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

5 January 2017

Mobile Lesson

Clark @ 8:04 am

Designing mLearning bookI’m preparing my keynote for a mobile conference, and it’s caused an interesting reflection.  My mlearning books came out in 2011, and subsequently I’ve written on the revolution.  And I’ve been speaking on both of late, but in some ways the persistent interest in mobile intrigues me.

While my services are pushing the better design of and the bigger picture of elearning, mobile isn’t going away. My trip to China to keynote this past year was on mlearning (and one the year before), and now again I’m talking on the topic.  What does this mean?

As I wrote before, China is much bigger into mobile than we are. It’s likely because we had more ubiquity of internet access and computers, but they’re also a highly mobile populace.  And it makes sense that they’re showing a continuing interest. In fact, they specifically asked for a presentation that was advanced, not my usual introduction.

I’m also going to be presenting on more advanced thinking to the audience coming up, because the entire focus of the event is mlearning and I infer that they’re already up on the basics.  The focus in my books was to get people thinking differently about mobile (because it’s not about courses on a phone), but certainly that was understood in China. I think it’s also understood by most of the developers. I’m less certain about the elearning field (corporate and education), at least not yet.

In many ways, mobile was a catalyst for the revolution.  I think of mlearning as much more than courses, and my models focused on performance support and social more than formal learning. That is really one of the two-fold focuses on the revolution (the “L&D isn’t doing near what it could and should”; to complement the “and what it is doing, it is doing badly” :).  In that way, these devices can be a wedge in the door for a broader focus.

Yet mobile is just a platform for enabling the type of experiences, the types of cognitive support, as any other platform  from conversation to artificial intelligence.  It is an important one, however, with the unique properties of doing things whenever & wherever you are and doing things because of when and where you are.

So I get that mlearning is of interest because of the ubiquity, but the thinking that goes into mobile really goes beyond mobile.  It’s about aligning with us, supporting our needs to communicate and collaborate.  That’s still a need, a useful message, and an opportunity.  Are you mobilizing?

 

21 September 2016

Collaborative Modelling in AR (and VR)

Clark @ 8:04 am

A number of years ago, when we were at the height of the hype about Virtual Worlds (computer rendered 3D social worlds, e.g. Second Life), I was thinking about the affordances.  And one that I thought was intriguing was co-creating, in particular collaboratively creating models that were explanatory and predictive.  And in thinking again about Augmented Reality (AR), I realized we had this opportunity again.

Models are hard enough to capture in 2D, particularly if they’re complex.  Having a 3rd dimension can be valuable. Similarly if we’re trying to match how the components are physically structured (think of a model of a refinery, for instance, or a power plant).  Creating it can be challenging, particularly if you’re trying to map out a new understanding.  And, we know that collaboration is more powerful than solo ideation.  So, a real opportunity is to collaborate to create models.

And in the old Virtual Worlds, a number had ways to create 3D objects.  It wasn’t easy, as you had to learn the interface commands to accomplish this task, but the worlds were configurable (e.g. you could build things) and you could build models.  There was also the overall cognitive and processing overhead inherent to the worlds, but these were a given to use the worlds at all.

What I was thinking of, extending my thoughts about AR in general,  that annotating the world is valuable, but how about collaboratively annotating the world?  If we can provide mechanisms (e.g. gestures) for people to not just consume, but create the models ‘in world’ (e.g. while viewing, not offline), we can find some powerful learning opportunities, both formal and informal.  Yes, there are issues in creating and developing abilities with a standard ‘model-building’ language, particularly if it needs to be aligned to the world, but the outcomes could be powerful.

For formal, imagine asking learners to express their understanding. Many years ago, I was working with Kathy Fisher on semantic networks, where she had learners express their understanding of the digestive system and was able to expose misconceptions.  Imagine asking learners to represent their conceptions of causal and other relationships.  They might even collaborate on doing that. They could also just build 3D models not aligned to the world (though that doesn’t necessarily require AR).

And for informal learning, having team or community members working to collaboratively annotate their environment or represent their understanding could solve problems and advance a community’s practices.  Teams could be creating new products, trouble-shooting, or more, with their models.  And communities could be representing their processes and frameworks.

This wouldn’t necessarily have to happen in the real world if the options weren’t aligned to external context, so perhaps VR could be used. At a client event last week, I was given the chance to use a VR headset (Google Cardboard), and immerse myself in the experience. It might not need to be virtual (instead collaboration could be just through networked computers, but there was data from research into virtual reality that suggests better learning outcomes.

Richer technology and research into cognition starts giving us powerful new ways to augment our intelligence and co-create richer futures.  While in some sense this is an extension of existing practices, it’s leveraging core affordances to meet conceptually valuable needs.  That’s my model, what’s yours?

7 September 2016

China is mobile!

Clark @ 8:14 am

I’ve had the fortune to be here in China speaking on mlearning.  And there are a couple of interesting revelations that I hadn’t really recognized when I did the same last year that I thought I’d share.

For one, while mobile is everywhere like many places, it’s more here.  It seems many people carry more than one phone, for a variety of reasons (one fellow said that he carried another because the battery wouldn’t last all day!).  But they’re all phones, I seem to see few tablets.  They vary in size from phones to phablets, but they’re here.

Which leads to a second recognition.  They are big into mlearning, and elearning. The culture does respect scholarship (no anti-intellectualism here), so they’re quite keen to continue their education. Companies with mlearning courses do well, and the government is investing in educational technology in a big way.  It’s not clear whether their pedagogy is advanced (I can’t read Chinese, I admit), but they do get ‘chunking’ into small bits. And, importantly, the recognition of the value of investment is important.

QuinnovationQRCodeOne other thing struck me as well: QR codes live! They’re everywhere here. They used them during my workshop to run a lottery, and to answer some polling questions on demographics of the audience.  They’re in the restaurants as a start to the payment process. And they’re scattered around on most ads.  They have an advantage that they seem to have mastered the art of having an app that systematically recognizes them (it’s built into the ubiquitous social media app, WeChat).

Establishing the consistent use of a standard can help build a powerful, and valuable, ecosystem.  I can wish that the providers in the US would work and play together a little bit more!  There may be better alternatives, but getting consistently behind one standard makes the investment amortize effectively.

I’m pleased to see that mLearning is taking off, and had fun sharing some of the models that I think provide leverage to rally take advantage.  Here’s to getting going with mobile!

4 May 2016

Learning in Context

Clark @ 8:09 am

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.

26 April 2016

Learning in context

Clark @ 8:10 am

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?

15 March 2016

Context Rules

Clark @ 8:15 am

I was watching a blab (a video chat tool) about the upcoming FocusOn Learning, a new event from the eLearning Guild. This conference combines their previous mLearnCon and Performance Support Symposium with the addition of video.  The previous events have been great, and I’ll of course be there (offering a workshop on cognition for mobile, a mobile learning 101 session, and one on the topic of this post). Listening to folks talk about the conference led me to ponder the connection, and something struck me.

I find it kind of misleading that it’s FocusOn Learning, given that performance support, mobile, and even video typically is more about acting in the moment than developing over time.  Mobile device use tends to be more about quick access than extended experience.  Performance support is more about augmenting our cognitive capabilities. Video (as opposed to animation or images or graphics, and similar to photos) is about showing how things happen in situ (I note that this is my distinction, and they may well include animation in their definition of video, caveat emptor).  The unifying element to me is context.

So, mobile is a platform.  It’s a computational medium, and as such is the same sort of computational augment that a desktop is.  Except that it can be with you. Moreover, it can have sensors, so not just providing computational capabilities where you are, but because of when and where you are.

Performance support is about providing a cognitive augment. It can be any medium – paper, audio, digital – but it’s about providing support for the gaps in our mental capabilities.  Our architecture is powerful, but has limitations, and we can provide support to minimize those problems. It’s about support in the moment, that is, in context.

And video, like photos, inherently captures context.  Unlike an animation that represents conceptual distinctions separated from the real world along one or more dimensions, a video accurately captures what the camera sees happening.  It’s again about context.

And the interesting thing to me is that we can support performance in the moment, whether a lookup table or a howto video, without learning necessarily happening. And that’s OK!  It’s also possible to use context to support learning, and in fact we can provide least material to augment a context than create an artificial context which so much of learning requires.

What excited me was that there was a discussion about AR and AI. And these, to me, are also about context.  Augmented Reality layers  information on top of your current context. And the way you start doing contextually relevant content delivery is with rules tied to content descriptors (content systems), and such rules are really part of an intelligently adaptive system.

So I’m inclined to think this conference is about leveraging context in intelligent ways. Or that it can be, will be, and should be. Your mileage may vary ;).

16 February 2016

Litmos Guest Blog Series

Clark @ 8:09 am

As I did with Learnnovators, with Litmos I’ve also done a series of posts, in this case a year’s worth.  Unlike the other series, which was focused on deeper eLearning design, they’re not linked thematically and instead cover a wide range of topics that were mutually agreed as being personally interesting and of interest to their argument.

So, we have presentations on:

  1. Blending learning
  2. Performance Support
  3. mLearning: Part 1 and Part 2
  4. Advanced Instructional Design
  5. Games and Gamification
  6. Courses in the Ecosystem
  7. L&D and the Bigger Picture
  8. Measurement
  9. Reviewing Design Processes
  10. New Learning Technologies
  11. Collaboration
  12. Meta-Learning

If any of these topics are of interest, I welcome you to check them out.

 

27 January 2016

Reactivating Learning

Clark @ 8:10 am

(I looked because I’m sure I’ve talked about this before, but apparently not a full post, so here we go.)

If we want our learning to stick, it needs to be spaced out over time. But what sorts of things will accomplish this?  I like to think of three types, all different forms of reactivating learning.

Reactivating learning is important. At a neural level, we’re generating patterns of activation in conjunction, which strengthens the relationships between these patterns, increasing the likelihood that they’ll get activated when relevant. That’s why context helps as well as concept (e.g. don’t just provide abstract knowledge).  And I’ll suggest there are 3 major categories of reactivation to consider:

Reconceptualization: here we’re talking about presenting a different conceptual model that explains the same phenomena. Particularly if the learners have had some meaningful activity from your initial learning or through their work, showing a different way of thinking about the problem is helpful. I like to link it to Rand Spiro’s Cognitive Flexibility Theory, and explain that having more ways to represent the underlying model provides more ways to understand the concept to begin with, a greater likelihood that one of the representations will get activated when there’s a problem to be solved, and will activate the other model(s) so there’s a greater likelihood of finding one that leads to a solution.  So, you might think of electrical circuits like water flowing in pipes, or think about electron flow, and either could be useful.  It can be as simple as a new diagram, animation, or just a small prose recitation.

Recontextualization: here we’re showing another example. We’re showing how the concept plays out in a new context, and this gives a greater base upon which to abstract from and comprehend the underlying principle, and providing a new reference that might match a situation they could actually see.   To process it, you’re reactivating the concept representation, comprehending the context, and observing how the concept was used to generate a solution to this situation.  A good example, with a challenging situation that the learner recognizes, a clear goal, and cognitive annotation showing the underlying thinking, will serve to strengthen the learning.  A graphic novel format would be fun, or story, or video, anything that captures the story, thinking, and outcome would work.

Reapplication: this is the best, where instead of consuming a concept model or an example, we actually provide a new practice problem. This should require retrieving the underlying concept, comprehending the context, and determining how the model predicts what will happen to particular perturbations and figuring out which will lead to the desired outcomes.  Practice makes perfect, as they say, and so this should ideally be the emphasis in reactivation.  It might be as simple as a multiple-choice question, though a scenario in many instances would be better, and a sim/game would of course be outstanding.

All of these serve as reactivation. Reactivation, as I’ve pointed out, is a necessary part of learning.  When you don’t have enough chance to practice in the workplace, but it’s important that you have the ability when you need it (and try to avoid putting it in the head if you can), reactivation is a critical tool in your arsenal.

31 December 2015

2015 Reflections

Clark @ 8:02 am

It’s the end of the year, and given that I’m an advocate for the benefits of reflection, I suppose I better practice what I preach. So what am I thinking I learned as a consequence of this past year?  Several things come to mind (and I reserve the right for more things to percolate out, but those will be my 2016 posts, right? :):

  1. The Revolution is real: the evidence mounts that there is a need for change in L&D, and when those steps are taken, good things happen. The latest Towards Maturity report shows that the steps taken by their top-performing organizations are very much about aligning with business, focusing on performance, and more.  Similarly, Chief Learning Officer‘s Learning Elite Survey similarly point out to making links across the organization and measuring outcomes.  The data supports the principled observation.
  2. The barriers are real: there is continuing resistance to the most obvious changes. 70:20:10, for instance, continues to get challenged on nonsensical issues like the exactness of the numbers!?!?  The fact that a Learning Management System is not a strategy still doesn’t seem to have penetrated.  And so we’re similarly seeing that other business units are taking on the needs for performance support, social media, and ongoing learning. Which is bad news for L&D, I reckon.
  3. Learning design is rocket science: (or should be). The perpetration of so much bad elearning continues to be demonstrated at exhibition halls around the globe.  It’s demonstrably true that tarted up information presentation and knowledge test isn’t going to lead to meaningful behavior change, but we still are thrusting people into positions without background and giving them tools that are oriented at content presentation.  Somehow we need to do better. Still pushing the Serious eLearning Manifesto.
  4. Mobile is well on it’s way: we’re seeing mobile becoming mainstream, and this is a good thing. While we still hear the drum beating to put courses on a phone, we’re also seeing that call being ignored. We’re instead seeing real needs being met, and new opportunities being explored.  There’s still a ways to go, but here’s to a continuing awareness of good mobile design.
  5. Gamification is still being confounded: people aren’t really making clear conceptual differences around games. We’re still seeing linear scenarios confounded with branching, we’re seeing gamification confounded with serious games, and more.  Some of these are because the concepts are complex, and some because of vested interests.
  6. Games  seem to be reemerging: while the interest in games became mainstream circa 2010 or so, there hasn’t been a real sea change in their use.  However, it’s quietly feeling like folks are beginning to get their minds around Immersive Learning Simulations, aka Serious Games.   There’s still ways to go in really understanding the critical design elements, but the tools are getting better and making them more accessible in at least some formats.
  7. Design is becoming a ‘thing’: all the hype around Design Thinking is leading to a greater concern about design, and this is a good thing. Unfortunately there will probably be some hype and clarity to be discerned, but at least the overall awareness raising is a good step.
  8. Learning to learn seems to have emerged: years ago the late great Jay Cross and I and some colleagues put together the Meta-Learning Lab, and it was way too early (like so much I touch :p). However, his passing has raised the term again, and there’s much more resonance. I don’t think it’s necessarily a thing yet, but it’s far greater resonance than we had at the time.
  9. Systems are coming: I’ve been arguing for the underpinnings, e.g. content systems.  And I’m (finally) beginning to see more interest in that, and other components are advancing as well: data (e.g. the great work Ellen Wagner and team have been doing on Predictive Analytics), algorithms (all the new adaptive learning systems), etc. I’m keen to think what tags are necessary to support the ability to leverage open educational resources as part of such systems.
  10. Greater inputs into learning: we’ve seen learning folks get interested in behavior change, habits, and more.  I’m thinking we’re going to go further. Areas I’m interested in include myth and ritual, powerful shapers of culture and behavior. And we’re drawing on greater inputs into the processes as well (see 7, above).  I hope this continues, as part of learning to learn is to look to related areas and models.

Obviously, these are things I care about.  I’m fortunate to be able to work in a field that I enjoy and believe has real potential to contribute.  And just fair warning, I’m working on a few areas in several ways.  You’ll see more about learning design and the future of work sometime in the near future. And rather than generally agitate, I’m putting together two specific programs – one on (e)learning quality and one on L&D strategy – that are intended to be comprehensive approaches.  Stay tuned.

That’s my short list, I’m sure more will emerge.  In the meantime, I hope you had a great 2015, and that your 2016 is your best year yet.

27 October 2015

Showing the World

Clark @ 8:03 am

One of the positive results of investigations into making work more effective has been the notion of transparency, which manifests as either working and learning ‘out loud‘, or in calls to Show Your Work.  In these cases, it’s so people can know what you’re doing, and either provide useful feedback or learn from you.  However, a recent chat in the L&D Revolution group on LinkedIn on Augmented Reality (AR) surfaced another idea.

We were talking about how AR could be used to show how to do things, providing information for instance on how to repair a machine. This has already been seen in examples by BMW, for instance. But I started thinking about how it could be used to support education, and took it a bit further.

So many years ago, Jim Spohrer proposed WorldBoard, a way to annotate the world. It was like the WWW, but it was location specific, so you could have specific information about a place at the place.  And it was a good idea that got some initial traction but obviously didn’t continue.

The point, however, would be to ‘expose’ the world. In particular, given my emphasis on the value of models, I’d love to have models exposed. Imagine what we could display:

  • the physiology of an animal we’re looking at to flows of energy in an ecosystem
  • the architectural or engineering features of a building or structure
  • the flows of materials through a manufacturing system
  • the operation of complex devices

The list goes on. I’ve argued before that we should expose our learning designs as a way to hand over learning control to learners, developing their meta-learning skills. I think if we could expose how things work and the thinking behind them, we’d be boosting STEM in a big way.

We could go further, annotating exhibits and performances as well.  And it could be auditory as well, so you might not need to have glasses, or you could just hold up the camera and see the annotations on the screen. You could of course turn them on or off, and choose which filters you want.

The systems exist: Layar commercially, ARIS in the open source space (with different capabilities).  The hard part is the common frameworks, agreeing what and how, etc.   However, the possibilities to really raise understanding is very much an opportunity.  Making the workings of the world visible seems to me to be a very intriguing possibility to leverage the power we now hold in our hand. Ok, so this is ‘out there’, but I hope we might see this flourishing quickly.  What am I missing?

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