college of arts & sciences: 21 departments and schools 13 interdisciplinary programs
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College of Arts & Sciences:
21 departments and schools13 interdisciplinary programs
2013-14 Fact Book:
7160 UG majors1360 G students
340,000 UG SCH (60% of UTK total)
460 T/TT faculty members190 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-timefreshmen
Transferstudents
$$$
+
+
Well-educated college
graduates prepared
to be responsible
global citizens
First-timefreshmen
Transferstudents
$$$
+
+
Well-educated college
graduates prepared
to be responsible
global citizens
External stakeholders’
view
First-timefreshmen
Transferstudents
$$$
+
+
Well-educated college
graduates prepared
to be responsible
global citizens
CHEM 120
MATH141
HIST261
CHEM369
ENGL118
MATH113
HIST242
ARTA342
PHIL120
MATH117
HIST373
FREN223
MUCO120
MATH141
GEOG131
SPAN300
Associate dean’s view
First-timefreshmen
Transferstudents
$$$
+
+
Well-educated college
graduates prepared
to be responsible
global citizens
CHEM 120
MATH141
HIST261
CHEM369
ENGL118
MATH113
HIST242
ARTA342
PHIL120
MATH117
HIST373
FREN223
MUCO120
MATH141
GEOG131
SPAN300
consumables
classrooms
lab rooms
instructors
GTAs
timesof day
First-timefreshmen
Transferstudents
$$$
+
+
Well-educated college
graduates prepared
to be responsible
global citizens
CHEM 120
MATH141
HIST261
CHEM369
ENGL118
MATH113
HIST242
ARTA342
PHIL120
MATH117
HIST373
FREN223
MUCO120
MATH141
GEOG131
SPAN300
consumables
classrooms
instructors
GTAs
timesof day
How to measure efficiency? Implies a choiceof quantitative metric(s). . .
Cost per student credit hour?
Mean time to degree?
First-year retention rate?
Mean class size?
Mean fill rate of classrooms?
Number of repeated courses?
lab rooms
First-timefreshmen
Transferstudents
$$$
+
+
CHEM 120
MATH141
HIST261
CHEM369
ENGL118
MATH113
HIST242
ARTA342
PHIL120
MATH117
HIST373
FREN223
MUCO120
MATH141
GEOG131
SPAN300
consumables
classrooms
instructors
GTAs
timesof 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?
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 schools13 interdisciplinary programs
2013-14 Fact Book:
7160 UG majors1360 G students
340,000 UG SCH (60% of UTK total)
460 T/TT faculty members190 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 130 . . .
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 130 . . .
How can we accommodatean increase in the size ofthe first-year class from4270 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 students320 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 students320 other students
Fall 2014, MATH 113 actual:
377 FT FY students346 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 students512 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 students512 other students
Fall 2014, MATH 115 actual:
202 FT FY students506 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 2014 100-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 2014 100-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 2013
2) 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 2013
4) 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
Nik Brodskiy
Thanks again for the projections you made for Fall 2014. 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?
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