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Clark Quinn’s Learnings about Learning

Personal Mobile Mastery

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A conversation with a colleague prompted a reflection.  The topic was personal learning, and in looking for my intersections (beyond my love of meta-learning), I looked at my books. The Revolution isn’t an obvious match, nor is games (though trust me, I could make them work ;), but a more obvious match was mlearning. So the question is, how do we do personal knowledge mastery with mobile?

Let’s get the obvious out of the way. Most of what you do on the desktop, particularly social networking, is doable on a mobile device.  And you can use search engines and reference tools just the same. You can find how to videos as well. Is there more?

First, of course, are all the things to make yourself more ‘effective’.  Using the four key original apps on the Palm Pilot for instance: your calendar to remind you of events or to check availability, using ToDo checklists to remember commitments to do something, using memos to take notes for reference, and using your contact list to reach people.  Which isn’t really learning, but it’s valuable to learn to be good at these.

Then we start doing things because of where you are.  Navigation to somewhere or finding what’s around you are the obvious choices. Those are things you won’t necessarily learn from, but they make you more effective.  But they can also help educate you. You can look where you are on a map and see what’s around you, or identify the thing on the map that’s in that direction (“oh, that’s the Quinnsitute” or “There’s Mount Clark” or whatever), and have a chance of identifying a seen prominence.

And  you can use those social media tools as before, but you can also use them because of where or when you are. You can snap pictures of something and send it around and ask how it could help you. Of course, you can snap pictures or films for later recollection and reflection, and contribute them to a blog post for reflection.  And take notes by text or audio. Or even sketching or diagramming. The notes people take for themselves at conferences, for instance, get shared and are valuable not just for the sharer, but for all attendees.

Certainly searching  things you don’t understand or, when there’s unknown language, seeing if you can get a translation, are also options.  You can learn what something means, and avoid making mistakes.

When  you are, e.g. based upon what you’re doing, is a little less developed.  You’d have to have rich tagging around your calendar to signal what it is you’re doing for a system to be able to leverage that information, but I reckon we can get there if and when we want.

I’m not a big fan of  ‘learning’ on a mobile device, maybe a tablet in transit or something, but not courses on a phone.  On the other hand, I am a  big fan of self-learning on a phone, using your phone to make you smarter. These are embryonic thoughts, so I welcome feedback.   Being more contextually aware both in the moment and over time is a worthwhile opportunity, one we can and should look to advance.  I think there’s  much  yet, though tools like ARIS are going to help change that. And that’ll be good.

 

Why models matter

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In the industrial age, you really didn’t need to understand why you were doing what you were doing, you were just supposed to do it.  At the management level, you supervised behavior, but you didn’t really set strategy. It was only at the top level where you used the basic principles of business to run your organization.  That was then, this is now.

Things are moving faster, competitors are able to counter your advances in months, there’s more information, and this isn’t decreasing.  You really need to be more agile to deal with uncertainty, and you need to continually innovate.   And I want to suggest that this advantage comes from having a conceptual understanding, a model of what’s happening.

There are responses we can train,  specific ways of acting in context.  These aren’t what are most valuable any more.  Experts, with vast experience responding in different situations, abstract models that guide what they do, consciously or unconsciously (this latter is a problem, as it makes it harder to get at; experts can’t tell you 70% of what they actually do!).  Most people, however, are in the novice to practitioner range, and they’re not necessarily ready to adapt to changes,  unless we prepare them.

What gives us the ability to react are having models that explain  the underlying causal relations as we best understand them, and then support in applying those models in different contexts.  If we have models, and see how those models guide performance in context A, then B, and then we practice applying it in context C and D (with model-based feedback), we gradually develop a more flexible ability to respond. It’s not subconscious, like experts, but we can figure it out.

So, for instance, if we have the rationale behind a sales process, how it connects to the customer’s mental needs and the current status, we can adapt it to different customers.  If we understand the mechanisms of medical contamination, we can adapt to new vectors.  If we understand the structure of a cyber system, we can anticipate security threats. The point is that making inferences on models is a more powerful basis than trying to adapt a rote procedure without knowing the basis.

I recognize that I talk a lot in concepts, e.g. these blog posts and diagrams, but there’s a principled reason: I’m trying to give you a flexible basis, models, to apply to your own situation.  That’s what I do in my own thinking, and it’s what I apply in my consulting.  I am a collector of models, so that I have more tools to apply to solving my own or other’s problems.   (BTW, I use concept and model relatively interchangeably, if that helps clarify anything.)

It’s also a sound basis for innovation.  Two related models (ahem) of creativity say that new ideas are either the combination of two different models or an evolution of an existing one.  Our brains are pattern matchers, and the more we observe a pattern, the more likely it will remind us of something, a model. The more models we have to match, the more likely we are to find one that maps. Or one that activates another.

Consequently, it’s also one  of the things I push as a key improvement to learning design. In addition to meaningful practice, give the concept behind it, the why, in the form of a model. I encourage you to look for the models behind what you do, the models in what your presented, and the models in what your learners are asked to do.

It’s a good basis for design, for problem-solving, and for learning.  That, to me, is a big opportunity.

L&D and working out loud #wolweek

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This week is Working Out Loud week, and I can’t but come out in support of a principle that I think is going to be key to organizational success. And, I think, L&D has a key role to play.

The benefits from working out loud are many. Personally, documenting what you’re doing serves as a reminder to yourself and awareness for others. The real power comes, however, from taking that next level: documenting not just what you’re doing, but why. This helps you in reflecting on your own work, and being clear in your thinking. Moreover, sharing your thinking gives you a second benefit in getting others’ input which can really improve the outcome.

In addition, it gives others a couple of benefits. They get to know what you’re up to, so it’s easier to align, but if your thinking is any good, it gives them the chance to learn from how you think.

So what is the role of L&D here? I’ll suggest there are two major roles: facilitating the skills and enabling the culture.

First, don’t assume folks know what working out loud means. And even if they do, they may not be good at it in terms of knowing how to indicate the underlying thinking. And they likely will want feedback and encouragement. First, L&D needs to model it, practicing what they preach. They need to make sure the tools are easily available and awareness is shared. Execs need to be shown the benefit and encouraged to model the behavior too. And L&D will have to trumpet the benefits, accomplishments, and encourage the behavior.

None of this is really likely to succeed if you don’t have a supportive culture. In a Miranda organization, no one is going to share. Instead, you need the elements of a learning organization: the environment has to value diversity, be open to new ideas, provide time for reflection, and most of all be safe. And L&D has to understand the benefits and continue to promote them, identify problems, and work to resolve them.

Note that this is not something you manage or control. The attitude here has to be one of nourishing aka (seed, feed, and weed). You may track it, and you want to be looking for things to support or behaviors to improve, but the goal is to develop a vibrant community of sharing, not squelching anything that violates the hierarchy.

Working out loud benefits the individual and the organization in a healthy environment. Getting the environment right, and facilitating the practice, are valuable contributions, and ones that L&D can, and should, contribute to.

#itashare

Learning Problem-solving

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While I loved his presentation, his advocacy for science, and his style, I had a problem with one thing Neil deGrasse Tyson said during his talk. Now, he’s working on getting deeper into learning, but this wasn’t off the cuff, this was his presentation (and he says he doesn’t say things publicly until he’s ready). So while it may be that he skipped the details, I can’t. (He’s an astrophysicist, I’m the cognitive engineer ;)

His statement, as I recall and mapped,  said that math wires brains to solve problems. And yes,  with two caveats.  There’s an old canard that they used to teach Latin because it taught you how to think, and it actually didn’t work that way. The ability to learn Latin taught you Latin, but not how to think or learn, unless something else happened.   Having Latin isn’t a bad thing, but it’s not obviously a part of a modern curriculum.

Similarly, doing math problems isn’t necessarily going to teach you how to do more general problem-solving.  Particularly doing the type of abstract math problems that are the basis of No Child Left Untested, er Behind.  What you’ll learn is how to do abstract math problems, which isn’t part of most job descriptions these days.  Now, if you want to learn to solve meaningful math problems, you have to be given meaningful math problems, as the late David Jonassen told us.  And the feedback has to include the problem-solving process, not just the math!

Moreover, if you want to generalize to other problem-solving, like science or engineering, you need explicit scaffolding to reflect on the process and the generality across domains.  So you  need  some problem-solving in other domains to abstract and generalize across.  Otherwise, you’ll get good at solving real world math problems, which is necessary but not sufficient.  I remember my child’s 2nd grade teacher who was talking about the process they emphasized for writing  –  draft, get feedback, review, refine – and I pointed out that was good for other domains as well: math, drawing, etc.  I saw the light go on.  And that’s the point, generalizing is valuable  in learning, and facilitating that generalization is valuable in teaching.

I laud the efforts to help folks understand why math and science are important, but you can’t let people go away thinking that doing abstract math problems is a valuable activity.  Let’s get the details right, and really accelerate our outcomes.

Taking note

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A colleague pointed me to this  article that posited the benefits of digital note-taking.  While I agree, I want to take it further.  There are some non-0bvious factors in note taking.

As the article points out, there are numerous benefits possible by taking notes digitally.  They can be saved and reviewed, have text and/or sketches and/or images (even video too), be shared, revised, elaborated with audio both to add to notes and to read back the prose, and more.  Auto-correct is also valuable.  And I absolutely believe all this is valuable.  But there’s more.

One thing the article touched on is the value of structure.  Whether outlining, where indents capture relationships, or networks similarly, capturing that structure means valuable processing by the note-taker. Interestingly, graphical frameworks can support cycles or cross references in the structure better than outlines can (I once was called out that there was no additional value to mindmaps over outlines, and this is one area where they are superior).

However, as the article noted, research has shown that taking verbatim notes doesn’t help. You have to actively reprocess the information, extracting structure through outlines or networks, and paraphrasing what you hear instead of parroting it. This is the real value of note taking.  You need to be actively engaged.

Note-taking  also helps keep that engagement. The mindmaps that I frequently post started as a way for me to listen better.   My brain can be somewhat lateral (an understatement; a benefit for Quinnovating, but a problem for listening to presentations), and if someone says something interesting, by the time I’ve explored the thought and returned, I’ve lost the plot. Mindmapping was a way to occupy enough extra cognitive overhead to keep my mind from sparking off.  It just so happens that  when I posted one, it drew significant interest (read: hits), and so I’ve continued it for me, the audience, and the events.

Interestingly, the benefit of the note taking can persist even if the notes aren’t reviewed; the act of note-taking with the extra processing in paraphrasing is valuable in itself.  I once asked an audience how many took notes, and many hands went up. I then asked how many read the notes afterwards, and the result was significantly less.  Yet that’s not a bad thing!

So, take notes that reprocess the information presented.  Then, review them if useful.  But give yourself the benefit of the processing, if nothing else.

#DevLearn 14 Reflections

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This past week I was at the always great DevLearn conference, the biggest and arguably best yet.  There were some hiccups in my attendance, as  several blocks of time were taken up with various commitments both work and personal, so for instance I didn’t really get a chance to peruse the expo at all.  Yet I attended keynotes and sessions, as well as presenting, and hobnobbed with folks both familiar and new.

The keynotes were arguably even better than before, and a high bar had already been set.

Neil deGrasse Tyson was eloquent and passionate about the need for science and the lack of match between school and life.    I had a quibble about his statement that doing math teaches problem-solving, as it takes the right type of problems (and Common Core is a step in the right direction)  and  it takes explicit scaffolding.  Still, his message was powerful and well-communicated. He also made an unexpected connection between Women’s Liberation and the decline of school quality that I hadn’t considered.

Beau Lotto also spoke, linking how our past experience alters our perception to necessary changes in learning.  While I was familiar with the beginning point of perception (a fundamental part of cognitive science, my doctoral field), he took it in very interesting and useful direction in an engaging and inspiring way.  His take-home message: teach not how to see but how to look, was succinct and apt.

Finally, Belinda Parmar took on the challenge of women in technology, and documented how  small changes can  make a big difference. Given the madness of #gamergate, the discussion was a useful reminder of inequity in many fields and for many.  She left lots of time to have a meaningful discussion about the issues, a nice touch.

Owing to the commitments both personal and speaking, I didn’t get to see many sessions. I had the usual situation of  good ones, and a not-so-good one (though I admit my criteria is kind of high).  I like that the Guild balances known speakers and topics with taking some chances on both.  I also note that most of the known speakers are those folks I respect that continue to think ahead and bring new perspectives, even if in a track representing their work.  As a consequence, the overall quality is always very high.

And the associated events continue to improve.  The DemoFest was almost too big this year, so many examples that it’s hard to start looking at them as you want to be fair and see all but it’s just too monumental. Of course, the Guild had a guide that grouped them, so you could drill down into the ones you wanted to see.  The expo reception was a success as well, and the various snack breaks suited the opportunity to mingle.  I kept missing the ice cream, but perhaps that’s for the best.

I was pleased to have the biggest turnout yet for a workshop, and take the interest in elearning strategy as an indicator that the revolution is taking hold.  The attendees were faced with the breadth of things to consider across advanced ID, performance support, eCommunity, backend integration, decoupled delivery, and then were led through the process of identifying elements and steps in the strategy.  The informal feedback was that, while daunted by the scope, they were excited by the potential and recognizing the need to begin.  The fact that the Guild is holding the Learning Ecosystem conference and their release of a new and quite good white paper by Marc Rosenberg and Steve Foreman are further evidence that awareness is growing.   Marc and Steve carve up the world a little differently than I do, but we say similar things about what’s important.

I am also pleased that  Mobile  interest continues to grow, as evidenced by the large audience at our mobile panel, where I was joined by other mLearnCon advisory board members Robert Gadd, Sarah Gilbert, and Chad Udell.  They provide nicely differing  viewpoints, with Sarah representing the irreverent designer, Robert the pragmatic systems perspective, and Chad the advanced technology view, to complement my more  conceptual approach.  We largely agree, but represent different ways of communicating and thinking about the topic. (Sarah and I will be joined by Nick Floro for ATD’s mLearnNow event in New Orleans next week).

I also talked about trying to change the pedagogy of elearning in the Wadhwani Foundation, the approach we’re taking and the challenges we face.  The goal I’m involved in is job skilling, and consequently there’s a real need and a real opportunity.  What I’m fighting for is to make meaningful practice as a way to achieve real outcomes.  We have some positive steps and some missteps, but I think we have the chance  to have a real impact. It’s a work in progress, and fingers crossed.

So what did I learn?  The good news is that the audience is getting smarter, wanting more depth in their approaches and breadth in what they address. The bad news appears to be that the view of ‘information dump & knowledge test = learning’ is still all too prevalent. We’re making progress, but too slowly (ok, so perhaps patience isn’t my strong suit ;).  If you haven’t, please do check out the Serious eLearning Manifesto to get some guidance about what I’m talking about (with my colleagues Michael Allen, Julie Dirksen, and Will Thalheimer).  And now there’s an app for that!

If you want to get your mind around the forefront of learning technology, at least in the organizational space, DevLearn is the place to be.

 

Learning in 2024 #LRN2024

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The eLearning Guild is celebrating it’s 10th year, and is using the opportunity to reflect on what learning will look like 10 years from now.  While I couldn’t participate in the twitter chat they held, I optimistically weighed in: “learning in 2024 will look like individualized personal mentoring via augmented reality, AI, and the network”.  However, I thought I would elaborate in line with a series of followup posts leveraging the #lrn2024 hashtag.  The twitter chat had a series of questions, so I’ll address them here (with a caveat that our learning really hasn’t changed, our wetware hasn’t evolved in the past decade and won’t again in the next; our support of learning is what I’m referring to here):

1. How has learning changed in the last 10 years (from the perspective of the learner)?

I reckon the learner has seen a significant move to more elearning instead of an almost complete dependence on face-to-face events.  And I reckon most learners have begun to use technology in their own ways to get answers, whether via the Google, or social networks like FaceBook and LinkedIn.  And I expect they’re seeing more media such as videos and animations, and may even be creating their own. I also expect that the elearning they’re seeing is not particularly good, nor improving, if not actually decreasing in quality.  I expect they’re seeing more info dump/knowledge test, more and more ‘click to learn more‘, more tarted-up drill-and-kill.  For which we should apologize!

2.  What is the most significant change technology has made to organizational learning in the past decade?

I reckon there are two significant changes that have happened. One is rather subtle as yet, but will be profound, and that is the ability to track more activity, mine more data, and gain more insights. The ExperienceAPI coupled  with analytics is a huge opportunity.  The other is the rise of social networks.  The ability to stay more tightly coupled with colleagues, sharing information and collaborating, has really become mainstream in our lives, and is going to have a big impact on our organizations.  Working ‘out loud’, showing our work, and working together is a critical inflection point in bringing learning back into the workflow in a natural way and away from the ‘event’ model.

3.  What are the most significant challenges facing organizational learning today?

The most significant change is the status quo: the belief that an information oriented event model has any relationship to meaningful outcomes.  This plays out in so many ways: order-taking for courses, equating information with skills, being concerned with speed and quantity instead of quality of outcomes, not measuring the impact, the list goes on.   We’ve become self-deluded that an LMS and a rapid elearning tool means you’re doing something worthwhile, when it’s profoundly wrong.  L&D needs a revolution.

4.  What technologies will have the greatest impact on learning in the next decade? Why?

The short answer is mobile.  Mobile is the catalyst for change. So many other technologies go through the hype cycle: initial over-excitement, crash, and then a gradual resurgence (c.f. virtual worlds), but mobile has been resistant for the simple reason that there’s so much value proposition.  The cognitive augmentation that digital technology provides, available whenever and wherever you are clearly has benefits, and it’s not courses!  It will naturally incorporate augmented reality with the variety of new devices we’re seeing, and be contextualized as well.  We’re seeing a richer picture of how technology can support us in being effective, and L&D can facilitate these other activities as a way to move to a more strategic and valuable role in the organization.  As above, also new tracking and analysis tools, and social networks.  I’ll add that simulations/serious games are an opportunity that is yet to really be capitalized on.  (There are reasons I wrote those books :)

5.  What new skills will professionals need to develop to support learning in the future?

As I wrote  (PDF), the new skills that are necessary fall into two major categories: performance consulting and interaction facilitation.  We need to not design courses until we’ve ascertained that no other approach will work, so we need to get down to the real problems. We should hope that the answer comes from the network when it can, and we should want to design performance support solutions  if it can’t, and reserve courses for only when it absolutely has to be in the head. To get good outcomes from the network, it takes facilitation, and I think facilitation is a good model for promoting innovation, supporting coaching and mentoring, and helping individuals develop self-learning skills.  So the ability to get those root causes of problems, choose between solutions, and measure the impact are key for the first part, and understanding what skills are needed by the individuals (whether performers or mentors/coaches/leaders) and how to develop them are the key new additions.

6.  What will learning look like in the year 2024?

Ideally, it would look like an ‘always on’ mentoring solution, so the experience is that of someone always with you to watch your performance and provide just the right guidance to help you perform in the moment and develop you over time. Learning will be layered on to your activities, and only occasionally will require some special events but mostly will be wrapped around your life in a supportive way.  Some of this will be system-delivered, and some will come from the network, but it should feel like you’re being cared for  in the most efficacious way.

In closing,  I note that, unfortunately,my Revolution book and the Manifesto were both driven by a sense of frustration around the lack of meaningful change in L&D. Hopefully, they’re riding or catalyzing the needed change, but in a cynical mood I might believe that things won’t change near as much as I’d hope. I also remember a talk (cleverly titled:  Predict Anything but the Future  :) that said that the future does tend  to come as an informed basis would predict  with an unexpected twist,  so it’ll be interesting to discover what that twist will be.

On the Road Fall 2014

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Fall always seems to be a busy time, and I reckon it’s worthwhile to let you know where I’ll be in case you might be there too! Coming up are a couple of different  events that you might be interested in:

September 28-30 I’ll be at the Future of Talent retreat   at the Marconi Center up the coast from San Francisco. It’s a lovely spot with a limited number of participants who will go deep on what’s coming in the Talent world. I’ll be talking up the Revolution, of course.

October 28-31 I’ll be at the eLearning Guild’s  DevLearn in Las Vegas (always a  great event; if you’re into elearning you  should be there).  I’ll be running a Revolution workshop  (I believe there are still a few spots), part of  a mobile panel, and talking  about how we are going about addressing the challenges of learning design at the Wadhwani Foundation.

November 12-13 I’ll be part of the mLearnNow event in New Orleans (well, that’s what  I call it, they call it LearnNow mobile blah blah blah ;).  Again, there are some slots still available.    I’m honored to be co-presenting with  Sarah Gilbert and Nick Floro  (with Justin Brusino pulling strings in the background), and we’re working hard to make sure it should be a really great deep dive into mlearning.  (And,  New Orleans!)

There may be one more opportunity, so if anyone in Sydney wants to talk, consider Nov 21.

Hope to cross paths with you at one or more of these places!

Vale Joe Miller

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This is a name you’re not likely to know, but I can’t let his passing go without comment.  Joe was an intensely private person who had a sizable  impact on the field of technology in learning, and I was privileged to know him.

I met Joe when my colleague Jim “Sky” Schuyler, who had hired for my first job out of college, subsequently dragged me back from overseas to work for him at a new company: Knowledge Universe Interactive Studios (KUIS).  I’d stayed in touch with Sky over the years, and I was looking to come back at the same time he had been hired to lead KUIS’s work to be an ISP for the KU companies, but also to create a common platform.  I was brought on board to lead the latter initiative.

To make a long story short, initially I reported to Sky, but ultimately he moved on and I began to report to the CEO, Joe, directly.  Sky had said that he liked working for people smarter than himself, and if indeed Joe was such this was quite the proposition, as Sky was not only a Northwestern PhD but a wise colleague in many ways. He’d been a mentor and friend as well as a colleague, and if Sky (reticent as he is) thought highly of Joe, this was high praise indeed.

I got to know Joe slowly. He was quite reserved  not only personally but professionally, but he did share his thinking.  It quickly became clear that not only did he have the engineering chops of a true techy, he also had the strategic insight of an visionary executive.  What I learned more slowly was that he was not just a natural leader, but a man with impeccable integrity and values.

I found out that he’d been involved with Plato via his first job at Battelle, and was suitably inspired to start a company supporting Plato. He moved  to the Bay Area to join Atari, and  subsequently was involved with Koala Technologies, which created  early PC (e.g. Apple) peripherals.  His trajectory subsequently covered gaming as well as core technology, eventually ending up at Sega before he convinced the KU folks to let him head up KUIS.  He seemed to know everyone.

More importantly, he had the vision to understand system and infrastructure, and barriers to same. He was excited about Plato as a new capability for learning. He supported systems at Koala for new interface devices. He worked to get Sega to recognize the new landscape.  In so many ways he worked behind the scenes to enable new experiences, but he was never at the forefront of the public explanation, preferring to make things happen at the back end (despite the fact that he was an engaging speaker: tall, resonant voice, and compelling charisma).

In my short time to get to know him, he shared his vision on a learning system that respected who learners were, and let me shape a team that could (and did) deliver on that vision.  He fought to give us the space and the resources, and asked the tough questions to make sure we were focused. We got a working version up and running before the 2001 crash.

He continued to have an impact, leading some of the major initiatives of Linden Labs as they went open source and met some challenging technical issues  while negotiating cultural change to take down barriers.  He ended up at SportVision, where he was beginning to help them understand they were not about information, but insight.  Unfortunately, I didn’t have much view  into what was happening there, as it was proprietary and Joe was, as I said, private.

Joe served as a mentor for me.  I found him to have deep values, and under his austere exterior he exemplified values of humanity and compassion.  I was truly grateful when I could continue to meet him regularly and learn from him as he expressed true interest as well as sharing his insights.

He was taken from us too early, and too quickly.  He fought a tough battle at the end, but at least was surrounded by the love of his life and their children as they passed.  Rest in Peace.

Update: there’s a memorial site for Joe, http://www.josephbmilleriii.com where you can leave thoughts, view pictures, and more.  RIP.