Learnlets
Clark Quinn's Learnings about Learning

I’ve earlier talked about the importance of failure in learning, and now it’s revealed that Apple’s leadership development program plays that up in a big way.  There are risks in sharing, and rewards. And ways to do it better and worse.

In an article in Macrumors (obviously, an Apple info site), they detail part of Adam Lashinsky’s new Inside Apple book that reports on Apple executive development program.  Steve Jobs hired a couple of biz school heavyweights to develop the program, and apparently “Wherever possible the cases shine a light on mishaps…”.  They use examples from other companies, and importantly, Apple’s own missteps.

Companies that can’t learn from mistakes, their own and others’, are doomed to repeat them.  In organizations where it’s not safe to share failures, where anything you say can and will be held against you, the same mistakes will keep getting made.  I’ve worked with firms that have very smart people, but their culture is so aggressive that they can’t admit errors.  As a consequence, the company continues to make them, and gets in it’s own way.  However, you don’t want to celebrate failure, but you do want to tolerate it. What can you do?

I’ve heard a great solution.  Many years ago now, at the event that led to Conner’s & Clawson’s Creating a Learning Culture, one small company shared their approach: they ring a bell not when the mistake is made, but when the lesson’s learned.  They’re celebrating – and, importantly,  sharing – the learning from the event.  This is a beautiful idea, and a powerful opportunity to use social media when the message goes beyond a proximal group.

There’s a lot that goes on behind this, particularly in terms of having a culture where it’s safe to make mistakes  Culture eats strategy for breakfast, as the saying goes..  What is a problem is making the same mistake, or dumb mistakes.  How do you prevent the latter?  By sharing your thinking, or thinking out loud, as you develop your planned steps.

Now, just getting people sharing isn’t necessarily sufficient.  Just yesterday (as I write), Jane Bozarth pointed me towards an article in the New Yorker (at least the abstract thereof) that argues why brainstorming doesn’t work.  I’ve said many times that the old adage “the room is smarter than the smartest person in the room” needs a caveat: if you manage the process right.  There are empirical results that guide what works from what doesn’t, such as: having everyone think on their own first; then share; focus initially on divergence before convergence; make a culture where it’s safe, even encouraged, to have a diversity of viewpoints; etc.

No one says getting a collaborating community is easy, but like anything else, there are ways to do it, and do it right.  And here too, you can learn from the mistakes of others…

After my post trying to characterize the differences between tablets and mobile, Amit Garg similarly posted that tablets are different. He concludes that “a conscious decision should be made when designing tablet learning (t-learning) solutions”, and goes further to suggest that converting elearning or mlearning directly may not make the most sense.  I agree.

As I’ve suggested, I think the tablet’s not the same as a mobile phone. It’s not always with you, and consequently it’s not ready for any use.  A real mobile device is useful for quick information bursts, not sustained attention to the device.  (I’ll suggest that listening to audio, whether canned or a conversation, isn’t quite the same, the mobile device is a vehicle, not the main source of interaction.)  Tablets are for more sustained interactions, in general. While they can be used for quick interactions, the screen size supports more sustained interactions.

So when do you use tablets?  I believe they’re valuable for regular elearning, certainly.  While you would want to design for the touch screen interface rather than mimic a mouse-driven interaction.  Of course, I believe you also should not replicate the standard garbage elearning, and take advantage of rethinking the learning experience, as Barbara Means suggested in the SRI report for the US Department of Education, finding that eLearning was now superior to F2F.  It’s not because of the medium itself, but because of the chance to redesign the learning.

So I think that tablets like the iPad will be great elearning platforms. Unless the task is inherently desktop, the intimacy of the touchscreen experience is likely to be superior.  (Though more than Apple’s new market move, the books can be stunning, but they’re not a full learning experience.)  But that’s not all.

Desktops, and even laptops don’t have the portability of a tablet. I, and others, find that tablets are taken more places than laptops. Consequently, they’re available for use as performance support in more contexts than laptops (and not as many as smart or app phones).  I think there’ll be a continuum of performance support opportunities, and constraints like quantity of information (I’d rather look at a diagram on a tablet) constraints of time & space in the performance context, as well as preexisting pressures for pods (smartphone or PDA) versus tablets will determine the solution.

I do think there will be times when you can design performance support to run on both pads and pods, and times you can design elearning for both laptop and tablet (and tools will make that easier), but you’ll want to do a performance context analysis as well as your other analyses to determine what makes sense.

I was boarding a plane away from home as Apple’s announcement was happening, so I haven’t had the chance to dig into the details as I normally would, but just the news itself shows Apple is taking on yet another industry. What Apple did to the music industry is  a closer analogy to what is happening here than what they did to the phone industry, however.

As Apple recreated the business of music publishing, they’re similarly shifting textbook publishing. They’ve set a price cap (ok, perhaps just for high school, to begin), and a richer target product. In this case, however, they’re not revolutionizing the hardware, but the user experience, as their standard has a richer form of interaction (embedded quizzes) than the latest ePub standard they’re building upon.  This is a first step towards the standard I’ve argued for, with rich embedded interactivity (read sims/games).

Apple has also democratized the book creation business, with authoring tools for anyone. They have kind of done that with GarageBand,  but this is easier.  Publishers will have the edge on homebrew for now, with a greater infrastructure to accommodate different state standards, and media production capabilities or relationships.  That may change,  however.

Overall, it will be interesting to see how this plays out. Apple, once again making life fun.

I was thinking today (on my plod around the neighborhood) about how come we’re still seeing so much garbage elearning (and frankly, I had a stronger term in mind).  And it occurred to me that their are multitudinous explanations, but it’s got to stop.

One of the causes is unenlightened designers. There are lots of them, for lots of reasons: trainers converted, lack of degree, old-style instruction, myths, templates, the list goes on. You know, it’s not like one dreams of being an instructional designer as a kid.  This is not to touch on their commitment, but even if they did have courses, they’d likely still not be exposed to much about the emotional side, for instance. Good learning design is not something you pick up in a one week course, sadly.  There are heuristics (Cat Moore’s Action mapping, Julie Dirksen’s new book), but the necessary understanding of the importance of the learning design isn’t understood and valued.  And the pressures they face are overwhelming if they did try to change things.

Because their organizations largely view learning as a commodity. It’s seen as a nice to have, not as critical to the business.  It’s about keeping the cost down, instead of looking at the value of improving the organization.  I hear tell of managers telling the learning unit “just do that thing you do” to avoid a conversation about actually looking at whether a course is the right solution, when they do try!  They don’t know how to hire the talent they really need, it’s thin on the ground, and given it’s a commodity, they’re unlikely to be willing to really develop the necessary competencies (even if they knew what they are).

The vendors don’t help. They’ve optimized to develop courses cost-effectively, since that’s what the market wants. When they try to do what really works, they can’t compete on cost with those who are selling nice looking content, with mindless learning design.  They’re in a commodity market, which means that they have to be efficiency oriented.  Few can stake out the ground on learning outcomes, other than an Allen Interactions perhaps (and they’re considered ‘expensive’).

The tools are similarly focused on optimizing the efficiency of translating PDFs and Powerpoints into content with a quiz. It’s tarted up, but there’s little guidance for quality.  When it is, it’s old school: you must have a Bloom’s objective, and you must match the assessment to the objective. That’s fine as far as it goes, but who’s pushing the objectives to line up with business goals?  Who’s supporting aligning the story with the learner? That’s the designer’s job, but they’re not equipped.  And tarted up quiz show templates aren’t the answer.

Finally, the folks buying the learning are equally complicit. Again, they don’t know the important distinctions, so they’re told it’s soundly instructionally designed, and it looks professional, and they buy the cheapest that meets the criteria.  But so much is coming from broken objectives, rote understanding of design, and other ways it can go off the rails, that most of it is a waste of money.

Frankly, the whole design part is commoditized.  If you’re competing on the basis of hourly cost to design, you’re missing the point. Design is critical, and the differences between effective learning and clicky-clicky-bling-bling are subtle.  Everyone gets paying for technology development, but not the learning design.  And it’s wrong.  Look, Apple’s products are fantastic technologically, but they get the premium placing by the quality of the experience, and that’s coming from the design.  It’s the experience and outcome that matters, yet no one’s investing in learning on this basis.

It’s all understandable of course (sort of like the situation with our schools), but it’s not tolerable.  The costs are high:meaningless  jobs, money spent for no impact, it’s just a waste.  And that’s just for courses; how about the times the analysis isn’t done that might indicate some other approach?  Courses cure all ills, right?

I’m not sure what the solution is, other than calling it out, and trying to get a discussion going about what really matters, and how to raise the game. Frankly, the great examples are all too few. As I’ve already pointed out in a previously referred post, the awards really aren’t discriminatory. I think folks like the eLearning Guild are doing a good job with their DevLearn showcase, but it’s finger-in-the-dike stuff.

Ok, I’m on a tear, and usually I’m a genial malcontent.   But maybe it’s time to take off the diplomatic gloves, and start calling out garbage when we see it.  I’m open to other ideas, but I reckon it’s time to do something.

I was defending Kirkpatrick’s levels the other day, and after being excoriated by my ITA colleagues, I realized there was not only a discrepancy between principle and practice, but between my interpretation and as it’s espoused.  Perhaps I’ve been too generous.

The general idea is that there are several levels at which you can evaluate interventions:

1. whether the recipient considered the intervention appropriate or not
2.  whether the recipient can demonstrate new ability after the intervention
3. whether the intervention is being applied in the workplace, and
4. whether the intervention is impacting desired outcomes.

That this is my interpretation became abundantly clear.  But let’s start with what’s wrong in practice.

In practice, first, folks seem to think that just doing level 1 (‘smile sheets’) is enough. Far fewer people take the next logical step and assess level 2. When they do, it’s too often a knowledge test.  Both of these fail to understand the intention: Kirkpatrick (rightly) said you have to start at level 4. You have to care about a business outcome you’re trying to achieve, and then work backwards: what performance change in the workplace would lead to the desired outcome. Then, you can design a program to equip people to perform appropriately and determine whether they can, and finally see if they like it.  And, frankly, level 1 is useless until you finally have had the desired impact, and then care to ensure a desirable user experience.  As a standalone metric, it ranks right up there with measuring learning effectiveness by the pound of learners served.

Now, one of the things my colleagues pointed out to me, beyond the failure in implementation, is that Kirkpatrick assumes that it has to be a course.  If it’s just misused, I can’t lay blame, but my colleagues proceeded to quote chapter and verse from the Kirkpatrick site to document that the Kirkpatricks do think courses are the solution. Consequently, any mention of Kirkpatrick only reinforces the notion that courses are the salve to all ills.

Which I agree is a mindset all too prevalent, and so we have to be careful of any support that could lead a regression to the status quo.  Courses are fine when you’ve determined that a skill gap is the problem.  And then, applying Kirkpatrick starting with Level 4 is appropriate.  However, that’s more like 15% of the time, not 100%.

So where did I go wrong?  As usual, when I look at models, I abstract to a useful level (my PhD focused on this, and Felice Ohrlich did an interesting study that pointed out how the right level of abstraction is critical).  So, I didn’t see it tied to courses, but that it could in principal be used for performance support as well (at least, levels 3 and 4).  I think also at least for some social learning interventions.

Moreover, I was hoping that by starting at level 4, you’d look to the outcome you need, and be more likely to look at other solutions as well as courses.  But I had neglected to note the pragmatic issue that the Kirkpatrick’s imply courses are the only workplace intervention to move the needles, and that’s not good.  So, from now on I’ll have to be careful in my reference to Kirkpatrick.

The model of assessing the change needed and working backward is worthwhile, as is doing so systematically.  Consequently, at an appropriate level of abstraction, the model’s useful.  However, in it’s current incarnation it carries too much baggage to be recommended without a large amount of qualification.

So I’ll stick to talking about impacting the business, and determining how we might accomplish that, rather than talk about levels, unless I fully qualify it.

I’ve been using the tag ‘learning experience design strategy’ as a way to think about not taking the same old approaches of events über ales.  The fact of the matter is that we’ve quite a lot of models and resources to draw upon, and we need to rethink what we’re doing.

The problem is that it goes far beyond just a more enlightened instructional design, which of course we need.  We need to think of content architectures, blends between formal and informal, contextual awareness, cross-platform delivery, and more.  It involves technology systems, design processes, organizational change, and more.  We also need to focus on the bigger picture.

Yet the vision driving this is, to me, truly inspiring: augmenting our performance in the moment and developing us over time in a seamless way, not in an idiosyncratic and unaligned way.  And it is strategic, but I’m wondering if architecture doesn’t better capture the need for systems and processes as well as revised design.

This got triggered by an exercise I’m engaging in, thinking how to convey this.  It’s something along the lines of:

The curriculum’s wrong:

• it’s not knowledge objectives, it’s skills
• it’s not current needs, it’s adapting to change
• it’s not about being smart, it’s about being wise

The pedagogy’s wrong:

• it’s not a flood, but a drip
• it’s not knowledge dump, it’s decision-making
• it’s not expert-mandated, instead it’s learner-engaging
• it’s not ‘away from work’, it’s in context

The performance model is wrong:

• it’s not all in the head, it’s distributed across tools and systems.
• it’s not all facts and skill, it’s motivation and confidence
• it’s not independent, it’s socially developed
• it’s not about doing things right, it’s about doing the right thing

The evaluation is wrong:

• it’s not seat time, it’s business outcomes
• it’s not efficiency, at least until it’s effective
• it’s not about normative-reference, it’s about criteria

So what does this look like in practice?   I think it’s about a support system organized so that it recognizes what you’re trying to do, and provides possible help.  On top of that, it’s about showing where the advice comes from, developing understanding as an additional light layer.  Finally, on top of that, it’s about making performance visible and looking at the performance across the previous level, facilitating learning to learn. And, the underlying values are also made clear.

It doesn’t have to get all that right away.  It can start with just better formal learning design, and a bit of content granularity. It certainly starts with social media involvement.  And adapting the culture in the org to start developing meta-learning.  But you want to have a vision of where you’re going.

And what does it take to get here?  It needs a new design that starts from the performance gap and looks at root causes. The design process then onsiders what sort of experience would both achieve the end goal and the gaps in the performer equation (including both technology aids and knowledge and skill upgrades), and consider how that develops over time recognizing the capabilities of both humans and technology, with a value set that emphasis letting humans do the interesting work.  It’ll also take models of content, users, context, and goals, with a content architecture and a flexible delivery model with rich pictures of what a learning experience might look like and what learning resources could be.  And an implementation process that is agile, iterative, and reflective, with contextualized evaluation.  At least, that sounds right to me.

Now, what sounds right to you: learning experience design strategy, performance system design, performance architecture, <your choice here>?

My colleague Harold Jarche pointed me to a post by Dave Snowden about deliberative practice, which I found interesting for a facet not part of the key article (which makes worthwhile points).  Among a list of important requirements for meaningful activity that is part of effective learning (i.e. it’s not just 10K hours of practice that makes an expert, but what sort of practice has an effect), Dave cites that “at least half of … experiments should fail”.  Think about that for a minute.

What that’s saying is that at least half of the money you invest in new things could be conceived of as being wasted.  You might be considered a very ineffective manager if 50% of your investments don’t yield returns!  Now, first of all, I’m sure you recognize that failed experiments aren’t a complete waste, as long as you learning something (“when you lose, don’t lose the lesson” as the saying goes).  Still, 50%  might still seem like a high failure rate.  But is low risk really good?

I remember hearing a talk by a Canadian AI researcher (who’s name escapes me after all these years) who had studied the optimal ratio of success to failures in helping a system learn. Now this was particular to the learning algorithm he’d chosen, but his result was roughly that you learned fastest if you failed two-thirds of the time, or around 67% failure.  Now that’d be pretty disheartening, but if you could take emotion out of the equation, e.g. made it safe to fail, would learning faster be a big enough argument to support bigger failure?

It depends on a lot: on how well you discern the lessons from failure, how well you tolerate failure, how much social scrutiny and how tolerant that public viewpoint is, but it’s interesting to contemplate what might be an optimal context for failure, and given that, what would be the fastest way to learn, and capitalize on that learning.  You want your experiments to be designed in the first place to yield maximum information, but if they do, what would a valuable success rate be?

I do believe that they who adapt fastest will be the survivors.  That adaptation may be subconscious, but I think conscious reflection is a valuable component.  Certainly for sharing the learning, so no one else has to make the same mistakes.  So are you learning just as fast as you can?

On this, the shortest day of the year here in the northern hemisphere, it seems like a good time to reflect on the past year and look forward to the coming one.  It’s certainly been an interesting year, and a good one personally.  I feel there are lots of reasons to hope for good things to be coming too.  The opportunities are big.

First of all, mobile really has taken off.  I know that many people are still wondering about how to take advantage of mobile, but awareness of the opportunities are growing. I’ve conducted several mobile brainstorming sessions with clients who have started with some apps and are looking to go further. I think more should be thinking about mobile from a strategy perspective as well.  While an initial initiative or two is ok, you have to recognize that mobile is a platform upon which solutions are created, and consequently the approach should go beyond just individual development efforts.  Still, the benefits of supporting workers wherever and whenever they are can make some big impacts on organizational outcomes.

Another area of excitement is social and informal learning. Even firms that have big concerns about security and government scrutiny are finding that they need to address it, and are beginning steps. Hey, if the CIA can deal with it, your organization can.  With the ITA in particular we have been successful in getting some traction in this area, and hope to help more organizations come to grips in the coming year.  The chance to really accelerate innovation and more is hard to ignore.

And I personally am excited about more activity around content: about more quality design, more structure around the content, and more awareness of the need for architectural work around it. I was thrilled to hear more discussion about this in a number of forums, and I think the opportunities to capitalize on finely granulated and articulated content will provide flexibility and personalization going forward.

Finally, it does appear more organizations are getting the message about moving to a strategic position in terms of learning technology.  And, of course, that means getting strategic about learning (big ‘L’ learning), and then aligning with the overall organization strategy. Of course, such an effort will not only result in better outcomes for the organization but also more credibility for the L&D group.

I’m really grateful to all those who’ve had a role in the past year (and in my past, period) in co-developing new understandings, and I look forward to more opportunities in the coming year.

This week, #change11 is being hosted by Jan Herrington (who I had the pleasure of meeting in West Australia many years ago; highly recommended). She’s talking about authentic learning, and has a nice matrix separating task type and setting to help characterize her approach.  It’s an important component of making our learning more effective.  On the way home from my evening yesterday, I wrote up some notes about a learning event I attended, that seem to be perfectly appropriate in this context:

I’ve been monitoring the comments on my #change11 posts, and rather than address them individually, I’m posting responses.  So, a couple of questions have recurred about the slow learning concept.  One is how the notion of quick small bites reflects a slower learning process.  Another is how it might play out in the organization.  And a final one is about the overall pedagogy.

To address the first one, the notion is that the learnings are wrapped around the events in your life, not where you’re taken away from the context of your life to have a learning experience.  I think of this as embedded learning versus event learning.  Yes, it’s quick bits, but they don’t mean as much on their own as in their cumulative effect over time.  Whereas the cumulative effect of the event model dissipates quickly, the distributed model builds slowly!

To address the pedagogy, it’s about having little bits of extra information that connect to the events in your life, not separate (unless the events in your life aren’t frequent enough, and then we might create little ‘alternate reality’ events that create plausible and fun scenarios that also provide the desired practice to develop you on the path.  It’s not breaking up event-based learning into smaller chunks so much as wrapping around the meaningful events in your life, when possible.

And that pedagogy will very much be our choice.  I do hope we can take the opportunity to include a sufficient level of challenge, and the opportunity to personalize it, rather than keep it generic. Consider minimalist approaches, weave in learning-to-learn, connecting people as well as providing additional information.  For instance, we should be asking personalization questions afterward (whether via system or person).  The algorithms hopefully will have some serendipity as well as relationships to my personal experience.  Some elliptical material. This would support discovering new relationships in learning, as well, as we mine the effects of some random juxtapositions across many experiences.

How to make this practical in organizations worried about immediate productivity?  In my experience, it’s already happening. Folks are (trying) to take responsibility for their learning.  They take the social media cigarette breaks to go out and connect to their networks when the office blocks access through the firewall.  They’re discussing work topics in LinkedIn groups, and using Twitter to both track new things and to get questions answered.  The question really is whether orgs will ignore or hamper this versus facilitating it.  That’s why I’m part of the Internet Time Alliance, where we are working with organizations to help them start supporting learning, not just offering training.

We do see small bits of moves toward slow learning, but I don’t like to assume everyone’s yet capable of taking ownership of it. And, yes, the sad state of the world is that typical schooling and old-style management can squelch the love of learning and not develop the skills that are needed.  We have multiple challenges, and I’m just suggesting the concept of slow learning, a drip-irrigation versus flood metaphor, is a wedge to help drive us out of the event-based model and start addressing the issues raised: pedagogy, curricula, infrastructure, technology, politics, and more.  The efforts to build such a system, I reckon, will force progress on many fronts.  Whether it’s the best approach to do that is a separate question. I welcome your thoughts.

And a thanks to all for their participation this week, it’s been a learning experience for me as well!