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Honored

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At the recent DevLearn conference, David and Heidi (the two-cofounders of the eLearning Guild) punk’d me.  Under the pretense of having me assist the keynote speaker, they had me sit at the front of the stage with another purpose in mind.

As background, the Guild is explicitly labeled and designed to reflect the original concept of an association of craftsmen in a particular trade.  The notion is that elearning professionals will be members of the guild to stay abreast of new developments, and interact with their peers.  Inherent in this is the notion of participants starting as apprentices and moving gradually to the center of a community of practice.  Consequently, the Guild hosts a number of things: online conferences (forums), Learning Solutions (an online magazine), research reports, discussion forums on LinkedIn, and of course their excellent conferences.

eLearning Guild Award

Heidi and David decided, apparently, that they wanted to reward those who were contributing, who were serving as defacto ‘masters’ of the community, following the historic traditions.  Consequently, they were reviewing who did what, who was writing, researching, and presenting, and apparently one name kept appearing at the top of the lists.   Mine.

Now, you have to understand that I have made no effort to see who was doing what; I see certain names regularly appear on their speaker lists, as well as new ones. I know a number of people have been involved in research, and they’re always getting new authors for the magazine. But I literally had no idea how much I did compared to others, so this was a complete surprise.

So they called me up on stage and bestowed upon me the honor of being the very first Guild Master, handed me this great chunk of gorgeous glass, all with me somewhat stunned and embarassed.  They have stated an intention to honor others at following conferences, which will be great.  I like how they view their role, think it’s valuable, and they strike the right balance in making a viable business that serves a community.  They continually experiment as well, and that’s a good thing.

Needless to say, I’m truly honored that they noticed and deemed me worthy.  It’s not always you get recognized for doing what you love, and when you do it’s humbling.  I’m very grateful to them, and the kind comments others have made subsequently.  And thanks to you for the feedback you’ve provided on my thoughts via this blog, helping me develop my understanding so I am better equipped for what I do. I am passionate about helping people perform better through technology, and as I often joke “this is what I would be doing even if I were independently wealthy (and you’re welcome to make that happen :)”.

I am truly pleased if what I’ve contributed has helped, and can only hope that I can continue.

Stop creating, selling, and buying garbage!

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I was thinking today (on my plod around the neighborhood) about how come we’re still seeing so much garbage elearning (and frankly, I had a stronger term in mind).  And it occurred to me that their are multitudinous explanations, but it’s got to stop.

One of the causes is unenlightened designers. There are lots of them, for lots of reasons: trainers converted, lack of degree, old-style instruction, myths, templates, the list goes on. You know, it’s not like one dreams of being an instructional designer as a kid.  This is not to touch on their commitment, but even if they did have courses, they’d likely still not be exposed to much about the emotional side, for instance. Good learning design is not something you pick up in a one week course, sadly.  There are heuristics (Cat Moore’s Action mapping, Julie Dirksen’s new book), but the necessary understanding of the importance of the learning design isn’t understood and valued.  And the pressures they face are overwhelming if they did try to change things.

Because their organizations largely view learning as a commodity. It’s seen as a nice to have, not as critical to the business.  It’s about keeping the cost down, instead of looking at the value of improving the organization.  I hear tell of managers telling the learning unit “just do that thing you do” to avoid a conversation about actually looking at whether a course is the right solution, when they do try!  They don’t know how to hire the talent they really need, it’s thin on the ground, and given it’s a commodity, they’re unlikely to be willing to really develop the necessary competencies (even if they knew what they are).

The vendors don’t help. They’ve optimized to develop courses cost-effectively, since that’s what the market wants. When they try to do what really works, they can’t compete on cost with those who are selling nice looking content, with mindless learning design.  They’re in a commodity market, which means that they have to be efficiency oriented.  Few can stake out the ground on learning outcomes, other than an Allen Interactions perhaps (and they’re considered ‘expensive’).

The tools are similarly focused on optimizing the efficiency of translating PDFs and Powerpoints into content with a quiz. It’s tarted up, but there’s little guidance for quality.  When it is, it’s old school: you must have a Bloom’s objective, and you must match the assessment to the objective. That’s fine as far as it goes, but who’s pushing the objectives to line up with business goals?  Who’s supporting aligning the story with the learner? That’s the designer’s job, but they’re not equipped.  And tarted up quiz show templates aren’t the answer.

Finally, the folks buying the learning are equally complicit. Again, they don’t know the important distinctions, so they’re told it’s soundly instructionally designed, and it looks professional, and they buy the cheapest that meets the criteria.  But so much is coming from broken objectives, rote understanding of design, and other ways it can go off the rails, that most of it is a waste of money.

Frankly, the whole design part is commoditized.  If you’re competing on the basis of hourly cost to design, you’re missing the point. Design is critical, and the differences between effective learning and clicky-clicky-bling-bling are subtle.  Everyone gets paying for technology development, but not the learning design.  And it’s wrong.  Look, Apple’s products are fantastic technologically, but they get the premium placing by the quality of the experience, and that’s coming from the design.  It’s the experience and outcome that matters, yet no one’s investing in learning on this basis.

It’s all understandable of course (sort of like the situation with our schools), but it’s not tolerable.  The costs are high:meaningless  jobs, money spent for no impact, it’s just a waste.  And that’s just for courses; how about the times the analysis isn’t done that might indicate some other approach?  Courses cure all ills, right?

I’m not sure what the solution is, other than calling it out, and trying to get a discussion going about what really matters, and how to raise the game. Frankly, the great examples are all too few. As I’ve already pointed out in a previously referred post, the awards really aren’t discriminatory. I think folks like the eLearning Guild are doing a good job with their DevLearn showcase, but it’s finger-in-the-dike stuff.

Ok, I’m on a tear, and usually I’m a genial malcontent.   But maybe it’s time to take off the diplomatic gloves, and start calling out garbage when we see it.  I’m open to other ideas, but I reckon it’s time to do something.

Level of ‘levels’

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I was defending Kirkpatrick’s levels the other day, and after being excoriated by my ITA colleagues, I realized there was not only a discrepancy between principle and practice, but between my interpretation and as it’s espoused.  Perhaps I’ve been too generous.

The general idea is that there are several levels at which you can evaluate interventions:

  1. whether the recipient considered the intervention appropriate or not
  2.  whether the recipient can demonstrate new ability after the intervention
  3. whether the intervention is being applied in the workplace, and
  4. whether the intervention is impacting desired outcomes.

That this is my interpretation became abundantly clear.  But let’s start with what’s wrong in practice.

In practice, first, folks seem to think that just doing level 1 (‘smile sheets’) is enough. Far fewer people take the next logical step and assess level 2. When they do, it’s too often a knowledge test.  Both of these fail to understand the intention: Kirkpatrick (rightly) said you have to start at level 4. You have to care about a business outcome you’re trying to achieve, and then work backwards: what performance change in the workplace would lead to the desired outcome. Then, you can design a program to equip people to perform appropriately and determine whether they can, and finally see if they like it.  And, frankly, level 1 is useless until you finally have had the desired impact, and then care to ensure a desirable user experience.  As a standalone metric, it ranks right up there with measuring learning effectiveness by the pound of learners served.

Now, one of the things my colleagues pointed out to me, beyond the failure in implementation, is that Kirkpatrick assumes that it has to be a course.  If it’s just misused, I can’t lay blame, but my colleagues proceeded to quote chapter and verse from the Kirkpatrick site to document that the Kirkpatricks do think courses are the solution. Consequently, any mention of Kirkpatrick only reinforces the notion that courses are the salve to all ills.

Which I agree is a mindset all too prevalent, and so we have to be careful of any support that could lead a regression to the status quo.  Courses are fine when you’ve determined that a skill gap is the problem.  And then, applying Kirkpatrick starting with Level 4 is appropriate.  However, that’s more like 15% of the time, not 100%.

So where did I go wrong?  As usual, when I look at models, I abstract to a useful level (my PhD focused on this, and Felice Ohrlich did an interesting study that pointed out how the right level of abstraction is critical).  So, I didn’t see it tied to courses, but that it could in principle be used for performance support as well (at least, levels 3 and 4).  Also for some social learning interventions.

Moreover, I was hoping that by starting at level 4, you’d look to the outcome you need, and be more likely to look at other solutions as well as courses.  But I had neglected to note the pragmatic issue that the Kirkpatrick’s imply courses are the only workplace intervention to move the needles, and that’s not good.  So, from now on I’ll have to be careful in my reference to Kirkpatrick.

The model of assessing the change needed and working backward is worthwhile, as is doing so systematically.  Consequently, at an appropriate level of abstraction, the model’s useful.  However, in it’s current incarnation it carries too much baggage to be recommended without a large amount of qualification.

So I’ll stick to talking about impacting the business, and determining how we might accomplish that, rather than talk about levels, unless I fully qualify it.

Contextualized Learning

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Recently, a colleague videotaped me responding to some questions about how mobile could change learning.  I find I riff a bit in such situations, and one of the ideas I had then is something I wanted to explore a little more. It had to do with context.

What we do, in so many of our formal learning designs, is create artificial contexts.  In face-to-face learning, we’ll do role-plays, and in online learning we’ll create simulations or games.  Now, this makes sense; you want to do practice away from real performance if the consequences are costly. Yet other times, e.g. after the learning experience, they end up performing (and, too often, before they’ve received sufficient practice because of time and money constraints as well as just bad habits).  A further opportunity is that out there in the real world, there may be some contexts that the learner comes across that may be relevant, and we could extend the learning experience.

Context-aware systems give us a chance to do something more here.  If you’re performing a task that’s related to some formal learning, your system could be equipped to notice, and bring in some appropriate content.  This was the promise of electronic performance support systems, and we can now start doing it not just in custom-designed environments, but we can connect context clues to associated content with semantic rules.  So, if you’re in a coaching meeting, the system could prepare you beforehand, provide support during, and some reflective evaluation afterward.  Say, a checklist.

Similarly, we can notice the context of the learner and even if it’s not a performance situation, if there’s a meaningful connection (I didn’t want to use semantic again :), the system could provide some mention of the linkage, which reactivates and contextualizes the learning, making it more likely to be retained and transferred.

Mobile, of course, decouples this capability from the desktop, and increases the likelihood that the connection opportunities are capitalized on, and even the performance support model can be brought to bear.  The two necessary components are the context-awareness (done via GPS, calendar) and semantic linkages (done with tagging).  This is no longer rocket science, just a product of decent task analysis and content engineering.

I reckon it’s time that we can, and should, lift our game a little to start looking at more sophisticated support technologies. If improving performance matters…and it should.

Mentoring Results

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Eileen Clegg from the Future of Talent Institute (and colleague, we co-wrote the Extremophiles chapter for Creating a Learning Culture) pinged me the other day and asked about my thoughts on the intersection of:

  1. The new role of managers in the results-oriented work environment (ROWE)
  2. The topic of  blending the Talent and Learning functions in the workplace.

She’d been excited about Cognitive Apprenticeship years ago after hearing me talk about it, and wondered if there was a role to play. I see it as two things: orgs need optimal execution just as the cost of entry: that’s where apprenticeship fits in, but they also need continual innovation. That needs collaboration, and we are still exploring that, though there are some really clear components.  Though one of the nice things about cognitive apprenticeship is that it naturally incorporates collaborative learning, and can develop that as it develops understanding of the domain.

I admit I’m a little worried about ROWE from the point of view that Dan Pink picks out in Drive, about how a maniacal focus on results could lead to people doing anything necessary to achieve results. It’s got to be a little more about taking mutual ownership (producer and whoever is ‘setting’ the result) that the result is meeting the org need in a holistic (even ‘wise’ way).

What has to kick in here is a shared belief in a vision/mission that you can get behind, individuals equipped to solve problems collaboratively (what I call big L learning: research, design, experimentation, etc), and tools to hand for working together. You apprentice both in tasks *and* learning, basically, until you’re an expert in your domain are defining what’s new in conjunction with your collaborators.

Expressed by my colleague was a concern that there was a conflict between”(a) supporting someone’s learning and (b) being invested in the success of their work product”. And I would think that the management is NOT directly invested in the product, only in the producer.  Helping them be the best they can be and all that.  If they’re not producing good output, they either need to develop the person or replace them, which indirectly affects the product.  However, this isn’t new for mentors as well: they want their charges to do well, but the most they can do is influence the performer to the best of their ability.

As a component, learners need to develop their PKM/PLN (personal knowledge management, personal learning network). And 21st century skills aren’t taken for granted but identified and developed. In addition, the performance ecosystem, aka workscape – not only formal learning but also performance support, informal learning, and social learning – is the responsibility of the integrated talent/learning functions (which absolutely should be blended).  And ‘management’ may move more toward mentorship, or be a partner between someone strategizing across tasks and a talent development function in the organization.

As an extension to my ‘slow learning’ model, I think that the distinction between learning and performing from the point of view of support needs to go away. We can and should be concerned with the current performance and the long-term development of the learner at the same time.  Thus, the long term picture is of ongoing apprenticeship towards mutually negotiated and understood goals, both work and personal development.

Learning Experience Design in Action

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I was working with one of my clients/partners on an opportunity to develop classroom learning on a tablet.  The first push is to get something to show teachers and trial in a classroom.  It’s not yet going to be socially enabled, nor particularly mobile, nor yet augmented with resources; the point now is to demonstrate capability to develop compelling interactives (pretty much regardless of whether it’s a tablet or not).

As context, they’d sent me some storyboards that I’d responded to with some comments.   They actually started from a good point, but there were nuances that needed to be teased out.  Their questions  led me to think through some principles that underpinned my recommendations.  In the course of their questions, I talked about these perspectives:

Start with visceral experience: I want to ground the learning in their world.  I want to start with phenomena that they understand, and have them do a little free exploration followed by some focused tasks, but at a qualitative, experiential level. Drill down from the bigger picture in the world, to intermediate issues, to why this in particular is important, and have them actively explore the relationships.

Connect conceptual to formal: after the learner has an experiential basis, then link it to formal representations.  Help the learners connect their actions to the tools used to structure our understanding.  At the end of the day, at least in this domain, we want them to be able to use the formal representations to solve problems that their capabilities can’t solve with their bodies (e.g. applying forces in microjoules or gigajoules).  As a guide, the point is not to teach science, say, but instead to teach them to be scientists, using tools to solve problems.  Finally, they should be taking measurements, transforming to manipulable representations, transforming the representations to a solution, and then applying that back to the world.

Focus on action, not content: rather than require learners to view this video or that document, make them available.  Ideally, the only required elements would be the series of activities, and the information resources surround the activities as options.  The challenge of the activities, and quality of the content, would ideally drive the learner to the resources, but there might be required quick overviews that point to deeper resources, and individuals who struggle might be pointed to the content.

Launch with a meaningful context: I suggested an overall task that would ultimately need to be performed, using a recognized problem as the motivation for learning this content, though there are other ways.  However, you do want to harness learners hearts as well as their brains in the endeavor.  In this case it was about saving people’s lives that motivated going through the course to be prepared to come back and provide the knowledge of what force to apply, in what direction.

And in one I didn’t convey, but is implicit in the learning situation but could and should be implicit in the development of the learning experience:

Scaffold the learning process: don’t assume that the learner is equipped for learning this way, provide support. Pedagogical support can be through an agent, and there has to be feedback involved both addressing the content and the process.  If only requiring the activities, the evaluation, inadequate performance might trigger a requirement to view content, for example.  A pedagogical avatar could be useful.

All of this is based upon a research base in learning theory, even the emotional side.  There could be more involved, as I had ides for options in being social, and actually being mobile, which are currently beyond the scope of their engagement, but the point is to start with a visceral and active base upon which to drive motivation for content, formalisms, and ultimate mastery.

What’s the right technology for schools?

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At the end of a conversation the other day, the topic turned to technologies in schools.  I was asked what I thought about the iPad in schools, and as I thought it through, I saw both pluses and minuses.

Let me, of course, make this generic to tablets and PDAs. And not smartphones, as there are problems with phones in schools that I don’t want to get into.  Having a wifi PDA (e.g. iPod Touch) is good enough for the issues at hand.

Now, many years ago Elliott Soloway decided that the form-factor of a laptop was not appropriate for kids, and created what ended up being the GoKnow suite of PDA apps.  Back then he was working on Palm devices and then Windows PDAs.  I think he had that right.

However, now that there are tablets, I think they have advantages for schools too.  They’re not too big (by and large), and are better for both content consumption and creation than laptops or even netbooks (though an additional keyboard might be handy).

As I thought more about it, I’d like the tablet in class (and maybe at home), but I’d like a PDA when kids hit the road.  Elliot had sensor-equipped PDAs being used to collect river pH measurements. There a host of reasons to get kids out gathering data and working on projects, including problem-based and service-learning type projects.  Having the devices available for accessing answers to questions when on field trips or taking notes also makes sense.

You can have these as separate devices, synching them into a common database, but I was reminded of an early proposal for a processor ‘block’ that could plug into a variety of devices, and your files would remain on the ‘block’.  You could do it with a U3 system, I suppose, but I really want that processor with it for consistency of OS, etc.  For example, running an OS (WebOS, iOS, Android, etc) on a PDA (w/ camera, etc), and then the PDA could be plugged into a tablet and the tablet would take over as the I/O channel.  Some may not get it, but I think it’s preferable to having to sync two devices.

This, I think, would provide the portability for field moves with screen real estate for creation and communication.  Of course the device would be equipped with a camera, microphone, wifi, bluetooth, etc, and a suite of software, but I really think that one platform isn’t enough, and two is too many, and a PDA is too small for creation and consumption and a tablet too small for fieldwork, so what you want is a hybrid hardware platform. Could there be a happy medium, perhaps, but I’m not sold.  What do you think?

Enterprise Thinking, or Thinking Enterprise

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I realize, with recent releases like Jane Bozarth’s Social Media for Trainers and Marcia Conner & Tony Bingham’s The New Learning (both recommended, BTW, reviews coming soon, with standard disclaimer that I’m mentioned in both) that the message is finally getting out about new ways to facilitate not just formal learning and execution, but informal learning and innovation.  But there’s more needed. It takes new thinking at the top.  You need to think about how the enterprise is thinking.

So what do you want for your enterprise thinking?  Shows like The Office make us laugh because we identify with it. We know the officious types, the clueless, the apathetic, the malevolent, the greedy, the ones just marking time.  They’re definitely not thinking about how to make the organization more successful, they’re thinking more about what will make their life most enjoyable, and there’s little or no alignment.  That’s not what you want, I’ll suggest, but is what’s seen, in various degrees, in most places.

Instead, you (should) want folks who know what the goal is, are working towards it individually and collectively.  That are continually looking for opportunities to improve the products, processes, and themselves.  This is where organizations will derive competitive advantage.

How do you get there?  It takes coordinating several things, including the dimensions of the learning organization: leadership, culture, and practices), and the information infrastructure for working well together.  You need to have the tools, you need to understand the behaviors required, you need to know that working this way is valued, and you need to be informed as to what the goals are.

We want to be empowering people with the models that help understand the shifts that are happening and how to cope, so they’re part of the movement.  They  need to understand things like networks and complexity, so that they’re equipped to contribute at the next level.

It’s time to stop thinking patchwork (“we’ll just put in the tools”, or “we’ll move in the direction of more open leadership”), and starting thinking systemically and strategically.  Identify and acknowledge where you are now, and figure out a path to get where you need to be.  It’s not likely to be easy, but it’s clearly time to get started.

Designing for an uncertain world

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My problem with the formal models of instructional design (e.g. ADDIE for process), is that most are based upon a flawed premise.  The premise is that the world is predictable and understandable, so that we can capture the ‘right’ behavior and train it.  Which, I think, is a naive assumption, at least in this day and age.  So why do I think so, and what do I think we can (and should) do about it?  (Note: I let my argument lead where it must, and find I go quite beyond my intended suggestion of a broader learning design.  Fair warning!)

The world is inherently chaotic. At a finite granularity, it is reasonably predictable, but overall it’s chaotic. Dave Snowden’s Cynefin model, recommending various approaches depending on the relative complexity of the situation, provides a top-level strategy for action, but doesn’t provide predictions about how to support learning, and I think we need more.  However, most of our design models are predicated on knowing what we need people to do, and developing learning to deliver that capability.  Which is wrong; if we can define it at that fine a granularity, we bloody well ought to automate it.  Why have people do rote things?

It’s a bad idea to have people do rote things, because they don’t, can’t do them well.  It’s in the nature of our cognitive architecture to have some randomness.  And it’s beneath us to be trained to do something repetitive, to do something that doesn’t respect and take advantage of the great capacity of our brains.  Instead, we should be doing pattern-matching and decision-making.  Now, there are levels of this, and we should match the performer to the task, but as I heard Barry Schwartz eloquently say recently, even the most mundane seeming jobs require some real decision making, and in many cases that’s not within the purview of  training.

And, top-down rigid structures with one person doing the thinking for many will no longer work.  Businesses increasingly complexify things but that eventually fails, as Clay Shirky has noted, and  adaptive approaches are likely to be more fruitful, as Harold Jarche has pointed out.  People are going to be far better equipped to deal with unpredictable change if they have internalized a set of organizational values and a powerful set of models to apply than by any possible amount of rote training.

Now think about learning design.  Starting with the objectives, the notion of Mager, where you define the context and performance, is getting more difficult.  Increasingly you have more complicated nuances that you can’t anticipate.  Our products and services are more complex, and yet we need a more seamless execution.  For example trying to debug problems between hardware device and network service provider, and if you’re trying to provide a total customer experience, the old “it’s the other guy’s fault” just isn’t going to cut it.  Yes, we could make our objectives higher and higher, e.g. “recognize and solve the customer’s problem in a contextually appropriate way”, but I think we’re getting out of the realms of training.

We are seeing richer design models. Van Merrienboer’s 4 Component ID, for instance, breaks learning up into the knowledge we need, and the complex problems we need to apply that knowledge to.  David Metcalf talks about learning theory mashups as ways to incorporate new technologies, which is, at least, a good interim step and possibly the necessary approach. Still, I’m looking for something deeper.  I want to find a curriculum that focuses on dealing with ambiguity, helping us bring models and an iterative and collaborative approach.  A pedagogy that looks at slow development over time and rich and engaging experience.  And a design process that recognizes how we use tools and work with others in the world as a part of a larger vision of cognition, problem-solving, and design.

We have to look at the entire performance ecosystem as the context, including the technology affordances, learning culture, organizational goals, and the immediate context.  We have to look at the learner, not stopping at their knowledge and experience, but also including their passions, who they can connect to, their current context (including technology, location, current activity), and goals.  And then we need to find a way to suggest, as Wayne Hodgins would have it, the right stuff, e.g. the right content or capability, at the right time, in the right way, …

An appropriate approach has to integrate theories as disparate as distributed cognition, the appropriateness of spaced practice, minimalism, and more.  We probably need to start iteratively, with the long term development of learning, and similarly opportunistic performance support, and then see how we intermingle those together.

Overall, however, this is how we go beyond intervention to augmentation.  Clive Thompson, in a recent Wired column, draws from a recent “man+computer” chess competition to conclude “serious cognitive advantages accrue to those who are best at thinking alongside machines”.  We can accessorize our brains, but I’m wanting to look at the other side, how can we systematically support people to be effectively supported by machines?  That’s a different twist on technology support for performance, and one that requires thinking about what the technology can do, but also how we develop people to be able to take advantage.  A mutual accommodation will happen, but just as with learning to learn, we shouldn’t assume ‘ability to perform with technology augmentation’.  We need to design the technology/human system to work together, and develop both so that the overall system is equipped to work in an uncertain world.

I realize I’ve gone quite beyond just instructional design.  At this point, I don’t even have a label for what I’m talking about, but I do think that the argument that has emerged (admittedly, flowing out from somewhere that wasn’t consciously accessible until it appeared on the page!) is food for thought.  I welcome your reactions, as I contemplate mine.

The GPS and EPSS

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It’s not unknown for me to enter my name into a drawing for something, if I don’t mind what they’re doing with it.  It’s almost unknown, however, for me to actually win, but that’s actually the case a month or so ago when I put a comment on a blog prior to the MacWorld show, and won a copy of Navigon turn-by-turn navigation software for my iPhone.  I’d thought a dedicated one might be better, though I’d have to carry two devices, but if I moved from an iPhone to Droid or Pre I’d suffer. But for free…

When I used to travel more (and that’s starting again), I’ve usually managed to get by with Google Maps: put in my desired location (so glad they finally put copy/paste in, such a no-brainer rather than have to write it elsewhere and type it on, or remember, usually imperfectly).  In general, maps are a great cognitive augment, a tool we’ve developed to be very useful.  And I’m pretty good with directions (thankfully), so when a trip went awry it wasn’t too bad.  (Though upper New Jersey…well, it can get scary.)  Still, I’d been thinking seriously about getting a GPS, and then I won one!

And I’m happy to report that Navigon is pretty darn cool.  At first the audio was too faint, but then I found out that upping the iPod volume (?) worked.  (And then it didn’t the last time, at all, with no explanation I can find.  Wish it used the darn volume buttons. We’ll see next time. ) However, it does a fabulous job of displaying where you are, what’s coming up, and recalculating if you’ve made a mistake.  It’s a battery hog, keeping the device on all the time, but that’s why we have charging holders (which I’d already acquired for long trips and music).  It also takes up memory, keeping the maps onboard the device (handy if you’re in an area with bad network coverage), but that’s not a problem for me.

However, my point here is not to extol the virtues of a GPS, but instead to use them as a model for some optimum performance support, as an EPSS (Electronic Performance Support System).  There’s a problem with maps in a real-time performance situation. This goes back to my contention that the major role of mlearning is accessorizing our brain.  Memorizing a map of a strange place is not something our brains do well.  We can point to the right address, and in familiar places choose between good roads, but the cognitive overhead is too high for a path of many turns in unfamiliar territories.  To augment the challenge, the task is ‘real time’, in that you’re driving and have to make decisions within a limited window of recognition.  Also, your attention has to be largely outside the vehicle, directed towards the environment. And to cap it all of, the conditions can be dark, and visibility obscured by inclement weather.  All told, navigation can be challenging.

While the optimal solution is a map-equipped partner sitting ‘shot-gun’, a GPS has been designed to be the next best thing (and in some ways superior).  It has the maps, knows the goal, and often more about certain peculiarities of the environment than a map-equipped but similarly novice partner.  A GPS also typically does not get it’s attention distracted when it should be navigating.  It can provide voice assistance while you’re driving, so you don’t need to look at the device when your attention needs to be on the road, but at safe moments it can display useful guidance about lanes to be in (and avoid) visually, without requiring much screen real estate.

And that’s a powerful model to generalize from: what is the task, what are our strengths and limitations, and what is the right distribution of task between device and individual?  What information can a device glean from the immediate and networked environment, from the user, and then provide the user, either onboard or networked?  How can it adapt to a changing state, and continue to guide performance?

Many years ago, Don Norman talked about how you could sit in pretty much any car and know how to drive it, since the interface had time to evolve to a standard.  The GPS has similarly evolved in capabilities to a useful standard.  However, the more we know about how our brains work, the more we can predetermine what sort of support is likely to be useful.  Which isn’t to say that we still won’t need to trial and refine, and use good principles of design across the board, interface, information architecture, minimalism, and more.  We can, and should, be thinking about meeting organizational performance, not just learning needs.  Memorizing maps isn’t necessarily going to be as useful as having a map, and knowing how to read it.  What is the right breakdown between human and tool in your world, for the individuals you want to perform to their best?  What’s their EPSS?

And on a personal note, it’s nice to have the mobile learning manuscript draft put to bed, and be able to get back into blogging and more. A touch of the flu has delayed my ability to think again, but now I’m ready to go.  And off I go to the Learning Solutions conference in Orlando, to talk mobile, deeper learning, and more.  The conference will both interfere with blogging and provide fodder as well.  If you’re there, please do say hello.