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Clark Quinn’s Learnings about Learning

Tools and Design

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I’ve often complained about how the tools we have make it easy to do bad design. They make it easy to put PPTs and PDFs on the screen and add a quiz. And not that that’s not so, but I decided to look at it from the other direction, and I found that instructive. So here’re some thoughts on tools.

Authoring tools, in general, are oriented on a ‘page’ metaphor; they’re designed to provide a sequence of pages. The pages can contain a variety of media: text, audio, video.  And then there are special pages, the ones where you can interact.  And, of course, these interactions are the critical point for learning. It’s when you have to act, to  do, that you retrieve and apply knowledge, that learning really happens.

What’s critical is  what you do.  If it’s just answering knowledge questions, it’s not so good.  If it’s just ‘click to see more’, it’s pretty bad.  The critical element is being faced with a decision about an action to take, then apply the knowledge to discriminate between the alternatives, and make a decision.  The learner has to commit!  Now, if I’m complaining about the tools making it easy to do bad things, what would be good things?

That was my thinking: what would be ideal for tools to support? I reasoned that the interactions should represent things we do in the real world.  Which, of course, are things like fill in forms, write documents, fill out spreadsheets, film things, make things.  And these are all done through typical interactions like drag, drop, click, and more.

Which made me realize that the tools aren’t the problem!  Well, mostly; click to see more is still problematic.  Deciding between courses of action can be done as just a better multiple choice question, or via any common form of interaction: drag/drop, reorder, image click, etc. Of course, branching scenarios are good too, for so-called soft skills (which are increasingly the important things), but tools are supporting those as well.  The challenge  isn’t inherent in the tool design.  The challenge is in our thinking!

As someone recently commented to me, the problem isn’t the tools, it’s the mindset.  If you’re thinking about information dump and knowledge test, you can do that. If you’re thinking about putting people into place to made decisions like they’ll need to make, you can do that. And, of course, provide supporting materials to be able to make those decisions.

I reckon the tool vendors are still focused on content and a quiz, but the support is there to do learning designs that will really have an impact.  We may have to be a bit creative, but the capability is on tap. It’s up to (all of) us to create design processes that focus on the important aspects.  As I’ve said before, if you get the design right, there are  lots of ways to implement it!

No all-singing all-dancing solution

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I was pinged on LinkedIn by someone who used the entrée of hearing me speak in next week’s Learning Solutions conference to begin discussing LMS capabilities. (Hint: they provide one.)  And I thought I’d elaborate on my response, as the discussion prompted some reflections.  In short, what are the arguments for and against having a single platform to deliver an ecosystem solution?

In Revolutionize Learning & Development, I argue for a Performance & Development ccosystem. The idea is more than courses, it’s performance support, social, informal, etc. It’s about having a performer-centric support environment that has tools and information to hand to both help you perform in the moment  and develop you over time. The goal is to support working alone and together to meet both the anticipated, and unanticipated, needs of the organization.

On principle, I tend to view an ‘all singing all dancing’ solution as likely to fail on some part of that. It’s implausible that a system would have all the capabilities needed.  First, there are  many functionalities: access to formal learning, supporting access to known or found resources, sharing, collaborating, and more.  It’s unlikely that all those can be done well in one platform. Let alone, doing them in ways that matches any one organization’s ways of working.

I’m not saying the LMS is a bad tool for what it does. (Note: I am not in the LMS benchmark business; there are other people that do that and it’s a full time job.) However, can an LMS be a full solution? Even if there is some capability in all the areas, what’s the likelihood that it’s best-of-breed in all? Ok, in some small orgs where you can’t have an IT group capable of integrating the necessary tools, you might settle for working around the limitations. That’s understandable. But it’s different than choosing to trust one system. It’s just having the people act as the glue instead of the system.

It’s always about tradeoffs, and so integrating best-of-breed capabilities around what’s already in place would make more sense to me.  For instance, how *could* one system integrate enterprise-wide federated search as a stand-alone platform? It’s about integrating a suite of capabilities to create a performer-centric environment. That’s pretty much beyond a solo platform, intrinsically. Am I missing something?

The Dearth of Science in Learning Technology

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Over the years, I’ve looked at a lot of learning technology.  And I see a dispiriting trend. There seems to be little learning science of late.  What I see are marketing driven decisions, even when there are claims to science!  And I think this is a problem.

First, I generally resist the ‘let me show you our product and give us your opinion’. That’s free consulting, and a very rude ask!  (Though I’m contemplating it but all they’ll get for free is the number of comments in each category I’ve noted. ;)  Still  I  will investigate things of my volition at times.  I end up seeing a lot of technology by checking it out when someone talks about it, or wandering expo halls.  And what I see concerns me.

For one, there are too many tools that have suites of features that are oriented towards ‘information dump and knowledge test’.  Which we know isn’t going to lead to meaningful learning.  Yet when I try to push them to the next level of engagement (cognitive and emotional), they’re uninterested.  The response: “this is what our customers say they want”.  Which, of course, isn’t what they need.

It gets worse when supposedly more advanced tools are proselytized. I recently sampled one system promoting their advanced memory model.  And the free-to-air course  on learning science was broken!  It failed on a couple of dimensions beyond drilling rote memory about one thing. That’s not a good example to be showing.  Yet people who don’t know better might be enthused.

For a quick test, check to see if there’s anyone who understands learning on the executive team of a vendor. You’ll see all the business roles filled.  Some might have advisory boards composed of learning folks, but it’s not clear what role they play.

And I get it.  Unfortunately, as an industry, we’re not informed consumers. I see continual conceptually fuzzy promotion of ideas, and even societies offering white papers on the latest buzzwords.  It’s business, and with business folks in charge (and shareholders to assuage), they’ll do what people want.  Yet this isn’t the professionalism we need.

Ok, so this rant doesn’t taint all companies, but it’s too true for many or most. It’s all too easy to look at the typical offerings and point out the fundamental flaws in what they’re doing, if you know how we learn. And you should.

So, I’ll continue on my crusade for us as an industry to lift our game. I hereby offer to assist any learning technology that wants to put it’s money where it’s mouth is to help them understand learning science, build it into their products, and help them promote the benefits. And I likewise offer any organization  using learning technology to help them lift their game and be better consumers.  I’ve done both before, and am ready to assist others. Because our learners need us to represent their true interests.

 

A broader view of Augmented Reality

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I was answering some questions about a previous post of mine on AR, and realized I have made some unnecessary limitations in my own thinking. And I may not be the only one!  So I thought I’d share my thoughts on a broader view of augmented reality.

Now, most people tend to think of Augmented Reality as visual augmentation of a scene. This typically done with a camera that registers what you’re seeing, and then adds information to the visual field.  The approach is usually either a projector on glasses (e.g. Google Glass) or by putting it on your screen (Apple’s ARKit).  But what occurred to me is that there’re more ways to augment the world with useful information.

One of the limitations of visual systems is their ‘directionality’; you have to be pointed in a particular direction to notice something.  Movement in the periphery of your vision may draw your attention elsewhere, but otherwise you’re pretty limited.  Yes, we have blindspots.

Audio, on the other hand, is direction-independent. It may be affected by distance, or interference (as is vision too), but is independent of where you’re looking. E.g. we can listen to the radio or podcasts while we drive, and the GPS notifications don’t require that we look at the map (“turn left in 200 feet”).

And this information  also can  augment our world.  It could be a narration of interesting points as you traverse some space, or it could be performance information. Or even notifications!  I regularly set alarms before events to do things like get me to the call or room on time, to remember to load presentations on flash drives, and more.  This extra information in the world is very helpful.  It’s what Don Norman called a ‘forcing function’, making it hard for your to avoid processing it. (His example was putting something you needed to take to work in front of the door so you couldn’t leave without at least moving it.)

Movement information can also  be useful. Vibration of a phone on silent, or the different taps that an Apple Watch can give to have you turn left or right are both examples.  (For that matter, I always wonder if airlines make it warmer during the flight to help you sleep, particularly at night, and colder before you need to wake up to land.)

There are lots of ways we can instrument the world to provide useful information (train arrival notifications, maps, street signs).  Digital support that is contextually cued is even more powerful.  But don’t limit yourself (as I was somewhat inclined to do) to just visual cues. Think of a rich suite of human perception and leverage accordingly.

 

2018 Trajectories

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Given my reflections on the past year, it’s worth thinking about the implications.  What trajectories can we expect if the trends are extended?  These are  not predictions (as has been said, “never predict anything, particularly the future”).  Instead, these are musings, and perhaps wishes for what could (even  should) occur.

I mentioned an interest in AR and VR.  I think these are definitely on the upswing. VR may be on a rebound from some early hype (certainly ‘virtual worlds’), but AR is still in the offing.  And the tools are becoming more usable and affordable, which typically presages uptake.

I think the excitement about AI will continue, but I reckon we’re already seeing a bit of a backlash. I think that’s fair enough. And I’m seeing more talk about Intelligence Augmentation, and I think that’s a perspective we continue to need. Informed, of course, by a true understanding of how we think, work, and learn.  We need to design to work  with us.  Effectively.

Fortunately, I think there are signs we might see more rationality in L&D overall. Certainly we’re seeing lots of people talking about the need for improvement. I see more interest in evaluation, which is also a good step. In fact, I believe it’s a good  first step!

I hope it goes further, of course. The cognitive perspective suggests everything from training & performance support, through facilitating communication and collaboration, to culture.  There are many facets that can be fine-tuned to optimize outcomes.Similarly, I hope to see a continuing improvement in learning engineering. That’s part of the reason for the Manifesto and the Quinnov 8.  How it emerges, however, is less important than that it  does.  Our learners, and our organizations, deserve nothing less.

Thus, the integration of cognitive science into the design of performance and innovation solutions will continue to be my theme.  When you’re ready to take steps in this direction, I’m happy to help. Let me know; that’s what I do!

Video Lessons

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So, I’ve been creating a ‘deeper elearning’ course for one of the video course providers. And I’m not mentioning where it is (yet), since it’s still under development.  But to do this, I had to do some serious learning about creating video.  And there were some realizations in this, of course.

One of the decisions to be made was how to include graphics.. My mentor/colleague/friend showed me (by video chat) his elegant setup.  He has green screens, and lights, and has a full studio in a separate room as well. Of course, he’s been doing video for decades.  I’ve hardly done much besides taking a multimedia course at least 20 years ago. And narrating the occasional Keynote deck.

In the meantime I asked around, and colleagues were pretty unanimous on ScreenFlow being  the tool to use.  So I got a copy. And, indeed, I was able to film myself.  Moreover, I quickly found out I could include diagrams and text right on the screen! That eliminated the need for a green screen.

My video imageI had a couple of lights, and without them my screen reflected on my glasses.  However, that’s not really fixable, since I didn’t get the anti-glare coating when I had them made.  Doh!  Next time, for sure. I positioned a couple of lights off to each side, and they reduced (though not eliminated) the glare.

We were moving my office back to the front of the house (long story), so we moved a bookcase behind me, with my library.  It looks good, but…you don’t see much of it anyway.  I filmed standing up (on my new stand/sit desk converter), and I block most of the background anyway (except for the Albert Einstein poster that sits on the wall).

Having read up,  I knew to have a written script, which, without a prompter, I just positioned to the top of the screen under the camera.  Of course I changed it a bit, and adlibbed a bit, but mostly stuck to what I’d written. It’s not quite as spontaneous (and goofy) as I am in person, but it ensures consistent quality. And I filled in diagrams a few times, and added some text a few times, to help keep pace.

Frankly, it’s not great, but I had a deadline.  It’s too much of me talking, without animation. But this is done by me, alone, under a tight deadline. And that’s my error, too, since I have video anxiety almost as bad as my phone anxiety, and dragged my heels until things were too late.  Dang emotions getting in the way again! (Even when you know this.)

I also created some quizzes, in mini-scenario fashion pretty much. That is, there’s a fair bit of dialog that you either are asked and/or choose to respond with. Because it’s only a multiple choice option, I was somewhat constrained.  I subsequently was prodded for some assignments, and found I could do what I’d talked about.  I used the assignment tool to create questions that asked learners to go out and do things and then provide them with some guidance to self-evaluate.

One thing I learned is that I don’t have a good mental model of how the software works. I ‘get’ the tracks, but there’s another aspect I don’t understand. So, it turns out though I’d filmed myself at 720p, and exported at 720p, it still had an unnecessary border. Fortunately, in stumbling around I found a ‘crop’ setting that forced it to 1280 x 720 (720p), but I don’t understand  why that was necessary!?!?

I still want to add some examples (as documents) before I feel it’s fully ready to go. And I now sympathize much more with those who struggle to do good learning design under real-world constraints.  It’s also certainly been an example of my accepting assignments that are within my reach, but not within my grasp; my learning style ;).   More later, but thought I’d share my struggles and learning. I welcome your feedback.

Usability and Networks

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As I mentioned in an earlier post, I have been using Safari and Google to traverse the networks. And in a comment, I mentioned that the recent launch of the new Firefox browser was prompting me to switch.  And that’s now been put through a test, and I thought it instructive to share my learnings.

The rationale for the switch is that I don’t completely trust Google and Apple with my data. Or anyone, really, for that matter.  On principle. I had used Safari over Chrome because I trust Apple a wee bit more, and Firefox was a bit slow.  And Safari just released a version that stops videos from auto-starting. And similarly, Google’s search has been the best, and with a browser extension and some adjustments, I was getting ads blocked, tracking stopped, and more.  Still, I wasn’t happy.  And I hadn’t figured out how to do an image search with DuckDuckGo (something I do a fair bit) the last time I tried, so that hadn’t been a search option.

All this changed with the release of Firefox’s new Quantum browser. After a trial spin, the speed was good, as was the whole experience.  Now, I want to have an integrated experience  across my devices, so I downloaded the Firefox versions for my iDevices as well.  And, as long as I was changing, I tried DuckDuckGo again, and found it did have browser search.    So I made it my search engine as well.

And, after about a week of experience, I’m not sticking with Firefox.  The desktop version is all I want, but the iDevice versions don’t cut it. I use my toolbar bookmarks a  lot.  Many times a day.  And on the iDevices, they  do synch, but…they’re buried behind four extra clicks. And that’s just not acceptable.  The user experience kills it for me. Those versions  also don’t take advantage of the revised code behind the new desktop version, but it wasn’t the speed that killed the deal.  The point I want to make is that you have to look at the total experience, not just one or another in isolation. It’s time for an ecosystem perspective.

On the other hand, I’m still trying DuckDuckGo.  It seems to have a good output on it’s hits.  And the fact that they’re not tracking me is important.  If I can avoid it, I will.  Sure, my ISP still can track me, and so can Apple, but I’ll keep working on those.  Oddly, it seems to return differently on different devices (?!?!).  Still testing.

And, as long as we’re talking the net, I’m going to do something I don’t usually do here; I’m going to take a position on something besides learning. To do so, let me provide some context. I’ve been on the net since before there was a web.  Way before.  Circa 1978, I was able to send and receive email even though there  wasn’t any internet. I was at a uni with ARPANET, however, so I had a taste. Roll forward a decade and more, and I was playing with Gopher and WAIS and USENET before Tim Berners-Lee had created http.  That is, there were other protocols that preceded it. (In fact, I was blasé about the web at first, because of that; doh!)  My point is that I’ve been leveraging the benefits of networks for a bloody long time.

And now we depend on it. The internet is the basis for elearning! And, of course, so much more.  It has vastly accelerated our ability to interact. And while that’s created problems, it’s also enabled incredible benefits.  Innovation flourishes when there are open standards.  When people can build upon a solid and open foundation, creativity means new opportunity.  Network effects are true for people and for data.

Which is why I’m firmly in the camp for net neutrality.  This is important!  (It must be, because I used bold, which I almost  never do ;). The alternative, where providers will be able to throttle or even bar certain types of data will stifle innovation.  It’s like plumbing, telephone, and electricity: they need to be available as long as you can pay your bill (and there need to be options to support those with limited incomes).  Please,  please,  please  let your elected representatives and the FCC know that this is important to you.

 

My Professional Learner’s Toolkit

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My colleague, Harold Jarche, recently posted about his professional learning toolkit, reflecting our colleague Jane Hart’s post about a Modern Learner’s Toolkit. It’s a different cut through the top 10 tools.  So I thought I’d share mine, and my reflections.

Favorite browser and search engine: I use Safari and Google, by default. Of course, I keep Chrome and Firefox around for when something doesn’t work (e.g. Qualtrics).  I would prefer another search engine, probably DuckDuckGo, but I’m not facile with it, for instance finding images.

A set of trusted web resources: That’d be Wikipedia, pretty much. And online magazines, such as eLearnMag and Learning Solutions, and ones for my personal interests. I use Pixabay many times to find images.

A number of news and curation tools: I use Google News and the ABC (Oz, not US) in my browser, and the BBC and News apps on my iDevices. I also use Feedblitz to bring blogposts into my email.  I keep my own bookmarks using my browser.

Favorite web course platforms: I haven’t really taken online courses. I’ve used Zoom to share.

A range of social networks: I use LinkedIn professionally, as well as Slack. And Twitter, of course.  I stay in touch with my ITA colleagues via Skype.  Facebook is largely personal.

A personal information system: I use both Notability and Notes to take notes.  Notes more for personal stuff, Notability for work-related. I use Omnigraffle for diagrams and mindmaps.  And OmniOutliner also helps when I want to think hierarchically.

A blogging or website tool: I use WordPress for Learnlets (i.e. here), and I use Rapidweaver for my sites: Quinnovation and my book sites.

A variety of productivity apps and tools: Calendar is crucial, and Pagico keeps me on track for projects. I use Google Maps for navigation. I use SplashID for passwords and other private data. I often read and markup documents on my iPad with GoodReader. CloudClip lets me share a multi-item clipboard across my devices.    Reflection: this overlaps with the personal information system.

A preferred office suite: I don’t have a preferred suite, though I’d like to use the Apple Suite. I use Word to write (Pages hasn’t had industrial-strength outlining), Keynote to create presentations (e.g. one from each suite). I don’t create sheets often.

A range of  communication and collaboration tools: I use Google Drive to collaborate on representations.  I have used Dropbox to share documents as well. And of course Mail for email.   Reflection: this overlaps with social networks.

1 or more smart devices: I’d be lost without my iPhone and iPad (neither of which is the latest model). I use the phone for ‘in the moment’ things, the iPad for when I have longer time frames.

So, that’s my toolkit, what’s yours?

Jane's toolkit diagram

Rules for AI

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After my presentation in Shanghai on AI for L&D, there were a number of conversations that ensued, and led to some reflections. I’m boiling them down here to a few rules that seem to make sense going forward.

  1. Don’t worry about AI overlords.  At least, not yet ;).  Rodney Brooks wrote a really nice  article talking about why we might be fearing AI, and why we shouldn’t. In it, he cited Amara’s Law: we tend to overestimate technology in the short-term, and underestimate the impact in the long term. I think we’re in the short-term of AI, and while it’s easy to extrapolate from smart behavior in a limited domain to similar behavior in another (and sensible for humans), it turns out to be hard to get computers to do so.
  2. Do be concerned about how AI is being used. AI  can  be used for ill or good, and we should be concerned about the human impact.  I realize that a focus on short-term returns might suggest replacing people when possible. And anything rote enough possibly  should be replaced, since it’s a sad use of human ability.  Still, there are strong reasons to consider the impact on the people being affected, not least humanitarian, but also practical. Which leads to:
  3. Don’t have AI without human oversight  (at least in most cases).  As stated above in 1, AI doesn’t generalize well.  While it can be trained to work within the scope you describe, it will suffer at the boundary conditions, and any ambiguous or unique situations. It may well make a better judgment in those cases, but it also may not. In most cases, it will be best to have an external review process for all decisions being made, or at least ones at the periphery. Because:
  4. Your AI is only as good as it’s data set and/or it’s algorithms. Much of machine learning essentially runs on historical datasets. And historical datasets can have historical biases in them.  For instance, if you were to look at building a career counselor based upon what’s been done in many examples across schools, you might find that women were being steered away from math-intensive careers. Similarly, if you’re using a mismatched algorithm (as happens often in statistics, for example), you could be biasing your results.
  5. Design as if AI means Augmented Intelligence, not Artificial Intelligence (perhaps an extension of 3). There are things humans do well, and things that computers do well. AI is an attempt to address the intersection, but if our goal is (as it should be) to get the best outcome, it’s likely to be a hybrid of the two. Yes, automate what can and should be automated, but first consider what the best total solution would be, and then if it’s ok to just use the AI do so. But don’t assume so.
  6. AI on top of a bad system is a bad system. This is, perhaps, a corollary to 4, but it goes further. So, for instance, if you create a really intriguing simulated avatar for practicing soft skills, but you’re still not really providing a good model to guide performance, and good examples, you’re either requiring considerable more practice or risking an inappropriate emergent model.  AI is not a panacea, but instead a tool in designing solutions (see 5).  If the rest of the system has flaws, so will the resulting solution.

This is by no means a full set, nor a completely independent one. But it does reflect some principles that emerged from my interactions around some applications and discussions with people. I welcome your extensions, amendments, or even contrary views!

Addressing Changes

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Yesterday, I listed some of the major changes that L&D needs to acknowledge. What we need now is to look at the top steps that need to be taken.  As serious practitioners in a potentially valuable field, we need to adapt to the changing environment as much as we need to assist our charges to do so. So what’s involved?

We need to get a grasp on technology  affordances. We don’t need to that the latest technology exists, whether AI, AR, or VR.  Instead, we have to understand what they mean  in the context of our brains.  What key capabilities are brought?  Can VR go beyond entertainment to help us learn better? How can AI partner with us?  If we can make practical use of AR, what would we do with it?

In conjunction, we need to  understand the realities about us.  We need to take ownership and have a suitable background in how people  really think, work, and learn. Further, we need to recognize that they’re all tied together, not separate things. So, for instance, we learn as we work, we think as we learn, etc.

For example, we need to understand situated and distributed cognition. That is, we need to grasp that we’re not formal logical thinkers, but instead very context dependent, and that our thinking is across our tools. As a consequence, we need to design solutions that recognize our individual situations, and leverage technology as an augment. So we want to design human/computer system solutions to problems, not just human or system solutions.

We also need to understand cultural elements. We work better when we are given meaningful work, freedom to pursue those goals, and get the necessary support to succeed. This is  not micromanagement, but instead, is leadership and coaching. We also need an environment where it’s safe, expected even, to experiment and even to make mistakes.

We also need to understand that we work better (read: produce better results), when we work together in particular ways. Where we understand that we should allow individual thought first, but then pool those ideas. And we need to show our work and the underlying thinking. Moreover, again, it has to be safe to do so!

And, these are all tied together into a systemic approach!  It can’t be piecemeal, because working together and out loud can’t be divorced from the technology used to enable these capabilities. And giving people meaningful work and not letting them work together, or vice-versa, just won’t achieve the necessary critical mass.

Finally, we also need to do this in alignment with the business. And, lets be clear, in ways that can be measured!  We need to be understanding what are the critical performance needs of the organization, and demonstrate that we’re impacting them in the ways above.

This can be done, and it will be the hallmark of successful organization. We’re already seeing a wide variety of converging evidence that these changes lead to success. The question is, are you going to lead your organization forward into the future, or keep your head down and do what you’ve always done?