College of Arts & Sciences: 21 departments and schools 13 interdisciplinary programs Fact Book: 7160 UG majors 1360 G students 340,000 UG SCH (60% of UTK total) 460 T/TT faculty members 190 non-TT faculty members My duties: Enrollment management, NTTF funding, curriculum, and a few other things

Chemistry: Studying matter and its transformations at the molecular level... Suri and Glorius, Org. Synth. (2014)

Efficiency in chemical synthesis: Minimize cost of starting materials? Minimize number of steps? Minimize time to completion? Suri and Glorius, Org. Synth. (2014)

Efficiency in chemical synthesis: Minimize cost of starting materials? Minimize number of steps? Minimize time to completion? Suri and Glorius, Org. Synth. (2014) Data!

Efficiency in chemical synthesis: Minimize cost of starting materials? Minimize number of steps? Minimize time to completion? As chemistry became a quantitative disci- pline, chemists began to understand that some efforts were unproductive... LeadGold Data!

Efficiency in chemical synthesis: Minimize cost of starting materials? Minimize number of steps? Minimize time to completion? As chemistry became a quantitative disci- pline, chemists began to understand that some efforts were unproductive... LeadGold Wait a minute! Is this CHEM 120 or the ALR? Data!

First-time freshmen Transfer students $$$ + + Well- educated college graduates prepared to be responsible global citizens

First-time freshmen Transfer students $$$ + + Well- educated college graduates prepared to be responsible global citizens External stakeholders’ view

First-time freshmen Transfer students $$$ + + Well- educated college graduates prepared to be responsible global citizens CHEM 120 MATH 141 HIST 261 CHEM 369 ENGL 118 MATH 113 HIST 242 ARTA 342 PHIL 120 MATH 117 HIST 373 FREN 223 MUCO 120 MATH 141 GEOG 131 SPAN 300 Associate dean’s view

First-time freshmen Transfer students $$$ + + Well- educated college graduates prepared to be responsible global citizens CHEM 120 MATH 141 HIST 261 CHEM 369 ENGL 118 MATH 113 HIST 242 ARTA 342 PHIL 120 MATH 117 HIST 373 FREN 223 MUCO 120 MATH 141 GEOG 131 SPAN 300 consumables classrooms lab rooms instructors GTAs times of day

First-time freshmen Transfer students $$$ + + Well- educated college graduates prepared to be responsible global citizens CHEM 120 MATH 141 HIST 261 CHEM 369 ENGL 118 MATH 113 HIST 242 ARTA 342 PHIL 120 MATH 117 HIST 373 FREN 223 MUCO 120 MATH 141 GEOG 131 SPAN 300 consumables classrooms instructors GTAs times of day How to measure efficiency? Implies a choice of quantitative metric(s)... Cost per student credit hour? Mean time to degree? First-year retention rate? Mean class size? Mean fill rate of classrooms? Number of repeated courses? How to measure efficiency? Implies a choice of quantitative metric(s)... Cost per student credit hour? Mean time to degree? First-year retention rate? Mean class size? Mean fill rate of classrooms? Number of repeated courses? lab rooms

First-time freshmen Transfer students $$$ + + CHEM 120 MATH 141 HIST 261 CHEM 369 ENGL 118 MATH 113 HIST 242 ARTA 342 PHIL 120 MATH 117 HIST 373 FREN 223 MUCO 120 MATH 141 GEOG 131 SPAN 300 consumables classrooms instructors GTAs times of day But also must measure effectiveness! Learning outcomes assessment Retention and graduation rates Undergraduate research & creative activity Early contact with TT faculty Study abroad, service learning, etc. Other measures? But also must measure effectiveness! Learning outcomes assessment Retention and graduation rates Undergraduate research & creative activity Early contact with TT faculty Study abroad, service learning, etc. Other measures? Well- educated college graduates prepared to be responsible global citizens lab rooms

Multiple claims on resources, and a diverse set of performance metrics: Data Priorities Policies

College of Arts & Sciences: 21 departments and schools 13 interdisciplinary programs Fact Book: 7160 UG majors 1360 G students 340,000 UG SCH (60% of UTK total) 460 T/TT faculty members 190 non-TT faculty members Large and decentralized. So as a chemist, I give in to my reductionist tendencies...

Courses taken by first-time first-year students: 30 courses in Arts & Sciences account for 2/3 of all Fall semester student credit hours attempted by first-time first-year students. ENGL 101 PSYC 110 CHEM 120 BIOL 101 MATH 119 MATH 141 BIOL

Courses taken by first-time first-year students: 30 courses in Arts & Sciences account for 2/3 of all Fall semester student credit hours attempted by first-time first-year students. ENGL 101 PSYC 110 CHEM 120 BIOL 101 MATH 119 MATH 141 BIOL How can we accommodate an increase in the size of the first-year class from 4270 to 4700? (a 10.1% increase)

The problem is still too big. Look at 100-level MATH courses taken by first-time first-year students. Fall 2013: 12 courses 3370 FT FY students (79% of FT FY class) 6340 enrollments (all students) Gateway courses for many majors More manageable...

Simplest possible approach: Assume the FT FY enrollments in each class will increase by 10.1%. Fall 2013, MATH 113 =336 FT FY students 320 other students Fall 2014, MATH 113 prediction: 374 FT FY students 320 other students 694 total

Simplest possible approach: Assume the FT FY enrollments in each class will increase by 10.1%. Fall 2013, MATH 113 =336 FT FY students 320 other students Fall 2014, MATH 113 prediction: 374 FT FY students 320 other students Fall 2014, MATH 113 actual: 377 FT FY students 346 other students 694 total 723 total

Hmmm... Try again? Fall 2013, MATH 115 =219 FT FY students 512 other students Fall 2014, MATH 115 prediction: 244 FT FY students 512 other students 756 total

Hmmm... Try again? Fall 2013, MATH 115 =219 FT FY students 512 other students Fall 2014, MATH 115 prediction: 244 FT FY students 512 other students Fall 2014, MATH 115 actual: 202 FT FY students 506 other students 756 total 708 total

At the course level, predictions range from 8% too low for some courses to 9% too high for other courses... But the approach predicts the total number of students enrolled in Fall level MATH courses to better than 1%! Why does this simple approach fail at the course level?

At the course level, predictions range from 8% too low for some courses to 9% too high for other courses... But the approach predicts the total number of students enrolled in Fall level MATH courses to better than 1%! Why does this simple approach fail at the course level? Hidden assumption: Course capacities in Fall 2013 were infinite, so enrollments were a perfect reflection of instructional demand.

Data sources used: 1) FT FY enrollments from Fall ) Size of Fall 2013 FT FY class 3) Projected size of Fall 2014 FT FY class Other relevant data sources might include: 1) Math ACT scores of FT FY students 2) Math AP scores of FT FY students 3) Waiting lists from Fall ) Majors selected by FT FY students

Would these additional data sources help? Waiting lists: A student seeking a Social Sciences General Education course might put herself on the waiting list for both POLS 101 and PSYC 110, intending to take the first course in which she can find a seat. If no seats open up in either class, the waiting lists will register “excess demand”.

Would these additional data sources help? Choice of major: Students’ major choices are rather fluid. For example, the Fall 2013 entering class had 158 declared psychology majors in May 197 declared psychology majors in August UTK typically grants 400 to 450 psychology B.A. degrees each year.

Take home message: Data-driven enrollment management is still in its infancy. We can take solace in this observation from the EAB pre-retreat reading (p. 3): “Many administrators held out hope for ‘a magic equation’ that would … serve as the basis for algorithms for setting optimal resource allocations … Unfortunately we did not discover such a magic equation.”

Thanks to: Pat Anthony Jason Smethers Nik Brodskiy

Thanks again for the projections you made for Fall It worked very well. I would like to adjust the Spring 2015 schedule. Could you please let me know the projections for Math enrollments for the spring semester?