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Following on my thoughts on writing yesterday, this was a topic that didn’t fit (the post got too long ;).  So here we go..  Colleagues have written that citations are important. If you’re making a claim, you should be able to back it up. On the other hand, if you’re citing what you think is ‘received wisdom’, do you need to bother?  Pondering…

Now, citations can interfere with the flow, I believe. If not the reading, they can interfere with the flow of my writing! (And, I’ve been accused of ‘name dropping‘, where instead I believe it’s important to both acknowledge prior work and show that you know what’s been done.) Still, it’s important to know what to cite, and when.

I admit that I don’t always cite the claims I make. Because, I take it as a given.  I may say something like “we know” or otherwise presume that what I’m saying is accepted premise. One problem, of course, is that I don’t know what others know (and don’t). And, of course, that this isn’t an official article source, this is my blog ;). Still, when I’m talking about something new to me (like thoughts from books), I will cite the locus.

Articles are different. When I write those, I try to provide sources. In both cases I generally don’t go to the extent of journal article links, because I’m not expect that folks have easy access to them, and so prefer to cite more commonly available resources, like books that have ‘digested’ the research.

And when I write ‘take down’ articles, I don’t cite the offender. It’s to make the point, not shame anyone. If you’re really curious, I’m sure you can track it down.

And, realize I don’t have easy access to journals either. Not affiliated with an institution, I don’t have access to the original articles behind a pay wall. I tend to depend on people who summarize including books and articles that summarize. Still, I’ve a grounding for over a decade in the original materials and am able to make inferences. And of course occasionally I’ll be wrong. Sometimes, I’ll even admit it ;).

The issue really is when do you need to make a citation. And I reckon it’s when you’re stating something that folks might disagree with. And I can’t always anticipate it. So I’ll try to consistently point to the basis for any claims I think might be arguable, or state that it’s my (NSH :) opinion.  And you can always ask!  Fair enough?

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.  

I’ve argued before that the differences between well-designed and well-produced learning, and just well-produced learning, are subtle. And, in general, nuances matter. So, in my recent book, the section on misconceptions spent a lot of time unpacking some terms. The goal there was ensuring that the nuances were understood. And a recent event triggered even more reflection on this.

Learnnovators, a company I’ve done a couple of things with (the Deeper eLearning series, and the Workplace of the Future project), interviewed me once quite a while ago. I was impressed then with the depth of their background research and thoughtful questions. And they recently asked to interview me on the book. Of course, I agreed. And again they impressed me with the depths of their questions, and I realized in this case there was something specific going on.

In their questions, they were unpacking what common concerns would be about some of the topics.  The questions dug in to ways in which people might think that the recommendations are contrary to personal experience, and more.  There were very specifically looking for ways in which folks might think to reject the findings.  And that’s important. I believe I had addressed most of them in the book, but it was worth revisiting them.

And that’s the thing that I think is important about this for our practice. We can’t just do the surface treatment. If we just say: “ok we need some content, and then let’s write a knowledge test on it”, we’ve let down our stakeholders.  If we don’t know the cognitive properties of the media we use, don’t sweat the details about feedback on assessment, don’t align the practice to the needed performance, etc., we’re not doing our job!

And I don’t mean you have to get a Ph.D. in learning science, but you really do need to know what you’re doing. Or, at least, have good checklists and quick reference guides to ensure you’re on track. Ideally, you review your processes and tools for alignment to what’s known. And the tools themselves could have support. (Ok, to a limit, I’ve seen this done to the extent of handcuffs on design.)

Nuances matter,  if you care about the outcomes (and if you don’t, why bother? ;).  I’ve been working on both a checklist and on very specific changes that apply to various places in design processes that represent the major ways folks go wrong. These problems are relatively small, and easy to fix, and are designed to yield big improvements. But unless you know what they are, you’re unlikely to have the impact you intend.

Businesses are composed of core functions, and they optimize them to succeed. In areas like finance, operations, and information technology, they prioritize investments, and look for continual improvement. But, with the shift in the competitive landscape, there‘s a gap that’s being missed. And I‘m wondering if a focus on cognitive science needs to be foregrounded.

In the old days, most people were cogs in the machine. They weren‘t counted on to be thinking, but instead a few were thinking for the many. And those who could do so were selected on that basis. But that world is gone.

Increasingly, anything that can be automated should be automated.   The differentiators for organizations are no longer on the execution of the obvious, but instead the new advantage is the ability to outthink the competition. Innovation is the new watchword.   People are becoming the competitive advantage.

However, most organizations aren‘t working in alignment with this new reality. Despite mantras like ‘human capital management’ or ‘talent development’, too many practices are in play that are contrary to what‘s known about getting the best from people. Outdated views like putting information into the head, squelching discussion, and avoiding mistakes are rife. And the solutions we apply are simplistic.

Ok, so neuroscientist John Medina  says our understanding of the brain is ‘childlike‘.   Regardless, we have considerable empirical evidence and conceptual frameworks that give us excellent advice about things like distributed, situated, and social cognition. We know about our mistakes in reasoning, and approaches to avoid making mistakes. Yet we‘re not seeing these in practice!

What I‘m suggesting is a new focus.   A new area of expertise to complement technology, business nous, financial smarts, and more.   That area is cognitive expertise. Here I’m talking about someone with organizational responsibility, and authority, to work on aligning practices and processes with what‘s known about how we think, work, and learn. A colleague suggested that L&D might make more sense in operations than in HR, but this goes further. And, I suggest, is the natural culmination of that thought.

So I‘m calling for a Chief Cognitive Officer. Someone who‘s responsibility ranges from aligning tools (read: UI/UX) with how we work, through designing continual learning experiences, to leveraging collective intelligence to support innovation and informal learning.   Doing these effectively are all linked to an understanding of how our brains operate, and having it distributed isn‘t working.  The other problem is that not having it coordinated means it‘s idiosyncratic at best.

One problem is that there‘s too little of cognitive awareness anywhere in the organization.  Where does it belong?  The people closest are (or should be) the L&D (P&D) people.  If not, what’s their role going to be?  Someone needs to own this.

Digital transformation is needed, but to do so without understanding the other half of the equation is sort of like using AI on top of bad data; you still get bad outcomes.  It’s time to do better. It’s a radical reorg, but is it a necessary change?  Obviously, I think it is. What do you think?

I sat in on a twitter chat yesterday, #DLNChat, that is a higher ed tech focused group (run by EdSurge). The topic was the link between higher ed and job skills, and I was a wee bit cynical. While I think there are great possibilities, the current state of the art leaves a lot to be desired.

So, I currently don’t think higher ed does a good job of preparation for success in business. Higher ed focuses too much on knowledge, and uses assignments that don’t resemble the job activities.  Frankly, there aren’t too many essays in most jobs!

Worse, I don’t think higher ed does a good job of developing meta-cognitive and meta-learning skills. There is little attempt to bridge assignments  across courses, so your presentations in psychology 101 and sociology 202 and business 303 aren’t steadily tracked and developed. Similarly with research projects, or strategy, or… And there’re precious little (read: none) typically found where you actually make decisions like you would need to.

And, sadly, the use of technology isn’t well stipulated either. You might use a presentation tool, a writing tool, or a spreadsheet, maybe even collaboratively, but it’s not typically tied to external resources and data.

Yes, I know there are exceptions, and it may be changing somewhat, but it still appears to be the case. Research, write a paper, take a test.

Yet the role of developing higher skills is possible and valuable.  We could be providing more meaningful assignments, integrating meta-learning layers, and developing both meaningful skills and meta-skills.

This doesn’t have to be done at the expense of the types of things professors believe are important, but just with a useful twist in the way the knowledge is applied. It might lead to a revision of the curriculum, at least somewhat, but I reckon it’d likely be for the better ;).

Our education system, both K12 and higher-ed, isn’t doing near what it could, and should. As Roger Schank says, only two things wrong: what we teach, and how we teach it.  We can do better. Will we?