design Archives - Page 44 of 84

Badass

10 February 2016 by Clark 1 Comment

That’s the actual title of a book, not me being a bit irreverent. I’ve been a fan of Kathy Sierra’s since I came across her work, e.g. I regularly refer to how she expresses ‘incrementalism‘. She’s on top of usability and learning in very important ways. And she’s got a new book out that I was pleased to read: Badass: Making Users Awesome. So why do I like it? Because it elegantly intermixes both learning and usability to talk about how to do design right (which I care about; I used to teach interface design besides my focus on learning design), but more importantly that the lessons invoked also apply to learning.

So what’s she doing differently? She’s taking product design beyond marketing and beyond customer desires. The premise of the book is that it’s not about the user and not about the product, it’s about the two together making the user more capable in ways they care about. Your audience should be saying “Look at what I can do” because of the product, not “I love this product”. This, she argues cogently, is valuable; it trumps just branding, and instead building customer loyalty as an intrinsic outcome of the experience they have.

The argument starts with making the case that it’s about what user goals are, and then figuring out how to get there in ways that systematically develop users’ capability while managing their expectations. Along the way, she talks about being clear on what will occur, and giving them small wins along the way. And she nicely lays out learning science and motivation research as practical implications.

While she’s more focused on developing complex products with interfaces that remove barriers like cognitive load, and provide incremental capability, this applies to learning as well. We want to get learners to new capabilities in steps that maintain motivation and prevent drop-off. She gets into issues like intermediate skills and how to develop them in ways that optimize outcomes, which is directly relevant to learning design. She cites a wide variety of people in her acknowledgements, include Julie Dirksen and Jane Bozarth in our space, so you know she’s tracking the right folks.

It’s an easy read, too. It’s unusual, paperback but on weighty paper supporting her colorful graphics that illustrate her every point. There’s at least an equal balance of prose and images if not more on the latter side. While not focused specifically on learning design, it includes a lot of that but also covers performance support and more in an integrated format that resonates with an overall perspective on a performance ecosystem.

While perhaps not as fundamental as Don Norman’s Design of Everyday Things (which she references; and everyone who designs for anyone else needs to read), it’s a valuable addition to those who want to help people achieve their goals, and that includes product designers, interface designers, and learning experience designers. If you’re designing a solution for others, whether a mobile app, an authoring tool, a LMS, or other, you do need this. If you’re designing learning, you probably need this. And if you’re designing learning as a business (e.g. designing learning for commercial consumption), I highly recommend giving this a read.

Reactivating Learning

27 January 2016 by Clark Leave a Comment

(I looked because I’m sure I’ve talked about this before, but apparently not a full post, so here we go.)

If we want our learning to stick, it needs to be spaced out over time. But what sorts of things will accomplish this? I like to think of three types, all different forms of reactivating learning.

Reactivating learning is important. At a neural level, we’re generating patterns of activation in conjunction, which strengthens the relationships between these patterns, increasing the likelihood that they’ll get activated when relevant. That’s why context helps as well as concept (e.g. don’t just provide abstract knowledge). And I’ll suggest there are 3 major categories of reactivation to consider:

Reconceptualization: here we’re talking about presenting a different conceptual model that explains the same phenomena. Particularly if the learners have had some meaningful activity from your initial learning or through their work, showing a different way of thinking about the problem is helpful. I like to link it to Rand Spiro’s Cognitive Flexibility Theory, and explain that having more ways to represent the underlying model provides more ways to understand the concept to begin with, a greater likelihood that one of the representations will get activated when there’s a problem to be solved, and will activate the other model(s) so there’s a greater likelihood of finding one that leads to a solution. So, you might think of electrical circuits like water flowing in pipes, or think about electron flow, and either could be useful. It can be as simple as a new diagram, animation, or just a small prose recitation.

Recontextualization: here we’re showing another example. We’re showing how the concept plays out in a new context, and this gives a greater base upon which to abstract from and comprehend the underlying principle, and providing a new reference that might match a situation they could actually see. To process it, you’re reactivating the concept representation, comprehending the context, and observing how the concept was used to generate a solution to this situation. A good example, with a challenging situation that the learner recognizes, a clear goal, and cognitive annotation showing the underlying thinking, will serve to strengthen the learning. A graphic novel format would be fun, or story, or video, anything that captures the story, thinking, and outcome would work.

Reapplication: this is the best, where instead of consuming a concept model or an example, we actually provide a new practice problem. This should require retrieving the underlying concept, comprehending the context, and determining how the model predicts what will happen to particular perturbations and figuring out which will lead to the desired outcomes. Practice makes perfect, as they say, and so this should ideally be the emphasis in reactivation. It might be as simple as a multiple-choice question, though a scenario in many instances would be better, and a sim/game would of course be outstanding.

All of these serve as reactivation. Reactivation, as I’ve pointed out, is a necessary part of learning. When you don’t have enough chance to practice in the workplace, but it’s important that you have the ability when you need it (and try to avoid putting it in the head if you can), reactivation is a critical tool in your arsenal.

Performance Detective

19 January 2016 by Clark Leave a Comment

I was on a case. I’m a performance detective, and that’s what I do. Someone wasn’t performing they way they were supposed to, and it was my job to figure out why. My client thought he knew. They always do. But I had to figure it out myself. Like always.

Before I hit the bricks, I hit the books. Look, there’s no point watching anyone if you don’t know what you’re looking for. What’s this mug supposed to be doing? So I read up. What’s the job? What’s the goal? How do you know when it’s going well? These are questions, and I need answers. So I check it out. Even better, if I can find numbers. Can’t always, as some folks don’t really get the value. Suckers.

Then I had to get a move on. You need what you find from the background, but you can’t trust it. There could be many reasons why this palooka isn’t up to scratch. Everyone wants to throw a course at it. And that may not the problem. If it isn’t a skill problem, it’s not likely a course is going to help. You’re wasting money.

The mug might not believe it’s important. Or not want to do it a particular way. There’re lots of reasons not do it the way someone wants. It could be harder, with no obvious benefit. If you don’t make it clear, why would they? People aren’t always dumb, it just seems that way.

Or they might not have what they need. Too often, some well-intentioned but under-aware designers wants to put some arbitrary information in their heads. Which is hard. And usually worthless. Put in the world. Have it to hand. They may need a tool, not a knowledge dump.

Or, indeed, they may not be capable. A course could be the answer. Not just a course, of course. It needs more. Coaching, and practice. Lots of practice. They may really be out of their depth, and dumping knowledge on them is only going to keep them drowning.

It’s not always easy. It may not be a simple answer. There can be multiple problems. It can be all of the above. Or any combination. And that’s why they bring me in. To get the right answer, not the easy answer. And certainly not the wrong answer.

So I had to go find out what was really going on. That’s what detectives do. They watch. They investigate. They study. That’s what I do. I want the straight dope. If you can’t do the hard yards, you’re in the wrong job. I love the job. And I’m good at it.

So I watched. And sure enough, there it was. Obvious, really. In retrospect. But you wouldn’t have figured it out if you hadn’t looked. It’s not my job to fix it. I told the client what I found. That’s it. Not my circus, not my monkeys. Get an architect to come up with a solution. I find the problem, and report. That’s what I do.

This quite literally came from a dream I had, and my subsequent thoughts when I woke up. And when I first conceived it, I wasn’t thinking about the role that Charles Jennings, Jos Arets, and Vivian Heijnen have as one of five in their new 70:20:10 book, but there is a nice resonance. Hopefully my ‘hard boiled’ prose isn’t too ‘on the nose’! More importantly, what did I miss? I welcome your thoughts and feedback.

Working wiser?

12 January 2016 by Clark Leave a Comment

Noodling: I’ve been thinking about Working Smarter, a topic I took up over four years ago. And while I still think there’s too little talk about it, I wondered also about pushing it further. I also talked in the past about an interest in wisdom, and what that would mean for learning. So what happens when they come together?

Working smarter, of course, means recognizing how we really think, work, and learn, and aligning our processes and tools accordingly. That includes recognizing that we do use external representations, and ensuring that the ones we want in the world are there, and we also support people being able to create their own. It means tapping into the power of people, and creating ways for them to get together and support one another through both communication and collaboration. And, of course, it means using Serious learning design.

But what, then, does working ‘wiser’ mean? I like Sternberg’s model of wisdom, as it’s actionable (other models are not quite specific enough). It talks about taking into account several levels of caring about others, several time scales, several levels of action, and all influenced by an awareness of values. So how do we work that into practices and tools?

Well, pragmatically, we can provide rubrics for evaluation of ideas that include considerations of others inside and outside your circles of your acquaintances, and in short- and long-term timeframes, and the impacts on existing states of affairs, ultimately focusing on the common good. So we can have job aids that provide guidance, or bake it into our templates. These, too, can be shown in collaboration tools, so the outputs will reflect these values. But there’s another approach.

But, at core, it’s really about what you value, and that becomes about culture. What values does the organization care about? Do employees know about the organization’s ultimate goal and role? Is it about short-term shareholder return, or some contribution to society? I’m reminded about the old statements about whether you’re about selling candles or providing light. And do employees know how what they do fits in?

It’s pretty clear that the values implicit in steps to make workplaces more effective are really about making workplaces more humane, that is: respecting our inherent nature. And movements like this, that provide real meaning, ongoing support, freedom of approach, and time for reflection, are to me about working not just smarter but also wiser.

We can work smarter with tools and practices, but I think we can work better, wiser, with an enlightened approach to who we are working with and how we work to deliver real value to not only customers but to society. And, moreover, I think that doing so would yield better organizational outcomes.

Ok, so have I gone off the edge of the hazy cosmic jive? I am a native Californian, after all, but I’m thinking that this makes real business sense. I think we can do this, and that the outputs will be better too, in all respects. No one says it’d be easy, but my suspicion is it’d be worthwhile.

2015 Reflections

31 December 2015 by Clark 3 Comments

It’s the end of the year, and given that I’m an advocate for the benefits of reflection, I suppose I better practice what I preach. So what am I thinking I learned as a consequence of this past year? Several things come to mind (and I reserve the right for more things to percolate out, but those will be my 2016 posts, right? :):

The Revolution is real: the evidence mounts that there is a need for change in L&D, and when those steps are taken, good things happen. The latest Towards Maturity report shows that the steps taken by their top-performing organizations are very much about aligning with business, focusing on performance, and more. Similarly, Chief Learning Officer‘s Learning Elite Survey similarly point out to making links across the organization and measuring outcomes. The data supports the principled observation.
The barriers are real: there is continuing resistance to the most obvious changes. 70:20:10, for instance, continues to get challenged on nonsensical issues like the exactness of the numbers!?!? The fact that a Learning Management System is not a strategy still doesn’t seem to have penetrated. And so we’re similarly seeing that other business units are taking on the needs for performance support, social media, and ongoing learning. Which is bad news for L&D, I reckon.
Learning design is rocket science: (or should be). The perpetration of so much bad elearning continues to be demonstrated at exhibition halls around the globe. It’s demonstrably true that tarted up information presentation and knowledge test isn’t going to lead to meaningful behavior change, but we still are thrusting people into positions without background and giving them tools that are oriented at content presentation. Somehow we need to do better. Still pushing the Serious eLearning Manifesto.
Mobile is well on it’s way: we’re seeing mobile becoming mainstream, and this is a good thing. While we still hear the drum beating to put courses on a phone, we’re also seeing that call being ignored. We’re instead seeing real needs being met, and new opportunities being explored. There’s still a ways to go, but here’s to a continuing awareness of good mobile design.
Gamification is still being confounded: people aren’t really making clear conceptual differences around games. We’re still seeing linear scenarios confounded with branching, we’re seeing gamification confounded with serious games, and more. Some of these are because the concepts are complex, and some because of vested interests.
Games seem to be reemerging: while the interest in games became mainstream circa 2010 or so, there hasn’t been a real sea change in their use. However, it’s quietly feeling like folks are beginning to get their minds around Immersive Learning Simulations, aka Serious Games. There’s still ways to go in really understanding the critical design elements, but the tools are getting better and making them more accessible in at least some formats.
Design is becoming a ‘thing’: all the hype around Design Thinking is leading to a greater concern about design, and this is a good thing. Unfortunately there will probably be some hype and clarity to be discerned, but at least the overall awareness raising is a good step.
Learning to learn seems to have emerged: years ago the late great Jay Cross and I and some colleagues put together the Meta-Learning Lab, and it was way too early (like so much I touch :p). However, his passing has raised the term again, and there’s much more resonance. I don’t think it’s necessarily a thing yet, but it’s far greater resonance than we had at the time.
Systems are coming: I’ve been arguing for the underpinnings, e.g. content systems. And I’m (finally) beginning to see more interest in that, and other components are advancing as well: data (e.g. the great work Ellen Wagner and team have been doing on Predictive Analytics), algorithms (all the new adaptive learning systems), etc. I’m keen to think what tags are necessary to support the ability to leverage open educational resources as part of such systems.
Greater inputs into learning: we’ve seen learning folks get interested in behavior change, habits, and more. I’m thinking we’re going to go further. Areas I’m interested in include myth and ritual, powerful shapers of culture and behavior. And we’re drawing on greater inputs into the processes as well (see 7, above). I hope this continues, as part of learning to learn is to look to related areas and models.

Obviously, these are things I care about. I’m fortunate to be able to work in a field that I enjoy and believe has real potential to contribute. And just fair warning, I’m working on a few areas in several ways. You’ll see more about learning design and the future of work sometime in the near future. And rather than generally agitate, I’m putting together two specific programs – one on (e)learning quality and one on L&D strategy – that are intended to be comprehensive approaches. Stay tuned.

That’s my short list, I’m sure more will emerge. In the meantime, I hope you had a great 2015, and that your 2016 is your best year yet.

Scenarios and Conceptual Clarity

10 December 2015 by Clark 5 Comments

I recently came across an article ostensibly about branching scenarios, but somehow the discussion largely missed the point. Ok, so I can be a stickler for conceptual clarity, but I think it’s important to distinguish between different types of scenarios and their relative strengths and weaknesses.

So in my book Engaging Learning, I was looking to talk about how to make engaging learning experiences. I was pushing games (and still do) and how to design them, but I also wanted to acknowledge the various approximations thereto. So in it, I characterized the differences between what I called mini-scenarios, linear scenarios, and contingent scenarios (this latter is what’s traditionally called branching scenarios). These are all approximations to full games, with various tradeoffs.

At core, let me be clear, is the need to put learners in situations where they need to make decisions. The goal is to have those decisions closely mimic the decisions they need to make after the learning experience. There’s a context (aka the story setting), and then a specific situation triggers the need to make a decision. And we can deliver this in a number of ways. The ideal is a simulation-driven (aka model-driven or engine-driven) experience. There’s a model of the world underneath that calculates the outcomes of your action and determines whether you’ve yet achieved success (or failure), or generates a new opportunity to act. We can (and should) tune this into a serious game. This gives us deep experience, but the model-building is challenging and there are short cuts.

In mini-scenarios, you put the learner in a setting with a situation that precipitates a decision. Just one, and then there’s feedback. You could use video, a graphic novel format, or just prose, but the game problem is a setting and a situation, leading to choices. Similarly, you could have them respond by selecting option A B or C, or pointing to the right answer, or whatever. It stops there. Which is the weakness, because in the real world the consequences are typically more complex than this, and it’s nice off the learning experience reflects that reality. Still, it’s better than knowledge test. Really, these are just a better written multiple choice question, but that’s at least a start!

Linear scenarios are a bit more complex. There are a series of game problems in the same context, but whatever the player chooses, the right decision is ultimately made, leading to the next problem. You use some sort of sleight of hand, such as “a supervisor catches the mistake and rectifies it, informing you…” to make it all ok. Or, you can terminate out and have to restart if you make the wrong decision at any point. These are a step up in terms of showing the more complex consequences, but are a bit unrealistic. There’s some learning power here, but not as much as is possible. I have used them as sort of multiple mini-scenarios with content in between, and the same story is used for the next choice, which at least made a nice flow. Cathy Moore suggests these are valuable for novices, and I think it’s also useful if everyone needs to receive the same ‘test’ in some accreditation environment to be fair and balanced (though in a competency-based world they’d be better off with the full game).

Then there’s the full branching scenario (which I called contingent scenarios in the book, because the consequences and even new decisions are contingent on your choices). That is, you see different opportunities depending on your choice. If you make one decision, the subsequent ones are different. If you don’t shut down the network right away, for instance, the consequences are different (perhaps a breach) than if you do (you get the VP mad). This, of course, is much more like the real world. The only difference between this and a serious game is that the contingencies in the world are hard-wired in the branches, not captured in a separate model (rules and variables). This is easier, but it gets tough to track if you have too many branches. And the lack of an engine limits the replay and ability to have randomness. Of course, you can make several of these.

So the problem I had with the article that triggered this post is that their generic model looked like a mini-scenario, and nowhere did they show the full concept of a real branching scenario. Further, their example was really a linear scenario, not a branching scenario. And I realize this may seem like an ‘angels dancing on the head of a pin’, but I think it’s important to make distinctions when they affect the learning outcome, so you can more clearly make a choice that reflects the goal you are trying to achieve.

To their credit, that they were pushing for contextualized decision making at all is a major win, so I don’t want to quibble too much. Moving our learning practice/assessment/activity to more contextualized performance is a good thing. Still, I hope this elaboration is useful to get more nuanced solutions. Learning design really can’t be treated as a paint-by-numbers exercise, you really should know what you’re doing!

Useful cognitive overhead

2 December 2015 by Clark 2 Comments

As I’ve reported before, I started mind mapping keynotes not as a function of filling the blog, but for listening better. That is, without the extra processing requirement of processing the talk into a structure, my mind was (too) free to go wandering. I only posted it because I thought I should do something with it! And I’ve realized there’s another way I leverage cognitive overhead.

As background, I diagram. It’s one of the methods I use to reflect. A famous cognitive science article talked about how diagrams are representations that map conceptual relationships to spatial ones, to use the power of our visual system to facilitate comprehension. And that’s what I do, take something I’m trying to understand, some new thoughts I have, and get concrete about them. If I can map them out, I feel like I’ve got my mind around them.

I use them to communicate, too. You’ve seen them here in my blog (or will if you browse around a bit), and in my presentations. Naturally, they’re a large part of my workshops too, and even reports and papers. As I believe models composed of concepts are powerful tools for understanding the world, I naturally want to convey them to support people in applying them themselves.

Now, what I realized (as I was diagramming) is that the way I diagram actually leverages cognitive overhead in a productive way. I use a diagramming tool (Omnigraffle if you must know, expensive but works well for me) to create them, and there’s some overhead in getting the diagram components sized, and located, and connected, and colored, and… And in so doing, I’m allowing time for my thoughts to coalesce.

It doesn’t work with paper, because it’s hard to edit, and what comes out isn’t usually right at first. I move things around, break them up, rethink the elements. I can use a whiteboard, but usually to communicate a diagram already conceived. Sometimes I can capture new thinking, but it’s easy to edit a whiteboard. Flip charts are consequently more problematic.

So I was unconsciously leveraging the affordances of the tool to help allow my thinking to ferment/percolate/incubate (pick your metaphor). Another similar approach is to seed a question you want to answer or a thought you want to ponder before some activity like driving, showering, jogging, or the like. Our unconscious brain works powerfully in the background, given the right fodder. So hopefully this gives you some mental fodder too.

Templates and tools

1 December 2015 by Clark 2 Comments

A colleague who I like and respect recently tweeted: “I can’t be the only L&D person who shudders when I hear the word ‘template'”, and I felt vulnerable because I’ve recently been talking about templates. To be fair, I have a different meaning than most of what’s called a ‘template’, so I thought perhaps I should explain.

Let’s be clear: what’s typically referred to as a template is usually a simple screen type for a rapid authoring tool. That is, it allows you to easily fill in the information and generate a particular type of interaction: drag-and-drop, multiple-choice, etc. And this can be useful when you’ve got well-designed activities but want to easily develop them. But they’re not a substitute for good design, and can make it easy to do bad design too. Worse are those skins that add gratuitous visual elements (e.g. a ‘racing’ theme) to a series of questions in some deluded view that such window dressing has any impact on anything.

So what am I talking about? I’m talking about templates that help reinforce the depth of learning science around the elements. I’m talking about templates for: introductions that ask for the emotional opener, the drill-down from the larger context, etc; practices that are contextualized, meaningful to learner, differentiated response options and specific feedback, etc; etc. This could be done in other ways, such as a checklist, but putting it into the place where you’re developing strikes me as a better driver ;). Particularly if it is embedded in the house ‘style’, so that the look and feel is tightly coupled to learner experience.

Atul Gawande, in his brilliant The Checklist Manifesto, points out how there are gaps in our mental processing that means we can skip steps and forget to coordinate. Whether the guidelines are in a template or a process tool like a checklist, it helps to have cognitive facilitation. So what I’m talking about is not a template that says how it’s to look, but instead what it should contain. There are ways to combine intrinsic motivation openings with initial practice, for instance.

Templates don’t have to stifle creativity, they can serve to improve quality instead. As big a fan as I am of creativity, I also recognize that we can end up less than optimal if there isn’t some rigor in our approach. (Systematic creativity is not an oxymoron!) In fact, systematicity in the creative process can help optimize the outcomes. So however you want to scaffold quality and creativity, whether through templates or other tools, I do implore you to put in place support to ensure the best outcomes for you and your audience.

CERTainly room for improvement

24 November 2015 by Clark 3 Comments

As mentioned before, I’ve become a member of my local Community Emergency Response Team (CERT), as in the case of disaster, the official first-responders (police, fire, and paramedics) will be overwhelmed. And it’s a good group, with a lot of excellent efforts in processes and tools as well as drills. Still, of course, there’s room for improvement. I encountered one such at our last meeting, and I think it’s an interesting case study.

So one of the things you’re supposed to do in conducting search and rescue is to go from building to building assessing damage and looking for people to help. And one of the useful things to do is to mark the status of the search and the outcomes, so no one wastes effort on an already explored building. While the marking is covered in training and there’re support tools to help you remember, ideally it’d be memorable, so that you can regenerate the information and don’t have to look it up.

The design for the marking is pretty clear: you first make a diagonal slash when you start investigating a building, and then you make a crossing slash when you’ve made your assessment. And specific information is to be recorded in each quarter of the resulting X: left, right, top, and bottom. (Note that the US standard set by FEMA doesn’t correspond to the international standard from the International Search & Rescue Advisory Group, interestingly).

However, when we brought it up in a recent meeting (and they’re very good about revisiting things that quickly fade from memory), it was obvious that most people couldn’t recall what goes where. And when I heard what the standard was, I realized it didn’t have a memorable structure. So, here are the four things to record:

the group who goes in
when the group completes
what hazards may exist
and how many people and what condition they’re in*

So how would you map these to the quadrants? And in one sense it doesn’t matter if there’s a sensible rationale behind them. One sign that there’s not? You can’t remember what goes where.

Our local team leader was able to recall that the order is: left – group, top – completion, right – hazards, and bottom – people. However, this seems to me to be less than memorable, so let me explain.

To me, wherever you put the in, left or top, the coming out ought to be opposite. And given our natural flow, group going in makes sense to the left, and coming out ought to go on the right. In – out. Then, it’s relatively arbitrary where hazards and people go. I’d make a case that top-of-mind should be the hazards found to warn others, but that the people are the bottom line (see what I did there?). I could easily make a case for the reverse, but either would be a mnemonic to support remembering. Instead, as far as I can tell, it’s completely arbitrary. Now, if it’s not arbitrary and there is a rationale, it’d help to share that!

The point being, to help people remember things that are in some sense arbitrary, make a story that makes it memorable. Sure, I can look it up, assuming that the lookup book they handed out stays in the pocket in my special backpack. (And I’m likely to remember now, because of all this additional processing, but that’s not what happens in the training.) However, making it regenerable from some structure gives you a much better chance of having it to hand. Either a model or a story is better than arbitrary, and one’s possible with a rewrite, but as it is, there’s neither.

So there’s a lesson in design to be had, I reckon, and I hope you’ll put it to use.

* (black or dead, red or needing immediate treatment for life-threatening issues, yellow or needing non-urgent treatment, and green or ok)

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