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Clark Quinn’s Learnings about Learning

Transparency

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I believe that transparency is a good thing. It builds trust, as it makes it hard to hide things.  And trust is important. So, in the spirit of transparency, it occurred to me to share a little bit about me and this blog. Here I lay out who I am, why I write it, and what I write about.

You can find out more via the ‘about Clark Quinn’ link in the right column, but in brief, I saw the connection between computing and learning as an undergraduate, and it’s been my career ever since. It’s not just my vocation, but it’s my avocation: I  enjoy exploring cognition and technology. And while I’ve done the science and track it, what I revel in (and have demonstrable capability for), is applying cognitive and learning science to create new approaches and fine-tune existing ones.  Learning engineering, if you will.

And, for a variety of reasons, I do this as a consultant. I make my living providing strategic guidance for clients.  I speak at events, and write books, but my main income is from consulting. Which means you  should hire me.  I assist organizations to improve their processes and products, both tactically and strategically. My clients have been happy, and find it’s good value. What you get are unique ideas that are practical and yet effective. Ideas you aren’t likely to have come up with, but are valuable. I really do Quinnovate! Check out the Quinnovation site for more.    Of course, I do have to live in the real world, and so I need to find ways to do this that are mutually beneficial.

Yet generating business isn’t why I write this blog.  I started writing this blog as an experiment and originally tried to write 5 days a week (but was happy if that ended up being 2-3 times a week).  My commitment now is 2 per week (which rarely yields 1 or 3).  And I haven’t monetized it: there’s no advertising, and while I occasionally talk about where I’m speaking or the like, I haven’t used this as a way to sell things. Hopefully that can continue.

So, the reason I write is to think ‘out loud’.  It’s largely for me: it makes me think. I’m just always curious!  I’ve previously recounted the story about how I was on a panel answering questions from the audience, and one of my fellow panelists commented that I had an answer for everything. And the reason is in the ongoing attempt to populate the blog, I’ve looked at lots of things. As my client engagements have been in many different areas, I also have wide-ranging experience to draw upon.  And I just naturally reflect, but getting concrete: diagramming and/or writing, provides additional benefits.

Thus, the process of continually writing (for over 10 years now) means I’m looking at lots of things, reflecting on them, and sharing my thoughts. I also make a point to look at related fields, and look for connections. I also look at what’s happening with technology. In general, I look with a critical eye, as I was trained as a scientist.  I think that’s valuable as well, because there still is a lot of nonsense trotted out, and there’s always some new buzzword that’s being loosely tossed about. Blogging’s given me cause to continue to tune my thinking, and at least some folks have commented that they’ve found it useful.

Mostly I write about things related to technology, learning, and individual and organizational implications. It includes diversions to innovation, design, wisdom, performance support, and the like, because they’ve implications for practice. In many ways I see approaches that aren’t well aligned with how we think, work, and learn, and that strikes me as both a shame, and an opportunity to improve. And that’s what I enjoy, finding ways to improve what we do.

So that’s it: I blog to facilitate my understanding, because cognitive science and technology  is my passion. It isn’t a direct business move.  I do need to make a living, and prefer to do it in the area of my passion, and fortunately have been successful so far.  (Which isn’t to say you shouldn’t find a reason to use me, there are never enough opportunities to assist in improvement, and I’m not a sales person ;).  And yes, this life is a learning experience all in itself!  I hope this is clear, but in the interests of transparency I welcome your inquiries and comments. Stay curious, my friends.

 

Mark Kelly C3 Keynote Mindmap

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Astronaut Mark Kelly gave a warm, funny, and inspiring talk.  He used stories from his youth, learning to fly, becoming an astronaut, and being husband to Gabby Gifford to emphasize key success factors.

(I confess that owing to his style of elocution, punctuating stories with very pithy comments, I may have missed a point or two at the beginning until I picked up on it.)

 

Coping with Cognition

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Our brains are amazing things. They make sense of the world, and have developed language to help us both make better sense together and to communicate our learnings. And yet, this same amazing architecture has some vulnerabilities too. And I just fell prey to one, and it’s making reflect on what we can do, and what we still can’t. Our cognition is powerful, but also limited.

So, yesterday I had a great idea for a post for today. Now, I multi-task, and I have several things going at once. I have strategies to get these things done despite the fact that multi-tasking doesn’t work. So for one, I have a specific goal for several of the projects each day. I write tasks for projects into a project management tool. I even keep windows open to remind me of things to do. And I write non-project oriented tasks into a separate ToDo list.  But…

I didn’t document the blog post idea before I did something else, and got distracted by one of my open projects. I don’t know which, but I lost the post.  Many times, I can regenerate it, but this time I couldn’t.

See, our brain has limitations, and one of them is a limited working memory. And we have evolved powerful tools to support those gaps, including those mentioned above. But we can’t capture all of them.  Will we be able to? Unless I consciously acted  at the time to do something, whether asked Siri to note it, or made a note, those ephemeral thoughts can escape.  And I’m not sure that’s a bad thing.

The flaws in our thinking actually have advantages.  We can let go ideas to deal with new ones. And we can miss things because we’re focusing on something. That’s the power of our architecture.  And if we focus on the power, and scaffold as much as we can, and let go what we can’t, we really shouldn’t ask for more.

Our ability to scaffold continues to get better. AI, better interfaces, more processing power, better device interoperations, and smaller and more capable sensors are all ongoing. We’re learning more about putting that to use by via innovation.  And yet we’ll still have gaps. I think we should be ok with that. Serendipity and experimentation mean we’ll have unintended consequences, and generally those may be bad, but every once in a while they may be better. And we can’t find that without some ‘wildness’ (which is also an argument for nature conservation).  So I’m trying to not get too upset.  I’m cutting our cognition some slack. Let’s not lose the ability to be human.

Extending Engagement

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My post on why ‘engagement’ should be added to effective and efficient led to some discussion on LinkedIn. In particular, some questions were asked that I thought I should reflect on.  So here are my responses to the issue of how to ‘monetize’ engagement, and how it relates to the effectiveness of learning.

So the first issue was how to justify the extra investment engagement would entail. It was an assumption that it  would take extra investment, but I believe it will. Here’s why. To make a learning experience engaging, you need some additional things: knowing why this is of interest and  relevance  to practitioners, and putting that into the introduction, examples, and practice.  With practice, that’s going to come with only a marginal overhead. More importantly, that is part of also making it more effective. There  is some additional information needed, and more careful design, and that  certainly is more than most of what’s being done now. (Even if it should be.)

So why would you put in this extra effort?  What are the benefits? As the article suggested, the payoffs are several:

  • First, learners know more intrinsically why they should pay attention. This means they’ll pay more attention, and the learning will be more effective. And that’s valuable, because it should increase the outcomes of the learning.
  • Second, the practice is distributed across more intriguing contexts. This means that the practice will have higher motivation.  When they’re performing, they’re motivated because it  matters. If we have more motivation in the learning practice, it’s closer to the performance context, so we’re making the transfer gap smaller. Again, this will make the learning more effective.
  • Third, that if you unpack the meaningfulness of the examples, you’ll make the underlying thinking easier to assimilate. The examples are comprehended better, and that leads to more effectiveness.

If learning’s a probabilistic game (and it is), and you increase the likelihood of it sticking, you’re increasing the return on your investment. If the margin to do it right is less than the value of the improvement in the learning, that’s a business case. And I’ll suggest that these steps are part of making learning effective,  period. So it’s really going from a low likelihood of transfer – 20-30% say – to effective learning – maybe 70-80%.  Yes, I’m making these numbers up, but…

This is really all part of going from information dump & knowledge test to elaborated examples and contextualized practice.  So that’s really not about engagement, it’s about effectiveness. And a lot of what’s done under the banner of ‘rapid elearning’ is ineffective.  It may be engaging, but it isn’t leading to new skills.

Which is the other issue: a claim that engagement doesn’t equal better learning. And in general I agree (see: activity doesn’t mean effectiveness in a social media tool). It depends on what you mean by engagement; I don’t mean trivialized scores equalling more activity. I mean fundamental cognitive engagement: ‘hard fun’, not just  fun.  Intrinsic relevance. Not marketing flare, but real value add.

Hopefully this helps!  I really want to convince you that you want deep learning design if you care about the outcomes.  (And if you don’t, why are you bothering? ;).  It goes to effectiveness, and requires addressing engagement. I’ll also suggest that while it  does affect efficiency,  it does so in marginal ways compared to substantial increases in impact.  And that strikes me as the type of step one  should be taking. Agreed?

 

My policies

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Like most of you, I get a lot of requests for a lot of things. Too many, really. So I’ve had to put in policies to be able to cope.  I like to provide  a response (I feel it’s important to communicate the underlying rationale), so I have stock blurbs that I cut and paste (with an occasional edit for a specific context).  I don’t want to repeat them here, but instead I want to be clear about why certain types of actions are going to get certain types of response. Consider this a public service announcement.

So, I get a  lot of requests to link on LinkedIn, and I’m happy to, with a caveat. First, you should have some clear relationship to learning technology. Or be willing to explain why you want to link. I use LinkedIn for business connections, so I’m linked to lots of people I don’t even know, but they’re in our field.

I ask those not in learntech  why they want to link. Some do respond, and often have a real reason (shifting to this field, their title masks a real role), and I’m glad I asked.  Other times it’s the ‘Nigerian Prince’ or equivalent. And those will get reported. Recently, it’s new folk who claim they just want to connect to someone with experience. Er, no.  Read this blog, instead. I also have a special message to those in learntech with biz dev/sales/etc roles; I’ll link, but if they pitch me, they’ll get summarily unlinked (and I do).

And I likely won’t link to you on Facebook.  That’s personal. Friends and family. Try LinkedIn instead.

I get lots of emails, particularly from elearning or tech development firms, offering to have a conversation about their services.  I’m sorry, but don’t you realize, with all the time I’ve been in the field, that I have ‘goto’ partners? And I don’t do biz dev: develop contracts and outsource production. As Donald H Taylor so aptly puts it,  you haven’t established a sufficient relationship to justify offering me anything.

Then, I get email with announcements of new moves and the like.  Apparently, with an expectation that I’ll blog it.  WTH?  Somehow, people think this blog is for PR.  No, as it says quite clearly at the top of the page, this is for  my  learnings about learning.  I let them know that I pay attention to what comes through my social media channels, not what comes unsolicited.  I also ask what list they got my name from, so I can squelch it. And sometimes they have!

I used to get a lot of offers to either receive or write blog posts. (This had died down, but has resurrected recently.)    For marketing links, obviously. I don’t want your posts; see the above: my learnings!   And I won’t write for you for free. Hey, that’s a service.  See below.

And I get calls with folks offering me a place at their event.  They’re pretty easy to detect: they ask about would I like to have access to  a specific audience,…  I have learned to quickly ask if it’s a pay to play.  It always is, and I have to explain that that’s not how I market myself.  Maybe I’m wrong, but I see that working for big firms with trained sales folks, not me. I already have my marketing channels. And I speak and write as a service!

I similarly get a lot of emails that let me know about a new product and invite me to view it and give my opinion.  NO!  First, I could spend my whole day with these. Second, and more importantly, my opinion is  valuable!  It’s the basis of 35+ years of work at the cutting edge of learning and technology. And you want it for free?  As if.  Let’s talk some real evaluation, as an engagement.  I’ve done that, and can for you.

As I’ve explained many times, my principles are simple: I talk ideas for free; I help someone personally for drinks/dinner; if someone’s making a quid, I get a cut.  And everyone seems fine with that, once I explain it. I occasionally get taken advantage of, but I try to make it only once for each way (fool me…).    But the number of people who seem to think that I should speak/write/consult for free continues to boggle my mind.  Exposure?  I think you’re overvaluing your platform.

Look, I think there’s sufficient evidence that I’m very good at what I do. If you want to refine your learning design processes, take your L&D strategy into the 21st century, and generally align what you do with how we think, work, and learn, let’s talk.  Let’s see if there’s a viable benefit to you that’s a fair return for me. Lots of folks have found that to be the case.  I’ll even offer the first conversation free, but let’s make sure there’s a clear two-way relationship on the table and explore it.  Fair enough?

 

 

Ethics and AI

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I had the opportunity to attend a special event pondering the ethical issues that surround Artificial Intelligence (AI).  Hosted by the Institute for the Future, we gathered in groups beforehand to generate questions that were used in a subsequent session. Vint Cerf, co-developer of the TCP/IP protocol that enabled the internet, currently at Google, responded to the questions.  Quite the heady experience!

The questions were quite varied. Our group looked at Values and Responsibilities. I asked whether that was for the developers or the AI itself. Our conclusion was that it had to be the developers first. We also considered what else has been done in technology ethics (e.g. diseases, nuclear weapons), and what is unique to AI.  A respondent mentioned an EU initiative to register all internet AIs; I didn’t have the chance to ask about policing and consequences.  Those strike me as concomitant issues!

One of the unique areas was ‘agency’, the ability for AI to  act.  This led to a discussion for a need to have oversight on AI decisions. However, I suggested that humans, if the AI was mostly right, would fatigue. So we pondered: could an AI monitor another AI?  I also thought that there’s evidence that consciousness is emergent, and so we’d need to keep the AIs from communicating. It was pointed out that the genie is already out of the bottle, with chatbots online. Vint suggests that our brain is layered pattern-matchers, so maybe consciousness is just the topmost layer.

One recourse is transparency, but it needs to be rigorous. Blockchain’s distributed transparency could be a model. Of course, one of the problems is that we can’t even explain our own cognition in all instances (we make stories that don’t always correlate with the evidence of what we do). And with machine learning, we may be making stories about what the system is using to analyze behaviors and make decisions, but it may not correlate.

Similarly, machine learning is very dependent on the training set. If we don’t pick the right inputs, we might miss some factors that would be important to incorporate in making answers.  Even if we have the right inputs, but don’t have a good training set of good and bad outcomes, we get biased decisions. It’s been said that what people are good at is crossing the silos, whereas the machines tend to be good in narrow domains. This is another argument for oversight.

The notion of agency also brought up the issue of decisions.  Vint inquired why we were so lazy in making decisions. He argued that we’re making systems we no longer understand!  I didn’t get the chance to answer that decision-making is cognitively taxing.   As a consequence, we often work to avoid it.  Moreover, some of us are interested in X, so are willing to invest the effort to learn it, while others are interested in Y. So it may not be reasonable to expect everyone to invest in every decision.  Also, our lives get more complex; when I grew up, you just  had phone and TV, now you need to worry about internet, and cable, and mobile carriers, and smart homes, and…  So it’s not hard to see why we want to abrogate responsibility when we can!  But when can we, and when do we need to be careful?

Of course, one of the issues is about AI taking jobs.  Cerf stated that nnovation takes jobs, and generates jobs as well. However, the problem is that those who lose the jobs aren’t necessarily capable of taking the new ones.  Which brought up an increasing need for learning to learn, as the key ability for people. Which I support, of course.

The overall problem is that there isn’t a central agreement on what ethics a system should embody, if we  could do it. We currently have different cultures with different values. Could we find agreement when some might have different view of what, say, acceptable surveillance would be? Is there some core set of values that are required for a society to ‘get along’?  However, that might vary by society.

At the end, there were two takeaways.  For one, the question is whether AI can helps us help ourselves!  And the recommendation is that we should continue to reflect and share our thoughts. This is my contribution.

Reflection ‘out loud’

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I am a fan of Show Your Work and Work Out Loud, but I’m wondering about whether they could mislead.  Not that that’s the intent, of course, but they don’t necessarily include reflection, a critical component. I believe they care about it, but the phrase don’t implicitly require annotating your thoughts. And I think it’s important.

The original phrase that resonated for me was ‘narrate your work’, which to me was more than just showing it.  When teachers told you to show your work, they just wanted intermediate steps. But Alan Schoenfeld’s research has documented that’s valuable to show the thinking  behind the steps. What’s your rationale for taking this step?

Teachers would be able to identify where you went wrong, but that doesn’t necessarily say  why you went wrong. On things as simple as multi-column subtraction, the answer would tell you whether they borrowed wrong or reversed the number or other specific misconceptions that would reveal themselves in the result. But on more complex problems, the intermediate steps may not preserve the rationale.

The design rationale approach emerged on complex projects for just this reason. New people could question earlier decisions and if they weren’t documented, you’d revisit them unnecessarily.  It’s important to capture not only the decision, but the criteria used, the others considered, etc.  It is this thinking  about what drove decisions that helps people understand your thinking and thereby improve it.

I don’t really think “reflection  out loud” is the right term. I like ‘narrate your work’ or ‘share your thinking’ perhaps better.  And I  do believe that those talking about working out loud and sharing your work do intend this, it’s just that too often I’ve seen people take the surface implications of a phrase and skip the real importance (*cough* Kirkpatrick’s levels *cough*). So, worst case, I’ve confused the terminology space, but hopefully I’ve also helped illuminate the valuable underpinning.  And practiced what I’m preaching ;).  Your thoughts?

Jay Cross Memorial Award 2017: Marcia Conner

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The Internet Time Alliance Jay Cross Memorial Award is presented to a workplace learning professional who has contributed in positive ways to the field of Real Learning and is reflective of Jay‘s lifetime of work. Recipients champion workplace and social learning practices inside their organization and/or on the wider stage. They share their work in public and often challenge conventional wisdom. The Jay Cross Memorial Award is given to professionals who continuously welcome challenges at the cutting edge of their expertise and are convincing and effective advocates of a humanistic approach to workplace learning and performance.

We announce the award on 5 July, Jay‘s birthday. Following his death in November 2015, the partners of the Internet Time Alliance (Jane Hart, Harold Jarche, Charles Jennings, and myself) resolved to continue Jay‘s work. Jay Cross was a deep thinker and a man of many talents, never resting on his past accomplishments, and this award is one way to keep pushing our professional fields and industries to find new and better ways to learn and work.

Marcia Conner, recipient of the Jay Cross Memorial Award

The Internet Time Alliance Jay Cross Memorial Award for 2017 is presented to Marcia Conner. Marcia was an early leader in the movement for individual and social learning, and an innovator. As a Senior Manager at Microsoft, she developed new training practices and wrote an accessible white paper on the deeper aspects of learning design. She subsequently was the Information Futurist at PeopleSoft.  She also served as a co-founder and editor at Learnativity, an early online magazine.

Marcia  co-organized and co-hosted the Creating a Learning Culture conference at the Darden School of Business at the University of Virginia, leading to a book of the same title.  As an advocate for the power of learning, alone and together, she wrote Learn More Now and co-wrote The New Social Learning (now in it‘s second edition) with Tony Bingham of the Association for Talent Development. She also was the instigator who organized the team for the twitter chat #lrnchat, which continues to this day.

Marcia‘s a recognized leader, writing for Fast Company, and keynoting conferences around the world. She currently helps organizations go beyond their current approaches, changing their culture.  She‘s also in the process of moving her focus beyond organizations, to society. In her words, “I‘m in pursuit of meaningful progress, with good faith and honesty, girded by what I know we are capable of doing right now. When we assemble all that is going on at the edges of culture, technology, and (dare I say) business, we find a wildly hopeful view of the future. People doing extraordinary things, on a human scale, that has the potential to change everything for the better.”

Marcia was a friend of Jay‘s for many years (including organizing the creation of his Wikipedia page), and we‘re proud to recognize her contributions.

Helen Blunden was the inaugural award winner in 2016.

FocusOn Learning reflections

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If you follow this blog (and you should :), it was pretty obvious that I was at the FocusOn Learning conference in San Diego last week (previous 2 posts were mindmaps of the keynotes). And it was fun as always.  Here are my reflections on what happened a bit more, as an exercise in meta-learning.

There were three themes to the conference: mobile, games, and video.  I’m pretty active in the first two (two books on the former, one on the latter), and the last is related to things I care and talk about.  The focus led to some interesting outcomes: some folks were very interested in just one of the topics, while others were looking a bit more broadly.  Whether that’s good or not depends on your perspective, I guess.

Mobile was present, happily, and continues to evolve.  People are still talking about courses on a phone, but more folks were talking about extending the learning.  Some of it was pretty dumb – just content or flash cards as learning augmentation – but there were interesting applications. Importantly, there was a growing awareness about performance support as a sensible approach.  It’s nice to see the field mature.

For games, there were positive and negative signs.  The good news is that games are being more fully understood in terms of their role in learning, e.g. deep practice.  The bad news is that there’s still a lot of interest in gamification without a concomitant awareness of the important distinctions. Tarting up drill-and-kill with PBL (points, badges, and leaderboards; the new acronym apparently)  isn’t worth significant interest!  We know how to drill things that must be, but our focus  should be on intrinsic interest.

As a side note, the demise of Flash has left us without a good game development environment. Flash is both a development environment and a delivery platform. As a development environment  Flash had a low learning threshold, and yet could be used to build complex games.  As a delivery platform, however, it’s woefully insecure (so much so that it’s been proscribed in most browsers). The fact that Adobe couldn’t be bothered to generate acceptable HTML5 out of the development environment, and let it languish, leaves the market open for another accessible tool. And Unity or Unreal provide good support (as I understand it), but still require coding.  So we’re not at an easily accessible place. Oh, for HyperCard!

Most of the video interest was either in technical issues (how to get quality and/or on the cheap), but a lot of interest was also in interactive video. I think branching video is a real powerful learning environment for contextualized decision making.  As a consequence the advent of tools that make it easier is to be lauded. An interesting session with the wise Joe Ganci (@elearningjoe) and a GoAnimate guy talked about when to use video versus animation, which largely seemed to reflect my view (confirmation bias ;) that it’s about whether you want more context (video) or concept (animation). Of course, it was also about the cost of production and the need for fidelity (video more than animation in both cases).

There was a lot of interest in VR, which crossed over between video and games.  Which is interesting because it’s not inherently tied to games or video!  In short,  it’s a delivery technology.  You can do branching scenarios, full game engine delivery, or just video in VR. The visuals can be generated as video or from digital models. There was some awareness, e.g. fun was made of the idea of presenting powerpoint in VR (just like 2nd Life ;).

I did an ecosystem presentation that contextualized all three (video, games, mobile) in the bigger picture, and also drew upon their cognitive and then L&D roles. I also deconstructed the game Fluxx (a really fun game with an interesting ‘twist’). Overall, it was a good conference (and nice to be in San Diego, one of my ‘homes’).

Nathalie Nahai #FocusOnLearn Keynote Mindmap

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Nathalie Nahai opened the second day of the FocuOn Learning conference. In a rapid fire presentation, she covered 7 principles that engage individuals into behaviors. With clear examples from familiar online experiences, she portrayed how these things work. Admirably, she finished with a call to ethical behavior.

Keynote mindmap