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Constraints on activities

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When we design learning activities (per the activity-based learning model), ideally we’re looking to create an integration of a number of constraints around that assignment. I was looking to enumerate them, and (of course) I tried diagramming it.  Thought I’d share the first draft, and I welcome feedback!

Multiple constraints on assignmentsThe goal is an assignment that includes the right type of processing. This must align with what they need to be able to do after the learning experience. Whether at work or in a subsequent class. Of course, that’s factored into the objective for this learning activity (which is part of an overall sequence of learning).

Another constraint is making sure the setting is a context that helps establish the breadth of transfer. The choice should be sufficiently different from contexts seen in examples and other practices to facilitate abstracting the essential elements. And, of course, it’s ideally in the form of a story that the learner’s actions are contributing to (read: resolve). The right level of exaggeration could play an (unrepresented) role in that story.

We also need the challenge in the activity to be in the right range of difficulty for the learner. This is the integration of flow and learning to create meaningful engagement.  And we want to include ways in which learners typically go wrong (read: misconceptions). Learners need to be able to make the mistakes here so we’re trapping and addressing them in the learning situation, not when it could matter.

Finally, we want to make sure there’s enough variation across tasks. While some similarities benefit for both consistency and addressing the objective, variety can maintain interest. We need to strike that balance. Similarly, look at the overall workload: how much are we expecting, and is that appropriate given the other constraints outside this learning goal.

I think you can see that successfully integrating these is non-trivial, and I haven’t even gotten into how to evaluate this, particularly to make it a part of an overall assessment. Yet, we know that multiple constraints help make the design easier (at least until you constrain yourself to an empty solution set ;).  This is probably still a mix of art and science, but by being explicit you’re less likely to miss an element.

We want to align activities with the desired outcome, in the full context.  So, what am I missing?  Does this make sense?

 

Labels, models, and drives

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In my post last week on engagement, I presented the alignment model from my  Engaging Learning  book on designing learning experiences. And as I thought about the post, I pondered several related things about labels, models, and drives. I thought I’d wrestle with them ‘out loud’ here, and troll (in the old sense) to see what you think.

Some folks have branded a model and lived on that for their career. And, in a number of cases, that’s not bad: they’re useful models and their applicability hasn’t diminished. And while, for instance, I think that alignment model is as useful as most models I’ve seen, I didn’t see any reason to tie my legacy to it, because the principles I like to comprehend and then apply to create solutions aren’t limited to just engagement. Though I wonder if people would find it easier to put the model in practice if it had a label.  The Quinn Engagement model or somesuch?

I’ve also created models around mobile, and about performance ecosystems, and more. I can’t say that they’re all original (e.g. the 4Cs of mobile), though I think they have utility. And some have labels (again, the 4Cs, Least Assistance Principle…) Then the misconceptions book is very useful, but the coverage there isn’t really mine, either. It’s just a useful compendium. I expect to keep creating models. But it’d led to another thought…

I’ve seen people driven to build companies. They just keep doing it, even if they’ve built one and sold it, they’re always on it; they’re serial entrepreneurs. I, for instance, have no desire to do that. There are elements to that that aren’t me.    Other folks are driven to do research: they have a knack for designing experiments that tease out the questions that drive them to find answers. And I’ve been good at that, but it’s not what makes my heart beat faster. I do  like action research, which is about doing with theory, and reflecting back. (I also like helping others become able to do this.)

What I’m about is understanding and applying cognitive science (in the broad sense) to help people do important things in ways that are enabled by new technologies.  Models that explain disparate domains are a hobby. I like finding ways to apply them to solve new problems in ways that are insightful but also pragmatic.   If I create models along the way (and I do), that’s a bonus. Maybe I should try to create a model about applying models or somesuch. But really, I like what I do.

The question I had though, is whether anyone’s categorized ‘drives’.  Some folks are clearly driven by money, some by physical challenges. Is there a characterization?  Not that there needs to be, but the above chain of thought led me to be curious. Is there a typology of drives? And, of course, I’m skeptical if there is one (or more), owing to the problems with, for instance, personality types and learning styles :D. Still, welcome any pointers.

Where’s Clark? Fall 2018/Spring 2019 Events Schedule

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Here’re the events where I’ll be through the last quarter of this year, and into the next. Of course, you can always find out what’s up at the Quinnovation News page… But this is a more likely place for you to start unless you’re looking to talk to me about work.  I hope to see you, virtually or in person, at one of these!

The week of October 22-26, Clark will be speaking (the same week!) at DevLearn on measurement and eLearning science, and at AECT on meta-learning architecture. (Yeah, both in one week…long story.)

On Litmos’ Live Virtual Summit on 7-8 November, Clark will talk Learning Experience. Stay tuned!

Clark will be a guest on Relate’s eLearnChat on 15 Nov.

2019

On the 9th of January, Clark will present The Myths that Plague Us as a webinar for HRDQ-U.

Clark will be presenting in the Modern Workplace Learning track at the LearnTec conference in Karlsruhe, Germany that runs 29-31 January.

Feb 25-27, Clark will serve as host of the Strategy Track at Training Magazine’s annual conference, opening with an overview and closing with a strategy-development session.

Clark will speak to the Charlotte Chapter of ISPI on the Performance Ecosystem on March 14.

At the eLearning Guild’s Learning Solutions conference March 25-28, Clark will be presenting a Learning Experience Design workshop, where we’ll go deep on integrating learning science and engagement.

If you’re at one of these events, please do introduce yourself and say hello (I’m not aloof, I’m just shy; er, ok, at least ’til we get to know one another :).

ONE level of exaggeration

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I’ve argued before that we should be thinking about exaggeration in our learning design. And I’ve noticed that it’s a dramatic trick in popular media. But you can easily think of ways it can go wrong. So what would be appropriate exaggeration?

When I look at movies and other story-telling media (comics), the exaggeration  usually is one level.  You know, it’s like real life but some aspect is taken beyond what’s typical. So, more extreme events happen: the whacky neighbor is  maniacal, or the money problems are  potentially fatal, or the unlikely events on a trip are just more extreme.  And this works; real life is mundane, but you go too far and it treads past the line of believability. So there’s a fine line there.

Now, when we’re actually performing, whether with customers or developing a solution, it matters. It’s our  job after all, and people are counting on us.  There’s plenty of stress, because there are probably not enough time, and too much work, and…

However, in the learning situation, you’re just mimicking the real world. It’s hard to mimic the stress that comes from real life. So, I’m arguing, we should be bringing in the extra pressure through the story. Exaggerate!  You’re not just helping a customer, you’re helping the foreign ambassador’s daughter, and international relations are at stake!  Or the person you’re sweet on (or the father of said person) is watching!  This is the chance to have fun and be creative!

Now, you can’t exaggerate everything. You could add extraneous cognitive load in terms of processing if you make it too complex in the details. And you definitely don’t want to change the inherent decisions in the task and decrease the relevance of the learning. To me, it’s about increasing the meaning of the decisions, without affecting their nature. Which may require a bit of interpretation, but I think it’s manageable.

At core, I don’t think I’m exaggerating when I say exaggeration is one of your tools to enhance engagement  and effectiveness. The closer we bring the learning situation to the performance situation, the higher the transfer. And if we increase the meaningfulness of the learning context to match the performance context, even if the details are more dissimilar, I think it’s an effective tradeoff. What do  you think?

User-experienced stories

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Yesterday I wrote about examples as stories. And I received a comment that prompted some reflection. The comment suggested that scenarios were stories too. And I agree!  They’re not examples, but they  are stories. With a twist.

So, as I’ve said many times, simulations are just a manipulable model of the world. And a motivated, self-capable learner  can learn from them. But motivated and self-capable isn’t always a safe bet. So, instead, we put the simulation in an initial state, and ask the learner to take it to a goal state, and we choose those such that they can’t get there until they learn the relationships we want them to understand. That’s what I call a scenario.  And we can tune those into a game. (Yes, we turn them into games by tuning; making the setting compelling, adjusting the challenge, etc.)

Now, a scenario needs a number of things. It needs a context, a setting. It needs a goal, a situation to be achieved. And, I’ll suggest, it should also have a reason for that goal to make sense. If you see the alignment that says why games  should be hard fun, you’ll see that making it meaningful is one of the elements. And that,  I say, is a story. Or, at least, the beginning of one.

In short, a story has a setting, a goal, and a path to get there. We remove boring details, highlight the tension, etc.  We flesh out a setting that the learner cares about, provide a sense of urgency, and enable the goal achievement.  But it’s not all done.

The reason this isn’t a complete story is we don’t know the path the protagonist uses to accomplish the goal, or ultimately doesn’t.  We’ve provided tools for that to happen, but we, as designers, don’t control the protagonist. The learner, really,  is the the protagonist!

What I’m talking about is that the story, certainly for the learner, is co-created between the world we’ve developed, and their use of the options or choices we provide. Together, a story is written for them by us  and them.  And, their decisions and the feedback are the story  and the learning!  It’s, voilà, a learning  experience.

Learning is powerful. Creating experiences that facilitate learning are creative hard fun for the designer, and valuable hard fun for the learner. Learning is about stories, some told, some c0-created, but all valuable.

Old and new school

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As I mentioned in yesterday’s post, I was asked for my responses to questions about trends.  What emerged in the resulting article, however, was pretty much contrary to what I said. I wasn’t misquoted, as I was used to set the stage, but what followed wasn’t what I said. What I saw was what I consider somewhat superficial evaluation, and I’d like to point to new school thinking instead.

So the article went from my claim about an ecosystem approach to touting three particular trends. And yet, these trends aren’t really new and aren’t really right!  They were touting mobile, gamification, and the ‘realities. And while there’s nothing wrong with any of them, I had said that I didn’t think that they’re the leading trends.

So, first, mobile is pretty much old news. Mobile first?  Er, it‘s only been 8 years or so (!) since Google declared that! What‘s cool about  mobile, still, is sensors and context-awareness, which they don‘t touch on.  And, in a repeated approach, they veered from the topic to quote a colleague. And my colleague was spot on, but it wasn’t in the least about mobile!  They ended this section talking about gamification and AR/VR, yet somehow implied that this was all about mobile. That would be “no”.

Then they talked about users wanting to be active.  Yay!  But, er, again they segued off-topic, taking personalization before going to microlearning and back to gamification and game-based learning(?).  Wait, what?  Microlearning is an ill-defined concept, and conflating it with game-based learning is just silly.  And games are real, but it‘s still hard to do them (particularly do them right, instead of tarted up drill-and-kill).  Of course, they didn‘t really stay on topic.

Finally, the realities. Here they stayed on topic, but really missed the opportunity. While AR and VR have real value, they talked about 360 photography and videography, which is about consumption, not interaction. And, that‘s not where the future is.

To go back to the initial premise – the three big trends – I think they got it wrong.  AI and data are now far more of a driver than mobile. Yes, AR/VR, but interaction, not just ‘immersion‘.  And probably the third driver is the ecosystem perspective, with systems integration and SaaS.

So, I have to say that the article was underwhelming in insight, confused in story, and wrong on topic. It’s like they just picked a quote and then went anywhere they wanted.   It’s old school thinking, and we’re beyond that. Again, my intention is not to continue to unpack wrong thinking (I’m assuming that’s not what you’re mostly here for, but let me know), but since this quoted me, I felt obliged.  It’s past time for new school thinking in L&D, because focusing on content is, like,  so last century.

Mobile Malarkey

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I was called out on a tweet pointing to an article on mobile. And, I have to say, I thought it was pretty underwhelming. It was the ‘old school’ view of mlearning, and I think that the post largely missed the point. So I thought it’d be valuable to walk through the claims. What I’m trying to accomplish is share how my thinking works, and perhaps contaminate you with a wee bit of it too ;). We need to get better at cutting through the hype (part of the debunking skills), and that includes microlearning and mobile malarkey as well.

The post makes four claims for why mobile is on the rise:

  • the advancements in mobile technology
  • the desire for small content
  • more engaging content
  • consumption ‘on the go’

So let’s go through these.  However, first I’m going to challenge the assumption!

Mobile is not ‘on the rise’.  That’s so 2012.  Mobile is well past the ‘new’ stage.  Heck, Google was arguing ‘mobile first’ back in 2010!  Even here in the US, it’s mainstream, and it’s been the ‘goto’ mode in other countries for much longer.

Now, the advancements in mobile technology  are continuing, and impressive.  Things like sensors for contextual information, networking for social connections, new interaction capabilities like pressure-sensitivity, and higher resolution screens and faster processors mean new capabilities.  What the article is talking about, is cutting edge content. Yes, video can be useful ‘on demand’, and interactivity can be powerful.  In context.  But they’re not picking up on that. This is still the ‘get training wherever you are’ mentality.  Mobile is really not about courses!  But maybe they’ll get better..

Next is the chunks. Ok, so I’ve already weighed in on ‘microlearning’.  Yes, small is better. It  does matter whether you’re talking performance support or spaced learning, but small is good. However, this article touts that we prefer smaller chunks (er, yes, and that’s not a good indicator).  And that we benefit from smaller. Yes, but this is still about ‘content consumption’.  Mobile can, and should be more than that.

On to engagement. Here the claim is that these small bits are more engaging, but that we can do interactive things as well. And this is good: mini-scenarios (better written multiple choice), even branching scenarios can lead to better. However, here they’re talking quizzes and infographics. Again, mostly content, and also focused on knowledge, not skills. This isn’t where the emphasis should be. Spaced learning yes, but reactivation – reconceptualization, recontextualization, and reapplication – not content dump and knowledge test.

Finally, it’s about remote workers. Yes, again, contextualization to give the right thing, to the right person, at the right time and place. But no, they’re talking about accessing training where/when/ever. Yes, that’s nice.  But not intrinsically exciting, and definitely not really capitalizing on mobile’s promise.

Look, the real mobile opportunity is about performance support and contextualized learning. Spaced learning is good (though not unique to mobile).  But to argue mobile’s on the rise, and it’s about content, is to misconstrue the state of the industry  and the opportunity. This is obviously a sales pitch for their mobile content delivery, but get clear about what you want from mobile. It’s a platform, so once you start people will expect more. It’s best if you need to think strategically about all that you can do and ensure you’ve seen the full picture before you settle on any one solution.

Reading List?

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I saw another query about ‘reading list recommendations’ (e.g. as an addition to Millennials, Goldfish,  Other Training Misconceptions  ;), and I thought I’d weigh in, with a different spin.  What qualifies what books should you read?  Maybe your level of expertise?  So, here is a reading list for what books should you read  depending on where you are as a designer.

Note, this is a relatively personal list, and not the mainstream ID texts. It’s not Gagné, Brown & Green, Dick & Carey, or even Horton. These are books that either get you going without those, or supplement then once you are going.  And they’re ones I know, and I can’t read  everything!

Beginning (e.g. the accidental instructional designer):

Cammy Bean’s The Accidental Instructional Designer.  Now, I think the fact that this book  needs to exist is kind of an indictment of our field. Do we have accidental surgeons?  Not to the extent we  prepare for them!  Still, it’s a reality, and Cammy’s done the field a real service in this supremely practical and  accessible book.

Michael Allen’s Guide to eLearning. Michael’s got the scientific credibility, the practical experience, a commitment to making things right, and a real knack for simplifying things. This book, with it’s SAM and CCAF framework, provides a very good go-to-whoa process for designing learning experiences what will work.

Practicing Designer:

Julie Dirksen’s  Design for How People Learn is a really accessible introduction to learning science, boiling it down into practical terms as a process for design.  With great illustrations, it’s an easy but important read.

Donald Norman’s  Design of Everyday Things  is pretty much key reading for  anyone who designs for people. (OK, so I’m biased, because he was my Ph.D. adviser,  but  I’m not the only one who says so.) Not specific to learning, but one of those rare books that is pretty much guaranteed to change the way you look at the world.

Going deeper:

Brown, Roediger, & McDaniel’s  Make it Stick. 10 points from learning science about what works.

Ericsson’s  Peak, a book about what makes real expertise, with a focus on the nuances of  deliberate practice.

Patti Shank’s new  Make it Learnable series gets into specifics on learning design. Comprehensive and yet accessible.

Ruth Clark’s  eLearning & The Science of Instruction (with Dick Mayer) and/or  Efficiency in Learning  with Sweller & Nguyen).

Of course, there are separate topics:

Mobile: my own  Designing mLearning  and anything  by Chad Udell  (e.g.  Learning Everywhere)

Games:  my own  Engaging Learning  and anything game from Karl Kapp (e.g. the new book with Sharon Boller, Play to Learn).

Realities:  Koreen Pagano’s  Immersive Learning, and perhaps Kapp & O’Driscoll’s Learning in 3D as a foundation.

Performance Support: Allison Rossett’s Job Aids & Performance Support  and Gottfredson & Mosher’s  Innovative  Performance Support.  

Social: Conner & Bingham’s  The New  Social Learning and Jane Bozarth’s Social  Media for Trainers.

Going Broader:

Informal:  Jay Cross’  Informal Learning.  Talking about the rest of learning besides formal.

Performance Ecosystem: Marc Rosenberg’s  Beyond eLearning  (the start), and/or  my  Revolutionize Learning & Development.  About L&D strategy; going beyond just courses to meet the real needs of the org.

Going Really Deep (if you really want to geek out on learning and cognitive science):

Daniel Kahnemann’s  Thinking Fast and Slow about how our brains don’t work logically. Or the behavioral economics stuff.

Andy Clark’s  Being There about the newer views on cognition including situated cognition.

Of course, there’re lots more, depending on whether you’re interested in assessment, evaluation, content, or more. But this is my personal and idiosyncratic set of recommendations. There are other people I’d point you to, too, but this is the suite of books you can, and should, get your mitts on. Now, what’s on  your list?

 

 

The ITA Jay Cross Memorial Award for 2018: Mark Britz

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In honor of the colleague, mentor, and friend that brought us together, every year the Internet Time Alliance presents the Jay Cross Memorial Award. The award is for an individual who represents the spirit of continuing informal learning for the workplace. This year, Mark Britz is the deserving recipient.

Jay was a fierce champion of social and informal learning. He saw that most of how we learn to do what we do comes from interacting with others.  As a response to his untimely passing, the remaining members of the ITA decided to honor his memory with an award.  Jane Hart, Harold Jarche, Charles Jennings, & myself each year collectively decide an individual who we think best reflects Jay’s vision. And we announce the recipient on the 5th of July, Jay’s birthday.

Mark has resonated and amplified the message of ongoing learning since we first crossed paths. He has interacted with the ITA members regularly via tweets, blogs, and in person when possible.  And we’ve appreciated his engagement with the ideas and his contributions to our thinking.

I got to know Mark’s thinking a bit better when he wrote a case study based upon his work at Systems Made Simple for the Revolution book (Jay wrote the foreword).  And he’s continued to blog about workplace learning at The Simple Shift with short but insightful posts. Currently part of the team running events for the eLearning Guild, Mark manages to consistently touts views that illuminate thinking about the new workplace.

The situation he cites in that case study is exemplary of this type of thinking. Charged with starting a corporate ‘university’ in an organization that was composed of many experts, he knew that ‘courses’ weren’t going to be a viable approach. Instead, he championed and built a social network that pulled these experts together to share voices. The core L&D role was one of facilitating communication and collaboration, rather than presenting information.

For his continuing work promoting communication, collaboration, and continual learning, we recognize Mark’s efforts with the 2018 Internet Time Alliance Jay Cross Memorial Award.

 

 

Microlearning Malarkey

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Someone pointed me to a microlearning post, wondering if I agreed with their somewhat skeptical take on the article. And I did agree with the skepticism.  Further, it referenced another site with worse implications. And I think it’s instructive to take these apart.  They are emblematic of the type of thing we see too often, and it’s worth digging in. We need to stop this sort of malarkey. (And I don’t mean microlearning as a whole, that’s another issue; it’s articles like this one that I’m complaining about.)

The article starts out defining microlearning as small bite-sized chunks. Specifically: “learning that has been designed from the bottom up to be consumed in shorter modules.” Well, yes, that’s one of the definitions.  To be clear, that’s the ‘spaced learning’ definition of microlearning. Why not just call it ‘spaced learning’?  

It goes on to say “each chunk lasts no more than five-then minutes.” (I think they mean 10). Why? Because attention. Um, er, no.  I like JD Dillon‘s explanation:  it needs to be as long as it needs to be, and no longer.

That attention explanation?  It went right to the ‘span of a goldfish’. Sorry, that’s debunked (for instance, here ;).  That data wasn’t from Microsoft, it came from a secondary service who got it from a study on web pages. Which could be due to faster pages, greater experience, other explanations. But not a change in our attention (evolution doesn’t happen that fast and attention is too complex for such a simple assessment).  In short, the original study has been misinterpreted. So, no, this isn’t a good basis for anything having to do with learning. (And I challenge you to find a study determining the actual attention span of a goldfish.)

But wait, there’s more!  There’s an example using the ‘youtube’ explanation of microlearning. OK, but that’s the ‘performance support’ definition of microlearning, not the ‘spaced learning’ one. They’re two different things!  Again, we should be clear about which one we’re talking about, and then be clear about the constraints that make it valid. Here? Not happening.  

The article goes on to cite a bunch of facts from the Journal of Applied Psychology. That’s a legitimate source. But they’re not pulling all the stats from that, they’re citing a secondary site (see above) and it’s full of, er, malarkey.  Let’s see…

That secondary site is pulling together statistics in ways that are  thoroughly dubious. It starts citing the journal for one piece of data, that’s a reasonable effect (17% improvement for chunking). But then it goes awry.  For one, it claims playing to learner preferences is a good idea, but the evidence is that learners don’t have good insight into their own learning. There’s a claim of 50% engagement improvement, but that’s a mismanipulation of the data where 50% of people would like smaller courses. That doesn’t mean you’ll get 50% improvement. They also make a different claim about appropriate length than the one above – 3-7 minutes – but their argument is unsound too. It sounds quantitative, but it’s misleading. They throw in the millennial myth, too, just for good measure.

Back to the original article, it cites a figure not on the secondary site, but listed in the same bullet list: “One minute of video content was found to be equal to about 1.8 million written words”.  WHAT?  That’s just ridiculous.  1.8 MILLION?!?!?  Found by who?  Of course, there’s no reference. And the mistakes go on. The other two bullet points aren’t from that secondary site either, and also don’t have cites.  The reference, however could mislead you to believe that the rest of the statistics were also from the journal!

Overall, I’m grateful to the correspondent who pointed me to the article. It’s hype like both of these that mislead our field, undermine our credibility, and waste our resources. And it makes it hard for those trying to sell legitimate services within the boundaries of science.  It’s important to call this sort of manipulation out.  Let’s stop the malarkey, and get smart about what we’re doing and why.