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Norman’s Design of Future Things

18 February 2013 by Clark Leave a Comment

Donald Norman’s book, The Design of Everyday Things is a must-read for anyone who creates artifacts or interfaces for humans. This one goes forward in the same vein, but talking about how new tech in the roughly 20 years since that book came out, and the implications. There are some interesting thoughts, though few hints for learning.

In the book, Don talks about how new technologies are increasingly smart, e.g. cars are almost self-driving (and since the book was published back in 2007, they’re now already on the cusp). As a consequence, we have to start thinking deeply about when and where to automate, having technologies make decisions, versus when we’re in the loop. And, in the latter case, when and how we’re kept alert (pilots lose attention trying to monitor an auto-pilot, even falling asleep).

The issue, he proposes, is that tenuous relationship between an aware partner and the human. He uses the relationship between a horse and rider as an example, talking about loose-rein control and close-rein control. Again, there are times the rider can be asleep (I recall a gent in an Irish pub bemoaning the passing of the days when “the horse knew the way home”).

He covers a range of data points from existing circumstances as well as experiments in new approaches. This ranges from noise to crowd behavior. For noise, he looks at how the way mechanical things made noises were clues to their state and operation, and that we’re losing those clues as we increasingly make things quiet. Engineers are even building in noise as a feature when it’s disappeared via technical sophistication. For crowd behavior, one example is how the removal of street signs in a couple of cities have reduced accidents.

At the end, he comes up with a set of design principles:

Provide rich, complex, and natural signals
Be predictable
Provide a good conceptual model
Make the output understandable
Provide continual awareness, without annoyance
Exploit natural mapping to make interaction understandable and effective

For learning, he talks about how robots that teach are one place in which such animated and embodied avatars make sense, whereas in may situations they’re more challenging. He talks about how they don’t need much mobility, can speak, and can be endearing. Not to replace teachers, but to supplement them. Certainly we have the software capability, but we have to wonder what sort of system makes sense to invest in the actual embodiment versus speaking from a mobile device or computer.

As an exercise, I looked at his design principles to see what might transfer over to the design of learning experiences. The main issue is that in learning, we want the learner facing problems, focusing on the task of creating a solution with overt cognitive awareness, as opposed to an elegant, almost unconscious, accomplishment of a goal. This suggests that rule 2, ‘be predictable’, might be good in non-critical areas of focus, but not in the main area. The rest seem appropriate for learning experiences as well.

This is a thoughtful book, weaving a number of elements together to capture a notion, not hammer home critical outcomes. As such, it is not for the casual designer, but for those looking to take their design to the ‘next level’, or consider the directions that will be coming, and how we might prepare people for them. Just as Don proposed that the interface design folks should be part of the product design team in The Invisible Computer, so too should the product support specialists, sales training team, and customer training designers be part of the design team going forward, as the considerations of what people will have to learn to use new systems are increasingly a concern in the design of systems, not just products.

Performance support-ing learning

11 February 2013 by Clark 8 Comments

In a post last week, I mentioned how Gloria Gery’s original vision of performance support not only was supposed to help you in the moment, it was also – at least in principle – of developing you over time. And yet I have yet to see it. So what am I talking about?

Let’s use an example. I think of the typical GPS as one of the purest models of performance support: it knows where you’re trying to go (since you tell it), and it helps you every step of the way. It can even adapt if you make a mistake. It will get you there.

However, the GPS will tell you nothing about the rationale it’s using to choose your route, which can seem different than one you might have chosen on your own. Even if it offers you alternatives, or you specify preferences like ‘no toll roads’, the underlying reasoning isn’t clear. Yet this might be an opportunity for navigational learning (e.g. “this route has more lights, so we prefer the slightly longer one with fewer opportunities for stopping”).

Nor does it help you learn anything along the way: geography, political boundaries, even geology, although it could do any of these with only a thin veneer of extra work: “as we cross the river, we are also crossing the boundary between X county and Y; in 1643 the pressure between the two cities of X1 and Y1 jockeying for power led to this settlement that shared the water resource.”

It could go further, using this as an example of a greater phenomena: “geographic features often serve as political boundaries, including mountains and rivers as well as oceans”. This latter would, in a sensible approach, only be used a few times (as the message,nonce known, could become annoying. And, ideally, you could choose what you wanted to learn about.

This isn’t limited to GPS, this could be used in any instance of guided performance. Sometimes you might not care (e.g. I suspect most users of Turbo Tax don’t want to know about the nuances of the tax, they just want it done!), but if you want people to understand the reasoning as a boost to more expert performance, e.g. so they can then start using that model to infer how to deal with things that fall outside of the range of performance support, this is a missed opportunity.

The point is to have even our programs to be ‘thinking out loud‘, both to help us learn, and to serve as a check on validity. Sure, it should be able to be shut off or customized, but the processing going on provides an opportunity for learning to happen in new and meaningful ways. The more we can couple the concept to the context, the more we can create learning that will really stick. And that is, or should be, the real goal.

Roger Schank #eli3 Keynote Mindmap

7 February 2013 by Clark 5 Comments

Roger Schank gave a passionate, inciteful and insightful talk about how learning really works and how he’s building businesses on those principles. He raced along and jumped around, making mapping challenging, but his message was apt.

Michael Moore #eli3 Keynote Mindmap

5 February 2013 by Clark Leave a Comment

Professor Moore gave a carefully detailed argument about why educational institutions (particularly higher ed) had to change, given the changes in society. He then argued some of the changes needed, and suggested some new institutional structure models that might provide guidance.

Real mLearning

4 February 2013 by Clark 5 Comments

Too many times, at conference expos and advertisements, it appears that folks are trying to say that courses on a tablet (or phone) are mlearning. On the contrary, I’ll suggest that courses on a phone or a tablet are elearning. Then, what is mlearning?

My argument is pretty simple: just because courses are on a different device, if they’re a traditional course – page turning with knowledge test, a virtual classroom, or even a simulation – if it’s only made touch-enabled, it’s still just elearning. Even if you strip it down to work on a phone, minimizing text, how is it really, qualitatively different?

Now, if you start breaking it up into chunks, and distributing it over time, we’re in a bit of a grey area, but really, isn’t that just what we should be doing in elearning, too? Learning needs to be distributed, but this is still just a greater degree of convenience than doing the same on a laptop. It’s a quantitative shift, not tapping into the inherent nature of mobile.

So, when is it really mlearning? I want to suggest that mlearning – and here I’m talking about courses, not mobile performance support, mobile social, etc, which also could and should be considered mlearning or at least mperformance – is when you’re using the local context to support learning. That could be restated as when you are turning a performance situation into a learning situation, wrapping the performance context with resources and support to take a performance experience and turn it into a learning experience.

Most of our formal learning involves what IBM termed ‘work-apart’ learning, something that happens away from your regular job. And most training and online learning are just that, separated from work. We artificially create contexts that mimic the workplace in most of our learning. And there are occasionally good reasons to do that, like handling multiple people and when failure can be costly or expensive.

Now, however, when we can bring digital technology wherever we are, we can use our real work to be the base of the learning experience. We don’t need an external context, we’re in one! We can provide concepts, examples, and feedback around real contextualized practice. Or, we can add a layer to performance support that educates, not just supports, as Gloria Gery had proposed (but is still to be seen).

And, if the work context is using the desktop, then mobile isn’t necessarily a sensible solution. However, on those increasing circumstances when we’re on a site visit, meeting, at an event, and generally away from our desks, mlearning as I’m construing it here makes sense.

I don’t want to discount the value of elearning on mobile devices, particularly on tablets (where I have argued that the intimacy may have uniquely beneficial impacts), but I do think we shouldn’t consider context-free courses on a small device as anything other than just elearning. So, the question I’m wrestling with is whether mlearning includes mobile performance support, informal, etc, or do we want a separate term for that? But I kinda do want to keep mlearning from not meaning ‘courses on a phone (or tablet)’. What say you?

Living with Complexity

30 January 2013 by Clark Leave a Comment

Don Norman (disclaimer, my PhD advisor and mentor) has had a string of important books, starting with his stellar Design of Everyday Things (tops my ‘recommended books’ list for designers). His latest, Living with Complexity, is not as landmark a book as that, but it has some very astute thinking to present.

The book, as the title implies, is largely about how complexity isn’t bad, it’s necessary, and the real issue is about designing to manage it. We want powerful systems to accomplish meaningful goals, and he makes the case that this naturally requires complexity, either at the front end or at the back end. Complexity at the front end offers powerful choice at the tradeoff of comprehensibility, which we often want. Complexity at the back end can seem like magic, but offers more opportunity for things to go wrong catastrophically.

Good design is naturally the solution. He suggests that good design makes complexity usable, and bad design makes complexity frustrating. And he makes a strong point that it’s now about services.

He goes beyond product design in detailing how you really aren’t designing just a product, but an experience, and that it takes a system to create an experience. Using Apple’s iPod, he points out how simplifying the purchasing (backend: lining up publishers to allow downloading individual titles for a simple fee) and downloading music (instead of converting files and storing in special folders) made a device that could carry a lot of music in a small package.

He goes deeper into service design, using the examples of waiting in lines (I now know why immigration in SFO can be so frustrating!). He finally gets to coverage of recommendations for improvements, including signifying (making affordances perceivable), checklists, and job aids (over courses). His focus is on tapping into how our minds work, and aligning tools with them. He covers both sides, including what designers should do differently, and what ‘consumers’ can do. He also covers some of the mismatches between design and consumers, going beyond the design to the overall system.

Overall, while seemingly not as well structured as previous books, this book offers some advanced thinking into design that will benefit those looking to take a bigger picture. Feeling more like a collection rather than a coherent narrative, each of the elements is related and there are important insights in each section. Recommended for the advanced designer.

Engagement, people!

28 January 2013 by Clark 5 Comments

I’m working on a project with a partner, and have this really sharp ID working with me. My role is to be guiding the design, not doing it, and it’s working well. The thing I see, however, is emblematic of what I’m seeing much more broadly: the dissociation between the designer and the learning experience.

Ok, so not many ID theorists are talking about the emotional engagement. Keller and his ARCS model is really the only one. And some folks are touting it for elearning. Michael Allen and his mantra of “no more boring elearning” has been at the forefront for a long time. Julie Dirksen covers it in her recent book, and it’s also implicit in Cathy Moore’s Action Mapping & Roger Schank’s Goal-Based Scenarios. Yet somehow the message isn’t getting through.

The output, however, is at arm’s distance from the learner. It’s got comprehensive coverage. It’s got stories, and animations (I’m having some effect :), but they’re so abstract. So overwritten. So impersonal. It’s not the ID’s fault. Where, in most programs in ID, in most settings, do you see a focus on learner experience? Not clicky-clicky bling bling, as Cammy Bean so aptly coined it, but really engaging learning. It’s harder to find than you think.

There are several important components:

Making it meaningful: focus on changes that will impact the workplace and help convey to the learner that this is real and really needed. If it’s not tied to impacting a business metric, it’s probably not the right topic.

Making it personal: this includes several things. One is writing like you’re talking to the person. Another is having them connect it to their own practices, either retroactively or proactively. Give them an assignment about what to do in the workplace that they bring back.

Making it visceral: this means introducing and using examples that go beneath the merely informative, and tap into basic instincts. Learners should be connected in a very emotional way, using fear or empathy or other hook that appeals directly to their personal needs in ways that cause them to resonate in their core.

Minimalizing: going through and slashing your verbiage. Most elearning is grossly overwritten, and can be trimmed at least 40%, and usually can be trimmed down 60% or more. You want to use rich media (I’m pushing graphic novel formats in the project) and animations, but much less prose and production than you think you need.

Putting it into practice: this means having the learner perform the way they’ll need to perform outside the learning experience. Get them making the decisions in practice that you want in the workplace. It’s not about knowing, it’s about doing. Until they can’t get it wrong.

Making it flow: think about not just the individual bits, but also the segue between them. What’s the emotional trajectory the learner goes through? How are they intrigued, and how do we lead them from apathy and anxiety to motivation and confidence?

These are the top level categories, but they map out into more practices. And you should be working on these in your teams. And I can state from experience that just workshops by themselves aren’t sufficient, and what really helps are an exposure to the principles and the practice, then feedback on a series of attempts until satisfied that the principles have been internalized in the practice. Please, go beyond content, and get into real experience design. Systematically, reliably, and repeatedly. For your learners, and for the industry. We need to lift our game.

Bob Pike #ASTDMENA Keynote Mindmap

14 January 2013 by Clark Leave a Comment

Bob Pike launched the third and final day of ASTD’s Middle East and North Africa event with a keynote that took some well-established principles of good learning design and put his own unique and engaging spin on them. Along the way he discussed learning styles (in a different phrase) and generations. And he certainly practices what he preaches.

Refining Designing

3 January 2013 by Clark 3 Comments

A couple of months ago, I posted on thinking about designing, calling for designing ‘backwards and forwards’. And it’s continued to percolate, rightly or wrongly.

As I originally structured it, you worked backwards (1) from the ultimate performance you need to put information in the head, and in the world, and then designed forward (2) the combined learning experience, and the performance resource. While the HPT movement thinks about this as well (they definitely talk about whether it should be a learning or performance support solution; I don’t know but assume they will do a mix if needed). Which I don’t disagree with, but I realized I needed to address one issue.

It occurred to me that when you design your resource(s), that has to happen first. If there are resources, they should be included in the learning experience. That is, you want to provide practice with the resources as part of the learning experience to develop the performer’s ability to use the resources in the performance situation.

Thus, I’ve ended up redesigning it such that performance resource(s) influence the learning experience design (3), and are available in the learning experience as well as in the performance environment. It’s more complex, but more accurately captures the types of thinking we need to have as designers. We need to create what’s in the world and then prepare what’s in the head to accommodate the new performance environment.

Which, of course, may actually need to be iterative. As Atul Gawande points out in his book, his checklists were rigorously trailed and refined. That sort of evaluation and revision should be part of our ongoing processes too. We shouldn’t assume we’ll get it perfect the first time. And the existing environment prior to our intervention will also factor into our resource and experience design.

That said, does this conceptualization help? I’m trying to find ways to represent design that helps reduce our overemphasis on all training being about trying to put everything ‘in the head’, and this, combined with my earlier thoughts on learning experience design, is part of my ongoing effort. If, however, it’s either too confusing, or already common knowledge, I need to work more. Feedback?

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