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

16 February 2017

Tackling the tough stuff

Clark @ 8:07 am

tacklingI was reflecting a wee bit on my books (and writings in general), and realized that there’s somewhat of a gap when I talk about games, and mobile, and more.  And it’s not unconscious, but instead principled, even if it arises somewhat implicitly. So I thought I’d talk briefly about why I tend to focus on the design, and not the practical implementations. Briefly, I think the places we fall short are not in executing, but in conceptualizing. And so I focus on tackling what I think is the tough stuff. I think we need to address the things that are more complex. My claim is that if we understand them, we have a better chance of achieving our goals and delivering the necessary outcomes.

I have stated before that I think we can implement most anything we can conceive, the problem is that our conceptions are limited.  So, I talk about design based on knowing how we think, work, and learn. I think we need these foundations if we’re truly going to realign what we do to actually work.  Frankly, I think we’re working under some misapprehensions (read: myths) that are limiting our ability to succeed.

When I talk about thinking, the myth is that it’s all in our head and logically principled.  It turns out that, instead, our thinking is very biased by circumstance and pre-existing beliefs, and we avoid effortful work.  We trust our instincts in far more circumstances than we should!  Similarly, we distribute our thinking across the world: our tools and representations assist us, and yet we don’t focus enough effort on ensuing that those are effectively designed.  There’s a real possibility for a valuable shift here.

My focus in working is to recognize that it’s not as individual as our business processes would assume. The ‘individual innovator’ myth is busted, and the empirical results are that we get better outputs when we work together. Certainly for innovation and creative work. Yet we isolate our work, assigning individual resources.  Similarly, people work best when given meaningful goals, but instead we micromanage too often. Again, there are big opportunities to improve our outcomes by reviewing our approaches.

And on learning, I’ve railed time and again about what’s not working, and been joined by colleagues in opposition.  We learn through designed action and guided reflection, not information dump and knowledge test.  Yet that’s not what we see. And again I suggest only small changes are needed to have a substantial impact.

So, in my books, I don’t talk about so much about how to build a game, or the ways to implement mobile learning, or social learning tools.  These will change. What you want to get your mind around is about our minds. Then you can design solutions that can be implemented in any  number of ways.  I may not be successful at communicating the solutions, but in general when I speak, run workshops, or yes write, people seem to convey that I’ve had some effect on helping them get a handle on these new approaches.  In addition, figuring out how to apply them is why I’m here.

What I’ve been able to do, successfully across years and organizations, is help align processes, products, services, and more with how our brains work.  And then work within the available resources to create solutions that reflect those insights in innovative and yet practical solutions.  It takes time to develop the type of thinking I want organizations to adopt, but it’s doable, and I’ve worked with a number of organizations to do just that. Taking the time to address the tough stuff is a bit of an effort. I think it’s an investment in success.  It’s doable, so the only real open question is whether you’re ready to make a shift in thinking, that leads to a shift in doing, that leads to a better impact for your organization.  And only you can answer that.

14 February 2017

Meta-Learning Tools?

Clark @ 8:06 am

I wrote an article for Jane Hart’s Modern Workplace Learning magazine, triggered by my thought that in her tools survey, I didn’t see a lot about a certain set of reflection (c.f. last weeks posts on diagramming) and experimentation tools: meta-learning tools. In particular, for the latter, I wondered about what there was to track your own learnings.  And Jane commented to me that she knew of one, and I was reminded of more.

Now, I don’t know much about any of these, but she mentioned PebblePad, and I noted that I’ve talked with Degreed before, and saw that HT2 has a tool called Red Panda. And I think this could become an interesting area.  Coupled with tools that support learning streams, personal learning could be boosted.

So tools like Axonify, Anders Pink, and EdCast all have varying models about making knowledge available and streaming bits and pieces over time. They’re pull as well, but for one definition of microlearning (that of streaming small bits over time to develop, e.g. slow learning), they could be a valuable part of personal development.

If we then track our learnings (and not just what’s through the tool, but other things we do such as attending events, interviewing people, etc), we can maintain ourselves on a path to efficacy.  That is, if we’ve registered goals, and broken it up into steps, and track our progress (and reward ourselves), we have a higher likelihood of continuing our improvement.

What I haven’t seen, as yet, and think could be an important part of this, is layering on  additional support for learning itself, meta-learning. For each type of learning activity, there could be support for doing that well, including setting and reviewing learning paths.

There’s more pressure for individuals to take responsibility for their own learning (as well as for enlightened organizations that want to support learning). So we need to be getting systematic about not only support for the content, but also for the process. This provides the opportunity is to accelerate the process. And our success.

9 February 2017

Diagramming

Clark @ 8:05 am

So yesterday I talked about the value of diagrams, but I thought I’d add a bit about the process of actually creating diagrams. Naturally, I created a diagram about it.

Diagram of diagram designI created this diagram for a session I ran on diagramming a number of years ago.  In that session I talked about our cognitive architecture, why we need models, how diagrams work, properties and design issues, and more. At the end, I proposed a potential process for it.  It captures an ideal picture of how diagramming could work.

So, you need to know the elements of the model you want to relate, identify the relationships, and any dimensions that characterize differences between the elements. Then you have to choose how you’re going to represent them: shape, color, weight, font, and more.

With your elements, you can then place them, connect them, and add the visual coding.  Then, of course, you tune.

This is an ideal process, but in reality it’s much more flexible, at least when I’m creating a model as a way of understanding.  I typically iterate, creating placeholder elements, and moving them around until I think I have the right ones.  Then I go about connecting them to make sure I have the relationships right. Then I work on adding dimensions, and colors, and aligning them, and grouping them, and… Except that I might add some elements, then group, or connect, then add more, and…  it’s a very iterative process.  It’s a creative process that involves lots of experimentation, revision, and more.

Sometimes, I even use a diagram and then realize it’s not working and revise it. So, for instance, I blogged about a representation of social process.  I got some feedback that it wasn’t very clear.  So, I made a second stab at it, and I think it worked better. Certainly, I continue to use it without complaints.

And I’m the first to admit that my diagrams may not look as good as the ones that professional graphic designers could create, but they’re good enough (and OmniGraffle does a good job of making it easy for me to make them up to a standard I think is at least acceptable and useful; it’s probably overkill but I’ve stuck with it for years now).  And that’s the point.  If they help you think better, it’s good enough. If it helps you communicate effectively with someone else, even better.  Diagrams are cognitive tools, offloading conceptual complexity to graphic relationships and visual processing.  And with the complex problems we increasingly face, I reckon the more tools the better.

 

8 February 2017

Diagram!

Clark @ 8:05 am

One of the things that I feel is a really useful tool in my ongoing learning, in my ‘making sense of the world’ is diagramming.  I find diagrams to be a really powerful way to understand not just elements, but relationships.  And yet it doesn’t feel like diagramming gets enough respect.  So I want to make a case for the diagram.

Language is good. Our brains have evolved to use it. But it has trouble communicating complex relationships.  For an example, once I wrote this:

They found that while subjects would rate the analogies, from best to worst, as literally similar, true analogy, mere appearance, and false analogy, their recall for stories, from best to worst, was literally similarly, mere appearance, true analogy, and false analogy.

Try discerning the important difference!  My PhD advisor kindly pointed out that actually parsing this was hard, and recommended a diagram instead. Here’s a rendition of what resulted:

structure task outcomes diagram

In this case it’s much easier to see how the two differed.  (If you want to find out what’s important in the diagram, I’m happy to talk about analogical reasoning for as long as you can stand it! ;)

The point I’m making is that there are times when diagrams are very useful for communicating.  And, if you’ve followed this blog for a fair amount of time, you’ve seen I use diagrams a lot. I use them to think ‘out loud’, and I think it’s important.  As Larkin & Simon argued in their Cognitive Science article, Why a Diagram is (Sometimes) Worth Ten Thousand Words, diagrams let us map conceptual relationships to spatial ones. And so if I want to understand the conceptual relationships, I start laying out spatially, and adjust until they make sense to me.

And my concern is that we aren’t using this powerful visual tool enough.  Sketchnotes are really nice ways to capture presentations, and depending on the skill of the noter, they may communicate it all, or help recall if you’ve seen it. Similarly, my mindmaps of keynotes capture the flow of the discussion and the relationships (at least as I parsed it), but may only make sense if you heard the talk.

But representing things with diagrams is not only a personal thinking tool, it can be a powerful way to communicate concepts, and that’s an important component of a good learning experience design, providing a conceptual model to guide performance.

So I’m surprised we don’t talk about diagrams more. It may seem hard (certainly trying to create an infographic is harder than it seems, from my experience ;), but there’s some systematicity to it. There are principles, and types of diagrams, and more to explore.  And tools that make it easier (though even Powerpoint or Keynote can be used to make diagrams).  Diagrams aren’t the only visuals that help (c.f. graphs and tables), but they’re an important tool in your thinking toolbox.  I encourage you, as part of your meta-learning toolkit, to play around and get your mind around diagrams. Your thinking, and your learning design, can be better as a consequence.

2 February 2017

Reordering the Serious eLearning Manifesto

Clark @ 8:09 am

So, as you may know (and if you don’t, you should), almost three years ago now, I teamed up with colleagues Michael Allen, Julie Dirksen, & Will Thalheimer (all worth knowing about) and put together the Serious eLearning Manifesto.  And I believe it’s a good thing. But it needs an update.

So, we were (and are) frustrated with what was and is happening under the rubric of eLearning.  Michael was intrigued by the concept of Serious Games, and wondered why we didn’t treat elearning seriously as well. (A rant I’ve made before ;). He came up with the idea of a manifesto, and we agreed to work with him on it.  And we finalized a list of 8 ways in which typical elearning differed from what we call Serious eLearning, and 22 research concepts behind it (drawn from work across decades and around the world, we don’t claim to own it). And we put it out there for free (Michael graciously sponsored it through his company with no attribution).

We don’t claim that these are the only ways that good elearning differs from what’s typically seen, of course, we just feel that these are the eight most serious ones that, if followed, have the biggest impact on your learning outcomes.  It wasn’t easy getting the four of us to agree, and we’ve received quite a few suggestions of how it could be expanded or improved, but we’re comfortable that this is a reasonable stance to take.

And it’s gotten a reasonable amount of attention. We had 30+ ‘trustees’ who put their names to it (and many more worthies would have), as well as sponsorship by the appropriate societies.  We’ve been given opportunities to speak and present about it. And we’ve got an ever-growing list of signatories. People recognize that it’s right, even if it hasn’t gotten the traction we’d like (e.g. everyone making a concerted effort to shift to it since it’s release).

HOWEVER…

When I explain it to others, I realize that I have a trouble with the ordering.  Most of it’s great, but one element somehow slipped out of position, in my mind.  So I’ve made an attempt to remedy that, reordering the list. I’ve made this as similar to the original graphic as possible, except that I’m not using the right fonts. So sue me.

8 differences between typical elearning and serious elearningWhat’s different is that I’ve grouped Real-World Consequences with Authentic Contexts and Realistic Decisions. The consequences naturally follow from realistic decisions made in authentic contexts. Then we can talk about Spaced Practice and Individualized Challenges. The latter of which, by the way, is the only thing that is (mostly) specific to elearning, otherwise it’s applicable to learning in general. The rest is the same.

So this is the version that I’ll be using, going forward.  I still hope you’ll visit the site, sign on, and work towards it. No one expects you to get all the way right away, but it is the right way to go.  If you need help, I’m happy to assist.

 

1 February 2017

Other writings

Clark @ 8:04 am

It occurs to me to mention some of the other places you can find my writings besides here (and how they differ ;).  My blog posts are pretty regular (my aim is 2/week), but tend to have ideas that are embryonic or a bit ‘evangelical’. First, I’ve written four books; you can check them out and get sample chapters at their respective sites:

Engaging Learning: Designing e-Learning Simulation Games

Designing mLearning: Tapping Into the Mobile Revolution for Organizational Performance

The Mobile Academy: mLearning For Higher Education

Revolutionize Learning &  Development: Performance and Information Strategy for the Information Age

They’re designed to be the definitive word on the topic, at least at the moment.

I’ve also written or co-written a number of chapters in a variety of books.  The books include The Really Useful eLearning Instruction ManualCreating a Learning Culture, Michael Allen’s eLearning Annual 2009,  and a bunch of academic handbooks (Mobile Learning, Experiential Learning, Wiley Learning Technology ;).  These tend to be longer than an article, with a pretty thorough coverage of whatever topic is on tap.

Then there are articles in a variety of magazines.  These tend to be aggregated thoughts that are longer than a blog post, but not as through as a chapter. In particular, they are things I think need to be heard (or read).  So, my writing has shown up in:

eLearnMag

Learning Solutions

CLO

The topics vary. (For the eLearnMag ones, you’ll have to search for my name owing to their interface, and they tend to be more like editorials.)

And then there are blog posts for others that are a bit longer than my usual blog post, and close to an article in focus:

The Deeper eLearning series for Learnnovators

A monthly article for Litmos.

These, too, are more like articles in that they’re focused, and deeper than my usual blog post.  For the latter I cover a lot of different topics, so you’re likely to find something relevant there in many different areas.

I’m proud of it all, but for a quick update on a topic, you might be best seeing if there’s a Litmos post on it first.  That’s likely to be relatively short and focused if there is one. And, of course, if it’s a topic you’re interested in advancing in and I can help, do let me know.

26 January 2017

Silo APIs?

Clark @ 8:06 am

I was in a conversation with my colleague Charles Jennings about organizational innovation, and one of the topics that arose was that of barriers to successful organizational function. In particular, we were talking about how the division of responsibility between organizational development (OD), leadership development, and learning & development is a problem. And I think the problem is bigger. Separating out functions into silos makes sense in a deterministic world, but that doesn’t characterize our current environment.

Now, separation of functions can be useful. Certainly in software engineering, having application program interfaces (APIs) have led to the ability to connect powerful capabilities.  A program can call a function and get data returned via an API, and the software doesn’t have to care how the function’s carried out.

In the org equivalent we could have a business unit request a course, for example, and L&D responds with said course. In fact, that’s not atypical.  Yet it’s problematic in human terms. The business unit may not have done the due diligence, the performance analysis, that ensures a course is the right solution.

Ok, we could change it: the business unit could indicate the performance problem and L&D could respond. However, again there’s a problem. Without understanding how things are done, L&D’s solution won’t be contextually accurate.  Any intervention won’t reflect how things are done unless interactions occur.

And that’s the point. Any meaningful work – problem-solving, trouble-shooting, improvement, innovation, research, design etc – any learning, is complex. And, done right, they inherently require engagement and interaction.  Moreover, we also know that the best solutions come from creative friction, people interacting.  Communication and collaboration is key!

Engagement between silos works best when you mix members from each.  Or, to put it another way, breaking down the silos is the only way to get the best outputs for the important work, the work that will advance the organization whether removing errors, creating new products or processes, etc.

People are complex (the human brain is arguably the most complex thing in the known universe).  Solutions that tap into that complexity, instead of trying to avoid it, are bound to yield the best insights. We’ve now got a lot of insight into processes that facilitate getting the best outcomes. It’s time to engage with it, to the benefit of the organization.

25 January 2017

Culture or Cultures?

Clark @ 8:02 am

A twitter pointer led me to an HBR article arguing that We’re Thinking about Organizational Culture all Wrong.  In it, the author argues that it’s fallacious to think that there’s just one organizational culture, , and that all people buy into it.  I agree, and yet where the author leads us is, I think, misleading, or at least not as helpful as it could be.

The argument includes two major thrusts. The first is that the cultural values may be interpreted differently.  What you mean by ‘free’ and what I mean may differ.  Take, for instance, the difference between ‘free beer’ and ‘free speech’ (a classic example).  And this certainly can be the case. The second is that people may comply with the culture even if they don’t agree with it. There are multiple reasons, such as job security, that could support this.

The result, according to the article, is that corporate ‘culture’ isn’t a set of shared values, it’s a “web of power relationships”.  That’s quite a leap, but the point is apt: these relationships can facilitate,  or hinder, individual goals.  However, one statement near the end rings wrong for me:

“Reliance on culture as a way to create unity can mislead those in positions of power into thinking that the core values expressed by the organization are actually uncritically accepted by employees.”.

I agree, but I think it’s simplistic. No one in power should be naive enough to believe that anyone uncritically accepts any values. Instead, the view should be to recognize what core values facilitate the most effective outcomes for the organization, and then follow some well-tested rules about change:

  • sell the vision
  • make it a choice
  • support
  • know how to address the expected problems
  • be prepared to address the unexpected
  • evangelize
  • reward
  • test and tweak
  • persist

It may make sense to start small and spread virally rather than make it an overall change initiative.  Still, I think it’s a worthwhile goal.

There is a clear value proposition about having a culture that supports innovation, and identifiable components.  Abandoning the effort because culture is complex seems a missed opportunity.  The benefits are big. Cultures are developed and do change. Doing so systematically, and systemically, seem to me to be the path to competitive success.  What am I missing?

19 January 2017

Errors and misconceptions

Clark @ 8:08 am

explosionWhen I was a grad student, my advisor looked a lot at error. HIs particular focus was to prevent it through good interface design.  He characterized them as of two types: slips and mistakes.  Slips are when you have the right intent, but from elements of our architecture end up making the wrong move.  Mistakes are when your intentions are wrong. From the learning perspective, it’s the latter we want to address.

So, I’ve argued that there’s some randomness in our architecture. We’re bad at doing rote things, even when we know what to do.  Athletes, for instance, practice for hours a day, day after day and their competitions are typically decided by who makes the fewest errors.  In fact, we’ve identified and created support tools to minimize these errors, like checklists.  We’re supposed to design systems so they minimize the opportunity for slips. These don’t always work; I was embarassed in my most recent presentation to find a couple of typos. They clearly had come in via auto-correct, but I’d missed them subsequently!  There may well be one in this post, too, some form of slip or another.

More importantly are what are termed ‘mistakes’.  Here we’re starting with the wrong intent.  This, from a learning perspective, is what I term a ‘misconception’.  Here, we’re supposed to be using a particular mental model to guide our performance, but we might not have the right model, or no model and we import a wrong one. Again, we should design to minimize these as well, but we also want to make sure we’ve got the right mental models to begin with.  This happens if we haven’t been given the right one, or activated an irrelevant one inappropriately.

Ideally, we want to identify the most likely ways we go wrong, and then make sure we understand what those are and why. From there, then make them available as options in practice. Then we can remediate them at the moment.  Of course, we’re also supposed to have the right model, and highlight how the model guides performance in examples, and then again through the feedback on both correct  and incorrect performance.

Designing practice that supports making the right decisions in context, and also the opportunity to make the wrong choice and get useful feedback, is a key learning design skill. Quiz questions that just test knowledge aren’t likely to lead to meaningful difference in performance.  Practice where the alternative to the right answer are silly or obvious (unless you really know the model) is a waste of your resources and your learner’s time.  Make practice meaningful. Not doing so is an error, too!

18 January 2017

Cognitive Business

Clark @ 8:07 am

One of my mantras is that organizations need to align better with how we think, work, and learn.  However, my focus has been specifically on what L&D can be doing (as that’s the folk I mostly talk to). But it occurs to me that it really goes farther.  There are applications of cognitive science (including neuroscience, cognitive psychology, sociology, philosophy, anthropology, etc) to more areas of business than just L&D.  And it’s worth being explicit about this.

I was recently reading how marketing has leveraged understanding of behavior change at a deep level. We need to incorporate this in our learning design, but it should go beyond training and learning and be involved in helping people understand why their work is important and how they contribute.

And similarly, the notion that our thinking is both situated (e.g. reconstructed in the moment, not formally abstract) and distributed (across representations, not all in the head) has broader implications. It’s not just about performance support, but should influence policies and tools as well.

And the fact that innovation is social, and an outcome of slow percolation, influences more than facilitating communication and collaboration. It should influence corporate culture and expectations and time frames.

The list goes on: research says that organizational change works better starting small and scaling rather than a monolithic effort.  We know that design processes are better when they’re cyclical rather than waterfalls. We’ve discovered that our inability to perform rote tasks flawlessly argues for changes in work processes and expectation. And we’ve found out that treating people fairly leads to better outcomes including retention, loyalty, and more.  Ultimately, we’ll want to be making smart cyborg choices about what to have people do and what  technology should do.

In short, we can be working smarter in many ways.  It’s hard to change from the old hierarchical models, but we’re continually learning that other approaches work better.  Heck, we may even be able to start working wiser!  Here’s hoping.

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