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They "don't want to ask librarians or tutors in the study center or stuff like that," she says. "It's more the informal networks that they're using."

"Aside from a few institutions' references to improvements in retention or pass rates, most interviewees did not explicitly mention a desire for better learning outcomes as a main factor behind their decisions to increase their online offerings," write Bacow and Bowen. To the contrary, "the belief that students in online courses may learn the material better than their traditional-format counterparts did not appear to be widely held."

"There was a uniform assertion at all types of institutions that faculty feel much better about teaching repurposed courses or reusing course materials created elsewhere if they are able to do some customization." Providing a way for instructors to "brand courses as their own" is the most glaring barrier to machine-learning adoption at traditional universities, according to the report. Inconveniently, it might also be the most difficult to solve. "To date, no sustainable platform exists that allows interested faculty either to create a fully interactive, machine-guided learning environment or to customize a course that has been created by someone else (and thus claim it as their own)," Bacow and Bowen write. "This is perhaps the largest obstacle to widespread adoption of ILO-style courses."