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

16 July 2014

Models for learning

Clark @ 8:10 am

In a previous post, I suggested that we should not do the ‘click to learn more’, as it was just about presenting content.  But we do need to present content, so what content makes sense?  Obviously, examples are one thing, but let me make the case that the ‘how to’, the concept, should be in the form of a model.

There’s a problem in that Subject Matter Experts (SMEs) don’t have access to the what they do,but they have access to what they know, so it’s real easy to get a knowledge dump. And it’s hard work to make sense of it, sometimes, and it’s easier to just recite it. For example, expertise in many areas requires careful distinctions (e.g. such as in instructional design between the elements of learning).  However, it’s hard for learners to acquire all those careful distinctions without the underlying rationale of how they differ.

Similarly, most procedures to do something are guided not by arbitrary reasons, but instead are sequenced because of inherent constraints.  These constraints guide the proper procedures.  There’s a reason you do X before Y, and then a causal relationship that explains what you look for before deciding to do W instead of Z.

Too often, I see someone presenting learners with an arbitrary list of different things, when there are conceptual reasons why they differ. Similarly, I’ll see steps presented without a rationale for why. And in both cases, learners will remember better, and perform more robustly (particularly in environments with changes), if they have the model that explains what to do as well as the information.  While this might seem like more information, it’s really not, as the model minimizes the amount of arbitrary information you present. And it leads to better outcomes, so it would be worth it anyways.

Models give us a couple of useful things; they help us explain what has happened, and predict what will happen (e.g. if we do A, we’ll see B).  Which makes us more flexible in our actions, a useful trait.  As an aside, models also can draw upon metaphors to facilitate developing a useful understanding. Whether it’s flows, transformations, whatever, finding a concrete equivalent in the world can help recollection and application.

The problem, of course, is getting the model. It’s not always there, nor even easily inferable.  Which doesn’t mean you can ignore it.  The designer must be willing to work until they can understand it.  But it’s doable, and valuable.

So, please, model your learning design on the model of good learning with models. (Ok, I went too far there :)

15 July 2014

Click to learn less

Clark @ 8:06 am

All too often, when I review content, I see a recurrent interaction. And I really can’t figure out why, except a thorough lack of understanding of learning, and a determination to put interaction in regardless. Click here to learn more.

It’s not just the next button I’m railing about here, but instead that, on a screen, there’ll be n things, tabs, boxes, something, with the instructions to ‘click to learn more’. The point being that information is available but not directly. It appears that the designer has a lot of content to present, and yet just presenting lots of content is obviously wrong, so we’ll make it more interactive by chunking it up and then showing it iteratively with clicks. That’s more interactive, yes?  Yes, and it’s bad. Two problems: the content, and the interactions.

First, if you’ve got so much content to present, it’s a strong indicator that something’s wrong. People aren’t good at remembering large bits of information. They retain gist, not details. If you’re presenting a lot of content, you’re undoubtedly presenting too many details. Put the detail in the world if it has to be accessible. And my guess is that lots of it is ‘nice to have’, not ‘must have’. If it really has to go in the head, you are really going to have to do a lot more than just have them read it, you’ll need drill and kill. Instead, find the core model that predicts the right actions, and have them learn the model. Then give them practice in applying it, which leads to the second problem.  Reading once just isn’t going to have much impact.

Learners should be having meaningful interaction. The learner should be using the content to do something. Which isn’t a click each, it’s a click the right one. It’s making a choice, taking an action, applying the knowledge in context to make a decision. What will make a difference to the organization is not the ability to recite knowledge (leave that to videos, documents, chatbots, what have you), but instead the ability to make better decisions.

You can do the ‘reveal’ in certain circumstances, such as to present an example: present the initial situation, then reveal to show the complication, then reveal to show the solution, and the results. (Here’s the story: click here to see the problem that arose, click here to see the alternatives considered, click here to see the decision made, click here to see the consequences). So, it might be a somewhat engaging way to present an example, but good writing would trump that. Or you might have alternative actions and click to see the consequences of that action. Which wouldn’t make sense if there were a right answer, or you should immediately be getting them to first commit to a choice and then provide feedback.

Where does this come from? I think it comes from the fact that Subject Matter Experts (SMEs) don’t have access to most of what they actually do, but they do have access to all they know, so they tend to put out information. There are processes to get around this, but designers have to have the gumption to stand up to knowledge dump on the part of the SMEs and fight to find out how that information is used. It’s not necessarily easy (though it gets easier with practice), but it is necessary.

So, please, avoid the ‘click here to learn more’ and instead look for ‘click here to choose an action to take’.

9 July 2014

Benign role-playing

Clark @ 8:06 am

In #lrnchat a couple of weeks ago on anxiety in learning, Shannon Tipton suggested that role plays are the worst.  Now, I know Shannon and respect her (we’re in synch, her Learning Rebels movement very much resonates with my Revolutionary tendencies), so this somewhat surprised me.  We debated it a bit on twitter, and we thought maybe we should make the argument more extended, so here’s my take.

Her concern, as I understood it, was role plays where a subset get up and play roles in front of the room are uncomfortable.  That is, there’re roles and goals, and they’re set up to illustrate a point.  And I can see that type of role play might create a problem for a non-assertive person, particularly in an uncomfortable environment.  (She mentions it here, and see the extended explanation in the comment.)

Now, a favorite model of mine is Ann Brown and Anne-Marie Palincsar’s reciprocal teaching.  In this model (generalized from the original focus on reading), everyone takes  a turn performing (including instructor) and others critique the performance.  Of course, there have to be ground rules, such as talking about the performance not the person, making it safe to share, small enough steps between tasks, etc.  However, the benefits are that you internalize the monitoring, becoming self-monitoring and self-improving.

As another data point, I think of the Online Role Playing as characterized by Sandra Wills, Elyssabeth Leigh, and Albert Ip. Here, learners take roles and goals and explore virtually over time.  The original one they reference was done by John Shepherd and Andrew Vincent and explored the mideast crisis. Learners got engaged in the roles, and the whole process really illuminated the tensions underlying the topic.

When I put these together, I see a powerful tool for learning.  You should design the roles and goals to explore a topic, and unpack an issue.  You should prep learners to help them do a fair job of the role. And, most of all, you have to make it safe.  The instructor should be willing to take on the challenging role, and similarly be seen to fail, or maybe everyone does it in groups so no one group is in front, then you facilitate a discussion.  I’ve done this in my game design workshop, where everyone pairs up and alternates being a SME and being an ID.

I understand that performing is an area of fear for many, but I think that role playing can be a powerful learning experience without anxiety when you manage the process right.  Bad design is bad design, after all (PowerPoint doesn’t kill people…).  What say you?

8 July 2014

Align, deepen, and space

Clark @ 8:12 am

I was asked about, in regards to the Serious eLearning Manifesto, about how people could begin to realize the potential of eLearning.  I riffed about this once before, but I want to spin it a different way.  The key is making meaningful practice.  And there are three components: align it, deepen it, and space it.

First, align it. What do I mean here?  I mean make sure that your learning objective, what they’re learning, is aligned to a real change in the business. Something you know that, if they improve, it will have an impact on a measurable business outcome.  This means two things, underneath. First, it has to be something that, if people do differently and better, it will solve a problem in what the organization is trying to do.  Second, it has to be something learning benefits from.  If it’s not a case where it’s a cognitive skill shift, it should be about using a tool, or replaced with using a tool. Only use a course when a course makes sense, and make sure that course is addressing a real need.

Second, deepen it.  Abstract practice, and knowledge test are both less effective than practice that puts the learner in a context like they’ll be facing in the workplace, and having them make the same decisions they’ll need to be making after the learning experience.  Contextualize it, and exaggerate the context (in appropriate ways) to raise the level of interest and importance to be closer to the level of engagement that will be involved in live performance.  Make sure that the challenge is sufficient, too, by having alternatives that are seductive unless you really understand. Reliable misconceptions are great distractors, by the way.  And have sufficient practice that leads from their beginning ability to the final ability they need to have, and so that they can’t get it wrong (not just until they get it right; that’s amateur hour).

Here’s where the third, space it, can come in.  Will Thalheimer has written a superb document (PDF) explaining the need for spacing. You can space out the complexity of development, and sufficient practice, but we need to practice, rest (read: sleep), and then practice some more. Any meaningful learning really can’t be done in one go, but has to be spread.  How much? As Will explains, that depends on how complex the task is, and how often the task will be performed and the gaps in between, but it’s a fair bit. Which is why I say learning should be expensive.

After these three steps, you’ll want to only include the resources that will lead to success, provide models and examples that will support success, etc, but I believe that, regardless, learners with good practice are likely to get more out of the learning experience than any other action you can take. So start with good practice, please!

25 June 2014

Karen McGrane #mLearnCon Keynote Mindmap

Clark @ 9:54 am

Karen McGrane evangelized good content architecture (a topic near to my heart), in a witty and clear keynote. With amusing examples and quotes, she brought out just how key it is to move beyond hard wired, designed content and start working on rule-driven combinations from structured chunks. Great stuff!

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24 June 2014

Larry Irving #mLearnCon Keynote Mindmap

Clark @ 10:03 am

Larry Irving kicked off the mLearnCon with an inspiring talk about the ways in which technology can disrupt education. His ideas about VOOCs and nanodegrees were intriguing, and wish he’d talked more about adaptive learning. A great kickoff to the event.

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18 June 2014

Curation trumps creation

Clark @ 8:36 am

In the past, it has been the role of L&D to ascertain the resources necessary to supporting performance in the organization.  Finding the information, creating the resources, and making them available has often been a task that either results in training, or complements it. I want to suggest, however, that the time has changed and a new strategy may be more effective, at least in many instances.

Creating resources is hard.  We’ve seen the need to revisit the principles of learning design because despite the pleas that “we know this stuff already”, there are still too many bad elearning courses out there. Similarly with job aids, there are skills involved in doing it right.  Assuming those skills is a mistake.

There’s also the situation that creating resources is time consuming. The time spent doing this may be better spent in other approaches.  There are plenty of needs that need to be addressed without finding more work.

On the flip side, there are now so many resources out there about so many things, that it’s not hard to find an answer.  Finding good answers, of course, is certainly more problematic than just finding an answer, but there are likely answers out there.

The integration here is to start curating resources, not creating them.  They might come internally, from the employees, or from external resources, but regardless of provenance, if it’s out there, it saves your resources for other endeavors.

The new mantra is Personal Knowledge Mastery, and while that’s for the individual, there’s a role for L&D here too: practicing ‘representative knowledge mastery’,  as well as fostering PKM for the workforce.  You should be monitoring feeds relevant to your role and those you’re responsible for facilitating.  You need to practice it to be able to preach it, and you should be preaching it.

The point is to not be recreating resources that can be found, conserving your energy for those things that are business critical.  One organization has suggested that they only create resources for internal culture, everything else is curated.  Certainly only proprietary material should be the focus.

So, curate over create. Create when you have to, but only then. Finding good answers is more efficient than generating them.

3 June 2014

From Content to Experience

Clark @ 8:12 am

A number of years ago, I said that the problem for publishers was not going from text to content (as the saying goes), but from content to experience.  I think elearning designers have the same problem: they are given a knowledge dump, and have to somehow transform that into an effective experience.  They may even have read the Serious eLearning Manifesto, and want to follow it, but struggle with the transition or transformation.  What’s a designer to do?

The problem is, designers will be told, “we need a course on this”, and given a dump of Powerpoints (PPTs), documents (PDFs), and maybe access to a subject matter expert (SME).  This is all about knowledge.  Even the SME, unless prompted carefully otherwise, will resort to telling you the knowledge they’ve learned, because they just don’t have access to what they know.  And this, by itself, isn’t a foundation for a course.  Processing the knowledge, comprehending it, presenting it, and then testing on acquisition (e.g. what rapid elearning tools make easy), isn’t going to lead to a meaningful outcome. Sorry, knowledge isn’t the same as ability to perform.

And this ignores, of course, whether this course is actually needed.  Has anyone checked to see that if the skills associated with this knowledge have a connection with a real workplace performance issue?  Is the performance need a result of a lack of skills?  And is this content aligned to that skill?  Too often folks will ask  for a course on X when the barrier is something else.  For instance, if the content is a bunch of knowledge that somehow you’re to magically put in someone’s head, such as product information or arbitrary rules, you’re far better off putting that information in the world than trying to put it in the head.  It’s really hard to get arbitrary information in the head.  But let’s assume that there is a core skill and workplace need for the sake of this discussion.

The key is determining what this knowledge actually supports doing differently.  The designer needs to go through that content and figure out what individuals will be able to do that they can’t do now (that’s important), and then develop practice doing that. This is so important that, if what they’ll be able to do differently, isn’t there, there should be push back.  While you can talk to the SME (trying to get them to talk in terms of decisions they can make instead of knowledge), you may be better off inferring the decisions and then verifying and refining with the SME.  If you have access to several SMEs, better yet get them in a room together and just facilitate until they come up with the core decisions, but there are many situations where that’s not feasible.

Once you have that key decision, the application of the skill in context, you need to create situations where learners can practice using it.  You need to create scenarios where these decisions will play out. Even just better written multiple choice questions that have: story setting, situation precipitating decision, decision alternatives that are ways in which learners might go wrong,  consequences of the decisions, and feedback.  These practice attempts are the core of a meaningful learning experience. And there’s even evidence that putting problems up front or at core is a valuable practice.  You also want to have sufficient practice not just ’til they get it right, but until they have a high likelihood of not getting it wrong.

One thing that might not be in the PDFs and PPTs are examples.  It’s helpful to get colorful examples of someone using  information to successfully solve a problem, and also cases where they misapplied it and failed.  Your SME should be able to help you here, telling you engaging stories of wins and losses.  They may be somewhat resistant to the latter; worst case have them tell them about someone else.

The content in the PDFs and PPTs then gets winnowed down into just the resource material that helps the learner actually able to do the task, to successfully make the decision.  Consider having the practice set in a story, and the content is available through the story environment (e.g. casebooks on the shelves for examples, a ‘library’ for concepts).  But even if you present the (minimized) content and then have practice, you’ve shifted from knowledge dump/test to more of a flow of experience.  The suite of  meaningful practice, contextualized well and made meaningful with a wee bit of exaggeration and careful alignment with learner’s awareness, is the essence of experience.

Yes, there’s a bit more to it than that, but this is the core: focus on do, not dump.  And, once you get in the habit, it shouldn’t take longer, it just takes a change in thinking.  And even if it does, the dump approach isn’t liable to lead to any meaningful learning, so it’s a waste of time anyway.  So, create experiences, not content.

 

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?

21 May 2014

Getting contextual

Clark @ 8:07 am

For the current ADL webinar series on mobile, I gave a presentation on contextualizing mobile in the larger picture of L&D (a natural extension of my most recent books).  And a question came up about whether I thought wearables constituted mobile.  Naturally my answer was yes, but I realized there’s a larger issue, one that gets meta as well as mobile.

So, I’ve argued that we should be looking at models for guiding our behavior.  That we should be creating them by abstracting from successful practices, we should be conceptualizing them, or adopting them from other areas.  A good model, with rich conceptual relationships, provides a basis for explaining what has happened, and predicting what will happen, giving us a basis for making decisions.  Which means they need to be as context-independent as possible.

WorkOppsSo, for instance, when I developed the mobile models I use, e.g. the 4C’s and the applications of learning (see figure), I deliberately tried to create an understanding that would transcend the rapid changes that are characterizing mobile, and make them appropriately recontextualizable.

In the case of mobile, one of the unique opportunities is contextualization.  That means using information about where you are, when you are, which way you’re looking, temperature or barometric pressure, or even your own state: blood pressure, blood sugar, galvanic skin response, or whatever else skin sensors can detect.

To put that into context (see what I did there): with desktop learning, augmenting formal could be emails that provide new examples or practice that spread out over time. With a smartphone you can do the same, but you could also have a localized information so that because of where you were you might get information related to a learning goal. With a wearable, you might get some information because of what you’re looking at (e.g. a translation or a connection to something else you know), or due to your state (too anxious, stop and wait ’til you calm down).

Similarly for performance support: with a smartphone you could take what comes through the camera and add it onto what shows on the screen; with glasses you could lay it on the visual field.  With a watch or a ring, you might have an audio narration.  And we’ve already seen how the accelerometers in fit bracelets can track your activity and put it in context for you.

Social can not only connect you to who you need to know, regardless of device or channel, but also signal you that someone’s near, detecting their face or voice, and clue you in that you’ve met this person before.  Or find someone that you should meet because you’re nearby.

All of the above are using contextual information to augment the other tasks you’re doing.  The point is that you map the technology to the need, and infer the possibilities.  Models are a better basis for elearning, too so that you teach transferable understandings (made concrete in practice) rather than specifics that can get outdated.  This is one of the elements we placed in the Serious eLearning Manifesto, of course.  They’re also useful for coaching & mentoring as well, as for problem-solving, innovating, and more.

Models are powerful tools for thinking, and good ones will support the broadest possible uses.  And that’s why I collect them, think in terms of them, create them, and most importantly, use them in my work.   I encourage you to ensure that you’re using models appropriately to guide you to new opportunities, solutions, and success.

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