Higher Education in the Digital Age: A Conversation with Michael Lovenheim

Since its inception, online education has faced heavy skepticism, if not downright opposition. A recent study by David Deming, Michael Lovenheim, and Richard Patterson finds that students benefit from the education quality improvements that traditional brick-and-mortar institutions make in response to the disruptive threat posed by their online competitors. Michael Lovenheim, one of the coauthors of this study, speaks to the challenges and future of online degree programs and higher education. Read more about his group’s research here.

What motivated you to study online degree programs and their effect on the higher education market?

There has been a massive increase in the provision of higher education online. People talk about it as a potentially disruptive force, and there are a lot of theoretic reasons to believe that is a valid argument. Most students go to college close to their homes, which gives local colleges a lot of market power. However, the expansion of online learning offers an opportunity to inject more competition into higher education and impacts the quality of services offered by brick-and-mortar schools. Another motivation is that a lot has been written about concerns regarding how good these online schools are. It is important to understand the entire set of effects these online programs have.

Given rising college tuition costs and college premiums on income, how do students benefit from a more competitive market?

Market competitiveness leads to higher-quality education services for a given price. Without competition, there are very low incentives for colleges to (1) allocate resources in an efficient manner and (2) provide services that people actually want or need in different economies. I think these are the two main mechanisms where competition in postsecondary education markets could benefit students. What we see is that, due to online competition, there is a shift towards instructional spending. This is consistent with the idea that competition is inducing schools to spend more on teaching, which should theoretically help students.

There is a lot of literature on how increasing spending does not improve education outcomes in K-12. Is this also the case in higher education?

What is interesting is that most of the evidence we have suggests that more spending does increase student outcomes in higher education, but it is much less clear in K-12. A good amount of work has been done, using different sources of variation, identification strategies and data. They all point to resources and spending being important drivers of higher education productivity.

What is the distinction between higher education and K-12 that makes higher education more responsive to spending?

First, there is no compulsory higher education, so the sets of students are different. The second difference is that there is more competition in higher education, even in places where there is little of it. Students can choose to attend college anywhere they want without staying at home. There is also direct tuition in higher education that makes people more attuned to what the schools are doing. In K-12, the funding mechanism is usually driven by a combination of federal and state allocations plus local property tax dollars. Yet, families of the students enrolled in public schools and charter schools, which account for 90 percent of the enrollment in the United States, are not charged directly like in higher education. All these forces put more competitive pressure on the higher education sector, but these are only potential explanations. There is still very little actual information and data on why the two sectors may respond differently to changes in monetary resources.

What are the regulatory challenges of online degree programs?

One of the challenges is making sure students have sufficient information about the quality of these programs. These programs take a lot of public money in terms of financial aid. That is fine if they are productive in generating long-run human capital outcomes for students. If students have full knowledge of the quality of online versus alternative education to make informed decisions, the online institutions will go out of business if they are not providing high-quality degrees. The problem comes when online programs are being heavily subsidized by the federal government, as all programs are in higher education, but they are providing a lower-quality product. The real issue is understanding the quality of online degree programs compared to non-online and other public alternatives, and improving the education services online schools offer.

There is a growing market of online certificate programs offered by startups focusing on programming skills. These courses capture the trend in the tech industry to emphasize skill mastery instead of degree completion. What kind of industry-specific effects could online education potentially have in the labor market?

Current online degree programs and the private for-profit sector are still more focused on technical and vocational training. Interaction between these programs and specific industries is super interesting and very under-explored, and technology is exactly the right place to go. Research at this stage is constantly trying to understand what industries and occupations are being affected, what actual types of workers these schools are providing, and how responsive these schools are to the demands of the labor market. One of the arguments for these types of schools is that they tend to be more demand-driven and offer the skills the labor market needs. The extent to which that this is actually occurring is not well understood yet. I have some projects underway that may shed some light on this. There is a general acknowledgement that this is where the literature needs to go, but it has not gone there yet.

Do you think data is the biggest challenge researchers face?

Yes, I think so. There is no dataset that is from a period when we had a lot of online schools, and for-profit and online enrollment is still too small to be able to say enough about the issues we want to understand. Hopefully, as existing large panel datasets follow people over long periods of time collect more data, they will help resolve some of these issues.

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