I've posted a couple of times before about research on student preferences for online or in-person education (see here and here). The takeaway from the two research papers I referenced in those posts was that on average students had a preference for in-person classes, because they were willing to pay less for online options, but a substantial minority of students do prefer online classes. A new article by Lauren Steimle (Georgia Institute of Technology) and co-authors, published in the journal Socio-Economic Planning Sciences (ungated earlier version here), adds a bit more detail to our understanding of these varying student preferences.
Steimle et al. collected survey data in June and July 2020 from 398 Georgia Tech industrial engineering students across all levels of undergraduate study. Importantly, their survey included a discrete choice experiment (DCE), which allows them to evaluate the willingness-to-pay of students for different characteristics of a return to study in the Fall semester of 2020. The characteristics (referred to as attributes) that Steimle et al. investigated:
...were Mode of Course Delivery, Safety on Campus, Residence Hall Operating Capacity, Tuition Reduction, and Limits on Events and Social Gatherings. Each of these attributes was assigned 4 levels based on the latest recommendations from the Centers for Disease Control and Prevention’s interim guidance to institutions of higher education to prepare for COVID-19...
Included the tuition reduction attribute allows Steimle et al. to measure the intensity of students' preferences for the other attributes in terms of how much percentage equivalent tuition reduction they are worth (which they refer to as tuition percentage point equivalent, or TPPE). Before getting to analysing the DCE, Steimle et al. look at the factors associated with students preferring online rather than in-person courses generally, finding that:
i. Students with greater current concern level are more likely to choose online courses than students with lower concern levels,
ii. Students with higher perceived risk of infection are more likely to choose online courses than those with lower perceived risk of infection,
iii. Students with better current living suitability for online courses are more likely to choose online courses than students with worse current living suitability for online courses,
iv. Students who are more risk-seeking are more likely to choose in-person courses than students who are less risk-seeking, and
v. Younger students are more likely to choose in-person courses than older students.
For the DCE, Steimle et al. employ a latent class analysis, which means that the research participants are first sorted into groups (classes), where each class has different preferences than the other classes. In this case, the optimal solution has three classes (although, looking at their diagnostics, I'm a little confused as to why they didn't choose a four-class approach, because it does appear that four classes fits the data better). The three classes differ most in terms of how concerned the students are about the pandemic, labelling the three classes 'low-concern', 'moderate-concern', and 'high-concern', where:
...29% of students fell into Class 1, being not-so-concerned, while 17% fell into Class 3, being highly concerned. Most of the students were in the “moderate-concern” class (i.e., there was an average 54% probability of belonging to Class 2).
Looking at the types of students in each class, Steimle et al. note that:
...students in the “moderate-concern” class or “high-concern” class had slightly better current living suitability for online courses... and were more likely to live off campus in Fall 2020...
Asian/Pacific Islander students were more likely to be in Class 2 or Class 3, while White/Caucasian students were more likely to be in Class 1... Students in the “moderate-concern” class or “high-concern” class tended to politically lean Democrat and had a more liberal world view. “Low-concern” students were inclined to lean Republican and had a more conservative world view. We did not observe substantial differences in the share of those on financial aid among the three classes.
In terms of the DCE results (analysed separately for each class of students), Steimle et al. find that:
...students in more concerned segments (i.e., Class 2 and Class 3) placed more importance on modes incorporating at least some online courses. However, students in Class 1 did not like having online courses compared to completely in-person courses. Students in the “high-concern” segment (Class 3) put much more importance on entirely online courses when deciding to enroll compared to students in the “moderate-concern” segment (Class 2), indicated by the result that the TPPE of “All courses delivered entirely online” in Class 3 was more than twice as large as the corresponding TPPE in Class 2.
Not too surprising there. In general, the high-concern students tend to prefer online classes, while the low-concern students tend to prefer in-person classes. However, that doesn't provide too much help to universities trying to decide what mix of attributes would best ensure high enrolments. Fortunately, Steimle et al. outline some scenarios based on different combinations of attributes:
The first is a “business-as-usual” scenario in which courses are delivered entirely in-person, no requirement on mask-wearing and no testing, 100% operating capacity for residence halls, full tuition, and no limit on the size of social gatherings. Under a “business-as-usual” scenario, the low-concern class (Class 1) was predicted to enroll with 98.9% probability and the “moderate-concern” class (Class 2) was predicted to enroll with 94.8% probability. However, the “high-concern” class (Class 3) was predicted to enroll with only 17.0% probability. Weighting by the class membership probabilities, the weighted average enrollment probability is 82.8% for this “business-as-usual” scenario. In contrast, another tested scenario is a “completely online” scenario in which a 5% tuition reduction is given and has weighted average enrollment probability of 94.6% with the low-concern class enrolling with 85.4% probability, the moderate-concern class enrolling with 99.7% probability, and the high-concern class enrolling with 93.9% probability. A scenario with a higher enrollment probability is a “strict on-campus hybrid” scenario in which large courses are delivered online with small courses delivered in-person, required mask-wearing and extensive testing, residence halls are at 25% capacity (in which there are no roommates and no shared bathrooms), no tuition reduction, and a limit of 20 people at social gatherings. This “strict on-campus hybrid” scenario has a weighted average enrollment probability of 97.6% because it broadly appeals to students from the different classes: low-concern class is expected to enroll with 94.7% probability, the moderate-concern class has a near 100% probability of enrolling, and the high-concern class has a 95.1% probability of enrolling.
All of this seems to accord with the results in the earlier studies, but with a bit more detail in terms of analysis. However, it pays to bear in mind that this study was limited to industrial engineering students, who might have greater preferences for in-person education due to the need for in-person labs. On the other hand, students with greater concern for their health might have been more likely to respond to the survey (although the latent class analysis segregated them into their own analysis, the proportions of students of each type would be biased, and therefore so would the enrolment scenarios that Steimle et al. presented).
Finally, given that the survey was undertaken while there was still great uncertainty over the state of the pandemic and future risk, we probably can't extrapolate from it to understanding student preferences for online or in-person classes outside of pandemic times. For that, we would need to replicate the study at a time when in-person classes are less inherently risky for students.
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