I was thinking about a talk on mobile I’m going to be giving, and realized that mobile is really about personal processing. Many of the things you can do at your desktop you can do with your mobile, even a wearable: answering calls, responding to texts.  Ok, so responding to email, looking up information, and more might require the phone for a keyboard (I confess to not being a big Siri user, mea culpa), but it’s still where/when/ever. So the question then became "what doesn’t make sense on a mobile". And my thought was that industrial strength processing doesn’t make sense on a mobile.  Processor intensive work: video editing, 3D rendering, things that require either big screens or lots of CPU.  So, for instance, while word processing isn’t really CPU intensive, for some reason mobile word processors don’t seamlessly integrate outlining.  Yet I require outlining for big scale writing, book chapters or whole books. I don’t do 3D or video processing, but that would count too. One of the major appeals of mobile is having versatile digital capabilities, the rote/complex complement to our pattern-matching brains, (I really wanted to call my mobile book ‘augmenting learning’) with us at all times.  It makes us more effective.  And for many things - all those things we do with mobile such as looking up info, navigating, remembering things, snapping pictures, calculating tips - that’s plenty of screen and processing grunt.  It’s for personal use. Sure, we’ll get more powerful capabilities (they’re touting multitasking on tablets now), and the boundaries will blur, but I still think there’ll be the things we do when we’re on the go, and the things we’ll stop and be reflective about.  We’ll continue to explore, but I think the things we do on the wrist or in the hand will naturally be different than those we do seated.   Our brains work in active and reflective modes, and our cognitive augment will similarly complement those needs.  We’ll have personal processing, and then we’ll have powerful processing. And that’s a good thing, I think. What think you?  

As I push for better learning design, I’m regularly reminded that working with subject matter experts (SMEs) is critical, and problematic.   What makes SMEs has implications that are challenging but also offers a uniquely valuable perspective.  I want to review some of those challenges and opportunities in one go. One of the artifacts about how our brain works is that we compile knowledge away.  We start off with conscious awareness of what we’re supposed to be doing, and apply it in context.  As we practice, however, our expertise becomes chunked up, and increasingly automatic. As it does so, some of the elements that are compiled away are awarenesses that are not available to conscious inspection. As Richard Clark of the Cognitive Technology Lab at USC lets us know, about 70% of what SMEs do isn’t available to their conscious mind.  Or, to put it another way, they literally can’t tell us what they do! On the other hand, they have pretty good access to what they know. They can cite all the knowledge they have to hand. They can talk about the facts and the concepts, but not the decisions.  And, to be fair, many of them aren’t really good at the concepts, at least not from the perspective of being able to articulate a model that is of use in the learning process. The problem then becomes a combination of both finding a good SME, and working with them in a useful way to get meaningful objectives, to start. And while there are quite rigorous ways (e.g. Cognitive Task Analysis), in general we need more heuristic approaches. My recommendation, grounded in Sid Meier’s statement that "good games are a series of interesting decisions" and the recognition that making better decisions are likely to be the most valuable outcome of learning, is to focus rabidly on decisions.  When SMEs start talking about "they need to know X" and "they need to know Y" is to ask leading questions like "what decisions do they need to be able to make that they don’t make know" and "how does X or Y actually lead them to make better decisions". Your end goal here is to winnow the knowledge away and get to the models that will make a difference to the learner’s ability to act.  And when you’re pressed by a certification body that you need to represent what the SME tells you, you may need to push back.  I even advocate anticipating what the models and decisions are likely to be, and getting the SME to criticize and improve, rather than let them start with a blank slate. This does require some smarts on the part of the designer, but when it works, it leverages the fact that it’s easier to critique than generate. They also are potentially valuable in the ways that they recognize where learners go wrong, particularly if they train.  Most of the time, mistakes aren’t random, but are based upon some inappropriate models.  Ideally, you have access to these reliable mistakes, and the reason why they’re made. Your SMEs should be able to help here. They should know ways in which non-experts fail.  It may be the case that some SMEs aren’t as good as others here, so again, as in ones that have access to the models, you need to be selective. This is related to one of the two ways SMEs are your ally.  Ideally, you’re equipped with stories, great failures and great successes. These form the basis of your examples, and ideally come in the form of a story. A SME should have some examples of both that they can spin and you can use to build up an example. This may well be part of your process to get the concepts and practice down, but you need to get these case studies. There’s one other way that SMEs can help. The fact that they are experts is based upon the fact that they somehow find the topic fascinating or rewarding enough to spend the requisite time to acquire expertise. You can, and should, tap into that. Find out what makes this particular field interesting, and use that as a way to communicate the intrinsic interest to learners. Are they playing detective, problem-solver, or protector? What’s the appeal, and then build that into the practice stories you ask learners to engage in. Working with SMEs isn’t easy, but it is critical. Understanding what they can do, and where they intrinsic barriers, gives you a better handle on being able to get what you need to assist learners in being able to perform.  Here are some of my tips, what have you found that works?

So what’s your social media policy?  It’s not something you should do lightly, or haphazardly, it seems to me. In fact, such a policy really is part of your personal knowledge mastery.  While your systems may vary, your results should be sources for you to find information, present yourself in your various communities, and to share your thoughts.  Let’s do this by platform. Facebook, is for me, the place I be me. Clark Quinn, not Quinnovation.  The people I connect to there are a relatively small group that I know through various phases of my life: there are people I’ve known since kindergarten through college, neighbors and friends through various of my various residences, and some professional associations that have also become friends.  And a few others that are hard to categorize other than that they interest me. Largely, it’s people I trust enough to let me be me. If I don’t connect to you there, it’s not a reflection of you, it’s that I just don’t know you well enough to connect.  I can see a B2C company using Facebook, but that’s not me, so it’s not a biz place. Oddly, I used to connect to almost anyone related to elearning on Facebook, but I realized that was a mistake.  I determined that LinkedIn was where I should harbor professional connections, so I trimmed my Facebook connections down and offer most anyone connected to elearning to connect to me on LinkedIn.  I even choose to connect to people I don’t know (rightly or wrongly).  On the other hand, I also get connection requests from bankers, real estate people, and others that I see no connection with. Typically I’ll ask why they want to connect, and when I do get responses, it’s typically a scam (you know, "dying and want to give you my millions"; yeah. right). They get the appropriate treatment. And a caveat, if there’s biz dev or sales in the title even if it is elearning, I sign but also respond that if the first thing they do is pitch me their services, I’ll disconnect. And do. Twitter, of course, is where I follow folks of interest professionally, personally, or even politically. It’s a place to get pointers to new things and of course to reciprocate.  It’s timely, short, and often fun. And there’re the various chats that I participate in around learning (e.g. #lrnchat, which I was recruited to be one of the original moderators, though I’ve finally stepped away, and a few others I join when I can), as another learning channel.  During those times I’ll generate and share a fair bit of tweets, otherwise it’s more opportunistic. And, of course, this is my blog, for deeper reflections. Like this.  I believe that if you find someone interesting, and follow both their blogs and their tweets, you can see what they’re tracking and then their reflections, and use them as a mentor.  A stealth mentor, as I like to call it ;).  And I follow a number of my colleagues who I think have demonstrated the ability to regularly contribute independent thoughts (not just rehashing others) and are tied into sources of real value (not just hype). I confess I’m not yet on Pinterest, Instagram, and others. With finite time, I have to find things that offer real value. And I have my own blinders, just like others.   I’m not facile with video (I also don’t have the attention to watch long things, I think I’m coming to grips with a touch of ADD, with all the good and bad that comes with it). Other social media tools I use for specific things include Yammer, Skype, and of course dedicated tools like Google Docs of various sorts, Doodle, and more.  And I use IFTTT to send blog announcements to Twitter, Facebook, and LinkedIn. I’m not a big user of Google Plus, but if IFTTT did have that as a recipe, I would post there too. Others have other strategies. Some are more closed on LinkedIn, I have friends and colleagues, don’t use Facebook, etc.  The point is to be conscious in your use, and understand the tradeoffs (e.g. the filter bubble).  I want to have a place to share with folks I’m not proximal with, but not professionally. And a place to connect with my professional colleagues. I need a place to follow pointers, and a place to reflect.  This is my social media learning strategy.  What’s yours?

Jane Hart has been widely and wisely known for her top 100 Tools for Learning (you too can register your vote).  As a public service announcement, I list my top 10 tools for learning as well: Google search: I regularly look up things I hear of and don’t know.  It often leads me to Wikipedia (my preferred source, teachers take note), but regularly (e.g. 99.99% of the time) provides me with links that give me the answer i need. Twitter: I am pointed to many amazing and interesting things via Twitter. Skype: the Internet Time Alliance maintains a Skype channel where we regularly discuss issues, and ask and answer each other’s questions. Facebook: there’s another group that I use like the Skype channel, and of course just what comes in from friends postings is a great source of lateral input. WordPress: my blogging tool, that provides regular reflection opportunities for me in generating them, and from the feedback others provide via comments. Microsoft Word: My writing tool for longer posts, articles, and of course books, and writing is a powerful force for organizing my thoughts, and a great way to share them and get feedback. Omnigraffle: the diagramming tool I use, and diagramming is a great way for me to make sense of things. Keynote: creating presentations is another way to think through things, and of course a way to share my thoughts and get feedback. LinkedIn: I share thoughts there and track a few of the groups (not as thoroughly as I wish, of course). Mail: Apple’s email program, and email is another way I can ask questions or get help. Not making the top 10 but useful tools include Google Maps for directions, Yelp for eating,  Good Reader as a way to read and annotate PDFs, and Safari, where I’ve bookmarked a number of sites I read every day like news (ABC and Google News), information on technology, and more. So that’s my list, what’s yours?  I note, after the fact, that many are social media. Which isn’t a surprise, but reinforces just how social learning is! Share with Jane in one of the methods she provides, and it’s always interesting to see what emerges.

So I was reading something that talked about designed versus emergent experiences.  Certainly we have familiarity with designed experiences: courses/training, film, theater, amusement parks. Yet emergent experiences seem like they’d have some unique outcomes and consequently could be more valuable and memorable.  So I wondered how an emergent experience might play out to reliably generate a good experience, regardless. The issue is that designed experiences, e.g. a Disney ride, are predictable.  You can repeat them and notice new things, yet the experience is largely the same.  And there can be brilliant minds behind them, and great outcomes including learning.  But could and should we shoot higher? What emergent experiences do we know?  Emergent means having to interact with something unpredictable and perhaps even reactive. It could be interacting with systems, or it could be interpersonal interaction.  So, what we see in clouds, and experiences we have with games, and certainly interpersonal experiences can be emergent.  Can they repeatedly have desired outcomes as well as unpredictable ones? I think the answer is yes if you allow for the role of some ‘interference’.  That is, someone playing a role in controlling the outcomes.  This is what happens in Dungeons and Dragons games where there is a Dungeon Master, or in Alternate Reality Game where there’s a Puppet Master, or in social learning where an instructor is structuring group assignments. I’m interested in the latter, and the blend between.  I propose that our desired learning experiences should go beyond fixed designs, as our limitations as designers and SMEs will constrain what outcomes we achieve.  They may be good, but what can happen when people interact with each other, and rich systems, allows for more self discovery and ownership.  An alternative to social interaction would be practice set in a simulation that’s richer and with some randomness that mimics the variations seen in the real world that go beyond our specific designs. By creating this richness through interpersonal interaction via dialogue and different viewpoints, or through simulations, we create experiences that go beyond our limitations in specific design.  It certainly may go beyond our resources: branching scenarios and asynchronous independent learning are understandably more pragmatic, but when we can, and when the learning outcomes we need are richer than we can suitably address in a direct fashion, say when we need flexible adaptation to circumstances, we should consider designing emergent experiences.  And I’m inclined to think that social learning is the cheaper way to go than a complex system-generated experience. I’m just thinking out loud here, a tangent sparked by a juxtaposition, part of my ongoing efforts to make sense of the world and apply that to creating more resilient and successful organizations. Based upon the above, I think emergent experiences can create more adaptable and flexible learning, and I think that’s increasingly needed. I welcome your thoughts, reflections, pointers, disagreements, and more.  

This past week, I took off a few days to get into the wilderness with some colleagues.  Five of us got dirty, smelly, and sweaty while hiking in the backcountry.  These are smart, successful, interesting, and funny folks, so the conversation was not PC™, but wise and witty.  And, of course, we got to places like this.  But, in addition to beauty and wisdom, there was a lesson for me, too. The first day out in the wilderness, the sky was threatening, and close to dinner time it suddenly turned worse. I was rushing to finish pumping water, couldn’t find the bag for the outflow (to keep it separate from the inflow) and didn’t quite make it back to the tent before the skies opened up.  I got a bit damp, and worse when the zipper on the fly wouldn’t close. Every time I reached out to try again, I’d get even more drenched. The worry, of course, is that you get your down sleeping bag wet, and it will lose all insulation capability! Well, the bag stayed dry, and the next morning we dried everything out, and were fine for the rest of the trip.  The interesting opportunity for me, however, was how I proceeded from then on. The next time I had to pump water, I took my time.  I very deliberately found a good place to sit, and took special care to work with setting up the inflow and then the outflow.  I did so similarly with firing up the stove and boiling water for dinner and breakfast. There was a pleasure in taking time to do it carefully and right.  Now, there are certain things I naturally do the deliberate way, and other things I rush through.   My realization is that there’s value in thinking more carefully about which things to do deliberately, and there’s an inherent pleasure in doing the things right that matter to you. There are the arguments that the internet is making us stupider, and value in doing things the hard way. I think that the important thing is to choose for yourself which things to ‘outsource’ or do just good enough, and those which to take on and do a personally good job on.  For example, I used to work on my cars myself (I could rebuild a carburetor, gap a distributor, etc; skills that are irrelevant now :), but as things have changed it’s not a worthwhile role for me anymore.  So the lesson for me was to pay more attention to which things I’m doing carefully and which I will choose to decide quick enough is good enough (and which to have others or apps do).    

If we’re talking about beginning to use IT in alignment with how we think, work, and learn, a question arises about who should be in the lead?  It could be HR, it could be L&D, it could be IT, or it could even be the business units that are taking advantage of the opportunity.  What makes sense? In one sense, it’s about using IT well, and that theoretically is IT’s job.  They’re supposed to provide an infrastructure that supports the business. They typically have not only the back end engineers, but the front end designers for any custom applications, and should be evaluating any off-the-shelf solution for viability as well.  Of course, this typically isn’t the case, as an eminent IT guru opined to me that IT doesn’t understand people.  In general, IT folks are highly selected to be able to do things most people can’t, and they’re not necessarily valuable when they can think like other people. Well, then, maybe it’s HR; the whole talent development perspective should include considering the tools to hand.  Unfortunately, HR isn’t particularly astute about people nor technology. They are more about administration and control than about empowerment and success.  The HR policies we  tend to see are almost antithetical to the culture that most promotes innovation. It could also be the business units themselves; they are being seen to create solutions to self-learning and collaboration rather than wait for them to emerge from other environments.  And they certainly (should) understand their own needs.  Unfortunately, they’re not likely to really understand people or IT either.  Too often they don’t realize what is effective. Let’s be clear, there are successes in all the categories above, but they’re typically more from an astute leader rather than a systematic organizational strategy.  And that’s not a repeatable approach. We need better. Ideally, L&D should own it.  They (should) understand people, and be able to work with IT in a product relationship to develop a full performance ecosystem that integrates learning, performance support, and social into a coherent whole.  Where the environment is optimized for an organization to not just survive, but thrive. This comes from the people, but it requires knowing how to help people perform and deliver. It requires new skill sets for sure, including working with IT, culture and change, facilitating innovation, performance consulting, and more (organizations like ATD & LPI are updating their competency definitions in these directions).  It requires getting strategic about metrics, impact, and business goals.  The vision of L&D being the critical core to organizational success through delivery of optimal execution and facilitation of continual innovation is what the Revolution is trying to achieve. This is a chance for L&D to move from the periphery to the center.  It’s worthwhile, but there isn’t infinite time; organizations need solutions, and they’ll get them wherever anyone can seize the opportunity to make a productive improvement. L&D has the opportunity, and here’s to hoping they don’t squander it.

I had the occasion last week to attend a day of ComicCon. If you don’t know it, it is a conference about comics, but also much, much, more. It covers movies and television, games (computers and board), and more. It is also a pop culture phenomenon, where new releases are announced, analysis and discussion occur, and people dress up.  And it is huge! I have gone to many conferences, and some are big, e.g. ATD’s ICE or Online Educa, or Learning Technology (certainly the exhibit hall).  This made the biggest of those seem like a rounding error.  It’s more like the SuperBowl.  People camp out in line to attend the best panels, and the exhibit hall is so packed that you can hardly move.  The conference itself is so big that it maxes out the San Diego Convention Center and spills out into adjoining hotels. And that is really the lesson: something here is generating mad passion.  Such overwhelming interest that there’s a lottery for tickets! I attended once in the very early days, when it was small and cozy (as a college student), but this is something else.  I haven’t been to the Oscars, but this is bigger than what’s shown on TV.  It’s bigger than E3. Again, I haven’t seen CES since the very early days, but it can’t be much larger. And this isn’t for biz, this is for the people and their own hard earned dollars.  In designing learning, we would love to achieve such motivation.  So what’s going on? So first, comics tap into some cultural touchstone; they appear in most (if not all) cultures that have developed mass media.  They tell ongoing stories that resonate with individuals, and drive other media including (as mentioned) movies, TV, games, and toys.  They can convey drama or comedy, and comment on the human condition with insight and heart. The best are truly works of art (oh, Bill Watterson, how could you stop?). They use the standard methods of storytelling, strip away unnecessary details, have (even unlikely) heroes and villains, obstacles and triumphs). And they can convey powerful lessons about values and consequences.  Things we often are trying to achieve. It’s done through complex characters, compelling narratives, and stylistic artwork.  As Hilary Price (author of the comic Rhymes with Orange) told us in a panel, she’s a writer first and an artist second. We don’t use graphic novel/comic/cartoon formats near enough in learning, and we could and should. Similarly with games, the interactive equivalent, for meaningful practice.  I fear we take ourselves too seriously, or let stakeholders keep us from truly engaging our learners. We can and should do better.  We need to understand audience engagement, and leverage that in our learning experiences.  To restate: it’s not about content, it’s about experience. Are you designing experiences?

I’ve been part of several online communities for some years now, and one just blew up. From the reasons why, I think that there are lessons to be had that go beyond personal to implications for L&D. The thing that was critical to the success of the group was trust; you could trust it was safe to share opinions, seek out others’ help, etc.  People ‘let it all hang out’, and that was a good thing. While it was risky, it worked because everyone was open and honest. Or so we thought. Then something happened that broke the trust. What had been safe no longer was.  And that undermined the very basis upon which the group had been valuable. If what was said wasn’t safe, the group couldn’t be used to share and learn from. The bigger implication, of course, is that trust is a critical part of a learning culture, one where the best outcomes come from. And trust is a fragile thing.  It only takes one violation to make it hard to rebuild.  And if you can’t share, you can’t benefit from working out loud, showing your work, and more.  It’s back to the Miranda organization, where anything you say can and will be held against you. The take-home here is that it’s hard to build a learning culture, and easy to undermine.  It takes committed leadership. The upside is of considerable value, but you have to get buy-in, and walk the walk. It’s doable, and even recoverable in many instances, but it won’t happen without work.  I’ll suggest that it’s worth it; what say you?

My colleague Jane Hart dobbed me (and several other colleagues) in for the #blimage challenge.  I usually resent when someone publicly asks me to do something, but fortunately this is easy and, well, it is Jane ;). She presented the following image and our task is to blog about it: So my take is how things grow in a nurturing environment.  Here plants are flourishing under the energy of the sun.  This to me is a metaphor for the benefits of creating a culture in which learning can flourish.  I’ve earlier detailed what the research says about the elements of a learning organization, and it’s clear that you  need a culture with several elements. First, learning independently has to be enabled. The resources to learn need to be there, as does the time for learning. Further, the ability to learn on one’s own shouldn’t be taken for granted; identify, model, evangelize, and develop these abilities. In addition, learning is social.  The possibilities to learn together need to be facilitated.  There need to be ways to find individuals with complementary skills to learn together. This in particular means collaboration: learning while innovating on solving new problems, devising new solutions, and more.  It also means being willing to share. It has to be safe to ‘show your work’!  Again, don’t assume skills for learning together, but scaffold the development of these abilities. It is really important that leadership reinforces learning, both by supporting and more importantly by practicing visibly! There’s evidence that when leadership doesn’t share, others won’t truly believe it’s valued. So there’s my blog on the image.  Two colleagues also were challenged with this image and have replied; you can see what they came up with: Jane Bozarth Charles Jennings Rather than dob in anyone in particular, I will simply recommend that you take your own stab, and here’s a proposed image: I hope to hear what you come up with; drop a link in the comments if you do!  

Learning is the new business imperative. It is now an indisputable business reality: companies must become more nimble and agile. As things move faster, new processes arise, and the time to copy a new business approach drops, it becomes clear that continual innovation is the only way to not just survive, but thrive.  And this doesn’t, can’t, come from the status quo. And if the answer isn’t known, as is inherent in situations like problem-solving, trouble-shooting, new product/service creation, and more, then this, too, is a form of learning. But not the type addressed by training rooms or eLearning courses. They serve a role, but not this new one, this needed approach,  We need something new. What we need are two things: effective collaboration and meta-learning. Innovation comes, we know, from collaboration.  Collaboration is the new learning, where we bring complementary strengths to bear on a problem in a process structured to be optimally aligned with how our brains work.  And we need to create a culture and set of skills around continually learning, which means understanding learning to learn, aka meta-learning. Accelerating the development of these capabilities means doing things different and new. It means sowing the seeds by instigating a learning process that develops not only some specific needed capabilities, but also the meta-learning and collaboration skills.  It means understanding, valuing, and explicitly developing the ability of people to learn alone and together. It means making it safe to share, to ‘work out loud’. And finally it means scaling up from small success to organizational transformation. This is a doable, albeit challenging move, but it is critical to organizations that will excel. Learning is no longer a ‘nice to have’, or even an imperative, it is the only sustainable differentiator.  The question is: are you ready?  Are you making the new learning a strategic priority?

I had lunch recently with Paul Signorelli, who’s active in helping libraries with digital literacy, and during the conversation he talked about his vision of the future of the library. What I heard was a vision of libraries moving beyond content to be about learning, and this had several facets I found thought-provoking. Now, as context, I’ve always been a fan of libraries and library science (and librarians). They were some of the first to deal with the issues involved in content organization, leading to information science, and their insight into tagging and finding is still influencing content architecture and engineering.  But here we’re talking about the ongoing societal role of libraries. First, to be about learning, it has to be about experience, not content. This is the crux of a message I’ve tried to present to publishers, when they were still wrestling with the transition from book to content!  In this case, it’s an interesting proposition about how libraries would wrap their content to create learning experiences. Interestingly, Paul also suggested that he was thinking broader, about how libraries could also point to people who could help. This is a really intriguing idea, about libraries becoming a local broker between expertise and needs.  Not all the necessary resources are books or even print, and as libraries are now providing video and audio as well as print, and on to computer access to resources beyond the library’s collection, so too can it be about people. This is a significant shift, but it parallels the oft-told story of marketing myopia, e.g. about how railroads aren’t about trains but instead are about transportation.  What is the role of the library in the era of the internet, of self-help. One role, of course, is to be the repository of research skills, about digital literacy (which is where this conversation had started).  However, this notion of being a center of supporting learning, not just a center of content, moves those literacy skills to include learning as well!  But it goes further. This notion turns the role of a library into a solution: whether you  need to get something done, learn something, or more, e.g. more than just learning but also performance support and social, becoming the local hub for helping people succeed.  He aptly pointed out how this is a natural way to use the fact that libraries tend to exist on public money; to become an even richer part of supporting the community. It’s also, of course, an interesting way to think about how the locus of supporting people shifts from L&D and library to a joint initiative.  Whether there’s still a corporate library is an open question, but it may be a natural partner to start thinking about a broader perspective for L&D in the organization. I’m still pondering the ways in which libraries could facilitate learning (just as trainers should become learning facilitators, so too should librarians?).  

There have been a couple of recent proposals about the relative role of cooperation and collaboration, and I’m trying to make sense of them.  Here are a couple of different approaches, and my first take at teasing them apart. Dion Hinchcliffe of Adjuvi tweeted a diagram about different types of working together that shows his take. He has coordination as a subsidiary to cooperation and on to collaboration.  So coordination is when we know what needs to be done, but we can’t do it alone. Cooperation is when we’re doing things that need to have a contribution from each of us, and requires some integration. And collaboration is when we’re working together with a goal but not clear how we’ll get there.  I think what’s core here is how well defined the task is and how much we contribute. In the meantime, Harold Jarche, my ITA colleague, as a different take.  He sees collaboration as working together to achieve a goal that’s for the organization, whereas cooperation goes beyond.  Cooperation is where we participate and assist one another for our own goals.  It’s contribution that’s uncoupled from any sense of requirement, and is freely given.  I see here the discussion is more about our motives; why are we engaged. With those two different takes, I see them as different ways of carving up the activities. My initial reaction is closer to Dion’s; I’ve always seen cooperation as willingness to assist when asked, or to provide pointers. To me collaboration is higher; it’s willing to not just provide assistance in clearly defined ways such as pointers to relevant work, answering questions, etc, but to actively roll up sleeves and pitch in.  (Coordination is, to me I guess, a subset of cooperation.) With collaboration I’ve got a vested interest in the outcome, and am willing to help frame the question, do independent research, iterate, and persist to achieve the outcome. I see the issue of motivation or goal as a different thing. I can cooperate in a company-directed manner, as expected, but I also can (and do) cooperate in a broader sense; when people ask for help (my principles are simple: talk ideas for free; help someone personally for dinner/drinks; if someone’s making a quid  I get a cut), I will try to assist (with the Least Assistance Principle in mind).  I can also collaborate on mutual goals (whether ITA projects or client work), but then I can also collaborate on things that have no immediate outcome except to improve the industry as a whole (*cough* Serious eLearning Manifesto *cough*). So I see two independent dimensions: one on the effort invested, just responding to need or actively contributing; and the other on the motivation, whether for a structured goal or for the greater good. Now I have no belief that either of them will necessarily agree with my take, but I’d like to reconcile these interpretations for the overall understanding (or at least my own!).  That’s my first take, feedback welcome!

If, indeed, learning is the new business imperative, what does that mean we need to learn?  What are the skills that we want to have, or need to develop?  I reckon they fall into two categories; those we do for our own learning, and those for learning with and through others. When we learn on our own, we need to address what information we want coming in and how we process it.  This falls under Harold Jarche’s Personal Knowlege Mastery of Seek - Sense - Share. To me there are two main components: what you actively seek, and what comes to you. What you actively seek really is your searching abilities.  Several things come into play. One is knowing where to look. When do you google, when do you do an internal search, when do you check out a book?  And how to look is also a component. Do you know how to make a good search string?  Do you know how to evaluate the quality of the responses you get?  I see too often that people aren’t critical enough in looking at purveyed information. Then, you also want to set up a stream of information that comes to you. Who to follow on social media?  What streams of information?  How do you find what sources others use?  How do you track what’s happening in your areas of interest and responsibility without getting overwhelmed?  This is personal information management, and it requires active management, as sources change.  And there are different strategies for different media, as well. Note that this crosses over into social, but people don’t necessarily know you’re following them.  While there may be a notification, they don’t know how much attention  you’re paying.  I’ve talked about ‘stealth mentoring’, where you can follow someone’s tweets and blog posts, and they can serve as a mentor for you without even knowing it! There’s some processing of that information, too. What do you do with it? How do you make sense of it? If you hear X over here, and Y over there, you should try to actively reconcile it (e.g. as I did here with collaboration and cooperation).  Do you diagram, write, make a video, ? Of course, if you do process it, do you share it? Now we’re crossing over into the social space more proactively.   There’re good reasons to ‘show your work’; in terms of helping others understand where you’re at in your process and for them to offer help.  And sharing  your thinking can help others.   Your thoughts, even interim, can help you and others sort out your thinking.  There are some skills involved in figuring out how to systematically share, and of course some diligence and effort is required too, at least before it becomes a habit. And, of course, there is explicitly asking for help. There are ways to ask for help that aren’t effective!  Similarly, there are ways to offer help that won’t necessarily be taken up.  So there are skills involved in communicating. Similarly, collaboration shouldn’t be taken for granted. Do you know different ways to collaborate on documents, presentations, and spreadsheets?  Hint: there are better ways than emailing around files!    How do you manage a collaboration process so that it maximizes the outcome? For instance, there are nuances to brainstorming. There are lots of skills involved, and not only should you develop your own, but you should consider the benefits to the organization to developing them systematically and systemically.  So, what did I miss?  Wondering if I should try to diagram this…  

We’ve heard about learning engineering and while the focus is on experience design, the pragmatics include designing content to create the context, resources, and motivation for the activity.  And it’s time we step beyond just hardwiring this content together, and start treating it as professionals. Look at business websites these days. You can customize the content you’re searching for with filters.  The content reacts to the device you’re on and displays appropriately.  There can even be content that is specific to your particular trace of action through the site and previous visits.  Just look at Amazon or Netflix recommendations! This doesn’t happen by hardwired sites anymore.  If you look at the conferences around content, you’ll find that they’re talking industrial strength solutions.  They use content management systems, carefully articulated with tight definitions and associated tags, and rules that pull together those content elements by definition into the resulting site.  This is content engineering, and it’s a direction we need to go. What’s involved is tighter templates around content roles, metadata describing the content, and management of the content. You write into the system, describe it, and pull it out by description, not by hard link. This allows flexibility and rules that can pull differentially by different contexts: different people, different role, different need, and different device. We also separate out what it says from how it looks, using tags to support rendering appropriately on different devices rather than hard-coding the appearance as well as the content and the assembly. This is additional work, but the reasons are several.  First, being tighter around content definitions provides a greater opportunity to be scientific about the role the content plays. We’re too lax in our content, so that beyond a good objective, we don’t specify what makes a good example, etc.   Second, by using a system to maintain that content, we can get more rigorous in content management.  I regularly ask audiences whether they have outdated legacy content hanging around, and pretty much everyone agrees. This isn’t effective content governance, and content should have regular cycles of review and expiry dates. By this tighter process, we not only provide better content design, delivery, and management, but we set the stage for the future.  Personalization and customization, contextualization, are hampered when you have to hand-configure every option you will support. It’s much easier to write a new set of rules and then your content can serve new purposes, new business models, and more. If you want to know more about this, I hope to see you at my session on content at DevLearn!

I’m increasingly realizing that the ways we design and develop content are part of the reason why we’re not getting the respect we deserve.  Our brains are arguably the most complex things in the known universe, yet we don’t treat our discipline as the science it is.  We need to start combining experience design with learning engineering to really start delivering solutions. To truly design learning, we need to understand learning science.  And this does not mean paying attention to so-called ‘brain science’. There is legitimate brain science (c.f. Medina, Willingham), and then there’s a lot of smoke. For instance, there’re sound cognitive reasons why information dump and knowledge test won’t lead to learning.  Information that’s not applied doesn’t stick, and application that’s not sufficient doesn’t stick. And it won’t transfer well if you don’t have appropriate contexts across examples and practice.  The list goes on. What it takes is understanding our brains: the different components, the processes, how learning proceeds, and what interferes.  And we need to look at the right levels; lots of neuroscience is not relevant at the higher level where our thinking happens.  And much about that is still under debate (just google ‘consciousness‘ :). What we do have are robust theories about learning that pretty comprehensively integrate the empirical data.  More importantly, we have lots of ‘take home’ lessons about what does, and doesn’t work.  But just following a template isn’t sufficient.  There are gaps where have to use our best inferences based upon models to fill in. The point I’m trying to make is that we have to stop treating designing learning as something anyone can do.  The notion that we can have tools that make it so anyone can design learning has to be squelched. We need to go back to taking pride in our work, and designing learning that matches how our brains work. Otherwise, we are guilty of malpractice. So please, please, start designing in coherence with what we know about how people learn. If you’re interested in learning more, I’ll be running a learning science for design workshop at DevLearn, and would love to see you there.

It’s time for another game of Where’s Clark?  As usual, I’ll be somewhat peripatetic this fall, but more broadly scoped than usual: First I’ll be hitting Shenzhen, China at the end of August to talk advanced mlearning for a private event. Then I’ll be hitting the always excellent DevLearn in Las Vegas at the end of September to run a workshop on learning science for design (you should want to attend!) and give a session on content engineering. At the end of October I’m down under at the Learning@Work event in Sydney to talk the Revolution. At the beginning of November I’ll be at LearnTech Asia in Singapore, with an impressive lineup of fellow speakers to again sing the praises of reforming L&D. That might seem like enough, but I’ll also be at Online Educa in Berlin at the beginning of December running an mlearning for academia workshop and seeing my ITA colleagues. Yes, it’s quite the whirl, but with this itinerary I should be somewhere near you almost anywhere you are in the world. (Or engage me to show up at your locale!) I hope to see you at one event or another before the year is out.  

I’m working on the learning science workshop I’m going to present at DevLearn next month, and in thinking about how to represent the implications of designing to account for how we work better when the learning context is concrete and sufficient contexts are used, I came up with this, which I wanted to share. The empirical data is that we learn better when our learning practice is contextualized.  And if we want transfer, we should have practice in a spread of contexts that will facilitate abstraction and application to all appropriate settings, not just the ones seen in the learning experience.  If the space between our learning applications is too narrow, so too will our transfer be. So our activities need to be spread about in a variety of contexts (and we should be having sufficient practice). Then, for each activity, we should have a concrete outcome we’re looking for. Ideally, the learner is given a concrete deliverable as an outcome that they must produce (that mimics the type of outcome we’re expecting them to be able to create as an outcome of the learning, whether decision, work product, or..).  Ideally we’re in a social situation and they’re working as a team (or not) and the work can be circulated for peer review.  Regardless, then there should be expert oversight on feedback. With a focus on sufficient and meaningful practice, we’re more likely to design learning that will actually have an impact.  The goal is to have practice that is aligned with how our learning works (my current theme: aligning with how we think, work, and learn). Make sense?

I’m realizing that a major theme of my work and the revolution is that what we do in organizations, and what we do as L&D practitioners, is not aligned with how we think, work, and learn.  And to that extent, we’re doomed to failure. We can, and need to, do better. Let’s start with thinking. The major mismatch here is that our thinking is done rationally and in our head. Results in cognitive science show, instead, that much of our thinking is irrational and is distributed across the world. We use external representations and tools, and unless we’re experts, we make decisions and use our brains to justify them rather than actually do the hard work. What does this mean for organizations and L&D?  It means we should be looking to augment how we think, with tools and processes like performance support, helping us find information with powerful search.  We want to have open book learning, since we’ll use the book in the real world, and we want to avoid putting it ‘in the head’ as much as possible. Particularly rote information. We should expect errors, and provide support with checklists, not naively expect that people can perform like robots. This carries over to how we work.  The old view is that we work alone, performing our task, and being managed from above with one person thinking for a number of folks.  What we now know, however, is that this view isn’t optimal. The output is better when we get multiple complementary minds working together.  Adaptation and innovation work best when we work together. So we don’t need isolation to do our work, we need cooperation and collaboration.  We need ways to work together. We need to give people meaningful tasks and give them space to execute, with appropriate support. We need to create environments where it’s safe to share, to show your work, to work out loud. And our models of learning are broken. The trend to an  event comprised of information dump and knowledge test we know doesn’t work. Rote procedures are no longer sufficient for the increasing ambiguity and unique situations our learners are seeing. And the notion that "practice ’til they get it right" will lead to any meaningful change in ability is fundamentally flawed. To learn, we need models to guide our behavior and help us adapt.  We need to identify and address misconceptions. We need learners to engage concretely and be scaffolded in reflection.   And we need much practice.  Our learning experiences need to look much more like scenarios and serious games, not like text and next. We’re in an information age, and industrial models just won’t cut it.  I’m finding that we’re hampered by a fundamental lack of awareness of our brains, and this is manifesting in too many unfortunate and ineffective practices.  We need to get better. We know better paths, and we need to trod them.  Let’s start acting like professionals and develop the expertise we need to do the job we must do. #itashare

In thinking through what makes experiences engaging, and in particular making practice engaging, I riffed on some core elements.   The three terms I came up with were Challenge, Choices, & Consequences. And I realized I had a nice little alliteration going, so I’m going to elaborate and see if it makes sense to me (and you). In general, good practice is having the learner make decisions in context. This has to be more than just recognizing the correct knowledge option, and providing a ‘right’ or ‘wrong’ feedback.  The right decision has to be made, in a plausible situation with plausible alternatives, and the right feedback has to be provided. So, the first thing is, there has to be a situation that the learner ‘gets’ is important. It’s meaningful to them and to their stakeholders, and they want to get it right. It has to be clear there’s a real decision that has outcomes that are important.  And the difficulty has to be adjusted to their level of ability. If it’s too easy, they’re bored and little learning occurs. If it’s too difficult, it’s frustrating and again little learning occurs.  However, with a meaningful story and the right level of difficulty, we have the appropriate challenge.  Then, we have to have the right alternatives to select from. Some of the challenge comes from having a real decision where you can recognize that making the wrong choice would be problematic. But the alternatives must require an appropriate level of discrimination.  Alternatives that are so obvious or silly that they can be ruled out aren’t going to lead to any learning. Instead, they need to be ways learners reliably go wrong, representing misconceptions. The benefits are several: first, you can find out what they really know (or don’t), and you have the chance to address them. Also, this assists in having the right level of challenge.  So  you must have the right choices. Finally, once the choice is made, you need to have feedback. Rather than immediately have some external voice opine ‘yes’ or ‘no’, let the learner see the consequences of that choice. This is important for two reasons. For one, it closes the emotional experience, as you see what happens, wrapping up the experience. Second, it shows how things work in the world, exposing the causal relationships and assists the learner understanding. Then you can provide feedback (or not, if you’re embedding this single decision in a scenario or game where other choices are precipitated by this choice). So, the final element are consequences. While this isn’t complete, I think it’s a nice shorthand to guide the design of meaningful and engaging practice. What do you think?

In a conversation I had recently, specifically about a community focused on research, I used the term ‘community of improvement’, and was asked how that was different than a community of practice. It caused me to think through what the differences might be.  (BTW, the idea was sparked by conversations with Lucian Tarnowski from BraveNew.) First, let me say that a community of practice could be, and should be, a community of improvement. One of the principles of practice is reflection and improvement.  But that’s not necessarily the case.  A community of practice could just be a place where people answer each other’s questions, collaborate on tasks, and help one another with issues not specifically aligned with the community.  But there should be more. What I suggested in the conversation was that a community should also be about documenting practice, applying that practice through action or design research, and reflecting on the outcomes and the implications for practice.  The community should be looking to other fields for inspiration, and attempting experiments. It’s the community equivalent of Schön’s reflective practitioner.  And it’s more than just cooperation or collaboration, but actively engaging and working to improve. Basically, this requires collaboration tools, not just communication tools. It requires: places to share thoughts; ways to find partners on the documentation, experimentation, and reflection; and support to track and share the resulting changes on community practices. Yes, obviously a real community of practice should be doing this, but too often I see community tools without the collaboration tools. So I think it’s worth being explicit about what we would hope will accompany the outcomes.  So, where do we do this, and how? #itashare

So, I found an interesting inconsistency.  I had to submit my deck for my DevLearn workshop on Cognitive Science for Learning Design last week, but oddly, for every thing I was recommending I had a diagram, except for the notion of using models.  This is ironic, since diagrams can be used to convey models.  It bugged me, so I pondered. And then I remembered that I gave a presentation years ago specifically on diagrams.  Moreover, in that presentation I had a diagram for a process for creating a diagram (Department of Redundancy Department).  So, I finally got around to trying to apply my own process to my lack of a model.  And voilà: The process is to identify the elements, and the relationships, and then additional dimensions.  Then you represent each, place them (elements first, relationships second, dimensions last), and tune. Here the notion is that you have a mental model of a concept, capturing elements and causal relationships.  When you see a situation, you select a model where you can map the elements in the model to elements in the context.  Then you can use the model to predict what will happen or explain what happened. Which gives you a basis for making decisions, and adapting decisions to different contexts in principled ways. Models are a powerful concept I’ve harped on before, but now I’ve an associated diagram.  And I like diagrams. I find mapping the conceptual dimensions to spatial dimensions both helps me get concrete about the models and then gives a framework to share with others.  Does this make sense to you, both the concept behind it, and the diagram to represent it? I’ll be presenting this in the workshop, amongst many other implications from how our brains work (and learn) to the design of learning experiences.  Would love to see you there.

It actually happened a while ago, but I was pleased to learn that Designing mLearning has been translated into Korean.  That’s kind of a nice thing to have happen!  A slightly different visual treatment, presumably  appropriate to the market. Who knows,  maybe I’ll get a chance to visit instead of just transferring through the airport.  Anyways, just had to share ;).

A continued bane of my existence is the ongoing requirements that are put in place for a variety of things.  Two in particular are related and worth noting: accreditation and compliance.  The way they’re typically construed is barking mad, and we can (and need to) do better. To start with accreditation. It sounds like a good thing: to make sure that someone issuing some sort of certification has in place the proper procedures.  And, done rightly, it would be. However, what we currently see is that, basically, the body says you have to take what the Subject Matter Expert (SME) says as the gospel. And this is problematic. The root of the problem is that SMEs don’t have access to around 70% of what they do, as research at the University of Southern California’s Cognitive Technology group has documented. However, of course, they have access to all they ‘know’. So it’s easy for them to say what learners should know, but not what learners actually should be able to do.  And some experts are better than others at articulating this, but the process is opaque to this nuance. So unless the certification process is willing to allow the issuing institution the flexibility to use a process to drill down into the actual ‘do’, you’re going to get knowledge-focused courses that don’t actually achieve important outcomes. You could do things like incorporating those who depend on the practitioners, and/or using a replicable and grounded process with SMEs that helps them work out what the core objectives need to be; meaningful ones, ala competencies. And a shoutout to Western Governors University for somehow being accredited using competencies! Compliance is, arguably, worse.  Somehow, the amount of time you spend is the important determining factor. Not what you can do at the end, but instead that you’ve done something for an hour.  The notion that amount of time spent relates to ability at this level of granularity is outright maniacal.  Time would matter, differently for different folks, but you have to be doing the right thing, and there’s no stricture for that.   Instead, if you’ve been subjected to an hour of information, that somehow is going to change your behavior. As if. Again, competencies would make sense.  Determine what you need them to be able to do, and then assess that. If it takes them 30 minutes, that’s OK. If it takes them 5 hours, well, it’s necessary to be compliant. I’d like to be wrong, but I’ve seen personal instances of both of these, working with clients. I’d really like to find a point of leverage to address this.  How can we start having processes that obtain necessary skills, and then use those to determine ability, not time or arbitrary authority!  Where can we start to make this necessary change?