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A richer suite of support

25 May 2016 by Clark 1 Comment

While it’s easy to talk about how we need to support the transition from novice to expert, it might help to be a little more detailed.  While it’s easy to say that the role of formal learning wanes, and the role of informal learning ramps up, what are the types of support we might look to?

I expanded a core diagram I’ve been using for quite a while, based upon earlier diagrams from  others.  It’s also been used by others, and the core of the diagram is clear, but I wanted to elaborate it. The underlying point is that as individuals gather expertise the value of formal learning drops, and the value of informal learning increases.  Ok, but what does that  mean?

InFormalSpaces It means that courses make sense for novices, who don’t know what they need nor why it’s important. As they start performing however, their needs change. They start knowing what they need, and why it’s important, and they start just needing those resources.  They can be designed or curated, but they are either performance support in the moment or learning resources that develop understanding or abilities.  For the former, we’re talking about  how-to videos, checklists, lookup tables, etc.  For the latter, we might be talking documents, documentaries, diagrams, or more interactive elements such as simulations.

At this stage we  also  need coaching and/or mentoring, and chances to communicate with our colleagues.  It’s the social work that will play a role in the development of the learner through interactions. Obviously, you can be doing communication in courses as well, and reflecting and collaborating at the practitioner stage as well, these are continua, not boxes as portrayed here.  The point, however, is that the nature of the necessary support and the activities change.

And, of course, once an individual advances far enough, there’s little anyone can be providing for them, instead they need the ‘creative friction’ of interactions with other experts and ideas to generate the new understandings that will advance the individual  and the organization.  Reflecting together, solving problems to gather, and more, are all part of the activities that individuals undertake.

These activities don’t always happen well, and can be facilitated in many ways.  There are cultural factors as well.  There is a clear need for  someone to be undertaking ensuring that these activities are happening in optimal ways in a conducive environment. It doesn’t  have  to be L&D, and it won’t be if all they do is focus on training and courses, but it should be someone who understands a bit about how we think, work, and learn.  And I don’t know another group that is better placed.  Can you?

The Human-Centered Organization

18 May 2016 by Clark 1 Comment

As I talk about aligning work with how we  brains think, work, and learn, I realize I’m talking about something bigger.  While I want L&D to lead the way (as those are the folks I know), it’s really about leading the way to an organization that’s aligned with  us, with people.  And I think that’s something bigger, and definitely better.

The point being, as we reorganize work to tap into the best of us, we’re creating organizations that are humane in a very specific, and hopefully deep, sense.  Humane for all employees, and further.

The industrial era organization, quite simply, wasn’t. The mechanization of human work, the drive for more efficiency at whatever cost, the top-down imposition of rules, and more, are all contrary to what brings out the best in people. It’s demeaning and unhealthy, but even from a business perspective  it’s rigid and inflexible.

Instead, when we talk about having work with purpose, and socially aware organizations, with tighter coupling to the market, and greater empowerment of employees, we’re talking about our finer human elements.  And, the evidence seems to be that such organizations are more successful.

Interestingly, I searched the term “Human Centered Organization”, and came across this proposal. (And, in fact, it’s now an ISO standard, 27500:2016, not that I’ve made it past the paywall to view the whole thing.) I found the  principles from the summary  to be a a good starting point:

  • capitalize on individual differences as an organizational strength
  • make usability and accessibility strategic business objectives
  • adopt a total system approach
  • ensure health, safety, and well-being are business priorities
  • value employees and create a meaningful work environment
  • be open and trustworthy
  • act in socially responsible ways

All of these reflect different areas I’ve either touted or am aware of specific work (and workers) in the area. I’d add that this should not be just internally-facing; this should reflect work with partners and customers as well.

Frankly, many companies I interact with seem driven to confuse me to the point that I make decisions that favor them. I don’t like that, and try to avoid them. A few organizations, instead, offer simple services with clear benefits.  Interestingly, when I engage with the people in the straightforward organizations, they  seem to like their employment circumstances.  When I can engage one of the others to speak to me honestly, or I know them through other channels than a business relationship, they admit they don’t like what they have to do.

OK, so I can be an idealist (and am a native Californian :), but it seems to me that organizations that move to a more humane approach are going to be the ones that will last.  There are known concrete steps to get there, but the path will vary by organization. I suggest that you start thinking about your strategy. Are you ready to get human?

Reading List additions

17 May 2016 by Clark Leave a Comment

I’ve been reading a few other books, and have written up some book reviews on two of them.

For the Revolution Reading List, I  strongly encourage you to read Amy Edmondson’s  Teaming, it’s a great review of the needed changes for organizations to embrace innovation.  My eLearn Mag review is here.

For no specific list, but as a book that was really transformational for my thinking, Todd Rose’s  The End of Average  really helped point out the problems with our current obsession with simplistic evaluations of people.  My review for eLearn Mag is here.

And some thoughts on Doug Engelbart, a visionary who’s contributed greatly  to our thinking can be seen in this article for Learning Solutions, here.

As always, I welcome hearing your thoughts on these, or your own recommendations!

Moving forward

11 May 2016 by Clark Leave a Comment

I’ve argued before that there’s a pretty clear path forward for organizations.  The necessity to become agile means that the old ‘command and control’ approach won’t cut it any longer. What’s required is tapping into the ability of people to work together.  The new structure is focused on teams (stayed tuned for my review of Amy Edmondson’s Teaming) that  are given the tasks to solve problems, trouble shoot, design new products and services, and generally continue to adapt.  In short, to learn. And I want to talk about the L&D role here, at least the potential one.

Certain elements are required.  The teams need  a number of things to be effective.  They have  to be given  meaningful tasks, to have the freedom to pursue them, to have the ability to experiment (and fail) as necessary, and to be accountable.  To collaborate successfully to accomplish their goals, they need certain features internally:  they need to have diverse representation, be open to new ideas, have time for reflection, and it has to  be safe to contribute.

This takes a new approach from the organization. It takes leadership to make such a culture, and the culture itself has to make it possible for these to occur and to get people to be motivated to contribute.  Two  elements really contribute: contribution,  and transparency.  People need to know what each other is doing, and be willing to chip in and assist.  This happens both within teams and beyond.

So what is L&D’s role?  First, to model the desired behavior. L&D should be practicing what it preaches in experimenting and continually improving. There should be teams assigned to tasks, and the practitioners should be acting as members of their communities.   They should be evangelizing, piloting, and sharing their successes with this approach, while continually learning more.

Then, L&D should be working with others as teams to meet their client needs.  They should be working to innovate around the solutions.  They should be promoting and executing on pilots that get fleshed out.  And they should be gradually raising awareness about the processes and the culture.

Done well, this movement reduces turnover, increases engagement, and produces better outcomes.  It’s not trivial; there are nuances and challenges that will have to be addresses.  On the other hand, evidence is converging that this  is the future of business. So are you preparing for it, or waiting to be blind-sided?  If you’re looking for guidance in getting going, I’m easy to find.

 

Two separate systems?

10 May 2016 by Clark Leave a Comment

I frequently say that L&D needs to move from just ensuring optimal execution to also supporting continual innovation.  Can these co-exist, or are they fundamentally different?  I really don’t know, but it’s worth pondering.

Kotter (the change management guru), has begun to advocate for a dual-operating system approach, where companies jointly support an operational hierarchy and an innovation network that are coupled.  I haven’t read his book on the topic, but it seems to be a bit  extrinsic, a way of bolting on innovation instead of making it intrinsic to the operation.

On the other hand, there is quite a bit of expression for more flexible systems, a more podular approach. Teaming or small nodes are increasingly appearing as not just for innovation, but ongoing operation. However, it’s not clear how the various different areas are coordinated, so how marketing across pods maintains coherent.

CoherentOrgExpandedThis is what led to our Coherent Organization model.  The notion is that the teams are coming in from, and reporting back up through, their communities. And their communities are communicating both within, and outside of, the organization.

It’s not clear to me whether the team  approach can scale to a global organization, or whether you need the hybrid model.  I can see that the hybrid model would appeal to existing business folks who would be concerned about optimization in execution.  I can see that the new model would at least require fundamental changes in mechanisms, and perhaps a willingness to tradeoff absolute perfection in execution to maintain continuing innovation and customer-responsiveness.

While  intuitively the more biologically inspired approach sounds like the longer-term solution, it’s non-trivial in terms of creating cultures that are appropriately conducive.  I think that organizational operations may be at an inflection point, and there does seem to be data that supports more radical flexibility.   I think a performance ecosystem coupled with a learning organization environment is likely going to be the way to move.  How you get there is part of the revolution that’s needed. Start small, scale out, etc. And I hope L&D can help lead the way.

Learning in Context

4 May 2016 by Clark 1 Comment

In a recent guest post, I wrote about the importance of context in learning. And for a featured session at the upcoming FocusOn Learning event, I’ll be talking about performance support in context.  But there was a recent question about how you’d do it in a particular environment, and that got me thinking about the the necessary requirements.

As context (ahem), there are already context-sensitive systems. I helped lead the design of one where a complex device was instrumented and consequently there were many indicators about the current status of the device. This trend is increasing.  And there are tools to build context-sensitive helps systems around enterprise software, whether purchased or home-grown. And there are also context-sensitive systems that track your location on mobile and allow you to use that to trigger a variety of actions.

Now, to be clear, these are already in use for performance support, but how do we take advantage of them for learning. Moreover, can we go beyond ‘location’ specific learning?  I think we can, if we rethink.

So first, we  obviously  can use those same systems to deliver specific learning. We can have a rich model of learning around a system, so a detailed competency map, and then with a rich profile of the learner we can know what they know and don’t, and  then when they’re at a point where there’s a gap between their knowledge and the desired, we can trigger some additional information. It’s in context, at a ‘teachable moment’, so it doesn’t necessarily have to be assessed.

This would be on top of performance support, typically, as they’re still learning so we don’t want to risk a mistake. Or we could have a little chance to try it out and get it wrong that  doesn’t actually get executed, and then give them feedback and the right answer to perform.  We’d have to be clear, however, about why learning is needed in  addition to the right answer: is this something that  really needs to be learned?

I want to go a wee bit further, though; can we build it around what the learner is doing?  How could we know?  Besides increasingly complex sensor logic, we can use  when they are.  What’s on their calendar?  If it’s tagged appropriately, we can know at least what they’re  supposed to be doing.  And we can develop not only specific system skills, but more general business skills: negotiation, running meetings, problem-solving/trouble-shooting, design, and more.

The point is that our learners are in contexts all the time.  Rather than take them away to learn, can we develop learning that wraps around what they’re doing? Increasingly we can, and in richer and richer ways. We can tap into the situational motivation to accomplish the task in the moment, and the existing parameters, to make ordinary tasks into learning opportunities. And that more ubiquitous, continuous development is more naturally matched to how we learn.

Showing my age, er, experience

3 May 2016 by Clark Leave a Comment

I’ve been reading What the Dormouse Said (How the Sixties Counterculture Shaped the Personal Computer Industry), and it’s bringing back some memories.  Ok, so most of this stuff is older than I am, but there are a few connections, so it’s reminiscing time.  I’ve said some of this before, I believe, so feel free to wander on.  This is me just thinking aloud.

I was taking some computer science classes because I’d found out that biology was rote memorization and cut-throat medical (which I did  not want to do; I was hoping for marine bio), and a buddy was doing it.  Given that I was at UCSD at the time, I naturally learned  UCSD Pascal (as well as Fortran, which I fortunately forgot almost immediately, and Mixal likewise). I enjoyed algorithms, however, and could solve problems. I also was enchanted with AI (despite my first prof).  And I was  tutoring for some extra pocket money, math and science (even classes I hadn’t taken yet!).

Then I got a job doing the computer support for the office that did the tutoring (literally carrying decks of cards in Algol to run through the computer center). And a light went off; computers for learning!  There was no major then at my school, but there was a program to design my own major, and I found a couple of professors willing to serve as my advisors  (thank you, Hugh Mehan and Jim Levin). They even let me work on a project with them (email for classroom discussion, circa 1978; we had ARPANET, the predecessor to the internet).  It eventually even got published as a journal article.

I called all over the country, trying to find someone who needed a person interested in computer learning.  I even interviewed at Xerox PARC with John Seely Brown, courtesy of Tom Malone (I didn’t get the job; they wanted something I’d done but I didn’t know their term for it!).  After a small job doing some statistical work for a research project, I managed to get a job designing and programming educational computer games for DesignWare (you can still play some of  the products here, the magic of  the internet).  We went from Basic to Forth (for speed and small size), though I later moved away from coding with the demise of HyperCard ;).

And the main connection to the cool stuff, besides the interview at PARC, was visiting the West Coast Computer Faire.  It was cool in and of itself, but there I met David Suess, who along with Bill Bowman was starting Spinnaker, a company to do home educational software.  DesignWare had been doing games to go along with publisher offerings, and I was pushing  the home market.  After a conversation, I introduced David to my boss Jim Schuyler (Sky) and off we went. As a reward, I got to do FaceMaker. Eventually, DesignWare started doing it’s own titles, and I also did Spellicopter and Creature Creator before I realized I wanted to go back to grad school.

Along the way I also read Byte magazine and tracked efforts like SmallTalk and folks like Alan Kay.  I’ve subsequently had the pleasure to meet him, as well as  Doug Engelbart and Ted Nelson, so I’ve somewhat closed the loop on those heady days.  There’s much more between then and now, but that’s enough for one post. And most of my counterculture experiences were behind me by that time, so I didn’t really get a chance to see those connections, but it was an exciting time, and a great exposure to the possibilities.

Moving forward

27 April 2016 by Clark Leave a Comment

A few weeks ago, I posted about laying out activities in a  space dividing the execution side from the innovation side, and in the head from in the world.  None of you took the bait about talking what it meant (I’m  so disappointed), but it continued to ponder it myself. And at least one idea came to mind.

LearningSpaceImplicationsSo what I’m thinking is that the point is to  not be using our heads to be doing simple execution. Machines (read: robots or computation agents) are very good at doing what they’re told. Reliably, and repeatably.  They may need oversight, but in many ways we’re seeing this play out.

What we should be doing is trying to automate execution. We aren’t good at doing rote things, and having us do them is silly.  Ideally you automate them, or outsource them in some way.  Let’s save our minds for doing important work.

Of course, many times the situations we’re increasingly seeing are not matters of simply executing. As things get more ambiguous, more novel, more  chaotic, we’re really discovering we need to have people handle those situations in innovative ways. So they’re really being moved over regardless.

And, of course, we want that innovation to be fueled by data, information in the world being made available to support making these decisions. Big analytics, or even little analytics are good basis, as are models and support tools to facilitate the processes.  And, of course, this doesn’t have to be all in one head, but drawing upon teams, communities, and networks to get solution.

The real point is to let machines do what they can do well, and leave to us what we do well. And, what we  want to be responsible for.  As I see it, the role of technology is to augment us, not replace us.  It’s up to us to make the choices, but we have the opportunity to work in ways that align with how our brains really think, work, and learn.  I reckon that choice is a no-brainer ;).

Learning in context

26 April 2016 by Clark 3 Comments

In preparation for the upcoming FocusOn Learning Conference, where I’ll be running a workshop  about cognitive science for L&D, not just for learning but also for mobile and performance support, I was thinking about how  context can be leveraged to provide more optimal learning  and performance.  Naturally, I had to diagram it, so let me talk through it, and you let me know what you think.

ApartLearningWhat we tend to do, as a default, is to take people away from work, provide the learning resources away from the context, then create a context to practice in. There are coaching resources, but not necessarily the performance resources.  (And I’m not even mentioning the typical lack of sufficient practice.) And this makes sense  when the consequences of making a mistake on the task are irreversible and costly.  E.g. medicine, transportation.  But that’s not as often as we think. And there’s an alternative.

We can wrap the learning around the context.  Our individual is  in the world, and performing the  task. There can  be coaching (particularly at the start, and then gradually removed as the individual  moves to acceptable competence). There are also performance resources – job aids, checklists, etc – in the environment. There also  can be learning resources, so the individual can continue to self-develop, particularly in the increasingly likely situation that the task has some ambiguity or novelty in it. Of course, that only works if we have a learner  capable of self learning (hint hint).

The problems with always taking people away from their jobs are multiple:

  • it is costly to interrupt their performance
  • it can be costly to create the artificial context
  • the learning has a lower likelihood to make it back to the workplace

Our brains don’t learn in an event model, they learn in little bits over time. It’s more natural,  more  effective, to dribble the learning out at the moment of need, the learnable moment.  We have the capability, now, to  be more aware of the learner, to deliver support in the moment, and develop learners over time. The way their brains actually learn.  And we should be doing this.  It’s more effective as well as more efficient.  It requires moving out of our comfort zone; we know the classroom, we know training.  However, we now also know that the effectiveness of classroom training can be very limited.

We have the ability to start making learning effective as well as efficient. Shouldn’t we do so?

Deeper Learning Reading List

20 April 2016 by Clark 3 Comments

So, for my last post, I had the Revolution Reading List, and it occurred to me that I’ve been reading a bit about deeper learning design, too, so I thought I’d offer some pointers here too.

The starting point would be Julie Dirksen’s Design For How People Learn (already in it’s 2nd edition). It’s a very good interpretation of learning research applied to design, and very readable.

A new book that’s very good is Make It Stick, by Peter Brown, Henry Roediger III, and Mark McDaniel, the former being a writer who’s worked with two scientists to take learning research into 10 principles.

And let me mention two Ruth Clark books. One with Dick Mayer from UCSB, e-Learning and the Science of Instruction, that focuses on the use of media.  A second with Frank Nguyen and the wise John Sweller, Efficiency in Learning, focuses on cognitive load (which has many implications, including some overlap with the first).

Patti Schank has come out with a concise compilation of research called The Science of Learning that’s available to ATD members. Short and focused with her usual rigor.  If you’re not an ATD member, you can read her  blog posts that contributed (click ‘View All’).

Dorian Peters book on Interface Design for Learning also has some good learning principles as well as interface design guidance.  It’s not the same for learning as for doing.

Of course, a classic is a compilation of research by a blue-ribbon team lead by John Bransford,  How People Learn, (online or downloadable).  Voluminous, but pretty much state of the art.

Another classic is  the Cognitive Apprenticeship  model of Allen Collins & John Seely Brown. A holistic model abstracted across some seminal work, and quite readable.

The Science of Learning Center has an academic integration of research to instruction theory by Ken Koedinger, et al,  The Knowledge-Learning-Instruction Framework, that’s freely available as a PDF.

I’d be remiss if I don’t point out the Serious eLearning Manifesto, which has 22 research principles underneath the 8 values that differentiate serious elearning from typical versions.  If you buy in, please sign on!

And, of course, I can point you to my own series for Learnnovators on Deeper ID.

So there you go with some good material to get you going. We need to do better at elearning, treating it with the importance it deserves.  These don’t necessarily tell you how to redevelop your learning design processes, but you know who can help you with that.  What’s on your list?

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