All Things Learning Design

[00:00:08] - [Speaker 0]
Welcome to the Learning and Development Podcast sponsored by InfoPro Learning. As always, I'm your host, Nolan Hout. Joining me today, have Julie Derksen, author of one of the best selling instructional design books of all time, designed for how people learn. It's an incredibly popular book, although it was written, I think maybe decade ago or so, there's been new releases and it continues to be popular today. She's also an internationally recognized speaker and learning consultant on a wide range of topics, but really has a special focus on incorporating behavioral science into learning interventions.

[00:00:41] - [Speaker 0]
Today, we're going to talk to Julie about a little bit of all things learning design from diagnosing the problem, creating sound design strategy, reducing cognitive load. And if it sounds like a lot, it's because it is. So we'll stop wasting time and meet Julie to come in here and bring some information. Julie, welcome to the podcast.

[00:01:00] - [Speaker 1]
Thanks for having me.

[00:01:02] - [Speaker 0]
The first thing that we always like to do when we start is just to learn a little bit more about our guests. Obviously, you know, as a best selling author and and and international speaker, you didn't start your career there. How did you get into this world of learning and development?

[00:01:16] - [Speaker 1]
Well, know, I feel like the origin story for a lot of people is what I sort of describe as, hey, you're a good customer service rep. We're gonna let you train the other customer service reps, which, you know, people come at it from domain knowledge. They know a lot about their topic. They're the person who's helpful. There's the person who's, you know, kinda been giving other people, you know, guidance on how to do it that gets tapped to then come and be the training person.

[00:01:40] - [Speaker 1]
That's more or less how it you know, that's kind of how it happened. I was I was doing data entry for a finance company when I was in college as a part time job, and then I graduated in the early nineties, so a long time ago, but it was not a very good economy. And so they said, hey, you wanna train other people how to do data entry? And I said, yeah, okay. I'd also been doing a certificate in teaching English as a foreign language.

[00:02:06] - [Speaker 1]
And so I was interested in the education piece. And then when I got into it, I found what I really liked was the design piece of it, right? Like, how do we create courses? What do we think about? How do we put this all stuff together?

[00:02:20] - [Speaker 1]
How do we use technology to support it? And that wound up being the part that I I kind of enjoyed the most. I I still like delivering workshops. I still do a certain amount of it, but I was not enough of an effusive extrovert to wanna be a, you know, a trainer full time. And so but the design piece I really loved.

[00:02:42] - [Speaker 1]
And so I went to graduate school in the late nineties to do instructional systems technology Indiana University, which at the time was one of the biggest, and probably still is, one of the biggest kind of instructional design programs.

[00:02:53] - [Speaker 0]
Yeah.

[00:02:55] - [Speaker 1]
And spent a bunch of time there kind of over in the, what we weren't even calling user experience design yet. It wasn't UX. It was still human computer interaction. So how do we, like, change the technology to support performance along with so I I think you kinda get it from both sides. Right?

[00:03:12] - [Speaker 1]
Like, how do I make the the technology or the environment support what we want people to do as much as possible, and how do you train people to be able to do those things? And so I think I've always had that perspective a little bit, which is, you know, sure you can train people, but it doesn't fix a bad computer system.

[00:03:30] - [Speaker 0]
Yeah. So it seems like and what's interesting, it seems like you have this, this, I don't know, core in you to just remain like, oh, I really want to understand how this thing works. Not just at like a superficial level, but like, I really need to understand the nuance of this or the science, I should say, not nuance, the science behind how are people learning this way. And that's kind of the praise I know that you've gotten in your book is it's very backed by this is what's working. This is what's right.

[00:03:59] - [Speaker 0]
So that's great. Well, and thanks for sharing. Getting into the podcast, one of the first things that we really wanted to talk about, you know, if we're going to kind of follow this story of, of how do we actually create these experiences and these programs that make an impact that we were just talking about. We have to start with diagnosing what that problem is. Talk to me a little bit about how we go about diagnosing the real learning problem.

[00:04:24] - [Speaker 1]
Yeah, yeah. Well, know, we have kind of a recurring theme as an industry around not being an order taker and not just kind of going, okay, when somebody shows up and says, you know, we want customer service training or something like that. And the real challenge is getting a good statement of what the problem is that they're trying to solve, you know?

[00:04:46] - [Speaker 0]
Yeah.

[00:04:46] - [Speaker 1]
And that's not always that easy to do because it assumes a few things. It assumes that they actually know what problem they're trying to solve rather than we're just generally unhappy with how it's going. And getting people to be really specific about it. And I always talk about, you know, when I'm doing kind of one on one workshops, always talk about is this, are you getting handed a problem to solve? Are you getting handed a solution to implement?

[00:05:09] - [Speaker 1]
If you're getting handed a solution to implement, it might look like, hey, we need sales training. Well, okay, what are they doing or not doing that's working right now and what do we need them to do differently? And, oh, okay, you're really concerned about cross selling or you're really concerned about the fact that they're going in and starting to announce all the features and benefits of the product without asking the customer any questions first. Well, okay, great. Let's let's focus in on that piece of it where you need to actually ask your customer about what their problems are and what they need help with before you start selling them solutions.

[00:05:42] - [Speaker 1]
Cool. That's fantastic. Let's talk about that as a you know, how do we help support that behavior? And it might be that it's a trading problem, probably is. Trading is probably an element of that.

[00:05:55] - [Speaker 1]
But it also might be, Hey, the way the sales literature is configured, it doesn't support the behavior that we want people to do, which is to start with what are the customer challenges? Or it might be that we're incenting certain behaviors where we're not giving people enough time because the only thing we're counting is how many sales calls you do per day and not how much repeat business you get, which the second one might be a better indicator of a really consultative sales approach than just how many sales calls did you cram in an eight hour period. And so all of those things may be contributing to why people aren't, you know, getting a good understanding of customer problems before they start selling stuff to them. But not all of those are training issues, you know?

[00:06:46] - [Speaker 0]
Yeah. And, yeah, and I, you know, I, I give an example. We were doing a rollout of a new customer facing software, kind of like a CRM, but it was back end and front end. So the customer service reps, And we were asking, what are the KPIs? What, how are we going to measure whether we did a good job?

[00:07:05] - [Speaker 0]
And they're like, well, the number one thing is like, we just don't want people in the queue. Like we just don't want a long queue. We want to get to their answers quickly. We're like, okay, cool. Like we get that.

[00:07:15] - [Speaker 0]
So we're servicing quickly, but then where, what is the value driver? And they're like, well, why does it really matter? And I'm like, well, you know, if you want people out of the queue, you kind of got to reduce talk time, but then you traditionally see a spike in, I don't know, or a decrease in first call resolution. And so you're going to have people calling back in. So how do we, how are you motivating?

[00:07:42] - [Speaker 0]
And they, and, and, and it was evident to that, that client that they needed to go back to their business and actually ask better questions. But I feel, but, but that was a challenge. It really was. And I remember them saying, yeah, you know, we went back and we weren't really able to get a straight answer. How do you in learning, how have you seen organizations best go back to the business and say, I'm going to solve your problem for sure.

[00:08:07] - [Speaker 0]
But actually, I think it might be a, you know, an incentive issue. Like they might, they're being incentivized on the wrong thing. How do you, how do you do that? Cause you're kind of stepping outside of your, you know, lane, if you would, in many How have you found the most success in educating the people in that?

[00:08:26] - [Speaker 1]
Yeah. And I mean, one of the things that I often think is like, you know, we want we want to have that relationship with them upfront where they trust us to kind of help be partners in solving their business problems. And sometimes, you know, sometimes you can make that happen on the first engagement, but honestly, a lot of it comes down to what's the relationship that you've built with them, right? Do they do they see you as a partner in this, or do they just see you as a vendor that they're gonna off you know, offload their training needs to and things like that. And so if you're working in an agency or something like that where you may only ever have one engagement with this client, I mean, in ideal in the ideal world, of course, we want our clients to come back to us for stuff.

[00:09:04] - [Speaker 1]
What of can you do to build that? And a lot of it is about the questions that you're asking. In your case, they were coming to you with a problem, but they actually had to go back to their Yeah. They actually had to go back to their internal client to try to get, you know, to try to get some some you know, because it is an interesting problem. Right?

[00:09:26] - [Speaker 1]
Like, if we reduce talk time, but we increase, you know, people calling back, then presumably, they're just gonna fill that queue up again.

[00:09:33] - [Speaker 0]
Right.

[00:09:34] - [Speaker 1]
Right. You know? And now we're in a race to the, like, who can get them off the phone the fastest, not how do we have, you know, how do we have, how do we, you know so because misaligned incentives happen a lot. Yeah. They're a frequent issue.

[00:09:51] - [Speaker 0]
But but you said something that was, like, so critical, I think, which is how you start the relationship is really important. And I'm having a lot of conversations and talking to a lot of leaders who realize that, that, that they have this skill, but they need to make sure that they continue to frame this skill as I'm helping with your performance problem. I'm not necessarily helping with your learning problem. Learning is prop, could be, maybe is the answer. But before that, I just, I need to understand your business so that I can better advise you on what the solution would be.

[00:10:27] - [Speaker 0]
If that's your, you know, we were actually, we were joking before this call about kind of the proliferation of, of, of people selling, you know, selling hammers and finding a bunch of nails that And maybe didn't so like, I think a lot of it is just, can you start with that? They're recognizing that value is just, can I be a business driver and then back into learning if that even becomes the thing?

[00:10:55] - [Speaker 1]
Yeah. Like, of the things I always ask people is like, well, what budget line item is paying for you? You know? Yeah. What is that?

[00:11:03] - [Speaker 1]
And and if that's a budget line item and, you know, this will you know, again, it could go back to KPIs or, you know, OKRs or, you know, any of these kinds of things. But it also goes to what's a win for the stakeholder that I'm working for, you know, which may or may not, you know, equal what's best for the audience or something like that. But you're you do have to manage that. Like, do have to kind of at least consider. I I was talking to somebody who really wanted to do better, you know, better, more interactive, more scenario based training, and he was trying to sell his boss on it.

[00:11:37] - [Speaker 1]
And his boss is like, look. We just need a quick win here. And he was really you know, the person I was talking to was really frustrated, and I'm like, yeah. But you're not you're not listening to what they need too. You know?

[00:11:47] - [Speaker 1]
Like, I love that you're trying to advocate for good learning experiences. I love that you're trying to, you know, figure out how to do better learning design. That is something I'm deeply passionate about. I think that's great. But you just blew right past, you know, your boss telling you this is this is the thing I need in order to, you know, feel successful.

[00:12:07] - [Speaker 1]
And I'm not saying that they aren't, you know, in opposition to each other because obviously faster and better don't always don't always add up.

[00:12:14] - [Speaker 0]
Yeah.

[00:12:15] - [Speaker 1]
But the fact that you're you're not listening to you know, your boss is telling you something that's that's obviously really crucial, you know, whether it's their KPIs or, you know, their performance review that they're concerned about, you know, with this kind of thing. They they need, you know, they need to figure this out. And so any solution that's gonna work for both of you has to be a negotiation between those two. You know, they don't have enough information about their situation to identify, you know, where can we where can we meet where can we meet both of those things, you know, better quality but also faster, may may not meet up, but is can we find any overlap on those two circles? So

[00:12:53] - [Speaker 0]
Yeah. Yeah. And I mean, you know, they say, you know, better, faster, cheaper, choose two, you know, and so a lot of times when you hear that, you kind of do have to find, okay, well, what is going to give? Which lever are we going to give? And that feeds right into kind of the next part.

[00:13:10] - [Speaker 0]
So once we, you know, once we've defined the problem, now we have to match the design strategy to the complexities of that problem. And we just talked about one of those things that factors into the equation. Maybe you could say that it shouldn't, but it absolutely does. Like, you know, budget cycle KPIs of the CEO, you know, whatever promises have been made across the organization. So certainly there's there's those situational things that come up.

[00:13:41] - [Speaker 0]
But for the most part, when we're talking about designing something to match the complexity of the problem, it's more about, you know, how deep is this problem and what are we trying to design? Can you talk a little bit about how you go about doing this?

[00:13:53] - [Speaker 1]
Yeah, I mean, one of the things that I do, and we've got the learning objectives identified, and hopefully they're behavioral objectives. Like I always, know, I think Bloom's Taxonomy is an amazing tool, but I don't really use it that much myself, because when you're in workplace learning, you're almost always dealing with the applied. What can they do with this? You know? And so the questions I always ask is, is this something that would happen in the real world?

[00:14:14] - [Speaker 1]
You know, if they know this thing, what are they gonna do with it? And can I tell? Could I you know, is there a recognizable behavior that I can kind of evaluate and use to judge that, like, yes, they're successful at it. So if I say, oh, programmers need to understand, you know, when or when to when JavaScript is an appropriate programming tool. Well, when are they gonna use that?

[00:14:34] - [Speaker 1]
They're gonna use it when they're evaluating a project. Right? Mhmm. So now my applied is programmers will be able to evaluate a project and determine if JavaScript is an appropriate programming tool. Sorry.

[00:14:45] - [Speaker 1]
This is going super nerdy, but but nonetheless, like, that framing helps because then it tells you what's the activity that they should be doing as part of the learning. Well, they should be looking at different projects and matching them up to, you know, appropriate, programming. Like, what's the right programming tool to apply to this project? Like, that's the thing we now we want them to do. And there's a number of different ways to kind of get to that.

[00:15:10] - [Speaker 1]
I was just talking to somebody about Kathy Moore's action mapping, which is nice, which is like business goal, the behaviors that support that business goal, the practice the kind of practice that then, you know, helps people learn those behaviors, and then the information needed to do that practice. And so we put information last, you know, as opposed to a lot of curriculums where information is, here's your list of topics that you need to train people on. We start with the information and maybe we work our way into the application. But you know, that's not how most people are applying this stuff in the workplace.

[00:15:43] - [Speaker 0]
No, no. It's like traditional learning as, you know, I need to learn something. Let me get my encyclopedia off the shelf. You know, which one is it? Okay.

[00:15:54] - [Speaker 0]
But that's, again, it's not, people are expecting that knowledge in a much quicker turnaround time than they used to. And it weaved in there, right. You mentioned, you know, how are they going to apply it? Are you seeing AI play a factor in that? I mean, cause it, it really touches all of those things, obviously like information, but specifically at application layer, right?

[00:16:17] - [Speaker 0]
With a lot of talk about leveraging agents, obviously Workday just bought Sana to implement and have essentially agents driving a lot of the back office. How is that being weaved into this kind of, you know, a complex problem, but being able to deliver a point solution?

[00:16:37] - [Speaker 1]
Well, you know, the challenge with the AI is I think we've been promised that we can hand over, I think, you know, like a 100% of the tasks to the AI, and it's like, no. No. Yeah. Yeah. But can it be helpful?

[00:16:50] - [Speaker 1]
Sure. Like, one of the things I always try to do when I'm doing a workshop for somebody is to use some of their learning objectives, use some of their tasks, try to translate some of the examples into their context because, you know, we know that, like, putting it within their context is gonna improve transfer of the information. And I've actually I've done stuff for a couple of, like, social service agencies or state agencies lately, where I'm like, hey, take give me you know, give me five learning objectives and give me, you know, this kind of information about it from this you know, here's the website where they're you know, all their training materials are. Give me five things that are plausible in this environment. Yeah.

[00:17:28] - [Speaker 1]
And then when I've taken them back to my clients and my stakeholders, they've been like, oh, yeah. These are pretty good, but no. Don't use that one. We never talk about that. Or this one's out of date.

[00:17:37] - [Speaker 1]
But those other ones, those are pretty good. And it's just saved a lot of time because usually I'd be like, hey, guys. I need some learning objectives. Can you get those for me? And then they try, and I'm like, oh, okay.

[00:17:47] - [Speaker 1]
Let's try again. Let me give you more clear guidance on what I'm really looking for. Okay. Good. Good.

[00:17:53] - [Speaker 1]
Good. Now we're getting know, and it'd be like four or five back and forth, you know, email sequences. And now I can just show up and be like, hey. This is what, you know, the AI gave me. Are these right?

[00:18:03] - [Speaker 1]
Are these good? And they're they can kind of vet them quickly, but they understand what I'm looking for, and we can move through it. And so, taking this and going, alright, have this general sales training, I want to apply it in this context with this product, with these things, can you redo all of these questions, or can you redo all these examples and put it into the specific context of people selling web services or something like that? And it's pretty good at that stuff. It's not perfect, you still need to check it, know, like that kind of taking something specific and customizing it for a particular audience, like, oh, it's kind of nice.

[00:18:42] - [Speaker 1]
This is actually easier. But I also was watching a video just yesterday of somebody who is a graphic design instructor, and she kept mentioning that she's got, I don't know, twenty five or thirty years experience in graphic design, and she had taken all of the clear prompt engineering and all this kind of stuff and was asking ChatGPT to teach her as, you know, a faux beginner how to do graphic design, and she's like she's pointing all the ways that it was terrible. And now granted it was a super visual topic and ChatGPT doesn't play well with that, but it was still just not good. It was you know, it asked her a million questions. It was very repetitious.

[00:19:21] - [Speaker 1]
It was really struggling with explanations and examples. It was just you know, it's not there yet. It's not there yet. Will that change? Maybe, but you know, one of the biggest issues with the AI stuff is it is still, and with the large language models likely to always be something where you need that expertise to evaluate the outputs, which means we're never gonna wanna turn it loose, you know, with beginners, because it's not, you know, it's not enough.

[00:19:54] - [Speaker 1]
And so, you know, is it is it going to get to the point where I can I can totally let beginners kind of stumble around in it? Maybe. But, you know, I'm I'm I'm still skeptical, but we'll see. It's better. It's better than it used to be.

[00:20:13] - [Speaker 0]
I was just talking the other day, and there was this actor, Werner Herzog, who was being interviewed by Conan O'Brien on this podcast. You know, he was saying, it's like when I was a kid, I learned how to use math and then I was given a calculator to apply it. And I really think that's a good, you know, analogy when it, you know, if, if I were to give my son a calculator and say, go learn math in your multiplication tables, he would know how to use the calculator really well, but he would never understand math. And if you ever took that away, he would never be able to leverage it. The core, you know, knowledge that he had, and he wouldn't be able to apply that into the next layer of math, right?

[00:21:04] - [Speaker 0]
The building blocks of calculus or algebra or whatever it is. And so I think that's really where it's key. And I was thinking about it as we were going to talk today about kind of this, you know, as the complexity of the problem gets higher, AI can simplify a lot of these highly technical things, especially for, for people who are not in the field, but when we're trying to design something for somebody else can kind of make it more attainable for us. But it is one of those, those things where as the topic becomes more complex, it's usually complex because there's a lot of nuance. And, and if you kind of don't relate those two things, and you're just thinking, oh, this is really complicated.

[00:21:44] - [Speaker 0]
Is it a perfect use case for AI? It actually might be the inverse of it is, you know, you actually need somebody to come in and chain like, I mean, and and change that skill to do something with it.

[00:21:57] - [Speaker 1]
Yeah. Well, and, you know, by definition, because it's still so relatively new, you know, what we've we've had rely, you know, sort of reliably done really useful AI for, like, two two, three years, somewhere in the Two

[00:22:11] - [Speaker 0]
and half years. Two and a half years, January 2020.

[00:22:14] - [Speaker 1]
Yeah. I it was just coming out when I was writing my last book, which is an interesting time to be writing a book. I'm gonna hopefully write another one this winter, and it's gonna even be more interesting. But, you know, like, what's the value of actually writing all the words on the page versus, you know, generating them? But the so by definition, the vast majority of people who are using AI in some kind of workplace context are people who know how to do their jobs.

[00:22:42] - [Speaker 1]
Yeah. And so therefore can use a it's kind of I have I have a whole metaphor about, like, it's kinda like the scooter, right? You can just get there faster and, you know Yeah. And easier than you would if you were having to, you know, do the whole slog yourself. But you, by definition, have the expertise to evaluate and judge whether or not this is now are people do people have the discipline to do that?

[00:23:04] - [Speaker 1]
That is a whole different it's a whole different question because that sort of psychological stamina to check the outputs is not necessarily a historically a historical strength of a lot of people. You know, there's a reason why most of us need some external proofreading when, you know, when we're doing stuff. Totally. But that is going to, change as we move forward and there will be people using this to do things that they can't judge the outputs on it. And we know that that's not a great formula right now, but we're gonna have to figure out how do we manage that, especially in organizations.

[00:23:41] - [Speaker 1]
What do I do if somebody's giving, you know, them answers that they can't, you know, they can't necessarily validate or verify?

[00:23:49] - [Speaker 0]
Yeah. It's I I talk with our so we have a gentleman who creates our know, who owns our leadership division of our our organization, you know, not managing our leadership, but our product that we go and sell. And we talk a lot about AI and the use of AI coaching. And so like right now, you know, we're, we're a pretty firm believer that you cannot just give an AI coach to somebody and say, kind of say, go at it, Take the calculator example. We're a firm believer that you have to actually sit down and teach the person, I don't know, communication with clarity, whatever it is, they have to, to, to actually understand the core of what you're needing to do.

[00:24:29] - [Speaker 0]
Now, what an AI coach can then do is say, you know, you may not apply this right away. It may take you three, four months. May take you a year before you have to apply this. Use it when at that moment, use it as a tool. Okay.

[00:24:42] - [Speaker 0]
Now you know what? I don't know, God, it's been forever since I had to, you know, identify the type of triangle isosceles or obtuse or whatever, like, but I know roughly what it is. Okay, so let me go in there and make some changes. So, but, but it, but then we also talk and so this idea though, as you said, of like letting AI loose and, and what happens when it gives the wrong answer? I'm a, I myself am a little bit, I don't really know where I stand because I also feel like, well, what's the alternative?

[00:25:17] - [Speaker 0]
Like, where are they going for those answers today? Right? We know managers aren't giving them any real coaching. They're not really giving that nobody's got the time to do it. So it's like, is this cheap version of this leadership coach better than no leadership coach or, better than the leadership coach that nobody wants, you know, in, you know, because there's bad coach, there's really bad coaches, there's coaches that do a lot more harm than they do good.

[00:25:44] - [Speaker 0]
So I don't know. I don't know. I still don't even know where I land on that, but I think again, coming, bring it back when we talk about like that complexity, if you're, if you're designing something, maybe think back to, okay, do I need to teach them two times three before I give them the calculator? That might be an easy one.

[00:26:02] - [Speaker 1]
Well, I mean, K-twelve is so not my area of expertise, but my memory is there is actually data that says that that's true. You want people

[00:26:10] - [Speaker 0]
to be able

[00:26:11] - [Speaker 1]
to do higher mathematics, having a good sense of your multiplication tables is what are the things that you need to have before you get there. And, you know, because that's actually been an interesting question, kind of, I think, my whole professional life was, is is there any is there any argument ever for making people memorize things? You know? Because we've got so many technology based resources for accessing information, and speed of access is definitely variable. Like, how quickly do you need to be able to use the information?

[00:26:42] - [Speaker 1]
You know, how easy is it to look it up? How easy is it to to access it? You know, those kinds of things. And and kind of being on the right side of the balance for that. But you need people to have the foundational knowledge to sort of do the remixing at the higher orders, right?

[00:27:01] - [Speaker 1]
So if you don't know lots of the foundational pieces, you can't necessarily come up with complex solutions to a problem or, you know, manage all the variables that are kind of coming at you. And, you know, so what does that all need to look like? And, you know, I was talking to a group yesterday where it was mostly instructional designers for higher education, and I'm like, I'm grateful not to be in their shoes right now because they're enormously, you know, faced like, they have the enormous issue that they're facing of how do you construct assignments where it's not, you know, it's not the easiest answer is to just feed it into ChatGPT and, you know, trot the results out. Like, you know, we know that there's a there's a great little talk by Rory Sutherland, who does a lot on, like, creativity and kind of behavioral science. He's an advertising guy.

[00:27:51] - [Speaker 1]
But he talks about, like, having good student essays as a product was never the point. The point was always nobody wants your student essays. Like, it was never about the product. It was always about the process. And so having we've created a whole system where grades are the ultimate output, and of course, students wanna take the fastest way to getting the grade.

[00:28:19] - [Speaker 1]
Yeah. You know? And so one of the things we're we're dealing with here is really having to reassess the entire way that we motivate student performance to getting them engaged with, hey, if the learning isn't kind of hard and I'm not even gonna wrangle with difficult things, I'm developing the mental kind of capacity to manage difficult stuff in the world. And yes, I'm going to have AI as a tool later to shortcut some of this stuff. But again, the whole issue of we need you to be able to make judgments about the output since we need you to have the skill set to do that, and you know, I mean, I think some students get it and they're buying in, but I, you know, I was a procrastinated college student.

[00:29:14] - [Speaker 1]
Would I be tempted occasionally? Yeah, probably.

[00:29:16] - [Speaker 0]
You know, our world is designed and humans are designed to use the least amount of energy to get maximum impact, you're not going to be able to fight that. Like that is a losing proposition.

[00:29:28] - [Speaker 1]
Yeah.

[00:29:28] - [Speaker 0]
You know, it's interesting. I never thought like for multiplication, you're like, you know, memory versus learning. But as I kind of feel like memorizing your times tables is kind of like memorizing the alphabet. Like it is the fundamental of it, but then something you mentioned is that, you know, how do we measure the output? It's really interesting because I do wonder if, you know, like, gosh, I hate, I was terrible at memorizing probably because I was such a procrastinator and it's really hard to like memorize things once, you know, or at least it is for me.

[00:30:03] - [Speaker 0]
I'm sure that somebody could tell me otherwise, but I couldn't. And I think back, I'm like, I always thought that was such a cheap teacher that made so much focus on, can you memorize every country's name in Europe? You know, I was like, that is so cheap. Talk to me about the application of, you know, and so I do wonder if it actually forces a higher level of thinking, which is really what is in short supply, like critical thinking skills of being able to, to, to, you know, they say that the literacy rate of America, you know, people can read the article, they can understand it, but they can't tell you what the author is trying to convince you to do. You know, they're not, they're not able to understand what is behind the source of the person.

[00:30:53] - [Speaker 0]
And so that that's in short supply. Yes, we can read. Yes, we can answer a question on it, But can we think critically about why the article was written in the first place or what motive there might author might have? Or is this person trying to convince me something that they shouldn't be? Is this fact?

[00:31:11] - [Speaker 0]
Is this fiction? Our ability to determine that is getting worse. And so I wonder, you know, as a byproduct of, of, you know, AI making teachers lives hell, because I'm sure it is hell. There's no getting around it. I wonder if eventually the byproduct though, is that we, we get to this higher level of of thinking.

[00:31:32] - [Speaker 0]
This is

[00:31:33] - [Speaker 1]
It's an interesting question because, you you know, there's so many things that we learn as kind of patterns. Yeah. And we don't I don't know if we always give enough credit to those, you know, like factual information. I was I was reviewing a managerial it was a tool for training manager skills managerial skills the other day, and it had a bunch of questions in there where it was like the you know, it was it was factual information based on some content that had been there. So, you know, like Mhmm.

[00:32:03] - [Speaker 1]
People typically remember 15%, 20%, 25% of Right. Blah blah blah or something. And I was just like, who cares? This isn't the thing. You know?

[00:32:12] - [Speaker 1]
Like, how why are we asking this? Why are we asking people what the percentage is? Like, them to apply it. Ask them to think about how they're gonna use it. And so, you know, this is one of the kind of you know, to go back to kinda where we started on this stuff is like, how do you match up interventions to the need?

[00:32:27] - [Speaker 1]
And one of the big things that is always an issue is kind of moving people beyond those lower level, you know, Bloom's taxonomy, identify, define, describe, you know, kinds of learning objectives, because it's like, I don't care if you can list this thing. I care if you can use it to to do And a that is actually interesting in terms of things like memorization tasks and stuff. Like, whenever we would do because, like, I have a I have a gap model where I'm like, here, think about what the gap is between current performance and future performance, and it's an expansion of KSAs, so this has all been out there in the world. But, like, if it's a knowledge gap, they just need to know something in order to be able to do it. And when I say know something, what do you mean by that?

[00:33:07] - [Speaker 1]
Right? Like, is it know it conceptually or know it, like, I can I can summon it out of my mind at will if I need it? And it was always hard to find examples of something that's just a knowledge problem because most things aren't. Mhmm. But one of the ones we used a lot was, like, learning airport codes for customer service reps for, like, airlines or something.

[00:33:24] - [Speaker 1]
Yeah. You know, their conversation's gonna be easier if they don't have to look out stop and look up every airport code. But the truth is, like, we can do a little game to memorize airport codes, and that's fine. But honestly, a lot of it's gonna come from use. Right?

[00:33:37] - [Speaker 1]
Like, I know a lot of airport codes now, but those are just because I keep looking up. I have to go to Orlando a lot for conferences. Know the I know the airport code. Right?

[00:33:47] - [Speaker 0]
Do you know Spokane? Would give you $5 if you can guess. Okay.

[00:33:53] - [Speaker 1]
Yeah. It's

[00:33:53] - [Speaker 0]
G E G, which makes no sense in the world. The airport is not weird. They're weird how they come up with this. With the name of the airport. I I should look that up.

[00:34:03] - [Speaker 0]
But now that you said that, I should look that up. That's an

[00:34:04] - [Speaker 1]
interesting indigo. There's an explanation somewhere. It came from the name of something or whatever, usually. But it's Anyway But it's not a consistent method. Like, there's no consistent method for airfare codes.

[00:34:15] - [Speaker 1]
But, you know, like, yes, if I can create a game and you can memorize much of error codes, you'll probably function better. But honestly, you'll probably they won't really become automatic until you've been on the job for a while, you just have to keep using these over and over again. You know? So is is there value in the memorization? Probably.

[00:34:33] - [Speaker 1]
You know, is it better when you apply it? I was doing I was looking around I was doing a presentation on learning games, and I was looking around for some learning games, and I found this little map game where you could memorize all the countries in Africa. And I was like, well, now I immediately wanna memorize all the countries in Africa. And the truth is, like, I could get pretty good at it. Like, I wouldn't think I was ever a 100%, but I was in the nineties, I think.

[00:34:55] - [Speaker 0]
Oh, yeah.

[00:34:57] - [Speaker 1]
But, like, I lose almost all of them, you know, in between because I've gone back to it a couple times to pull the example and stuff like that. And the ones that I remember are the ones that are significant to me somehow. Right? Like, there's some reason there's something about the country, you know, like, oh, okay. You know, Ethiopia and Eritrea are near each other, and they've got kind of similar cultures, so that's gonna help me figure out which one's Ethiopian, which one's Eritrea.

[00:35:23] - [Speaker 1]
Or, you know, like I've been to Ghana and Nigeria, so I'm gonna remember those, you know, those kinds of things. And so it was learning stuff in a decontextualized way and memorizing things that way, not that helpful because you're gonna lose it. Right? It's it's almost always about learning it in context if you possibly can. So, yeah, sure, you know, like, the pure memorization tasks are worth it if we're trying to get somebody to 100%, and so we need to kind of over learn some of the less common ones or, you know, just as a foundation to get started with.

[00:35:53] - [Speaker 1]
But unless you're reinforcing it with, you know, something around why is this meaningful, why do I care, how am I going to use this, you know, this stuff's going to degrade pretty quickly, and we're going to forget about it. So information and knowledge is almost always better learned in context because it's got to be more meaningful and you're going to hang on to it longer. And so that's a piece of it too, right? Why do I care about this? How do I learn it in a way that is meaningful to me or gives me something to do with it?

[00:36:26] - [Speaker 1]
There's a guy who blogs a lot about math education that I really like, Dan Meyer. He's been writing a lot about AI, and he's finally backed off of it a little bit lately because I think he just was tired or needed to direct his attention elsewhere. But he was talking about the issue with the AI tutors, he's like, look, a lot of these technological solutions to help people learn about math are catering to a subset of the students who are good at being self directed learners.

[00:36:58] - [Speaker 0]
Yeah.

[00:36:58] - [Speaker 1]
You know, so when they look at things like Khan Academy, they look at it and they say, alright, this is a great tool, definitely. But when they try to measure the efficacy of Khan Academy, they have to throw out something like 95% of the logins and not collect data from it because those are people who haven't used it enough to actually have any measurable results from it. So 5% of the people who log in, and granted, I had a Khan Academy log in for a while just because I wanted to go look around, not because I was going to use it to learn algebra, so it's appropriate for them from a study point of view to throw away my data, but presumably some of those people who signed up meant to use it and didn't. And so when we look at, is this a good technology based tool for learning, what audience are we serving? Well, know, again, if it's a self motivated audience who's good at regulating their own learning, well, that's great, but that's plain on easy level, right?

[00:37:51] - [Speaker 1]
That's not addressing all the people who need more support than that.

[00:37:56] - [Speaker 0]
Yeah. And that's where I yeah, oddly enough, I have an anecdote on Eritrea and Ethiopia.

[00:38:04] - [Speaker 1]
Do you really?

[00:38:05] - [Speaker 0]
Okay. You will get, I don't know. Don't know if we have time. We got a little bit of time. So I'll tell you this just because you brought it up.

[00:38:12] - [Speaker 0]
I feel like I need to give you a cookie because you've learned this thing. So I had this Uber driver on the way to Sea Tac Seattle, Seattle's airport, and he's from Eritrea. And this I have never met a more proud person of his country than this And he's talking about how they won their independence and blah, blah, blah. And he's also kind of at the same time, like bad mouthing in Ethiopia. He's like, you know, like we won our independence from them.

[00:38:41] - [Speaker 0]
Like, he's like these people, you know, they think that we're just like a city within there because so many people just think that, but we're our own country, we're our own thing. And I'm like, oh yeah, really interesting. And just so passionate. My next driver coming home was from Ethiopia. I'm asking him and I'm like, tell me, Oh, and he, so he's and he couldn't really care.

[00:39:05] - [Speaker 0]
He's like, Oh yeah, I'm from Ethiopia. It's okay. Whatever. And I'm like, you know, what's so fascinating. My last driver was from Eritrea.

[00:39:12] - [Speaker 0]
He goes, that's not a country. That's just like a city of art. So anyway, mean, to me that really interesting, that taught me tremendous perspective actually of like, you know, where you sit and, like, you know, like the golden rule. He who has the gold has the you know, makes the rule kind of sometimes. Yeah.

[00:39:34] - [Speaker 0]
Right? And and, like, the lion doesn't concern themselves with zebras. So, you know, it really helped me put a little

[00:39:39] - [Speaker 1]
bit of Yeah. But now if you were if you were playing the map game to learn all the countries of Africa, you would have a very different you know, like, would have

[00:39:46] - [Speaker 0]
you would have know where they relationships

[00:39:48] - [Speaker 1]
with I had

[00:39:49] - [Speaker 0]
to look it up, and I looked And it and so but but speaking of that, so kind of coming all the way back, right? So afterwards I actually went and learned a little bit more about both these countries because it was so fascinating. They learned where they were because I was like, how close are they? What is their significance of where they're positioned? And you just brought up, you know, we threw out all these other things because that, I mean, they're logged in once, but, but it requires somebody who is self directed.

[00:40:15] - [Speaker 0]
And I think that's actually one of the big things that, that is the one of the tides that can raise all boats, especially now with so much information and with the ability of being able to pull an answer from a Gen AI agent is this idea of curiosity. And the more curious you can come, the more curious you can kind of leave people and even in your education, while you're educating people, if you can make them curious about why something is enough to care to go apply it or to go research or to go do whatever. I think that's a really big win. That's how I realized that I learned a lot about what I did with AI is because when I got a wrong answer and I was at, you know, I knew enough about the field to know what was wrong. I asked, well, why did you do that?

[00:41:03] - [Speaker 0]
And what's fascinating is AI will tell you, like, tells you what it was thinking, which is really an interesting way to get a peek into its brain or whatever brain, whatever computing power. But if you can remain like curious, and so I think that's a big component, especially will be an even larger component of how we how we engage people and like, you know, want to learn more because they need to care enough to go do learning. I know you write a lot about, forget what you title it, but I was reading some of your stuff and you were talking about like, how do we get people to care about care enough to learn? And I think at the high level, it's like that curiosity almost.

[00:41:44] - [Speaker 1]
Yeah, when we talk about, you know, a lot of times what I'm doing behavior change workshops and stuff, people will be like, we want our learners to be more self directed. And I mean, we do. We want them to be like, oh, here are resources. I will go look this up, you know, but this is not a simple equation, right? Like, it's got to be useful enough to them.

[00:42:02] - [Speaker 1]
They have to see the utility of it enough, you know, to do it. And so sometimes they've got a specific problem they're trying to solve, and so what's the easiest way to solve this problem? Was it asking the person sitting next to me? Which is less available now that so many people are working remotely, but is it doing a quick Google? Is it asking ChatGPT?

[00:42:22] - [Speaker 1]
Or is it looking up in the resource base that we spend a lot of money setting up and has answers that we think are right for our organization and things like that? Well, if you want people to do that, you have to kind of build that habit in them. They have to have experience of going there and finding useful information. They have to have an easy to navigate, you know, like, they have to know that they'll find it fairly quickly and that it might be faster than some of these other options, you know, some things like that. And so, you know, to go back to, you know, the sort of the gaps piece, which is I still think where we started on all of this was, is it a knowledge gap?

[00:42:57] - [Speaker 1]
Is it a skills gap, which means it's something that people need to practice and maybe see a lot of case examples to start to get good at, some of those more intangible or tacit skills? Is it habit gap, which is, you know, like, I can have very good intentions about a behavior, like, I really should floss every day or I should wear sunscreen. And it's just not a habit. Like that you can know what to do, you can want to do it, you can have the ability to do it. And it can still not be happening because it just isn't a habit that's built into your routine.

[00:43:27] - [Speaker 1]
And there aren't as many strategies as I would like, but there are strategies to help people with that, and we can build that into our curriculum. You know, how do we help people foster habits? You know, there's action planning, there's cue identification, there's practicing, you know, there's a number of things we can do around that. Is it a motivation issue where they know what to do but they still aren't doing it? In which case, we go down a whole other rabbit hole of identifying what the issues are there.

[00:43:54] - [Speaker 1]
And that's where a lot of the behavioral science stuff can come in and be informative, because when you really start kind of scratching the surface and scratching the surface, you find that, you know, your assumptions about why people are not doing a particular behavior may be completely wrong. Know, I the was last case study in the Talk to the Elephant book, which is the one about designing for behavior change, came from somebody named Manja Dodson, who was working with Japigo, one of the NGOs, and they were trying to figure out how do we get more men in Nigeria to get HIV screened. Right? And there were a lot of assumptions about what it was, right? Like they couldn't be bothered or they weren't interested or you know?

[00:44:35] - [Speaker 1]
And when they looked at motivators, they were like, well, are they gonna be motivated by messages about being, you know, a strong man protects his partner, kind of, you know, all of these sorts of things. And they did this WhatsApp group where they really spent a lot of time talking to people about it, and they had a real kind of along the way where what what they found was that getting HIV screened, you know, that that may have been one of the real issues is getting HIV screened is scary because your whole life's going to change if you get a if you get a bad result And these are people who grew up in the age of AIDS where it meant you were gonna die, probably. And that's not true anymore because of the way the medications is necessarily true anymore because of the medications. But it was still a really scary thing to have to face up to. And the belief was your whole life's going to change.

[00:45:26] - [Speaker 1]
You're not going to be able to, you know, date the way that you want to, or you're not going to be able to like drink as much because you gotta be healthy and you're not going to be able to have fun and you're not going to be, you know, like and so what they found was a far more effective set of messages where, hey, the meds are really effective right now. It's one pill a day. It doesn't have to change your whole life. You're still going to be worthy of love. Somebody's still gonna wanna be with you.

[00:45:48] - [Speaker 1]
You know, all of these kinds of things, like, let's try to diffuse. And you don't have to commit right away, but maybe, hey, start the conversation with us, and you can decide down the road if you really wanna get tested, but we're here to help you, and you're the they had this whole thing about how you're the VIP, and we're here to be you know? Mhmm. We're here to help you with stuff and, you know, things like that. And this shift in the messaging away from let's try to almost guilt you into getting tested, you know, versus let's make this less scary and let's

[00:46:17] - [Speaker 0]
And this make is like, yeah, this has been proven so many times. I think it started like, I don't know, like in the eighties when they realized that lung cancer was becoming, well, they didn't realize lung cancer was on the rise and they found the people least likely to get screened for lung cancer are people that smoked. Yeah. Because they were like, they knew they they're like, I know I've got it. Like what's even bothering me?

[00:46:45] - [Speaker 0]
If I find out I have it, what am I going to like? I'm going to have to lay in a bed and get chemo every day of my life. Like, I'd rather just keep smoking and not know. So that fear

[00:46:57] - [Speaker 1]
of

[00:46:59] - [Speaker 0]
almost the unknown, the people that need to know the most sometimes are afraid to do it.

[00:47:07] - [Speaker 1]
Right. Well, and just the fact that, you know, we make all these assumptions about people. If I, you know, if I had $100 for every time somebody told me that people in their target audience are lazy, I was just like, really? How to hire all the lazy people? That's a good trick.

[00:47:23] - [Speaker 1]
Maybe your hiring practices need some work. Everybody I know is so busy they can't see straight. Like, I don't know that many lazy people. I mean, I'm sure they exist. I'm sure they're out there.

[00:47:32] - [Speaker 1]
You know, like, who who how did you you know, and and the truth is they're probably not lazy. They probably just have better things to do because everybody's got 37 things they're doing with every minute of every day, and we're trying to motivate them to take their compliance training. Well, you know, there's a reason why that's not that compelling. Come on.

[00:47:50] - [Speaker 0]
Yeah. You know? Yeah. I mean, I I I feel bad when I take, so I do the podcast from my house and then I have an office that I can go into as well. And when I'm at my house, I almost feel like when I go down and like talk to my wife or take a little bit of time, man, I'm really like wasting time, you know, versus like, if I was in and off when I'm in my office, I waste tons of time.

[00:48:15] - [Speaker 0]
I always I didn't want to tell you how much time I waste just walking the hall. I was in her office in India last week. I just spent half the time, you know, wasting time. You know, it was not wasting, but it was just like, hey, what's going on or whatever? And so, yeah, you're right.

[00:48:29] - [Speaker 0]
I don't think there's that many, like, just straight up lazy people.

[00:48:34] - [Speaker 1]
Well, and I mean, you know, we hear it from both sides. Right? Like, we're not supposed to be optimizing, increasing efficiency, and all these kinds of things. And it's like, well, in those environments where we push so hard on efficiency, we know bad things happen. Right?

[00:48:47] - [Speaker 1]
Like Yeah. You know, the the Wells Fargo example was always the misaligned incentives where we push so hard on, you know, cross selling target goals that people met them the only way they could figure out how, which was to sign people up for things without telling them. And, hey. Guess what? That's illegal.

[00:49:02] - [Speaker 1]
It was a real problem.

[00:49:03] - [Speaker 0]
For those that don't know, Wells Fargo, especially their bankers, were incentivized to open up accounts like checking accounts. If you had a checking account, open a savings account, like vice versa, open up an account for your mom. And so people would just these tellers and other people were creating accounts, as you said, without even informing the customer, just saying, Oh, they'll never know. Don't put any money in there. Boom, boom, boom.

[00:49:26] - [Speaker 0]
Come to find out, Oh, I've got an account or creating fraudulent accounts. Gosh, that's crazy. That was, don't know how long ago it was, but I

[00:49:34] - [Speaker 1]
didn't Yeah, even it know long ago

[00:49:36] - [Speaker 0]
was. It was so many years. That's why I was like, was I had a buddy who worked for Wells Fargo, which is what made and he called me to open an account at one point and I didn't. Well, maybe I did. Who

[00:49:46] - [Speaker 1]
knows? But,

[00:49:49] - [Speaker 0]
you know, we didn't get to cover one of the things we want to talk about, which was, you know, how do we reduce cognitive load? But I think we covered so many more fascinating things that I hope people forgive us and maybe we'll have you on. Definitely had to have you on whenever, you know, I know. What is the how long is the process from starting to write a book to it actually coming out? I know nothing about this.

[00:50:09] - [Speaker 1]
My publisher, you know, assuming like I haven't submitted the proposal yet, so this is all hypothetical at this point, but but they're actually pretty quick. So with the Elfa book, I dropped that in I I started writing it in in January 2020 is it 2023? I guess. Yeah. Can't remember anything anymore.

[00:50:30] - [Speaker 1]
And I turned in my manuscript in, like, my final manuscript in May, and it was out by, like, August, but they're fast.

[00:50:39] - [Speaker 0]
Okay. Well, when that when you get published, when the next one comes out, we'd love to have you on give away some books to some listeners. So let's have you back and we can finally I know everyone's saying, why didn't you get to the cognitive load? Maybe we can talk about.

[00:50:54] - [Speaker 1]
Yeah. No. We can totally talk about cognitive load. Just let me know. I'm happy to talk about that.

[00:50:58] - [Speaker 1]
That's a great topic.

[00:50:59] - [Speaker 0]
I'm I'm I'm sure my Eritrea story was much more important than

[00:51:05] - [Speaker 1]
We can we can we can do some super inside baseball about how John Swellers dropped chair main cognitive load from the the model and stuff like that. So if you really wanna get into the

[00:51:15] - [Speaker 0]
nerdy the nerdy

[00:51:16] - [Speaker 1]
deep dive. But

[00:51:18] - [Speaker 0]
Well, we we can save that for a different time. But thank you so much for joining. This was a great session, Julie. Really appreciate it. We'll definitely have you on soon again.

[00:51:27] - [Speaker 1]
All right. Fantastic.

[00:51:28] - [Speaker 0]
All right. Thank you.