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New recommended readings

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My Near Book ShelfOf late, I‘ve been reading quite a lot, and I‘m finding some very interesting books. Not all have immediate take homes, but I want to introduce a few to you with some notes. Not all will be relevant, but all are interesting and even important. I‘ll also update my list of recommended readings. So here are my new recommended readings. (With Amazon Associates links: support your friendly neighborhood consultants.)

First, of course, I have to point out my own Learning Science for Instructional Designers. A self-serving pitch confounded with an overload of self-importance? Let me explain. I am perhaps overly confident that it does what it says, but others have said nice things. I really did design it to be the absolute minimum reading that you need to have a scrutable foundation for your choices. Whether it succeeds is an open question, so check out some of what others are saying. As to self-serving, unless you write an absolute mass best-seller, the money you make off books is trivial. In my experience, you make more money giving it away to potential clients as a better business card than you do on sales. The typically few hundred dollars I get a year for each book aren‘t going to solve my financial woes! Instead, it‘s just part of my campaign to improve our practices.

So, the first book I want to recommend is Annie Murphy Paul‘s The Extended Mind. She writes about new facets of cognition that open up a whole area for our understanding. Written by a journalist, it is compelling reading. Backed in science, it’s valuable as well. In the areas I know and have talked about, e.g. emergent and distributed cognition, she gets it right, which leads me to believe the rest is similarly spot on. (Also her previous track record; I mind-mapped her talk on learning myths at a Learning Solutions conference). Well-illustrated with examples and research, she covers embodied cognition, situated cognition, and socially distributed cognition, all important. Moreover, there‘re solid implications for the redesign of instruction. I‘ll be writing a full review later, but here‘s an initial recommendation on an important and interesting read.  

I‘ll also alert you to Tania Luna‘s and LeeAnn Renninger‘s Surprise. This is an interesting and fun book that instead of focusing on learning effectiveness, looks at the engagement side. As their subtitle suggests, it‘s about how to Embrace the Unpredictable and Engineer the Unexpected. While the first bit of that is useful personally, it‘s the latter that provides lots of guidance about how to take our learning from events to experiences. Using solid research on what makes experiences memorable (hint: surprise!) and illustrative anecdotes, they point out systematic steps that can be used to improve outcomes. It‘s going to affect my Make It Meaningful  work!

Then, without too many direct implications, but intrinsically interesting is Lisa Feldman Barrett‘s How Emotions Are Made. Recommended to me, this book is more for the cog sci groupie, but it does a couple of interesting things. First, it creates a more detailed yet still accessible explanation of the implications of Karl Friston‘s Free Energy Theory. Barrett talks about how those predictions are working constantly and at many levels in a way that provides some insights. Second, she then uses that framework to debunk the existing models of emotions. The experiments with people recognizing facial expressions of emotion get explained in a way that makes clear that emotions are not the fundamental elements we think they are. Instead, emotions social constructs! Which undermines, BTW, all the facial recognition of emotion work.

I also was pointed to Tim Harford‘s The Data Detective, and I do think it‘s a well done work about how to interpret statistical claims. It didn‘t grip me quite as viscerally as the afore-mentioned books, but I think that‘s because I (over-)trust my background in data and statistics. It is a really well done read about some simple but useful rules for how to be a more careful reviewer of statistical claims. While focused on parsing the broader picture of societal claims (and social media hype), it is relevant to evaluating learning science as well.  

I hope you find my new recommended readings of interest and value. Now, what are you recommending to me? (He says, with great trepidation. ;)

The case for model answers (and a rubric)

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Human body modelAs I‘ve been developing online workshops, I‘ve been thinking more about the type of assessment I want. Previously, I made the case for gated submissions. Now I find another type of interaction I‘d like to have. So here‘s the case for model answers (and a rubric).

As context, many moons ago we developed a course on speaking to the media. This was based upon the excellent work of the principals of Media Skills, and was a case study in my  Engaging Learning book. They had been running a face to face course, and rather than write a book, they wondered if something else could be done. I was part of a new media consortium, and was partnered with an experienced CD ROM developer to create an asynchronous elearning course.  

Their workshop culminated in a live interview with a journalist. We couldn‘t do that, but we wanted to prepare people to succeed at that as an optional extra next step. Given that this is something people really fear (apocryphally more than death), we needed a good approximation. Along with a steady series of exercises going from recognizing a good media quote, and compiling one, we wanted learners to have to respond live. How could we do this?

Fortunately, our tech guy came up with the idea of a programmable answering machine. Through a series of menus, you would drill down to someone asking you a question, and then record an answer. We had two levels: one where you knew the questions in advance, and the final test was one where you‘d have a story and details, but you had to respond to unanticipated questions.  

This was good practice, but how to provide feedback? Ultimately, we allowed learners to record their answers, then listen to their answers and a model answer. What I‘d add now would be a rubric to compare your answer to the model answer, to support self-evaluation. (And, of course, we’d now do it digitally in the environment, not needing the machine.)

So that‘s what I‘m looking for again. I don‘t need verbal answers, but I do want free-form responses, not multiple-choice. I want learners to be able to self-generate their own thoughts. That‘s hard to auto-evaluate. Yes, we could do whatever the modern equivalent to Latent Semantic Analysis is, and train up a system to analyze and respond to their remarks. However, a) I‘m doing this on my own, and b) we underestimate, and underuse, the power of learners to self-evaluate.  

Thus, I‘m positing a two stage experience. First, there‘s a question that learners respond to. Ideally, paragraph size, though their response is likely to be longer than the model one; I tend to write densely (because I am). Then, they see their answer, a model answer, and a self-evaluation rubric.  

I‘ll suggest that there‘s a particular benefit to learners‘ self-evaluating. In the process (particularly with specific support in terms of a mnemonic or graphic model), learners can internalize the framework to guide their performance. Further, they can internalize using the framework and monitoring their application to become self-improving learners.

This is on top of providing the ability to respond in richer ways that picking an option out of those provided. It requires a freeform response, closer to what likely will be required after the learning experience. That‘s similar to what I‘m looking for from the gated response, but the latter expects peers and/or instructors to weigh in with feedback, where as here the learner is responsible for evaluating. That‘s a more complex task, but also very worthwhile if carefully scaffolded.  

Of course, it‘d also be ideal if an instructor is monitoring the response to look for any patterns, but that‘s outside the learners‘ response. So that‘s the case for model answers. So, what say you? And is that supported anywhere or in any way you know?

How to be an elearning expert

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I was asked (and have been a time or two before): “What’s the one most important thing you’d like to tell to be successful Ed Tech industry leader” Of course there wasn‘t just one ;). Still, looking at colleagues who I think fit that characterization, I find some commonalities that are worth sharing. So here‘s one take on how to be an elearning expert.

Let‘s start with that ‘one thing‘.   Which is challenging, since it‘s more than one thing! Still, I boiled it down into two components: know your stuff, and let people know.   That really is the core. So let‘s unpack that some more.   The first thing is to establish credibility. Which means demonstrating that you track and promote the right stuff.  

Some folks have created a model that they tout. Cathy Moore has Action Mapping, Harold Jarche has PKM, Con Gottfredson has the 5 moments of need, and so on.   It‘s good having a model, if it‘s a good, useful one (there are people who push models that are hype or ill-conceived at best). Note that it‘s not necessarily the case that these folks are just known for this model, and most of these folks can talk knowledgeably about much more, but ‘owning‘ a model that is useful is a great place to be. (I occasionally regret that I haven‘t done a good job of branding my models.) They understand their model and its contribution, it‘s a useful one, and therefore they contribute validly that way and are rightly recognized.

Another approach like this is owning a particular domain. Whether gaming (e.g. Karl Kapp), visuals (Connie Malamed), design (Michael Allen), mixed realities (Ann Rollins), AI (Donald Clark), informal (Jane Hart), evaluation (Will Thalheimer), management (Matt Richter), and so on, they have deep experience and a great conceptual grasp in a particular area. Again, they can and do speak outside this area, but when they talk about these topics in particular, what they say is worthy of your attention!

Then there are other folks who don‘t necessarily have a single model, but instead reliably represent good science. Julie Dirksen, Patti Shank, Jane Bozarth, Mirjam Neelen, and others  have established a reputation for knowing the learning science and interpreting it in accurate, comprehensible, and useful ways.  

The second point is that these folks write and talk about their models and/or approaches. They‘re out there, communicating. It‘s about reliably saying the important things again and again (always with a new twist). A reputation doesn‘t just emerge whole-cloth, it‘s built step by step. They also practice what they preach, and have done the work so they can talk about it. They talk the talk and walk the walk. Further, you can check what they say.  

So how to start? There are two clear implications. Obviously, you have to Know. Your. Stuff! Know learning, know design, know engagement, know tech. Further, know what it means in practice!   You can focus deeply in one area, or generate one useful and new model, or have a broad background, but it can‘t just be in one thing. It‘s not just all your health content for one provider. What you‘re presenting needs to be representative and transferable.  Further, you need to keep up to date, so that means continually learning: reading, watching, listening.

Second, it‘s about sharing. Writing and speaking are the two obvious ways. Sure, you can host a channel: podcast, vlog, blog, but if you‘re hosting other folks, you‘re seen as well connected but not necessarily as the expert. Further, I reckon you have to be able to write and speak (and pretty much all of these folks do both well).   So, start by speaking at small events, and get feedback to improve. Study good presentation style. Then start submitting for events like the Learning Guild, ATD, or LDA (caveats on all of these owing to various relationships, but I think they‘re all scrutable). I once wrote about how to read and write proposals, and I think my guidance is still valid.

Similarly, write. Learning Solutions or eLearn Mag are two places to put stuff that‘s sensibly rigorous but written for practitioners.   Take feedback to heart, and deliberately improve. Make sure you‘re presenting value, not pitching anything. What conferences and magazines say about not selling, that your clear approach is what sells, is absolutely true.  

Also, make sure that you have a unique ‘voice’. No one needs the same things others are saying, at least in the same way. Have a perspective, your own take. Your brand is not only what you say, but how you say it.

A related comment: track some related fields. Most of the folks I think of as experts have some other area they draw inspiration from. UX/UI, anthropology, software engineering, there are many fields and finding useful insight from a related one is useful to the field and keeps you fresh.

Oh, one other thing. You have to have integrity. People have to be able to trust what you say. If you push something for which you have a private benefit, or something that‘s trendy but not real, you will lose whatever careful credibility you‘ve built up. Don‘t squander it!  

So that‘s my take on how to be an elearning expert. So, what have I missed?

Overworked IDs

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I was asked a somewhat challenging question the other day, and it led me to reflect. As usual, I‘m sharing that with you. The question was “How can IDs keep up with everything, feel competent and confident in our work” It‘s not a trivial question! So I‘ll share my response to overworked IDs.

There was considerable context behind the question. My interlocutor weighed in with her tasks:  

“sometimes I wonder how to best juggle everything that my role requires: project management, design and ux/ui skills, basic coding, dealing with timelines and SMEs and managers. Don‘t forget task analysis and needs assessment skills, making content accessible and engaging. And staying on top of a variety of software.”  

I recognize that this is the life of overworked IDs, particularly if you‘re the lone ID (which isn‘t infrequent), or expected to handle course development on your own. Yet it is a lot of different competencies. In work with IBSTPI, where we‘re defining competencies, we‘re recognizing that different folks cut up roles differently. Regardless, many folks wear different competency requirements that in other orgs are handled by different teams. So what‘s a person to do?

My response focused on a couple of things. First, there‘re the expectations that have emerged. After 9/11, when we were avoiding travel, there was a push for elearning. And, with the usual push for efficiency, rapid elearning became the vogue. That is, tools that made it easy to take PDFs and PPTs and put it up online with a quiz. It looked like lectures, so it must be learning, right?

One of the responses, then, is to manage expectations. In fact, a recent post addressed the gap between what we know and what orgs should know. We need to reset expectations.

As part of that, we need to create better expectations about what learning is. That was what drove the Serious eLearning Manifesto [elearningmanifesto.org], where we tried to distinguish between typical elearning and serious elearning. Our focus should shift to where our first response isn‘t a course!  

As to what is needed to feel competent and confident, I‘ve been arguing there are three strands. For one (not surprisingly ;), I think IDs need to know learning science. This includes being able to fill in the gaps in and update on instructional design prescriptions, and also to be able to push back against bad recommendations. (Besides the book, this has been the subject of the course I run for HR.com via Allen Academy, will be the focus of my presentation at ATD ICE this summer, and also my asynchronous course for the LDC conference.)  

Second, I believe a concomitant element is understanding true engagement. Here I mean going beyond trivial approaches like tarting-up drill-and-kill, and gamification, and getting into making it meaningful. (I‘ve run a workshop on that through the LDA, and it will be the topic of my workshop at DevLearn this fall.)

The final element is a performance ecosystem mindset. That is, thinking beyond the course: first to performance support, still on the optimal execution side of the equation. Then we move to informal learning, facilitating learning. Read: continual innovation! This may seem like more competencies to add on, but the goal is to reduce the emphasis (and workload) on courses, and build an organization that continues to learn. I address this in the  Revolutionize L&D book, and also my mobile course for Allen Interactions (a mobile mindset is, really, a performance ecosystem mindset!).

If you‘re on top of these you should prepared to do your job with competence and confidence. Yes, you still have to navigate organizational expectations, but you‘re better equipped to do so. I‘ll also suggest you stay tuned for further efforts to make these frameworks accessible.  

So, there‘re my responses to overworked IDs. Sorry, no magic bullets, I‘m afraid (because ‘magic‘ isn‘t a thing, sad as that may be). Hopefully, however, a basis upon which to build. That‘s my take, at any rate, I welcome hearing how you‘d respond.

What about books | conferences?

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Responding to a frequent question  yet again, I decided to post an answer to the “what about books | conferences?” question.

And, as usual, the transcript.

Once again, after talking about how learning requires meaningful practice, I was asked the seemingly timeless question: “but what about books” Similarly, I regularly get “what about conferences”   So, for the record, let me say when and why books and lectures make sense. And when not. Hopefully I won‘t have to answer another “what about books | conferences” question.

To start, learning is action and reflection. That is, learning ‘outside‘ formal instruction. We act in the world and reflect on it to cement the lesson. It‘s slightly more complicated, because certain things, e.g. Geary‘s biologically primary things, may not really need reflection. Further some things may be really challenging to learn on your own even with reflection. But basically, doing things and reflecting (which can be reading, experimenting, writing/representing), etc is the way we learn on our own.  

Which, as I‘ve argued before, suggests that instruction  be designed action and guided reflection. That is, instructors should be choosing meaningful activities and scaffolding reflection around it. When we‘re designing for novices [link], in particular, when the learner doesn‘t know what‘s important nor why, we need to do the whole enchilada (darn, now I‘m hungry).

Which also means that when we‘ve segued beyond novice to practitioner (and beyond), we begin to know what‘s important and why, and we just need it. We want resources that can fill in the gaps. We want support for reflection.

So now we can explain why we can attend conferences, read books and articles, and the like. When we‘re deeply engaged in something, whether work or a passion, reading a book, listening to someone tell their story, and the like, serves as the necessary adjunct to our activity! They provide the complement to our own endeavors; the reflection to our action!

Now, hopefully, we‘ll never again need to discuss this. Realistically, we can point people here when we‘ get “what about books | conferences”? At least, that‘s my story, what‘s yours?  

Deep learning and expertise

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A colleague asked “is anyone talking about how deep learning requires time, attention, and focus” He was concerned with “the trend that tells us everything must be short.”   He asked if I‘d written anything, and I realize I really haven‘t. Well, I did make a call  for “slow learning” once upon a time, but it‘s probably worth doing it again.   So here‘s a riff on deep learning and expertise.

First, what do we mean by deep learning? Here, I‘m suggesting that the goal of deep learning is expertise. We‘ve automated enough of the component elements that we can use our conscious processes to make expert judgments in addressing performance requirements. This could be following a process, making strategic decisions such as diagnoses and prescriptions, and more. It can also require developing pre-conscious responses, such as we train airline pilots to respond to emergencies.  

Now, these responses can vary in their degree of transfer. Making decisions about how to remedy a piece of machinery that‘s misbehaving is different than deciding how to prioritize the new product improvements. The former is more specific, the latter is more generic. Yet, there are certain things that are relevant to both.  

Another issue is how often it needs to be performed. You can develop expertise much quicker with lots of opportunities to apply the knowledge. It‘s more challenging to achieve when there aren‘t as many times it‘s relevant in the course of your workflow. The aforementioned pilots are training for situations they never hope to see!

Before we get there, however, there‘s one other issue to address: how much has to go in the head, and how much can be in the world?   In general, getting information in the head is hard (if we‘re doing it right), and we should try to avoid it when possible. I argue  for backwards design, starting with what the performance looks like if we‘ve focused on IA (intelligence augmentation ), that is, looking for the ideal combination of smarts between technology (loosely defined) and our heads. As Joe Harless famously said “iInside every fat course there‘s a thin job aid crying to get out.”  

Once we‘ve determined that we need human expertise, we also need to acknowledge that it takes time! I put it this way: the strengthening of connections (what learning is at the neural level) can only be done so much in any one day before the strengthening function fatigues; you literally need sleep before you can learn more. And only so much strengthening can happen in that one day. So to develop strong connections, e.g. strong enough that it will be triggered appropriately, is going to have to be spaced out over time.  

This does depend on the pre-existing knowledge of the learner, but it was Anders Ericsson who posited the approximately 10K hours of practice to achieve expertise. That‘s both not quite accurate and not quite what he said, but as a rule of thumb it may be helpful. The important thing is that not just any practice will work. It takes what he called ‘deliberate practice‘, that is the right next thing for this learner. Continued, over time, as the learners‘ ability increases new practice focuses are necessary.

All that can‘t come from a course (no one is going to sit through 10000 hours!). Instead, if we follow the intent of the 70:20:10 framework, it‘s going to take some initial courses, then coaching, with stretch assignments and feedback, and joining a relevant community of practice, and….

We also can‘t assume that our learners will develop this as efficiently as possible. Unless we‘ve trained them to be good self-learners, it will take guided learning across their experience. Even if it‘s only at a particular point; most people who are pursuing a sport, hobby, what have you, eventually will take a course to get past their own limitations and accelerate development.

The short answer is that deep expertise doesn‘t, can‘t, come from a short learning experience. It comes from an extended learning experience, with spaced, deliberate, and varied practice with feedback. If you want expertise, know what it takes and do it. That‘s true whether you‘re doing it for yourself or you‘re in charge of it for others. Deep learning and expertise comes with hard work. (Also, let‘s make that ‘hard fun‘ ;).  

Book hiccups

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As much as writing books is something I do (and I’m immodestly proud of the outcomes), they don’t always come out the way I expect. And that turns out to be true for almost every one!  So here, for the record and hopefully as both mea culpas and lessons learned, are my book hiccups. And you really don’t have to read this, unless you want some things to check for.

After my first book,  Engaging Learning, came out, someone asked me “how do I know it’s really your book?” He had a valid point, because while there was a bio, there was no picture of me. Somehow, I just expected it (and if memory serves, they’d asked for one). Yet it didn’t appear on the dust jacket nor on the author page. In fact, the only Wiley book that  did have my picture ended up being the next one.

Shortly after my next book came out,  Designing mLearning,  I got an email asking for clarification. The correspondent pointed to a particular diagram, and asked what I meant. It turns out, in editing (they’d outsourced it, I understand), someone had reversed the meaning of a caption for a diagram! Worse, I hadn’t caught it. At this time I can no longer find what it was, but it was an unhappy experience.

For my third book,  The Mobile Academy, I asked my friend and colleague John Ittelson to write the preface. And somehow, it wasn’t in the initial printing!  That was a sad oversight, but fortunately they remedied it very quickly.

I had been upset by how expensive the first two books were. Consequently, I was pleased to find out that my fourth,  Revolutionize  Learning & Development, that I really wanted to see do well, was priced much more reasonably. Of course, then I found out why; it was made with paper that wasn’t of the best quality. At least it’s affordable, and I continue to hear from people who have found it useful.

I’m happy to say that the next one,  Millennials, Goldfish & Other Training Misconceptions  has been hiccup free. After switching to ATD Press (they’d been a co-publisher of the previous book), they did a great job with the design, taking my notion of humorous sketches for each topic and executing against it graphically. It’s been well-recognized.

Unfortunately, as I just found out after getting my mitts on the most recent one,  Learning Science for Instructional Designers,  two of the four blurbs I solicited from esteemed colleagues don’t show up in the book!  They do show up on the ATD site, at least (and of course they’re on my own page for the book). I didn’t get a copy of the back cover beforehand, so I couldn’t have checked. My apologies to them. I checked, and it turns out having to do with a space issue because of book formatting. 🤷  Other than that, I’m  as  happy with this book as the last (that is, really happy)!

I can say that I’ve always tried to write in a way that focuses on the aspects that relate to our mental architecture. The goal is that as the technology changes, the implications are still appropriate. Our brains aren’t changing as fast at the tech! I guess I’m just not ready to accept planned obsolescence, so I’m keeping them available.

So there you have it, the book hiccups that can come with publishing. If you’ve made it this far, at least I hope you have some more things to check to make sure your books come out as good as possible.

 

How I write

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I’d queued up this topic for a post, and then a conversation with a friend and colleague moved it to the front. We were talking about our process, and he pointed me to an article that nicely catalyzed my thinking. So here’s a brief post about how I write my books (written, of course).

The article my friend pointed me to was titled: “The Simple Way To Outline A Nonfiction Book”, and it’s nicely resonant, and a bit deeper, than my own approach. If you’re thinking about writing a book, I think this is very good advice. And the author even provides a template to get you started. And you should be thinking about writing. It does a couple of things: it forces you to think through your topic, and if it comes to fruition, it gives you some collateral. Be aware: the advice I’ve found to be true is that you make more money giving the book away. It’s a better business card!

So what the article suggests, and what aligns with what I do, is outline. That is, I outline the whole book. He suggests first doing the table of contents, generating your chapters first, then elaborating each. I do a bit more, creating a multi-level outline (often as much as up to five levels, though the innermost level often is just notes to myself what I’ll put in that section). However, this isn’t a one pass thing, it’s iterative. I’ll revisit it a time or two beforehand, and then as I write sometimes I restructure.

Which is why I need industrial strength outlining in my writing package. I want to be able to manipulate the whole document, moving sections. Which is why I use Microsoft Word, I just haven’t found that Pages can do it. Similarly, Google Docs is too awkward, and I never got my mind around Scrivener.

From there, he has a template for chapters as well. It reflects what I’ve seen in many non-fiction books, starting the chapter with a story that sets up the topic. I haven’t been able to get that formulaic, but it might be better!  I tend to write to the outline, but I’m not always telling a story to start, but I do try to set the stage with some interesting element.

Different books have emerged differently. My first,  Engaging Learning, on designing serious games, just flowed. Probably because I’d been thinking about the topic for over a decade… My second one,  Designing mLearning, was much more incremental. I’d write some, then think of something else to add up above, and then maybe a restructure of a bit, and continue, and add a bit more above, and… It was quite the effort to get to the end!  The others have varied.

My most recent effort (I’m working on a ‘Make it Meaningful’ text; how it manifests is still an open question) is an interesting case, since I’ve restructured it somewhat once already, and I think it needs a more major overhaul.  It’s partly that I’m still exploring (and people are lobbing interesting things my way). Also, it’s partly that in trying to incorporate some of my earlier stuff, I was inconsistent. It’s just that even with structure like an outline, you write in spurts, and they don’t always proceed smoothly.

Even in my more immediately forthcoming book,  Learning Science for Instructional Designers, I’d find  that I’d written about the same concept in two different places. While a text is linear, the ideas are interconnected, and can appear more than once in any path through. However, you have to choose one, and saying the same thing again is redundant.

By the way, some of that awareness comes after writing. I’ll admit that it’s an incredible ego crush to get back feedback from the editors: copy and proof. I feel stupid with all the (virtual) red ink I get! Yet, I also see how my writing changes from session to session, and having someone pull it together and point out some reliable flaws helps me improve. I completely value my editors, and am so grateful to them.

Your mileage may vary. If you don’t have a process and structure, however, you’ll struggle more than if you do. Recognize you’ll struggle, at first, and that you should allocate appropriate time. Also, each book is unique and will require its own flow, so also allocate time to discover that on subsequent efforts. Also recognize that even if you block off regular time slots to work, and set goals for those slots (and I don’t do either, by the way, I grab time when I can), you’ll still need to allocate time for revisions and even restructuring.

However, the real value is sharing your learnings. I’ve argued before that you should speak at conferences. If your ideas persist to create a coherent whole, you should consider putting them into book form. Further, if you’ve ambitions to stand out, it’s a useful way. So you should write. In your own way, of course. This is just how I write, but writing, I believe, is a good thing.

 

 

Animation thoughts

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Sparked by a conversation, I generate some animation thoughts.

And, as always, a transcript.

In a conversation the other day, my colleague mentioned how she was making a practice of creating animations. I found this interesting, because while I think animations are important, I don‘t do them all that much (or so I thought). Particularly intriguing was the notion of what principles might guide animations, including when to use them. I was prompted to reflect, and so here are some animation thoughts.

First, let‘s be clear what I mean. I‘ve argued that we don‘t use graphic novel/comic formats enough, and that likewise applies to cartoons. Which are also known as animations. Yet, that‘s not really what I‘m talking about. I think we could use them more, but that‘s another reflection.

Instead, here I‘m talking about animated diagrams. And I think there are times when these are not just engaging, but cognitively important. Diagrams map conceptual relationships to spatial ones, and can add additional coding with color and shape. Animations add the dimension of time, so these relationships can change. In my categorization, these are dynamic diagrams, useful when the conceptual relationships change in important ways depending on other factors.

Interestingly, in the conversation, it came up what one form of her animations were diagram builds.  I use diagrams a lot, not only to communicate, but as a tool for my own understanding! And, I‘d done some builds, but after Will Thalheimer‘s Presentation Science course I realized I needed to do that more systematically (and now do so).  Building diagrams is helpful. Cognitively, a diagram can be overwhelming if there are too many elements. By starting at one point, and gradually adding in other elements, you can prevent cognitive overload. And in a presentation, in particular, you want to highlight important points.  

However, I also think that there are things worth indicating how they work dynamically. Like how a content system would work, e.g. context and rules combining to pull content out by description. Or how coordinates change based upon trigonometric values. I haven‘t done much of this, for the simple reason that I don‘t have a good animation tool. And, yes, I‘m aware that you do motion in PowerPoint and/or Keynote, but I haven‘t gotten into it. Time for a skill upgrade!

There are problems with animations, and guidelines. John Sweller‘s cognitive load plays out with Dick Mayer‘s work on multimedia research (as captured in his book with Ruth Clark: eLearning and the Science of Instruction), as indicated above. Thus, you shouldn‘t try to have people read text while watching visual dynamics (use audio). Also, you should help people focus attention by removing extraneous details and/or highlighting the appropriate focus.  

The general principles of media apply as well. Accessibility suggests some alternate representations. Timing suggests having a pause ability for any animation longer than a certain time, and of course the ability to replay. Similarly, the animation design should use appropriate white space, highlighting, and other aspects that make it visually clear and appealing.  

Overall, I‘d suggest that there are times when animations are the best option for conveying dynamic conceptual information. To use them, however, you have to take into account our cognitive limitations. So, these are some of my animation thoughts. I welcome yours.  

If not the myths person, then…?

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There’s a potential belief that I’m the ‘myths‘ person, and I’ve both principled and practical reasons to try to counter that. Here’s my thinking.

And, as always, the text.

I’ve a dilemma. These days, if someone posts some learning myth, people tend to let me know. And I don‘t really mind, but I do worry that it buckets me as the ‘myths‘ person. Despite the book, that‘s not really my role. Another way to bucket me would be the learning science person (my next book). That‘s better, but maybe still not quite accurate. So what the <x> person am I?

Yes, I did write a book about myths. But the purpose there was to point out bad things we‘re doing, so we can instead do better things. In fact, that‘s included: what you should do instead. It‘s really about better design, not about myths.

Similarly, the learning science book coming out is a primer on the underlying cognitive science and the implications for learning design. With the emphasis on learning design, not learning science. It concludes with two chapters on the implications and the important bits. So it‘s not about learning science per se, but as a basis for what we do with it.

Really, what I am is a learning science translator, not a myths debunker. Practically, that‘s because there‘s essentially no money in being a myths debunker. They might hire a talk, but what‘s the business model? Are you going to hire me to come in and debunk your myths? Er, that‘d be no. But there‘s a principled reason, too.  

It‘s about redesigning your learning design processes to better incorporate learning science (and avoid myths). The evidence is that the processes aren‘t well done, because we see too much bad learning. And the rationales are myriad: lack of knowledge, focus on efficiency, tool orientations, and more. Consequently, the services are similarly varied: workshops on learning science-informed design, consulting on the minimal changes to keep impacts on budget low but increase the effectiveness of the outcomes, and of course beyond: to performance consulting, informal learning, and more.

Because, L&D should properly be aligned with learning (and cognitive) science. And there are many ways to improve. That‘s what I‘m about, and that‘s why I‘m here. You can think of it as learning engineering (applied learning science), but that‘s a term still in flux in terms of meaning, since it also can mean the folks who spin the bits on complex platforms for adaptive learning, or the folks who analyze data to improve outcomes.  

I‘ve been recently calling myself a learning experience design strategist. Which is conceptually accurate, and yet unwieldy (since no one knows what it means). Yet it‘s about being strategic in learning experience design: creating processes that successfully integrate learning science with engagement to create outcomes that are effective, even transformative.

There are lots of things I do:  

  • Improve learning design processes to make learning more engaging and effective
  • Architect design approaches to address learning needs
  • Understand new technologies’ ability to enhance   learning experiences
  • Educate clients, audiences, and employees about the nuances of learning design
  • Review designs to improve effectiveness and engagement  
  • Convince clients (internal and/or external) and audiences about the value of learning science-based approaches
  • Interpret learning science and engagement research into practical guidelines

All of these are focused on being strategic about learning design. And I struggle to find another term: learning architect, learning strategist, and more. Still, there are several colleagues who are myths debunkers and learning science translators, and I‘ll suggest that you should follow, listen to, and most importantly, hire us. So, I’m not the myths person, but we do need more people applying learning science appropriately, and getting help to do so well. So whatever you want to term my role (suggestions welcome ;), do apply what we‘re talking about. Here‘s to better learning design!