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Clark Quinn’s Learnings about Learning

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Thinking Strategically

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Repurposed from another use.

In today‘s increasing rate of change and competition, coupled with growing ambiguity and uncertainty, L&D just can‘t be about delivering courses on demand. Optimal execution, the result of formal learning, is only the cost of entry, and continual innovation will be the necessary element for organizations to thrive. Organizations have to move faster, be more agile, and adapt more effectively.   And it‘s here that L&D has a true opportunity, and imperative, to contribute. It’s about thinking strategically.

That means, intrinsically, that L&D has to start thinking about how to move forward..   People are learning on their own more and more. The tools to access information are quite literally in the palm of their hands.   L&D can no longer be about controlling content.   Instead a new role is needed.

Rethinking Formal

How does L&D cope? The answer involves a couple of major shifts, from familiar to challenging. The first is that courses go from an event model to an approach that better reflects how we actually learn. We need to have spaced, distributed practice to truly master our skills.   This is harder than the ‘information dump and knowledge test‘ that too often characterizes organizational learning, which brings up two issues: 1) formal learning should be reserved for when it absolutely, positively has to be in the head, and 2) putting information in the world when possible.  

That latter is referring to performance support, the first step in broadening the L&D perspective. The point is that we too often use courses when cognitive skills are not the problem. Performance consulting is a process to identify the real problem and cause, and provide appropriate solutions. Performance support is often a solution we can use instead of a course!   Note that this is a first step out of the comfort zone, as it means engaging with our stakeholders, the business units we are tasked to assist. But it‘s past time!

Beyond Formal

Doing courses the right way, coupled with performance support, are the key to optimizing execution. But that‘s just the starting point.   The key to organizational improvement will be the ability to learn. And that should be L&D‘s role.   But this means we have to again step out of our comfort zone.  

We need to branch out into informal and social learning.   Employees do learn on their own, but the evidence suggests that they‘re not particularly good at it. There are lots of folk stories about what works that just aren‘t aligned with what science tells us!   Assisting the individuals and the organization to learn, independently and collectively, is the new opportunity. Assisting the organization to innovate means moving to the core of competitive advantage. And that‘s a valuable place to be.

Wishful thinking isn’t the answer. It takes both knowing the bigger picture, the performance ecosystem, and working strategically to get from here to there. That‘s what‘s on the table. It might be scary, but the opportunity offers a brighter future for L&D.   I‘m excited about the prospects, and hope you’ll be making the move.  I’d welcome the opportunity to assist, as well.

Editing, process, topics, and other reflections

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My lass let me know there was a typo in my recent post on Transformation.  I’m thrilled that she’s reading them (!), but she triggered many thoughts about my writing approach. I thought I’d share how I deal with blogging, articles, and writing in general, as a ‘show your work‘ effort. And, in a sense, solicit your thoughts on approach, editing, and topics (amongst other things).

Process

It starts with my commitment to two blog posts a week. And I’m pretty sure I average that, since while I occasionally only get one, I also occasionally get three (say, during a week at a conference with mindmaps).  That means, however, that sometimes I’m brimming with ideas and have them queued up a week or two in advance, and sometimes I’m writing them at the last minute (*cough* this one *cough*).  When I know I’ll be on the road on a particular week, I definitely try to have them in the hopper in advance.

Regardless, I tend to write each in one fell swoop. Something sparks a thought, and I rush to get it down. Sometimes I’ll have an idea elsewhere, and jot myself a one line reminder, and need to generate the full prose. But my writing’s often like that: once I’m going, I have to let that full idea gestate. Even when writing a full book (as I’ve done a time or two ;), I outline it in a go, and then write sections in a burst.

Now, I write in several channels: my blog, my committed articles, and of course books. And, not surprisingly, I write them differently.  The blog comes out ‘as is’. I do reread it after it’s first done, typically, but as my lass discovered, it can have flaws. I reread my Trends article after posting, for instance, and noticed a couple of flaws. (I’ve fixed them, of course, similarly when folks comment in one way or another about something I’ve left confusing or wrong.)

My articles are different. I write them typically in one go, but I always hang on to them for at least a day, and reread with fresh eyes. I think that’s obligatory for such efforts. In one case, I have an editor who reads them with a careful eye, and always sends back a revised version. I don’t get to  see the revisions (which is frustrating), but the articles are always improved. Editing is valuable!

For books, as I mentioned, I outline it, then write sections. And, depending on the book, the experience changes. With  Engaging Learning, it had been percolating for so long it kind of flew out of my fingers onto the page.  For  Designing mLearning, it was different; I outlined, and wrote, and as I got further in I found myself rearranging the structure and going back to add things.  The Revolutionize L&D book was closer to the Designing mLearning book, with two changes. I didn’t reorganize as much, but I kept going back and adding stuff. It was hard to finish!

With my books, I’ve always had an editor. The ones from the publisher varied in quality (good experiences generally), but I also have m’lady serve as my first (and best) editor. And I’ve learned to truly value an editor. The benefit of a second eye without the assumptions and blinders the writer brings is great!

Topics

The ideas come differently as well. My blog tends to get whatever I’m thinking about (like this). My articles tend to be a deeper dive into whatever I think (or we agree, with my editor) is important. I keep a list of potential topics for each, and take whatever feels ‘right’ for the month.

Books, of course, are a bigger story. For one, you need a publisher’s agreement (unless you self-publish). My first book was based upon my research for years on games and engagement. The mLearning books were publisher requests, and yet I had to believe I could do a proper job. Revolutionize emerged from my work with people and orgs and looking at the industry as a whole, and was something I think needed to be said. My latest, on myths, was also requested, but also something I felt comfortable doing (and needed to be done).

(Interestingly, on the requested books, I first checked to see if someone else might write it instead, but when the obvious candidates declined, I was happy to step up. I got their voices in anyway. ;)

The hard part, sometimes, is coming up with topics. The commitment to two posts a week is a great catalyst for thinking, but sometimes I feel bereft. I welcome suggestions for topics for any of the above as well. Someone asked what my next book would be, and I asked them what they thought it should be.  However, I’m not ready to write a memoir yet; I’m not done!  Thoughts solicited on any or all of the above.

Transformation!

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butterfly cocoonI’m a fan of the notion of ‘learning experience design’ (not so sure about  platforms;  I need to investigate them more ;).  The idea of integrating effective education and engaging experiences is something I’ve been  on about for a  very long time. And I want to push it a little further. I want to talk about transformation.

What am I talking about? So, I’ve previously referred to Pine & Gilmore’s concept of the Transformation Economy. That is, going beyond experiences (e.g. themed restaurants) to ones that change us. And I argue that’s what we do; we create (or should) experiences that give us new skills, new abilities to  do.  But I want to push it further.

Here I’m talking about deliberately using the idea of transformation as a learning design goal. Not just change, but leveraging the emotions as well as cognition to have the learner not just feel empowered, but transformed!  This may sound like a lofty goal, fine for a TED Talk (just read the book; recommended), but is it practical for elearning?  Well, that’s an interesting question.

Let me spin it another way: I do  not think we should be shooting for an information dump and knowledge test. For two reasons: one is that it’s not inspiring. More importantly, however, it also isn’t effective. You end up with what cognitive scientists call ‘inert knowledge’. You’ll learn it and pass a test on it, but when it’s relevant in practice it won’t even get activated!  Because you’ve never used it in ways like you practice.

I think if we are actively thinking about transformation as a goal, we might do a better job of thinking about the necessary practice and the emotional engagement.  We can focus on thinking “what will lead to the transformation we want”, and “how do we make people want it and celebrate when they’ve made the breakthrough?”  And I think this is a useful perspective.

Even for things like compliance, I’d suggest that we should be having visceral reactions like “Ok, I get it <bad behavior> is pretty heinous”, and “safety  is important, and I commit to following these rules”.  For more important things, you’d like them to feel “yes, I see, this will change how I  do this!”

Yes, it’s ambitious. But why set ourselves limited goals? When I was teaching interface design, I maintained that if I accommodated the engineers lack of background in Psych, I’d get them only so far. If I pushed them, they’d end up farther than if I was conciliatory. Similarly, here, I think we’ll do a better job if we think ‘ambitious’, and end up not as far as we’d like. I’ll suggest that’s better than satisfactorily achieving mediocrity. Most importantly, I truly think we’ll do a better job of design if we strive for transformation.

And, if there’s nothing transformative about what we’re covering, should we really be using our resources?  Let me put it another way: why  shouldn’t we do this? Seriously, I’m asking.  So, what’s your answer?

 

Making Multiple Choice work

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For sins in my past, I’ve been thinking about assessments a bit lately. And one of the biggest problems comes from trying to find solutions that are meaningful yet easy to implement. You can ask learners  to  develop meaningful artifacts, but getting them assessed at scale is problematic. Mostly, auto-marked stuff is used to do trivial knowledge checks. Can we do better.

To be fair, there are more and more approaches (largely machine-learning powered), that can do a good job of assessing complex artifacts, e.g. writing. If you can create good examples, they can do a decent job of learning to evaluate how well a learner has approximated it. However, those tools aren’t ubiquitous. What is are the typical variations on multiple choice: drag and drop, image clicks, etc. The question is, can we use these to do good things?

I want to say yes. But you have to be thinking in a different way than typical. You can’t be thinking about testing knowledge recognition. That’s not as useful a task as knowledge retrieval. You don’t want learners to just have to discriminate a term, you want them to  use the knowledge to do something. How do we do that?

In  Engaging Learning, amongst other things I talked about ‘mini-scenarios’. These include a story setting and a required decision, but they’re singular, e.g. they don’t get tied to subsequent decisions. And this is just a better form of multiple choice!

So, for example, instead of asking whether an examination requires an initial screening, you might put the learner in the role of someone performing an examination, and have alternative choices of action like beginning the examination, conducting an initial screening, or reviewing case history. The point is that the learner is making choices  like the ones they’ll be making in real practice!

Note that the alternatives aren’t random; but instead represent ways in which learners reliably go wrong. You want to trap those mistakes in the learning situation, and address them  before they matter!  Thus, you’re not recognizing whether it’s right or not, you’re using that information to discriminate between actions that you’d take.  It may be a slight revision, but it’s important.

Further, you have the consequences of the choice play out: “your examination results were skewed because…and this caused X”.  Then you can give the principled feedback (based upon the model).

There are, also, the known obvious things to do. That is, don’t have any ‘none of the above’ or ‘all of the above’. Don’t make the alternatives obviously wrong. And, as Donald Clark summarizes, have two alternatives, not three. But the important thing, to me, is to have different choices based upon using the information to make decisions, not just recognizing the information amongst distractors. And capturing misconceptions.

These can be linked into ‘linear’ scenarios (where the consequences make everything right so you can continue in a narratively coherent progression) or branching, where decisions take you to different new decisions dependent on your choice.  Linear and branching scenarios are powerful learning. They’re just not always necessary or feasible.

And I certainly would agree that we’d like to do better: link decisions and complex work products together into series of narratively contextualized settings, combining the important types of decisions that naturally occur (ala Schank’s Goal Based Scenarios and Story-Centered Curriculum and other similar approaches).  And we’re getting tools that make this possible. But that requires some new thinking. This is an interim step that, if you get your mind around it, sets you up to start wanting more.

Note that the thinking here also covers a variety of interaction possibilities, again drag’n’drop, image links, etc. It’s a shift in thinking, but a valuable one. I encourage you to get your mind around it. Better practice, after all, is better learning.

Constraints on activities

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When we design learning activities (per the activity-based learning model), ideally we’re looking to create an integration of a number of constraints around that assignment. I was looking to enumerate them, and (of course) I tried diagramming it.  Thought I’d share the first draft, and I welcome feedback!

Multiple constraints on assignmentsThe goal is an assignment that includes the right type of processing. This must align with what they need to be able to do after the learning experience. Whether at work or in a subsequent class. Of course, that’s factored into the objective for this learning activity (which is part of an overall sequence of learning).

Another constraint is making sure the setting is a context that helps establish the breadth of transfer. The choice should be sufficiently different from contexts seen in examples and other practices to facilitate abstracting the essential elements. And, of course, it’s ideally in the form of a story that the learner’s actions are contributing to (read: resolve). The right level of exaggeration could play an (unrepresented) role in that story.

We also need the challenge in the activity to be in the right range of difficulty for the learner. This is the integration of flow and learning to create meaningful engagement.  And we want to include ways in which learners typically go wrong (read: misconceptions). Learners need to be able to make the mistakes here so we’re trapping and addressing them in the learning situation, not when it could matter.

Finally, we want to make sure there’s enough variation across tasks. While some similarities benefit for both consistency and addressing the objective, variety can maintain interest. We need to strike that balance. Similarly, look at the overall workload: how much are we expecting, and is that appropriate given the other constraints outside this learning goal.

I think you can see that successfully integrating these is non-trivial, and I haven’t even gotten into how to evaluate this, particularly to make it a part of an overall assessment. Yet, we know that multiple constraints help make the design easier (at least until you constrain yourself to an empty solution set ;).  This is probably still a mix of art and science, but by being explicit you’re less likely to miss an element.

We want to align activities with the desired outcome, in the full context.  So, what am I missing?  Does this make sense?

 

Labels, models, and drives

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In my post last week on engagement, I presented the alignment model from my  Engaging Learning  book on designing learning experiences. And as I thought about the post, I pondered several related things about labels, models, and drives. I thought I’d wrestle with them ‘out loud’ here, and troll (in the old sense) to see what you think.

Some folks have branded a model and lived on that for their career. And, in a number of cases, that’s not bad: they’re useful models and their applicability hasn’t diminished. And while, for instance, I think that alignment model is as useful as most models I’ve seen, I didn’t see any reason to tie my legacy to it, because the principles I like to comprehend and then apply to create solutions aren’t limited to just engagement. Though I wonder if people would find it easier to put the model in practice if it had a label.  The Quinn Engagement model or somesuch?

I’ve also created models around mobile, and about performance ecosystems, and more. I can’t say that they’re all original (e.g. the 4Cs of mobile), though I think they have utility. And some have labels (again, the 4Cs, Least Assistance Principle…) Then the misconceptions book is very useful, but the coverage there isn’t really mine, either. It’s just a useful compendium. I expect to keep creating models. But it’d led to another thought…

I’ve seen people driven to build companies. They just keep doing it, even if they’ve built one and sold it, they’re always on it; they’re serial entrepreneurs. I, for instance, have no desire to do that. There are elements to that that aren’t me.    Other folks are driven to do research: they have a knack for designing experiments that tease out the questions that drive them to find answers. And I’ve been good at that, but it’s not what makes my heart beat faster. I do  like action research, which is about doing with theory, and reflecting back. (I also like helping others become able to do this.)

What I’m about is understanding and applying cognitive science (in the broad sense) to help people do important things in ways that are enabled by new technologies.  Models that explain disparate domains are a hobby. I like finding ways to apply them to solve new problems in ways that are insightful but also pragmatic.   If I create models along the way (and I do), that’s a bonus. Maybe I should try to create a model about applying models or somesuch. But really, I like what I do.

The question I had though, is whether anyone’s categorized ‘drives’.  Some folks are clearly driven by money, some by physical challenges. Is there a characterization?  Not that there needs to be, but the above chain of thought led me to be curious. Is there a typology of drives? And, of course, I’m skeptical if there is one (or more), owing to the problems with, for instance, personality types and learning styles :D. Still, welcome any pointers.

Where’s Clark? Fall 2018/Spring 2019 Events Schedule

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Here’re the events where I’ll be through the last quarter of this year, and into the next. Of course, you can always find out what’s up at the Quinnovation News page… But this is a more likely place for you to start unless you’re looking to talk to me about work.  I hope to see you, virtually or in person, at one of these!

The week of October 22-26, Clark will be speaking (the same week!) at DevLearn on measurement and eLearning science, and at AECT on meta-learning architecture. (Yeah, both in one week…long story.)

On Litmos’ Live Virtual Summit on 7-8 November, Clark will talk Learning Experience. Stay tuned!

Clark will be a guest on Relate’s eLearnChat on 15 Nov.

2019

On the 9th of January, Clark will present The Myths that Plague Us as a webinar for HRDQ-U.

Clark will be presenting in the Modern Workplace Learning track at the LearnTec conference in Karlsruhe, Germany that runs 29-31 January.

Feb 25-27, Clark will serve as host of the Strategy Track at Training Magazine’s annual conference, opening with an overview and closing with a strategy-development session.

Clark will speak to the Charlotte Chapter of ISPI on the Performance Ecosystem on March 14.

At the eLearning Guild’s Learning Solutions conference March 25-28, Clark will be presenting a Learning Experience Design workshop, where we’ll go deep on integrating learning science and engagement.

If you’re at one of these events, please do introduce yourself and say hello (I’m not aloof, I’m just shy; er, ok, at least ’til we get to know one another :).

ONE level of exaggeration

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I’ve argued before that we should be thinking about exaggeration in our learning design. And I’ve noticed that it’s a dramatic trick in popular media. But you can easily think of ways it can go wrong. So what would be appropriate exaggeration?

When I look at movies and other story-telling media (comics), the exaggeration  usually is one level.  You know, it’s like real life but some aspect is taken beyond what’s typical. So, more extreme events happen: the whacky neighbor is  maniacal, or the money problems are  potentially fatal, or the unlikely events on a trip are just more extreme.  And this works; real life is mundane, but you go too far and it treads past the line of believability. So there’s a fine line there.

Now, when we’re actually performing, whether with customers or developing a solution, it matters. It’s our  job after all, and people are counting on us.  There’s plenty of stress, because there are probably not enough time, and too much work, and…

However, in the learning situation, you’re just mimicking the real world. It’s hard to mimic the stress that comes from real life. So, I’m arguing, we should be bringing in the extra pressure through the story. Exaggerate!  You’re not just helping a customer, you’re helping the foreign ambassador’s daughter, and international relations are at stake!  Or the person you’re sweet on (or the father of said person) is watching!  This is the chance to have fun and be creative!

Now, you can’t exaggerate everything. You could add extraneous cognitive load in terms of processing if you make it too complex in the details. And you definitely don’t want to change the inherent decisions in the task and decrease the relevance of the learning. To me, it’s about increasing the meaning of the decisions, without affecting their nature. Which may require a bit of interpretation, but I think it’s manageable.

At core, I don’t think I’m exaggerating when I say exaggeration is one of your tools to enhance engagement  and effectiveness. The closer we bring the learning situation to the performance situation, the higher the transfer. And if we increase the meaningfulness of the learning context to match the performance context, even if the details are more dissimilar, I think it’s an effective tradeoff. What do  you think?

User-experienced stories

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Yesterday I wrote about examples as stories. And I received a comment that prompted some reflection. The comment suggested that scenarios were stories too. And I agree!  They’re not examples, but they  are stories. With a twist.

So, as I’ve said many times, simulations are just a manipulable model of the world. And a motivated, self-capable learner  can learn from them. But motivated and self-capable isn’t always a safe bet. So, instead, we put the simulation in an initial state, and ask the learner to take it to a goal state, and we choose those such that they can’t get there until they learn the relationships we want them to understand. That’s what I call a scenario.  And we can tune those into a game. (Yes, we turn them into games by tuning; making the setting compelling, adjusting the challenge, etc.)

Now, a scenario needs a number of things. It needs a context, a setting. It needs a goal, a situation to be achieved. And, I’ll suggest, it should also have a reason for that goal to make sense. If you see the alignment that says why games  should be hard fun, you’ll see that making it meaningful is one of the elements. And that,  I say, is a story. Or, at least, the beginning of one.

In short, a story has a setting, a goal, and a path to get there. We remove boring details, highlight the tension, etc.  We flesh out a setting that the learner cares about, provide a sense of urgency, and enable the goal achievement.  But it’s not all done.

The reason this isn’t a complete story is we don’t know the path the protagonist uses to accomplish the goal, or ultimately doesn’t.  We’ve provided tools for that to happen, but we, as designers, don’t control the protagonist. The learner, really,  is the the protagonist!

What I’m talking about is that the story, certainly for the learner, is co-created between the world we’ve developed, and their use of the options or choices we provide. Together, a story is written for them by us  and them.  And, their decisions and the feedback are the story  and the learning!  It’s, voilà, a learning  experience.

Learning is powerful. Creating experiences that facilitate learning are creative hard fun for the designer, and valuable hard fun for the learner. Learning is about stories, some told, some c0-created, but all valuable.

Old and new school

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As I mentioned in yesterday’s post, I was asked for my responses to questions about trends.  What emerged in the resulting article, however, was pretty much contrary to what I said. I wasn’t misquoted, as I was used to set the stage, but what followed wasn’t what I said. What I saw was what I consider somewhat superficial evaluation, and I’d like to point to new school thinking instead.

So the article went from my claim about an ecosystem approach to touting three particular trends. And yet, these trends aren’t really new and aren’t really right!  They were touting mobile, gamification, and the ‘realities. And while there’s nothing wrong with any of them, I had said that I didn’t think that they’re the leading trends.

So, first, mobile is pretty much old news. Mobile first?  Er, it‘s only been 8 years or so (!) since Google declared that! What‘s cool about  mobile, still, is sensors and context-awareness, which they don‘t touch on.  And, in a repeated approach, they veered from the topic to quote a colleague. And my colleague was spot on, but it wasn’t in the least about mobile!  They ended this section talking about gamification and AR/VR, yet somehow implied that this was all about mobile. That would be “no”.

Then they talked about users wanting to be active.  Yay!  But, er, again they segued off-topic, taking personalization before going to microlearning and back to gamification and game-based learning(?).  Wait, what?  Microlearning is an ill-defined concept, and conflating it with game-based learning is just silly.  And games are real, but it‘s still hard to do them (particularly do them right, instead of tarted up drill-and-kill).  Of course, they didn‘t really stay on topic.

Finally, the realities. Here they stayed on topic, but really missed the opportunity. While AR and VR have real value, they talked about 360 photography and videography, which is about consumption, not interaction. And, that‘s not where the future is.

To go back to the initial premise – the three big trends – I think they got it wrong.  AI and data are now far more of a driver than mobile. Yes, AR/VR, but interaction, not just ‘immersion‘.  And probably the third driver is the ecosystem perspective, with systems integration and SaaS.

So, I have to say that the article was underwhelming in insight, confused in story, and wrong on topic. It’s like they just picked a quote and then went anywhere they wanted.   It’s old school thinking, and we’re beyond that. Again, my intention is not to continue to unpack wrong thinking (I’m assuming that’s not what you’re mostly here for, but let me know), but since this quoted me, I felt obliged.  It’s past time for new school thinking in L&D, because focusing on content is, like,  so last century.