1. Enrollment Projecting The Magic of Modeling and Deposits Rachel Morris Data & Reporting Coordinator Missouri University of Science and Technology rachelm@mst.edu

2. Overview Who are we Institutional Goals KPI’s (Key Performance Indicators) Benchmarks Enrollment Projections Assessment

3. 1.Establish timeline with upper-level managers; on-going communication 2.Determine critical benchmarks & track progress towards goals at specific points in time 3.Know where opportunities exist to adjust strategy 4.Build trend lines for key performance indicators 5.Refine models overtime Guidelines for forecasting enrollment

4. Know Your Profile

5. 1. We’re one of America’s top technological research universities. 2. Our students get great jobs at great salaries. 3. Our students graduate with the ability to address real-world problems. 4. We’re one of America’s “30 safest campuses.” 5. S&T is one of the top 10 “best value” national public universities. A Top Technological Research University

6. A university with…  At least 25% of students studying engineering  A majority of students studying mathematics, engineering, science, business and computing  A robust graduate program  Strong research culture  Exceptional liberal arts, humanities and social science degree programs that complement the technological strengths of the university What is a “Technological Research University?”

7. Missouri S&T Michigan Tech Colorado Mines SD Mines New Mexico Mining & Tech Illinois Tech Cal Tech Florida Tech Georgia Tech Clarkson New Jersey Tech Stevens Tech MIT WPI Rensselaer America’s Technological Research Universities U of A - Huntsville

8.  Applied Math  Biological Sciences & Pre-Med  Business  Chemistry  Computer Science  Economics  English  Geology & Geophysics  History & Philosophy  Information Science & Technology  Physics  Psychology  Materials Science*  Technical Communication  Engineering: 1.Aerospace 2.Architectural 3.Ceramic 4.Chemical 5.Civil 6.Computer 7.Electrical 8.Engineering Management 9.Environmental 10.Explosives* 11.Geological 12.Manufacturing* 13.Mechanical 14.Metallurgical 15.Mining 16.Nuclear 17.Petroleum 18.Systems* Degree Programs +60 Degree Programs 34 BS/BA MBA/MST 29 MS/ME 20 PhD Learn More degrees.mst.edu *Masters degree only

9. Missouri S&T: 90% engineering, science and computing majors 19 th in Nation for Largest Undergraduate Engineering Enrollment 17 th in Nation for Number of Engineering Degrees Granted to African-Americans 19 th in Nation for Number of BS Engineering Degrees Granted

10. TOTAL Enrollment7,206  Undergraduate students 5,504  Graduate students1,702  New freshman class 1,170  New transfer class 388 Miners’ Fall 2010 Stats Breaking National Trends

11. Fall 2010 43 8 4 3 2 4 3 29 41 19 5 56 128 36 29 4,901 54 8 125 7 4 20 459 28 20 34 20 18 1625 7 24 12 3 22 3 2 6 17 4 4 12 Total Enrollment  48 states & 51 nations  70% Missouri residents  10% minority students  9% international students DC 1 4 Students’ Home States 1 2 Unofficial data until after 4 th week census

12. Enrollment diversity

13. International Student Enrollment

14.  Average Age: 21.6 years old  Gender:  23% Female  77% Male  First Generation College Students:  2005-06: 37%  Residency:  Missouri Residents: 76%  Out-State Students: 22%  International: 2%  Ethnicity:  African-American: 4%  Asian-American: 3%  Caucasian: 83%  Hispanic: 2%  Native-American: 1%  Non-resident, International: 2%  Not Disclosed: 5%  From a Community <40,000: 45% approx.  Average Family Income: $82,000  Average Indebtedness at Graduation:  $23,500 USD approx.  High Financial Need (Pell qualifier): 24%  Freshmen with Credit Cards:  24%  6 arrive with over $1000 USD standing balance  Students with PCs:  94%  +70% laptops  7% Macs  Students with Cell Phones  97% Undergraduate demographics and psychographics

15. 35% increase in test senders with family incomes of $60,000+ SOURCE: ACT AIM, 2008

16. Demographics Can Impact Historical Models

17. 1050 to 1150 students with the following profile: Academic Preparedness: 27 average ACT score (upper 10% in nation) 90% having completed the full Missouri college-prep curriculum 50% from the upper 20% of high school class Geography: 70% in-state 25% out-of-state 5% international Gender: 30% female 70% male Ethnicity: 13% under-represented minority students Majors: 70% Engineering (all programs) 5% Liberal Arts (psychology, history, English, technical communication, philosophy) 8% Business, Information Technology and Economics 9% Natural Sciences and Mathematics (biology, chemistry, physics) 8% Computer Science Success Rate:90% first to second year retention rate 80% return for third year 65-70% graduate in six years An ideal Missouri S&T freshman class

18.  The Midwest and Northeast will experience a 4% to 10% decline in high school graduates between 2009 – 2014 (WICHE)  The profile of college-bound students is rapidly becoming more ethnically diverse and female dominant (NCES, WICHE, ACT, College Board)  The number of students interested in engineering, computer science, and natural science degrees has declined to record lows (ACT, CIRP)  More full-time college freshmen are choosing to start at two-year colleges (IPED, MODHE)  More students are enrolling in more than one college at a time (National Student Clearinghouse)  Future student market growth will include more students requiring financial aid and loans to complete a degree (WICHE) Challenge: changes in the college-bound student markets

19. The Trends are Diverse: Regions within Regions

20. College-going rates, 2006

21. Some Trends that have not Changed: The Golden Circle for Recruitment +70% enroll within 140 miles of home +80% enroll in home state

22. +1 -15 +4 -5 +21 -14 +13 +53 +27 -9 +27 -23 +1 +16 -8 -2 -3 +22 +14 -4 -2 -6 -3 +2 -7 +10 -6 +2 0 0 -12 -6 +1 +9 -3 -31 -6 -8 -14 -19 -17 -14 Source: Chronicle of Higher Education Almanac 2006-07 Projected change in high school graduates 2007-2017 > 20% +11% to +20% 0% to +10% Decreases +1 +10

23. WICHE, 2008 National vs. regional trends

24. % change in Missouri population by county 2000-2008 Source: USDA, Bureau of the Census Published by: University of Missouri Extension, April 2 2009 -14.4% - -0.1% 0% - 4.9% 5% - 9.9% 10% - 19.9% 20% - 39% Missouri Average = 5.6%

25. By 2012, Missouri will have 4,000 fewer HS graduates each year

26.  Establish timeline with upper-level managers; on- going communication  Determine critical benchmarks & track progress towards goals at specific points in time  Know where opportunities exist to adjust strategy  Build trend lines for key performance indicators  Refine models overtime Guidelines for forecasting enrollment

27. Basic Enrollment Funnel

28.  Goal setting tool based on previous performance and benchmarks  Tool for building enrollment budgets  Primary dashboard indicators for In-cycle assessments of recruitment progress and projecting enrollments  Tool to measure effectiveness of activities along the matriculation path  Ability to determine market share  Tool to better focusing communications and messaging How We Use the Funnel

29. How S&T Tracks Progress

31. Percent of ACT Tested College Freshmen Who Selected an Engineering Major

32. Missouri’s 2010 Student Funnel for All Engineering Fields  High School Seniors:74,681  High School Graduates:64,009  ACT Testers/College Bound: 48,290  Any Engineering Interest (all testers): 1,836  Any Engineering Interest, (+21 testers): 1,299 (21 = MO average score / 50%)  Engineering Interest, +24 comp. score: 969 (24 = UM minimum for auto admission)  Missouri S&T Freshmen Engineering Enrollees: 721 SOURCES: MODESE 2011, ACT EIS 2010, PeopleSoft

33. Domestic Overall Freshmen Enrollment Yield Funnel FS2005-FS2010 200520062007200820092010 Inquiries836184569629 11427 11514 11510 Applicants189819842305226025152693 Admits180918702154208823432479 Enrollees 865 9501040103111051155 % Admits Enrolled 48% 51% 48% 49% 47% 47% % Inquiries Enrolled 10% 11% 11% 9% 10% 10%

34. Domestic Freshmen from Missouri Enrollment Yield Funnel FS2005-FS2010 200520062007200820092010 Inquiries476450616247 6325 56586053 Applicants133913971641158317911912 Admits102013101511146116651762 Enrollees 703 767 822 835 899 931 % Admits Enrolled 69% 58.5% 54% 57% 54% 53% % Inquiries Enrolled 15% 15% 13% 13% 16% 15%

35. Domestic Freshmen Online Application Enrollment Yield Funnel FS2005-FS2010 200520062007200820092010 Applicants N/A 9951276140418232170 Admits N/A 9501213130417002017 Enrollees N/A 423 550 591 771918 % Admits Enrolled N/A 44.5% 45% 45% 45% 45%

36. Domestic Freshmen Paper Application Enrollment Yield Funnel FS2005-FS2010 200520062007200820092010 Applicants N/A 9881029 859 692 523 Admits N/A 919 941 787 643 462 Enrollees N/A 527 490 440 335 237 % Admits Enrolled N/A 57% 52% 56% 52% 51%

37. FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries FS2010 First Time College Freshmen Funnel

38. FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries FS2010 First Time College Freshmen Funnel

39. FS2010 First Time College Missouri Freshmen FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries

40. FS2010 First Time College St. Louis Area Freshmen FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries

41. FS2010 First Time College Kansas City Area Freshmen FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries

42. FS2010 First Time College Chicago Area Freshmen FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries

43. FS2010 First Time College Dallas Area Freshmen FS2010 FTC Enrolled FS2010 FTC Admit FS2010 FTC Applicants FS2010 FTC Inquiries

44. 13% (+375) increase in FAFSA submissions over AY09 25% (+641) increase in FAFAS submissions over AY07

45. Getting Started

46. Where to Begin? 1.Determine critical information needed and begin data collection Understand your student population and know your data 2. Verify data quality accurate, complete, shared definition & metrics 3. Identify key benchmarks points in time when data must be gathered and compared to build historical trends 4. Holistic approach to data management requires buy-in from “data managers” (create / manage data) 5. Build baseline year assess effectiveness and refine over time

47.  Factor analysis is a statistical method used to describe variability among observed variables in terms of a potentially lower number of unobserved variables called factors.  Factor analysis searches for joint variations in responses to unobserved latent variables.  The information gained about the interdependencies between observed variables can be used later to reduce the set of variables in a dataset. Factor Analysis Defined

48. 1.Gender 2.Geographic Origin 3.Degree Program 4.Application Type 5.Academic Profile/Scholarship  ACT Composite Score  HS GPA  HS Class Rank 6.Overall/Combination Fall 2010 99.1% accurate Adjusted Projection: 1,161 Opening Week: 1,171 4 th Week Census: 1,070 6 month projection for freshmen fall enrollment (1 of 7 best factors)

49.  Originated in psychometrics, and is used in behavioral sciences, social sciences, marketing, product management, operations research, and other applied sciences that deal with large quantities of data. Factor Analysis is Key

50. Enrollment Yields and Predictions by Gender and State Residency For First Time College (FTC) FS2007Admits as ofEnrolled%Enrolled FS05/FS06/FS 07Admits as ofEnrolled Ave%EnrolledFS2008Admits as ofFS08 Projected Yield 2/22/2007 2/21/2005 & 06 &07 FS05 & FS06 & FS072/21/2008(Admits X %Yield) FTC1965102852.30%FTC1760.7947.353.80%FTC19591053 M152782053.70%M1386.3749.754.10%M1491806 F43620847.70%F373.3197.753.00%F465245 U2 U10 U30 1028 1051 MO134179559.30%MO1213747.361.60%MO1343827 IL1928443.70%IL184.67540.60%IL22390 OOS43214934.50%OOS42412529.50%OOS393116 10281033 Enrollment Yields and Predictions By Schools FS2007Admits as ofEnrolled%Yield FS05/FS06/FS 07Admits as ofEnrolled Ave% YieldFS2008Admits as ofFS08 Projected Yield 2/21/2007 2/21/2005 & 06 &07 FS05 & FS06 & FS072/21/2008(Admits X %Yield) CAS32815848.20%CAS296.714649.2%CAS315155 SOE157483453.00%SOE141077154.7%SOE1593871 SMIS502856.00%SMIS44.724.755.2%SMIS3921 SOMEER13861.50%SOMEER9.35.761.2%SOMEER127 196510281054 Enrollment Yields and Predictions by Scholarships FS2007Admits as ofEnrolled%Yield FS05/FS06/FS 07Admits as ofEnrolled Ave% YieldFS2008Admits as ofFS08 Projected Yield 2/21/2007 2/21/2005 & 06 &07 FS05 & FS06 & FS072/21/2008(Admits X %Yield) No GO Scholarship63439562.30% No GO Scholarship545.7353.364.70% No GO Scholarship627405 100N/A 100N/A **58%1001710 11045821146.10%110388180.346.50%110401186 111161487.50%11118.315.383.60%11100 115N/A 115N/A **58%1157443 120542342.60%120613252.40%1205127 125N/A 125N/A **58%125116 13013861.50%13013.38.765.40%13064 15042120448.50%150392196.350.00%150422211 16036917346.90%160342161.347.20%160350165 19651028Ave:56.4%Ave: 58%1057 *Departmental Scholarships not included **Average % for 1st year scholar index Ave of 4 Projections for FS2008 Total:1049

51. Are Linear Models Accurate?  YES – if there are limited alterations in the variable factors (see the profile and demographics noted before).  Current S&T model has predicted the final fall freshman class enrollment within 2% since 2005.  Best to re-assess the factor analysis every 5 years.

52. Enrollment Projecting The Magic of Modeling and Deposits Rachel Morris Data & Reporting Coordinator Missouri University of Science and Technology rachelm@mst.edu