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Clark Quinn’s Learnings about Learning

Activity or Application?

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I’m a fan of Michael Allen’s, not only because he knows his stuff and he’s a very good person, but also because he has a knack for making things accessible.  For example, his Guide to eLearning is as good a guide to designing elearning as you can get (that and Julie Dirksen’s Design for How People Learn, both appropriately in their second edition).  So when I thought to criticize one of his models, I had to think  really hard!  And I’m still wrestling with it, but I also realize I’d gone down the same path!  Obviously, it’s time to explore the issue.

One of Michael’s models is the CCAF model for making meaningful elearning.  That’s:

  • Context: that sets up the situation
  • Challenge: that prompts the need for action
  • Activity: that the learner takes, and
  • Feedback: that comes from the situation.

There are nuances about this, but it nicely incorporates some of the best principles about designing effective (and engaging) practice. If you put people in a context and ask them to act, you’re minimizing the distance between the practice and the actual performance. Which is, of course, key to successful transfer.  So this is a very handy shorthand, like Cathy Moore’s Action Mapping.

Now, in many ways, this is similar to my own activity-based design, which is more a curricular model than a pedagogical one, but it foregrounds activity instead of content. The goal is to have learners  do something!  And, of course, I’m thinking of creating a work product in many instances, or making meaningful decisions.

So what was I concerned about?  Perhaps because I’d been thinking (and whinging) about ‘click to see more’ interactions, I want those activities to  mean something!  You could have an activity that’s just ‘matching’, or ‘identify the right word’ type of knowledge test. Those  are activities, just not cognitively challenging ones.  And of course Michael emphasizes this in his descriptions, but…there’s an opportunity for people to be slack.

I wondered about using ‘application’ instead of activity, focusing on the fact that people should be applying the knowledge to  do something, not just doing any sort of activity. Do the semantics matter enough to be worth considering?  Application-based design?  Context-Challenge-Application-Feedback? Perhaps not, but I thought I’d think ‘out loud’ as usual. (Both to reiterate the point as well as to solicit your input.) So, what are your thoughts? Worth it?  Or too much ‘splitting angel’s hairs on the head of a pin’ (metaphors mixed while you wait)?

Possible versus practical

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Last week, I gave a presentation to the local chapter of ATD. And I was surprised that their request was for mobile learning. Now that  is something I can speak to, but given that my book on the topic came out seven years ago now, it seemed like a dated topic. And I was wrong.  And the difference is between what’s possible and what’s practical.

Ok, so I am somewhat out ahead of the curve.  My games book came out in 2005, but the market wasn’t quite ready.  I similarly think my L&D revolution book, in 2014, was ahead of the market (the topic is finally getting more traction, close to four years later), though closer. But I thought the mlearning book was timely (not least because my publisher asked for it more than it was my initiative ;).

However, the audience was eager.  And it was relatively large for the group.  And it took a comment from the organizer to raise my awareness.  He said (and I paraphrase): “you think that it’s old, but it’s not old for everyone”. And that was indeed a wakeup call.  Because while mobile to me is very practical, for many it’s still possible.

I  do tend to move on once I reckon I’ve figured something out. I’m interested when it’s still something to be understood or solved. Once I have my mind around it, my restless brain is on to something new.  That’s why I have this blog, for instance, to wrestle with new thoughts. If they get organized enough, it becomes a presentation or even a book.  (Though sometimes I do ones that are requested, e.g. my forthcoming one on myths, and I’m supposed to be reviewing the second round of proofs!)

But the interesting thing to me is to look beyond my own bubble (and what my colleagues are talking about).  We’re looking at what’s possible but not yet done, or what’s on the horizon. Yet I need to remember to continue to tout what’s now on the menu, and recognize not everyone’s yet started moving.  The things that I think are already practical to implement are still on the ‘possible’ list for others.

If you’re reading this blog, you’re probably with me, but feel free to let others know that the things in my past I’m still happy to help with!  In any way: consulting or workshops or even speaking.  For instance, I’ll be talking engagement for the Guild at Learning Solutions, and in a webinar for AECT’s Learner Engagement group.  Just as I talk new things, like myths.  What goes around comes around, I guess, and what’s been possible is now practical.  Ask me how!

 

Consciously Considering Consciousness

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Consciousness is an interesting artifact of our cognitive architecture. And no, (despite being a native Californian ;) I’m  not talking about social or environmental or higher consciousness. Here I’m talking about our conscious thinking, the insight we have (or not) into our own internal thinking. And it’s interesting  and  relevant.

First, we really don’t have a full understanding of consciousness. It’s a phenomena ew pretty much all experience, but the actual mechanism about how, or where, it arises in our brain is still a mystery.  How do we have this perception of a serial narrative in our head, but our brain is massively parallel?  Yet it’s there. At least, to conscious inspection ;).

Actually, much of our processing  is subconscious. We compile away our expertise as we develop it. We use conscious dialog (internal  or external) to shape our performance, but what we actually  do gets stored away without explicit access. In fact, research says that 70% of what experts do (and that’s us, in our areas of expertise) isn’t accessible. Thus, experts literally  can’t tell us what they do! (Warning, warning: important implications for working with SMEs!)

In fact, consciousness is typically used to deal with situations that aren’t practiced: conversations on topics, dealing with unique problems, and of course learning new things.  Informal learning is pretty much all conscious, while formal learning is about practicing to make the conscious become unconscious!

Which, of course, is why the ‘event’ model of learning doesn’t work. There’s not enough practice, spaced out over time, for that learning to become automated. And we don’t expect our formal learning to get us all the way there, we use coaching and feedback to continue to happen.

As learning experience designers or learning engineers, our job is to make sure we provide the  right support for using our conscious thoughts to guide our practice.  That includes models to explain and predict outcomes, and cognitive annotated examples to model the appropriate solution. And, of course, practice that gradually develops the expertise in appropriate sized chunks and spacing between.  I suppose we should be conscious of consciousness in our design ;). So what am I unconsciously missing?

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.

 

The necessary program?

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Things are moving faster, and careers are supposed to be changing more frequently. What does that mean for university degrees (or other employment preparation)?  Yes, university degrees aren’t necessarily  just employment preparation, but I’m thinking about a degree program that provides a useful preparation for the coming world. And I think it’s got several key components.

For one, anything we do, in working together and in meeting client needs,  must be aligned with how our brains work. Industrial design, interface design, learning design, marketing; increasingly everything  about  our products and services must be producing  experiences.  And, if the prognostications are to be believed, experiences that  transform  us.  Increasingly, organizations will need to work in such ways, and those that understand this will be core. Similarly, increasingly products and services will likewise need to adapt. At core, everything we do revolves around thinking,  and our brains aren’t changing. Understanding cognition is a sustainable value.

A second such areas is understanding information technology. Increasingly, the capability of computational systems to serve as configurable information processing machines is fundamental to society. It’s the perfect cognitive complement, doing well what our brains don’t, and vice-versa.  And while the technology continues to evolve, some core understandings don’t. Computational thinking is focused on breaking down problems into tractable steps, and that’s part of it. And understanding how AI works (e.g. machine learning, symbolic logic, neural nets, etc), and even quantum computing, are tools to solve problems. People need to understand computational technology to complement our cognitive capability, and it’s stable enough to again be a sustainable edge.

Then, the question is, what complements these to provide a solid foundation. I have two answers: one is design (e.g. design thinking), and the other is business. And I had trouble reconciling this until recently.  So, in some sense, design is an  outcome of our cognitive processes, and an application. (To design is human!)  But being systematic about it is a useful integration of the other two. For those who haven’t had experience in business, however, an overall understanding of business is key.  This suggests that a full bachelor’s program would include design  and business, while a master’s program could focus more specifically on the design (assuming some business experience).

Could these be minors on some other area people might want? It might be good to supplement this with specific interests whether bio, art, or what have you.  You do want to support people’s passions. But I’ll suggest that these elements  should be part of all folks preparation for life going forward.  So, what do you think?

 

Chief Cognitive Officer?

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Businesses are composed of core functions, and they optimize them to succeed. In areas like finance, operations, and information technology, they prioritize investments, and look for continual improvement. But, with the shift in the competitive landscape, there‘s a gap that’s being missed. And I‘m wondering if a focus on cognitive science needs to be foregrounded.

In the old days, most people were cogs in the machine. They weren‘t counted on to be thinking, but instead a few were thinking for the many. And those who could do so were selected on that basis. But that world is gone.

Increasingly, anything that can be automated should be automated.   The differentiators for organizations are no longer on the execution of the obvious, but instead the new advantage is the ability to outthink the competition. Innovation is the new watchword.   People are becoming the competitive advantage.

However, most organizations aren‘t working in alignment with this new reality. Despite mantras like ‘human capital management’ or ‘talent development’, too many practices are in play that are contrary to what‘s known about getting the best from people. Outdated views like putting information into the head, squelching discussion, and avoiding mistakes are rife. And the solutions we apply are simplistic.

Ok, so neuroscientist John Medina  says our understanding of the brain is ‘childlike‘.   Regardless, we have considerable empirical evidence and conceptual frameworks that give us excellent advice about things like distributed, situated, and social cognition. We know about our mistakes in reasoning, and approaches to avoid making mistakes. Yet we‘re not seeing these in practice!

What I‘m suggesting is a new focus.   A new area of expertise to complement technology, business nous, financial smarts, and more.   That area is cognitive expertise. Here I’m talking about someone with organizational responsibility, and authority, to work on aligning practices and processes with what‘s known about how we think, work, and learn. A colleague suggested that L&D might make more sense in operations than in HR, but this goes further. And, I suggest, is the natural culmination of that thought.

So I‘m calling for a Chief Cognitive Officer. Someone who‘s responsibility ranges from aligning tools (read: UI/UX) with how we work, through designing continual learning experiences, to leveraging collective intelligence to support innovation and informal learning.   Doing these effectively are all linked to an understanding of how our brains operate, and having it distributed isn‘t working.  The other problem is that not having it coordinated means it‘s idiosyncratic at best.

One problem is that there‘s too little of cognitive awareness anywhere in the organization.  Where does it belong?  The people closest are (or should be) the L&D (P&D) people.  If not, what’s their role going to be?  Someone needs to own this.

Digital transformation is needed, but to do so without understanding the other half of the equation is sort of like using AI on top of bad data; you still get bad outcomes.  It’s time to do better. It’s a radical reorg, but is it a necessary change?  Obviously, I think it is. What do you think?

About this change to the site…

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So, I’d been unhappy with how hard it was to update my site. It had some problems, but I was afraid to change it because of the repercussions. Well, it turns out that’s not a problem! So what you see is my first stab at a new site. A little background…

My ISP, a good friend, colleague, and mentor, was making some changes to how my sites are implemented.  While my other sites (Quinnovation and the book sites) are all done in a WYSIWIG tool called RapidWeaver, Learnlets is a WordPress site. While I could do a blog  in Rapidweaver, I’m afraid I’d lose my decade+ of posts!  So, I’ve kept it in WordPress.  And that’s handy for updating the site when I’m on the road (e.g. for mindmaps).

However, my ISP, in addition to being a tech guru, is also a security guru.  He does tech for a living, and is kind enough to host me as well. To prevent some of the attacks that were happening to WordPress sites (hey, write a script that hammers WordPress vulnerabilities and point it to all their sites you can find), he instituted some security measures. One was that I couldn’t get into the PHP code for my sidebar!  It made sense, because if anyone could get access to my admin code, they could not only change the look and feel (easy to fix), they could alter the code and put in malicious stuff. Not good. But…

I’d cobbled it together with cut-and-pasted code, but now I couldn’t edit it without downloading the raw source (once I could find the file in the WordPress hierarchies), editing it, and uploading.  I couldn’t even access the sidebar editor!  I had a second login for upgrading the site, but it wouldn’t allow access to things I wanted to customize. And I have a bad habit of tinkering!  As things happen, I might want to add an image, or…what have you.

So, with this upgrade, I mentioned my problems with the site, and he installed some new themes I could play with.  And, I found, it was pretty much click and type to create a new sidebar. Suddenly, it’s  easy to change the site, without coding!  It’s not perfect, but it’s better for mobile (a friend had complained about that).

As evidence, somehow it seized up in the midst of creating the first draft.  I was going to have to  re-create the new site!  First, it would’ve been easy. I’d created most of the graphics and put them in a location.  And, it remembered my previous choices, and restored them so I didn’t have to!

I asked my lad, who has a good digital aesthetic, to give me feedback on two of the options my colleague installed, and he liked this one, with a suggestion on the background (not a stock photo).  I’m using the background image from the  Designing mLearning book cover, but that can be changed.  He didn’t like the idea of the bag of bulbs from the Quinnovation site, as he thought it was ‘stock’. I  think it’s aligned with the notion of Quinnovations (or I wouldn’t have used it), and so too with Learnlets, but in honor of his opinion I’m sticking with this for now.  And I appreciate that he shared his thinking!

Now that I have a draft up, what’s working and what’s not?  I still need to figure out a way to let folks sign up for Learnlets as an email feed (beyond RSS, but through Feedblitz, the service I use), but other than that it’s pretty much the same. And easier to tweak! (E.g., I have subsequently gone to the Feedblitz site, used their tool to create the widget HTML code, and it’s now on the sidebar as well.)

So, the question is, what  should I tweak?  I’ll definitely listen on usability issues, and I’ll consider aesthetic ones ;).  Regardless, thought I’d share the rationale and the process, because that’s what ‘working out loud’ is, and I think it’s part of the moves we need to see. And in return, getting feedback. So, what doesn’t work for you?

Skeptical Optimist or Hopeful Cynic? A Science Mindset

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Is there any difference? At core, my new book  is  about learning science. And, as I’ve lamented before, the lack of understanding of cognitive science is a barrier to better L&D. However, it takes a certain mindset to put this into practice in practical ways.

Should you overall be optimistic or cynical?  Applying cognitive science (see what I did there?), I would err on the side of optimism.  Research suggests a positive attitude is overall better.  Thus, I guess I’m arguing for the former ;). The alternative, a cynic still looking for good, is less optimal.

However, optimism tempered with  a healthy skepticism! There are those who’d take advantage of naivete, as has reliably been exposed.  A vigilant evaluation of what’s presented is healthy for dialog and moving the industry forward!

You need to be prepared for the variety of ways people can mislead you (and even themselves).  Without a decent understanding of scientific validity, you might be swayed by statistical sleight-of-hand.  Worst case, you listen to those who carry the standard of rigor in evaluation.  I don’t necessarily mean the scientists, because they don’t always present it in comprehensible ways (writing in their native academese).  Instead, there are those who serve as translators of research to practice.

People like Will Thalheimer, Patti Shank, Julie Dirksen, Guy Wallace, Mirjam Neelen, and more (including yours truly), have boiled down learning science into practical approaches. Whether it’s overviews, processes, or even acronyms, their guidance is soundly based.  We may not always agree, but you’re far better off betting on them than on those with a vested interest.

On your own, of course, you should be conducting several validity checks.  Who’s telling you, and what’s in it for them?  Is their message supported by external validation? Are there alternate views? Does it pass the ‘sniff’ test (that is, does it make a plausible causal story)?  Of course, “if it sounds too good to be true, it probably is”.

In addition to empirical grounds, one should also evaluate the theoretical basis.  Did the work emerge from empirical data, or was it made from someone’s musings, and untested?  Is there a reason to accept the underlying frameworks?

Overall, I suggest that practitioners in learning first need to be grounded in understanding  how we learn. Then, I reckon we need to be rigorous in evaluating new approaches.  There will be wheat amongst the chaff, but the relative ratios are the issue. Make sure you’re finding nuggets, not tailings (I like my metaphors mixed).

 

At the edge

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Revolutionize book coverAnother response to my request for topics asked about moving from the classroom to the ‘fringe’.  Here, I have a very simple response: the case studies in Revolutionize Learning & Development. Each was chosen and structured to talk about the context, specific situation, the plan, the results, and advice.  Each also represents a diversity of settings and needs.  These represent some folks working at the edge, away from the ‘event’.

Mark Britz, facing more experts than novices, structured his corporate university as a network, not a series of courses.  Communities of Practice served as a model for this thinking.  This included and Enterprise Social Network and a Knowledge Management system.

Jos Arets and Vivian Heijnin at Tulser talked through a case study working with a medical care organization.  The problem was too much hierarchy. Using a Human Performance Improvement approach, they decentralized the work to more self-directed teams.  The solution includes continuous assessment, mobile performance support, and coaching.

Coaching also played a role in the case study Jane Bozarth provided.  The issue was solving workplace problems. Instead of courses, the solution connected those with demonstrable skills to mentor those who could benefit.  A ‘yellow pages’ to find ‘in the moment’ help was also a part.

For an internal self-help solution, Allison Anderson developed a community of practice with events, portal, and a networking platform. Here, the issues was getting disparate groups performing similar functions (L&D) to share best principles.

I had Charles Jennings recount his actions while serving as CLO in a global organization. With a mantra of ‘from event to process’, he used the 70:20:10 framework to rethink a balance of ‘push’ and ‘pull’ services.

In the book, they tell the stories in their own words. They unpack the thinking behind their choices, ‘showing their work’.  The contributions are very valuable, and I’m very grateful that they agreed to share them.  For that matter, you should find and track these folks!

Each of these were chosen as exemplary of the type of thinking that takes us from the old model to the ‘edge’. We want to be looking holistically at how people think, work, and learn, and aligning our infrastructure (policies, technology, procedures, and culture) accordingly.  This is the L&D part of a larger push to make the workplace more effective by making it more humane (read: more aligned with  us).