“These strategies are generalizable to other academic programs,” stress the report’s authors (Steven Christensen, the Center’s accountant; Scott Howell, the Center’s director; and Jordan Christensen, research assistant and student at the Center), “and can help extend academic programs at a distance, including online courses.”
1.How can we best use main campus enrollments to predict which courses to offer at the extended campus?
Administrators sought to determine the number of course enrollments the Salt Lake Center might anticipate for a given course based on the number of enrollments in the same course on the main campus. The question assumes the classes offered at the Center are a sample of the true population of all classes offered on the main campus. According to the report, the sample mean percentage was derived by taking a weighted average of the percentage of enrollments in all classes offered at the Salt Lake Center over the past five years and then compared to the corresponding classes offered on the main campus (more on this methodology can be found in the report). “It was of interest…to observe the wide variances in these percentages across semesters/terms,” note the authors. “If a course (and all of its sections) on the main campus enrolled 1,000 students, then this variable would predict the BYU Salt Lake Center would enroll 33 students during fall semester; 29 enrollments during winter semester; 100 enrollments during spring term; and 75 enrollments during summer term.”
The researchers then validated the approach, and, with the exception of only one course, the current enrollments fit within the range.
The report explains that this variable is also being used to identify those courses on the main campus not currently offered at the BYU Salt Lake Center which most likely would enroll the most students if added to the course portfolio.
2.How can we best use the waitlist for courses offered on the main campus to inform course offerings at the extended campus?
The authors write that the initial idea was to use the waitlist as a way to measure demand for courses on the main campus and then predict which courses would meet the minimum enrollment requirement at the Center. The assumption was that a course with a large number of students on the waitlist would predict increased enrollments for the corresponding course if offered at the Center. However, the administrators found that there is no indication of a strong link between waitlist students and enrollments at the Center: the assumption that a large waitlist predicted a successful offering at the Salt Lake Center was not always correct.
The report speculates that it is likely other factors and variables influence this correlation; for example, “the majority of classes offered at the BYU Salt Lake Center are general education classes which target freshman and sophomore students and it is possible this student demographic is less likely to travel from the main campus to the Center.”
Although the predictive abilities of the waitlist are still uncertain, say the report’s authors, “it still serves well to illustrate enrollment trends across campus…[and] on an aggregated level it may expose trends that merit further consideration not only for the current semester but for the semester a year out.”
3.How can we apply the Amazon principle of “customers who bought this item also bought…” to predict which courses to offer in tandem?
The variable, says the report, is derived by analyzing which classes students usually take in tandem to other courses, and as part of a grouping of courses. This more sophisticated scheduling was just made possible as the Center began offering day courses, too. For example, using the Center’s recently licensed “big data” software reporting tool, it was revealed that if a student at BYU enrolls in MATH 110 they are most likely to also enroll in Rel A 121 or WRTG 150 as companion courses, and even more so in the fall semester than in the winter semester; suggesting that MATH 110, and either REL A 121 or WRTG 150, be offered in tandem to MATH 110.
(Next page: Strategies 4-6)
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