Evan Cortens (Mount Royal University) on Mastering Data for Effective Higher Education Strategies

On today’s episode of the Illumination by Modern Campus podcast, podcast host Shauna Cox was joined by Evan Cortens to discuss strategies for institutions to effectively ask the right questions and optimize their data for student success. 

Transcript

Welcome to Illumination by Modern Campus, the leading podcast focused on transformation and change in the higher education space. On today’s episode, we speak with Evan Cortens, who is Dean of Continuing Education and Extension at Mount Royal University. Evan and podcast host Shauna Cox discuss strategies for institutions to effectively ask the right questions and optimize their data for student success. 

Shauna Cox (00:02):Evan, welcome to the Illumination podcast. I'm so glad you could chat with me today.

Evan Cortens (00:06):Thanks so much for having me, Shana. Great to be here.

Shauna Cox (00:09):Absolutely. Well, we're here to talk about data and all things data, especially in the context of ce, accessing it, leveraging it. So let's start off the conversation by asking first, how do you believe asking better questions around data can positively impact decision making within higher ed?

Evan Cortens (00:31):Yeah, that's a great question. I think, and I think one of the reasons why I've chosen to work in higher education is that higher education has a vital role to play in our society. I think continuing education specifically has a really unique opportunity to meet learners where they are to meet acute labor market needs to try and help, for instance, new Canadians transition into the labor market in a way that traditional education, not to say that it can't, but maybe isn't as well suited to. So there's a unique opportunity there. But if we don't understand who our students are, if we don't understand what their needs are, if we don't understand our community and what our community's needs are, we're not going to be able to effectively do that. And really what we're talking about there are data questions. Who are our students? Where do they come from?

(01:28):What are they seeking from us? What are their goals in attending continuing education or higher education more generally? And then of course, are we actually meeting those goals? If somebody is saying, well, I'm taking this course in project management because I want to advance in my career, did they actually advance in their career? I think that we find, and I don't mean this to sound critical, that we can often be making what you might call hunch based decisions. Well, I know that that class is high quality or I've talked to folks out in community and they speak positively about our reputation and those things are important. But I think being able to combine that with the numbers, like 92% of students who said they were seeking a promotion at work got it. After they took this program at our continuing education unit. That's vital.

Shauna Cox (02:26):Absolutely. And I kind of want to dovetail off of the point you made in terms of those hunch ideas that were just kind of basing things off of and ask you, what are some of the challenges that higher ed leaders face when they're first trying to obtain that kind of data? And then once they have it, what are the challenges for asking the right questions?

Evan Cortens (02:47):Yeah, that's a great question. So I think in higher education, generally speaking, I think we often don't have an issue where a shortage of data, I have a background in institutional research, for instance, and I often used to say we have every grade for every student, for every course they've ever taken, sitting in a database going back 30 plus years. We have no shortage of data. Where we have a challenge is access to that data internally and then asking good questions. So to kind of highlight a few things, I think in higher ed generally, very often I find that the reason why you either collect data or report it a particular way is driven by sometimes external reporting requirements. So in Canada, statistics Canada or your provincial ministry in the US systems like IEDs or what have you, or by internal management or operational needs in Con-Ed, kind of by definition, so-called traditional content or whatever you want to call it, it is typically not ministry or government regulated or therefore reported.

(04:04):

And that means that we're often in a situation where we have to define these things for ourselves. So when you're thinking about within the context of an institution, if you have say a central data office or IT or what have you, their priorities are going to be defined by meeting those institutional accountabilities. And so you may struggle, for instance, with lack of support for your CE unit, and likewise, you may struggle with some of those definitions, but this can be an opportunity too. It means that you as a unit can take ownership over those things and then define and develop things that make sense to you. I sometimes think of this, I guess you might call this maybe sort of three levels of data maturity or something like that. So I start with the obvious one, which is access to data for obvious reasons. Our IT departments, our registrar's office, they have strong mandates around security of data, around integrity of data, and they often can be a little nervous about sharing access to that data even in an aggregate way.

(05:14):So you need to start there. If you don't have access to the data, you're not going to get anywhere. The next thing that follows on from that is what you might call definitional questions or data governance. Data governance is an extraordinarily hot topic in higher education. I was at the Canadian Institutional Research and Planning Association National Conference a year ago, it was last year, and I think every other session was on data governance. A lot more questions than answers, but if you say the word student and I say the word student and we don't mean the same thing, we're going to create far more confusion with our data than make any kind of answers. And the sort third level, I guess, of data maturity, I sort of think of it as visualization or reporting tools or what have you. I think sometimes the folks that are trying to sell you things like Tableau or Power BI will tell you, install our system and it will help you make data-driven decisions.

(06:14):Well, that's only true if you're at the end of this kind of three-step maturity process. You still have to build the reports, you still have to define things. And then to the final part of your question, once you've done that, so you've got access to the data, you know what you mean by a registration, you know what you mean by a student, and you've got a report that you can go into a system, the dean or director can run it, but also operationally, a program coordinator can use that report to help them do their job better. Now the point is asking good questions. I sometimes, sometimes joke that folks who aren't used to data informed decision-making think, well, if I just have the right spreadsheet, it will make the decision for me. That is rarely true. Rarely are you in a situation where it's obvious this program is successful and we should double its size, or this program is not succeeding and we need to start scaling back.

(07:16):So data is not going to make the decision for you. A colleague of mine, you'll note I used it there as well, has taken to avoiding the phrase data driven decisions and thinking of data informed decisions. And that I think is a kind of good guidepost. The final point I would add just on this is to be mindful sometimes in our field or around our institution, I can get a bit of a reputation as a numbers guy, but I remind folks that my background is actually in the humanities. My background of all things is in music history. And so I certainly understand, and I think it's important to remind yourself that not everything can necessarily be quantified. And even things that can be quantified often can't be quantified very well. So I mentioned before things like industry sentiment or reputational impact, or you can you turn those into numbers.

(08:17):Sure you can, but you're probably not going to be able to collect very good data on it or quantify it very well. So a lot of folks sometimes refer to a balanced scorecard approach. So you're looking at those hard financial figures, you're combining them with, well-defined accurate enrollment data. But then you're also using that in the context of understanding, well, what are those things that are important to my community? What is making an impact on local industry? What am I hearing from my program advisory committees and using those to make data informed decisions, but also in a way that is human.

Shauna Cox (08:57):Absolutely. And there was so many little golden nuggets in there in your response, and I kind of want to elaborate on a few points that you've made and talk about those opportunities that you mentioned, even despite the challenges that may be there and talk about what are some of the best practices to overcome these obstacles? Where do people start in trying to get the data and having the data, and what are some other best practices to help ask the right questions once they have that data?

Evan Cortens (09:29):Yeah, that'ss a great question. So as I mentioned before, I don't think it's the case that when you go out to a part of the university or even another organization or another higher educational institution and say, can I have this data? And they say no, I think generally speaking, folks are not trying to be obstacles. They're not trying to be difficult. There's just a kind of, I guess you might call it like a misalignment of purpose, maybe a lack of shared understanding. One of the things that I have found is the information that might be valuable to a higher ed leader is very often that same data or those same data points that are very valuable operationally take financial data. You might have an accounts receivable operation that is responsible for the integrity of student fees being collected, but then you also have a keen interest in tracking, well, how is my revenue doing in my continuing education unit?

(10:33):Same data, very different purpose. But if that person who is kind of focused on the operational integrity of the data doesn't also see how this translates into a kind of call it what you will, a management accountability or a financial mandate or what have you, you're going to have a challenge. But on the flip side of that, the sort of need for reliable management reporting can't override that need for solid operational data because now you're not charging students the correct fees. Now your system isn't even functioning in those operational ways. So I think I have found that by sitting down with your finance department, with your IT department, with your registrar's office, and just sharing with them what your perspective is, what your challenges are, what you are needing in order to do your job better. I've often found a receptive audience. I hope that's not just my institution.

(11:34):I hope that that is generally the case. The other thing I would add, I think in terms of a best practice is working with some of our larger organizations that represent our industry. So in Canada, the Canadian Association for University Continuing Education or ca in the states, which I believe is just the acronym now, but was formerly the University Professional Continuing Education Association. And these are organizations, again, I'm not trying to suggest that they perform a regulatory or accountability function. Absolutely not. So they're not equivalent to your state or federal education departments or ministries, but what they can provide is surveying, they do collecting consistent information, encouraging the development of some of those definitions. And they can also, and I found this myself directly, they can help you advocate within your institution if you are able to say, well, 80% of institutions say that they rely on this kind of data and we don't have it in our unit. That can be a valuable tool for you to be able to say to whatever internal partners you may have, well, we need to find a way to solve this problem. So those are some ways maybe that hopefully will help overcome some of those obstacles.

Shauna Cox (13:00):Absolutely. And I want to go back to a point that you're talking about when it comes to a possible misalignment of purpose when you're talking about data, especially when it comes to the broader institution and a CE division, depending on how you're positioned, sometimes they're still siloed off and maybe not as centralized as they should be. So how can higher leaders, maybe particularly in the CE division, ensure that the questions that they're asking and the data that they have is aligning to the institution's missions and its goals? And then maybe that can even help CE have a seat at the table if they don't have one already.

Evan Cortens (13:43):Yeah, that's a great point. I was thinking about this a little bit in the context of I think basically everybody who works in higher ed, at least in Canada reads Alex Usher every day. And he had an article last week where he was speaking about kind of history of continuing education units in Canada as kind of like, I forget exactly the phrase to use, but it was like an institution within an institution. And I think that has a lot of strength about it for sure. It means that we can be entrepreneurial, that we can be responsive, that we can be very directly engaged with our communities. But I think you definitely have to counterbalance that by saying, but you are still within an institution and that institution has particular goals and a particular mission. There is a famous saying from Peter Drucker, the management expert, that what gets measured gets managed.

(14:48):And I always bear in mind, right, if I'm starting to put together a report to run some data or say we're going to focus on this number, that you're going to start to create incentives for people to say, well, I'm going to focus on this potentially at the expense of that. And if those choices aren't, as you say, aren't aligned with the institutional goals, you're going to have a problem for sure. I often think of, our provost likes the phrase integrated planning, not unique to Mount Royal by any means. You see this elsewhere. But the way we've manifested that here is what you might call kind of cascading or nested plans. So a university plan nested within that, an academic plan, and then nested within that, a continuing education plan. And to me, this speaks to a kind of best practice when it comes to data, which is that I'm trying to kind of manage this tension between, I guess you might call it bottom up and top down.

(15:56):I need to be mindful of what data do I actually have or what data might I reasonably be able to collect, but also counterbalancing that with, well, what are my institution's goals? What are my unit's goals? So even if maybe I don't have that data, maybe I should, maybe that should be a priority. So I guess what I'm trying to say here is you should start with that goal or that focus area in mind and then seek to structure and collect data that will support that rather than the other way around. If you start the other way around, what you end up with is spreadsheets with 250 columns, which is great data, but isn't going to help you make any actual decisions.

Shauna Cox (16:43):Absolutely. It already sounds just terrifying to have 250 columns and nobody wants to be staring at that and analyzing that. And so I want to close this out here by more. So looking at the big picture and ask you what trends do you expect to see when it comes to data in higher ed and how people are going to start leveraging it?

Evan Cortens (17:06):Yeah, so as I think about the question of trends, I think there are few that come to mind. Certainly an obvious one on the tip of all of our tongues is artificial intelligence. It'd kind of be crazy to talk about data without mentioning ai. I think for me, and again, I don't want to oversell myself here. I've never built an AI system and my command of linear algebra is rudimentary at best. But even knowing that, I think it's important for us to be, I guess I would say realistic. So chat, GPT as an example, technology I think has shown us what's what's possible. There's a famous quote, I don't know who said it, something like any sufficiently advanced technology is indistinguishable from magic and chat. GPT can appear like magic. And not just magic, it can appear like intelligence, but it really isn't. What it is is a fairly straightforward mathematical model combined with an enormous amount of data, more data than has ever been brought to bear before and really, really fast computing technology.

(18:22):We saw, for instance yesterday the chip maker Nvidia recently became what the most valuable company in the world? And those chips are being used in systems like Chat GPT, and that hasn't previously been possible. But I think it's important to remember the system isn't thinking, it isn't actually intelligent. What it's doing is it's allowing you to process enormous quantities of data in a way that wasn't previously feasible. And that I think is a pretty exciting opportunity. The amount of data we have in a continuing education unit pales in comparison to the entire public internet. And if we can use some of those same systems that help us ask better questions of whole repositories of human knowledge also to bear for higher education data, I think that could be really productive. But we have to do it in a way that is honest, that is ethical and also bears in mind the limitations of such systems.

(19:26):A few more trends maybe. I think one is that one's pretty high minded. These others I think are maybe a little more down to earth. One is we've been seeing this for probably 10 or 15 years now, which is a move more and more from on-prem systems to cloud-based systems. I think there's a lot of opportunity there for sure. They can be more efficient, they can be more affordable, and they can provide more consistency if we're all using the same system in the same way. We can do things in a way where we benefit from each other's shared experience. But there's a trade-off there to be sure if you're not building your own in-house bespoke system specifically tailored to your business process, well that can be a bit of a risk. And we have seen that in our unit. For instance, we have a music conservatory and a continuing education unit, both of which used in-house built systems 30 years ago.

(20:28):We moved off those systems a long time ago. But the processes that existed around those systems sometimes don't always make those migrations quite as smoothly. So I think when you think about the use of data that then creates for you the potential challenge, but also the potential opportunity to say, well, again, I want to make sure when I say a student, I'm saying the same thing. And when in the past if you had that on-prem system with that in-house developer, well they just build you that custom report or they just change the process or you're using a cloud-based system that isn't possible. So you need to make sure that you're ahead of that. I think we know third trend here, continuing education in a way is becoming, it's not necessarily more competitive, but I think the way that this kind of education is provided is it's becoming a more interesting space, let's put it that way.

(21:30):I don't think there is any shortage of demand for education. We all listen to other podcasts or we watch videos on YouTube and you see ads for things like Skillshare. We see LinkedIn learning. There is huge demand for this, but I think it forces us, and I kind of started this way right off at the top as a continuing education unit, we need to understand our audience and our community better than ever before and data can help us do that. And finally, we've seen a lot of talk around micro-credentials, the micro-credential space, and a lot of interest from governments and industry there. And that might potentially push us towards, so where there is more funding available, which is a great thing, there's also a greater expectation of accountability. And one of the ways that accountability is going to be manifest is in the provision of data. So if we may find ourselves in situations where things that weren't previously reported to our governments may be required to be reported to our governments, and again, we don't want to be caught flatfooted there. We want to be ahead of that and ready should such an accountability arise.

Shauna Cox (22:45):Absolutely. Well, Evan, that's all the questions that we have for you. But before I let you go, we are going to have to get a restaurant recommendation from you. So you are based in Calgary, Alberta. Where do people need to go?

Evan Cortens (23:01):Yeah, absolutely. I think in Calgary, we're in the wild West. You certainly can't go wrong with steak, but if I had to pick just one restaurant, it would be pigeonhole on 17th Avenue, one of my favorites.

Shauna Cox (23:16):Amazing. I love that. Evan, thank you so much for joining me. I really appreciate it.

Evan Cortens (23:21):Thanks, Shauna. Thanks for having me.