Archives for 2015

I recently opined that good learning design was complex, really perhaps close to rocket science.  And I suggested that a consequent problem was that the nuances are subtle.  It occurs to me that perhaps discussing some example problems will help make this point more clear.

Without being exhaustive, there are several consistent problems I see in the elearning content I review:

• The wrong focus. Seriously, the outcomes for the class aren’t meaningful!  They are about information or knowledge, not skill.  Which leads to no meaningful change in behavior, and more importantly, in outcomes. I don’t want to learn about X, I want to learn how to  do  X!
• Lack of motivating introductions.  People are expected to give a hoot  about this information, but no one helps them understand why it’s important?  Learners should be assisted to viscerally ‘get’ why this is important,  and helped to see how it connects to the rest of the world.  Instead we get some boring drone about how this is really important.  Connect it to the world and let me see the context!
• Information focused or arbitrary content presentations. To get the type of flexible problem-solving organizations need, people need mental models about why  and how  to do it this way, not just the rote steps.  Yet too often I see arbitrary lists of information accompanied  by a rote knowledge test.  As if that’s gonna stick.
• A lack of examples, or trivial ones.  Examples need to show a context, the barriers, and how the content model provides guidance about how to succeed (and when it won’t).  Instead we get fluffy stories that don’t connect to the model and show the application to the context.  Which means it’s not going to support transfer (and if you don’t know what I’m talking about, you’re not ready to be doing design)!
• Meaningless and insufficient practice.  Instead of asking learners to make decisions like they will be making in the workplace (and this is my hint for the  first  thing to focus on fixing), we ask rote knowledge questions. Which isn’t going to make a bit of difference.
• Nonsensical alternatives to the right answer.  I regularly ask of audiences “how many of you have ever taken a quiz where the alternatives to the right answer are so silly or dumb that you didn’t need to know anything to pass?”  And  everyone raises their hand.  What possible benefit does that have?  It insults the learner’s intelligence, it wastes their time, and it has no impact on learning.
• Undistinguished feedback. Even if you do have an alternative that’s aligned with a misconception, it seems like there’s an industry-wide conspiracy to ensure that there’s only one response for all the wrong answers. If you’ve discriminated meaningful differences to the right answer based upon how they go wrong, you should be addressing them individually.

The list goes on.  Further, any one of these can severely impact the learning outcomes, and I typically see  all of these!

These are really  just the flip side of the elements of good design I’ve touted in previous posts (such as this series).  I mean, when I look at most elearning content, it’s like the authors have no idea how we really learn, how our brains work.  Would you design a tire for a car without knowing how one works?  Would you design a cover for a computer without knowing what it looks like?  Yet it appears that’s what we’re doing in most elearning. And it’s time to put a stop to it.  As a first step, have a look at the Serious eLearning Manifesto, specifically the 22 design principles.

Let me be clear, this is just the surface.  Again, learning engineering is complex stuff.  We’ve hardly touched on engagement, spacing, and more.    This may seem like a lot, but this is really the boiled-down version!  If it’s too much, you’re in the wrong job.

Yesterday I went off about how learning design should be done right and it’s not easy.  In a conversation two days ago, I was talking to a group that was  supporting several initiatives in adaptive learning, and I wondered if this was a good idea.

Adaptive learning is  desirable.  If learners come from different initial abilities, learn at different rates, and have different availability, the learning should adapt.  It should skip things you already know, work at your pace, and provide extra practice if the learning experience is extended.  (And, BTW, I’m  not talking learning styles).  And this is worthwhile,  if the content you are starting  with is good.  And even then, is it really necessary. To explain, here’s an analogy:

I have heard it said that the innovations for the latest drugs should be, in many cases, unnecessary. The extra costs (and profits for the drug companies) wouldn’t be necessary. The claim is that the new drugs aren’t any more effective than the existing treatments  if they were used properly.  The point being that people don’t take the drugs as prescribed (being irregular,  missing, not continuing past the point they feel better, etc), and if they did the new drugs wouldn’t be as good.  (As a side note, it would appear that focusing on improving patient drug taking protocols would be a sound strategy, such as using a mobile app.)  This isn’t true in all cases, but even in some it makes a point.

The analogy here is that using all the fancy capabilities: tarted up templates for simple questions, 3D virtual worlds, even adaptive learning, might not be needed if we did better learning design!  Now, that’s not to say we couldn’t add value with using the right technology at the right points, but as I’ve quipped in the past: if you get the design right, there are  lots of ways to implement it.  And, as a corollary, if you don’t get the design right, it doesn’t matter how you implement it.

We do need to work on improving our learning design, first, rather than worrying about the latest shiny objects. Don’t get me wrong, I  love  the shiny objects, but that’s with the assumption that we’re getting the basics right.  That was my assumption ’til I hit the real world and found out what’s happening. So let’s please get the basics right, and then worry about leveraging the technology on  top of a strong foundation.

As I’ve been working with the Foundation over the past 6 months I’ve had the occasion to review a wide variety of elearning, more specifically in the vocational and education space, but my experience mirrors that from the corporate space: most of it isn’t very good.  I realize that’s a harsh pronouncement, but I fear that it’s all too true; most of the elearning I see will have very little impact.  And I’m becoming ever more convinced that what I’ve quipped  in the past is true:

Quality design is hard to distinguish from well-produced but under-designed content.

And here’s the thing: I’m beginning to think that this is not just a problem with the vendors, tools, etc., but that it’s more fundamental.  Let me elaborate.

There’s a continual problem of bad elearning, and yet I hear people lauding certain examples, awards are granted, tools are touted, and processes promoted.  Yet what I see really isn’t that good. Sure, there are exceptions, but that’s the problem, they’re exceptions!  And while I (and others, including the instigators of the Serious eLearning Manifesto) try to raise the bar, it seems to be an uphill fight.

Good learning design is rigorous. There’re some significant effort just getting the right objectives, e.g. finding the  right  SME, working with them and not taking what they say verbatim, etc.  Then working to establish the right model and communicating it, making meaningful practice, using media correctly.  At the same time, successfully fending off the forces of fable (learning styles, generations, etc).

So, when it comes to the standard  tradeoff    –  fast, cheap, or good, pick two – we’re ignoring ‘good’.  And  I think a fundamental problem is  that everyone ‘knows’  what learning is, and they’re not being astute consumers.  If it looks good, presents content, has some interaction, and some assessment, it’s learning, right?  NOT!  But stakeholders don’t know, we don’t worry enough about quality in our metrics (quantity per time is not a quality metric), and we don’t invest enough in learning.

I’m reminded of a thesis that says medicos reengineered their status in society consciously.  They went from being thought of ‘quacks’ and ‘sawbones’ to an almost reverential status today by a process of making the process of becoming a doctor quite rigorous.  I’m tempted to suggest that we need to do the same thing.

Good learning design is complex.  People don’t have predictable properties as does concrete.  Understanding the necessary distinctions to do the right things is complex.  Executing the processes to successfully design, refine, and deliver a learning experience that leads to an outcome is a complicated engineering endeavor.  Maybe we do have to treat it like rocket science.

Creating learning should be considered a highly valuable outcome: you are helping people achieve their goals.  But if you really aren’t, you’re perpetrating malpractice!  I’m getting stroppy, I realize, but it’s only because I care and I’m concerned.  We have  got to raise our game, and I’m seriously concerned with the perception of our work, our own knowledge, and our associated processes.

If you agree, (and if you don’t, please do let me know in the comments),  here’s my very serious question because I’m running out of ideas: how do we get awareness of the nuances of good learning design out there?