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Clark Quinn’s Learnings about Learning

70:20:10 and the Learning Curve

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My colleague Charles Jennings recently posted on the value of autonomous learning (worth reading!), sparked by  a diagram provided by another ITA colleague, Jane Hart (that I also thought was insightful). In Charles’ post he also included an IBM diagram that triggered some associations.

So, in IBM’s diagram, they talked about: the access phase where learning is separate, the integration where learning is ‘enabled’ by work, and the on-demand phase where learning is ’embedded’. They talked about ‘point solutions’ (read: courses) for access, then blended models for integration, and dynamic models for on demand.  The point was that the closer to the work that learning is, the more value.

However, I was reminded of Fits & Posner’s model of skill acquisition, which has 3 phases of cognitive, associative, and autonomous learning. The first, cognitive, is when you benefit from formal instruction: giving you models and practice opportunities to map actions to an explicit framework. (Note that this  assumes a good formal learning design,  not rote information and knowledge test!)  Then there’s an associative stage where that explicit framework is supported in being contextualized and compiled away.  Finally, the learner continues to improve through continual practice.

I was initially reminded of Norman & Rumelhart’s accretion, restructuring, and tuning learning mechanisms, but it’s not quite right. Still, you could think of accreting the cognitive and explicitly semantic knowledge, then restructuring that into coarse skills that don’t require  as much conscious effort, until it becomes a matter of tuning a finely automated skill.

721LearningCurveThis, to me, maps more closely to 70:20:10, because you can see the formal (10) playing a role to kick off the semantic part of the learning, then coaching and mentoring (the 20) support the integration or association of the skills, and then the 70 (practice, reflection, and personal knowledge mastery  including informal social learning) takes over, and I mapped it against a hypothetical improvement curve.

Of course, it’s not quite this clean. While the formal often does kick off the learning, the role of coaching/mentoring and the personal learning are typically intermingled (though the role shifts from mentor to mentee ;). And, of course, the ratios in 70:20:10 are only a framework for rethinking investment, not a prescription about how you apply the numbers.  And I may well have the curve wrong (this is too flat for the normal power law of learning), but I wanted to emphasize that the 10 only has a small role to play in moving performance from zero to some minimal level, that mentoring and coaching really help improve performance, and that ongoing development requires a supportive environment.

I think it’s important to understand how we learn, so we can align our uses of technology to support them in productive ways. As this suggests, if you care about organizational performance, you are going to want to support more than the course, as well as doing the course right.  (Hence the revolution. :)

#itashare

Getting strategic means getting scientific

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I’ve been on a rant about learning design for a few posts, but I ended up talking about how creating a better process is part of getting strategic.  The point was that our learning design has to embody what’s know about how we learn, e.g. a learning engineering.  And it occurs to me that getting our processes structured to align with how we work is part of a bigger picture of how our strategies have to similarly be informed.

So, as part of the L&D Revolution I argue we need to have, I’m suggesting organizations, and consequently L&D, need to be aligned with how we think, work, and learn. So our formal learning initiatives (used only when they are really needed) need to be based upon learning science. And performance support similarly needs to reflect how we process information, and, importantly, things we don’t do well and need support for.  The argument for informal and social learning similarly comes from our natural approaches, and similarly needs to provide facilitation for where things can and do go wrong.

And, recursively, L&D’s processes need to similarly reflect what we do, and don’t, do well.  So,  just as we should provide support for performers to execute, communicate, collaborate, and continue to improve (why L&D needs to become P&D), we need to make sure that we practice what we preach.  And a scientific method means we need to measure what we’re doing, not just efficiency, but effectiveness.

It’s time that L&D gets out of the amateur approach, and starts getting professional. Which means understanding the organization’s goals, rejecting requests that are nonsensical, examining what we do, using technology in sophisticated ways (*cough* content engineering *cough*), and more.  We need to know about how we think, work, and learn, and apply it to what we do. We’re about people, after all, so it’s about time we understood the science in our field, and quit thinking that our existing practices (largely from an industrial age) are inherently  relevant. We must be scrutable, and that means we must scrutinize.  Time to  get to work.

#itashare

It’s the process, silly!

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So yesterday, I went off on some of the subtleties in elearning that are being missed.  This is tied to last weeks posts about how we’re not treating elearning seriously enough.  And part of it is in the knowledge and skills of the designers, but it’s also in the process. Or, to put it another way, we should be using steps and tools that align with the type of learning we need. And I don’t mean ADDIE, though not inherently.

So what  do I mean?  For one, I’m a fan of Michael Allen’s Successive Approximation Model (SAM), which iterates several times (tho’ heuristically, and it could be better tied to a criterion).  Given that people are far less predictable than, say, concrete, fields like interface design have long known that testing and refinement need to be included.  ADDIE isn’t inherently linear, certainly as it has evolved, but in many ways it makes it easy to make it a one-pass process.

Another issue, to me, is to structure the format for your intermediate representations so that make it hard to do aught but come up with useful information.  So, for instance, in recent work I’ve emphasized that a preliminary output  is a competency doc that includes (among other things)  the objectives (and measures), models, and common misconceptions.  This has evolved from a similar document I use in (learning) game design.

You then need to capture your initial learning flow. This is what Dick &  Carey call your instructional strategy, but to me it’s the overall experience of the learner, including addressing the anxieties learners may feel, raising their interest and motivation, and systematically building their confidence.  The anxieties or emotional barriers to learning may well be worth capturing at the same time as the competencies, it occurs to me (learning out loud ;).

It also helps if your tools don’t interfere with your goals.  It should be easy to create animations that help illustrate models (for the concept) and tell stories (for examples).  These can be any media tools, of course. The most important tools are the ones you use to create meaningful practice. These should allow you to create mini-, linear-, and branching-scenarios (at least).  They should have alternative feedback for every wrong answer. And they should support contextualizing the practice activity. Note that this does  not mean tarted up drill and kill with gratuitous ‘themes’ (race cars, game shows).  It means having learners make meaningful decisions and act on them in ways like they’d act in the real world (click on buttons for tech, choose dialog alternatives for interpersonal interactions, drag tools to a workbench or adjust controls for lab stuff, etc).

Putting in place processes that only use formal learning when it makes sense,  and then doing it right when it does make sense, is key to putting L&D on a path to relevancy.   Cranking out courses on demand, focusing on measures like cost/butt/seat, adding rote knowledge quizzes to SME knowledge dumps, etc are instead continuing down the garden path to oblivion. Are you ready to get scientific and strategic about your learning  design?

Reflections on 15 years

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For Inside Learning & Technologies 50th edition, a number of us were asked to provide reflections on what has changed over the past 15 years.  This was pretty much the period in which I’d returned to the US and took up with what was kind of a startup and led to my life as a consultant.  As an end of year piece, I have permission to post that article here:

15 years ago, I had just taken a step away from academia and government-sponsored initiatives to a new position leading a team in what was effectively a startup. I was excited about the prospect of taking the latest learning science to the needs of the corporate world. My thoughts were along the lines of “here, where we have money for meaningful initiatives, surely we can do something spectacular”. And it turns out that the answer is both yes and no.

The technology we had then was pretty powerful, and that has only increased in the past 15 years. We had software that let us leverage the power of the internet, and reasonable processing power in our computers. The Palm Pilot had already made mobile a possibility as well. So the technology was no longer a barrier, even then.

And what amazing developments we have seen! The ability to create rendered worlds accessible through a dedicated application and now just a browser is truly an impressive capability. Regardless of whether we overestimated the value proposition, it is still quite the technology feat. And similarly, the ability to communicate via voice and video allows us to connect people in ways once only dreamed of.

We also have rich new ways to interact from microblogs to wikis (collaborative documents). These capabilities are improved by transcending proximity and synchronicity. We can work together without worrying about where the solution is hosted, or where our colleagues are located. Social media allow us to tap into the power of people working together.

The improvements in mobile capabilities are also worth noting. We have gone from hype to hyphens, where a limited monochrome handheld has given way to powerful high-resolution full-color multi-channel always-connected sensor-rich devices. We can pretty much deliver anything anywhere we want, and that fulfills Arthur C. Clarke’s famous proposition that a truly advanced technology is indistinguishable from magic.

Coupled with our technological improvements are advances in our understanding of how we think, work, and learn. We now have recognition about how we act in the world, about how we work with others, and how we best learn. We have information age understandings that illustrate why industrial age methods are not appropriate.

It is not truly new, but reaching mainstream awareness in the last decade and more is the recognition that the model of our thinking as formal and logical is being updated. While we can work in such ways, it is the exception rather than the rule. Such thinking is effortful and it turns out both that we avoid it and there is a limit to how much deep thinking one can do in a day. Instead, we use our intuition beyond where we should, and while this is generally okay, it helps to understand our limitations and design around them.

There is also a spreading awareness of how much our thinking is externalized in the world, and how much we use technology to support us being effective. We have recognized the power of external support for thinking, through tools such as checklists and wizards. We do this pretty naturally, and the benefits from good design of technology greatly facilitate our ability to think.

There is also recognition that the model of individual innovation is broken, and that working together is far superior to working alone. The notion of the lone genius disappearing and coming back with the answer has been replaced by iterations on top of previous work by teams. When people work together in effective ways, in a supportive environment, the outcomes will be better. While this is not easy to effect in many circumstances, we know the practices and culture elements we need, and it is our commitment to get there, not our understanding, that is the barrier.

Finally, our approaches to learning are better informed now. We know that being emotionally engaged is a valued component in moving to learning experience design. We understand the role of models in supporting more flexible performance. We also have evidence of the value of performing in context. It is not news that information dump and knowledge test do not lead to meaningful skill acquisition, and it is increasingly clear that meaningful practice can. It is also increasingly clear that, as things move faster, meaningful skills – the ability to make better decisions – is what is going to provide the sustainable differentiator for organizations.

So imagine my dismay in finding that the approaches we are using in organizations are largely still rooted in approaches from yesteryear. While we have had rich technology opportunities to combine with our enlightened understanding, that is not what we are seeing. What we see is still expectations that it is done in-the-head, top-down, with information dump and meaningless assessment that is not tied to organizational outcomes. And while it is not working, demonstrably, there seems little impetus to change.

Truly, there has been little change in our underlying models in 15 years. While the technology is flashier, the buzz words have mutated, and some of the faces have changed, we are still following myths like learning styles and generational differences, we are still using ‘spray and pray’ methods in learning, we are still not taking on performance support and social learning, and perhaps most distressingly, we are still not measuring what matters.

Sure, the reasons are complex. There are lots of examples of the old approaches, the tools and practices are aligned with bad learning practices, the shared metrics reflect efficiency instead of effectiveness, … the list goes on. Yet a learning & development (L&D) unit unengaged with the business units it supports is not sustainable, and consequently the lack of change is unjustifiable.

And the need is now more than ever. The rate of change is increasing, and organizations now have more need to not just be effective, but they have to become agile. There is no longer time to plan, prepare, and execute, the need is to continually adapt. Organizations need to learn faster than the competition.

The opportunities are big. The critical component for organizations to thrive is to couple optimal execution (the result of training and performance support) with continual innovation (which does not come from training). Instead, imagine an L&D unit that is working with business units to drive interventions that affect key KPIs. Consider an L&D unit that is responsible for facilitating the interactions that are leading to new solutions, new products and services, and better relationships with customers. That is the L&D we need to see!

The path forward is not easy but it is systematic and doable. A vision of a ‘performance ecosystem‘ – a rich suite of tools to support success that surround the performer and are aligned with how they think, work, and learn – provides an endpoint to start towards. Every organization‘s path will be different, but a good start is to start doing formal learning right, begin looking at performance support, and commence working on the social media infrastructure.

An associated focus is building a meaningful infrastructure (hint: one all-singing all-dancing LMS is not the answer). A strategy to get there is a companion effort. And, ultimately a learning culture will be necessitated. Yet these components are not just a necessary component for L&D, they are the necessary components for a successful organization, one that can be agile enough to adapt to the increasing rate of change we are facing.

And here is the first step: L&D has to become a learning organization. Mantras like ‘work out loud’, ‘fail fast’, and ‘reflect’ have to become part of the L&D culture. L&D has to start experimenting and learning from the experiments. Let us ensure that the past 15 years are a hibernation we emerge from, not the beginning of the end.

Here’s to change for the better.  May 2015 be the  best year yet!

Why L&D?

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One of the concerns I hear is whether L&D still has a role.  The litany is  that  they’re so far out of touch with their organization, and science, that it’s probably  better to let them die an unnatural death than to try to save them. The prevailing attitude of this extreme view is that the Enterprise Social Network is the natural successor to the LMS, and it’s going to come from operations or IT rather than L&D.  And, given that I’m on record suggesting that we revolutionize L&D rather than ignoring it, it makes sense to justify why.  And while I’ve had other arguments, a really good argument comes from my thesis advisor, Don Norman.

Don’s on a new mission, something he calls DesignX, which is scaling up design processes to deal with “complex socio-technological systems”.   And he recently wrote an article about  why  DesignX that put out a good case why L&D as well.  Before I get there, however, I want to point out two other facets  of his argument.

The first is that often design has to go  beyond science. That is, while you use science when you can, when you can’t you use theory inferences,  intuition, and more to fill in the gaps, which you hope  you’ll find out later (based upon later science, or your own data) was the right choice.  I’ve often had to do this in my designs, where, for instance, I think research hasn’t gone quite far enough in understanding engagement.  I’m not in a research position as of now, so I can’t do the research myself, but I continue to look at what can be useful.  And this is true of moving L&D forward. While we have some good directions and examples, we’re still ahead of documented research.  He points out that system science and service thinking are science based, but suggests design needs to come in beyond those approaches.   To the extent L&D can, it should draw from science, but also theory and keep moving forward regardless.

His other important point is, to me, that he is talking about systems.  He points out that design  as a craft  works well on simple areas, but where he wants to scale design is to the level of systemic solutions.  A noble goal, and here too I think this is an approach  L&D needs to consider as well.  We have to go beyond point solutions – training, job aids, etc – to performance ecosystems, and this won’t come without a different mindset.

Perhaps the most interesting one, the one that triggered this post, however, was a point on why designers are needed.  His point is that others have focuses on efficiency and effectiveness, but he  argued that  designers have empathy for the users as well.  And I think this is really important.  As I used to say the budding software engineers I was teaching interface design to: “don’t trust your intuition, you don’t think like normal people”.  And similarly, the reason I want L&D in the equation is that they (should) be the ones who really understand how we think, work, and learn, and consequently they should be the ones facilitating performance and development. It takes an empathy with users to facilitate them through change, to help them deal with fears and anxieties dealing with new systems, to understand what a good learning culture is and help foster it.

Who else would you want to be guiding an organization in achieving effectiveness in a humane way?   So Don’s provided, to me, a good point on why we might still want L&D (well, P&D really ;)  in the organization. Well, as long as they also addressing the bigger picture and not just pushing info dump and knowledge test.  Does this make sense to you?

#itashare #revolutionizelnd

Challenges in engaging learning

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I’ve been working on moving a team to deeper learning design.  The goal is to practice what I preach, and make sure that the learning design is competency-aligned, activity-based, and model-driven.  Yet, doing it in a pragmatic way.

And this hasn’t been without it’s challenges.  I  presented to the team my vision, we worked out a process, and started coaching the team during development.  In retrospect, this wasn’t proactive enough.  There were a few other hiccups.

We’re currently engaged in a much tighter cycle of development and revision, and now feel we’re getting close to the level of effectiveness  and  engagement we need.  Whether a) it’s really better, and b) whether we can replicate it yet scale it as well is an open question.

At core are a few elements. For one, a rabid focus on what learners are  doing is key.  What do they need to be able to do, and what contexts do they need to do it in?

The competency-alignment focus is on the key tasks that they have to do in the workplace, and making sure we’re preparing them across pre-class, in-class, and post-class activities to develop that ability.  A key focus is having them make the decision in the learning experience that they’ll have to make afterward.

I’m also pushing very hard on making sure that there are models behind the decisions.  I’m trying hard to avoid arbitrary categorizations, and find the principles that drove those categorizations.

Note that all this is  not easy.  Getting the models is hard when the resources  provided don’t include that information.  Avoiding presenting just knowledge and definitions is hard work.  The tools we use make certain interactions easy, and other ones not so easy.  We have to map meaningful decisions into what the tools support.  We end up making  tradeoffs, as do we all.  It’s good, but not as good as it could be.  We’ll get better, but we do want to run in a practical fashion as well.

There are more elements to weave in: layering on some general biz skills is embryonic.  Our use of examples needs to get more systematic.  As does our alignment of learning goal to practice activity.    And we’re struggling to have a slightly less didactic and earnest tone;  I haven’t worked hard enough on pushing a bit of humor in, tho’ we are ramping up some exaggeration.  There’s only so much you can focus on at one time.

We’ll be running some student tests next week before presenting to the founder.  Feeling mildly confident that we’ve gotten a decent take on quality learning design with suitable production value, but there is the barrier that the nuances of learning design are  subtle. Fingers crossed.

I still believe that, with practice, this becomes habit and easier.  We’ll see.

Transformative Experiences

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I’ve had the pleasure last  week of keynoting  Charles Sturt University’s annual Education conference.  They’re in the process of rethinking what their learning experience should be, and I talked about the changes we’re trying to make at the Wadhwani Foundation.

I was reminded of previous conversations about learning experience design and the transformative experience.   And I have argued in the past that what would make an optimal value proposition (yes, I used that phrase) in a learning market would be to offer a transformative learning experience.  Note that this is not just about the formal learning experience, but has two additional components.

Now, it does start with a killer learning experience.  That is, activity-based,  competency-driven, model-guided, with lean and compelling content.  Learners need role-plays and simulations to be immersed in practice, and scaffolded with reflection to develop their flexible ability to apply these abilities going forward.  But wait, there’s more!

As a complement, there needs to be a focus on developing the learner as well as their skills. That is, layering on the 21st Century skills: the ability to communicate, lead, problem-solve, analyze, learn, and more.  These need to be included and developed  across the learning experience.  So learners not only get the skills they need to succeed now, but to adapt as things change.

The third element is to be a partner in their success.  That is, don’t give them a chance to sink or swim on the basis of the content, but to look for ways in which learners might be struggling with other issues, and work hard to ensure they succeed.

I reckon that anyone capable of developing and delivering on this model provides a model that others can only emulate, not improve upon.  We’re working on the first two initially at the Foundation, and hopefully we’ll get to the latter soon.  But I reckon it’d be great if this were the model all were aspiring to.  Here’s hoping!

 

 

L&D and working out loud #wolweek

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This week is Working Out Loud week, and I can’t but come out in support of a principle that I think is going to be key to organizational success. And, I think, L&D has a key role to play.

The benefits from working out loud are many. Personally, documenting what you’re doing serves as a reminder to yourself and awareness for others. The real power comes, however, from taking that next level: documenting not just what you’re doing, but why. This helps you in reflecting on your own work, and being clear in your thinking. Moreover, sharing your thinking gives you a second benefit in getting others’ input which can really improve the outcome.

In addition, it gives others a couple of benefits. They get to know what you’re up to, so it’s easier to align, but if your thinking is any good, it gives them the chance to learn from how you think.

So what is the role of L&D here? I’ll suggest there are two major roles: facilitating the skills and enabling the culture.

First, don’t assume folks know what working out loud means. And even if they do, they may not be good at it in terms of knowing how to indicate the underlying thinking. And they likely will want feedback and encouragement. First, L&D needs to model it, practicing what they preach. They need to make sure the tools are easily available and awareness is shared. Execs need to be shown the benefit and encouraged to model the behavior too. And L&D will have to trumpet the benefits, accomplishments, and encourage the behavior.

None of this is really likely to succeed if you don’t have a supportive culture. In a Miranda organization, no one is going to share. Instead, you need the elements of a learning organization: the environment has to value diversity, be open to new ideas, provide time for reflection, and most of all be safe. And L&D has to understand the benefits and continue to promote them, identify problems, and work to resolve them.

Note that this is not something you manage or control. The attitude here has to be one of nourishing aka (seed, feed, and weed). You may track it, and you want to be looking for things to support or behaviors to improve, but the goal is to develop a vibrant community of sharing, not squelching anything that violates the hierarchy.

Working out loud benefits the individual and the organization in a healthy environment. Getting the environment right, and facilitating the practice, are valuable contributions, and ones that L&D can, and should, contribute to.

#itashare

#DevLearn 14 Reflections

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This past week I was at the always great DevLearn conference, the biggest and arguably best yet.  There were some hiccups in my attendance, as  several blocks of time were taken up with various commitments both work and personal, so for instance I didn’t really get a chance to peruse the expo at all.  Yet I attended keynotes and sessions, as well as presenting, and hobnobbed with folks both familiar and new.

The keynotes were arguably even better than before, and a high bar had already been set.

Neil deGrasse Tyson was eloquent and passionate about the need for science and the lack of match between school and life.    I had a quibble about his statement that doing math teaches problem-solving, as it takes the right type of problems (and Common Core is a step in the right direction)  and  it takes explicit scaffolding.  Still, his message was powerful and well-communicated. He also made an unexpected connection between Women’s Liberation and the decline of school quality that I hadn’t considered.

Beau Lotto also spoke, linking how our past experience alters our perception to necessary changes in learning.  While I was familiar with the beginning point of perception (a fundamental part of cognitive science, my doctoral field), he took it in very interesting and useful direction in an engaging and inspiring way.  His take-home message: teach not how to see but how to look, was succinct and apt.

Finally, Belinda Parmar took on the challenge of women in technology, and documented how  small changes can  make a big difference. Given the madness of #gamergate, the discussion was a useful reminder of inequity in many fields and for many.  She left lots of time to have a meaningful discussion about the issues, a nice touch.

Owing to the commitments both personal and speaking, I didn’t get to see many sessions. I had the usual situation of  good ones, and a not-so-good one (though I admit my criteria is kind of high).  I like that the Guild balances known speakers and topics with taking some chances on both.  I also note that most of the known speakers are those folks I respect that continue to think ahead and bring new perspectives, even if in a track representing their work.  As a consequence, the overall quality is always very high.

And the associated events continue to improve.  The DemoFest was almost too big this year, so many examples that it’s hard to start looking at them as you want to be fair and see all but it’s just too monumental. Of course, the Guild had a guide that grouped them, so you could drill down into the ones you wanted to see.  The expo reception was a success as well, and the various snack breaks suited the opportunity to mingle.  I kept missing the ice cream, but perhaps that’s for the best.

I was pleased to have the biggest turnout yet for a workshop, and take the interest in elearning strategy as an indicator that the revolution is taking hold.  The attendees were faced with the breadth of things to consider across advanced ID, performance support, eCommunity, backend integration, decoupled delivery, and then were led through the process of identifying elements and steps in the strategy.  The informal feedback was that, while daunted by the scope, they were excited by the potential and recognizing the need to begin.  The fact that the Guild is holding the Learning Ecosystem conference and their release of a new and quite good white paper by Marc Rosenberg and Steve Foreman are further evidence that awareness is growing.   Marc and Steve carve up the world a little differently than I do, but we say similar things about what’s important.

I am also pleased that  Mobile  interest continues to grow, as evidenced by the large audience at our mobile panel, where I was joined by other mLearnCon advisory board members Robert Gadd, Sarah Gilbert, and Chad Udell.  They provide nicely differing  viewpoints, with Sarah representing the irreverent designer, Robert the pragmatic systems perspective, and Chad the advanced technology view, to complement my more  conceptual approach.  We largely agree, but represent different ways of communicating and thinking about the topic. (Sarah and I will be joined by Nick Floro for ATD’s mLearnNow event in New Orleans next week).

I also talked about trying to change the pedagogy of elearning in the Wadhwani Foundation, the approach we’re taking and the challenges we face.  The goal I’m involved in is job skilling, and consequently there’s a real need and a real opportunity.  What I’m fighting for is to make meaningful practice as a way to achieve real outcomes.  We have some positive steps and some missteps, but I think we have the chance  to have a real impact. It’s a work in progress, and fingers crossed.

So what did I learn?  The good news is that the audience is getting smarter, wanting more depth in their approaches and breadth in what they address. The bad news appears to be that the view of ‘information dump & knowledge test = learning’ is still all too prevalent. We’re making progress, but too slowly (ok, so perhaps patience isn’t my strong suit ;).  If you haven’t, please do check out the Serious eLearning Manifesto to get some guidance about what I’m talking about (with my colleagues Michael Allen, Julie Dirksen, and Will Thalheimer).  And now there’s an app for that!

If you want to get your mind around the forefront of learning technology, at least in the organizational space, DevLearn is the place to be.

 

Neil deGrasse Tyson #DevLearn Keynote Mindmap

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Neil deGrasse Tyson opened this year’s DevLearn conference. A clear crowd favorite, folks lined up to get in (despite the huge room). In a engaging, funny, and poignant talk, he made a great case for science and learning.

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