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Clark Quinn’s Learnings about Learning

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Nuances Matter

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I’ve argued before that the differences between well-designed and well-produced learning, and just well-produced learning, are subtle. And, in general, nuances matter. So, in my recent book, the section on misconceptions spent a lot of time unpacking some terms. The goal there was ensuring that the nuances were understood. And a recent event triggered even more reflection on this.

Learnnovators, a company I’ve done a couple of things with (the Deeper eLearning series, and the Workplace of the Future project), interviewed me once quite a while ago. I was impressed then with the depth of their background research and thoughtful questions. And they recently asked to interview me on the book. Of course, I agreed. And again they impressed me with the depths of their questions, and I realized in this case there was something specific going on.

In their questions, they were unpacking what common concerns would be about some of the topics.  The questions dug in to ways in which people might think that the recommendations are contrary to personal experience, and more.  There were very specifically looking for ways in which folks might think to reject the findings.  And that’s important. I believe I had addressed most of them in the book, but it was worth revisiting them.

And that’s the thing that I think is important about this for our practice. We can’t just do the surface treatment. If we just say: “ok we need some content, and then let’s write a knowledge test on it”, we’ve let down our stakeholders.  If we don’t know the cognitive properties of the media we use, don’t sweat the details about feedback on assessment, don’t align the practice to the needed performance, etc., we’re not doing our job!

And I don’t mean you have to get a Ph.D. in learning science, but you really do need to know what you’re doing. Or, at least, have good checklists and quick reference guides to ensure you’re on track. Ideally, you review your processes and tools for alignment to what’s known. And the tools themselves could have support. (Ok, to a limit, I’ve seen this done to the extent of handcuffs on design.)

Nuances matter,  if you care about the outcomes (and if you don’t, why bother? ;).  I’ve been working on both a checklist and on very specific changes that apply to various places in design processes that represent the major ways folks go wrong. These problems are relatively small, and easy to fix, and are designed to yield big improvements. But unless you know what they are, you’re unlikely to have the impact you intend.

Plagiarism and ethics

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I recently wrote on the ethics of L&D, and I note that I  didn’t  address one issue. Yet, it’s very clear that it’s still a problem. In short, I’m talking about plagiarism and attribution.  And it needs to be said.

In that article, I  did say:

That means we practice ethically, and responsibly. We want to collectively determine what that means, and act accordingly. And we must call out bad practices or beliefs.

So let me talk about one bad practice: taking or using other people’s stuff without attribution.  Most of the speakers I know can cite instances when they’ve seen their ideas (diagrams, quotes, etc) put up by others without pointing back to them.  There’s a distinction between citing something many people are talking about (innovation, microlearning, what have you) with your own interpretation, and literally taking someone’s ideas and selling them as your own.

One of our colleagues recently let me know his tools had been used by folks to earn money without any reimbursement to him (or even attribution).  Others have had their diagrams purloined and used in presentations.  One colleague found pretty much his entire presentation used by someone else!  I myself have seen my writing appear elsewhere without a link back to me, and I’m not the only one.

Many folks bother to put copyright signs on their images, but I’ve stopped because it’s too easy to edit out if you’re halfway proficient with a decent graphics package.  And you can do all sorts of things to try to protect your decks, writing, etc, but ultimately it’s very hard to protect, let alone discover that it’s happening. Who knows how many copies of someone’s images have ended up in a business presentation inside a firm!  People have asked, from time to time, and I have pretty much always agreed (and I’m grateful when they do ask). Others, I’m sure, are doing it anyway.

This isn’t the same as asking someone to work for free, which is also pretty rude. There are folks who will work for ‘exposure’, because they’re building a brand, but it’s somewhat unfair. The worst are those who charge for things, like attendance or membership, or organizations who make money, yet expect free presentations!  “Oh, you could get some business from this.”  The operative word is ‘could’.  Yet they  are!

Attribution isn’t ‘name dropping‘. It’s showing you are paying attention, and know the giants whose shoulders you stand on.  Taking other people’s work and claiming it as your own, particularly if you profit by it, is theft. Pure and simple.  It happens, but we need to call it out.  Calling it out can even be valuable; I once complained and ended up with a good connection (and an apology).

Please, please, ask for permission, call out folks who you see  are plagiarizing, and generally act in proper ways. I’m sure  you are, but overall some awareness raising still needs to happen.  Heck, I know we see amazing instances in people’s resumes and speeches of it, but it’s still not right.  The people in L&D I’ve found to be generally warm and helpful (not surprisingly). A few bad apples isn’t surprising, but we can do better. All I can do is ask you to do the right thing yourself, and call out bad behavior when you do see it.  Thanks!

 

The meta-program

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A couple of weeks ago, I posited what I thought might make the basis for a sustainable degree program. That is, one that prepares students for a world with increasing change. In it I talked about the domains that I thought would provide a solid basis, but I did  not talk about something else important.  It’s also about the learning to learn and work skills that accompany the foundational knowledge. It’s about ‘meta’ skills.

Meta-skills, like learning to learn and learning to work well (21C skills), can’t be developed on their own. They  need to be layered on top of other things. We teach them  across  other domains, so they’re abstracted and can be reapplied to new problems and situations.   Thus, these challenges must reappear across the curriculum.

What skills?  I think things like the ability to research questions, design and run experiments, communicate results, collaborate, ask and answer questions in ways that work, and more.  This includes using technology for these tasks, as well as working with others.  Thus, creating spreadsheets, diagrams, and presentations is as much a part as is participating in and leading projects, commenting constructively, and coaching and mentoring.

So, using an application-based pedagogy,  there are a series of activities that require application, but they vary in type: research, design, problem-solve, interact, and in output. Then we evaluate those cross-discipline skills as well as the domain knowledge and skills.  How was your research process on this interface design project?  How well did you communicate your learnings from that experiment on recursion in learning programs?

Curriculum  and the pedagogy can be refined, and in fact are interleaved. Then we use technology to serve both as a tool for learners to construct (make) outcomes, and to track their progress.  We need to go meta in both!

And this isn’t true just for formal education, and can and should play a role in organizational learning as well.  We shouldn’t take our learners’ learning skills for granted, and we can and should track and develop them as well.  This isn’t currently supported, but perhaps can be in existing tools, or we may need a new platform.  But we should, I suggest.  Your thoughts?

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?