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Clark Quinn’s Learnings about Learning

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From platitudes to pragmatics

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It’s easy to talk principle. (And I do. ;) Yet, there are pragmatics we have to deal with, as well. For instance, with ‘clients’ (internal or external), giving us their desired outcomes that are vague and unfocused. We generally don’t want to educate them about our business, yet we need more focused guidance. Particularly when it comes to designing meaningful practice. How, then, do we get from platitudes to pragmatics?

To be clear, what’s driving this is trying to create practice that will lead to actual outcomes. That’s, first, because our practice is the most tangible manifestation of the performance objectives.  Also, because it is also the biggest contributor to learning actually having an impact! We need good objectives to know what we’re targeting and then the next thing we need to do is design the practice. After we design practice, we can develop the associated content, etc. How do we get this focus?

I see several ways. Ideally, we can engage with clients in a productive conversation. We can do the advocated ‘yes and…’ approach, where we turn the conversation to the outcomes they’re looking for, and ideally even to metrics. E.g. “how will we know when we’ve succeeded?” When we hear “our sales cycle takes too long” or “our closure rate isn’t good enough” if the topic is sale, there’re metrics there. If we hear “too many errors in manufacturing” or “customer service ratings aren’t high enough”, that’s quantifiable, and we have a target.

There are other situations, however. We might not get metrics, so then we might have to infer them from the performance outcomes.  When we hear “we need sales training” or “we need to review the manufacturing process” or “we need a refresher on customer service”, it’s a bit vaguer.  We should try and dig in (“what part of sales isn’t up to scratch” or “what are customers complaining about”), but we may not always have the opportunity. Still, we can make practice assignments around these. We can provide practice around the specific associated tasks.

What really is the biggest problem is ‘awareness’ courses. “I just want folks to know this.” (Which begs the question: why?) I fear that part of the answer is a legacy belief that we’re formal logical reasoning beings and so new information will change our behavior. (NOT!) It can also be because the client just doesn’t know any better, nor have any greater insight than “if they know it, it is good”. However, I still think there’s something we can do here. Even if it’s a case of ‘easier to get forgiveness than permission’.

I think we can infer what people would do with the information. If they insist we need to be aware of harassment, or diversity, or… we can ask ourselves “what would folks do differently?” One decision is to intervene, or report, or ignore. Another might be where and how to do those things. In general, even though the requester isn’t aware, there’s something they actually expect people to do. We have to infer what that can be. Then, they can critique, but it’s more effective for the organization  and more engaging for the learner. That, to me, is a reasonable justification!

Whether it’s mapped to multiple choice questions (see Patti Shank’s seminal book on the topic), scenarios (Christy Tucker is one of our gurus), or full games (I have my own book on that ;), we need to give learners practice in dealing with the situations that use the information. I think we can work from platitudes to pragmatics, and should. What do you think?

Two steps for L&D

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In a conversation, we were discussing how L&D fares. Badly, of course, but we were looking at why. One of the problems is that L&D folks don’t have credibility. Another was that they don’t measure. I didn’t raise it in the conversation, but it’s come up before that they’re also not being strategic. That came up in another conversation. Overall, there are two steps for L&D to really make an impact on.

Now, I joke that L&D isn’t doing well what it’s supposed to be doing, and isn’t doing enough. My first complaint is that we’re not doing a good job. In the second conversation, up-skilling came up as an important trend. My take is that it’s all well and good to want to do it, but if you really want persistent new skill development, you have to do it right! That is, shooting for retention and transfer. Which will be, by the way, the topic of my presentation at DevLearn this year, I’ve just found out. Also the topic of the Missing LXD workshop (coming in Asia Pacific times this July/Aug), in linking that learning science grounding to engagement as well.

I’ve argued that the most important thing L&D can do is start measuring, because it will point out what works (and doesn’t). That’s a barrier that came up in the first conversation; how do we move people forward in their measurements. We were talking about little steps; if they’re doing learner surveys (c.f. Thalheimer), let’s encourage them to move to survey some time after. If they’re doing that, let’s also have them ask supervisors. Etc.

So, this is a necessary step. It’s not enough, of course. You might throw courses at things where they don’t make sense, e.g. where performance support would work better. Measurement should tell you that, in that a course isn’t working, but it won’t necessarily point you directly to performance support. Still, measurement is a step along the way. There’s another step, however.

The second thing I argue we should do is start looking at going beyond courses. Not just performance support, but here I’m talking about informal and social learning, e.g. innovation. There are both principled and practical reasons for this. The principled reason is that innovation is learning; you don’t know the answer when you start. Thus, knowing how learning works provides a good basis for assisting here. The practical reason is it gives a way for L&D to contribute to the most important part of organizational success. Instead of being an appendage that can be cut when times are tough, L&D can be facilitating the survival and thrival strategies that will keep the organization agile.

Of course, we’re running a workshop on this as well. I’m not touting it because it’s on offer, I’m behind it because it’s something I’ve organized specifically because it’s so important! We’ll cover the gamut, from individual learning skills, to team, and organizational success. We’ll also cover strategy. Importantly, we have some of the best people in the world to assist! I’ve managed to convince  Harold Jarche, Emma Weber, Kat Koppett, and Mark Britz (each of which alone would be worth the price of entry!), on top of myself and Matt Richter. Because it’s the Learning Development Accelerator, it will be evidence-based. It’ll also be interactive, and practically focused.

Look, there are lots of things you can do. There are some things you should do. There are two steps for L&D to do, and you have the opportunity to get on top of each. You can do it any way you want, of course, but please, please start making these moves!

The Role of a Storyboard?

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In a recent conversation, the issue of storyboards came up. It was in the larger context of representations for content development. In particular, for communicating with stakeholders (read: clients ;). The concern was how do you communicate the content versus representing the experience. So, the open question is what is the role of a storyboard?

So, there are (at least) several elements that are important in creating a learning experience. One is, of course, the domain. What are the performance objectives? Moreover, how are you providing content support. Specifically, what models are you using, and what examples. Then, of course, there’s the practice. Ideally, practice aligns with the performance objectives, and the models and examples support the practice.

There’s also the experience flow. How are you hooking learners up front? We are concerned with balancing the quantity of content with the actual practice, keeping engagement throughout.

In both cases, we need to communicate these to the clients. Too often, of course, clients raise concerns about making sure ‘the content’ is covered. In many cases, they really don’t understand that less is better, and have a large amount they’ve heard from subject matter experts (SMEs). Not knowing, of course, that SMEs have access to what they know about the domain, but less about what they do! Thus, they’re looking to make sure the content’s covered.

There will also be concern about the experience. This, likely not ideally, comes after assurance about the content. I personally have experienced situations where stakeholders say ‘ok’ to a storyboard, but then balk at the resulting experience. Some (surprisingly high) proportion of folks can’t infer an experience from a storyboard.  This has been echoed by others.

The question is what is the role of a storyboard. In game design, there is a (dynamic) design document that captures everything as it develops. Is this the right representation to communicate the experience? It  communicates to developers, but is it good for clients? I argue that we want more iterative representations, for instance getting sign-off on what we’ve heard from the analysis and documenting what will be the focus of the design. We also want to separate out the domain from the experience.

Overall, I advocate representing the experience, for instance in (mocked up) screenshots with narration to represent a sample interaction. That can accompany the storyboard, but when folks have to sign-off on an experience, and they can’t get it from the usual representations, you’ll need an augment. I wonder whether we should fight against presenting the content that’ll be covered.

We should show the objectives, models, and examples, but fight against content ‘coverage’. Cathy Moore does a good job in her ‘Action Mapping’ to argue that what the minimum is to achieve success on appropriate performance tasks is a good goal. I agree, as does learning science. The role of a storyboard is to capture development for developers. It may not be the right communication tool for stakeholders. I welcome your thoughts.

Curriculimb

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Ok, so I’m going to go out on a limb here, and talk a wee bit about what I’ve been learning about designing curricula. I care about doing it right (and probably haven’t always). It’s not the average course that’s the issue, but big ones, or multiple courses addressing skill gaps. It’s been challenging to find a systematic approach, which is why I’m teetering on a curriculimb.

So, the issue is how to develop a curriculum. I know in higher ed (I was there once) it tends to be a process of figuring out what content they need, and distributing across courses. It’s probably more art than science, where you move stuff around until it feels like you’ve got the right sized amount of content for each subject and it covers the ‘right stuff’. How people meet the criteria can vary. In a more research institution, I could design my HCI course my way. In more teaching-focused institutions, people may actually be given course syllabi to teach to!

My problem is when I have an uncertain amount of content, say for a large domain, and I want to develop specific capabilities. On principle, we should work backwards from the final performance. Which might include some very rich types of capabilities, so we might have a lot of concepts and practice involved. We’d need to create a large map. We might even break it up into conceptual stages (e.g. with programming: learning conditionals and then loops), and addressing them separately.

You probably also need to provide some practice to deal with misconceptions. That is, where are folks likely to get off track and maybe discouraged? Then you want to create practice for that. The things you’d rather they learned before it matters.

When I looked for good principles around this, it seemed like most of what I found basically said it’s iterative, there are no overarching principles (except work backwards and iterate ;). Which was less than satisfying, and some evidence-based practice would be nice.

Now, one of the things I was pondering in the dark of the night was how AI could help. I’ve been hearing how it can parse content and create maps. However, I also realized that to do so, it needs well-structured content. Kind of a circular argument. I think we need people to define it then AI can align it.

Again, right now it seems more like an art than a science. And I get that; it’s a lot like designing in engagement: create a first best guess and then test. Still, there are some solid results in engagement that give us some grounds for the first pass. I feel less like that at the next level up. So, I’m out on a curriculimb, and welcome help getting down!

Attention is underrated

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Attention is a complex phenomena. Thinking that we can simply address is probably naive. Worse, there is at least one pervasive myth about it. Trivial attention is probably overrated, but meaningful attention is underrated.

Attention, I’ll suggest, is how we pay conscious awareness to our thinking. We pay attention to the sensory stream that’s available, and as working memory is has limits, our attention chooses what ends up being in working memory (which is where we see conscious thought). This is the picture I paint in Learning Science for Instructional Designers,  my recent book on how we learn. That’s how I learned it in grad school, and little seemed to change that.

As an aside, I suggest that the basic human information processing loop is something that is critical to understand. This is true for learning designers, but I would suggest there’s broader applicability. Knowing how information flows:

  • from sensory store to working memory via attention
  • from working memory to long term memory via elaboration
  • back to working memory via retrieval
  • and to decision from working memory

as a simplified story, shows how humans work in many ways. It gets more complex in important ways, but this is a key basis. On top of it comes aspects of how we think, and learn, but this is the core.  It benefits anyone dealing with people, basically: UI, marketing, etc. In short, most everyone.

Recent pictures of the information processing loop suggest, however, that attention has a bigger purview. They have it influencing most of the above. Which may be more accurate, in that if you need to attend to what’s in working memory, and manage the process of attending to information while evaluating what decision to make. You must maintain conscious focus on what you want to learn.

The myth, which still persists, is that our attention span has dropped to 8 seconds. Which folks tout as less than that of a goldfish. (How do we know what the attention span of a goldfish is?) The origin of this myth came from StatBrain misinterpreting a study, and was amplified since it was published by Microsoft Canada.  Marketing, mind you, not their research group! A myth I busted in a previous book!

There is apparently some evidence that our attention span has dropped (to 4o-something seconds, not eight), but we can still disappear into movies, novels, and games for hours. I reckon it’s about how engaging it is. Which, not completely surprisingly, is the topic of my most recent book, Make It Meaningful.

So, please, avoid the myths, and learn the core. Attention is underrated, as is the whole human information processing loop. Learn it, and benefit.

Misleading Malarkey

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Recently, I saw a claim that was, well, a tad extreme. Worse, I think it was wrong, and possibly harmful. Thus, I feel it’s right to address it, to avoid misleading malarkey.

So, here’s the claim that riled me up:

Short-form edutainment is the most effective teaching method for both children and adults. TikTok and YouTube shorts will ultimately replace high schools and universities. Employment sector will phase out LMS systems and replaced with AI-powered compliance tools. If you are considering instructional design as a career, you may want to become a YouTuber or TikToker instead.

If you’ve tuned in at all, you’ll know that I’m a fan of engagement, properly construed.  Heck, it’s the topic of my most recent book! So, talking about the value of engagement in learning is all to the good. However…

…this claim goes over the top. Most notably, there’s the claim that edutainment is the most effective teaching method. If only! That puts me off, because teaching should yield a learning outcome, and just watching video shorts won’t do that (under most circumstances). Not surprisingly, I asked for research.

The author pointed to a study where mice genetically low on dopamine learned better when given dopamine. Yes, but the study had the mice do more than just watch videos, they performed tasks! I tried to go deeper, saying that engagement may be desirable, but it’s not sufficient. Without practice, watching entertaining and informative material (e.g. edutainment) isn’t a path to learning outcomes.

The conversation was derailed by my comment that edutainment had gotten a bad name from games. In the 80s, in an industry I was in, this was the case! I was accused of having a ‘gamification’ mindset! (Ahem.)  I tried steering the conversation back to the point it’s not about gamification, it’s about engagement combined with practice.

Interestingly, there was an almost parallel conversation about how engagement wasn’t the same as learning (which I pointed to in the exchange). The general take is that engagement is desirable but insufficient. Yes! Yet here we see the claim that engagement is all we need!

I believe in engagement for learning. I just don’t believe that by itself it will lead to learning. Learning science supports both the value of engagement, and the necessity of practice and feedback. That’s all. But claims like the above are misleading malarkey. It may be we’re talking an outrageous marketing claim (infamy is better than not being known at all?), but when it misleads, it’s a problem. Am I missing something?

Missing LXD Workshop

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We interrupt your regularly scheduled reading for this commercial announcement:

What is Learning Experience Design (LXD)? Further, why should you care? Finally, (and arguably most important) what does it mean you should do differently? Those, to me, are important questions. My short answer is that LXD is the elegant integration of learning science and engagement. Which, to me, implies some important nuances on top of what’s traditionally done in instructional design (ID). How to address it? There’s actually quite a lot in LXD, but it’s also a lot of overlap with traditional ID practices and processes. I reckon the easiest (and best) way to address it is to talk about the delta. That is, what’s different between the two. So, in my role for Upside Learning, I developed a missing LXD workshop. We ran it internally to good outcomes, and now, you can take it!

I believe that the difference starts with objectives; you can’t make a meaningful experience if you don’t have learners acquiring relevant new skills (not just an information dump). From there, there are nuances on designing individual practice activities, and then aggregated into practices (that is, putting practices together). Moving on, we look at the content elements of models and examples, and then the emotional aspects of learning. The workshop closes by looking at a design process that accommodates these. Recognizing that folks don’t want to throw out their whole process to start anew, it works from a generic model.

In the workshop, I cover each of those topics in a week; so it’s a six week experience. In between, I ask attendees to do some interim processing to both cement their understanding and to change their practices. Each week we’ll cover underlying concepts, see examples of what we’re talking about, actively process the information, and do a major application task.

To make this available more broadly, Upside’s partnered with the Learning Development Accelerator (LDA) to deliver it. Full disclosure: I’m co-director of the LDA, and Chief Learning Strategist for Upside Learning (in addition to my ongoing role for Quinnovation). (So, it’s all about me! :) Seriously, I think this puts together the tools I believe are necessary to lift our industry.

To be clear, since the advance notice timeframe puts this in summer, we’re offering it in Asia time-frames first (tho’ anyone is welcome!):

Australian Eastern Standard Time: July 7, 14, 21, 28, August 4 and 11 from 12h00 to 14h00 each day
Singapore Time: July 7, 14, 21, 28, August 4 and 11 from 10h00 to 12h00 each day
India Standard Time: July 7, 14, 21, 28, August 4 and 11 from 07h30 to 09h30 each day
New York Time: July 6, 13, 20, 27, August 3 and 10 from 22h00 to 24h00 each day

We’re offering it for US$100 to LDA members, and US$350 to non-members (for only $40 more, you get the full LDA offerings as well).

We’re planning to offer the missing LXD workshop again at a later date at East Coast/Europe friendly times (probably at a steeper price, we’ll have worked the bugs out ;). You can find out more at the LDA site. It’s got learning science and engagement bundled up into a coherent whole, for those who’ve already been doing ID and want to lift their game. I hope you’ll find it worth your while.

We now return you to your regularly scheduled reading until next week at the usual time.

Comic openings

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Humor is important, we have to address this seriously!

Speaking of irreverent, I’ve argued, in the past, that we don’t use comics enough in learning. In general, I mean serious comics, graphic novel formats, to tell dramatic stories. However, we can use comics for humor, as well. In particular, to accomplish our motivation goals on opening. So here I ponder comic openings.

To start, as I mention in talking about making learning meaningful, I believe you need to open up people emotionally. Even before you open up cognitively! We know that activating relevant knowledge is important cognitively, but I suggest that it won’t stick as well unless you’ve piqued their awareness. I’m arguing that we need a visceral awareness that this is relevant.

It doesn’t take much, but I suggest it is worth doing. I like to use the consequences of having, or not, this ability is what’s key. There are things you can do that you couldn’t without it. Making that clear is, to me, a WIIFM (What’s In It For Me).

I believe you can do this dramatically or humorously. That is, you could make a dramatic story of saving someone because of the information you have, or the bad outcomes from not having it. Then there’s the alternative.

You can also have humorous aspects of having the info. For instance, saving the day not because the hero knows it, but the sidekick happens to, instead. However, my favorite approach is to humorously point out the consequences of not having the knowledge. (OK, admitting my predilection for sarcasm. ;) This can be done with just a simple comic! I’ve done so in content we developed for a client, and am doing so again in a demo we’re creating.

It might also set the tone for the learning. It can help learners relax, trust that the environment’s safe, reducing anxiety.

I suggest this is easy to create, easy to develop, quick, engaging for the learners, and effective. Now, I don’t have specific research on that (I’d love to: anyone got pointers or want to do the study?). However, I think it’s a plausible inference from what we do know from learning science.

I’ll also acknowledge that there are times this won’t be the best approach! Certain topics probably aren’t good candidates, similarly certain audiences might similarly not match. However, I do think it’s more broadly applicable than we think. Even for modules within an overall topic. If they’re inexpensive and high impact, use them liberally. So I’ll suggest we use comic openings liberally!

Process and Product

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Of late, I’ve been talking a fair bit about my take on learning experience design (LXD). To me, it’s the elegant integration of learning science with engagement. Of course, I’m biased, as my two most recent books are specifically to those ends! I don’t claim it’s automatic, but I do believe that with practice, it gets easier. You need to address both process and product, of course.

Our goals are, ultimately, to achieve learning outcomes, typically retention and transfer. That is, retaining skills over time ’til needed and transferring to all appropriate (and no inappropriate) situations. This requires, cognitively, sufficient practice and an appropriate spread of contexts. Emotionally, it requires an initial hook and then maintaining commitment through the experience via relevant activities.

I’ve been running a workshop with my partner, Upside Learning, on the ‘missing bits’. That is, the fine tuning that takes what you normally do in ID and fills in the extra steps that will successfully provide the integration. It’s been great for stress-testing the workshop (stay tuned!), and extremely insightful. I get to hear what these smart and experienced folks are realizing in their own practices, and what they’re struggling to change.  That’s my goal, of course: to help them bake learning science and engagement into their processes and products.

One of the concerns, not surprisingly, is that it takes more time. That includes upfront analysis (which clients can also resist). Then it requires a bit more thought on designing practice and winnowing content. Finally, it should be iterative. I’m not the only one focusing on the latter, of course. However, I argue that it ultimately really doesn’t take that much more time, but there will be a speed bump until the new way of thinking becomes automatic.

Still, it will require adjusting how we develop, to impact what we develop. Process and product are linked at the wrist and ankles. Understanding the underlying principles, the learning science and engagement integration, is a necessary foundation. That’s my take, I welcome yours.

I’ll be offering a free webinar with Training Magazine Network on the core principles of LXD on Wednesday March 22 at 9AM PT (noon ET). I note that if there’s a conflict, they’ll make the recording available afterwards if you register. I welcome seeing you there!

Vale Roger Schank

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I’d first heard of Roger Schank’s work as an AI ‘groupie’ during my college years. His contributions to cognitive science have been immense. He was a challenging personality and intellect, and yet he fought for the right things. He passed away yesterday, and he will be missed.

Roger’s work connected story to cognition. He first saw how we had expectations about events owing to his experience at a restaurant with an unusual approach. At Legal Seafoods (at the time) you paid before being served (more like fast food than a sit-down venue). Surprised, Roger realized that there must be cognitive structures for events that were similar to the proposed schemas for things. He investigated the phenomena computationally, advancing artificial intelligence and cognitive science. Roger subsequently applied his thinking to education, writing Engines for Education (amongst other works), while leading a variety of efforts in using technology to support learning. He also railed against AI hype, accurately of course. I was a fan.

I heard Roger speak at a Cog Sci conference I attended to present part of my dissertation research. The controversy around his presentation caused the guest speaker, Stephen Jay Gould, to comment “you guys are weird”! His reputation preceded him; I had one of his PhD graduates on a team and he told me Roger was deliberately tough on them, saying “if you can survive me, you can survive anyone”.

I subsequently met up with Roger at several EdTech events hither and yon. In each he was his fiery, uncompromising self. Yet, he was also right. He was a bit of a contradiction: opinionated and unabashed, but also generous and committed to meaningful change. He also was a prodigious intellect; if you were as smart as him, I guess you had a reason to be self-confident. I got to know him a bit personally at those events, and then when he engaged me for advice to his company. He occasionally would reach out for advice, and always offer the same.

He could be irritating in his deliberate lack of social graces, but he was willing to learn, and had a good heart. In return, I learned a lot from him, and use some of his examples in my presentations. It was an honor to have known him, and the world will be a little duller, and probably a little dumber, without him. Rest in peace.