Search Results for: engag

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‘ ;).  

Sparked by a conversation, I generate some animation thoughts.

And, as always, a transcript.

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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.  

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.

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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!

This is the third of four posts about making learning meaningful. Here, I talk about the implications for some key learning elements.

And, as always, the text.

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This is the third post about how to ‘make it meaningful‘. I talked about tricks and tips in the previous one, and here I want to talk about the implications for elements in creating experiences that matter. Here, I‘ll talk about Introductions, Examples, Practice, and Closings.

The introduction first, of course, hooks them in as we talked about in the first post. That might even happen before the learning experience introduction, though you will want to reiterate the WIIFM.   I like to use what I call a ‘motivating‘ example, that shows the consequences from having (or not) the skill(s) addressed. It‘s not a reference example that shows the whole process, but instead just makes clear the outcomes of this in a way the learner ‘gets‘.  

In addition to the cognitive necessity of reactivating relevant knowledge (which can be done in an engaging way), we want to also set appropriate expectations about the coming experience. A mismatch can undermine learner motivation. So, if there are things that they won‘t expect (unless that‘s deliberate), ensure that they have fair understandings.  

We also want to ensure that they understand what the outcomes will be. This does not mean sharing our design objectives, but instead the objectives that they care about. Rewrite them as (again) the WIIFM that they‘ll get out of it. The point being that basically we‘re opening the emotional as well as the cognitive story.

Examples are modeling the application of the model (which I‘m not covering here) to a context. These are important to help the learner understand how the skill gets applied to particular situations. From a cognitive standpoint, there are a number of elements such as showing the thinking and covering an appropriate suite of contexts. From an engagement perspective, however, these should be engaging stories (see the previous post). There should be a challenge, and the struggle of solving, and finally an outcome (including bad ones).  

The spread across contexts necessity plays out in practice, too. And, so too, does story. From an engagement perspective, as we discussed last week, we need appropriate challenge, and a settings that‘s both appealing to the learner and relevant to the goal. This is the biggest point at which creativity comes into play. Getting this right is key.

And, just as we opened the emotional experience with the introduction, we need to close it too. In addition to the usual ‘further directions‘ and re-contextualization of what they‘ve learned, we have some engagement aspects. We should acknowledge the learner‘s effort and accomplishments, and signify their transition to a new state of being. This could include connecting them to their new community of practice.

There‘s more, and this order is not the one you‘d use in design, but these are the critical elements. There‘re more details to this, of course And, if you‘re interested in the more, I‘ll encourage you to sign up for the workshop. This is the topic of the third week!   Of course, it‘s a full workshop, so in addition to the content, we‘ll have live sessions to workshop some ideas and discuss what we‘ve done, and assignments with personal feedback.   Hope to see you there! More in my next post.

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All posts in the Make It Meaningful series:

First: Hook

Second: Tips’n’Tricks

Third: Elements

Four Process

This is the second of four posts where I’m talking about the next step beyond trivial engagement. Here I talk about some tips ‘n’ tricks that help us take our learning designs deeper in meaning.

And, as always, the text.

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This is the second post about how to ‘make it meaningful‘. I talked about some tricks to maintain engagement in the previous one, and here I want to talk about what this means for the elements of learning. Here, I‘ll talk about story, challenge, exaggeration, and humor.  

First, a good experience has the characteristics of a lived story. To me, there are three major components: goal, role, and world. The goal is what the learner needs to achieve. (We choose this so that the learner won‘t achieve it unless or until they understand the necessary elements.) The role is the character that the learner is playing in trying to achieve this goal. They should be aligned. And the world is the context in which this is happening. The fantasy wrapping. Again, alignment.

The challenge to actually achieving the goal is important as well. This is what leads to learning and engagement. The alignment between Csikszentmihalyi‘s Flow and Vygotsky‘s Zone of Proximal Development lets us know that there‘re two extremes: ‘so difficult as to be frustrating‘ and ‘so easy as to be boring‘. In between is where learning, and engagement, happen. This increases as the learner‘s abilities do.

Another element to keep things from being boring is some exaggeration. That is, most of life is mundane, but our work is challenging. In the learning experience, however, what would seem challenging at work seems mundane because there is nothing really at stake.  

Thus, we can exaggerate: let‘s not work on just a patient, but the rebel leader‘s daughter, or not just a business deal, but the one that will save the company!   And, typically, we keep this down to about one level above real life, to not violate the willingness to suspend disbelief.

Finally, we can talk about humor. It‘s challenging to do, as it can be culturally specific, but appropriately applied humor can build trust and safety, and support greater exploration. And, if we realize business is a culture, we find some universals we can leverage. Timing matters, too, not just in the ‘letting a joke land‘ sense, but where and when humor‘s appropriate.  

There‘s more, but these tips ‘n’ tricks are typically missed opportunities. There‘re more details to this, of course. And, if you‘re interested in the more, I‘ll encourage you to sign up for the workshop. This is the topic of the second week!   Of course, it‘s a full workshop, so in addition to the content, we‘ll have live sessions to workshop some ideas and discuss what we‘ve done, and assignments with personal feedback.   Hope to see you there! More in my next post.

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All posts in the Make It Meaningful series:

First: Hook

Second: Tips’n’Tricks

Third: Elements

Four Process

I believe that in addition to learning science, the other key element of Learning Experience Design is engagement. More than the trivial tarting-up, however, trying to make it meaningful. I’ve put together four posts covering some of the key elements, and this is the first. I’m talking about setting the ‘hook’ (and, really, the key element).

And, as always, the text.

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In anticipation of my upcoming ‘Make it Meaningful‘ workshop through the Learning Development Accelerator, I wanted to provide an overview of the topic. I think it‘s important to share some of the elements that are on tap. There‘re four parts: 1. The Hook, 2. Elaborations, 3. Elements, and 4. Process.  

Today, I want to talk about the core principle that makes it work. To do so, I want to start with the structure that I suggest is at core what you need to initially hook folks. And that takes 3 separate elements that the learner needs to ‘get‘:

1. You know, I do need this
2. And, I don‘t already know it
3. And, this experience will change that

That‘s it. I‘ll posit that if you can achieve this, you‘ll have a learner willing to start the learning experience. And, as a concomitant claim, that we can do this. Let me elaborate.

I think that we can get people to recognize that they need it. It‘s actually an implication from Deci & Ryan‘s Self-Determination Theory that Matt Richter of the Thiagi group helped me understand. I claim that we need learners to see the WIIFM, the What‘s In It For Me. And I‘ll suggest this comes from consequences, either the positive consequences of knowing it, or the negative ones of not knowing it. It‘s not as good, perhaps, as true intrinsic motivation, but it‘s good enough, and more reliable.

Then, you can‘t have them thinking they already know it. In general, that might not be a problem, but in certain circumstances it can be. For instance, in a truck-selling situation, the sales folks believed they already knew how. We had to make it very clear that they didn‘t before they were willing to engage. And, once they were aware, they were quite competitive in trying to rectify the situation.

Finally, learners have to believe that what you‘re doing will effectively accomplish this (in a reasonable fashion). And this may be particularly problematic, if they‘ve previously experienced engaging but not effective, or even worse, boring content.   You may have to do some extra work to convince them that you‘ve really changed!

Once you‘ve got your learners hooked, you‘ll have to deliver, but if you don‘t hook ‘em up front, it‘ll be of no avail. To paraphrase, you may be able to bring a learner to learning, but you can‘t make ‘em think. We‘ll talk about this in the next segment.  

So, get the WIIFM, and help them see that they need it. There‘re more details to this, of course. And, if you‘re interested in the more, I‘ll encourage you to sign up for the workshop. This is the topic of the first week!   Of course, it‘s a full workshop, so in addition to the content, we‘ll have live sessions to workshop some ideas and discuss what we‘ve done, and assignments with personal feedback.   Hope to see you there! More in my next post.

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All posts in the Make It Meaningful series:

First: Hook

Second: Tips’n’Tricks

Third: Elements

Four Process

I know, I know, I’ve been doing a lot of updates: books, workshops, and now webinars. I promise I’ll get back to my regular posting on learning things, but the benefit of these, unlike books or courses, is that they’re free. And several are coming up! So I thought I’d at least let you have a chance. So, here’s an update on my webinars.

First, I’ll be talking for eLearning Learning on the 27th of January at 11AM PT (2PM ET). They were interested in discussing about the impact on Covid, and of course I’m taking it in an aspirational direction. I’m presenting about how we’re not well aligned with how we think, work, and learn, and what that looks like in general, and in particular online.

Then, I’m doing a ‘make it meaningful’ presentation for iSpring on 25 Feb at 9AM PT (noon ET). The coordinates to sign up are here.   It aligns with their theme and I’ll get into some top-level issues.

Then, on 18 March, at 10AM, I’ll talk with Barbara Covarrubias Venegas on facilitating innovation. Since here topic is on virtual space, I suspect we’ll focus there. It’s a LinkedIn Live event, you can see it as one of her list of interviews.

Finally, at 10 AM PT (1PM ET) on Thursday the 13th (not Friday), I’ll be talking learning science for ATD.  That, as yet, doesn’t have a page AFAIK. More info as it emerges.

(BTW, there’s a recording of my webinar last week on learning science.)

This actually presents a pretty fair coverage of my areas of focus, so if any one (or more) is of interest, here’s a chance to see my thoughts. My general focus, as I like to quip, is on those things L&D isn’t doing, and what they’re doing badly. Which is most everything! 😁  I’m sure more webinars will eventuate, but that’s it for now. So there you go, an update on my webinars. Hope to see you there!