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Clark Quinn’s Learnings about Learning

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How do you drive yourself?

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How do I drive myself? I was asked that in a coaching session. The question is asking how I keep learning. There are multiple answers, which I’ve probably talked about before, but I’ll reflect here. I think it’s important to regularly ask: “how do you drive yourself?”

As it’s the end of the year, my conversant was looking at professional development. It’s the time to ask for next year’s opportunities, and the individual was breaking out of our usual conversation to talk about this topic. And so he asked me what  I  did.

And my first response, which I’ve practiced consciously at least since grad school, is that I accept challenges. That is, I take on tasks that stretch me. (It might be that ‘sucker’ tattoo on my forehead, but note that my philanthropic bandwidth is pretty stretched. ;). This is professionally  and personally.

That is, I look to find challenges that I think are within my reach, but not already my grasp. Or, to put it another way, in my Zone of Proximal Development. Accepting assignments or engagements where, with effort, I can succeed,  but it’s not guaranteed.

Which means, of course, that there’s risk as well. Occasionally, I do screw up. Which I  really really hate to do. Which is a driver for me to push out of my comfort zone and succeed. Or, at least, learn the lesson.

There’s more, of course. One thing I did started with my first Palm Pilot (the Palm III, the accompanying case is still my toiletry bag!).  I had to justify to myself the expense, so I made sure that I really used it to success. This was part of the driver of the thinking that showed up in Designing mLearning,  how to complement cognition. IA instead of AI, so to speak.

I also live the mantra “stay curious, my friends”. I’m still all too easily distracted by a new idea, but I don’t think that’s a bad thing. Well, as long as it’s balanced with executing against the challenges.

That’s how I drive myself. So, how do you drive yourself?

Direct Instruction and Learning Experience Design

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After my previous article on direct instruction versus guided discovery, some discussion mentioned Engelmann’s Direct Instruction (DI). And, something again pointed me to the most comprehensive survey of educational effects. So, I tracked both of these down, and found some interesting results that both supported, and confounded, my learning. Ultimately, of course, it expanded my understanding, which is always my desire. So it’s time to think a bit deeper about Direct Instruction and Learning Experience Design.

Engelmann’s Direct Instruction is very scripted. It is rigorous in its goals, and has a high amount of responses from learners.  Empirically, DI has great success, with some complaints about lack of teacher flexibility. It strikes me as very good for developing core skills like reading and maths.  I was worried about the intersection of many responses a minute and more complex tasks, though it appears that’s an issue that has been addressed. I couldn’t find the paper that makes that case, however.

Another direction, however, proved fruitful.  John Hattie, an educational researcher, collected and conducted reviews of 800+ meta-analyses to look at what worked (and didn’t) in education.  It’s a monumental work, collected in his book Visible Learning. I’d heard of it before, but hadn’t tracked it down. It was time.

And it’s impressive in breadth  and depth.  This is arguably the single most important work in education. And it opened my eyes in several ways.  To illustrate, let me collect for you the top (>.4)  impacts found, which have some really interesting implications:

  • Reciprocal teaching (.74)
  • Providing feedback (.72)
  • Teaching student self-verbalization (.67)
  • Meta-cognition strategies (.67)
  • Direction instruction (.59)
  • Mastery learning (.57)
  • Goals-challenging (.56)
  • Frequent/effects of testing (.46)
  • Behavioral organizers (.41)

Reciprocal teaching and meta-cognition strategies coming out highly, a great outcome. And of course I am not surprised to see the importance of feedback. I have to say that I  was surprised to see direct instruction and mastery learning coming out so high.  So what’s going on?  It’s related to what I mentioned in the afore-mentioned article, about just what the definition of DI is.

So, Hattie says: …”what the critics mean by direct instruction is didactic teacher-led talking from the front…” And, indeed, that’s my fear of using the label. He goes on to point out the major steps of DI (in my words):

  1. Have clear learning objectives: what should the learner be able to  do?
  2. Clear success criteria (which to me is part of 1)
  3. Engagement: an emotional ‘hook’
  4. A clear pedagogy: info (models & examples), modeling, checking for understanding
  5. Guided practice
  6. Closure of the learning experience
  7. Reactivation: spaced and varied practice

And, of course, this is pretty much everything I argue for as being key to successful learning experience design. And, as I suspected, DI is not what the label would lead you to believe (which I  do think is a problem).  As I mentioned in a subsequent post, I’ve synthesized my approach across many elements, integrating the emotional elements along with effective education practice (see the alignment).  There’s so much more here, but it’s a very interesting result. Direct Instruction and Learning Experience Design have a really nice alignment.

And a perfect opportunity to remind you that I’ll be offering a Learning Experience Design workshop at DevLearn, which will include the results of my continuing investigation (over decades) to create an approach that’s doable and works. Hope to see you there!

Theory or Research?

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There’s a lot of call for evidence-based methods (as mentioned yesterday): L&D, learning design, and more. And this is a good thing. But…do you want to be basing your steps on a particular empirical study, or the framework within which that study emerged? Let me make the case for one approach. My answer to theory or research is theory. Here’s why.

Most research experiments are done in the context of a theoretical framework. For instance, the work on worked examples comes from John Sweller’s Cognitive Load theory. Ann Brown & Ann-Marie Palincsar’s experiments on reading were framed within Reciprocal Teaching, etc. Theory generates experiments which refine theory.

The individual experiments illuminate aspects of the broader perspective. Researchers tend to run experiments driven by a theory. The theory leads to a hypothesis, and then that hypothesis is testable. There  are some exploratory studies done, but typically a theoretical explanation is generated to explain the results. That explanation is then subject to further testing.

Some theories are even meta-theories! Collins & Brown’s Cognitive Apprenticeship  (a favorite) is based upon integrating several different theories, including the Reciprocal Teaching, Alan Schoenfeld’s work on examples in math, and the work of Scardemalia & Bereiter on scaffolding writing. And, of course, most theories have to account for others’ results from other frameworks if they’re empirically sound.

The approach I discuss in things like my Learning Experience Design workshops is a synthesis of theories as well. It’s an eclectic mix including the above mentioned, Cognitive Flexibility, Elaboration, ARCS, and more. If I were in a research setting, I’d be conducting experiments on engagement (pushing beyond ARCS) to test my own theories of what makes experiences as engaging and effective. Which, not coincidentally, was the research I was doing when I  was  an academic (and led to  Engaging Learning). (As well as integration of systems for a ubiquitous coaching environment, which generates many related topics.)

While individual results, such as the benefits of relearning, are valuable and easy to point to, it’s the extended body of work on topics that provides for longevity and applicability. Any one study may or may not be directly applicable to your work, but the theoretical implications give you a basis to make decisions even in situations that don’t directly map. There’s the possibility to extend to far, but it’s better than having no guidance at all.

Having theories to hand that complement each other is a principled way to design individual solutions  and design processes. Similarly for strategic work as well (Revolutionize L&D) is a similar integration of diverse elements to make a coherent whole. Knowing, and mastering, the valid and useful theories is a good basis for making organizational learning decisions. And avoiding myths!  Being able to apply them, of course, is also critical ;).

So, while they’re complementary, in the choice between theory or research I’ll point to one having more utility. Here’s to theories and those who develop and advance them!

Skating to where L&D needs to be

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“I skate to where the puck is going to be, not where it has been.” – Wayne Gretsky

This quote, over-used to the point of being a cliché, is still relevant. I was just reading Simon Terry’s amusing and insightful  post on ‘best practices’ (against them, of course), and it reminded me of this phrase. He said “Best practices are often racing to where someone used to be”, and that’s critical. And I’ve argued against best practices, and I want to go further.

So he’s right that when we’re invoking best practices, we’re taking what someone’s already done, and trying to emulate it. He argues that they’ve already probably iterated in making it work,  in their org. Also, that by the time you do, they’ve moved on. They may even have abandoned it!  Which isn’t, directly, my complaint.

My argument against best practices is that they worked for them, but their situation’s different. The practice may be antithetical to your culture. And thinking that you can just graft it on is broken. Which is kind of Simon’s point to.    And he’s right that if you do get it working, you find that the time it hass taken means it’s already out of date.

So my suggestion has been to look to best principles:  why  did it work?  Abstract out the underlying principle, and figure out how (or even whether) to instantiate that in your own organization.  You’d want to identify a gap in your way of working, search through possible principles, identify one that matches, and work to implement it.  That makes more sense.  And, of course, it should be a fix that even if it takes time, will be meaningful.

But now I want to go further. I argue for comprehending the affordances of new technology to leapfrog the stage of replicating what was done in the old. Here I’m making a similar sort of argument. What I want orgs to do is to define an optimal situation, and then work to that! Yes, I know it sounds like a fairytale, but I think it’s a defensible approach. Of course, your path there will differ from another’s (there’s no free lunch :), but if you can identify what a good state for your org would be, you can move to it. It involves incorporating many relevant principles in a coherent whole. Then you can strategize the path there from your current content.

The point is to figure out what the  right future is, and skate there, not back-filling the problems you currently have. Beyond individual principles to a coherent whole. Proactive instead of reactive. That seems to make sense to me. Of course, I realize the other old cliché, “when. you’re up to your ass in alligators”, but maybe it’s time to change the game a bit more fundamentally. Maybe you shouldn’t be in the swamp anyway?  I welcome your thoughts!

 

Redesigning Learning Design

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Of late, a lot of my work has been designing learning design. Helping orgs transition their existing design processes to ones that will actually have an impact. That is, someone’s got a learning design process, but they want to improve it. One idea, of course, is to replace it with some validated design process. Another approach, much less disruptive, is to find opportunities to fine tune the design. The idea is to find the minimal set of changes that will yield the maximal benefit. So what are the likely inflection points?  Where am I finding those spots for redesigning?  It’s about good learning.

Starting at the top, one place where organizations go wrong right off the bat is the initial analysis for a course. There’s the ‘give us a course on this’, but even if there’s a decent analysis the process can go awry. Side-stepping the big issue of performance consulting (do a reality check: is this truly a case for a course), we get into working to create the objectives. It’s about how you work with SMEs. Understanding what they can,  and can’t, do well means you have the opportunity to ensure that you get the right objectives to design to.

From there, the most meaningful and valuable step is to focus on the practice. What are you having learners  do, and how can you change that?  Helping your designers switch to good  assessment writing is going to be useful. It’s nuanced, so the questions don’t  seem that different from typical ones, but they’re much more focused for success.

Of course, to support good application of the content to develop abilities, you need the right content!  Again, getting designers to understand what the nuances of useful examples from just stories isn’t hard but rarely done. Similarly knowing why you want  models and not just presentations about the concept isn’t fully realized.

Of course, making it an emotionally compelling experience has learning impact as well. Yet too often we see the elements just juxtaposed instead of integrated. There  are systematic ways to align the engagement and the learning, but they’re not understood.

A final note is knowing when to have someone work alone, and when some collaboration will help.  It’s not a lot, but unless it happens at the right time (or happens at all) can have a valuable contribution to the quality of the outcome.

I’ve provided many resources about better learning design, from my 7 step program white paper  to  my deeper elearning series for Learnnovators.  And I’ve a white paper about redesigning as well. And, of course, if you’re interested in doing this organizationally, I’d welcome hearing from you!

One other resource will be my upcoming workshop at the Learning Solutions conference on March 25 in Orlando, where we’ll spend a day working on learning experience design, integrating engagement and learning science.  Of course, you’ll be responsible for taking the learnings back to your learning process, but you’ll have the ammunition for redesigning.  I’d welcome seeing you there!

The pain of learning

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My dad, in his last years, lost the use of his hands and most of his hearing. It seemed like he then gave up. I finally challenged him on it, and he said “when you’re in constant pain…”.  And I got it.

So, turns out I’ve a misbehaving disk in my back, and it started pressing on the nerve over the summer. Pain scales are 1-10; this ultimately got to an 8 when I was trying to walk or even stand (from my lower back down my leg to my toes). Tried physio, non-steroidal anti-inflammatories, and then a steroid pack; nope. The ‘big hammer’ option was a cortisone injection, and that happened. Better yet, it knocked it back; down to 1). Er, for some six – eight weeks, then it came back. They gave me another one sooner than they were supposed to, but it hasn’t worked (ok, it’s knocked it to a 6 on average, but…this isn’t tolerable).  And my point here isn’t that I’m looking for sympathy, but to (of course) talk about the learnings. Because, despite the physical pain, there are learnings (good and bad).

Because there’re a physiological basis (pressing on the nerve), I’ve stuck with treatments likely to minimize the inflammation. I haven’t looked at a chiropractor nor acupuncture. Given that the current approaches are failing, those may come up, though I’m expecting surgery as the nuclear option. Not that I’m eager (to the contrary!). One learning is how close minded I can be about exploring alternative solutions. On the other hand, as it shoots down the leg into my foot, I’ve learned a lot more about physiology!

In the course of navigating airports and the like while in the throws of this (long story), I  also  found that the milk of human kindness can be diluted by pain. When you’re muttering obscenities under your breath because of the knives that accompany every step, clueless actions on the part of others – like stopping suddenly, blocking access, or even just bad signage – can earn muffled imprecations and aspersions on parentage and intelligence.  I’ve always tried to maintain ‘situational awareness’ (and know I’ve failed at times), but I highly recommend it!

On the other hand, when sitting (the only time it settles down), I’m expanding on my growing recognition over the past years that I have no idea what anyone else may be going through.  I’m sure my limping through parking lots and stores can be perceived as congenital damage or wear and tear. There’s no real way for anyone to know how much someone else hurts. We don’t have meters over our heads or icons.

And I’m increasingly grateful!  That may sound odd, but this experience is teaching me (and I am trying to find the positive).  Finding ways to minimize it is an ongoing experimentation. The support of my family helps, and I’ve learned (some) to ask for help.  But even an involuntary and undesirably challenging experience still is an experience.

Also, as much as it may be hard to struggle to find time and motivation for exercise, you learn to miss it. It seems every time I start taking a serious stab at diet and exercise, something goes wrong!  It’s almost like I’m not supposed to; and I know that’s wrong.  (I’ve also learned to secretly suspect my pain doctor is a closet sadist, but that’s the pain talking. :)

This is definitely  not ‘hard fun‘, to be clear. This is much more lemonade.  Fingers crossed that this, too, will pass. And if you do see me limping around, cut me some slack ;).  But also, please understand that it’s hard to know what other people are going through, and do your best to be sympathetic. Which seems like the right message for this time of year anyway. Wishing you and yours all the best for the holidays and the new year!

Citations

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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?

Realities: Why AR over VR

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In the past, I’ve alluded to why I like Augmented Reality (AR) over Virtual Reality. And in a conversation this past week, I talked about realities a bit more, and I thought I’d share. Don’t get me wrong, I like VR  alot, but I think AR has the bigger potential impact.  You may or may not agree, but here’s my thinking.

In VR, you create a completely artificial context (maybe mimicking a real one).  And you can explore or act on these worlds. And the immersiveness has demonstrably improved outcomes over a non-immersive experience.  Put to uses for learning, where the affordances are leveraged appropriately, they can support  deep practice. That is, you can minimize transfer to the real world, particularly where 3D is natural. For situations where the costs of failure are high (e.g. lives), this is  the best practice before mentored live performance. And, we can do it for scales that are hard to do in flat screens: navigating molecules or microchips at one end, or large physical plants or astronomical scales at the other. And, of course, they can be completely fantastic, as well.

AR, on the other hand, layers additional information on  top of our existing reality. Whether with special glasses, or just through our mobile devices, we can elaborate on top of our visual and auditory world.  The context exists, so it’s a matter of extrapolating on it, rather than creating it whole. On the other hand, recognizing and aligning with existing context is hard.  Yet, being able to make the invisible visible where you already are, and presumably are for a reason that makes it intrinsically motivating, strikes me as a big win.

First, I think that the learning outcomes from VR are great, and I don’t mean to diminish them. However, I wonder how general they are, versus being specific to inherently spatial, and potentially social, learning.  Instead, I think there’s a longer term value proposition for AR. There’s less physical overhead in having your world annotated versus having to enter another one. While I’m not sure which will end up having greater technical overhead, the ability to add information to a setting to make it a learning one strikes me as a more generalizable capability.  And I could be wrong.

Another aspect is of interest to me, too. So my colleague was talking about mixed reality, and I honestly wondered what that was. His definition sounded like  alternate reality, as in alternate reality games. And that, to me, is also a potentially powerful learning opportunity. You can create a separate, fake but appearing real, set of experiences that are bound by story and consequences of action that can facilitate learning. We did it once with a sales training game that intruded into your world with email and voicemail. Or other situations where you have situations and consequences that intrude into your world and require decisions and actions. They don’t have  real consequences, but they do impact the outcomes. And these could be learning experiences too.

At core, to me, it’s about providing either deep practice or information at the ‘teachable moment’. Both are doable and valuable. Maybe it’s my own curiosity that wants to have information on tap, and that’s increasingly possible. Of course, I love a good experience, too. Maybe what’s really driving me is that if we facilitate meta-learning so people are good self-learners, having an annotated world will spark more ubiquitous learning. Regardless, both realities are good, and are either at the cusp or already doable.  So here’s to real learning!

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?

 

 

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.