We’re thrilled to reach another milestone: 350 episodes of the Leading Learning Podcast. We are grateful to our listeners for making this possible.
Milestones are opportunities to reflect, both on what’s past and what’s to come. In this episode, we focus on three areas we expect to be of continuing and growing importance in the learning landscape and for learning businesses: AI, the X factor, and the work/learn connection.
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Celisa Steele: [00:00:27] Welcome to episode 350 of the Leading Learning Podcast. Yes, that’s right—350 episodes, and we’re going to claim having 350 episodes out in the world as a milestone.
Jeff Cobb: [00:00:40] I certainly think it’s a milestone. I think I’m prepared to have a Twitter duel with anybody who tries to tell me it’s not. That is a lot of podcast episodes that we’ve put out there, hopefully to the benefit of humanity or, at least, the learning business world. Milestones are always opportunities to reflect. We’re, of course, big fans of reflection, and that can be reflection on what’s past and what’s to come. But we want to focus this milestone episode—yes, it is a milestone—on three areas we’re thinking about, based on what we’re seeing happening with learning and what we’re hearing from learning businesses.
Celisa Steele: [00:01:18] Yes, milestones are great times for reflection. We are big fans of reflection. But I think milestones are also great times for gratitude. So we want to be sure to thank you, dear listeners, for your very important part in getting us to this milestone. Without you, listeners, we would have not made it to 350. Thank you for listening. Thank you for sharing episodes with colleagues. Thank you for making time to discuss with your team and to delve into the ideas and topics that we touch on in episodes.
Jeff Cobb: [00:01:51] And we also want to thank all the interviewees who’ve carved out time to talk with Celisa or me and share their expertise, opinions, and stories. I’m not 100-percent certain how many of our episodes have been interviews, but we typically run a couple of interviews and then have a Jeff-and-Celisa episode, so we’ve certainly done at least 200 interviews and probably more like 250.
Celisa Steele: [00:02:16] We also want to be sure to thank the sponsors that we’ve had over the years, who have helped to offset the costs of the considerable effort that goes into doing the podcast week in and week out.
Jeff Cobb: [00:02:29] Yes, and, if you’re looking for a way to help Leading Learning out, we do hope you’ll sign up for our free newsletter, visit the show notes for episodes, follow us on social media (Twitter, Facebook, and LinkedIn), and just generally spread the word so that others can benefit from what we’re doing here on the Leading Learning Podcast.
Celisa Steele: [00:02:47] So with some thanks given, let’s now turn to those three areas that you mentioned, Jeff. And, for each of the three areas, we’ll offer a couple of points for consideration, things that might prompt some reflection or action in your learning business.
Artificial Intelligence (AI)
Jeff Cobb: [00:03:02] First up on our list is what’s really the elephant in the room these days, maybe the robotic elephant in the room, and that, of course, is artificial intelligence.
Celisa Steele: [00:03:15] That’s right. There’s been an incredible buzz about AI since the release of ChatGPT in November 2022. In fact, we’ve dedicated a couple of recent podcast episodes to AI already, but AI still has our attention, and, in fact, we think it deserves attention because of the kinds of disruption that it’s causing or that it will cause.
Jeff Cobb: [00:03:38] And it’s going to cause more because GPT-4 is now out. Going forward, ChatGPT will be based on that. It’s just going to continue getting better, even though there are still pitfalls with it, and we cover some of those in our episode on it. But, right now, we want to highlight two broad areas where AI seems most likely to impact learning businesses.
Celisa Steele: [00:04:04] And the first area we have in mind is core work. What is it that you do day in and day out, and how will AI impact that? And, in particular, how might it help you do what you’re already doing faster and more efficiently? One way to think about this is to use the domains of the Learning Business Maturity Model as a way to categorize your core work. And, as a reminder, the Learning Business Maturity Model, which we’ve talked about on the podcast before, contains five domains: strategy, leadership, marketing, portfolio, and capacity. You can use those five areas as buckets to categorize the types of work that you’re already doing. And that can be all over the map, from decision-making to content production to evaluation and analysis. And what you want to do is make this documentation of what you’re already doing and then begin to think about how might AI be leveraged to help you do what you’re already doing faster and more efficiently?
Jeff Cobb: [00:05:20] It’s a great time to start doing that sort of inventory, to start experimenting. This is a great topic, if you’ve got a team that you’re working with, to sit down and have a session or a few sessions about this with your team. Whether you use the maturity model or you have other ways that you lay out your day-to-day operations, how can you layer AI on top of that to get that greater efficiency, to get that greater speed, and. frankly, just to get better at the things you’re doing? How is AI going to help you get better? You don’t have to have some fabulous, new innovation that you’re going after with AI—that may come eventually as you get used to using the tools, But, right now, just look at that core work and how does AI apply to that core work.
Celisa Steele: [00:06:02] And we do encourage you to actually do some experimentation. Do this inventory work, think about how AI could be applied, and then try it out. It’s not always going to be necessarily a win. You may find out that whatever AI tool you tried out at first isn’t actually all that helpful, but, in fact, your time and effort went up some. And then you’ll just have to assess. Is it because you are learning the new tools, and you can expect, actually, for that process to get much faster and better over time? Or is it just that it wasn’t a good fit? We don’t necessarily think that AI tools are going to be a panacea and fix everything, but you do need to be trying it out and do need to be thinking about where it could make sense in your learning business.
Jeff Cobb: [00:06:45] And, along with that, if you have not yet tried ChatGPT or the tools that it’s built on like Jasper AI or just some of the other common tools that are out there, now is the time. You have to roll up your sleeves and actually see what these programs can do so that you have an understanding of that. I think if we were able to, we’d ask our listeners to raise their hands and say whether they actually have tried ChatGPT at this point or not. In fact, you can just do that wherever you are, as long as you’re not driving. Just randomly raise your hand if you’ve tried ChatGPT, and the people around you can stare at you and wonder what on earth you’re doing. But we’ll know in our hearts that, out there, you’ve told us you’ve tried ChatGPT or another AI tool.
Celisa Steele: [00:07:25] That’s the first area where we’re seeing an impact of AI on learning businesses, and it’s around the speed and efficiency with which you can do your core work. A second area where we see AI having implications for learning businesses is in the area of learner experience and learner expectations. And we would make the argument that learner expectations have already been changing. COVID was a big driver of this. Essentially everyone was forced online during the pandemic, and then there was the fatigue from being on Zoom all the time, and people were trying to figure out what they do or don’t like when it comes to e-learning experiences. And so these learner expectations have been changing and evolving. But now, with AI, it’s going to just be another push in learner expectations.
Jeff Cobb: [00:08:18] It’s the shift that we’ve just already been seeing for years, even pre-COVID, just now really being accelerated and reaching a tipping point. The adoption of ChatGPT itself is sort of a harbinger of this. It went from zero to more than 100 million users really rapidly. People are obviously jumping in and using this. And, when you start using AI tools, they become integrated into things like search and our everyday types of software that we use. Think of your common set of productivity tools that you’re using at work. AI is going to be there if it’s not there already. And what that is essentially enabling is on-the-fly creation of very targeted, very personalized learning content. You can think of, back in the day, electronic performance support systems (EPSS) were a big thing in the learning and training world. And that happened before the Web even came along. And then the Web came along and became an even bigger possibility. But we’re now reaching the point where that’s just such a reality.
It’s embedded in our lives. We all have these performance support systems and learning systems that AI is just making better and better for us all the time, and that’s inevitably going to change expectations. It’s going to inevitably change how expertise is thought of and valued and what role formal learning experiences really will best play moving forward since so much of this is really informal, in the flow of life and work.Jeff Cobb
Celisa Steele: [00:09:45] If you think about these two points that we just raised, one is more internally focused. What is it that AI might mean for how you, as a learning business, operate? The second one is more externally focused on your learners, on the audience that you serve. What will this broader access to AI mean for what learners can and hope to do during a learning experience?
Jeff Cobb: [00:10:09] That’s one of the first areas we’re focused on as we find ourselves settling into this great milestone of 350 episodes of the podcast. And you’ve already heard from us on the podcast about AI. You’re hearing from us about it right now. You will, no doubt, be hearing quite a bit more from us about it as we move forward. But we promise to try to look at it in ways that are really useful, valuable, and helpful to learning businesses because, obviously, there’s a lot of buzz out there around AI right now, and people are probably getting sick of hearing about it. But we do have to embrace it and be constructive about how it’s going to shape our experience and our businesses going forward.
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The X Factor
Jeff Cobb: [00:11:48] The next area that we are focused on beyond AI (though related to AI in many ways) is what we’re describing as the X factor. And what we mean here is that there’s an ever-increasing focus on the total experience that customers, members, and learners have with our offerings. We’re thinking about the X factor as in UX, LX, and MX (user experience, learner experience, and member experience), and you can probably come up with some other places where X has been applied, but that X factor is really heavy out there right now.
Celisa Steele: [00:12:27] And so, again, in this area of the X factor, we’re going to offer two points in particular for your consideration. And the first point is just around the growing importance of humor—human interaction.
Jeff Cobb: [00:12:42] Humor is important too.
Celisa Steele: [00:12:43] Humor is also important, and humans are particularly good at humor.
Jeff Cobb: [00:12:47] Some are.
Celisa Steele: [00:12:48] That’s true. And so, in terms of what this means for learning businesses and learners, we’re seeing renewed and deeper interest in things like cohorts, communities, and coaching. And I think that a lot of this is driven by the desire, the need that humans have for interaction with one another. There’s been some pent-up demand for that kind of human interaction because, during the pandemic, we were limited in our ability to gather physically together. But now, as we’re emerging from the pandemic, as gathering together is safer, there’s this renewed acknowledgment that cohorts, communities, and coaching—any of these types of experiences that really make effective use of human interaction—can provide for richer, more personal, and then, ultimately, more effective learning experiences.
Jeff Cobb: [00:13:45] It does contribute to more effective. Most certainly, this is happening in interaction. People are really having to express themselves, absorb other ideas, play with those ideas, share them, and negotiate them with others. That really contributes to a more effective learning experience than sitting in isolation in front of a screen and trying to absorb information. Though that does have its place. I won’t completely dis that—it does have its place—but there is this hunger for human interaction. Human interaction contributes to effectiveness. We are certainly susceptible to this and eager for interaction ourselves. In fact, we should mention that we got together with 15 learning business leaders in DC recently for a couple of hours just to share. We had three people talk about initiatives or areas of focus, and, in fact, we shared the very points that we’re talking about right now on this podcast. And there was also time for other questions, more sharing. I can say that I think the energy was just really high. People were eager to be able to have those kinds of conversations with others who were experiencing similar things, in our case, in this world of the learning business. And I think it’s safe to say that quite a bit of learning went on there, and it was really driven by human interaction.
Celisa Steele: [00:14:59] The second point we’ll raise around the X factor, we’re going to call this “accessible relevance,” and this is just the growing importance of getting to the right content easily and quickly. This is really upping the emphasis on things like search. It’s upping the emphasis and need for curation. And I will say that curation could include things like learning pathways that you might spell out for your learners, different career pathways for them. I think there’s also a growing relevance and need for accessible design and accessible technology, and that can mean accessible for people with disabilities. It can mean accessible in terms of diversity, equity, and inclusion. It can mean accessible in terms of the time and budget that people have to spend on learning. Just broad accessibility concerns. And then there’s also a growing need and interest in smaller and more-targeted content, things like microlearning, because we have so many demands on our time, and yet we know that we need new skills and knowledge. And so microlearning can be that magic bullet that helps us get what we need but doesn’t take too much time and energy. All of these things get wrapped up in this overall concern with the X factor and what the experience is for the learner.
Jeff Cobb: [00:16:27] And these are certainly topics most of which we’ve covered on the podcast before. I know we’ve talked about curation. We’ve had Diane Elkins on to talk about accessibility. This is what I can remember most recently. I think we’ve talked about it on other occasions as well. We’ve certainly talked about microlearning. We need to have an episode about search at some point. I’m not sure we really have focused on search enough, but it’s just so important when you’ve got assets distributed across Web sites and across the Web broadly. How do you provide search that’s really going to get people to what they want? And, by the way, how do you incorporate AI into that going forward since AI is already a part of search, and it’s going to be more so going forward? All of this leads to a need to assess, rebalance, and renovate your portfolio. We use in thinking about this—and we’ll see how well we can do this in the context of an audio episode because it’s a visual tool—but it’s a double-axis chart. We’re consultants at heart, and so we have to always be able to pull out a good double-axis chart. In this case, the axes that we’re thinking about, one running from left to right, would be one-time learning experiences over to recurring learning experiences. You can think of that as your horizontal axis. And then your vertical axis, on the bottom is very simple learning experiences, and then those go up to very complex learning experiences.
Jeff Cobb: [00:17:50] As a double-axis chart does, this gives you four quadrants. In the lower left, where you have one-time and simple, you have things like what I think is too often still how e-learning is thought of, your on-demand, self-paced course for those one-time, simple experiences. Above that in the one-time complex, you have cohorts. We’ve talked about cohorts on the podcast before, and, certainly, those are extremely important. In the bottom right quadrant, where you have simple and recurring, you have things like subscription models. We’ve had Jack Coursen on the blog, writing about his subscription programs. Certainly, something we want to dive into more over time. And, in the top right, where you’ve got complex and recurring, this is happening over time, is community. And we’ve recently talked about community.
Celisa Steele: [00:18:54] Whether you use this double-axis chart or something else, the take-home message is to think about your portfolio and think about how well you are responding to and providing as close to an ideal learner experience as possible. Really think through your offerings and where they fit in that portfolio and what might be missing.
The Work/Learn Connection
Jeff Cobb: [00:19:24] That’s two areas we’re focused on—artificial intelligence and the X factor. And that brings us to our third area, which is the work/learn connection.
Celisa Steele: [00:19:36] We think that there’s a growing conversation, at least that we’re hearing, around the role of lifelong learning in work and in people’s careers. And, in particular, we’re seeing a lot of new interest or growing interest in the academic continuing education world, where, admittedly for them, this is a new area. They haven’t typically been as focused on work and career, and they’re seeing this now as a possibility for market expansion or at least a way to grow their influence and impact.
Jeff Cobb: [00:20:12] It’s been a real boom in the academic world because, as we know, degree programs have been under fire now for a number of years because of the cost, the relevance, and that sort of thing. And we don’t expect them to go away. But academic institutions rightly are looking at how do we engage with a different type of adult learner, the non-traditional learner and the continuing learner. That’s always been there to some extent, but it’s really become a booming area of academia now. And, like you said, I think they’re very tuned to it, possibly because it does feel like a new and innovative area for them to expand into. It’s funny—where we have seen less focus on it is in the trade and professional association world. Our theory there is it’s sort of a “we’re soaking in it” thing. It’s just so much a part of what you’ve already been doing for so long that you don’t notice that it’s become a big deal. And so I think there’s certainly an opportunity for those organizations to wake up a little bit and realize, “Hey, we’re playing an extremely important role already in something that’s becoming more and more important. And let’s let our voice and our leadership be heard here.”
Celisa Steele [00:21:20] And that’s on the positive side. On the negative side, it’s also being aware that there is new interest from others in this area, which means competition. Just being aware of that, that is another reason to perhaps revisit and reinvigorate what you’re already doing to help professionals in whatever field or industry you serve. So the two areas that we’ll offer to think about in this work/learn connection area, the first one is around workable credentials. What we have in mind here is that there is an evolving demand for credentials that, one, have some value to them—and that’s value in the eyes of the learners themselves and in the eyes of employers—and then, two, credentials that don’t necessarily require a major time and money commitment, at least not on the level that’s associated with degrees or traditional big certifications.
Jeff Cobb: [00:22:18] Right. This is that whole alternative credential world, things like badges, things like assessment-based certificates. We’re seeing the need and the demand for those go up, and, as you said, Celisa, seeing more ways to actually put some teeth and get some value in those. We find a lot of organizations that have certificate programs or even have certifications taking into account the value of those credentials in the employment market. And this is the workable side of this. You need employers to value those. You need learners to value them as something that’s going to contribute to their career development and advance them along their career paths. And we’re focused on work here, as a work/learn area, but the same can apply in more life-oriented credentials as well. But, in general, credentials are having a moment now.
Celisa Steele: [00:23:07] I think, if you are serious about making sure that your credential is valuable to employers, it means you need to make sure that you’re hearing their voice as you develop what goes into a particular credential so that it’s not just your guess about what someone needs to know to succeed in a particular position. You’re actually talking to those employers about what it takes to have a successful candidate and an employee that really just hits it out of the park in an area, and bake that into your credential. Take that into account.
Jeff Cobb: [00:23:37] And pay attention to the standards that are evolving in this area as well. We recently had an episode with the folks at 1EdTech, formerly IMS Global, and they’re deeply involved in standards around the portability of credentials, the shareability of credentials, and establishing the validity of credentials. And you want to make sure that you’re paying attention to that as you’re deploying different types of, particularly, digital badges, microcredentials that can be used in a variety of ways. So that’s the workable credentials area. And then we also want to highlight the concept of demonstrable impact. We’ve talked about impact a lot over the years of the podcast, in our work. In fact, we’ve got at least one entire episode devoted to impact. But this one, we think, it’s just becoming more and more important, and it relates back to some of the other things that we’re talking about. There is more competition out there. There is just more noise out there in terms of learning opportunities, getting people’s attention, getting people to actually pull out the figurative wallet or literal wallet and pay for learning experiences. And, increasingly, you have to be able to show that you’re having impact.
Jeff Cobb: [00:24:45] We’ve been asking for years about the decision factors that influence whether a person is willing to pay to participate in an educational experience. And we’ve been asking this of different organizations and audiences for lifelong learning, members of a trade or professional association. We’ll survey that audience and ask about these decision factors. There’s one question that has been a top two or three decision factor for years now and is growing stronger and stronger. The way we describe this is “The activity has been shown to produce demonstrable improvements in knowledge or performance for those who take part.” And so we’re asking survey respondents where they rank that on a one-to-five scale, along with a number of other types of decision factors. Usually, number one is the subject matter expert, the instructor, or the facilitator—their reputation. But this response to whether it’s actually creating demonstrable improvement is generally ranked two or three consistently for years, so learners do care about this. They do want to know that learning experiences have impact.
Artificial intelligence, the experience factor, and the work/learn connection all have our attention because we expect them to be of continuing and growing importance in the learning landscape, and they warrant discussion and action in learning businesses.Celisa Steele
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