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Clark Quinn’s Learnings about Learning

General or specific change

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I was reflecting on the two books I recently wrote about, Scaling Up and Changing the Game,  versus the cultural approach of the Learning Organization I wrote about years ago (and refer to regularly).  The thing is that both of the new books are about choosing either a very specific needed change, whether  determined by fiat  or based upon something already working well, whereas the earlier work identified general characteristics that make sense. And my thought was when does each make sense?  More importantly,  what is the role of Learning & Development (L&D; which really should be P&D or Performance & Development) in each?

If an organization is in need of a shakeup, so that a particular unit is underperforming, or a significant shift in the game has been signaled by new competition or a technology/policy/social change, the targeted change makes sense. As I suggested, some of the required elements from the more general approach are implicit or explicit, such as facilitating communication.  The  role here for L&D, then, is to support the training required for executives leading the shift in terms of communicating and behaving, as well as ongoing coaching.  Similarly for the behaviors of employees, and watching for signs of resistance, in general facilitating the shift.  However, the locus of responsibility is the executive team in charge of the needed change.

On the other hand, if the organization is being moderately successful, but isn’t optimized in terms of learning, there’s a case for a more general shift.  If the culture doesn’t have the elements of a real  learning organization – safe to share, valuing diversity, openness to new ideas, time for reflection – then there’s a case to be made for L&D to lead the charge on the change. Let’s be clear, it cannot be done without executive buy-in and leadership, but L&D can be the instigator in this case.  L&D here sells the benefits of the change, supports leadership in execution both by training if necessary and coaching, and again coaches the change.

Regardless, L&D  should be instigating this change within their own unit.  It’s going to lead to a more effective L&D unit, and there’re the benefits of walking the walk as a predecessor to talking the talk.

Ultimately, L&D needs to understand effective culture and the mechanisms to culture change, as well as facilitating social learning, performance consulting, information architecture,  resource design, and of course formal learning design.  There’re new roles and new skillsets to be mastered on the path to being an effective and strategic contributor to the organization, but the alternative is extinction, eh?

Changing Culture: Changing the Game

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I previously wrote about Sutton & Rao’s Scaling up Excellence, and have now finished a quick read of Connors & Smith’s  Change the Culture, Change the Game.  Both books cover roughly the same area, but in very different ways.  Sutton & Rao’s was very descriptive of the changes they observed and the emergent lessons.  Connors & Smith, on the other hand, are very prescriptive.  Yet both are telling similar stories with considerable overlap.

Let’s be clear, Connors & Smith have a model they want to sell you.  You get the model up front, and then implementation tools in the second half. Of course, you  aren’t supposed to actually try this without having their help.  As long as you’re clear on this aspect of the book, you can take the lessons learned and decide whether you’d apply them yourself or use their support.

They have a relatively clear model, that talks about the results you want, the actions people will have to take to get to the results,  the beliefs that are needed to guide those actions, and the experiences that will support those beliefs. They aptly point out that many change initiatives stop at the second step, and don’t get the necessity of the subsequent two steps. It’s a plausible story and model, where  the actions, beliefs, and experiences are the elements that create the culture that achieves the results.

Like Kirkpatrick’s levels, the notion is that you start with the results you need, and work backward.  Further, everything has to be aligned: you have to determine what actions will achieve the new results, and then what new beliefs can   guide those new actions, and ultimately what  experiences are needed  to foster those new beliefs.  You work rigorously to only focus on the ones that will make a difference, recognizing that too much will impact the outcome.

The second half talks about tools to foster these steps. There are management tools,  leadership  skills, and  integration steps.  There’s necessary training associated with these, and then coaching (this is the sales bit).   It’s very formulaic, and makes it sound like close adherence to these approaches will lead to success.  That said, there is a clear recognition that you need to continually check on how it’s going, and be active in making things happen.

And this is where there’s overlap with Sutton & Rao: it’s about ongoing effort, it requires accountability (being willing to take ownership of outcomes),  people must be  engaged and involved, etc.  Both are different approaches to dealing with the same issue: working systematically to make necessary changes in an organization. And in both cases, the arguments are pretty compelling that it takes transparency and commitment by the leadership to walk the talk.  It’s up to the executives to choose the needed change, but the empowerment to find ways to make that happens is diffused downward.

Whether you like the more organic approach of Sutton & Rao or the more formulaic model of Connors & Smith, you will find insight into the elements that facilitate change.  For me, the synergy was nice to see.  Now we’ll see if these are still old-school by comparison to Laloux’s  Reinventing Organizations,  that has received strong support  from some  colleagues I have learned to trust.

#itashare

 

Changing Culture: Scaling Up Excellence

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I’ve found myself    picking up books about how to change culture, as it seems to be the big barrier to a successful revolution.  I’ve finished a quick read of  Scaling Up Excellence, am in the midst of Change the Culture, Change the Game, and have Reinventing Organizations and Organize for Complexity (the latter two recommended by my colleague Harold Jarche) on deck.  Here are my notes on the first.

Scaling Up Excellence is the work of two Stanford professors who have looked for years at what makes organizations succeed, particularly when they need to grow, or seed a transformation.  They’ve had the opportunity to study a wide variety of companies, most as success stories, but they do include some cautionary tales as well.  Fortunately, this doesn’t read like an academic book, and while it’s not equipped  with formulas, there are overarching principles that have been extracted.

The overarching principle is that scaling is “a ground war, not an air war”.  What they mean is that you can’t make a high level decision and expect change to happen.  It requires hard work in the trenches.  Leaders have to go in, figure out what needs to change, and then lead that change.  Using a religious metaphor, they distinguish between Buddhist and Catholic approaches, where you’re either wanting everyone to follow the same template, or modify it to their unique situation.  Some organizations need to replicate a particular customer experience (think fast food), whereas others will need to be more accommodating to unique situations (think high-end retailers).

There are some principles around scaling, such as getting mental buy-in, helping people see the bigger picture and how the near term necessities are tied into that, and that going slow initially may help things go better. An interesting one, to me, is that accountability is a key factor; you can’t have folks sit on the side lines, and no slackers (let alone those who undermine).

Another suite of principles include cutting the cognitive load to getting things done the right way, mixing together emotional issues with clever approach, connecting people. One important element is of course allegiance, where people believe in the organization  and it’s clear the organization  is also believing in the people.  No one’s claiming this is easy, but they have lots of examples and guidance.

One really neat idea that I haven’t heard before was the concept of a pre-mortem, that is, imagining a period some time in the future and asking “why did it go right”, and also “why did it go wrong”.  A nice way to distance  oneself from the moment and reflect effectively on a proposed plan. If separate groups do this, the inputs can help address potential risks, and emphasize useful actions.

I worry a bit that it’s still ‘old school’ business, (more on that after I finish the book I’m currently reading and look to the two ‘new thinking’ books), but they do seem to be pushing the values of doing meaningful work and sharing  it.  A bit discursive, but overall I thought it insightful.

#itashare

Malicious metrics

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Like others, I have been seduced by the “what X are you” quizzes on FaceBook. I certainly understand why they’re compelling, but I’ve begun to worry about just why they’re so prevalent.  And I’m a wee bit concerned.

People like to know things about themselves. Years ago, when we built an adaptive learning system (it would profile you versus me, and then even if we took the same course we’d be likely to have a different experience), we realized we’d need to profile learning  a priori.  That is, we’d ask an initial suite of questions, and that’d prime the system. (And we  intended this profiling to be a game, not a set of quiz questions). Ultimately that initial model built by the questions would get refined by learner behavior  in  the system (and we also intended a suite of interventions ‘layered’ on top that would help improve learner characteristics that were malleable).

The underlying mission given us by my CEO was to help learners understand themselves  as learners, and use that to their advantage.  So, in addition to asking the questions, we’d share with them what we’d learned about them as learners.  The notion was what we irreverently termed the ‘Cosmo quiz’, those quizzes that appeared in Cosmopolitan magazine about “how good a Y” you are, where one  takes quizzes and then adds up the score.

Fast forward to now, and I began to wonder about these quizzes. They seem cute and harmless, but without seeing all the possible outcomes, it certainly seemed like it might not take that many questions to determine which one you’d qualify as.  Yes, in good test design, you ask a question a number of times to disambiguate.  But it occurred to me that you could use fewer questions (and the outcomes are always written intriguingly so you don’t necessarily mind which you become), and then wonder what are the other questions being used for.  And the outcomes here don’t really matter!

So, it’d be real easy to insert demographic questions and use that information (presumably en masse) to start profiling markets.  If you know other information about these people, you can start aggregating data and mining for information.  One question  I saw, for instance, asked you to pick which setting (desert, jungle, mountain, city), etc.  Could that help recommend vacations to you?

When I researched these quizzes, rather than finding concerns about the question data, instead I found that much more detailed information about your account  was allowed to be passed from Facebook  to  the quiz hoster.  Which is worse!  Even if not, I begin to worry that while they’re fun, what’s the motivation to keep creating new ones?  What’s the business relationship?  And I think it’s data.

Now, getting better data means you might get more targeted advertising.  And that might be preferable than random (I’ve seen some pretty funny complaints about “what made them think this was for me”).  But I don’t feel like giving them that much insight. So I’m not doing any more of those.  I don’t think they really know what animal/movie character/color/fruit/power tool  I am.  If you want to know, ask me.

From Content to Experience

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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.

 

Vale Don Kirkpatrick

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Last week, Don Kirkpatrick passed away.  Known for his four ‘levels‘ of measuring learning, he’s been hailed and excoriated.  And it’s instructive to see why on both sides.

He derived his model as an approach to determine the impact of an intervention on organizational performance.  He felt that you worked backward from the change you needed, to determine whether the workplace performance was changing, as then to see if that could be attributed to the training, and ultimately to the learner.  He numbered his steps so that step 1 was seeing what learners thought, 2 was that learners  could demonstrate a change, 3 was that the change was showing up in the workplace post intervention, and 4 was it impacting business measures.

This actually made a lot of sense. Rather than measuring the cost of hour of seat time or some other measure of efficiency, or, worse, not measuring at all, here was a plan that was designed to focus on meaningful change that the business needed.  It was obvious, and yet also obviously needed.    So his success in bringing awareness to the topic of business impact is to be lauded.

There were two major  problems, however.  For one, having numbered it the way that it was, people seemed that they could take a partial attempt.  Research shows that the number of people would only do step 1 or 2, and these are useless without ultimately including 4.  He even later wondered if he should have numbered the approach in the reverse.  The numbers have been documented (from a presentation with results from the ASTD Benchmarking Forum) as dropping in implementation from 94% doing level 1, 34% doing level 2, 13% doing level 3, and 3% doing level 4.  That’s  not  the idea!

The second problem was that whether or not he intended it (and there are reasons to believe he didn’t), it become associated only with training interventions.  Performance support interventions or social network outcomes  could similarly be measured (at least on levels 3 and 4), yet the language was all about training, which made it easy for folks to wrongly conclude that training was your only tool.  And we still see folks using courses as the only tool in their repertoire, which just isn’t aligned with how we think, work, and learn (hence the revolution).

Kirkpatrick rode this tool for the rest of his career,  created a family business in it, and he wasn’t shy about suggesting that you buy a book to learn about it.  I certainly can’t fault him for it either, as he did have a sensible model and it could be put into effective use.  There are worse ways to earn a living.

Others have played upon his model.  The Phillips have made a similar career with their fifth level, ROI, measuring the cost of impacting level 4 against the value of the impact.  Which isn’t a bad move to make  after you focus on making an impact.  Similarly, a client opined that there was also level 0, are the learners even showing up for the training!

In assessing the impact, part of me is mindful that tools can be used for good or ill.  Powerpoint doesn’t kill people, people do, as the saying goes.  Still, Kirkpatrick could’ve renumbered the steps, or been more outspoken about the problems with just step 1.

So, I laud his insight, and bemoan the ultimate lack of impact.  However, I reckon it’s better to argue about it than be ignorant.  Rest in peace.

Setting Story

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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?

‘Sharing’ culture

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I was in a recent conversation about a company facing strong growth and worried about the impact on culture.  Companies with a positive culture, a valuable offering, and a good business model are liable to face growth issues, and maintaining or starting a good culture becomes a critical issue to maintaining the organization’s success.

This company had a positive culture, in that people were diverse, friendly, upbeat, and committed to contributing. These are all positive elements that had led to the early success. Growth, both through hiring and acquisitions, was leading to concerns about the ability for those factors to continue.

One of the things that wasn’t obvious from the initial portrayal of the company was whether folks there were capturing and sharing what they were doing, how they were working, what challenges they were facing, and what results they were seeing. In a small company, this happens naturally through conversation, but face to face communication isn’t scalable.

One obvious possibility is to implement or more systematically leverage an enterprise social network (ESN; essentially    using social media in the org).  Working out loud, as it’s known, has many benefits.  As people share their work, others can comment and improve it.  People can ask for help and get collaboration on those new problems and innovation needs that are increasingly arising.  Mistakes can be made and the lessons learned can be shared so no others have to make the same mistakes.

One of the offshoot benefits of such sharing is that it takes the positive cultural attributes already being shown and makes them visible (if implicitly) as well.  It’s not guaranteed, but with an awareness of the behaviors and manifestations of culture through the network, a systematic process could lead to that positive culture scaling  and yield those additional benefits that accompany working out loud.

It takes all the elements of a learning culture and organizational change, of course. You need to continue to welcome diversity, be open to new ideas, and have it safe to contribute.  You also need to develop a vision, message it, have the leadership model it, facilitate it, anticipate problems and be prepared to address them, and ultimately reward the desired outcomes.  But this is doable.

The benefits of a positive culture are becoming known, and the value of social networks are also emerging. Linking them together is not only necessary, but the benefits are more than the sum of the parts.

#itashare

Getting contextual

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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.

Peeling the onion

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I’ve been talking a bit recently about deepening formal design, specifically to achieve learning that’s flexible, persistent, and develops the learner’s abilities to become self-sustaining in work and life.  That is, not just for a course, but for a curriculum.  And it’s more than just what we talked about in the Serious eLearning Manifesto, though of course it starts there.    So, to begin with, it needs to start with meaningful objectives, provide related practice, and be trialed and developed, but there’s more, there are layers of development that wrap around the core.

One element I want to suggest is important is also in the Manifesto, but I want to push a bit deeper here.  I worked to put in that the elements behind, say, a procedure or a task, that you apply to problems, are models or concepts.  That is, a connected body of conceptual relationships that tie together your beliefs about why it should be done this way.  For example, if you’ve a procedure or process you want people to follow, there is (or should be) a  rationale  behind it.

And  you should help learners discover and see the relationships between the model and the steps, through examples and the feedback they get on practice.  If they can internalize the understanding behind steps, they are better prepared for the inevitable changes to the tools they use, the materials they work on, or the process changes what will come from innovation.  Training them on X, when X will ultimately shift to Y, isn’t as helpful unless you help them understand the principles that led to performance on X and will transfer to Y.

Another element is that the output of the activities should create scrutable deliverables  and  also annotate the thoughts behind the result.  These provide evidence of the thinking both implicit and explicit, a basis for mentors/instructors to understand what’s good, and what still may need to be addressed, tin the learner’s thinking.  There’s also the creation of a portfolio of work which belongs to the learner and can represent what they are capable of.

Of course, the choices of activities for the learner initially, and the design of them to make them engaging, by being meaningful to the learner in important ways, is another layer of sophistication in the design.  It can’t just be that you give the traditional boring problems, but instead the challenges need to be contextualized. More than that (which is already in the Manifesto), you want to use exaggeration and story to really make the challenges compelling.  Learning  should   be hard fun.

Another layer is that of 21st Century skills (for examples, the SCANS competencies).  These can’t be taught separately, they really need to manifest across whatever domain learnings you are doing. So you need learners to not just learn concepts, but apply those concepts to specific problems. And, in the requirements of the problem, you build in opportunities to problem-solve, communicate, collaborate, e.g. all the foundational and workplace skills. They need to reappear again and again and be assessed (and developed) separately.

Ultimately, you want the learner to be taking on responsibility themselves.  Later assignments should include the learner being given parameters and choosing appropriate deliverables and formats for communication.  And this requires and additional layer, a layer of annotation on the learning design. The learners need to be seeing  why the learning was so designed, so that they can internalize the principles of good design and so become self-improving learners. You, for example, in reading this far, have chosen to do this as part of your own learning, and hopefully it’s a worthwhile investment.  That’s the point; you want learners to continue to seek out challenges, and resources to succeed, as part of their ongoing self-development, and that comes by having seen learning design and been handed the keys at some point on the journey, with support that’s gradually faded.

The nuances of this are not trivial, but I want to suggest that they  are doable.  It’s a subtle interweaving, to be sure, but once you’ve got your mind around it (with scaffolded practice :), my claim is that it can be done, reliably and repeatedly.   And it should.  To do less is to miss some of the necessary elements for successful support of  an individual to become the capable and continually self-improving learner that we need.

I touched on most of this when I was talking about Activity-Based Learning, but it’s worthwhile to revisit it (at least for me :).