One way to manage the problem of inexperienced online professors is to increase the number of students being taught by the most successful teachers. Scale is currently a big part of online college, because that’s where all the profits are. It’s why for-profit colleges got into the online game early, and why public and private institutions are rapidly growing their offerings now.

But scale requires time and money upfront. The only way for one professor to reach hundreds or even thousands of students is to embed the learning process in technology. The simplest example is recording a lecture that students can view online. But effective online courses require much more. Many campuses now employ full-time “instructional designers” who help faculty map out courses and degree programs. They also create learning modules, online exercises, virtual laboratories and assessments.

The designers are good at their jobs and getting better. But it’s an expensive and labor-intensive process. The reason that many colleges are signing away up to 70 percent of future online tuition revenue to private for-profit companies is that those firms offer the financial capital and expertise needed to convert traditional courses online.

It’s impossible to transform a college course into the virtual world overnight. Which means the students currently boxing up their clothes and laptops also won’t benefit from the advantages of technology-enabled personalization. Fully online courses are usually, in whole or in part, “asynchronous,” meaning that students can learn when they need to.

A parent with a job can log on after putting the kids to bed at night, rather than hunt for a parking spot to make a 10 a.m. on-campus lecture. That’s a simple but powerful kind of personalization, particularly if people are caring for loved ones who are sick.

While the popular idea of individual “learning styles” has been largely discredited by academic research, people still bring vastly different levels of knowledge, talent and context to the classroom, virtual or otherwise. The long-sought-after dream of technology-enabled education is to build machines that can assess these differences, react to them, and give students a better educational experience — personalized to what they know and need.

There are decades of research in this field, and many promising theories and tools, but as of yet no breakthrough technologies in terms of cost and student learning.