Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

A few posts ago, I wrote about how we might be rushing too fast into cognitive computing. Not that there’s anything wrong with augmenting us, but I was wondering if we’d be better off focusing on developing our non-cognitive systems first. And, of course, it occurred to me after a conversation that there might be another example of this ‘tech fix before smart fix’ problem: adaptive learning over good design. Is this a tech solution to the wrong problem?

So, I’m a fan of adaptive learning. Heck, I led a team that developed an adaptive learning system back circa 2000 (ahead of the times, as always ;). And I know that there are good things we can do with adaptive learning.  Some are still relatively impractical (e.g. intelligent tutoring systems), some make sense (e.g. adapting on learner performance), and, of course, some are pretty silly (e.g. learning styles).  Still, done well, adaptive learning could and should be a benefit.  (And serious games are adaptive!)

But I would posit that before you charge off for adaptive learning, you make sure you’re doing good learning design first.  Adaptation on top of good learning design is likely to add some extra benefits, but adaptation on old learning design just doesn’t make sense.  And, I’ll suggest, good learning design is cheaper, and likely to have a bigger impact.

So, for instance, adapting a large knowledge-based course will still leave it as a problematic solution in search of a problem.  Creating a better course focusing on critical skills with meaningful practice is going to have a bigger impact on the bottom line than adapting the course for learner progress. It’s not a bad thing, but it’s a secondary concern, I reckon.

Games are a special case of adapting on the basis of learner performance. When well done, they’re the next best thing to live practice.  Yet, at core, they too need good design.

There are a lot of adaptive solutions emerging, with a strong push to optimize your outcomes.  Some of them have a pretty good basis, too. But your goal is to achieve business impact, and what will hit that first, and best, is starting with good design.  Adaptive isn’t a panacea, it’s a fillip to design, not a replacement.    Master the rules of good design, then come back and add in those extra elements, whether adaptivity and/or game mechanics.   Please?

It occurs to me to mention some of the other places you can find my writings besides here (and how they differ ;).  My blog posts are pretty regular (my aim is 2/week), but tend to have ideas that are embryonic or a bit ‘evangelical’. First, I’ve written four books; you can check them out and get sample chapters at their respective sites:

Engaging Learning: Designing e-Learning Simulation Games

Designing mLearning: Tapping Into the Mobile Revolution for Organizational Performance

The Mobile Academy: mLearning For Higher Education

Revolutionize Learning &  Development: Performance and Information Strategy for the Information Age

They’re designed to be the definitive word on the topic, at least at the moment.

I’ve also written or co-written a number of chapters in a variety of books.  The books include The Really Useful eLearning Instruction Manual, Creating a Learning Culture, Michael Allen’s eLearning Annual 2009,  and a bunch of academic handbooks (Mobile Learning, Experiential Learning, Wiley Learning Technology ;).  These tend to be longer than an article, with a pretty thorough coverage of whatever topic is on tap.

Then there are articles in a variety of magazines.  These tend to be aggregated thoughts that are longer than a blog post, but not as through as a chapter. In particular, they are things I think need to be heard (or read).  So, my writing has shown up in:

eLearnMag

Learning Solutions

CLO

The topics vary. (For the eLearnMag ones, you’ll have to search for my name owing to their interface, and they tend to be more like editorials.)

And then there are blog posts for others that are a bit longer than my usual blog post, and close to an article in focus:

The Deeper eLearning series for Learnnovators

A monthly article for Litmos.

These, too, are more like articles in that they’re focused, and deeper than my usual blog post.  For the latter I cover a lot of different topics, so you’re likely to find something relevant there in many different areas.

I’m proud of it all, but for a quick update on a topic, you might be best seeing if there’s a Litmos post on it first.  That’s likely to be relatively short and focused if there is one. And, of course, if it’s a topic you’re interested in advancing in and I can help, do let me know.

As luck would have it, I found out about an event on Storytelling Across Media being run in the city, and attended a couple of the panels: half of one on interactive design and Telltale Games, one on story and games, and one on story and VR.  There were interesting quotes from each about story, games, and VR that prompted reflection, and I thought I’d share my thoughts with  you.

Story and Games

The first quote that struck home was “nonlinear storytelling strikes a balance between narrative and choice”. This is the challenge that I and I think all game designers struggle with. So, I subsequently asked “How do you integrate storytelling with experience design?”  The panelists acknowledged that this was the ongoing challenge. Another comment was that “stories are created in your imagination”.  That’s key, I think, to create experiences that the player will end up writing as a story they can tell.

I found myself  thinking about story machines versus experience engines.  It appears to me that, ala Sid Maier’s “a good game is a series of interesting decisions”, that it’s all about the decisions you make.  It’s easier to tell a good story when you put a game ‘on rails’; it’s harder when you want to have an open world and still ramp up the tension across the board.  Having rules and timers give you the opportunity.  For serious games, however, not commercial ones, I reckon it’s more ok for the story to be somewhat linear.

Another interesting comment was about how things are going transmedia.  An issue that emerged was the business of transmedia, how you might start with a comic to build interest and revenue to fund adding in a game, or a movie.  Telling stories across media is an interesting challenge, and could have real opportunity for learning. I have been a fan of Andrea Phillips Transmedia Storytelling and Koreen Pagano’s Immersive Learning, which I think give good clues about how this might go.  I’m also thinking about the movie The Game (Michael Douglas & Sean Penn), and how it’s a great example of an alternate reality game. I’d love to do something like that, but serious. We did a demo once about sales that captured some of the opportunity, but…

Also, I’ve looked at many instances of experience design: movies, theatre, amusement parks, games, etc.  And I’ve advocated that those interested in making experience engaging, particularly learning, should similarly explore this. It’s hard work, you know ;).  However, one of the panelists commented on ‘circus design’. That’s something I had never thought to explore, so it’s now on my ‘todo’ list!

There were also several mentions of a theatre experience in New York called Sleep No More.  It involves two intersecting stories: Macbeth and a lady looking for someone. There’s no dialog, and it plays out across several venues. The interesting thing is that you, as an audience member, choose where to go, who to follow, and what to watch.  Now I need to find a way to experience this! (Wish I’d heard about it before my keynote there in June.)

VR

The other theme was VR, and there were some very interesting comments made. It was repeatedly made clear by the practitioners that this was a field  still very much in development. The tools and technologies had become good and cheap enough to allow tinkering and exploration, but the business models and viable experiences were still being explored.

One quote that was interesting was a response to the issue of what the ‘frame is’.  In computer games, the frame is the screen. But in VR there’s no ‘screen’, you’re surrounded.  A response to this was “the player is the ‘frame’ in VR”.  That’s an interesting perspective.  I might reframe it as “the player’s attention is the ‘frame’ in the game”, and manipulating that may be the key.  To ponder.

Another interesting comment was “proximity breeds empathy”.  I was reminded of the phrase “familiarity breeds contempt”, but I can see that an experiential approach may help generate sympathy and comprehension.  Can you actually share someone else’s experience?  Certainly, immersion has yielded concrete learning improvements, and successful behavioral interventions.

Which brings up a response on the question of where the future of VR is (that seemed to be reflected by the other panelists) is that shared VR is the future.  Clearly, social has big benefits for learning, and can be the basis of strong emotions (sometimes negative!)

There are clearly times when VR has unique and valuable advantages for learning, though I continue to think that AR may provide the greater overall opportunity, when it’s done right.  It might be like the difference between courses and mentoring.  That is, VR to make a step change, and the AR for continual development.  Where do ARGs fit in?  Perhaps more for developing the ability to deal with the unexpected?

One of the panelists mentioned Magic Leap, and I was reminded that that type of experience will be where we can really get opportunities for transformative experiences. I think that’s where Google Glass was going, and they’re right to hold off and get it right, but when we can really start annotating the world, combining it with ARGs, there will be real potential.  We can start designing now, but it’ll definitely be some time before tools and technologies hit the ‘experimentation’ phase VR has reached.

Lots of fodder for thinking!

I attended  ComicCon  again this year, and addition to the wild costumes, crowded exhibit hall, and over-priced food, there are a series of sessions. They cover television, movies, and print in a wide variety of markets.  And I like the sessions that aren’t associated with popular media (as waiting in lines is something I’m fairly averse too).  One I saw this year (not all of, for several reasons) was particularly thought-provoking.

As background, when I was approached by the Australian Children’s Welfare Agency, many years ago, to do a game to help kids who grow up in ‘non-parental’ situations, they’d already spent their money on a video, and a comic book, and a poster.  As far as I know, it was the first serious game you could play on the web (and I’m happy to have that disconfirmed, but as I’ve thought about it and tried to find out to the contrary, I haven’t found to the contrary). And back then we didn’t even have the label ‘serious game’!

And I’ve been a fan of serious games since before then (my first job out of college was designing and programming educational computer games).  In fact, one of the reasons I went to grad school was because  I saw the connection between adventure games and learning, but it wasn’t clear they were commercially viable (at that time).

But I didn’t think about the comic book much.  I got a copy as part of the overall launch when the game was released along with the other materials, so I’m sure I read it (it may even be lurking somewhere in a cubbyhole somewhere, though could also have been the victim of a move or a tidiness binge).  And I’ve argued before about how graphic novel and such formats aren’t used enough in learning.

So this session was on serious comics, and it of course resurrected those thoughts. One panelist opened about how they were using comics to spark reading, and I was reminded how apparently the original Pokemon games (not Go, though that was obsessing my kids on the trip) required and consequently sparked lots of reading. The second speaker introduced how he was using comics to spread STD/HIV awareness. These are actually both serious issues.

Of course, I was also reminded of an interactive comic book I once read on my iPad that had games interspersed that advanced the storyline (I couldn’t finish because I couldn’t complete one of the games: I’ve little time to spend developing the necessary ‘twitch’ skills).  However, more serious games, requiring applying the knowledge available through the comic, could provide an embedded practice environment.  It’s sort of a blend between a pure comic and a pure game, for important outcomes.  And this is very doable in ebook formats, even if the ‘game’ is just a mini-scenario or several, but with HTML 5 embedded you could do more.

I once wrote that in the future there would be lots of little interactive ‘learnlets’ that would teach you anything you needed to know (including how to make learnlets ;) and games or even interactive comics are what I meant and what could be pretty close to ideal.  It’s been doable for a while, but now it’s doable pretty much with commercially available tools (e.g. not requiring custom programming).  We can make learning ‘hard fun’, and we should. So, what are you waiting for?

Professor John Black of Columbia Unveristy gave a fascinating talk about how games can leverage “embodied cognition” to achieve deeper learning. The notion is that by physical enaction, you get richer activation, and sponsor deeper learning.  It obviously triggered lots of thoughts (mine are the ones in the bubbles :). Lots to ponder.

I’ve had lurking in my ‘to do’ list a comment about doing a post on when to gamify. In general, of course, I avoid it, but I have to acknowledge there are times when it makes sense.  And someone challenged me to think about what those circumstances are. So here I’m taking a principled shot at it, but I also welcome your thoughts.

To be clear, let me first define what gamification is to me.  So, I’m a big fan of serious games, that is when you wrap meaningful decisions into contexts that are intrinsically meaningful.  And I can be convinced that there are times when tarting up memory practice with quiz-show window-dressing makes sense, e.g. when it has to be ‘in the head’.  What I typically refer to as gamification, however, is where you use external resources, such as scores, leaderboards, badges, and rewards to support behavior you want to happen.

I happened to hear a gamification expert talk, and he pointed out some rules about what he termed ‘goal science’.  He had five pillars:

1. that clear goals makes people feel connected and aligns the organization
2. that working on goals together (in a competitive sense ;) makes them feel supported
3. that feedback helps people progress in systematic ways
4. that the tight loop of feedback is more personalized
5. that choosing challenging goals engages people

Implicit in this is that you do good goal setting and rewards. You have to have some good alignment to get these points across.  He made the point that doing it badly could be worse than not doing it at all!

With these ground rules, we can think about when it might make sense.  I’ll argue that one obvious, and probably sad case, would be when you don’t have a coherent organization, and people aren’t aware of their role in the organization.  Making up for effective communication isn’t necessarily a good thing, in my mind.

I think it also might make sense for a fun diversion to achieve a short-term goal. This might be particularly useful for an organizational change, when extra motivation could be of assistance in supporting new behaviors. (Say, for moving to a coherent organization. ;) Or some periodic event, supporting say a philanthropic commitment related to the organization.

And it can be a reward for a desired behavior, such as my frequent flier points.  I collect them, hoping to spend them. I resent it, a bit, because it’s never as good as is promised, which is a worry.  Which means it’s not being done well.

On the other hand, I can’t see using it on an ongoing basis, as it seems it would undermine the intrinsic motivation of doing meaningful work.  Making up for a lack of meaningful work would be a bad thing, too.

So, I recall talking to a guy many moons ago who was an expert in motivation for the workplace. And I had the opportunity to see the staggering amount of stuff available to orgs to reward behavior (largely sales) at an exhibit happening next to our event. It’s clear I’m not an expert, but while I’ll stick to my guns about preferring intrinsic motivation, I’m quite willing to believe that there are times it works, including on me.

Ok, those are my thoughts, what’ve I missed?

It’s the end of the year, and given that I’m an advocate for the benefits of reflection, I suppose I better practice what I preach. So what am I thinking I learned as a consequence of this past year?  Several things come to mind (and I reserve the right for more things to percolate out, but those will be my 2016 posts, right? :):

1. The Revolution is real: the evidence mounts that there is a need for change in L&D, and when those steps are taken, good things happen. The latest Towards Maturity report shows that the steps taken by their top-performing organizations are very much about aligning with business, focusing on performance, and more.  Similarly, Chief Learning Officer‘s Learning Elite Survey similarly point out to making links across the organization and measuring outcomes.  The data supports the principled observation.
2. The barriers are real: there is continuing resistance to the most obvious changes. 70:20:10, for instance, continues to get challenged on nonsensical issues like the exactness of the numbers!?!?  The fact that a Learning Management System is not a strategy still doesn’t seem to have penetrated.  And so we’re similarly seeing that other business units are taking on the needs for performance support, social media, and ongoing learning. Which is bad news for L&D, I reckon.
3. Learning design is rocket science: (or should be). The perpetration of so much bad elearning continues to be demonstrated at exhibition halls around the globe.  It’s demonstrably true that tarted up information presentation and knowledge test isn’t going to lead to meaningful behavior change, but we still are thrusting people into positions without background and giving them tools that are oriented at content presentation.  Somehow we need to do better. Still pushing the Serious eLearning Manifesto.
4. Mobile is well on it’s way: we’re seeing mobile becoming mainstream, and this is a good thing. While we still hear the drum beating to put courses on a phone, we’re also seeing that call being ignored. We’re instead seeing real needs being met, and new opportunities being explored.  There’s still a ways to go, but here’s to a continuing awareness of good mobile design.
5. Gamification is still being confounded: people aren’t really making clear conceptual differences around games. We’re still seeing linear scenarios confounded with branching, we’re seeing gamification confounded with serious games, and more.  Some of these are because the concepts are complex, and some because of vested interests.
6. Games  seem to be reemerging: while the interest in games became mainstream circa 2010 or so, there hasn’t been a real sea change in their use.  However, it’s quietly feeling like folks are beginning to get their minds around Immersive Learning Simulations, aka Serious Games.   There’s still ways to go in really understanding the critical design elements, but the tools are getting better and making them more accessible in at least some formats.
7. Design is becoming a ‘thing’: all the hype around Design Thinking is leading to a greater concern about design, and this is a good thing. Unfortunately there will probably be some hype and clarity to be discerned, but at least the overall awareness raising is a good step.
8. Learning to learn seems to have emerged: years ago the late great Jay Cross and I and some colleagues put together the Meta-Learning Lab, and it was way too early (like so much I touch :p). However, his passing has raised the term again, and there’s much more resonance. I don’t think it’s necessarily a thing yet, but it’s far greater resonance than we had at the time.
9. Systems are coming: I’ve been arguing for the underpinnings, e.g. content systems.  And I’m (finally) beginning to see more interest in that, and other components are advancing as well: data (e.g. the great work Ellen Wagner and team have been doing on Predictive Analytics), algorithms (all the new adaptive learning systems), etc. I’m keen to think what tags are necessary to support the ability to leverage open educational resources as part of such systems.
10. Greater inputs into learning: we’ve seen learning folks get interested in behavior change, habits, and more.  I’m thinking we’re going to go further. Areas I’m interested in include myth and ritual, powerful shapers of culture and behavior. And we’re drawing on greater inputs into the processes as well (see 7, above).  I hope this continues, as part of learning to learn is to look to related areas and models.

Obviously, these are things I care about.  I’m fortunate to be able to work in a field that I enjoy and believe has real potential to contribute.  And just fair warning, I’m working on a few areas in several ways.  You’ll see more about learning design and the future of work sometime in the near future. And rather than generally agitate, I’m putting together two specific programs – one on (e)learning quality and one on L&D strategy – that are intended to be comprehensive approaches.  Stay tuned.

That’s my short list, I’m sure more will emerge.  In the meantime, I hope you had a great 2015, and that your 2016 is your best year yet.

I recently came across an article ostensibly about branching scenarios, but somehow the discussion largely missed the point.  Ok, so I can be a stickler for conceptual clarity, but I think it’s important to distinguish between different types of scenarios and their relative strengths and weaknesses.

So in my book Engaging Learning, I was looking to talk about how to make engaging learning experiences.  I was pushing games (and still do) and how to design them, but I also wanted to acknowledge the various approximations thereto.  So in it, I characterized the differences between what I called mini-scenarios, linear scenarios, and contingent scenarios (this latter is what’s traditionally called branching scenarios).  These are all approximations to full games, with various tradeoffs.

At core, let me be clear, is the need to put learners in situations where they need to make decisions. The goal is to have those decisions closely mimic the decisions they need to make after the learning experience. There’s a context (aka the story setting), and then a specific situation triggers the need to make a decision.  And we can deliver this in a number of ways. The ideal is a simulation-driven (aka model-driven or engine-driven) experience.  There’s a model of the world underneath that calculates the outcomes of your action and determines whether you’ve yet achieved success (or failure), or generates a new opportunity to act.  We can (and should) tune this into a serious game.  This gives us deep experience, but the model-building is challenging and there are short cuts.

In mini-scenarios, you put the learner in a setting with a situation that precipitates a decision.  Just one, and then there’s feedback.  You could use video, a graphic novel format, or just prose, but the game problem is a setting and a situation, leading to choices. Similarly, you could have them respond by selecting option A B or C, or pointing to the right answer, or whatever.  It stops there. Which is the weakness, because in the real world the consequences are typically more complex than this, and it’s nice off the learning experience reflects that reality.  Still, it’s better than knowledge test.  Really, these are just a better written multiple choice question, but that’s at least a start!

Linear scenarios are a bit more complex. There are a series of game problems in the same context, but whatever the player chooses, the right decision is ultimately made, leading to the next problem. You use some sort of sleight of hand, such as “a supervisor catches the mistake and rectifies it, informing you…” to make it all ok.  Or, you can terminate out and have to restart if you make the wrong decision at any point. These are a step up in terms of showing the more complex consequences, but are a bit unrealistic.  There’s some learning power here, but not as much as is possible. I have used them as sort of multiple mini-scenarios with content in between, and the same story is used for the next choice, which at least made a nice flow. Cathy Moore suggests these are valuable for novices, and I think it’s also useful if everyone needs to receive the same ‘test’ in some accreditation environment to be fair and balanced (though in a competency-based world they’d be better off with the full game).

Then there’s the full branching scenario (which I called contingent scenarios in the book, because the consequences and even new decisions are contingent on your choices).  That is, you see different opportunities depending on your choice. If you make one decision, the subsequent ones are different.  If you don’t shut down the network right away, for instance, the consequences are different (perhaps a breach) than if you do (you get the VP mad).  This, of course, is much  more like the real world.  The only difference between this and a serious game is that the contingencies in the world are hard-wired in the branches, not captured in a separate model (rules and variables). This is easier, but it gets tough to track if you have too many  branches. And the lack of an engine limits the replay and ability to have randomness. Of course, you can make several of these.

So the problem I had with the article that triggered this post is that their generic model looked like a mini-scenario, and nowhere did they show the full concept of a real branching scenario. Further, their example was really a linear scenario, not a branching scenario.  And I realize this may seem like an ‘angels dancing on the head of a pin’, but I think it’s important to make distinctions when they affect the learning outcome, so you can more clearly make a choice that reflects the goal you are trying to achieve.

To their credit, that they were pushing for contextualized decision making at all is a major win, so I don’t want to quibble too much.  Moving our learning practice/assessment/activity to more contextualized performance is a good thing.  Still, I hope this elaboration is useful  to get more nuanced solutions.  Learning design really can’t be treated as a paint-by-numbers exercise, you really should know what you’re doing!

I’ve talked in the past about the importance of engaging emotionally before beginning learning. And I’ve talked about the importance of understanding what makes a topic intrinsically interesting. But I haven’t really separated them out, as became clear to me in a client meeting. So let me remedy that here.

I’ve argued, and believe, that we should open up learners emotionally before we address them cognitively. Before we tell them what they’ll learn, before we show them objectives, we should create a visceral reaction, a wry recognition of “oh, yes, I do need to know this”. It can be a dramatic or humorous exaggeration of the positive consequences of having the knowledge or the negative consequences of not. I call this a ‘motivating example’ different than the actual reference examples used to illustrate the model in context. In previous content we’ve used comics to point out the problems of not knowing, and similarly Michael Allen had a fabulous video that dramatized the same. Of course, you also have a graphic novel introduction of someone saving the day with this knowledge. It of course depends on your audience and what will work for them.

Another story I tell is when a colleague found out I did games, and asked if I wanted to assist him and his team. The task was, to me and many, not necessarily a source of great intrinsic interest, but he pointed out that he’d discovered that to practitioners, it was like playing detective. Which of course gave him a theme, and a overarching hook. And this is the second element of engagement we can and should lever.

Once we’ve hooked them into why this learning is important, we then want to help maintain interest through the learning experience. If we can find out what makes this particular element interesting, we should have it represented in the examples and practice tasks. This will help illuminate the rationale and develop learner abilities by integrating the inherent nature of the task into the learning experience.

Often SMEs are challenging, particularly to get real decisions out of, but here’s where they’re extremely valuable. In addition to stories illustrating great wins and losses that can serve as examples (and the motivating example I mentioned above), they can help you understand why this is intrinsically interesting to them. They’ve spent the time to become experts in this, we want to unpack why this was worth such effort. You may have to drill a bit below “make the world a better place”, but you could and should be able to.

By hooking them in initially by making them aware of the role of this knowledge, and then maintaining interest through the learning experience, you have a better chance of your learning sticking. And that’s what we want to achieve, right?

In thinking through what makes experiences engaging, and in particular making practice engaging, I riffed on some core elements.   The three terms I came up with were Challenge, Choices, & Consequences. And I realized I had a nice little alliteration going, so I’m going to elaborate and see if it makes sense to me (and you).

In general, good practice is having the learner make decisions in context. This has to be more than just recognizing the correct knowledge option, and providing a ‘right’ or ‘wrong’ feedback.  The right decision has to be made, in a plausible situation with plausible alternatives, and the right feedback has to be provided.

So, the first thing is, there has to be a situation that the learner ‘gets’ is important. It’s meaningful to them and to their stakeholders, and they want to get it right. It has to be clear there’s a real decision that has outcomes that are important.  And the difficulty has to be adjusted to their level of ability. If it’s too easy, they’re bored and little learning occurs. If it’s too difficult, it’s frustrating and again little learning occurs.  However, with a meaningful story and the right level of difficulty, we have the appropriate challenge. 

Then, we have to have the right alternatives to select from. Some of the challenge comes from having a real decision where you can recognize that making the wrong choice would be problematic. But the alternatives must require an appropriate level of discrimination.  Alternatives that are so obvious or silly that they can be ruled out aren’t going to lead to any learning. Instead, they need to be ways learners reliably go wrong, representing misconceptions. The benefits are several: first, you can find out what they really know (or don’t), and you have the chance to address them. Also, this assists in having the right level of challenge.  So  you must have the right choices.

Finally, once the choice is made, you need to have feedback. Rather than immediately have some external voice opine ‘yes’ or ‘no’, let the learner see the consequences of that choice. This is important for two reasons. For one, it closes the emotional experience, as you see what happens, wrapping up the experience. Second, it shows how things work in the world, exposing the causal relationships and assists the learner understanding. Then you can provide feedback (or not, if you’re embedding this single decision in a scenario or game where other choices are precipitated by this choice). So, the final element are consequences.

While this isn’t complete, I think it’s a nice shorthand to guide the design of meaningful and engaging practice. What do you think?