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You know you’re mobile when…

26 July 2012 by Clark 3 Comments

I was thinking about the different ways you can be mobile, and I think it’s broader than most people think. So I tried to capture it in a diagram. For once, I’m not particularly happy with it, but in the spirit of ‘thinking out loud’…

When are you mobile?

The notion is there that you’re mobile when you’re not at your desk with your desktop or even laptop. Now, sometimes you have a laptop with you, but increasingly I think it’ll be tablet or just a pocketable device (and see my earlier distinctions around those, particularly that laptops don’t typically count). When you’re at your desk, you’re clearly using your desktop or laptop for work, and you’re not mobile.

With the caveat that if the organization is blocking access to some sites (e.g. any search term like ‘game’ or social media site like Facebook and Twitter), you’re highly likely to use your mobile device to get around this. Rightly so, I must say. Increasingly your network is part of your brain and your solution set, and anyone who’d block it is keeping you from being as effective as possible. If they’re worried about, or you really aren’t using it for work purposes, the problem is not the network.

Now, you can be out of your particular workspace but still in either your own office, a satellite office, or even in someone else’s office (e.g. client or partner’s office), but you’re in an office. You may be having meetings, making a site visit, whatever. I reckon attending a conference or a workshop is similar. There you are mobile, unless you’ve lugged your desktop with you (umm, no). Again, increasingly it’ll be a tablet or a pocketable.

And there’s the particular situation of being ‘on the go’, when you’re actually in motion, in a way station (in a shop, restaurant, coffeeshop, or pub), or even some place where there’s no real seating (factory floor, for example). There you’re far more likely to be using your pocketable device in opposition to the laptop or tablet.

You’ll still be accessing your social network, too. More so; you’ll not only getting answers and assistance, but updating people as well.

There are a couple of unique situations. One is attending a virtual meeting. At your desktop, you’d use it. When in another context, you can use your laptop or your tablet. It’s not quite as feasible with a pocketable device (though that will change). Your mobile, but your part of an out-of-context or virtual context event, so it’s conceptually distinct, though practically it may not be.

The other is context-specificity. If the device is doing something unique because of where or when you are, it’s really a different situation than accessing just any content or capability you need. Particularly if the interaction is context-specific. And capturing your context, with media, really is a different category.

The point I’m trying to make is that, particularly in the middle category, mobile is more ubiquitous than you think. You know you’re mobile when you’re not at your desk. And that’s an increasing amount of the time for most people. Which is healthier anyway.

Emergent & Semantic Learning

10 July 2012 by Clark 2 Comments

The last of the thoughts still percolating in my brain from #mlearncon finally emerged when I sat down to create a diagram to capture my thinking (one way I try to understand things is to write about them, but I also frequently diagram them to help me map the emerging conceptual relationships into spatial relationships).

What I was thinking about was how to distinguish between emergent opportunities for driving learning experiences, and semantic ones. When we built the Intellectricity© system, we had a batch of rules that guided how we were sequencing the content, based upon research on learning (rather than hardwiring paths, which is what we mostly do now). We didn’t prescribe, we recommended, so learners could choose something else, e.g. the next best, or browse to what they wanted. As a consequence, we also could have a machine learning component that would troll the outcomes, and improve the system over time.

And that’s the principle here, where mainstream systems are now capable of doing similar things. What you see here are semantic rules (made up ones), explicitly making recommendations, ideally grounded in what’s empirically demonstrated in research. In places where research doesn’t stipulate, you could also make principled recommendations based upon the best theory. These would recommend objects to be pulled from a pool or cloud of available content.

However, as you track outcomes, e.g. success on practice, and start looking at the results by doing data analytics, you can start trolling for emergent patterns (again, made up). Here we might find confirmation (or the converse!) of the empirical rules, as well as potentially new patterns that we may be able to label semantically, and even perhaps some that would be new. Which helps explain the growing interest in analytics. And, if you’re doing this across massive populations of learners, as is possible across institutions, or with really big organizations, you’re talking the ‘big data’ phenomena that will provide the necessary quantities to start generating lots of these outcomes.

Another possibility is to specifically set up situations where you randomly trial a couple alternatives that are known research questions, and use this data opportunity to conduct your experiments. This way we can advance our learning more quickly using our own hypotheses, while we look for emergent information as well.

Until the new patterns emerge, I recommend adapting on the basis of what we know, but simultaneously you should be trolling for opportunities to answer questions that emerge as you design, and look for emergent patterns as well. We have the capability (ok, so we had it over a decade ago, but now the capability is on tap in mainstream solutions, not just bespoke systems), so now we need the will. This is the benefit of thinking about content as systems – models and architectures – not just as unitary files. Are you ready?

Piecing together collaboration and cooperation: The Coherent Organization

3 July 2012 by Clark 8 Comments

In an insightful piece, Harold Jarche puts together how collaboration and cooperation are needed to make organizations work ‘smarter’, integrating workgroups with the broader social network by using communities of practice as the intermediary. This makes a lot of sense to me, and I was inspired to take a look at the practices within those categories. (Jay Cross has explored different facets of the implications of this way of thinking and talks about how we are building on this.)

In this depiction,we see behaviors of effective collaboration within work groups, such as coaching each other, using good practices for brainstorming, the elements of a learning organization, being willing to admit to problems, and being willing to lose if you don’t lose the lesson.

At the next level, communities of practice need to continue to evolve their practices, sharing issues and working together to resolve them. Within these communities, sharing pointers as well as deeper thoughts are mechanisms for ‘stealth mentoring‘ and explicit mentoring is valuable as well.

At the outermost level, social networks are about tracking what’s happening and who knows what, looking for developments in related fields as mechanisms for improving designs, and sharing practice is a way to give back to the community.

At the intersections, you need practices of both sharing outward and bringing inward, always looking for fresh inspiration and valuable feedback. The transparency provides real value in developing trust among the constituencies.

I put reflection underpinning all of these, as a core practice. Reflection is absolutely critical to continual improvement in every area.

Note that the firewall tends to cross the middle of the diagram, and by blocking access you’re effectively cutting off a portion of the corporate brain!

This should not by any means be considered definitive, as it’s my first draft, but I think it helps (me, at least) think about what practices could accelerate an organization to be both effective and efficient, able to move nimbly to deliver ongoing customer delight by continual innovation while executing as well. We’re thinking about this as the ‘Coherent Organization’, aligning the flows of information, and aligning the work with the organizational goals. As always, I welcome your feedback: what should be added, removed, modified, etc.

BJ Fogg #mLearnCon Keynote Mindmap

19 June 2012 by Clark Leave a Comment

BJ Fogg, known from his work on persuasive technology, talked about making persistent behavior change via tiny habits. Very interesting research with important implications both personally and commercially.

George Siemens #iel12 Keynote Mindmap

6 June 2012 by Clark Leave a Comment

George Siemens delivered an enlightening talk contextualizing analytics, tying the need for more effective coupling in decision making with new types of data.

Tony O’Driscoll #iel12 Keynote Mindmap

6 June 2012 by Clark Leave a Comment

Tony O’Driscoll kicked off the Innovations in eLearning Symposium with an entertaining and apt tour of the changes in business owing to information change, and the need to adapt. My take was that organizations have to become in a more organic relationship with their ecosystem by empowering their people to engage and act. His final message was that the learning community are the folks who have to figure this out and engage.

Taking the step

6 June 2012 by Clark 3 Comments

A while ago, I wrote an article in eLearnMag, stating that better design doesn’t take longer. In it, I suggested that while there would be an initial hiccup, eventually better design doesn’t take longer: the analysis process is different, but no less involved, the design process is deeper but results in less overall writing, and of course the development is largely the same. And I’m interested in exposing what I mean by the hiccup.

What surprised me is that I haven’t seen more movement. Of course, if you’re a one-person shop, the best you could probably do is attend a ‘Deeper ID’ workshop. But if you’re producing content on a reasonable scale, you should realize that there are several reasons you should be taking this on.

Most importantly, it’s for effectiveness. The learning I see coming out of not only training shops and custom content houses, but also internal units, is just not going to make a difference. If you’re providing knowledge and a knowledge test, I don’t care how well produced it is, it’s not going to make a difference. This is core to a unit’s mission, it seems to me.

It’s also a case of “not if, but when” when someone is going to come in with an effective competing approach. If you can’t do better, you’re going to be irrelevant. If you’re producing for others, your market will be eaten. If you’re producing internally, your job will be outsourced.

Overall, it’s about not just surviving, but thriving.

Yes, the nuances are subtle, and it’s still possible to sell well-produced but not well-designed material, but that can’t last. People are beginning to wake up to the business importance of effective investments in learning, and the emergence of alternate models (Khan Academy, MOOCs, the list goes on) is showing new ways that will have people debating approaches. It may take a while, but why not get the jump on it?

And it’s not about just running a workshop. I do those, and like to do them, but I never pretend that they’re going to make as big a difference as could be achieved. They can’t, because of the forgetting curve. What would make a big difference isn’t much more, however. It’s about reactivating that knowledge and reapplying.

What I envision (and excuse me if I make this personal, but hey, it’s what I do and have done successfully) is getting to know the design processes beforehand, and customizing the workshop to your workflow: your business, your processes of working with SMEs, your design process, your tools, and representative samples of existing work. Then we run a workshop where we use your examples. Working through the process, exploring the deeper concepts, putting them into practice, and reflecting to cement the learning. Probably a day. People have found this valuable in an of itself.

However, I want to take it just a step further. I’ve found that being sent samples of subsequent work and commenting on it in several joint sessions is what makes the real difference. This reactivates the knowledge, identifies the ongoing mistakes, and gives a chance to remediate them. This is what makes it stick, and leads to meaningful change. You have to manage this in a non-threatening way, but that’s doable.

There are more intrusive, higher-overhead ways, but I’m trying to strike a balance between high value and minimal intensiveness to make a pragmatic but successful change. I’d bet that 90% of the learning being developed could be improved by this approach (which means that 90% of the learning being developed really isn’t a worthwhile investment!). It seems so obvious, but I’m not seeing the interest in change. So, what am I missing?

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