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Adaptive or just good design?

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A few posts ago, I wrote  about how we might be rushing too fast into cognitive computing. Not that there’s anything wrong with augmenting us, but I was wondering if we’d be better off focusing on developing our non-cognitive systems first. And, of course, it occurred to me after a conversation that there might be another example of this ‘tech fix before smart fix’ problem: adaptive learning over good  design. Is this a tech solution to the wrong problem?

So, I’m a fan of adaptive learning. Heck, I led a team that developed an adaptive learning system back circa 2000 (ahead of the times, as always ;). And I know  that there are good things we can do with adaptive learning.  Some are still relatively impractical (e.g. intelligent tutoring systems), some make sense (e.g. adapting on learner performance),  and, of course, some are pretty silly (e.g. learning styles).  Still, done well, adaptive learning could and should be a benefit.  (And serious games are  adaptive!)

But I would posit that before you charge off for adaptive learning, you make sure you’re doing  good learning design first.  Adaptation on top of good learning design is likely to add some extra benefits, but adaptation on old learning design just doesn’t make sense.  And, I’ll suggest, good learning design is cheaper, and likely to have a bigger impact.

So, for instance, adapting a large knowledge-based course will still leave it as a problematic solution in search of a problem.  Creating a better course focusing on critical  skills with meaningful practice is going to have a bigger impact on the bottom line than adapting the course for  learner progress. It’s not a bad thing, but it’s a secondary concern, I reckon.

Games are a special case of adapting on the basis of learner performance. When well done, they’re the next best thing to live practice.  Yet, at core, they too need good design.

There are a lot of adaptive solutions emerging, with a strong push to optimize your outcomes.  Some of them have a pretty good basis, too. But your goal is to achieve business impact, and what will hit that first, and best, is starting with good design.  Adaptive isn’t a panacea, it’s a fillip to  design, not a replacement.    Master the rules of good design, then come back and add in those extra elements, whether adaptivity and/or game mechanics.   Please?

Microdesign

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There’s been a lot of talk about microlearning of late – definitions, calls for clarity, value propositions, etc – and I have to say that I’m afraid some of it (not what I’ve linked to) is a wee bit facile. Or, at least, conceptually unclear.  And I think that’s a problem. This came up again in a recent conversation, and I had a further thought (which of course I have to blog about ;).  It’s about how to do microdesign, that is,  how  to  design micro learning. And it’s not trivial.

VirusSo one of the common views of micro learning is that it’s just in time. That is, if you need to know how to do something, you look it up.  And that’s just fine (as I’ve recently ranted). But it’s not  learning. (In short: it’ll help you in the moment, but unless  you design it to support learning, it’s performance support instead).  You can call it Just In Time support, or microsupport,  but properly, it’s not micro learning.

The other notion is a learning that’s distributed over time. And that’s good.  But this takes a bit more thought. Think about it. If we want to systematically develop somebody over time, it’s not just a steady stream of ‘stuff’.  Ideally, it’s designed to optimally get there, minimizing the time taken on the part of the learner, and yet yield reliable improvements.  And  this is complex.

In principle, it should be a steady  development, that reactivates and extends learners capabilities in systematic ways. So, you still need your design steps, but you have to think about granularity, forgetting, reactivation, and development in a more fine-grained way.  What’s the minimum  launch?  Can you do ought but make sure there’s an initial intro, concept, example, and a first practice?  Then, how much do we need to reactivate versus how much do we have to expand the capability in each iteration? How much is enough?  As Will Thalheimer says in his spaced learning report,  the amount and duration of spacing depends on the complexity of the task and the frequency with which it’s performed.

When do you provide more practice, versus another example, versus a different model?  What’s the appropriate gap in complexity?  We’ll likely have to make our best guesses and tune, but we have to think consciously about it.  Just chunking up an existing course into smaller bits isn’t taking the decay of memory over time and the gradual expansion of capability. We have to design an experience!

Microlearning is the right thing to do, given our cognitive architecture. Only so much ‘strengthening’ of the links  can happen in any one day, so to develop a full new capability will take time. And that means small bits over time makes sense. But choosing the right bits, the right frequency, the right duration,  and the right ramp up in complexity, is non-trivial.  So let’s laud the movement, but not delude ourselves either that performance support  or a stream of content is learning. Learning, that is systematically changing the reliable behavior of the most complex thing in the known universe, is inherently complex.  We should take it seriously, and we can.

Learning Design Insights

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I attended a recent Meetup of the Bay Area Learning Design & Technology, and it led to some insights. As context, this is a group that meets in the evening maybe once or every other month or so.  It’s composed of students or new graduates as well as experienced-practitioners. The topic was Themes from a  Hat  (topics are polled and then separate discussions are held). I was tapped to host the Learning Design conversation (there were three others: LMS, Measurement, and Social Learning), and that meant that a subset of the group sat in on the discussion. We had four separate discussions for each group, so everyone had a chance to discuss every topic (except us topic hosts ;).

I’d chosen to start with 3 or four questions to prompt discussion:

  • What is good learning design?
  • Are you doing good learning design?
  • What are the barriers to good learning design?
  • What can we do to improve learning design?

In each case, we never got beyond the first question!  However, in the course of the discussions, we ended up talking quite a bit about the others.  I confess that I’m a just a wee bit opinionated and a stickler for conceptual clarity, so I probably spoke  too much about important distinctions.  Yet  there were also some valuable insights from the group.

First, it was a great group: enthusiastic, with a wide range of experience and backgrounds.  Folks had come into the field from different areas, everything from neuroscience to rabbinical practice!  And there were new students still in a Master’s program, job seekers, and those who were active in work.  Everyone contributed.  While it meant missing #lrnchat, it was worthwhile  to have a different experience.  And everyone was kind enough to understood when I had to have my knee up as rehab (thanks!).

The responses to the first question were very interesting: what is good learning design?  While most everyone talked about features of the experience, we also were talking  both the outcome  and the process.  There even emerged a discussion about what learning was.  I offered  the traditional (behaviorist) description: a change in behavior in the same context, e.g. responding in a different (and presumably better) way.  I also mentioned my usual: learning is action and reflection; instruction is  designed  action and  guided reflection.

One element that appeared in all four groups was ‘engaging’.  Exactly that word. (Only once did I feel compelled to mention that Engaging Learning  was the title of my first book! ;)  There were other terms that encompassed it, including ‘experience’, ‘stimulating’, and ‘motivating’.  I was pleased to see the recognition of the  value! To define it, discussion several times ranged across  things like challenging practice and making it meaningful to learners.

Another element that reoccurred was ‘memorable’. It seemed  what was meant was ‘retention’ (over time until needed) rather than the learning experience was worth recalling. This did bring up a discussion of what led to retention and a discussion of spaced learning.  That is, the fact that our brains can only strengthen associations so much in one day before sleep is needed. Slow learning.  Reactivation.

That same discussion came up with another repeated term: micro learning.  There appeared to be  little  differentiation  between different interpretations of that term, so I made distinctions (as one does ;).  People too often use the term micro learning to mean looking something up just when needed  (such as a video about how to do something).  And that’s  valuable.  Yet  it can  lead to successful performance in the moment without any  learning (e.g. forgotten shortly thereafter). Which is fine, but it’s not learning! Microlearning  might be some very small thing that can be learned right in the moment, but I reckon those are rare. What I really think micro learning could and should be is for spaced learning.  I think that to do that successfully is a non-trivial exercise, by the way.

We covered other topics about design, too.  In at least one group we talked about SME limitations and how to work with them.  We also talked about the  benefits of collaboration, and knowing your audience. And engaging the audience, making the learning meaningful to them  and the organization. Minimalism came up in several different ways as well, not wasting the learner’s time.

One question had arisen in discussion with colleagues, and I took the opportunity in a couple groups to ask about their design practices. The question was how frequent was the process of giving a course demand to a designer and having them work alone from go to whoa.  It varied, but it seemed like there was some of that, there was also a fair bit of both collaboration at least at certain points, and some iterative testing. This was heartening to hear!  Doing  performance consulting and meaningful measurement, however, did appear somewhat challenging.

Overall, there’s an opportunity for some deeper science behind elearning, yet  I was very heartened by the enthusiasm and that the design processes weren’t as ‘solitary waterfall’ as I feared. So, who’s up for a deeper learning science workshop?  ;)

 

Improving design processes

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Recently, I had a chance to catch up with a client who’d used my services to review their design processes. Per my approach, I’d generated a report with a large number of suggestions. What happened, not surprisingly, is that a subset  of them actually were implemented.  Still, it was gratifying to hear of the changes, and I think they’re worth exploring as an opportunity to show how small changes can yield big improvements.

One of the major areas was to work on how they use SMEs. Instead of just having a contracted expert, they’re moving to work with folks who have ‘on the ground’ expertise to couple with their domain expertise.  I argue for triangulating on the real objectives with several perspectives, and this approaches that ideal.

A second thing was that there was a bit of a ‘waterfall model’, and instead I suggest having collaboration at critical  points along the way. In this case, they have  moved to more collaboration at an important juncture point, with more roles involved to be more innovative on the possibilities.

Also, in their particular case, they have to abide by certain constraints, such as amount of time.  As a result of looking at the opportunities, they are  moving to meeting their requirements by adding more practice, not more content.  This is a big win for the learners, and the learning.

They are  also looking at applying their refined understanding of the nuances of learning. This is embryonic, I was told, but they are moving to looking to redesigning their content to better align with what is known about learning science. At this point it may not be instituted in their processes, but it’s already affecting the mindset they bring to the task.

There are a couple of other things they’re beginning, but I reckon these are some  big wins for their audience and the outcomes. With only small changes in what they are doing, they are increasing the likelihood of effective  learning.  And that’s the point: for any design process, there are inflection points where better outcomes can be achieved with minimal impact on the overall processes. That is, the processes may change, but they’re different, not hugely larger.

There’s much we can and should be doing to improve our learning design processes, for our learners, and the learning. We know what the opportunities are, now we just need to marshal the will to make changes.  Are you ready?

Thoughts on Learning Design Strategy

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learning design strategy questionsAt the DevLearn conference, I ran a Morning Buzz on Learning Design Strategy. I’m happy to say that the participants threw in lots of ideas, and I thought they were worth capturing. I started with a set of questions to address, so I’ll go through their comments in roughly that order (though we didn’t exactly follow this structure):

What  is learning design strategy?

I had in mind the approach taken by an organization to their learning design.  Attendees suggested it’s your goals and approach, ensuring you are delivering effectively.  It’s also your review approach, and metrics.  These are all elements that indeed contribute to strategy.

What gaps are we seeing in  learning design strategy?

The participants  offered up a suite of places that were problems, including aligning with organizational goals and access to support measuring impact, both of which are indeed strategic issues.  They also raised problems with prioritization of the demands, the need to move beyond just courses, and the  lack of learning design knowledge. All are real problems.

What do we need to be able to improve?

The audience offered up a number of suggestions.  For one, there was a desire for strategies (probably more tactics) for doing beyond ‘the event’.  Support for selling changes in the way of doing things was mentioned as well.  The shift to self-learning was mentioned, leading to concern over how to support this.  Attendees also mentioned a need of awareness in designing ‘backwards‘. Finally, a culture of learning was expressly discussed.

What are possible solutions?

The participants  offered a suite of suggestions. One was adopting a learn-apply-perform model, which another termed a learn-practice-demo. Both were getting at the need for active practice and an ability to actually demonstrate performance.  There was also a mention of looking to social networks and peer recommendations to lower the demand and facilitate self-learning.  A culture shift was suggested, supported by the methods used to teach! A final solution was to move quickly to mentoring, which implicitly suggests including mentoring  in the design.

Steps to take to move forward?

I also wanted to know what how they might move forward, and what they needed.  Two clear suggestions emerged.  One was for examples, and I reckon both of better learning designs, and approaches to implement those learning designs in organizations.  The other was for tools. Here it was clear that they weren’t talking about tools to develop learning, but tools to support them doing good design, and following processes.

At the end I left with mixed feelings. It’s good to know that the problems I see are reflected in what the practitioners reports; we see the same problems  It’s also sad that these problems exist.  I do believe that the Serious eLearning Manifesto is one piece of support.  And I’ve written on practices (e.g. with SMEs), but it’s clear that some practical scaffolding would help. I’ve worked with a few organizations, but I’m struggling to find ways to help more.  (Maybe this is the topic of my next book?)  So, what ideas do  you  have?

(I’m offering a webinar next week that will address these issues, if you’re serious about making changes.)

Special Webinar on Learning Design Strategy

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Learning, properly, should have an impact. It’s about systematically changing behavior, developing new skills to meet ever-changing needs. That’s why we invest in learning: training or elearning.  If elearning doesn‘t make an impact,  who cares how accessible or affordable is seems? It‘s actually undermining your goals for increasing expertise, effectiveness and productivity.

Too much of what is done under this umbrella isn’t sufficient. It’s quite simply not effective. Here’re some signs that your elearning might not be working:

  • Your learning unit develops courses on demand
  • You work from PDFs and PPTs to develop your course
  • You have a knowledge quiz at the end
  • You use libraries to add graphics & interactions
  • Your learners avoid the courses
  • You track completion
  • You evaluate impact by learner feedback

burning moneyIf you’re spending money to develop elearning, and it has any of the above features, there’s a strong chance you’re burning  money.

The good news is that it’s not as  hard to change as you think!  The design processes you are using now, the ones that reflect the above issues, are not that far removed from ones that offer real outcomes.  Yes, there are changes, but they’re changes within the process, not fundamental. You can be making changes that will make a marginal impact on the development measures, but a real impact on the learning outcomes.  It’s not trivial, but it is doable.

If this is of interest, I’m offering a free webinar to talk through the issues. It’s not for everyone: if you don’t have the authority or the resources to make a change, there are other posts that talk through the opportunities.  This webinar is for those who really want to explore the possibilities. If that’s something you want to be thinking about, if you’d really like to consider consider how you get from here to there, I encourage you to  keep reading.

Webinar: 7 Unbelievable eLearning Mistakes

Date: December 7

Time: 10 AM to 11AM Pacific

Via: Zoom Conference Service

Have you been concerned about your learning design: whether your designs are actually producing results? Ultimately, is your elearning changing behaviors, developing skills, and increasing capacity? And how do you know?  There are a lot of reasons to believe that most elearning is not delivering on the promise. And yet elearning has the potential to be a powerful tool for organizational excellence. The barriers are not unsurmountable; we know the problems, and steps to change.  However, as has been said: “When all is said and done, more is said than done.” I want to give you the chance to take the steps. In this complimentary webinar we‘ll explore barriers to getting measurable results from elearning.

This isn’t your usual webinar, however. Here we are specifically talking to organizations that want their elearning to actually have an impact. If you don’t have the resources and position to make a change, this really isn’t for you. If you want your organization to take it more seriously, invite your boss ;).

This is for you, if:

  • You’re ready to look at your elearning with a serious eye
  • You want to ensure that you are getting value for your investment
  • You need to operate in the real world, under real constraints
  • You’re willing to invest for a real change that has impact

This isn’t for you if:

  • You are happy with the status quo
  • You haven’t the authority or the resources to make a change

If you are ready to take a serious look at your elearning,  I invite you to sign up.   There’s a limit to how many can attend, so please register early. When you register I’ll send you the necessary details. Hope to see you!

The webinar was run on schedule, and signups are now closed.

Deeper Design: Working out Loud and the Future of Work

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Over the past year, I’ve been working on a project.  After I wrote the Deeper eLearning series of 6 posts with Learnnovators, we wondered what to do next.  We decided to do a course together, free-to-air, and write about the process as well  (a bit of Working Out Loud), with the  intention was to try to do deep design on a pragmatic basis.  And, just as a hint, the topic is the Future of Work, the choice  of which is
part of the story. It’s a tribute to our late friend and colleague, Jay Cross, with the assistance of my colleagues in  the Internet Time Alliance.

learnnovators course design example

Well, that goal was accomplished.  First,  there are four articles talking about the design, that Learning Solutions magazine was kind enough to host:

The first post  talks about our initial plans, and how we settled on a topic.

The second post talks about our initial design decisions, scoping the overall course.

The third post talks about our detailed design decisions.

And the fourth post talks about our development process.

We intend a fifth post talking about what we learn  after the release!

and now there’s also  a press release that provides a  link to the course.  There’s an opportunity at the end of the course to leave some thoughts and comments, if you go through it (it’s designed for 20-30 minutes).

And, of course, if you do go through and want to talk about it, you can comment on the posts or here.  I welcome your thoughts!

Levels of Design

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In a recent conversation, we were talking  about the Kirkpatrick model, and a colleague  had an interesting perspective that hadn‘t really struck me overtly. Kirkpatrick is widely (not widely enough, and wrongly) used as an evaluation tool, but he talked about using it as a design tool, and that perspective made clear for me a problem with our approaches.

So, there‘s a lot of debate about the Kirkpatrick model, whether it helps or hinders the movement towards good learning. I think it‘s misrepresented (including by its own progenitors, though they‘re working on that ;), and while I‘m open to new tools I think it does a nice job of framing a fairly simple but important idea. The goal is to start with the end in mind.

And the evidence is that it‘s not being used well. The largest implementation of the model is level 1, which isn‘t of use (correlation between learner reaction and actual impact is .09, essentially zero with a rounding error). Level 2 drops to a third of orgs, and it drops from there. And this is broken.

The point, and this is emphasized by the ‘design‘ perspective, is that you are supposed to start with level 4, and work back. What‘s the measurable indicator in the organization that isn‘t up to snuff, and what behavior (level 3) would likely impact that? And how do we change that behavior (Level 2)? And here‘s where it can go beyond training: that intervention might be a job aid, or access to a network (which hasn‘t been much in the promotion of the model).

To be fair, the proponents do argue you should be starting at Level 4, but with the numbering (which Don admits he might have got wrong) and the emphasis on evaluation, it doesn‘t hit you up front. Using it as a design tool, however, would emphasize the point.

So here‘s to thinking of learning design as working backwards from a problem, not forwards from a request. And, of course, to better learning design overall.

Designing mLearning in Korean

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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 ;).

DesigningmLearningKorean

Designing Learning Like Professionals

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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.