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Clark Quinn’s Learnings about Learning

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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 Outdated views like putting information into the head, squelching discussion, and avoiding mistakes are rife.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?

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

#AECT17 Conference Contributions

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So, at the recent AECT 2017 conference, I participated in three ways that are worth noting.  I had the honor of participating in two sessions based upon writings I’d contributed, and one based upon my own cogitations. I thought I’d share the thinking.

For my own presentation, I shared my efforts to move ‘rapid elearning’ forward. I put Van Merrienboer’s 4 Component ID and Guy Wallace’s Lean ISD as a goal, but recognized the need for intermediate steps like Michael Allen’s SAM, David Merrill’s ‘Pebble in a Pond‘, and Cathy Moore’s Action Mapping. I suggested that these might be too far, and want steps that might be slight improvements on their existing processes. These included three thing: heuristics, tools, and collaboration. Here I was indicating specifics for each that could move from well-produced to well-designed.

In short, I suggest that while collaboration is good, many corporate situations want to minimize staff. Consequently, I suggest identifying those critical points where collaboration will be useful. Then, I suggest short cuts in processes to the full approach. So, for instance, when working with SMEs focus on decisions to keep the discussion away from unnecessary knowledge. Finally, I suggest the use of tools to support the gaps our brain architectures create.   Unfortunately, the audience was small (27 parallel sessions and at the end of the conference) so there wasn’t a lot of feedback. Still, I did have some good discussion with attendees.

Then, for one of the two participation session, the book I contributed to solicited a wide variety of position papers from respected ed tech individuals, and then solicited responses to same.  I had responded to a paper suggesting three trends in learning: a lifelong learning record system, a highly personalized learning environment, and expanded learner control of time, place and pace of instruction. To those 3 points I added two more: the integration of meta-learning skills and the breakdown of the barrier between formal learning and lifelong learning. I believe both are going to be important, the former because of the decreasing half-life of knowledge, the latter because of the ubiquity of technology.

Because the original author wasn‘t present, I was paired for discussion with another author who shares my passion for engaging learning, and that was the topic of our discussion table.  The format was fun; we were distributed in pairs around tables, and attendees chose where to sit. We had an eager group who were interested in games, and my colleague and I took turns answering and commenting on each other’s comments. It was a nice combination.  We talked about the processes for design, selling the concept, and more.

For the other participation session, the book was a series of monographs on important topics.  The discussion chose a subset of four topics: MOOCs, Social Media, Open Resources, and mLearning. I had written the mLearning chapter.  The chapter format included ‘take home’ lessons, and the editor wanted our presentations to focus on these. I posited the basic mindshifts necessary to take advantage of mlearning. These included five basic principles:

  1. mlearning is not just mobile elearning; mlearning is a wide variety of things.
  2. the focus should be on augmenting us, whether our formal learning, or via performance support, social, etc.
  3. the Least Assistance Principle, in focusing on the core stuff given the limited interface.
  4. leverage context, take advantage of the sensors and situation to minimize content and maximize opportunity.
  5. recognize that mobile is a platform, not a tactic or an app; once you ‘go mobile’, folks will want more.

The sessions were fun, and the feedback was valuable.

Revisiting 70:20:10

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Last week, the Debunker Club (led by Will Thalheimer) held a twitter debate on 70:20:10 (the tweet stream can be downloaded if you’re curious).  In ‘attendance’ were two of the major proponents of 70:20:10, Charles Jennings and Jos Arets.  I joined Will as a moderator, but he did the heavy lifting of organizing the event and queueing up questions.  And there were some insights from the conversations and my own reflections.

Learning curveTo start, 70:20:10 is a framework, it’s not a specific ratio but a guide to thinking about the whole picture of developing organizational solutions to performance problems. In the book by Jos & Charles, along with their colleague Vivian Heijnen,  on the topic, there’s a whole methodology that encompasses 5 roles and 28 steps. The approach goes from a problem to a solution that incorporates tools, formal learning, coaching, and more.

The numbers come from a study on leaders, who felt that 10% of what they learned to do their jobs came from formal learning, 20% came from working with others and coaching, and 70% they learned from trying and reflecting on the outcomes. The framework’s role is to help people recognize this, and not leave the 70 and 20 to chance. The goal is to help people along the learning curve, not just leave them to chance after the ‘event’.

First, my impression was that a lot of people  like that the 70:20:10 framework provides a push beyond the event model of ‘the course’. Also, a number struggle with the numbers as a brand, because they feel that the numbers are misleading. And some folks clearly believe that good instructional design  should include the social and the activity, so the framework is a distraction. A colleague felt that there were also some who feel that formal learning is a waste of time, but I don’t think that many truly ignore the 10, they just want it in the proper perspective (and I could be wrong).

MoreFormalNow, there are times when the ratio changes. In roles where the consequences of failure are drastic (read: aerospace, medical, military), you tend to have a lot  more formal.  It can go quite a ways up the learning curve. Ideally, we’d do this for every situation, but in real life we have to strike a balance.  If we can do the job right in the 10, and then similarly ensure good practices around the 20 and the 70, we’ll get people up the curve.

Another issue, for me, is that 70:20:10 not only provides a push towards thinking of the whole picture, but like Kirkpatrick (and perhaps better) it serves as a design tool. You should start from what the situation looks like at the end and figure out what can be in the world and what has to be in the head, and then go backwards. You then design your tools, and then your training, and 70:20:10 suggests including coaching, etc.  But starting with the 70 is one of the messages.

So, I like the realization of 70:20:10 (except typing all those redundant zeros and colons, I often refer to it as 721 ;): the focus on designing the full solution, including tools and coaching and more.  I don’t see 70:20:10 being the full solution, as the element of continual innovation and a learning culture are separate, but it’s a good solution for the performance part of the picture, and the specific  parts of the development.

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?

Acknowledging Changes

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There are a serious number of changes that are affecting organizations.  We’re seeing changes in the information flow, in technology, and in what we know about ourselves. Importantly, these are things that L&D needs to acknowledge and respond to.  What are these changes?

It’s old news that things are happening faster. We’re being overwhelmed with information, and that rate is accelerating. On the other hand, our tools to manage the information flow are also advancing.

Which is the second topic. We’re getting more powerful technology. We can create systems that do tasks that used to be limited to humans. They can also partner with us, providing information based upon who we are, what we’re doing, and what else is going on.

And there are increasing demands for accountability (and transparency). Your actions should be justified. What are you doing, why, and what effect is it having? If you can’t answer these questions, you’re going to be looking for a job.

Most importantly, we’ve learned quite a bit about ourselves that is contrary to many pre-existing beliefs. Specifically ones that influence organizational approaches.  Our myths about how we think, work, and learn are holding us back from achieving optimal outcomes.

For one, there’s a persistent belief that our thinking is in our heads.  Yet research shows that our thinking is distributed across our tools. We use external representations to capture at least part of our thinking, and access information that we can’t keep in our heads effectively.  Yet we seem to depend on courses to put it in the head instead of tools to put it in the world.

Our thinking is also distributed across others. “You’re no longer what you know, but who you know” is a new mantra. So is “the room is smarter than the smartest person in the room” (with the caveat: if you manage the process right ;). Informal and social learning is the work.  Yet we still act as if we believe that people should solve problems independently.

And we also act as if how we learn is by information dump.  Add a quiz, so we know they can recognize the right answer if they see it, and they’ve learned!  Er, no. Science tells us that this is perhaps the worst thing we could do to facilitate learning.

In short, our practices are out of date. We’re using patch-it (or ignore-it) solutions to systemic issues.  We address simple things as if they’re not all connected. It’s time to get on top of what’s known, and then act accordingly.  Are you ready to join the 21st century?

Developing L&D

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One of the conversations I’ve been having is how to shift organizations into modern workplace learning. These discussions have not been with L&D, but instead targeted directly at organizational strategy. The idea is to address a particular tactical goal as  part of a strategic plan, and to do so in ways that both embody and develop learning and a collaboration culture. The topic was then raised about how you’d approach an L&D unit under this picture. And I wondered whether you’d use the same approach to developing L&D as part of L&D operations. The answer isn’t obvious.

So what I’m talking about here would be to take an L&D initiative, and do it in this new way, with coaching and scaffolding. The overall model involves a series of challenges with support.  You’re developing some new organizational capability, and you’d scaffold the process initially with some made up or pre-existing challenges.  Then you gradually move to real challenges. So, does this model change for L&D?

My thought was that you’d take an L&D initiative, and something out of the ordinary, an experiment.  Depending on the particular organization’s context, it might be performance support, or social media, or mobile, or…  Then you define an experiment, and start working on it. To develop the skills to execute, you give a team (or teams) some initial challenges: e.g. critique a design. Then more complex ones, so: design a solution to a problem someone else has solved. Finally, you give them the real task, and let them go (with support).

This isn’t slow; it’s done in sprints, and still fits in between other work. It can be done in a matter of weeks.  In doing so, you’re having the team collaborate with digital tools (even if/while working F2F, but ideally you have a distributed team). Ultimately, you are developing both their skills on the process itself  and on working together in collaborative ways.

In talking this through, I think this makes sense for L&D as well, as long as it’s a new capability that’s being developed.  This is an approach that can rapidly develop new tactical skills and change to a culture oriented towards innovation: experimentation and iterative moves. This is the future, and yet it’s unlike most of the way L&D operates now.

Most importantly, I think, is that this opportunity is on the table now for a brief period. L&D can internally develop their understanding and ability of the new ways of working as a step towards being an organization-wide champion. The same approach taken within  L&D then can be taken and used elsewhere.  But it takes experience with this approach before you can scale it.  Are you ready to make the shift?

Realities 360 Reflections

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So, one of the two things I did last week was attend the eLearning Guild‘s Realities 36o conference.  Ostensibly about Augmented Reality (AR)  and Virtual Reality (VR), it ended up being much more about VR. Which isn’t a bad thing, it’s probably as much a comment on the state of the industry as anything.  However, there were some interesting learnings for me, and I thought I’d share them.

First, I had a very strong visceral exposure to VR. While I’ve played with Cardboard on the iPhone (you can find a collection of resources for Cardboard  here), it’s not quite the same as a full VR experience.  The conference provided a chance to try out apps for the HTC Vive, Sony Playstation VR, and the Oculus.  On the Vive, I tried a game where you shot arrows at attackers.  It was quite fun, but mostly developed some motor skills. On the Oculus, I flew an XWing fighter through an asteroid field and escorted a ship and shoot enemy Tie-fighters.  Again, fun, but mostly about training my motor skills in this environment.

It was the one I think on the Vive that gave me an experience.  In it, you’re floating around the International Space Station. And it was very cool to see the station and experience the immersion of 3D, but it was very uncomfortable.  Partly because I was trying to fly around (instead of using handholds), my viewpoint would fly through the bulkhead doors. However, the positioning meant that it gave the visual clues that my chest was going through the metal edge.  This was extremely disturbing to me!  As I couldn’t control it well, I was doing this continually, and I didn’t like it. Partly it was the control, but it was also the total immersion. And that was impressive!

There are empirical results that demonstrate better learning outcomes for VR, and certainly  I can see that particularly, for tasks inherently 3D. There’s also another key result, as was highlighted in the first keynote: that VR is an ’empathy’ machine. There have been uses for things like understanding the world according to a schizophrenic, and a credit card call center helping employees understand the lives of card-users.

On principle, such environs should support near transfer when designed to closely mimic the actual performance environment. (Think: flight or medicine simulators.)  And the tools are getting better. There’s an app that allows you to take photos of a place to put into Cardboard, and game engines (Unity or Unreal or both) will now let you import AutoCAD models.  There was also a special camera that could sense the distances in a space and automatically generate a model of it.  The point being that it’s getting easier and easier to generate VR environments.

That, I think, is what’s holding AR back.  You can fairly easily use it for marker or location based information, but actually annotating the world visually is still challenging.  I still think AR is of more interest, (maybe just to me), because I see it eventually creating the possibility to see the causes and factors  behind the world, and allow us to understand it better.  I could argue that VR is just extending sims from flat screen to surround, but then I think about the space station, and…I’m still pondering that. Is it revolutionary or just evolutionary?

One session talked about trying to help folks figure out when VR and AR made sense, and this intrigued me. It reminded me that I had tried to characterize the affordances of virtual worlds, and I reckon it’s time to take a stab at doing this for VR and AR.  I believed then that I was able to predict when virtual worlds would continue to find value, and I think results have borne that out.  So, the intent is to try to get on top of when VR and AR make sense.  Stay tuned!

What is the Future of Work?

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which is it?Just what is the Future of Work  about? Is it about new technology, or is it about how we work with people?  We’re seeing  amazing new technologies: collaboration platforms, analytics, and deep learning. We’re also hearing about new work practices such as teams, working (or reflecting) out loud, and more.  Which is it? And/or how do they relate?

It’s very clear technology is changing the way we work. We now work digitally, communicating and collaborating.  But there’re more fundamental transitions happening. We’re integrating data across silos, and mining that data for new insights. We can consolidate platforms into single digital environments, facilitating the work.  And we’re getting smart systems that do things our brains quite literally can’t, whether it’s complex calculations or reliable rote execution at scale. Plus we have technology-augmented design and prototyping tools that are shortening the time to develop and test ideas. It’s a whole new world.

Similarly, we’re seeing a growing understanding of work practices that lead to new outcomes. We’re finding out that people work better when we create environments that are psychologically safe, when we tap into diversity, when we are open to new ideas, and when we have time for reflection. We find that working in teams, sharing and annotating our work, and developing learning and personal knowledge mastery skills all contribute. And we even have new  practices such as agile and design thinking that bring us closer to the actual problem.  In short, we’re aligning practices more closely with how we think, work, and learn.

Thus, either could be seen as ‘the Future of Work’.  Which is it?  Is there a reconciliation?  There’s a useful way to think about it that answers the question.  What if we do either without the other?

If we use the new technologies in old ways, we’ll get incremental improvements.  Command and control, silos, and transaction-based management can be supported, and even improved, but will still limit the possibilities. We can track closer.  But we’re not going to be fundamentally transformative.

On the other hand, if we change the work practices, creating an environment where trust allows both safety  and accountability, we can get improvements whether we use technology or not. People have the capability to work together using old technology.  You won’t get the benefits of some of the improvements, but you’ll get a fundamentally different level of engagement and outcomes than with an old approach.

Together, of course, is where we really want to be. Technology can have a transformative amplification to those practices. Together, as they say, the whole is greater than the some of the parts.

I’ve argued that using new technologies like virtual reality and adaptive learning only make sense  after you first implement good design (otherwise you’re putting lipstick on a pig, as the saying goes).  The same is true here. Implementing radical new technologies on top of old practices that don’t reflect what we know about people, is a recipe for stagnation.  Thus, to me, the Future of Work starts with practices that align with how we think, work, and learn, and are augmented with technology, not the other way around.  Does that make sense to you?

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’).