Making Adaptive Learning 3.0 Work in Your Organization

Adaptive Learning benefits both the learner and an organization’s bottom line. In this episode of Powered by Learning, Craig Joiner, Senior Vice President, Brand Experience at Fulcrum Labs dispels some myths about Adaptive Learning and explains how organizations can put it to work to achieve their goals.

Show Notes:

Craig Joiner breaks down the barriers to Adaptive Learning in this episode of Powered by Learning. His key points include:

• Adaptive Learning is like a high-tech version of one-to-one coaching. It should challenge each learner just above their current knowledge level to boost confidence and push toward subject mastery. 
• Remember that Adaptive Learning isn’t a magic bullet. It integrates a variety of training best practices including competency-based learning, microlearning, and personalized learning.
• Adaptive Learning helps learners avoid taking training they don’t need. Instead, they invest their learning time in areas where they need more knowledge and skills.
• If you’re new to Adaptive Learning, you may want to start with a pilot with a small defined number of learning objectives that need to be delivered to a relatively large number of learners. 

Read more about Adaptive Learning in this Training Industry article written by Fulcrum Labs Founder Patrick Weir.

Powered by Learning earned Awards of Distinction in the Podcast/Audio and Business Podcast categories from The Communicator Awards and a Gold and Silver Davey Award. The podcast is also named to Feedspot's Top 40 L&D podcasts and Training Industry’s Ultimate L&D Podcast Guide.

Learn more about d'Vinci at www.dvinci.com.
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Transcript

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[00:00:00] Susan Cort: This is Powered by Learning, a podcast designed for learning leaders to hear the latest approaches to creating learning experiences that engage learners and achieve improved performance for individuals and organizations.

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[00:00:16] Sponsor: Powered by Learning is brought to you by d'Vinci Interactive. For more than 25 years, d'Vinci has provided custom learning solutions to government agencies, corporations, medical education and certification organizations, and educational content providers. We collaborate with our clients to bring order and clarity to content and technology. Learn more at dvinci.com.

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[00:00:40] Susan: Hello and welcome to Powered by Learning. I'm your host, Susan Cort. Today, I'm joined by d'Vinci CEO, Luke Kempski, who's going to talk to our guest, Craig Joiner, Senior Vice President, Brand Experience at Fulcrum Labs. Fulcrum Labs has developed a 3.0 Adaptive Learning platform and has helped partners from both enterprise and higher education achieve their goals. Welcome, Craig.

[00:01:06] Craig Joiner: Hi, how are you doing, Susan?

[00:01:07] Luke Kempski: Hey. Great welcome, Craig. I'm so glad you could join us this morning.

[00:01:11] Craig: Thank you, Luke. It's great to be here. I've listened to a couple of your podcasts now and very insightful, both on the questions and the answers provided a lot of additional clarity and perspective for me.

[00:01:21] Susan: Well, good, thank you. We're going to ask you to do the same today. Let's start out, telling us a little bit about your role at Fulcrum Labs.

[00:01:29] Craig: I am Senior Vice President of Brand Experience, and I work hand in hand with our Client Success Director. Fulcrum is a very outcomes-driven company, and these two roles work very closely to make sure that we're delivering for our partners on what their main KPIs are and also in translating that into marketing materials or engagement materials and just all-around thinking of new ways. With learning, there's always new challenges, and sometimes we even step a little beyond what you would consider a traditional SaaS adaptive platform role. That's where I help fill in.

[00:02:09] Luke: That makes sense, Craig. I think that adaptive learning is such an interesting topic and one you hear talked about a lot in theory, but you don't always get concrete examples or practices. Can you start by giving me your definition of adaptive learning and how that applies to what you do at Fulcrum Labs?

[00:02:27] Craig: I can. Thanks, Luke, this is a good question. Over time, we've seen people's understanding evolve. I'll take it from the most general level, the real general ideas of adaptive learning, and this is pretty simple, the idea is obviously to maximize the impact and efficiency of learning, and it's really by having the trainee adjust to the individual learner's needs.

At Fulcrum, we think of adaptive learning as basically, an extremely high-tech version of a one-on-one coach. That's a very visual concept. We've all experienced a one-on-one coach, and we've all experienced the benefits of having that personalization. Where the definition of adaptive gets more complex really is in the ways that different adaptive platforms adapt and why they adapt, what those decisions are and what data goes into those decisions on how it adapts.

Obviously, I can't speak a lot for other providers, but for Fulcrum, one of the main goals of that activity is simply to achieve optimal challenge, really, that learning sweet spot for each learner that's just above their current capability to maximize that application-level mastery and to boost their confidence in these new skills. Really, it all comes down to what I say all the time, which is so that people can apply these skills back on the job. This isn't just theoretical knowledge.

I'd also like to mention that while adaptive is really this critical component in achieving great training results and reducing training times, it's really just part of what an adaptive platform like Fulcrum is all about and why they're so successful. Adaptivity, while it's very powerful, when you combine it with other things like microlearning, or competency-based approach, or data analytics, learner choice, any of these things, that's really where you start to see the dramatic results in terms of learning outcomes and also the learner experience, which, as you know, is key to engagement.

When you're combining those things, it really is that 1+1+1=10. You really get this, adaptivity is the hot thing right now that people want to talk about because they've seen the results, and they understand the benefit of that idea of a one-on-one coach, but really, it's the combination of these other elements that really make it the most powerful.

[00:04:42] Luke: Yes, and that definitely is what's most interesting about it is how different aspects of learning and some of the current approaches to learning are overlapping with this whole idea of adaptive learning. It would be great if you could zoom in on an example of how adaptive learning can apply in an enterprise setting.

[00:05:03] Craig: One of the things we've talked about in the past is we talked about something very topical right now, is companies are seeing a significant amount of turnover. I'm sure you've heard it as well. Obviously, having their advantages to be able to get your employees trained up, both in terms of speed but also getting them on the job. Something that we talk about, which is what you don't want to have happen, is you don't want to have training and check the box.

You don't want people to go on the job and be, as we say, faking it till they make it where they're out there really making mistakes. Obviously, some situations are more critical than others. We often talk about and people ask me, "What does Fulcrum specialize in?" I said, "If the idea of people in your company faking it till they make it just scares the hell out of you and you can't sleep at night because of that, then we're probably someone that you should be talking to."

For a specific example, one of them is onboarding. Again, very topical, we're seeing a lot of turnover. We've heard terms like the Great Resignation. A lot of people, because of the pandemic, are reevaluating life and moving around, taking different jobs, having different criteria, so onboarding is very important. One of the partners that we work with, really high turnover rate, in the 80% range, and the skills that people were applying were critical and, in some cases, dangerous.

They began using it for onboarding. What they saw, the way that they were measuring, we always talk about, we want to make sure that they have success. In this case, they were measuring equipment damage as their primary KPI, if these people were actually applying the training on the job. What we saw, what the training delivered in Fulcrum's platform is they told us within the first year, they had reduced accidents by almost 60%.

When we heard that, it was almost too much. It's like, "Oh, people aren't going to believe us." Again, this is the partner's number. We were astounded by that. They said they had three months during the year where there were zero accidents. This is incredible for them in terms of cost savings and worker's comp that they were having to pay when equipment was damaged and things like that.

[00:07:18] Luke: In that case, Craig, can you talk about, what was the learning experience like? How did the learning actually adapt? Without getting into it really technically, if it's in a manufacturing environment, for instance, how does the learning adapt to the learner?

[00:07:34] Craig: One of the things that Adaptive is really good at is not penalizing people who come in with preexisting knowledge. We see this with onboarding, time after time. You might have someone who's just coming into the field for the first time, this is their first job. They basically need everything, all your skill set. Then you have other people who might have changed companies, and they're coming into your company from another company.

Onboarding is very different for them. What those people specifically talk about, they say, "I love that you didn't penalize me for the things I already knew, that this system allowed me to test out of areas." That's a common theme, too, testing out. Adaptive allows you to test out again at application-level mastery. It allows you to test out and very quickly move through the training.

Then the people who didn't know anything, they said, "I felt very supported. I made a lot of mistakes in the beginning." Again, we see that in the data. People come in, they don't have any existing knowledge, they make a lot of mistakes. The system is delivering at the optimal challenge, so the whole time, they feel confident. They never lose confidence, they always think, "I can do this. I can do this" because it's not, for example, serving them content that's difficult and then serving them even harder content.

It's understanding, it's mapping both their performance in the course but also their behaviors, and it's making suggestions to them. That's something that they say, "Oh, I loved it."

The other thing that people talk about, you talk about, how is this for the learner? They talk about how the platform, they say, "It put me in the driver's seat." It's funny because the learner doesn't necessarily talk about the adaptivity in that sort of a way, they talk about the experience. "I love that it put me in the driver's seat" is something we hear a lot of.

[00:09:20] Luke: That's great. I know that adaptive learning in terms of how it's evolved over time, what we talked about five years ago or even longer ago about adaptive learning is different than what the evolution of technology, and the use of data, and other things coming along that have really influenced-- I know at Fulcrum you talk about Adaptive Learning 3.0. Can you give us a brief history of the prior versions and leading to what's new about it today?

[00:09:48] Craig: I can. We've had a front-row seat to that because these aren't just versions, this is literally the experience that Fulcrum went through developing. When we started out, adaptivity was really about branching, very basic branching. In a lot of cases, we were a little more advanced, but the most basic branching being someone went in at the very beginning, gave some input, and then a pathway was projected for them that they went on, and there was no further adaptivity beyond that.

We started to evolve, and that was a little more various points along the learning education in Adaptive 1.0 where it was also further branching. That was really the beginning for us and for a lot of Adaptive platforms as well. What we started to see in the next level of sophistication of Adaptive 2.0 was the use of algorithms. It's like, "Okay, we could write these algorithms. We could put these things in place, and it could adjust a little, in a much more detailed way."

We could tap along the way, people, their pathway could be adjusted. That was great. That got us a long way until we realized, well, the systems should be learning and in comes Adaptive 3.0, which is really taking advantage of artificial intelligence and having the system learn from what is successful, what's not successful and really optimizing that. The accuracy, what you get with the AI, the ML compliment in Adaptive 3.0 is you get the ability to more accurately deliver exactly at the person's need, again, more to that optimal challenge.

[00:11:26] Luke: How would that apply in the situation we were talking about before, in terms of the onboarding at the 3.0 level where the system is actually learning? Can you give an example of that?

[00:11:37] Craig: I can actually give two quick examples. The system is learning and adjusting. One of the ways I'll give an example is the system is whilst the AI is going through and not only evaluating what to deliver to the individual learner, it's actually identifying how well the course is performing and giving us analysis, very actionable analysis. It's actually flagging content areas that are problematic.

What we've seen is that when we go in, we've adjusted these problematic areas, we've seen something really interesting. As you would expect, what we saw in this onboarding scenario, we saw an increase in performance in those areas where the content wasn't performing well, but what we additionally saw that is more interesting and also very powerful extension we saw performance in the whole course increase.

For example, if we identified a few problem areas and we fixed those areas, we saw overall course performance go up so that what it's proving is that when people have these experiences and it's not great, it's not optimal, people are underperforming in other areas of content. You go into a new section, you might be-- Let's say you're in hydraulics and all of a sudden you move into another section that's on weights and balance or some completely different subject.

The under-performance of the one content is bleeding into the other. Being able to fix those things and also the other thing you see is the instructional designer gets smarter. They start to learn how to craft better questions because they're seeing actionable analysis and they can A/B the content that they've edited.

[00:13:11] Luke: I'm glad you pointed out the instructional designer impact. I think that would be a good place to go next. A lot of our listeners, Powered by Learning, are involved in the development of learning experiences. How do they have to change in their approach to developing learning experiences based on having an adaptive platform at their fingertips?

[00:13:35] Craig: That's a great question. Obviously, part of that depends on where they're coming from. For example, we're based on a microlearning framework, all the studies have shown that microlearning increases performance. If you come from a microlearning, the transition into a Fulcrum platform is even smoother. Obviously, if you're not microlearning, I would suggest you start doing that anyway because all the studies are showing that that's the most effective way to deliver training.

A lot of it has to do with when I talk to instructional designers, what I get a lot of is a lot of myths. You talk to them and they say, "I'm hesitant. I love the idea of adaptive learning, but I don't want to give up. Craig, I love Storyline 360," or "I love Rise," or "I love this simulation tool that I've been using. I'm not interested in." That's just a myth that's out there. That's not with Fulcrum's platform.

We have the benefit that we originally also had a content division, so the fact that our content team of 40 people was working with our tech team, we were really building a CMS and a design system that accommodated for, and we had feedback all the time. We built a system that can accommodate any of that. Although people often come to us, they don't think that at first.

The other thing is, building a course in our Adaptive platform is actually a lot more similar to a traditional e-building and traditional e-learning course when people think. I think another myth that's out there is people think, "Oh, I have to think of all these pathways. It's Adaptive, so I must be thinking of all the schematic of all these pathways that could happen." That's really not the case. You build a fairly traditional style and then the system is really what takes care of all that. That often comes as both a huge surprise and a huge relief to people when we talk to them.

[00:15:47] Luke: Yes, that makes sense, and it sounds like the real key to it is to think in terms of small chunks, in terms of microlearning so that the system can pull in what's needed to adapt, based on t hose learning elements or those learning objects or those microlearning pieces, however you want to refer to them.

[00:16:06] Craig: Exactly. Again, we're achieving application-level mastery, and part of the way that we do that, as well, is also we're based on a Bloom's system, so we're pushing people towards application [unintelligible 00:16:19] level.

[00:16:20] Luke: Excellent. Adaptive learning makes a lot of sense. It still hasn't penetrated a lot of organizations, I guess, in their approach to learning. What do you think gets in the way of that?

[00:16:32] Craig: A lot of it is back to the myths. Eight years ago, nine years ago when people were like, "Adaptive? What's that?" and we would have to really explain like, "Here's what Adaptive is." Over the years, what we've seen is now there's more interest in it. There's been enough time where there are results out there, but there are a lot of different platforms that are out there or have been out there that are no longer out there but put a lot of ideas out in the workspace.

It's really just about educating people on the differences, and I think people come to it sometimes with a dated idea. We talked about Adaptive 1.0, 2.0, and 3.0. Sometimes people come to us and their concept of Adaptive is more of a 1.0 or a 2.0 thought, so they're like, "Well, it sounds pretty good," which 1.0 and 2.0 were pretty good for the time. We have to get them up to speed on what the latest and greatest--

Usually, what perks people's ears is, "Would it be valuable for you to be able to objectively measure the results of your training?" That usually gets a lot of heads nodding. We've always been challenging. Most of the people we start out with are at the level of surveys, right?

[00:17:50] Luke: Yes, absolutely. I wonder if you could take it another step further in terms of that value to the organization and maybe talk about if there was, for instance, a large health system with lots of employees, multiple facilities, multiple locations, defined roles but a lot of variations in roles, where would having an adaptive learning platform bring value in that scenario?

[00:18:16] Craig: Well, when you start talking about a health system. I'll go back to what I said earlier, which is, "Oh, that sounds like not a good 'fake it till you make it' scenario."

[laughter]

Whether people's lives are at risk here, it's like, on the clinical side, these are situations where you want people to do the training. The first time they apply that skill on the job, it needs to be accurate. The big value of Fulcrum is application-level mastery, and we achieve that. Two things, one is we get people to application-level mastery. The other thing that is part of Fulcrum's mission is helping turn these people into confident subject matter masters.

It's giving people the confidence. Adaptive can be really powerful in terms of giving people confidence, again, because it's adjusting. Think of when you're at the gym and you have a trainer working with you, and they're pushing you at optimal challenge, and you know they're not going to get you hurt. They know your limits of your body better than you do, and that's the way the system is, as well.

Very quickly, they understand how you learn better than your understanding of how you've marked, so it's able to get in there and get you to that, deliver the content to you just above that level, the appropriate level for you. It really maximizes your efficiency, gets your confidence high because you need to have that confidence to apply things. What we see traditionally is when people have a skill set but they don't have confidence, they can have a tendency to go back to some old bad habits.

What we really give a health system like that is, we give application-level mastery, we give confidence. We give people objective, measurable data on the results, and that's in terms of how their learners are performing. They have the confidence due to data that the course is performing well.

Because the analytics, again, the AI is going through and flagging any content areas that are underperforming, and they're able to adjust those, they basically instantaneously push those live, track those versions, track the performance of the content, A/B the content, and see how it's doing, fully optimize that course.

For a lot of-- like in a health system, compliance is a big deal. What you have in that case is, it's training that you have to legally deliver every year or 18 months or whatever so every time that's going through, it's optimized, optimized, optimized, it's getting better and better and better. What Adaptive provides for those people, who are going through compliance is, if they know the material because they've taken it last year and they know it and they're applying it, then they test out of it.

They don't have to consume that content. It helps get them through quicker. Time is, obviously, money, whether you're an accounting firm or whether you're a hospital, time is still money, and then the other thing it does for the organization is, we want people to be lifelong learners. Any L&D department healthcare, being no different, has a lot of training that they need to deliver.

The more that your employees respect your training, because your training respects them, the greater the buy-in. We don't want to have everything be mandatory. We're going to have some learning programs that are voluntary. The way that we get engagement is we show people those things are relevant, and forcing people to do things that they already know teaches them the opposite, right? The way that we encourage a culture of learning is by offering these meaningful learning experiences. Does that help give you some color on a health system?

[00:22:03] Luke: Yes, absolutely. I think you can start to see how this Adaptive Learning 3.0, combined with AI and machine learning, has the potential to be revolutionary in how we distribute learning in an enterprise like a health system. I think it also could be a bit overwhelming for a learning leader in terms of, if they currently haven't done anything yet that would be deemed adaptive or haven't implemented any aspects of adaptive learning. Where should they start?

[00:22:42] Craig: MVP, what they talk about all the time in the tech world is a minimum viable product, right? It's like, "Don't think you have to take on something huge." The most important thing, you do a pilot. You see if it works, you test it, and the way that you do that I would say there's two criteria. It's like, pick something small. They say the best way to eat an elephant is one bite at a time. You pick something that's bite-size.

What we've seen, we've worked, in particular, with a healthcare provider on something small, and by that I mean it might be between 6 and 12 learning objectives that you don't need a whole lot. 6 and 12 learning objectives could be like, I don't know, a half-hour to an hour course, depending on people's knowledge, and you try it. You don't hook it into anything else. You let the platform be a standalone, and you try it.

The most important thing is picking something little that's going to be meaningful so that when you see these results, it's meaningful to you. The other thing is when you go into it, you really need to set your-- and this is something we work with on our partners, you really need to set your KPIs, to know what you're shooting for so that you're really rock-solid, and you do something small, let it prove itself. Our biggest marketing tool is pilots. When people do a pilot, people sign up.

[00:24:01] Luke: Now, that makes complete sense. I know that we've seen clients do a really great job at being able to embrace that pilot approach and take a base-level learning objective that needs to be achieved across a number of different audiences or learning groups within their organization and really have a big impact, with that. It sounds like something that would be a really good first topic for you.

[00:24:28] Craig: Absolutely. The other thing that people really like sometimes when they go in, people say, "Craig," do you know that first part you mentioned, the part about picking something meaningful," they say to us, "We don't know. We what it is." Fair enough, our tool can be used for needs analysis, a very efficient adaptive needs analysis. If you want to or you need to start there, that's a great way to go as well.

List out skills that you think are important, let's put people through, and let's see where they are. The benefit of Adaptive, if the system sees that they don't have some critical-- again, it's going towards application-level mastery. If the system sees, "Hey, these people don't have application-level mastery in this component of this skill," it doesn't bother with the rest of the questions.

It's like, "Okay, that person's going to need to be trained on that because they don't have the complete set." It'll throw out scores of questions related to that specific skill. It's like, "Okay, that that person needs training. Let's just flag them as they're going to need this training." It becomes very, very efficient. That can either be done as a standalone, just needs analysis, or that can then customize and build the course that a person then goes through based on how they perform.

[00:25:48] Luke: Yes. It makes me think of an example. One time we did a course on handwashing and hand hygiene in a medical environment and how the different-- depending on who the learner is within an environment, within a health system environment, they need maybe more advanced learning or maybe they have already learned it, and then you have everybody from people who work in the kitchen or work in maintenance or work actually in a clinical position and how the learning may vary and adapt based on that pre-existing knowledge and maybe even on their position and what they need to know.

[00:26:25] Craig: That's a really good point. Additionally, too, Luke, in a system like ours, when you build something like that handwashing course or skill set, what you can then do is you can then-- Let's just say, I don't know, food service. It's like there are a lot of other skills that food service employees need. You could build a food service training course and then you take that handwashing and drop that in as well. It's like, "Okay," and then you can multipurpose that. You can then, "Hey, we need it over here also for people who do X or Y, we'll drop it into that as well."

[00:26:58] Luke: Yes. You're really disconnecting the learning elements so that they can exist over multiple types of course bundles.

[00:27:07] Craig: Exactly, or you just throw it in, you say, "Hey, we just want a refresher, and people can easily test out of this." The other thing, too, we're collecting part of what makes Fulcrum. The reason I work here is I love learner choice, and that's something very powerful for me, just as a learner, and that's something that I gravitated towards, too. Being able to offer that to people is something very powerful. Studies have shown that even on boring material when you give people choice, people will engage longer.

[00:27:37] Susan: Well, I love, Craig, that the adaptive learning can really lead toward the confidence to make people more proficient in their job, also build engagement, and even retention, to your earlier point about keeping people on the job, and then conversely, the fact that adaptive learning can help shape the training. I think it sounds like a win-win.

[00:27:57] Craig: That's what we found. I'll say this, too, Luke asks about value propositions. I got to say, some of the value propositions we learn end up coming from our partners. They find once they really understand how the tool works, they're constantly coming to us showing us new ways that they want to use the tools.

[00:28:16] Luke: That's the beauty of AI is that the more the system gets used, the more the system's going to improve and add more value as it learns and adapts.

[00:28:26] Craig: Exactly. To my other point, on that learner choice is when you're able to give people choice, you not only provide them with these opportunities to let things play out the way they want them to, but you're also able to collect more data. For example, on that, when people would get an answer incorrect, we used to show them a hint, something that would move them towards understanding, on their own, what the correct answer was, not giving them the answer.

What we realized was, "You know what, let's not do that because not everyone just wants that hint, let's do like a great tutor" where they say, "Do you want a hint?" and they're allowed the opportunity to use that or not. By doing that, we did two things. One is we empowered people with more choice. The other thing we did is, we were then able to because when we just showed it, we didn't know who was taking advantage of it.

Now we know who's taken advantage of it, and when we look at who's using the hints and who's not, if the people using the hints are not doing better, then the hints aren't effective. It gives us some idea of how to make those hints more effective or that we need to.

[00:29:30] Luke: That's great. I think we've done a good job of covering different applications of adaptive learning and looking at it, both at an enterprise level and on a learning experience level, and then an instructional design level. To wrap this up, Craig, talk about, what's next with Adaptive Learning? Is there a 4.0 in the future?

[00:29:48] Craig: [laughs] There is. As you probably guessed, this is going to keep going. With some of our current partners, we're in Adaptive 4.0. What adaptive 4.0 gets you, it's everything at Adaptive 3.0, plus what we're doing is we're taking external performance data, and that could be, let's just say there was a certification task after or where people-- they were measuring something in the workplace. What we can then do is we can overlay that with the data in the platform, and we can do two things.

We can make the training more effective. We can be just that much more granular and effective. The other thing we can do is we can make even greater predictions. Where we are, what people find the most useful right now is, the platform is able to predict people who are going to actually apply those skills back on the job before they go back on the job, and that's something that our employers have found very valuable, and the platform allows a lot of customization.

For example, you could set the platform to encourage some level of self-remediation, or you can make that self-remediation mandatory with a lot of customization in it. What 4.0 will really allow people to do is make even more predictions, make correlations. We're all about actionable data. When we build our dashboards, there's a lot more that we could put in there than we do, but what we put in there is for the general customer, the things that are going to be very actionable so we don't overwhelm them.

[00:31:21] Luke: Boy, you got my mind going, for sure. I can think of so many applications across so many d'Vinci clients and newer approaches that they can take. Thank you so much for joining us, Craig.

[00:31:32] Susan: Yes, thanks, Craig.

[00:31:32] Craig: Thank you. Thank you, Susan. Thank you, Luke. It's a great conversation. You asked a lot of really intelligent questions, and I think your audience will really be rewarded.

[00:31:43] Susan: Thanks for taking the time to talk with us today, Craig.

[00:31:45] Craig: You're welcome.

[00:31:48] Susan: Luke, Craig did a great job of breaking down some of the perceived barriers to adaptive learning and showing how it can benefit both the learner and the trainer. What were some of your takeaways?

[00:31:58] Luke: Yes, that was a great discussion. He certainly helps us think about adaptive learning in different ways. He started with defining adaptive learning. He defined it as having the training adjust to the individual learners and thinking of it like a high-tech version of one-on-one coaching. Adaptive learning should challenge each learner just above their current competency, striving for mastery and boosting confidence in the learner.

He also said that adaptive learning doesn't live in a vacuum but is part of a lot of training trends: competency-based learning, microlearning, personalized learning, and then of course using data, data analytics, and AI. He talked about how adaptive learning could be applied to onboarding and bring even more value in a high-turnover environment. Craig also pointed out that we sometimes punish learners by putting them through training that they don't need.

With adaptive learning, we give them the ability to test out and save time while on the other hand, if someone needs more training, they get more. He also talked about the evolution of adaptive learning, starting with version 1.0, providing learning pathways, going up to 2.0, adjusting levels based on system algorithms, and then 3.0 where the learning adapts based on learner inputs and also on analyzing and optimizing content by applying artificial intelligence.

He also talked about the impact on instructional design. He said instructional designers should still be able to use their favorite tools to develop learning experiences. They just need to think more in terms of microlearning, developing microlearning objects, rather than developing whole courses. That way, the learning platform can personalize the learning versus forcing every user to go through a whole course.

Two other takeaways stuck out from Craig. First, he recommended if you're new to adaptive learning, you may want to start with a pilot and have that pilot just have a small defined number of learning objectives that need to be delivered to a relatively large number of learners. The final takeaway was what's next in Adaptive Learning. It seems like version 4.0 can extend across the boundaries of an organization and take advantage of intelligence and analysis gathered from multiple organizations in an industry to have an impact that's even on a greater scale. Really, it was just a great conversation with Craig.

[00:34:27] Susan: Thanks, Luke, and many thanks to Craig Joiner of Fulcrum Labs for joining us today. If you have any questions about what we talked about, you can reach out to us on d'Vinci's social channels through our website, dvinci.com, or by emailing us@poweredbylearningatdvinci.com.

[00:34:46] Sponsor: Powered by Learning is brought to you by d'Vinci Interactive. For more than 25 years, d'Vinci has provided custom learning solutions to government agencies, corporations, medical education and certification organizations, and educational content providers. We collaborate with our clients to bring order and clarity to content and technology. Learn more at dvinci.com.

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