Archives for July 2018

Reading List?

31 July 2018 by Clark 1 Comment

I saw another query about ‘reading list recommendations’ (e.g. as an addition to Millennials, Goldfish, Other Training Misconceptions ;), and I thought I’d weigh in, with a different spin. What qualifies what books should you read? Maybe your level of expertise? So, here is a reading list for what books should you read depending on where you are as a designer.

Note, this is a relatively personal list, and not the mainstream ID texts. It’s not Gagné, Brown & Green, Dick & Carey, or even Horton. These are books that either get you going without those, or supplement then once you are going. And they’re ones I know, and I can’t read everything!

Beginning (e.g. the accidental instructional designer):

Cammy Bean’s The Accidental Instructional Designer. Now, I think the fact that this book needs to exist is kind of an indictment of our field. Do we have accidental surgeons? Not to the extent we prepare for them! Still, it’s a reality, and Cammy’s done the field a real service in this supremely practical and accessible book.

Michael Allen’s Guide to eLearning. Michael’s got the scientific credibility, the practical experience, a commitment to making things right, and a real knack for simplifying things. This book, with it’s SAM and CCAF framework, provides a very good go-to-whoa process for designing learning experiences what will work.

Practicing Designer:

Julie Dirksen’s Design for How People Learn is a really accessible introduction to learning science, boiling it down into practical terms as a process for design. With great illustrations, it’s an easy but important read.

Donald Norman’s Design of Everyday Things is pretty much key reading for anyone who designs for people. (OK, so I’m biased, because he was my Ph.D. adviser, but I’m not the only one who says so.) Not specific to learning, but one of those rare books that is pretty much guaranteed to change the way you look at the world.

Going deeper:

Brown, Roediger, & McDaniel’s Make it Stick. 10 points from learning science about what works.

Ericsson’s Peak, a book about what makes real expertise, with a focus on the nuances of deliberate practice.

Patti Shank’s new Make it Learnable series gets into specifics on learning design. Comprehensive and yet accessible.

Ruth Clark’s eLearning & The Science of Instruction (with Dick Mayer) and/or Efficiency in Learning with Sweller & Nguyen).

Of course, there are separate topics:

Mobile: my own Designing mLearning and anything by Chad Udell (e.g. Learning Everywhere)

Games: my own Engaging Learning and anything game from Karl Kapp (e.g. the new book with Sharon Boller, Play to Learn).

Realities: Koreen Pagano’s Immersive Learning, and perhaps Kapp & O’Driscoll’s Learning in 3D as a foundation.

Performance Support: Allison Rossett’s Job Aids & Performance Support and Gottfredson & Mosher’s Innovative Performance Support.

Social: Conner & Bingham’s The New Social Learning and Jane Bozarth’s Social Media for Trainers.

Going Broader:

Informal: Jay Cross’ Informal Learning. Talking about the rest of learning besides formal.

Performance Ecosystem: Marc Rosenberg’s Beyond eLearning (the start), and/or my Revolutionize Learning & Development. About L&D strategy; going beyond just courses to meet the real needs of the org.

Going Really Deep (if you really want to geek out on learning and cognitive science):

Daniel Kahnemann’s Thinking Fast and Slow about how our brains don’t work logically. Or the behavioral economics stuff.

Andy Clark’s Being There about the newer views on cognition including situated cognition.

Of course, there’re lots more, depending on whether you’re interested in assessment, evaluation, content, or more. But this is my personal and idiosyncratic set of recommendations. There are other people I’d point you to, too, but this is the suite of books you can, and should, get your mitts on. Now, what’s on your list?

Social Cognition

25 July 2018 by Clark Leave a Comment

In the two preceding posts, I discussed situated and distributed cognition. In this closing post of the series, I want to talk about social cognition. They’re related, and yet each needs explicit consideration. If we don’t know how we think, work, and learn, we can’t optimally support both performance in the moment and continual innovation over time.

The traditional definition of social cognition is how we think about social interactions. But here I’m emphasizing instead the fact that our thinking isn’t just in our heads or our tools, but also across our partners. That’s partly distributed cognition, but I want to emphasize it. And this is true for formal and informal learning as well as performing.

There are two ways to think about this. For one, we benefit from formal social interactions as ways to get richer interpretations. It works the same way when we are problem-solving: working together (under constraints) increases the likelihood of the best outcome. As I like to say, the room is smarter than the smartest person in the room if you manage the process right. The implications of this are several.

First, we need to make sure we have the right constraints. When we have people working together, it helps if it’s the right people and the right environment. We know that diversity helps, as long as there is overlap in values. Similarly, it needs to be psychologically safe to contribute, the environment helps to be open, and there needs to be time for reflection.

There’re also benefits to mentoring and coaching, helping people in the moment. We want to succeed, and we like to be challenged, and we learn when we are, so having scaffolding helps. Developing coaching and mentoring skills is a good investment in the workplace.

There’re also times when we want help, or someone else does and we can help. That is, we need to support serendipitous inquiry. It helps, by the way, to assist people in learning how to ask questions or answer them in useful ways. There also needs to be the channels to accomplish these goals.

Recognize that there are times when the answer can come from the network, not our own efforts. Particularly if things are changing fast, or the situation’s unique or hard to anticipate. In fact, it frees us up to do more if we take advantage of that as often as possible! It takes nurturing the networks to become a community so that the answer’s likely to be right.

The point being, there are lots of considerations to making the ecosystem sociable as well as effectively distributed and situated. If you want to optimize the environment, it helps to have the latest understanding of the users of that environment. Hope this makes sense, and in the spirit of social, I welcome your thoughts and comments!

Distributed Cognition

24 July 2018 by Clark Leave a Comment

In my last post, I talked about situated cognition. A second, and related, cognitive revelation is that thinking is distributed between our heads and the world. That is, the model that it all occurs between the ears doesn’t recognize that we incorporate external representations are part of our processing. Hutchins, in his Cognition in the Wild, documented a variety of ways that our thinking is an artefact of our tools and our models.

So, for example, navigation typically involves maps as well as thinking. Business reasoning is typically accompanied by tools like a spreadsheet. We use diagrams, tables, graphs, charts, and more to help us understand situations better. And we are unlikely to be able to do things like long division without paper and pencil or a calculator. This means that putting everything in the head isn’t necessary. And this is just what we should be doing! Designing for the right distribution of tasks between world and mind(s) is the optimal solution.

We know that it’s difficult to get things in the head (how hard is it to learn, say, to drive), and therefore undesirable anyway. It’s about designing solutions that put into the world what can be in the world, and then putting into the head what has to be in the head. This includes performance support in a variety of ways. It also should address what we consider to be worth training.

When we want to optimize performance, we should recognize that we need a bigger picture. We need to consider the person & tools, or people & tools, as a whole entity when it comes to achieving the end goal. This is also true for learning. Our reflective representations are part of our thinking process. So, too, our collaborative representations.

We are better thinkers and learners when we consciously consider tools, and their availability in the ecosystem. In fact, our ecosystem is the tools and people we have ‘to hand’, accessible in or from the workflow. And elsewhere, in our times for reflection, and discussion. So, have you optimized your, and your organization’s thinking and learning toolset?

Situated Cognition

18 July 2018 by Clark 5 Comments

In a recent article, I wrote about three types of cognition that are changing how we think about how we think (how meta!). All are interesting, but they also have implications for understanding for supporting us in doing things. I think it’s important to understand these cognitions, and their implications. First, I want to talk about situated cognition.

The psychological models of thinking really started with the behavioral models. The core argument was that we couldn’t look ‘inside the box’, and had to study inputs and outputs. Cognitive psychology was a rebellion from this perspective. The new frameworks started showing that we could posit quite a bit about what went on ‘in the box’. We got concepts like sensory, working, and long-term memory, and processes like attention, rehearsal, encoding, and retrieval. With most of our learning prescriptions. However, both were about the ‘the box’.

However, the observed behavior didn’t match the formal logical reasoning that underpinned the model. We needed new explanations. The computational model fell apart. And, despite rigorous attempts to create logical models that described human behavior, they were awkward at best. The shift came when Rumelhart & McClelland, in their PDP book, described what became known as neural networks. Associated with this was a new model of cognition.

What gets activated in the brain is not a reliably pure representation, and is strongly affected by the context. Thinking is ‘situated’ in the context it arises in. If our thinking is the emergent behavior of patterns across neurons, and those patterns are the result of both internal and external stimuli, then we’re very strongly influenced by what’s happening ‘in the moment’. And that means that we can be captured (and fooled) by elements that may not even be consciously processed.

What this means in practice is that it’s harder than we think to get reliable performance across a range of conditions. That we should ensure that patterns are generated across ‘noise’ so that they’re reliable in the face of the appropriate triggers, despite any accompanying contextual patterns. and recognize that decisions can be biased, and design scaffolding to prevent in appropriate outcomes. Developing mental models that provide reasoning abilities about causes and outcomes are useful here. This flexibility is advantageous (and why machine learning struggles outside it’s range of training), but we want to tap into it in helpful ways.

Our approaches should reflect what’s known, and therefore we need to keep up. Situated cognition is a perspective that’s relevant to more effectively supporting individual and organizational performance and learning. So, what is your thinking about this?

Designing with science

17 July 2018 by Clark 1 Comment

How should we design? It’s all well and good to spout principles, but putting them into practice is another thing. While we always would like to follow learning science, there’re not always all the answers we need. I was thinking about this with a project I’m working on, and it occurred to me that there might be some confusion. So I thought I’d share how I like to think and go about it, and see what you think.

So, first of all, you should go with the science. There are good principles around in a variety of forms. Some good guidance comes in books such as:

eLearning & the Science of Instruction (Clark & Mayer)
Design for How People Learn (Dirksen)
the Make it Learnable series (Shank)
and less directly but no less applicably, Michael Allen’s Guide to eLearning

There’s also ATD’s Science of Learning topic (with some good and some less good stuff). And the 3 Star Learning site. Both of these, of course, aren’t as comprehensive as a book. And, of course, you can also go right to the pure journals, like Instructional Science, and Learning Sciences, and the like, if you are fluent in academese. For that matter, I’ve a video course that is about Deeper Instructional Design, e.g. a design approach with learning science ‘baked in’.

But what I was thinking of what happens when they don’t address the specific concern you are wondering about. The second approach I recommend is theory. In particular, Cognitive Apprenticeship (my favorite model; Collins & Brown), or other theories like Elaboration Theory (Reigeluth), Pebble in a Pond (Merrill), or 4 Component ID (Van MerriÃ«nboer). Or, arguably more modern, something from Jonassen on problem-based learning or other more social constructivist approaches. They’re based on empirical data, but pulled together, and you can often make inferences in between the principles. While the next step is arguably better, in the real world you want a scrutable approach but one that gets you moving forward the fastest.

Finally, you test. If science and theory can’t provide the answer, you either wing it, but it’s better if you set up an experiment. Ideally, with your sample population. So, for instance, you don’t know whether to place the learner’s role in the simulation game as a consultant to many orgs or as a role in one org with many situations. There’re tradeoffs: in the former it’s easier to provide multiple contexts for practice, but the latter may be more closely aligned with job performance. You can test it, and see what learners think about the experience. Of course, it may be that in the process of just designing both that you have some insight. And that’s ok.

And, if you’re a reflective practitioner (and we should be), you might share your findings. What did you learn? Learning science advances to the extent that we continue to explore and test. Speaking of which, how does this approach match with what you do?

Organizational Psychology?

13 July 2018 by Clark 1 Comment

I read an article calling for organizational psychology and the things these folks do for companies. And, interestingly, many of the tasks seem like things that I’ve been calling for L&D to do. So now I have to ask what’s the relationship between these two areas?

My background is psychology, specifically the cognitive kind (ok more cog sci than just psych, but still). And so I’ve been pushing the idea of doing a cognitive analysis of organizations, and incorporating new understandings of cognition in how we run our companies, and more. The point being that we need to align how our organizations operate with how our brains do.

In a sense, then, I’m arguing for a psychological approach to organizations. This includes best principles across the board: working together, learning alone, etc. Yet, I’m typically talking to and about Learning & Development (even when I argue it needs a revolution). Am I missing the forest for the trees?

Now, it’s clear that the formal role of organizational psychology is bigger. It’s about hiring, and incentives, and occupational stress and a number of other things that I normally don’t consider. And, it doesn’t seem to be much about technology, the approaches to innovation seem limited, and some of the things it investigates seem more like outcomes. Yet it also includes training & workforce development, culture, and more.

I also have to say that it’s history seems to be in behavioral psychology. It appears (on the surface, mind you) to be a bit mired in thinking linearly, not networked. Of course, I’m probably biased here, and this is true for L&D too! There’re probably pockets of modernity as well.

So is L&D a subset? I really don’t know. I’d like to hear what you have to say on it. Perhaps my arguments really are (cognitive) organizational psychology. In another sense, I’m not sure it’s important. It’s not so much where you come from as what you are about, and the methods you use. Still, this is a question I’d like to hear thoughts on. Is there a definitive answer?

Why L&D Should Lead

10 July 2018 by Clark 1 Comment

So, I’ve seen a bright future for L&D. It’s possible, and desirable. But is it defensible? I want to suggest that it is. L&D should be the business unit with the best understanding of our brains (except, perhaps, in a neurology company, e.g. medical, or a cognitive company, e.g. AI). And I’ve argued that’s a key role. So, if we grasp that nettle and lead the change, we could and should be leading the way to a brighter new future for organizational success.

Look, cognitive science is somewhat complex. In fact, the human brain is arguably the most complex thing in the known universe! However, we have a good understanding of cognition for the purposes of guiding learning and performance in the workplace. Or, as I like to say, understanding how we think, work, and learn. Moreover, we really can’t (and shouldn’t) be doing our jobs unless we have that knowledge. (I have a workshop that can help. ;)

Now, it’s also becoming a cliche that the organizations that learn fastest will be the ones that thrive (not just survive, or not!). We must learn, individually and together. And knowing how to have people work and play well together, representing, reflecting, collaborating, and more should be L&D’s role. We should be the ones who know the most and best about how to do those things in consonance with how our cognitive architecture works.

And, to be clear, there are lots of practices in organizations that are contrary to the best learning. Fear, lack of time for reflection, micro-management, old-school brainstorming, the list goes on. Without knowledge, we may firmly be convinced we’re doing it right, and instead undermining the best outcomes! (One way to tell if it’s safe to share in your org: put in a social network. If no one participates…) On the flip side, there are lots of practices that science tells us work. Details around formal learning, creating spaces for informal learning, practices for short-term and long-term innovation, etc.

We have an uphill battle gaining the credibility we need, but I say start now, and start small. Instill the practices within L&D, take ownership of the necessary skills and knowledge, make it work, document it, and then use that success as a stepping stone to spread the word.

Then, if we are doing that facilitation of learning, you should be able to see that we are enabling the most important work in the organization! We can be the key to org success, going forward. L&D should lead the change. That’s the vision I see, at least. Does this sound good and make sense to you?

The ITA Jay Cross Memorial Award for 2018: Mark Britz

5 July 2018 by Clark Leave a Comment

In honor of the colleague, mentor, and friend that brought us together, every year the Internet Time Alliance presents the Jay Cross Memorial Award. The award is for an individual who represents the spirit of continuing informal learning for the workplace. This year, Mark Britz is the deserving recipient.

Jay was a fierce champion of social and informal learning. He saw that most of how we learn to do what we do comes from interacting with others. As a response to his untimely passing, the remaining members of the ITA decided to honor his memory with an award. Jane Hart, Harold Jarche, Charles Jennings, & myself each year collectively decide an individual who we think best reflects Jay’s vision. And we announce the recipient on the 5th of July, Jay’s birthday.

Mark has resonated and amplified the message of ongoing learning since we first crossed paths. He has interacted with the ITA members regularly via tweets, blogs, and in person when possible. And we’ve appreciated his engagement with the ideas and his contributions to our thinking.

I got to know Mark’s thinking a bit better when he wrote a case study based upon his work at Systems Made Simple for the Revolution book (Jay wrote the foreword). And he’s continued to blog about workplace learning at The Simple Shift with short but insightful posts. Currently part of the team running events for the eLearning Guild, Mark manages to consistently touts views that illuminate thinking about the new workplace.

The situation he cites in that case study is exemplary of this type of thinking. Charged with starting a corporate ‘university’ in an organization that was composed of many experts, he knew that ‘courses’ weren’t going to be a viable approach. Instead, he championed and built a social network that pulled these experts together to share voices. The core L&D role was one of facilitating communication and collaboration, rather than presenting information.

For his continuing work promoting communication, collaboration, and continual learning, we recognize Mark’s efforts with the 2018 Internet Time Alliance Jay Cross Memorial Award.

Silly Design

3 July 2018 by Clark Leave a Comment

Time for a brief rant on interface designs. Here we’re talking about two different situations, one device, and and one interface. And, hopefully, we can extract some lessons, because these are just silly design decisions.

First up is our timer. And it’s a good timer, and gets lots of use. Tea, rice, lots of things. And, sometimes, a few things at a time. As you can see, there’re 3 timers. And, as far as I know, we’ve only used at most two at a time. So what’s the problem?

Well, there’re different beeps signaling the end of different timers. And that’s a good thing. Mostly. But there’s one very very silly design decision here. Let me tell you that one has one beep, one has two beeps, and one has three. So, guess which number of beeps goes to which timer? You can see they’re numbered…

Got your guess? It’d be sensible, of course, if the one beep went with the first timer, and two beeps went with the second. But you know we’re not going there! Nope, the first timer has two beeps. The second timer has 3 beeps. And the 3rd timer, of course, has one.

It’s a principle called ‘mapping’ (see Don Norman’s essential reading for anyone who designs for people: The Design of Everyday Things). In it, you make the mapping logical, so for instance between the number of the timer and the number of beeps. How could you get this wrong? (Cliche cue: you had one job…)

On to our second of today’s contestants, the iTunes interface. Now, everyone likes to bash iTunes, and either it’s a bad design for what it’s doing, or it shouldn’t be trying to do too many things. I’m not going there today, I’m going off on something else.

I’ve always managed the files on the qPad through iTunes. It used to be straightforward, but they changed it. Of course. There’re also more ways to do it: AirDrop & iFiles being two. And, frankly, they’re both somewhat confusing. But that’s not my concern today. The new way I use is only a slight modification on the old way, which is why I use it. And it works. But there’s a funny little hiccup…

So, there are two ways to bring up a list of things on your iPad. For one, you select it from the device picture at the top (to the right of the forward/back arrows), and you see a list of things you can access/adjust: music, movies, etc. As you see to the left.

On the other hand (to the right), you select it from a list of devices, and you get the drop down you see to the right. Note that the lists aren’t the same.

Wait, they’re not the same? No, only one has “File Sharing”! So, you have to remember which way to access the device before you can choose to add a file. This is just silly! Only recently have I started remembering which way works (bad design, BTW, trusting to memory), and before that I had to explore. It’s not much, just an extra click, but it’s unnecessary memory load.

The overhead isn’t much, to be clear, but it’s still irritating. Why, why would you have two different ways to access the device, and not have the same information come up? It’s just silly! Moreover, it violates a principle. Here, the principle is consistency (and, arguably, affordances). When you access a device, you expect to be able to manipulate the device. And you don’t expect that two different ways to get to what should be the same place would yield two different suites of information. (And don’t even get me started about the stupid inconsistencies between the mobile and web app versions of LinkedIn!)

At least if you haven’t communicated a clear model about why the one way is different than the other. But it’s not there. It’s a seemingly arbitrary list. We operate on models, but there’s no obvious way to discriminate between these two, so the models are random. Choosing the device, either way, is supposed to access the device. That’s the affordance. Unless you convey clearly why these are different.

This holds for learning too. Interface folks argued that Gloria Gery’s Electronic Performance Support Systems were really making up for bad design. And so, too, is much training. Don argued in his The Invisible Computer that UI should be up front in product design, because they could catch the design decisions that would make it more difficult to use. I want to argue that it’s the same with the training folks: they should be up front in product or service design to catch decisions that will confuse the audience and require extra support costs.

Design, learning or product/service, works best when it aligns with how our brains work. If we own that knowledge, we can then lobby to apply it, and help make our organizations more successful. If we can make happier users, and less support costs, we should. And as Kathy Sierra suggests, really it’s all about learning.