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Clark Quinn’s Learnings about Learning

Aligning and enabling transformation

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In what was my last Quinnsights column for Learning Solutions, I wrote about how the transformation wasn’t (or shouldn’t) be digital. In many ways we aren’t aligned with what’s best for our thinking. Thus,  digitizing existing approaches doesn’t make sense. Instead, we should be fixing our organizational alignment first,  then  digitizing. The opportunity is in aligning  and enabling transformation.

First, we should be looking at  all  the levels of organizational alignment. At the individual level we can be doing things like implementing federated search, to support individual learning. This should be coupled with providing development of writing good search strings and evaluating search outcomes. This also means curating a suite of resources aligned with learning directions and future opportunities. The point being that we should be supporting evidence-based methods for individual development, then supporting digitally. For instance, supporting learning-to-learn skills. Taking them for granted is a mistake! It’s also about ongoing support for development, e.g. coaching. Good practices help, and tools that document approaches and outcomes can assist.

At the group level, there are again ways in which we can be fostering effectiveness. This includes having good collaboration tools, and assisting people in using them well. It can also be about policies that make ‘show your work’ safe. Then you can augment with ‘show your work’ tool. Again, having the right practices and policies makes the digital transformation investment more valuable. You could pick the wrong tools if you’re instituting the old ways instead of doing the process work first.

This holds true at the organizational level as well, of course. The policies and practices cross the organization. Thus, what works for teams comes from an organizational focus on learning. Then, the digital investments are focused on the most optimal outcomes. The alternative, digitizing unaligned practices, can only hinder improvement to be a successful organization.

There are a lot of myths about what works. This includes learning myths, but also bad HR practices. Many stem from maintaining approaches that are carryovers from industrial age business. Instead, we should be leveraging our knowledge of thinking to be strategic. L&D can be critically contributing to organizational success! Or not. There’s a big opportunity to shift practices in a positive direction, with upsides for outcomes. However, it takes the understanding and the will. What will you do?

This is related to the talk I’ll be giving as the opening keynote for the ATD Japan Summit in December (though I’m filming it for virtual delivery). I get my thinking done here first ;).  

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.

Higher-education Myths

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I’ve been in a variety of higher education roles in several ways: as a victim, er, student; as a grad student; post-doc; tenured/promoted faculty member; textbook publishing consulting;  strategic elearning consulting… Further, in general, I’m a supporter. I do have quibbles, and one is the persistence of learning myths. Trust me, I wrote a whole book on what the research says about them! In addition to having talked about org learning myths, let me explore some elements of higher-education myths.

I saw an article in the top education news source in the country, The Chronicle of Higher Education. I get their daily newsletter, just to keep my finger on the pulse. However, this article was touting issues for Gen Z students. Yet, research says that the ‘generations’ framework isn’t valid. There’s no reliable data that generations is a viable discrimination. In fact, it literally  is discrimination (in terms of using arbitrary distinctions to label people.

This is only part of the broader problem. A colleague regularly chides his alma mater for continuing to believe in learning styles. This, too, is a myth! While learners do differ, there’s no evidence we should adapt learning to learning styles, let alone can we reliably identify them. It’s appealing, but wrong. Not that it isn’t also prevalent amongst K12 teachers as well.

Which is related to another problem, business school curricula. I was surprised, and dismayed, to find that a prominent business school has personality instruments as part of it’s curricula! This includes MBTI, which is discredited both theoretically and empirically. Other such instruments, also with flaws, continue to be indicated. I’m sure there may be some financial motivation as well. (E.g. like Apple & Microsoft did offering huge discounts to schools, to get new users used to their experience.)

We should not tolerate learning myths in university. Aren’t these bastions of science? Ok, that’s another myth, that universities aren’t riven with politics, but that’s not the focus here. Still, universities should be better at rejecting myths, just as they should also be better about using the best pedagogies. Which they also aren’t doing, by and large ;).

There are more myths about universities, and issues like what their role in society  should be. That’s not what I’m talking about here, though. For all their other issues, they should  not be perpetuators of higher-education myths. (Here’s hoping they’re also not guilty of the ‘attention span of a goldfish’ myth!)

The (Post) Cognitive Perspective

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I’m deeply steeped in the cognitive sciences, owing to a Ph.D. in cognitive psych. Fortuitively, this was at the time my advisor was creating the cognitive science program (and more). So I’ve a bias. Yet I also have a fair bit of empirical evidence that taking a cognitive perspective accomplishes things that are hard to do in other ways. So let me make the case that the cognitive perspective is more than just a useful one, but arguably a necessary one.

I‘ll start by reflecting back on something I wrote before, about virtual world affordances. At the time, platforms like Second Life were touting the advantages of an immersive navigable world. Of course, the promises were all-encompassing: everything would move to virtual worlds. In retrospect, it didn‘t eventuate. Why? I argue it’s because the cognitive overhead of virtual worlds means that there has to be a sustained value proposition, and that came from when you truly need 3D immersion and social.  

Similarly, when I wrote my books on games and mobile, I focused on the cognitive impacts. The first reason was because technology was changing so fast that anything hardware-specific would be out of date before the book was published. The second is because our brains don‘t change that fast, so what works will work regardless of the technology .  

Note that our understanding of cognition has changed. We‘re now in a ‘post-cognitive‘ era, where the notion that all our formal, logical thinking is done in our heads is wrong. Research is showing that we‘re far more ‘situated‘ than we think, and distributed as well. That includes distributed across external representations and other people! It’s very contextual, and it’s not all in our heads!

So these days, when I look at things, I try to look with a cognitive (ok, post-cognitive) perspective. I look to see how things align, or not, with how our brains work. When I evaluate learning technologies, for instance, I look to see how well they do things like provide meaningful practice: active and contextualized. You can also see when particular technologies (e.g. VR/AR/AI) will be valuable, and not. Similarly, when I look at workplace change proposals, I look at how well they reflect our mechanisms for adapting to change.  

I‘ll argue that these perspectives are valuable. You can quickly see why most training doesn‘t work, cut through hype from vendors, create explanations about why myths are mythtaken, etc. You can save money, be more effective, etc when you align with how our brains work. I‘ve talked before about how there are gaps. This is the flip side, how to avoid those gaps, and do better.   In short, you‘re better able to assist your organization in being more effective (and efficient).  

That‘s why I‘m pleased that I am able to put these basics into the learning science book, and workshops. It‘s possible to get better at this sort of perspective. It‘s also possible to get it on tap as needed. However, it does take both the cognitive understanding and the experience in applying it. So, how‘s your cognitive perspective?

On a side note, I want to encourage you to consider my workshop at DevLearn on Make It Meaningful, a full day exploring how we make learning experiences deeply engaging (adding to effectiveness). This is also the topic of my online workshop through the Learning Development Accelerator. This is, to me, the most important topic to  complement  learning science. (Available as a book and workshop. ;) In both cases, I’m trying  to help us  stop making boring courses that people want to avoid, and suggest that this  can be done for most any topic. It also leads to more effective learning outcomes! Hope to see you at one! (Of course, if your organization would like your own private version, let me know!)

Meta-ethics of learning design

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I‘ve addressed ethics elsewhere, but I‘m looking at it a different way now. I’m thinking from the perspective of situated cognition, and recognizing that there are certain things we can do. For better or worse. Further, these choices have ramifications beyond the initial impact. I think we need to be aware of the possibilities, and then consider the meta-ethics of learning design.

My particular concern sparks from the notion of how we are contextually sensitive. To make this concrete, think of the research by Beth Loftus. I”ll characterize a whole suite of research with a simply paraphrased experiment. So, she had folks watch a video of an accident. Then, she prompted recall of the amount of damage they witnessed. For one, she just asked them. For another group, the recall was prompted by “Besides the broken glass,…”. The latter group recalled worse damage. And. There. Was. No. Broken. Glass!  

The point here is that context can influence our thinking and memory. Which is what I see worry about with videos. They can take a statement as if it‘s fact, and then continue on with that as received wisdom. It‘s a classic cognitive approach, making a statement as if it‘s assumed.The bad part is that there‘s a narrative flow, and it‘s hard to stop and reflect. Versus, say, reading.  

On the other hand, of course, we can build in reflection time. Sure, learners can use the pause button, but there are times they may not. For instance, if the learner is following confirmation bias, that is looking at things that align with what you believe.  

We have the option to use coercive techniques for good, of course. However, we can also choose to use legitimate presentation techniques. I believe we should. Part of the development of metacognition is to see the pedagogy being used and internalizing it. If our pedagogy is visible (as it should be), it needs to be scrutable if we want our learners to adopt appropriate skills.  

Our designs, and our meta-designs, need to be ethically designed, both to effectively achieve our ends, and to develop our learners. We need to support the meta-ethics of learning design, as well as the ethics themselves.  

Complexity in Learning Design

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a fractalI recently mentioned that one of the problems with research is that things are more interconnected than we think. This is particularly true with cognitive research. While we can make distinctions that simplify things in useful ways (e.g. the human information processing system model*), the underlying picture is of a more interactive system.  Which underpins why it makes sense to talk about Learning Experience Design (LXD) and not just instructional design. We need to accommodate complexity in learning design.  (* Which I talk about in Chapter 2 of my learning science book, and in my workshops on the same topic through the Allen Academy.)

We’re recognizing that the our cognition is more than just in our head. Marcia Conner, in her book  Learn More Now  mentioned how neuropeptides passed information around the body. Similarly, Annie Murphy Paul’s  The Extended Mind talks about moving cognition (and learning) into the world. In my Make It Meaningful workshops (online or F2F at DevLearn 19 Oct), I focus on how to address the emotional component of learning. In short, learning is about more than just information dump and knowledge test.

Scientifically, we’re finding there are lots of complex interactions between the current context, our prior experience, and our cognitive architecture. We’re much more ‘situated’ in the moment than the rational beings we want to believe. Behavioral economics and Daniel Kahneman’s research have made this abundantly clear. We try to avoid the hard mental work using shortcuts that work sometimes, but not others. (Understanding when is an important component of this).

We get good traction from learning science and instructional design approaches, for sure. There are good prescriptions (that we often ignore, for reasons above) about what to do and how. So, we should follow them. However, we need more. Which is why I tout LXD  Strategy! We need to account for complexity in learning design approaches.

For one, our design processes need to be iterative. We’ll make our best first guess, but it won’t be right, and we’ll need to tune. The incorporation of agile approaches, whether SAM or LLAMA or even just iterative ADDIE, reflects this. We need to evaluate and refine our designs to match the fact that our audience is more complex than we thought.

Our design also needs to think about the emotional experience as well as the cognitive experience. We want our design processes to systematically incorporate humor, safety, motivation, and more. Have we tuned the challenge enough, and how will we know?  Have we appropriately incorporated story? Are our graphics aligned or adding to cognitive load? There are lots of elements that factor in.

Our design process has to accommodate SMEs who literally can’t access what they do. Also learner interests, not just knowledge. We need to know what interim deliverables, processes for evaluation, times when we shouldn’t be working solo, and tools we need. Most importantly, we have to do this in a practical way, under real-world resource constraints.

Which is why we need to address this strategically. Too many design processes are carry-over from industrial approaches: one person, one tool, and a waterfall process. We need to do better. There’s complexity in learning design, both on the part of our learners, and ourselves as designers. Leveraging what we know about cognitive science can provide us with structures and approaches that accommodate these factors. That’s only true, however, if we are aware and actively address it. I’m happy to help, but can only do so if you reach out. (You know how to find me. ;) Here’s to effective and engaging  learning!

Iterating and evaluating

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Design cycleI’ve argued before about the need for evaluation in our work. This occurs summatively, where we’re looking beyond smile sheets to actually determine the impact of our efforts. However, it also should work formatively, where we’re seeing if we’re getting closer. Yet there are some ways in which we go off track. So I want to talk about iterating and evaluating our learning initiatives.

Let’s start by talking about our design processes. The 800 lb gorilla of ADDIE has shifted from a water flow model to a more iterative approach. Yet it still brings baggage. Of late, more agile and iterative approaches have emerged, not least Michael Allen’s SAM and Megan Torrance’s LLAMA. Agile approaches, where we’re exploring, make more sense when designing for people, with their inherent complexity.

Agile approaches work on the basis of creating, basically, Minimum Viable Products, and then iterating.  We evaluate each iteration. That is, we check to see what need to be improved, and what is good enough. However,  when are we done?

In my workshops, when talking about iteration, I like to ask the audience this question. Frequently, the answer is “when we run out of time and money”. That’s an understandable answer, but I maintain it’s the  wrong answer.

If we iterate until we run out of time and money, we don’t know that we’ve actually met our goals. As I explained about social media metrics, but applies here too, you  should be iterating until you achieve the metrics you’ve set. That means you know what you’re trying to do!

Which requires, of course, that you set metrics about what your solution should achieve. That could include usability and engagement (which come before and after, respectively), but most critically ‘impact’. Is this learning initiative solving the problem we’re designing it to achieve?  Which also means you need to have a discussion of why you’re building it, and how you know it’s working.

Of course, if you’re running out of time and money faster than you’re getting close to your goal, you have to decide whether to relax your standards, or apply for more resources, or abandon your work, or…but at least you’re doing so consciously. Yet this is still better than heuristically determining that three iterations is arbitrarily appropriate, for example.

I do recognize that this isn’t our current situation, and changing it isn’t easy. We’re still asked to make slide decks look good, or create a course on X, etc. Ultimately, however, our professionalism will ask us to do better. Be ready. Eventually, your CFO should care about the return on your expenditures, and it’ll be nice to have a real answer. So, iterating and evaluating  should  be your long term approach. Right?

Making it Meaningful

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I volunteer for our local Community Emergency Response Team (CERT; and have learned lots of worthwhile things). On a call, our local organizer mentioned that she was leading a section of the train-the-trainers upcoming event, and was dreading trying to make it interesting. Of course I opened my big yap and said that’s something I’m focusing on, and offered to help. She took me up on it, and it was a nice case study in making it meaningful.

Now, I have a claim that you can’t give me a topic that I can’t create a game for. I’m now modifying that to ‘you can’t give me a topic I can’t make meaningful’.  She’d mentioned her topic was emergency preparedness, and while she thought it was a dull topic, I was convinced we could do it. I mentioned that the key was making it visceral.

I had personal experience; last summer our neighbor was spreading the rumor that we were going to have to evacuate owing to a fire over the ridge. (Turns out, my neighbor was wrong.) I started running around gathering sleeping bags, coats, dog crate, etc. Clearly, I was thinking about shelter. When I texted m’lady, she asked about passports, birth certificates, etc. Doh!

However, even without that personal example, there’s a clear hook. When I mentioned that, she mentioned that when you’re in a panic, your brain shuts down some and it’s really critical to be prepared. However, she mentioned that someone else was taking that bit, and her real topic was different types of disasters. Yet my example had already got her thinking, and she started talking about different people being familiar with an earthquake (here in California).

I thought of how when talking with scattered colleagues, they disclaim about how earthquakes are scary, and I remind them that  every place has its hazards. In the midwest it could be tornados or floods. On the east coast it’s hurricanes. Etc. The point being that everyone has some experience. Tapping into that, talking about consequences, is a great hook.

That’s the point, really. To get people willing to invest in learning, you have to help people see that they  do need it. (Also, that they don’t know it now,  and that this experience will change that.). You need to be engaged in making it meaningful!

Again, in my mind learning experience design (LXD) is about the elegant integration of learning science with engagement. You need to understand both. I’ve got a book and a workshop on learning science, and I’ve a workshop at DevLearn on the engagement side. I’ve also got a forthcoming book and an online workshop coming for more on engagement. Stay tuned!

More lessons from bad design

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I probably seem like a crank, given the way I take things apart. Yet, I maintain there’s a reason beyond “get off my lawn!” I point out flaws not to complain, but instead to point to how to do it better. (At least, that’s my story and I’m sticking to it. ;) Here’s another example, providing more lessons from bad design.

In this case, I’ll be attending a conference and the providers have developed an application to support attendees. In general, I look forward to these applications. They provide ways to see who’s attending, and peruse sessions to set your calendar. There are also ways to connect to people. However, two major flaws undermine this particular instance.

The first issue is speed. This application is  slow! I timed it; 4 seconds to open the list of speakers or attendees. Similarly, I clicked on a letter to jump through the list of attendees. The amount of time it takes varied from 4 to 8 seconds. Jumping to the program took 6 seconds.

While that may seem short, compare that to most response times in apps. You essentially can’t time them, they’re so fast. More than a second is an era in mobile responsiveness. I suspect that this app is written as a ‘wrapped’ website, not a dedicated app. Which works sometimes, but not when the database is too big to be responsive. Or it could just be bad coding. Regardless, this is  basically unusable. So test the responsiveness before it’s distributed to make sure it’s acceptable. (And then reengineer it when it isn’t.)

That alone would be sufficient to discount this app, but there’s a second problem. Presumably for revenue reasons, there are ads that scroll across the top. Which might make sense to keep the costs of the app down, but there’s a fundamental problem with our visual architecture.

Motion in the periphery of our vision is distracting. That was evolutionarily adaptive, allowing us to detect threats from places that we weren’t focusing on. Yet, when it’s not a threat, and we  are trying to focus on something, it interferes. We learned about this in the days of web pages with animated gifs: you couldn’t process what you were there to consume!

In this app, the scrolling of the ads makes it more difficult to read the schedule, attendee lists, and other information. Thus, the whole purpose of the application is undermined. You could have static ads that are randomly attached to the pages you click on. The audience is likely to go to several pages, so all the ads will get seen. Having them move, however, to ensure that you see them all undermines the whole purpose of the app.

Oddly enough, there are other usability problems here. On the schedule, there’s a quick jump to times on a particular day. Though it stops at 2PM!?!? (The conference extends beyond that; my session’s at 4PM.) You’d think you could swipe to see later times on that ‘jump’ menu, but that doesn’t work. I can’t go farther, because the usability makes it too painful; we may miss more lessons from bad design.

Our cognitive architecture is powerful, but has limitations. Designing to work in alignment with our brains is a clear win; and this holds true for designing for learning as well as performance support. Heck, I’ve written a whole book  about how our minds work, just to support our ability to design better learning! Conflicting with our mental mechanisms is just bad design. My goal is that with more lessons in bad design, we can learn to do better. Here’s to good design!

Caveat Malarkey

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After continuing to take down marketing blather, it’s time for a plea. Caveat Malarkey!

And, as always, the prose.

If you‘ve been paying attention, you will have seen that a number of my blog posts take down a variety of articles that are rife with malarkey. A lot of them come from connections or pointers on LinkedIn. (If you want to live in infamy, feel free to point me to your posts. ;) It‘s time to address what I‘m seeing, from two points of view. One is my advice to vendors in the L&D space. The other is advice to you who are consumers of education & technology products. The underlying theme is Caveat Malarkey!

What I‘m talking about is the large number of posts that do one of several things. First, they use myths to promote products. These are things like the attention span of a goldfish, learning styles, generations/digital natives, etc. Second, they are unclear on concepts. They toss around bizbuzz without being clear about what the terms mean, and more importantly what it takes to make it work and not! Of course, there are ones that accomplish both.  

So let‘s start with myths. Heck, I wrote a book about them, just because they won‘t go away!   For instance, while we know that learners differ, we can‘t (and shouldn‘t) address our learning to match styles. There‘s no evidence that adapting to styles helps. Worse, there is, as yet, no meaningful way to reliably characterize learners according to styles. Similarly, the claim that our attention span has dropped doesn‘t stand up to biological nor empirical scrutiny. We don‘t evolve that fast, and there‘s plenty of counter-evidence. The claim comes from a misinterpretation of an essentially irrelevant study. The notion that we can characterize people by the ‘generation‘ they‘re born in, or that people who grew up with digital phones are somehow ‘natives‘ are also both found lacking when looked at closely. There were 13 more myths in my book that can also be seen.  

Then there‘s conceptual clarity. Again, my most recent book is on learning science, trying to provide the foundation for clear understanding. Thus, when we hear terms like microlearning or workflow learning or whatever else will emerge, tread carefully! There are some powerful ideas on tap, but people who don‘t bother to unpack the terms and detail how they differ in design and use shouldn‘t be trusted.

My message is twofold. For one, as consumers, watch out for these approaches. If someone‘s being glib, be wary! First, learn about the concepts and the myths, and then dig in. If there‘s a claim, take several steps. First, give it the ‘sniff test‘. If it doesn‘t make conceptual sense, and/or isn‘t relevant to you, back away. Second, track it back. Who‘s making this claim, and what‘s their vested interest? Is anyone independently saying the same thing? Importantly, is there anyone saying to the contrary, and what‘s their interest? Eventually, you might go back to the original research, but if you haven‘t been trained, I encourage you to look to the reputable purveyors of evidence-based perspectives.  

To the vendors, please help. We need to raise our industry to a professional level. Get someone to write your articles who knows what they‘re talking about. Don‘t let social media interns (let alone the “I‘ll write articles for you” cold-mailers) write your materials. Find someone who understands learning. More importantly, get someone who understands learning to actually guide your products and/or service design, and then you can tout scrutable opportunities.

In the long term, we can lift our industry to an evidence-based, professional standard. In the short term, we need to focus on questionable claims, and shoot for real value. Caveat malarkey!