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The HigherEdJobs Podcast is dedicated to helping higher education professionals find fulfillment in their careers and be the change agents that higher education needs in today's world. Join hosts Andrew Hibel and Kelly Cherwin, along with guest experts, as they examine job search strategies and break down the latest news and trends in higher education.
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[00:00:00] Andrew Hibel: Welcome to the HigherEdJobs Podcast. I'm Andy Hibel, the Chief Operating Officer and one of the co-founders of HigherEdJobs.
[00:00:09] Kelly Cherwin: And I'm Kelly Cherwin, the Director of Editorial Strategy. Today we are going to talk about faculty success, retention, and avoiding burnout in STEM departments. And we are lucky to have Aditya Dori, who is a Professor of Information Sciences and Technology in the School of Computing, College of Engineering and Computing at George Mason University. His research is in computing and engineering education and the use of technology for teaching and learning. He's a past recipient of an NSF Early Career Award and a Fulbright Distinguished Chair Award. Thank you, Adi, for joining us today.
[00:00:40] Aditya Johri: Thank you for having me. I'm really glad to be here and talking to you.
[00:00:44] Kelly Cherwin: Good. I look forward to the conversation. Let's kind of set the stage and talk about some general trends in the areas of STEM field right now.
[00:00:52] Aditya Johri: Great. I think I'm going to start with saying that STEM is a very broad field, and that acronym, Science, Technology, [00:01:00] Engineering, and Mathematics encompasses a lot of different subfields within it.
And as most of the folks in academia are kind of aware, STEM has become a very popular field overall, and within STEM as well, there are a lot of different subfields and disciplines such as computer science, a lot of engineering majors, data science, and quite a few science majors that have become very, very popular.
The big trend these days in terms of higher education is a growth in enrollment across all STEM fields. And with this growth in enrollment across STEM fields, there are quite a few challenges that a lot of higher educational institutions now face, and these have to do with. Teaching more classes, hiring faculty, training faculty, providing students with opportunities related to their major, especially workforce development related opportunities, and so on.
So, there's an opportunity overall to get more students, enroll more students, but [00:02:00] also then to ensure that there's quality in education, but also a work life balance for faculty who kind of teach these courses. And as I'm talking about STEM, I also want to kind of emphasize that. Science, technology, engineering, mathematics, as I said, encompasses a lot.
And within that, my expertise largely is with computing and engineering education and with technology related fields. And I feel like engineering, computing, technology is facing a little bit of unique challenges in the sense that engineering schools and within the computer science and information science majors have experienced some of the highest growths in the last decade in terms of number of students.
My institution and other institutions I'm aware of, the number of students who are pursuing, for instance, computer science has almost doubled in the last five years. So just my department right now at George Mason University, in our information technology degree, we have 2, 000 undergraduate students in just [00:03:00] one department. So significant growth overall.
[00:03:02] Andrew Hibel: And would you say that the faculty has doubled in the past five years, and how about the support staff to also go along with that?
[00:03:10] Aditya Johri: So the answer to both of those is no, and I think that's not just our institution. Across the board, the answer would be no, the faculty size has not doubled, and the staff size has not doubled, and There are quite a few reasons for that.
One is that the funding that comes from enrollment growth doesn't necessarily flow directly to the departments. So, there are different budget models and a lot of the funding for a lot of the institutions first goes to, you know, the administrative provost level, that level, then comes, trickles down to colleges, then comes down to departments.
There is always a lag in terms of recruiting faculty and enrollment growth. Second, recruiting faculty, especially in computer science, information sciences, and a lot of engineering fields is very, very difficult right now. [00:04:00] There are not that many folks on the market looking for those jobs and the other additional challenges.
Competing with the industry to hire faculty, especially if you have a Ph.D. in a highly marketable area like machine learning or A.I. or data mining or cyber security, you're very likely to look at industry jobs rather than faculty positions. So it's really kind of tough to hire faculty to do both research and teaching.
I mean, it's tough at both ends to get faculty. Of course, academic salaries don't often compare. I mean, that's often the norm. And especially if you are an institution that is in a area where the cost of living is high. For instance, we are in 1 of those areas near Washington, D.C. Then it becomes much harder to hire faculty.
And so I think it's a challenge, and it's the same challenge for staff, because a lot of the skills that you need for being a staff, especially if you're at the research side or even supporting [00:05:00] teaching, there are a lot of opportunities. So I would say hiring has kind of lagged in both aspects. It doesn't mean we have not hired.
We have hired. Most institutions that are hiring in computer science and information technology are hiring. There are jobs out there every year, but there is a lag in terms of faculty growth compared to student enrollment.
[00:05:20] Andrew Hibel: I'm presuming if we could see everybody listening to this podcast right now, everybody would be shaking their head in strong agreement with what you've just said, and all of those challenges.
Some are extremely unique to a fast growing program like yours, but some of them are unique to institutions that are fighting a cost of living issue, or as you stated that the issue that you're competing with industry for talent, which really kind of gets into the heart of this podcast, which is a how do you create faculty success, which then helps you to retain and helps you to avoid burnout?[00:06:00]
What would you say? You've worked hard, you've battled industry, you've battled the cost of living in DC, and then you've also gotten somebody who's actually interested in being a faculty member coming and working for you. I'm, I'm, I'm kind of talking early stage here. You're dealing with a blank slate.
How are you setting that faculty member up for success? i.e., retaining that faculty member?
[00:06:30] Aditya Johri: That's a great question. And once again, the small caveat here is I'm going to respond to it more from the perspective of a researcher in R1 institution at this point. I know the challenges are very different for teaching institution or smaller institutions.
So if you are in kind of an R1 large university, what we are trying to do is provide mentorship in different areas. So I think what we have recognized is that. In terms of success [00:07:00] of that faculty member, what's going to happen is if we think back from what will it take for instance, somebody on the tenure track to get tenured and the different dimensions that we kind of look at, we look at their research, we look at the teaching, and then we look at the service to the institution to the larger research and professional community.
And research for a lot of folks who are in engineering schools, especially computer sciences within the engineering school, has to do with getting external funding so you can support your graduate students and publishing in high quality venues, including journals and conferences, because a lot of our fields conferences have as high a value as journals because, you know, the faster turnaround, research fields move very fast.
Conference publications are needed. And so that's the research side of it on the teaching side of things, which is for me, the interesting part, because a lot of the faculty that we hire do not [00:08:00] necessarily come with a lot of teaching experience. This is true of most of academia, especially when you're hiring folks for the research expertise, they might have some courses, maybe taught a course, but did not really prepared for what happens in the classroom.
So there's a lot of mentoring around teaching, and for that, it has to do with different aspects like. What is the nature of students that we get? What are the goals of the students who are in your classes? Where do we want them to be? So the teaching, mentoring part, and the services, you know, getting a sense of what this institution is about and how do you contribute to the institution in terms of serving on different committees and so on and so forth.
From the mentoring perspective, these are the different things that we want to cover. And I think initially the way we do it here, and I think a lot of institutions do it, is that a lot of the mentoring is centered around research, especially getting external funding, because it often takes time. So, funding is not guaranteed.
You're [00:09:00] applying to NSF or NIH or, you know, the defense departments, different agencies, so you kind of need to know how to work, and you need to be able to kind of, you know, work with the genre of writing proposals and getting funding. So, A lot of the effort in terms of mentoring goes there, and then there's also teaching, but the different aspects to teaching, whether you're teaching graduate courses, undergrad, large classes, service classes, classes in your areas of expertise, and what a lot of institutions do, and we do there to help them is all the tenure track faculty have a reduced teaching load, so rather than teaching a normal 2 2 or a 2 1, depending on the institution, um, You're doing one one or something like that, right?
So you're trying to mentor that. Now, of course, there's a lot of effort that goes into all of this, and a lot of resources are needed. So a lot of engineering school, computer science school do have good startup packages, at least in our ones to [00:10:00] support, uh, the first Up to, I would say, 3 years because the 1st big review for us is in the 3 years of faculty.
So, you have the mentors, you have assigned mentors, you have mentorship that they get. They also get startup packages to help recruit students, get help in other ways that they need, travel money, attending conferences. So there are a lot of things that are built into this whole package in terms of mentoring, in terms of ensuring that new faculty get all the support that is needed, because you're thinking about the long term and in academia, in a lot of institutions, faculty do stay for a long time, so you want to ensure that they are supported well in their early years.
So, that's just like the kind of general framework for how we try to support new faculty, or most institutions try to support new faculty.
[00:10:52] Kelly Cherwin: That's fantastic. Thank you for explaining the mentoring program and you actually answered a couple questions as you were talking there I was trying to think of a new faculty [00:11:00] member coming in and You know kind of maybe having a little bit of a deer in headlights like how do I start?
But it sounds like your institution assigns them a mentor, which is amazing. Do you think this is pretty common for most institutions? Are they assigned or does a new faculty member kind of have to seek out because that can be a little bit overwhelming.
[00:11:14] Aditya Johri: It can be. So for my department, it's the new model, but I know from my experience at other institutions that formal mentoring where you assign the mentor has been common.
So, honestly, I mean, personally, I'm okay with assigning mentors, I think is useful, but I think new faculty need to learn also how to reach out and get mentors for yourself. I think in academia, it's a very, very important skill. So I like to see or think of mentorship as a scaffolding process. Yes, initially, you do need to give them formal mentors, help them in the departments, but also somebody outside who can guide them.
So, you know, you're not embroiled in the departmental politics or whatever, right? You [00:12:00] want someone from outside to also be able to help you. But I think one of the things that really kind of is important for your success in the long run in academia is the ability to find mentors on your own that kind of fit.
With what you want, and you might like, and especially true, I would say, for underrepresented minorities, diverse candidates, because your department, even your school, might not always have the kind of people you want as your role model in some ways, or as your mentors. So then you have to reach out, and I think it's important then to learn how to do that, how to reach out, how to meet people at conferences, at networking events.
When you go for review panels for NSF or something like that, basically being aware that that is something that you have to do, and that it's an essential part of developing as an academic. So, I think that's something you have to be very aware of. And I think. [00:13:00] Often, a lot of people are perceive of networking as this very.
Opportunistic kind of thing, and they don't look at it in a positive way as an asset, which I think is something that, you know, junior faculty, I've mentored and thinking about it the other way. It's like, we have to think about how you can actually do it. Well, because. It's good for you. It's also good for mentors and people do like to mentor.
It's not just because you've been assigned a job to mentor, but you know, you find commonalities. Those people in the long run might become your collaborators. You might get amazing ideas from talking to people who are new, who have been doing research right now. So, you know, there are a lot of benefits for both parties, I think, in the mentoring game.
[00:13:42] Andrew Hibel: We actually try to remind people regularly that mentoring is not a monogamous relationship. You can have more than one mentor. If you had a second mentor, you're not going to end up on a daytime talk show with your two mentors battling it out on stage. So, go out [00:14:00] there. Find those mentors. I love the use of the word collaborators.
I think mentoring is so prevalent, so important, but sometimes diminishes the importance of collaborators, people who you can work with in your profession, no matter what you do to share common experiences, share common ground and share common goals. And those people are wonderful. And yeah, in those collaborator relationships, there's usually a lot of mentoring going back and forth.
Oh, I never actually figured out how to do this. Did you? Yeah, I did. This is how you do it. And those collaborators are just, those are kind of your lifelong mentors, mentees, and the relationship is really fluid. I think what's interesting about what you said, and I suspect this is similar, With lots of institutions, that three year point for a new faculty member and kind of going more towards retention at that three year point does a new faculty member and as a good practice to kind of map [00:15:00] out, okay, this is what the path is.
We like you here. We want you to be here. This is what your future is going to look like. We like you here. There's some stuff we want to work on. And if we can work on that, which we think we can, this is where you're going to end up. Or, hey, listen, you really need to work on these things, and we really need to kind of revisit this and have a regular performance conversation about this, about where you're going.
How transparent and how direct Our folks at three years with what I wouldn't call like your career path, but like a little bit of a sketch of what the, the little bit of road in front of you might look like at our institution. Cause I think that would go a long way and letting people know where they stand and retaining them.
[00:15:45] Aditya Johri: No, absolutely. And I think given how hard it is to hire faculty in a lot of the fields right now, I think one of the things we do impress upon new hires, I personally do, is that if you've come through this process, you [00:16:00] have been hired, especially if you're on a tenure track, you know, we are hiring to tenure, right?
Most institutions, they want to support you to kind of reach that goal. And at the three year point, that is something that is Told to the candidates again, but there is also a very honest and direct feedback of what you need to do from that point onwards. Because if you're going up for tenure in your 6th year, that means, you know, your portfolio is kind of getting done in the end of fifth year and so on.
Right? So there is this thing about what we like to do here. And most institution is. Be a little direct about this is what you have accomplished. This is all looking great. These are the two or three things that you need to do and also trying to map out that if it looks like you've done a good job and you really are on the path to tenure in some ways.
Then, also thinking about towards the end of [00:17:00] this five, six year period, how are you going to position yourself for the next round? Because it is true that a lot of faculty, getting tenured becomes such a big event in some ways. And in some ways, a psychological event that there is a burnout at that point.
And I have seen that quite a bit with faculty where they think like once they've achieved best. It's like taking a break and what happens then is research is a game of momentum. You lose momentum. It takes you that much longer to get back to it. So you have to kind of impress both things that yes, you're working towards this big goal.
We want you to get there. These are the things you need to do, but also ensuring that they also are thinking long term beyond that point. You can be in a very hot fields, so to say, but you can see that in the next few years, the trajectory of that discipline or the subfield is going to change. So how are [00:18:00] you going to pivot?
So for me, it's always about getting to that point. And then also though thinking long term of your career. I think what I've seen is that thinking just about these small kind of steps and not thinking about your long term career progression is not a very productive way about going to an academic career.
Because the short term tendency then makes you go too much after short term grants or things that are not necessarily building towards the longer term academic career. And I think it's very important for those faculty who have joined academia to be in their long term to think about that path. So maybe I'm not so clear, but I hope you're getting my message.
I mean, it's like balancing both things.
[00:18:45] Kelly Cherwin: Yeah, and I loved how you say that research is a game of, you know, momentum, and thank you for that explanation. That was great. Looking for more conversations in higher ed? We invite you to join the higher ed military community as we discuss issues, best practices, news, and general trends affecting our institutions and the higher ed military [00:19:00] affiliated community.
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I actually want to switch over to one of your passions, which is using technology for teaching and learning. So, what innovative methods have you been doing or you can recommend to other faculty that could help in their success? And not only their success, but obviously the students as well. Is there anything you want to share?
[00:19:37] Aditya Johri: I do a lot of my teaching online using, you know, different learning management systems, using different technologies, and I really think that the use of technology comes down to how good a job you're doing in thinking about the learning outcomes of what you're teaching, and then kind of connecting it back to the How are you going to [00:20:00] assess that and let students know what they've learned, right?
So it's about using technology for the right things. You know, I teach this standard like large service course that for all of our students is about ethics of technology. That's part of our accreditation and also about, you know, what we want to teach students. We want to teach them about how technology influences society, what are some ethical implications, the morality of using technology, and I teach one of those courses.
And one of the ways I do that is through using case studies of different incidents, but a role play case studies. So I give a scenario to students. And I give them specific roles to play while discussing the scenario and coming to some kind of recommendation. For instance, one simple scenario is your university wants to use facial recognition all across campus because they think it will enhance safety.
So, if you have this facial recognition technology everywhere. What are the moral ethical implications? And students are [00:21:00] given different roles that you are, you know, the chief technology officer of the university. You are a cyber security person. You are somebody who's looking at diversity in the organizations and you have to balance all views.
Right? So students take on different roles. They discuss these things. And, you know, you can use it in class, but it works really well when you use it online and students do it using like Zoom or breakout groups. So there are these ways of balancing how you're using technology that is out there. And of course, there's a lot of use of technology for grading and assessment.
And there are more and more of these things coming out. So I really think the use of technology in teaching and learning obviously is going to increase over time. I think there is no doubt about that simply because that's the way our society is going. That's what students are used to more and more. And.
One of the biggest shifts that has brought about for students, at least in computing [00:22:00] or engineering, is the availability of so many different ways to learn different topics, whether it's through YouTube videos, it's through, you know, massive open online courses, Coursera, LinkedIn, and so on. So students are becoming used to building their own pathway towards learning something, and it's not just through the in class or course based learning at the institution, but by using all these resources that are available to them.
Of course, this is where faculty really need to guide them into how to do it well, because you go on YouTube, you're going to find a million things. It doesn't necessarily mean they're all good resources for learning what you want to learn. So, how do you help students kind of get a better sense of this is what I want to achieve, how do I achieve it, and how do I use all these resources that are available to me to kind of get there?
And I think that kind of the facilitation part that faculty now have [00:23:00] to do has. Increased a lot. And I think it's a very important part of what faculty do in terms of teaching and guiding student learning.
[00:23:08] Andrew Hibel: That kind of goes to kind of the pinnacle of this discussion, which is avoiding burnout. Once again, I mean, we've, we can kind of go through ending with that, trying to teach students how to best use the technology that's available to them, how to evaluate what's good technology and helping them learn.
And what's just kind of noise within the system add to it. There's twice as many students. Add to it, you have a very challenging time getting to this place called tenure after six years. Et cetera, et cetera, et cetera. But then you have the institution who has twice as many students with, with similar resources to what they had at five years ago, it's almost a recipe for burnout.
How is fact we can speak to STEM faculty. We can also speak to diverse STEM faculty and the challenges that might be unique to them, but then faculty in [00:24:00] general, what are some of the best methods that you would suggest to avoid burnout, both as a faculty member, but also somebody. Who's supervising faculty members as a chair and trying to retain them?
What can you be doing as a chair and what can you be doing as a faculty member? And maybe what are some of the unique challenges for diverse faculty?
[00:24:20] Aditya Johri: You know, this is a tough question because I really do see now that faculty burnout over the past few years, at least has increased a lot. And it's not just COVID.
At least for STEM faculty, especially engineering, computing, but even other fields, there is a lot of flux. And there's a lot of uncertainty, and it's very, very hard for a lot of us to operate in that context. And the flux and uncertainty has come from higher enrollment, getting more students in, having to teach more and more.
But also from the perspective of the faculty, it's in how rapid the advancement in different [00:25:00] fields are, and having to keep up with research where your topic, what you're looking at, and so on, is changing so fast. So, that's one of the things we haven't talked about is that if you're doing cutting end research in a field in computing or technology, that field is also changing so fast.
The number of conference and journal articles that come out in a day is what used to come out in a month, in a decade ago, I would say, right? So, there's this huge thing that you have to think about. What faculty can do, and I think in terms of if you really want to provide some scaffolding or training to faculty, which, when I talk to them about it.
You have to go back to the basics and the basics are learning how to manage your time better. You have to think seriously about time management. You have to like, I personally did like a time management course online, not because I'm bad at managing my time, but you know, there's something I think you have to keep reminding yourself about.
The time management at the fundamental level [00:26:00] is very, very important. Second, it's focus. There is a lot of noise, and it's not just noise, there's a lot of interesting things happening, but at the end of the day, you have to be able to focus back on what are the fundamentals in terms of doing research, what are the fundamentals in terms of teaching, and keep coming back to them, and keep reminding yourself that focus is very important.
It's hard to take things slow and do deep research in this context, and I kind of understand that, but you can still focus. And the other advice that I was given a long time ago is most of the things that faculty do, they take as much time as you give it. So you have to be very cognizant that in terms of especially your teaching and your service work, how much time is it that I want to give this thing?
It's okay to be good enough in certain things, because the other thing, faculty always face the. If you are a good researcher, you're just trained [00:27:00] to do things really, really, really well. And yes, that's important, but it's also important in a lot of contexts to do things, do them good enough, and move on. I think managing your time, focusing to what is important, trying to keep the noise out, which are all very, very hard things.
But I think there are aspects of that which are skill based. That you can work on, and I think that's one of the ways to kind of avoid having too much of a burnout. It is very hard. I'm not saying any of this is easy.
[00:27:34] Kelly Cherwin: That's why I think your example of like a 10 minute class, we can all be open to reminders.
[00:27:39] Andrew Hibel: It helps us all. So thank you for those. It's interesting to hear the unique challenges that you have in your role, but I think it's very similar to a lot of other institutions, whether they be small private liberal arts colleges or R1 institutions, whether they be Urban based like near D. C. or somewhere here in the Midwest within a giant [00:28:00] cornfield here pops up a university with that the big challenge that I think academia is having that's different than five or 10 years ago is making the case for why academia is a worthy career above all.
And if you were the person that academia is selected to go up there and every profession has to state its case, why would you say somebody who's looking at other options but could have an incredible academic career, why should they consider academia?
[00:28:34] Aditya Johri: The case I make to most folks that I know who I think would be good for academia and should consider academia has to do with all said and done, it's still one profession where you do really do get to decide what you want to do and how you want to do it. Not just on the daily basis, but in terms of pursuing your interest truly. And more and more I think a lot of my [00:29:00] students are realizing how hard it is to do in other professions. In spite of all the pressures that we feel, the burnout that we feel.
We really do get to pursue what we think is important, what we think is worthy, that kind of alliance with our interests, and I think that's really something worth it in life. And it's a long term thing. And one of my co mentors always used to say, the other great thing is, every seven to ten years, you can decide you want to do something other interesting and worthy, and you can still do it.
And you can do it like four or five times over your life. So I think for me, that's the case I like to make. And my students who have done good research, once they get the reward of doing good work, Appreciate that they realize it. I don't think everyone realizes it, but at least those who have done good work and seen the rewards reward in terms of all.
What it, how it makes you feel and what you feel about it, I mean, [00:30:00] then they want to pursue it. And I think that's the case I make.
[00:30:03] Kelly Cherwin: That was fantastic. I love that perspective. Thank you, Adi.
[00:30:06] Aditya Johri: Thank you. Great to be here.
[00:30:09] Andrew Hibel: And if you have any questions, please feel free to tweet us at HigherEdJobs, or feel free to email us at podcast@higheredjobs.com.
We'd love to hear your thoughts, your questions, your ideas, your reflections on this podcast. There was a lot out there for folks to think about. So, thank you very much. And we look forward to talking to you next time.