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Debating debates

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This is the year, at the LDA, of unpacking thinking (the broader view of my previous ‘exposure‘). The idea is to find ways to dig a bit into the underlying rationale for decisions, to show the issues and choices that underly design decisions. How to do that? Last year we had the You Oughta Know series of interviews with folks who represent some important ideas. This year we’re trying something new, using debates to show tradeoffs. Is this a good idea? Here’s the case, debating debates.

First, showing underlying thinking is helpful. For one, you can look at Alan Schoenfeld’s work on showing his thinking as portrayed in Collins & Brown’s Cognitive Apprenticeship. Similarly, the benefits are clear in the worked examples research of John Sweller. While it’s fine to see the results, if you’re trying to internalize the thinking, having it made explicit is helpful.

Debates are a tried and tested approach to issues. They require folks to explore both sides. Even if there’s already a reconciliation, I feel, it’s worth it to have the debate to unpack the thinking behind the positions. Then, the resolution comes from an informed position.

Moreover, they can be fun! As I recalled here, in an earlier debate, we agreed to that end. Similarly, in some of the debates I had with Will Thalheimer (e.g. here), we deliberately were a bit over-the-top in our discussions. The intent is to continue to pursue the fun as well as exposing thinking. It is part of the brand, after all ;).

As always, we can end up being wrong. However, we believe it’s better to err on the side of principled steps. We’ll find out. So that’s the result of debating debates. What positions would you put up?

Meta-reflections

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Lake reflectionI was recently pinged about a new virtual world, a ‘metaverse‘ inspired new place for L&D. It looked like a lot of previous efforts! I admit I was underwhelmed, and I think sharing why might be worthwhile. So here are some meta-reflections.

I’ve written before on virtual worlds. In short, I think that when you need to be social and 3D, they make sense. At other times, there’s a lot of overhead for them to be useful that can be met in other ways. Further, to me, the metaverse really is just another virtual world. Your mileage may vary, of course.

This new virtual world had, like many others, the means to navigate in 3D, and to put information around. The demo they had was a virtual museum. Which, I presume, is a nice alternative to trying to get to a particular location. On the other hand, if it’s all digital, is this the best way to do it? Why navigate around in 3D? Why not treat it as an infographic, and work in 2D, leading people through the story? What did 3D add? Not much, that I could see.

My take has, and continues to be, as they say, “horses for courses”. That is, use the right tool for the job. I complained about watching a powerpoint presentation in Second Life (rightly so). Sure, I get that we tend to use new technologies in old ways first until we get on top of the new capabilities. However, I also argue that we can short-circuit this process if we look at core affordances.

The followup message was that this was the future of L&D, and we’d get away from slide decks and Zoom calls, and do it all in this virtual world. I deeply desire this not to be true! My take is that slide decks, Zoom, virtual worlds, and more all have a place. It’s a further instance of get the design right first, then figure out how to implement it. I want an ecosystem of resources.

Sure, I get that such a meta verse could be an integrating environment. However, do you really want to do all your work in a virtual world? Some things you can’t, I reckon, machining materials, for instance. Moreover, we have benefits from being out in the world. There are other issues as well. You might be better able to deal with diversity, etc, in a virtual world, but it’ll disadvantage some folks. Better, maybe, to address the structural problems rather than try to cover them over?

As always, my takeaway is use technology to implement better approaches, don’t meld your approaches to your tech. Those are, at least, my meta-reflections. What are yours?

Designing a conference

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When I agreed to join as co-director of the Learning & Development Accelerator, I’d already attended their first two conferences. Those had been designed to reflect the circumstances at the time, e.g. the pandemic. In addition, there was a desire on the part of Matt Richter & Will Thalheimer (the original directors) to reflect certain values. Matt and I are running the event again, but times have changed. That means we have to rethink what’s being done. So here’s my thinking about designing a conference.

First, the values Matt and Will started with included being as global as possible, and being virtual. The former was reflected in having presentations given twice, once early in the US day, and then again later. That supported everything from Europe, Africa, and the Mideast to Asia and Australia. The virtual was, at least partly, a reaction to the lack of desire to travel and meet face to face, but also to provide options for those who might struggle.

We’re definitely still focusing on being virtual. Folks who would find it challenging to arrange travel for whatever reason can attend this event. There’s also the environmental considerations. Yes, technology requires resources, but not as much as collective travel. While there’s also a desire to meet different time needs, we’ve found less demand for multiple times. However, we will be recording sessions that are synchronous, so they can be viewed at convenient times. We also are spreading it over six weeks, so that there’s time to consume as much as you want. Further, faculty can choose when they’re offering ;).

The original design was focused on evidence-based L&D (which remains a key guiding principle for the LDA). Matt & Will solicited their presenters based upon their representation, but the agenda was largely what those folks wanted to present. Which, in many ways, reflects what other conferences do. In this new era, we wondered what would make a compelling proposition when you can travel to F2F events. We decided that we wanted to step away from ‘what we get’, and focus on ‘what the audience needs’.

This event, then, has a curriculum, across two tracks, designed to address specific needs. There’s also a different pedagogy than most conferences.We also have specific faculty, rather than presenters based upon submissions. Of course, there are tradeoffs. At least we can share our thinking.

The faculty are folks we know and trust to present evidence-based content. You won’t hear promotion for snake oil, like learning styles. We have a pretty impressive lineup, frankly, of people we think are world-class. This includes folks like Ruth Clark, Mirjam Neelen & Paul Kirschner, Karl Kapp, Julie Dirksen, Kat Koppett, Stella Lee, Nigel Paine, Will Thalheimer, and Thiagi. On top of, of course, Matt and myself. Reality means that a few folks we would’ve liked to have couldn’t commit, but this is a a broad and reputable group.

The tracks are basics and advanced. We want to be able to serve multiple audiences. The intent is that the basic track has the core knowledge an L&D person should know. As best we can, as we negotiate with the faculty, of course. Then, the advanced topics are things that are emergent and need addressing. Of course, there’s no commitment that you have to stay in one or another. As with other conferences, you can pick and choose what to view.

We’re also not just having presentations; we’ve asked the faculty to provide development. That is, we’re intending several rounds of content, activity, and feedback, spread out over several days or weeks. We don’t want people to hear good ideas, and maybe take them back. We want folks to take action! We’re also designing in the opportunity for mentoring.

Of course, there’ll be some social events, and other ways to not only hear content and apply it, but to mingle with faculty and other attendees. We want to foster some community. Also, we’re intending to somewhat front load stuff so that we can adapt. If we hear that we need to do something we haven’t planned, we’re looking to have leeway to address it. The nice thing about being small is the ability to be flexible!

None of this is saying you don’t get much of the same from conferences (except, perhaps, the design). I’ve been on conference program committees, and know conference organizers as well. They typically get more proposals than they can accept, so they can choose a suite that reflect things for various ranges of experience and cover important topics. They may not, however, know all the submitters, and take chances on a few. I laud that, actually, because we can’t know if a new approach or person is worthwhile without experimentation. Still, there is the chance for gaps, and for bad presentations/presenters. They’re also, except for the pre-conference workshops (e.g. my Make It Meaningful one at the upcoming DevLearn), one-off events.

We’re taking a chance on our format, too. We haven’t done it before. It may not work, though we have good reasons to believe it will. So, we hope to see you at the Learning & Development Conference, Oct 10 – Nov 18, if the above thinking about designing a conference sense. We think it does, we hope you do, too.

Projects That Didn’t Fly

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I’ve had the pleasure of leading the design of a number of projects that have had some impact. These include a mobile app a company could point to. Also a game that helped real kids. Even a context-sensitive performance support system that was worth a patent. Then, of course, are the projects that didn’t, for whatever reason, see the light of day.  So here are some reflections on a few projects that didn’t fly.

Back in the mid-90s, I was part of a government-sponsored initiative in online learning, and we were looking for a meaningful project. We made a connection to two folks with a small company that taught about communicating to the press. They could’ve come out with a book, but they wanted to do something more interesting. We collaborated on an online course on speaking to the media. I partnered with an experienced digital producer, and backstopped with a university-based media team. We had a comic skit writer, and cartoonists, to augment our resources. The result was technically sophisticated, educationally sound, and engaging both visually and in prose. It never flew, however, as we didn’t partner it with a viable business model. Which was reflective of the times.

Then, at the end of the 90’s, I was asked to lead a team developing an adaptive learning system. The charge was to help learners understand themselves as learners. I had a stellar team: software engineer, AI expert, psychometrician, learning science guru, visual designer, and an interface designer. The model was to do an initial profile, then present you with learning elements (concepts, examples, practice, etc) and update your model based on your performance. There was even a machine learning component to improve the models as we went along. We actually got a first draft up and running (10 elements in the student model), before ego and greed undermined and killed it. The lessons learned, of course, have continued to inform me, including, for instance, my calls for content systems.

Then, around the mid-2000s, I was given the task to devise a content model for a publisher.  They wanted to develop once and populate a variety of business products. Drawing on previous experience, I developed a robust model, which started from individual elements and supplemented and aggregated them in a systematic way. This also ended sadly. In this case, the software side never reached fruition.

There are lots of reasons good intentions can go awry.  In my case, it wasn’t going to be on a lack in the learning design ;). What I’ve learned, however, is that learning design isn’t the only element that matters. There’s vision, and execution, and partners, and more. All are ways in which things can go wrong. Yet, that doesn’t mean we shouldn’t try. It just means that we should, to the extent of our abilities, also try to ensure the success of the other comments. It’s worth exploring projects that didn’t fly so as to see how future ones might.

The ‘late adopter’ strategy

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I was asked about the latest techno-hype, bionic reading. At the same time, there’s a discussion happening about learning affordances of the metaverse. I realize my strategy is the same, which I learned many years ago (wish I could remember from whom!). The short version is, wait until the dust settles. Why? Let’s evaluate the late adopter strategy.

So, for anything new, there all-too-frequently seems to be a lot of flash. In my experience, a lot more than substance! That is, many things rise, and most fall. When things calm down after the initial exuberance, most simply disappear. There are myriad factors: acquisition and shut down by competitors, other elements fail despite a good premise, or even unexpected factors outside of control (e.g. a pandemic!). Of course, the usual suspect is that there’s no real there there!

I remember the hype over Second Life, and recognizing that the core elements were 3D and social. Yet, what we saw were slide presentations in a virtual world. Which was nonsensical. I’ve suggested before that you can infer the properties of new technologies, in many cases, by considering their cognitive affordances. I’ll await the meta-verse manifestation, but it seems to me to be the same, just more immersion. Still, lots of technical and cognitive overhead to make it worthwhile.

Similarly with bionic reading. There’s now  lots  of anecdotal suggestions that it’s better. That’s not the same, however, as a true experimental study. Individual experiences don’t always correlate with actual impact. There’re myriad reasons for this too, e.g. self-fulfilling prophecy, perception vs reality, etc. Still, I really want to have some more convergent evidence. Here it’s harder to do the affordances. Yes, it might support people who have difficulty reading, but might it interfere with others? How will we know?

On the basis of the above, however, I suggest waiting until something’s been around, and then if it persists, start investigating what the affordances might be. Many things have come and gone, and I’m glad I didn’t bite. I might then be late to a platform, but that’s OK. I still tend to get opportunities to innovate around ideas of application  after they’re established, because, well, that’s what I do ;). Affordances help, as does lateral thinking and having on tap  lots of mental models to spark ideas.

We’re too easily enchanted with the latest shiny object. No argument it’s worth experimenting with them, but don’t swallow the hype until you’ve either had your own data, or someone else’s. I reckon rushing in has a greater opportunity for loss than gain. Let those with needs, resources, and opportunity take the first cuts. There’s no need to bleed prematurely, there’ll be plenty of opportunities to need to tune and test again even once principles emerge. So that’s my take on the value of a ‘late adopter’ strategy. What’s yours?

The cognitive basis of LXD

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Image of the brainWhen ATD asked me to write the learning science book, I’d already had the intention of writing a Learning Experience Design (LXD) book. I’d even begun, and the first section on learning was underway, so essentially I was partly done! I’d also realized that it was going to be monumental undertaking. This is because LXD, to me, encompasses three things, all based on cognitive science. To properly address it, I would have to be talking a master’s course, not just a book!. So here I’d like to make the case why I think that there’s a cognitive basis of LXD.

First, look at the three elements of LXD: learning, experience, and design. For experience, you can think: engagement and/or emotion. That is, ensuring that there’re explicit feelings associated, not just occurrences. Each one of those three things, then, has a cognitive underpinning.

As I’ve discussed previously, learning science was an outgrowth of cognitive science. The inter-disciplinary approach to cognition that inspired the formation of cognitive science subsequently led to learning science. Design, too, was a subject of study. I happened to be a grad student at the time that user-centered approaches, subsequently UX, were being explored. This, too, is cognitive; first because design approaches have to reflect aligning with how users brains work. Then, also, because design processes have to accommodate how designers brains work, and don’t!

Then we come to the experience side. It turns out that understanding ‘experience’ is a cognitive exercise as well. Why are we driven by curiosity? How come we remember emotionally-charged events better? What creates positive affect? It’s an interdisciplinary approach as well, integrating research on emotion and events and more. It’s the topic of my just-released book (which includes design as well, to serve as the complement to my learning science book).

I continue to explore all three, from a professional responsibility and personal interest. I admit I nerd out about these things, and am always eager to find out more and discuss it. And  I’ve do have  a bias. My Ph.D. is in Cog Psych, so I do look at world with that filter. But I also see that the perspective provides some useful leverage. My current ideal is to make experiences that are transformative, in that they change people in ways that they want, or need, to change. That’s the goal.

I will continue to maintain that knowing the underpinning architecture, and then the manifestations in the three areas, are important. I believe that knowing the cognitive basis of LXD is an advantage in being able to execute against the requirements in optimal ways. So, am I missing anything?

 

Good and bad advice all in one!

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I was asked to go to read an article and weigh in. First, please don’t do this if you don’t know me. However, that’s not the topic here, instead, I want to comment on the article. Realize that if you ask me to read an article, you’re opening yourself up to my opinion, good  or bad. This one’s interesting, because it’s both. Then the question is how do you deal with good and bad advice all in one.

This article is about microlearning. If you’ve been paying attention (and there’s no reason you should be), I’ve gone off on the term before. I think it’s used loosely, and that’s a problem because there are separate meanings, which require separate designs, and not distinguishing them means it’s not clear you know what you’re talking about. (If someone uses the term, I’m liable to ask which they mean! You might do the same.).

This article starts out saying that 3-5 minute videos are  not  microlearning. I have to agree with that. However, the author then goes on to document 15 points that are important about microlearning. I’ll give credit for the admission that there’s no claim that this a necessary and complete set. Then, unfortunately, I also have to remove credit for providing no data to  support the claims!  Thus, we have to evaluate each on it’s own merits.  Sorry, but I kinda prefer some sort of evidence, rather than a ‘self-evident’ fallback.

For instance, there’s a claim for brevity. I’ve liked the admonition (e.g. by JD Dillon) that microlearning should be no longer, and no shorter, than necessary. However, there’s also a claim here that it should be “3 – 10 minutes of attention span”. Why? What determines this? Human attention is complex, and we can disappear into novels, or films, or games, for hours. Yes, “Time for learning is a critical derailer”, but…it’s a factor of how important, complex, and costly if wrong the topic is. There’s no one magic guideline.

The advice continues in this frame: there’re calls for simplicity, minimalism, etc. Most of these are good principles,  when appropriately constrained. However, arbitrary calls for “one concept at a time is the golden rule”  isn’t necessarily right, and isn’t based on anything other than “our brains need time for processing”. Yes, that’s what automation is about, but to build chunks for short term memory, we have to activate things in juxtaposition. Is that one concept? It’s too vague.

However, it could be tolerated if some of the advice didn’t fall prey to fallacious reasoning. So, for instance, the call for gamification leans into “Millennials and Gen Z workforce” claims. This is a myth. Gamification itself is already dubious, and using a bad basis as an assumed foundation exacerbates the problem.  There are other problems as well. For one, automatically assuming social is useful is a mistake. Tying competition into the need to compete is a facile suggestion. Using terms like ‘horde’ and ‘herd’ actually feels demeaning to the value of community. A bald statement like “Numbers speak louder than words!” similarly seems to suggest that marketing trumps matter. I don’t agree.

Overall, this article is a mixed bag. So then the question arises, how do you rate it? What do you do? Obviously, I had to take it apart. The desire for a comment isn’t sufficient to address a complex suite of decent principles mixed up with bad advice and justified (if at all) on false premises. I have to say that this isn’t worth your time. There’s better advice to be had, including on microlearning. In general, I’ll suggest that if there’s good and bad advice all in one, it’s overall bad. Caveat emptor!

Generic Thinking Skills?

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Recently, a colleague asked a few of us about our views on critical thinking skills. This is actually a contentious topic. There are broad claims of the need for them, increasingly, even showing up in job advertisements. On the other hand, researchers and others have weighed in against them, saying that expertise is the only lever. I tend to lump critical thinking skills in with the broader issue of generic thinking skills, so what are the issues?

Upfront, I’ll admit that I like the concept of generic thinking skills. Say, for instance,  learning-to-learn skills. That is, domain independent skills that lead to better approaches. It seems to make sense that, in the absence of specific knowledge, some general approaches are more useful than others. For instance, faced with a new domain, I’d be inclined to expect that systematic experimentation and observation would be better than random trial and error.

On the other hand, prominent psychologists like John Sweller and Paul Kirschner have said that domain-specific skills are the only way to bet. There is significant evidence that expertise matters in successful approaches to problem-solving, and others. While we have some innate skills for domains that are biologically primary, learning in other domains requires expertise.

Is there, then, any evidence for generic skills? Based on Micki Chi’s work on the value of self-explanation, Kate Bielaczyc and others have found that instruction on systematically explaining steps in examples help, across domains. In my own Ph.D. thesis, I trained folks on analogical reasoning skills, and found improvement (for component skills that weren’t a) already ceilinged or b) were perceived to be immutable, across different problem types.

How, then, do we reconcile these conflicting viewpoints? My (self- :) explanation is that it’s a matter of degree, a continuum rather than a dichotomy. The more domain knowledge you possess, the more likely you are to find a good answer. However, what if you’re in a new domain where you don’t have relevant expertise to hand? In that case, I’ll suggest that there are benefits to some approaches over others, and training those general skills is justifiable. That is, general skills are weaker than domain specific skills, but general skills are better than nothing!

We know that there are practices that improve outcomes. For instance, I’ve written about how to, and not to, do brainstorming. Similarly, I believe Harold Jarche’s Seek-Sense-Share model works across domains. Systematic creativity is  not an oxymoron!  That’s the story I’m holding on to about generic thinking skills. What are your thoughts on the topic?

Tech Thoughts

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I’m late with a post this week, owing to several factors, all relating to technology. I hadn’t quite pulled together a complete lesson, but by writing down these tech thoughts, I got there. (A further argument for the benefits of reflection.)

It started with upgrading our phones. We needed to (I tend to hand mine down, but really we both needed an upgrade this time). Of course there are hiccups, particularly since m’lady’s was so old that it couldn’t do the amazing thing mine had done. What happened with mine was that you just put the old phone and the new phone together and the new one just sucks the data off the old one and then the old one asks if you want to wipe it clean!  That’s some serious user experience. Something we should look more to in our LXD, so that we’re doing proper backwards design and we have the right combination of tools and learning to make performance relatively effortless.

Then another thing was quite interesting. An individual linked to me on the basis of a citation in a book. I didn’t know the book, so he sent me a picture of the page. He also asked if I could read Dutch. Sadly, no. However, I had recently upgraded my OS, and when I opened the picture, I noticed I could click on the text. Of. The. Picture!  I could select all the text (my OS was doing OCR on the picture live!), and then I could paste into Google Translate (another amazing feat) and it recognized it as Dutch and translated it into English. Whoa!

On the flip side, owing to the unusually heavy rain (for California), first our internet went out, and then the power. Fortunately both were working by the next morning. However, after that my backup drives kept dismounting and I couldn’t execute a backup reliably. I thought it might be the laptop, and I did a couple of increasingly difficult remedial measures. Nope. Had the drives been damaged by the power outage? Power outages aren’t quite new around here (we’re a bit up a hillside, and squirrels regularly blow the transformer), yet it hadn’t happened before.

Then I was on a Zoom call, and I started having hiccups in the microphone and camera. Even typing. What? When I switched to the laptop camera, it was all good.  All the things, drives, microphone, external monitor, are connected by a external hub. The hub had gone wonky! Instead of having to replace drives, I picked up a new hub last nite, and all’s good now. Phew!

I guess my take home tech thoughts is that we’re making true a promise I’ve mentioned when talking mobile: we really do have magic. (Asimov famously said any truly advanced technology is indistinguishable from magic.) We can do magical things like talk at distance, have demons do tasks on our behalf (picture text transcribing and translation), etc. On the other hand, when it doesn’t work, it can be hard to identify the problem!  Overall, it’s a win. Well, when it’s designed right! Which involves testing and tuning. As Dion Hinchcliffe put it: “Seamless #cx is now table stakes.” So let’s get designing, testing, and tuning, and make magical experiences.

Levels of Organizational Alignment

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Several years ago, I was pushing the notion of the Coherent Organization. While I still feel it’s relevant, perhaps the time wasn’t right or I wasn’t convincing enough. However, as I continue to consider the issue of alignment of what we do in L&D (and organizational) practices, I realize there’s more. One way, then, to think about the coherent organization is as achieving levels of organizational alignment.

Starting from the top, I think of the alignment with the organization and society. Normally, and probably most importantly for survival, organizations need to think about alignment with their market. (In appropriate ways; I’m reminded how the freight business got upended when companies thought they were in the train business and not the transportation business.) However, there  is a level above the market, and that is whether the org is serving the market in a society-appropriate way. For instance, if you’re helping your customers rip off their clients, it may be lucrative but it’s not a scrutable way to do business. I like the notion of benefit corporations  (though they may not go far enough). Don’t do well by doing ill.

Which is the next level of alignment, of employees with the organization’s mission. They’ll be more engaged if that mission is appropriate!  Further, I like the notion of ’employee experience’. I’ve heard it said that you can’t have a good customer experience if you don’t have a good employee experience. That’s plausible. I think Dan Pink’s  Drive says it well, you want your employees to have Mastery, Autonomy, and Purpose. Which means having a clear raison d’être, goals and the freedom to pursue them, and support to succeed.

Accompanying that is a workplace culture that’s supportive of success. I like Jerry Michalski’s focus on trust; start from there. Then have transparency, e.g. ‘show your work’ and ‘learn out loud‘. I’m also a fan of the Learning Organization Dimensions of Garvin, Edmondson, & Gino. I like how Amy Edmondson has gone on to advocate for including both safety and accountability as complementary components of success.

Of course, this carries down to the individual level. For instance, including a focus on having performers prepared up front and developed over time. This includes a shift to coaching and mentoring, as well as learning experience design grounded in the sciences of learning and engagement.  Going further, we should havie people not just knowing their purpose but getting feedback on how they‘re doing to achieve it. Recognition matters, with positive recognition of accomplishment or support to improve. Against an objective metric, of course, not comparative to others.

There’s more, but most importantly, it’s aligning all these from bottom to top. For instance, you could be creating a great culture to serve a bad purpose. Alternatively, you could have a great purpose but use industrial era methods to get there. I have to admit that, having served in orgs of various sizes, and seen the pockets of inefficiency that can emerge, I wonder how any business makes any money! Still, there’s evidence that the better you’re aligned, the better you do. (See the Toward Maturity Top Deck results or Laurie Bassi’s work on the link between people approaches and org success.

Achieving success at all  levels of organizational alignment is a path to success. No one’s saying it’s easy, but it  is doable. Further, it’s your best investment in the future. Just as with designing learning, get the core right before you add shiny objects, the same is true for organizations. There’s a transformation in practices to be done before you then apply the digital transformation. However, once you align these, as well, you’re on an upward path. Shall we?

By the way, this is aligned :) with the theme of what I’ll be  talking about in my opening keynote for the ATD Japan Summit.