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

24 February 2016

When to gamify?

Clark @ 8:10 am

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?

31 December 2015

2015 Reflections

Clark @ 8:02 am

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.

10 December 2015

Scenarios and Conceptual Clarity

Clark @ 6:02 am

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.

MiniScenarioIn 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!

LinearScenarioLinear 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).

BranchingScenarioThen 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!

3 November 2015

Nuancing Engagement

Clark @ 8:14 am

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?

26 August 2015

3 C’s of Engaging Practice

Clark @ 2:28 pm

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?

28 April 2015

Got Game?

Clark @ 8:15 am

Why should you, as a learning designer, take a game design workshop?  What is the relationship between games and learning?  I want to suggest that there are very important reasons why you should.

Just so you don’t think I’m the only one saying it, in the decade since I wrote the book Engaging Learning: Designing e-Learning Simulation Games, there have been a large variety of books on the topic. Clark Aldrich has written three, at least count. James Paul Gee has pointed out how the semantic features of games match to the way our brains learn, as has David  Williamson Shaeffer.  People like Kurt Squire, Constance Steinkuhler, Henry Jenkins, and Sasha Barab have been strong advocates of games for learning. And of course Karl Kapp has a recent book on the topic.  You could also argue that Raph Koster’s A Theory of Fun is another vote given that his premise is that fun is learning. So I’m not alone in this.

But more specifically, why get steeped in it?  And I want to give you three reasons: understanding engagement, understanding practice, and understanding design.  Not to say you don’t know these, but I’ll suggest that there are depths which you’re not yet incorporating into your learning, and  you could and should.  After all, learning should be ‘hard fun’.

The difference between a simulation and a game is pretty straightforward.  A simulation is just a model of the world, and it can be in any legal state and be taken to any other.  A self-motivated and effective self-learner can use that to discover what they need to know.  But for specific learning purposes, we put that simulation into an initial state, and ask the learner to take it to a goal state, and we’ve chosen those so that they can’t do it until they understand the relationships we want them to understand. That’s what I call a scenario, and we typically wrap a story around it to motivate the goal.  We can tune that into a game.  Yes, we turn it into a game, but by tuning.

And that’s the important point about engagement. We can’t call it game; only our players can tell us whether it’s a game or not. To achieve that goal, we have to understand what motivates our learners, what they care about, and figure out how to integrate that into the learning.  It’s about not designing a learning event, but designing a learning experience.  And, by studying how games achieve that, we can learn how to take our learning from mundane to meaningful.   Whether or not we have the resources and desire to build actual games, we can learn valuable lesssons to apply to any of our learning design. It’s the emotional element most ID leaves behind.

I also maintain that, next to mentored live practice, games are the best thing going (and individual mentoring doesn’t scale well, and live practice can be expensive both to develop but particularly when mistakes are made).  Games build upon that by providing deep practice; embedding important decisions in a context that makes the experience as meaningful as when it really counts.  We use game techniques to heighten and deep the experience, which makes it closer to live practice, reducing transfer distance. And we can provide repeated practice.  Again, even if we’re not able to implement full game engines, there are many important lessons to take to designing other learning experiences: how to design better multiple choice questions, the value of branching scenarios, and more.  Practical improvements that will increase engagement and increase outcomes.

Finally, game designers use design processes that have a lot to offer to formal learning design. Their practices in terms of information collection (analysis), prototyping and refinement, and evaluation are advanced by the simple requirement that their output is such that people will actually pay for the experience.  There are valuable elements that can be transferred to learning design even if you aren’t expecting to have an outcome so valuable you can charge for it.

As professionals, it behooves us to look to other fields with implications that could influence and improve our outcomes. Interface design, graphic design, software engineering, and more are all relevant areas to explore. So is game design, and arguably the most relevant one we can.

So, if you’re interested in tapping into this, I encourage you to consider the game design workshop I’ll be running for the ATD Atlanta chapter on the 3rd of June. Their price is fair even if you’re not a chapter member, and it’s great deal if you are.  Further, it’s a tried and tested format that’s been well received since I first started offering it. The night before, I’ll be busting myths at the chapter meeting.  I hope I’ll see you there!

3 March 2015

On the road again

Clark @ 7:42 am

Well, some more travels are imminent, so I thought I’d update you on where the Quinnovation road show would be on tour this spring:

  • March 9-10 I’ll be collaborating with Sarah Gilbert and Nick Floro to deliver ATD’s mLearnNow event in Miami on mobile
  • On the 11th I’ll be at a private event talking the Revolution to a select group outside Denver
  • Come the 18th I’ll be inciting the revolution at the ATD Golden Gate chapter meeting here in the Bay Area
  • On the 25th-27th, I’ll be in Orlando again instigating at the eLearning Guild’s Learning Solutions conference
  • May 7-8 I’ll be kicking up my heels about the revolution for the eLearning Symposium in Austin
  • I’ll be stumping the revolution at another vendor event in Las Vegas 12-13
  • And June 2-3 I’ll be myth-smashing for ATD Atlanta, and then workshopping game design

So, if you’re at one of these, do come up and introduce yourself and say hello!

 

 

8 October 2014

The resurgence of games?

Clark @ 8:44 am

I talked yesterday about how some concepts may not resonate immediately, and need to continue to be raised until the context is right.  There I was talking about explorability and my own experience with service science, but it occurred to me that the same may be true of games.

Now, I’ve been pushing games as a vehicle for learning for a long time, well before my book came out on the topic.  I strongly believe that next to mentored live practice (which doesn’t scale well), (serious) games are the next best learning opportunity.  The reasons are strong:

  • safe practice: learners can make mistakes without real consequences (tho’ world-based ones can play out)
  • contextualized practice (and feedback): learning works better in context rather than on abstract problems
  • sufficient practice: a game engine can give essentially infinite replay
  • adaptive practice: the game can get more difficult to develop the learner to the necessary level
  • meaningful practice: we can choose the world and story to be relevant and interesting to learners

the list goes on.  Pretty much all the principles of the Serious eLearning Manifesto are addressed in games.

Now, I and others (Gee, Aldrich, Shaffer, again the list goes on) have touted this for years.  Yet we haven’t seen as much progress as we could and should.  It seemed like there was a resurgence around 2009-2010, but then it seemed to go quiet again. And now, with Karl Kapp’s Gamification book and the rise of interest in gamification, we have yet another wave of interest.

Now, I’m not a fan of the extrinsic  gamification, but it appears there’s a growing awareness of the difference between extrinsic and intrinsic. And I’m seeing more use of games to develop understanding in at least K12 circles.  Hopefully, the awareness will arise in higher ed and corp too.

As some fear, it’s too costly, but my response is twofold:

  • games aren’t as expensive as you fear; there are lots of opportunities for games in lower price ranges (e.g. $100K), don’t buy into the $1M and up mentality
  • they’re actually likely to be effective (as part of a complete learning experience), compared to many if not most of the things being done in learning

So I hope we might finally go beyond Clicky Clicky Bling Bling, (tarted quiz shows, cheesy videos and more) and get to interaction that actually leads to change.  Here’s hoping!

28 August 2014

Kris Duggan #LnDMeetup Gamification Mindmap

Clark @ 8:05 am

Kris Duggan spoke on gamification at the Bay Area Learning Design & Technology MeetUp. He talked about some successes at his Badging role and then his new initiative bringing gamification more intrinsically into organizations. He proposed five Goal Science rules that resonated with other principles I’ve heard for good organizations.

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27 May 2014

Setting Story

Clark @ 8:15 am

I’ve been thinking about the deep challenge of motivating uninterested learners.  To me, at least part of that is making the learning of intrinsic interest.  And one of those elements is practice, and this is arguably the most important element to making learning work.  So how to do we make practice intrinsically interesting?

One of the challenging but important components of designing meaningful practice is choosing a context in which that practice is situated.  It’s really about finding a story line that makes the action meaningful to both the learner and the learning. It’s creative (and consequently fun), but it’s also not intrinsically obvious (which I’ve learned after trying to teach it in both game design and advanced ID workshops). There are heuristics to be followed (there’s no guaranteed formula except brainstorm, winnow, trial, and refine), however, that can be useful.

While Subject Matter Experts (SMEs) can be the bane of your existence while setting learning goals (they have conscious access to no more than 30% of what they do, so they tend to end up reciting what they know, which they do have access to), they can be very useful when creating stories. There’s a reason why they’ve spent the requisite time to become experts in the field, and that’s an aspect we can tap into. Find out why it’s of interest to them.  In one instance, when asking experts about computer auditing, a colleague found that auditors found it like playing detective, tracking back to find the error.  It’s that sort of insight upon which a good game or practice exercise can hinge.

One of the tricks to work with SMEs is to talk about decisions.  I argue that what is most likely to make a difference to organizations is that people make better decisions, and I also believe that using the language of decisions helps SMEs focus on what they do, not what they know.  Between your performance gap analysis of the situation, and expert insight into what decisions are key, you’re likely to find the key performances you want learners to practice.

You also want to find out all the ways learners go wrong.  Here you may well hear instructors and/or SMEs say “no matter what we do, they always…”. And that’s the things you want to know, because novices don’t tend to make random errors.  Yes, there’s some, owing to our cognitive architecture (it’s adaptive), which is why it’s bad to expect people to do rote things, but it’s a small fraction of mistakes.  Instead, learners make patterned mistakes based upon mistakes in their conceptualizations of the performance, aka misconceptions.  And  you want to trap those because you’ll have a chance to remediate them in the learning context. And they make the challenge more appropriately tuned.

You also need the consequences of both the right choice and the misconceptions. Even if it’s just a multiple choice question, you should show what the real world consequence is before providing the feedback about why it’s wrong. It’s also the key element in scenarios, and building models for serious games.

Then the trick is to ask SMEs about all the different settings in which these decisions embed. Such decisions tend to travel in packs, which is why scenarios are better practice than simple multiple choice, just as scenario-based multiple choice trumps knowledge test.  Regardless, you want to contextualize those decisions, and knowing the different settings that can be used gives you a greater palette to choose from.

Finally, you’ll want to decide how close you want the context to be to the real context.  For certain high-stakes and well-defined tasks, like flying planes or surgery, you’ll want them quite close to the real situation.  In other situations, where there’s more broad applicability and less intrinsic interest (perhaps accounting or project management), you may want a more fantastic setting that facilitates broader transfer.

Exaggeration is a key element. Knowing what to exaggerate and when is not yet a science, but the rule of thumb is leave the core decisions to be based upon the important variables, but the context can be raised to increase the importance.  For example, accounting might not be riveting but your job depends on it.  Raising the importance of the accounting decision in the learning experience will mimic the importance, so you might be accounting for a mob boss who’ll terminate your existence if you don’t terminate the discrepancy in his accounts!  Sometimes exaggeration can serve a pedagogical purpose as well, such as highlighting certain decisions that are rare in real life but really important when they occur. In one instance, we had asthma show up with a 50% frequency instead of the usual ~15%, as the respiratory complications that could occur required specific approaches to address.

Ultimately, you want to choose a setting in which to embed the decisions. Just making it abstract decreases the impact of the learning, and making it about knowledge, not decisions, will render it almost useless, except for those rare bits of knowledge that have to absolutely be in the head.  You want to be making decisions using models, not recalling specific facts. Facts are better off put in the world for reference, except where time is too critical. And that’s more rare than you’d expect.

This may seem like a lot of work, but it’s not that hard, with practice.  And the above is for critical decisions. In many cases, a good designer should be able to look at some content and infer what the decisions involved should be.  It’s a different design approach then transforming knowledge into tests, but it’s critical for learning.  Start working on your practice items first, aligned with meaningful objects, and the rest will flow. That’s my claim, what say you?

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