Archives for September 2011

The Mobile Academy

29 September 2011 by Clark Leave a Comment

If you’ve been paying attention to mobile learning, hopefully you’ve heard about my recent book, Designing mLearning. I’m proud of it, as I feel I did a pretty good job of addressing the important issue: helping you get your mind thinking different which is an important component of taking advantage of mobile. I also covered examples (thoughtfully provided by a number of my colleagues in the space), design processes, strategy and more.

However, as the subtitle suggests (Tapping into the Mobile Revolution for Organizational Performance), it’s focused on helping businesses and other organizations take advantage of mobile technologies to largely meet internal learning and performance needs. Unfortunately, the term mlearning tends to get people to immediately think of ‘courses on a phone’, which is not the value proposition mobile largely provides. So the book is relatively sparse on the side of formal learning.

So I was asked to write a book on mobile learning for higher education, which means focusing on using mobile to support the student experience (otherwise, it’s back to the first book). And I’m pleased to announce that this book is now out: The Mobile Academy: mLearning for Higher Education. And it’s a very different book, with a very different cut through mlearning.

This book is more completely about how do you use mobile devices to augment formal learning. While there is a chapter on meeting student administrative needs, the rest is focused on looking at the different elements of instruction and how mlearning can be used to broaden and deepen the experience. Consequently, three of the main chapters are on content roles in learning, developing interactivity for practice, and adding in the social component. While it’s specifically focused on higher education for practical reasons, there are no fundamental reasons why a large portion of it is relevant at least in secondary schools as well (with no discussion of developmental levels nor child-appropriate form-factors, it’s less applicable to K-6).

So now there are two different books, for two different audiences. If you’re focused on formal learning, that is in delivering courses as a business, this new one is for you. If, instead, your role is supporting performance in the organization (including but not limited to augmenting courses), the original one is for you. (And, please, do not assume you want the new one if you’re part of the learning or training unit in an organization, unless there’s another unit responsible for performance support and social learning.)

I hope that one or the other of these will help you ‘get going’ with mlearning.

Smart Habits

28 September 2011 by Clark Leave a Comment

I admit that I’m not patient. While this has it’s faults, I use it to drive certain behaviors that are positive. For instance, I’m almost an obsessive optimizer in travel. I try to minimize my luggage (I typically travel out of just an expanded briefcase for trips of around 3 days), and similarly the amount of times sitting in lines. And I use apps to try to find the best places to eat in airports and around wherever I’m staying.

App use is one of the tools we have to accessorize our brains. We can use the standard PIM software (e.g. memos, tasks, contacts, calendar) and any other built-in features, but for me the real opportunity is the distinction between smartphone and the app phone as David Pogue calls it. The ability to customize the device with software that meets my particular interests and needs lets me configure with free or paid apps to get the capabilities I need. So, yes, I can use the built-in camera to record hotel room numbers or parking spots, but more importantly I can get a train app to let me plan a trip, or a diagramming tool to let me capture some thoughts, or…

Another habit we can get into is thinking. I just recently blogged about reflection as a powerful tool, and we can make blogging a habit, for instance. I also deliberately will queue up a problem I’m working on before I start exercising or taking a shower, and see if I can’t come up with some new ideas.

The point is that deliberately thinking about possible ways to think smarter and work smarter is a good habit to get into, and one that you can cultivate to discover other habits. How about deciding, at the next conference you go to, to not only pay attention to the messages but also the presentations, to see what you can learn? Pay attention to how a meeting is being run next time, or what the coaching process you are receiving (or not) is? And watch or even ask how other people handle things. How do they book travel, or find out about the program, or… I ask my mobile workshop audiences how they use their devices to make themselves smarter, and I always seem to find out about a new app or two.

The point is that there are some well-known self-improvement tips like reading books, but there are more that are just sitting there awaiting your attention. Why not look for opportunities to work smarter, not harder? It’s the smart thing to do.

Reflecting socially

23 September 2011 by Clark 5 Comments

About ten years ago, now, Jay Cross and I met and with some other colleagues, started what we called the Meta-Learning Lab. We’ve maintained our interest in meta-learning across our involvement now with the Internet Time Alliance, and a component we identified as one of the most valuable activities you can do is reflection.

We don’t mean just navel-gazing, of course, but instead we mean systematically stepping back and reviewing ongoing activity with a view towards looking for improvement. It’s baked into things like Watts Humphrey’s Personal Software Process, and without that level of rigor, it still has benefits. Even more so if it’s shared.

So, blogging is one way of sharing your thoughts and getting feedback (as I do here). The social processing that happens when sharing is not just for formal learning, but for personal, self-directed learning as well. Creating a representation of your understanding is valuable in and of itself, to make your thinking concrete, but sharing and getting feedback is even more powerful.

This isn’t just for individuals, of course, but also for teams. If teams share their collective thinking (blogs again, or perhaps wikis), they can get feedback not just from each other but also from non-team individuals. This improves the thinking.

And we can start using richer media than just text. We can capture our understanding with images, audio or video, e.g. conducting interviews (you think differently creating a response to a deep question synchronously than asynchronously). You can go out and create a video of something that communicates what you think. You can even film a performance by the individual or team and bring it back for discussion. What a couple of high-tech firms have done, having outstanding performers talk about or perform on video, and adding their own reflections (‘directors notes’ versions), is really powerful for learners too.

Mobile gives us the capability to be more flexible in our communication capture and sharing, which decouples our thinking from the desktop. We also may be able to review interactions in a social media system, messages and such, to reflect on our communication patterns and improve. And facilitating all this is, to me, one of the opportunities for the learning professional as we start a) expanding our responsibility for all performance, not just ‘training’, and b) start investing our efforts in proportion to the workplace impact (c.f. 70:20:10).

So, I encourage you to start reflecting personally, of course, but consider also reflecting socially, with your colleagues, teammates, and more. Learning out loud is a key to moving forward faster and more effectively.

Contextualized Learning

22 September 2011 by Clark Leave a Comment

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.

Cognitive Task Analysis

19 September 2011 by Clark 2 Comments

While I argue strongly for stepping away more frequently from formally structured learning, not least because we overuse it, there are times when it is crucial. As naysayers of informal learning like to point out, you wouldn’t want your pilot or heart surgeon to have picked up the task by reading a book. When performance is critical, you really want to understand what the important elements are, whether to train them or provide support.

A technique for doing that is Cognitive Task Analysis (CTA). This is not a shortcut, it’s deep in terms of the knowledge elicitation techniques, the analytical task, and the representation of results. Based in decades of cognitive research, integrating work on mental models, expertise, and more, it provides a mechanism to try to unearth the tacit understanding experts hold. Because experts compile away their knowledge to the point that they no longer have access to it, it is hard to get at this knowledge, and it takes a rigorous process.

While useful for system design, CTA is also valuable for designing performance support, and training. The deep elicitation process can derive what the task really is, and what should be in the learner’s head and what support can and should be available. When I talk about the performance ecosystem, particularly for complex tasks, you want just this sort of support to determine what should be distributed across formal learning and performance support.

One of the problems with CTA is that there have been a number of different approaches, and they tend to be buried in academic papers or proprietary processes. The good news is that there’s now a book about CTA, Working Minds, by Beth Crandall, Gary Klein, & Robert Hoffman, academics and practitioners. It boils down the divergence into a fairly reasonable set of steps, with techniques that can be used at each stage. The bad news is, of course, that it still is a daunting read, with considerable depth.

If you’ve got performances that absolutely have to be right, you’ll want to do the analysis ala CTA, and use it to decide what really needs to be in training, checklists, etc. This goes deeper than HPT even, tho’ I think it’s as weak when it comes to the benefits of social learning, but I reckon it’s for expert *performance*, not innovation. That’s another layer. Still, a valuable tool in the quiver of supporting performance.

Please at least understand what CTA is, and know when you need it. You may not need to be an expert in it, but you should at least be aware.

Meaningful processing

14 September 2011 by Clark 1 Comment

Sometimes I worry about the myths that are out there about learning. Ok, to be honest I worry about them a lot. Learning styles, generational differences, digital natives, the list goes on. But one that has personally been surfacing a lot is the type of activity that leads to meaningful learning. So it’s time for me to lay it out, for the record.

I’ve talked previously about social processing, so I’m going to focus specifically on individual processing. And, realize, my goals are not the ability to recite rote knowledge, but I’ll even address that. Note, by the way, that there are really two types of knowledge (c.f. Van MerriÃ«nboer), the things you need and the complex problems you apply them to. So, first we’ll start with the knowledge you need, and then the problems you apply them to.

To help folks get knowledge down, memorizing the core facts they’ll draw upon in solving complex problems, the main component necessary is reactivating the knowledge. You need to match the term with the definition, the model with it’s relationships, etc. Sheer repetition doesn’t help, even here it’s making choices and getting feedback.

So, for instance, coloring a poster with the associated words doesn’t do the necessary processing, you need to activate the necessary concepts with connections to relevant things. You need to semantically process the terms again and again. Elaborating them, putting them in context, applying them to simple problems is necessary. Flash cards work because they require the association task. Just exposure doesn’t work, even with testing, it’s discrimination from competing alternatives.

Then we get to the application. And frankly, if you’re not having folks learn things to use them, why are you bothering? That’s why I like Cathy Moore’s Action Mapping, she works backwards from the task and then only focuses on the knowledge necessary to do the task. A good heuristic approach that couples elegantly to a principled foundation. And, as converging theories suggest, you need to be applying knowledge to support the ability to transfer that skill out of the learning experience.

So, you need to be looking at the knowledge to be learned in a more discriminating fashion than just exposure, and you then need to be applying that knowledge to a suite of tasks to support making it useful. There’s more, such as the necessary spread of tasks to support appropriate decontextualization to support transfer, and sufficient and spacing of practice to support retention, but here I just want to emphasize that rote exposure to knowledge doesn’t mean it will be learned, and that learning facts without applying them doesn’t lead to any meaningful outcome. So can we start focusing on learning activities that generate meaningful processing? Please?

Ownership versus ubiquity

13 September 2011 by Clark Leave a Comment

The notion that soon everything will be in the cloud, and we’ll just use an interface surface near us is not new. The notion is that the technology will recognize you and present your environment, ready for you to accomplish your goals. This is a nice idea, and I can see it working, but it’s not trivial.

Contrast this to the element that Judy Brown talks about as important component of mobile learning. For her, mobile devices have to be something you’re familiar with and have with you all the time. And that, to me, is the sticking point.

With an interface surface you come upon, would you necessarily recognize the different ways the interface would manifest? You don’t want a big touchscreen (despite Minority Report imaginings) for very complex work, because the research shows your arms fatigue too quickly. So you might have a keyboard on some devices. And the variety could be high. And, yes, it’s your interface, but with all the different possible form-factors, could you make it comprehensible? And you’re still at the mercy of availability of surfaces (kinda like waiting in line for computers to check email at conferences has been).

Now, I can see having a mobile device and then using an accessible interface that recognizes you by the device proximity, so you’re not stuck. And I can imagine that it would be possible to make a scalable interface (just not necessarily easy). I do wonder, however, about some surfaces being so designed for aesthetics that the usability is compromised (c.f. The Design of Everyday Things).

And, particularly for my notion of slow learning (which I need to augment with ubiquity and personalization – quick, I need a new phrase! :), the ability for a device to be with you may be required to do the teachable moment thing. That is, having a context-sensitive device right that at the appropriate place and time may be needed to really develop us in the ways we deserve.

So I don’t take that vision of ubiquitous computing surfaces at face value, I think that there are some reasons why mobile devices may still make sense. Which isn’t to say there’s not a way, but I’m still holding out for something with me.

Working Smarter

12 September 2011 by Clark 2 Comments

Work smarter, not harder.

Have you heard that? I did, in my first job out of college; my boss said it, but it wasn’t clear what it meant. What does ‘work smarter’ mean? I already thought I was working smarter. Well, as I’ve learned (in conjunction with my ITA colleagues), it means a number of things that organizations can, and should, do.

So, what is known about when we work smarter? We work smarter under a number of conditions: when we have a clear goal of what we’re supposed to achieve and we recognize it’s importance; when we’re free to experiment, explore, and even fail; when we have colleagues to collaborate with; and when we have the resources we need available ‘to hand’. This provides some guidance about what an organization should be doing to optimize the likelihood of success.

We need to be doing meaningful work that we’re excited about. We need to be connected to a vision, and understand how our role contributes. There needs to be transparency above and below as well as ahead, so we can see how the parts are working together.

We also need a culture where that transparency is empowering, not threatening. It has to be safe to perform in public, to share our thoughts, and to both provide and receive help to others. Where, when mistakes are made, the lessons are learned and shared.

We need to see it as important to contribute, and be enabled to communicate to the right people, and be able to work together to get the job done. We need time to reflect as well, to take time to think about what we’re doing. We should be doing that publicly too. We need to learn out loud and together.

Finally, we need the tools available. We shouldn’t have to take time to go multiple places to get what we need, and use inconsistent interfaces to use them. We should have an environment where we’re focused on our tasks, and can get who and what we need to stay focused.

How to work smarter isn’t a mystery. The mystery is why more organizations aren’t systematically breaking down the barriers to working smarter. Are you ready to get going?

Layering learning

8 September 2011 by Clark 3 Comments

Electronic Performance Support Systems are a fabulous concept, as pioneered by Gloria Gery back in the early 90’s. The notion is that as you use a system, and have entries or decisions to make, there are tools available that can provide guidance: proactively, intelligently, and context-appropriate. Now, as I heard the complaint at the time, this would really be just good interface design, but the fact is that many times you have to retrofit assistance on top of a bad design for sad but understandable reasons.

The original were around desktop tasks, but the concept could easily be decoupled from the workplace via mobile devices. One of my favorite examples is the GPS system: the device knows where you are, and where you want to go (because you told it), and it gives you step by step guidance, even recalculating if you make a change. Everything from simple checklists to full adaptive help is possible, and I’ve led the design of such systems.

One of the ideas implicit in Gery’s vision, however, that I really don’t see, is the possibility of having the system not only assist you in performing, but also help you learn. She talked about the idea in her book on the subject, though without elaborating how that would happen, but her examples didn’t really show it and I haven’t seen it in practice in the years since. Yet the possibility is there.

I reckon it wouldn’t really take much. There is (or should be) a model guiding the decisions about what makes the right step, but that’s often hidden (in our learning as well). Making that model visible, and showing how it guides the support and recommendations that are made, could be made available as a ‘veneer’ over the system. It wouldn’t have to be visible, it could just be available at a click or as a preference for those who might want it.

Part of my vision of how to act in the world is to ‘learn out loud’. Well, I think our tools and products could be more explicit about the thinking that went into them, as well. Many years ago, in HyperCard, you could just use buttons and field, but you could open them up and get deeper into them, going from fixed links to coded responses. I have thought that a program or operating system could work similarly, having an initial appearance but capable of being explored and customized. We do this in the real world, choosing how much about something we want to learn (and I still want everyone who uses a word processor to learn about styles!) about something. Some things we pay someone else to do, other things we want to do ourselves. We learn about some parts of a program, and don’t know about others (it used to be joked that no one knows everything about Unix, I feel the same way about Microsoft Word).

We don’t do enough performance support as it is, but hopefully as we look into it, we consider the possible benefits of supporting the performance with some of the underlying thinking, and generating more comprehension with the associated benefits that brings. It’s good to reflect on learning, and seeing how thinking shapes performance both improves us and can improve our performance as well.