eAIR caught up with Lee D. Lambert, J.D., Chancellor of Pima Community College, to talk about online learning, how COVID-19 has impacted of data use, automation and AI, and what enrollment may look like this fall.

eAIR: Could you tell us a little about your data background?

Because I have a law background where everything is driven by data and evidence, I’m always looking at how I can prove the assumption or argument I’m going to make. I have to have data, whether qualitative or quantitative, to support the argument. Also, throughout college, I took statistics, calculus, and a number of other related courses. Due to this foundation, I focus on a way of thinking through a logic model in which data and evidence become an important part of the equation.

eAIR: There’s one topic front and center on everyone’s mind right now as we face issues around COVID-19. How do you think the pandemic has impacted Pima's data use?

We were already using data to inform the fulfillment of our mission. I don’t think that changes in the crisis. Because we have been doing that work, we understand what the focus should be. Now that the pandemic has hit, it’s another layer of validation for what we’ve been doing. Granted, we didn’t do the work in preparation for a crisis; we did the work because we wanted to be better at fulfilling our mission.

For example, looking at the trends in higher education and disaggregating the data, you quickly realize that online learning is an opportunity for institutional growth. Because of that, Pima started to make a really concentrated effort in the area of online learning, which is now the fastest growing part of the college. That positioned us nicely going into this crisis because we had an infrastructure for remote learning already in place. Now, we can take that and apply it to other parts of the institution in an accelerated fashion. That was all pre-COVID work, so if institutions weren’t doing that, then I think they were probably caught off guard.

Obviously, the pandemic is having a major effect on organizations, there’s no doubt about it, but for us it’s an accelerant. I wouldn’t look at it as a negative disruptor.

eAIR: In the last few years there has been a growing focus on data analytics, automation, artificial intelligence, and the future of our work. What developments do you anticipate in those areas moving forward?

I think the pandemic reveals that these will be areas which will help each and every one of our organizations to not only survive, but to lay the groundwork to thrive moving forward. That includes teaching students and developing programs around these areas, as these are going to be relevant to our work. As an organization, you not only have to be modeling all of that, but you have to have programs that are educating and training folks for it as well. I don’t think many organizations are going to escape the need to incorporate data and artificial intelligence into their operations going forward.

eAIR: What do you think this fall is going to look like in terms of enrollment?

I think it’s going to vary. Before COVID-19, we had some institutions that functioned pretty well in an online modality with high levels of online enrollment, and I don’t see that changing for those institutions. In fact, those institutions might be beneficiaries of the current reality.

By contrast, colleges that had not made those investments and are trying to do so now are caught off guard, and they have to weigh the risks of returning to a face-to-face environment because they don’t really have the true online capabilities to make online courses a quality educational experience. I think we’re going to see the full spectrum between those two possibilities, and I believe the notion of a blended or hybrid model is going to prevail.

eAIR: Do you have any final comments that you’d like to share with the AIR community?

We should not be using data for data’s sake, but instead using them to solve problems and recognizing that sometimes there aren’t always data for a particular problem that needs to be solved. We just have to acknowledge that breakthrough innovations sometimes happen where data leave off, so our ability to fill in the gaps with human ingenuity and creativity should never be underestimated. At the same time, data should always inform that ingenuity and creativity. It’s about the balance between the two. We can’t lose sight of that.