Course Cube Student Cube ORACLE (warehouse) Faculty Cube Enrollment Report

  14. Formula Funding Cube

  15. Measures • SCH • Weighted SCH • Enrollment (Seats Taken) • Number Unique Sections • Average End Class Grade • Formula Funding Amount

  16. Dimensions • Offering College / Department • Year / Semester • Funding Level • Funding Area • Funding Status • Course Level • Student Level • Student Major College / Department • Tenure Status • Primary Instructor Rank • Semester Group

  17. Can Answer Questions Like… • What is the recent trend in weighted SCH production by (major/offering) College? • What is the trend in formula funding amounts generated by College? • How has the overall SCH production varied by funding area and level since 2005?

  18. And… • How many SCH and $ are generated, by student level and course level? • What are the funding area WSCH and $ change trends from year to year • How many WSCH and $ were unrealized due to repeatability limits? • What percent of undergraduate SCH production was taught by Tenured/Tenure-Track faculty?

  19. Disclaimers • Limitations: • Fiscal Year vs. Base Period Year • 108 hour rule for seniors in masters courses • Doctoral students over the 99 hour limit • Some funding area mismatches w/ THECB area • Data will not match SCH provided by THECB • Completed cube is 95% validated; not yet moved to production; not yet used campus-wide

  20. DEMO

  21. What is the recent trend in weighted SCH by college?

  22. What is the trend in funding amount?

  23. How has SCH by funding area and level changed?

  24. How many SCH and $ are generated by student and course level?

  25. What are the funding area WSCH and $ change trends from year to year?

  26. How many WSCH and $ unrealized due to repeatability limits?

  27. What percent of undergraduate SCH production was taught by TT faculty?

  28. Initial Results 07-08 Pilot Data • $417k+ in lost funds due to excess hours • $468k+ in lost funds due to repeatability rules • Graduate students in undergraduate courses

  29. Questions? Kristi D. Fisher University of Texas at Austin Office of Information Management and Analysis kfisher@austin.utexas.edu (512)471-3833

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