Search Results for: engag

Non-invasive Brain Surgery

28 October 2015 by Clark Leave a Comment

Changing behavior is hard. The brain is arguably the most complex thing in the known universe. Simplistic approaches aren‘t likely to work. To rewire it, one approach is to try surgery. This is problematic for a several reasons: it‘s dangerous, it‘s messy, and we really don’t understand enough about it. What‘s a person to do?

Well, we do know that the brain can rewire itself, if we do it right. This is called learning. And if we design learning, e.g. instruction, we can potentially change the brain without surgery. However, (and yes, this is my point) treating it as anything less than brain surgery (or rocket science), isn‘t doing justice to what‘s known and what‘s to be done.

The number of ways to get it wrong is long. Information dump instead of skills practice. Massed practice instead of spaced. Rote knowledge assessment. Lack of emotional engagement. The list goes on. (Cue the Serious eLearning Manifesto.) In short, if you don‘t know what you‘re doing, you‘re likely doing it wrong and are not going to have an effect. Sure, you‘re not likely to kill anyone (unless you‘re doing this where it matters), but you‘ll waste money and time. Scandalous.

Again, the brain is complex, and consequently so is learning design. So why, in the name of sense and money, do we treat it as trivial? Why would anyone buy a story that we can achieve anything meaningful by taking content and adding a quiz (read: rapid eLearning)? As if a quiz is somehow going to make people do better. Who would believe that just anyone can present material and learning will occur? (Do you know the circumstances when that will work?) And really, throwing fuzzy objects around the room and ice-breakers will somehow make a difference? Please. If you can afford to throw money down the drain (ok, if you insist, throw it here ;), and don‘t care if any meaningful change happens, I pity you, but I can‘t condone it.

Let‘s get real. Let‘s be honest. There‘s a lot (a lot) of things being done in the name of learning that are just nonsensical. I could laugh, if I didn‘t care so much. But I care about learning. And we know what leads to learning. It‘s not easy. It‘s not even cheap. But it will work. It requires good analysis, and some creativity, and attention to detail, and even some testing and refinement, but we know how to do this.

So let‘s stop pretending. Let‘s stop paying lip-service. Let‘s treat learning design as the true blend of art and science that it is. It‘s not the last refuge of the untalented, it‘s one of the most challenging, and rewarding, things a person can do. When it‘s done right. So let‘s do it right! We‘re performing brain surgery, non-invasively, and we should be willing to do the hard yards to actually achieve success, and then reap the accolades.

OK, that‘s my rant, trying to stop what‘s being perpetrated and provide frameworks that might help change the game. What‘s your take?

The Polymath Proposition

15 October 2015 by Clark 3 Comments

At the recent DevLearn conference, one of the keynotes was Adam Savage. And he said something that gave me a sense of validation. He was talking about being a polymath, and I think that’s worth understanding.

His point was that his broad knowledge of a lot of things was valuable. While he wasn’t the world’s expert in any particular thing, he knew a lot about a lot of things. Now if you don’t know him, it helps to understand that he’s one of the two hosts of Mythbusters, a show that takes urban myths and puts them to the test. This requires designing experiments that fit within pragmatic constraints of cost and safety, and will answer the question. Good experiment design is an art as well as a science, and given the broad range of what the myths cover, this ends up requiring a large amount of ingenuity.

The reason I like this is that my interests vary broadly (ok, I’m coming to terms with a wee bit of ADD ;). The large picture is how technology can be designed to help us think, work, and learn. This ends up meaning I have to understand things like cognition and learning (my Ph.D. is in cognitive psychology), computers (I’ve programmed and designed architectures at many levels), design (I’ve looked at usability, software engineering, industrial design, architectural design, and more), and organizational issues (social, innovation…). It’s led to explorations covering things like games, mobile, and strategy (e.g. the topics of my books). And more; I’ve led development of adaptive learning systems, content models, learning content, performance support, social environments, and so on. It’s led me further, too, exploring org change and culture, myth and ritual, engagement and fun, aesthetics and media, and other things I can’t even recall right now.

And I draw upon models from as many fields as I can. My Ph.D. research was related to the power of models as a basis for solving new problems in uncertain domains, and so I continue to collect them like others collect autographs or music. I look for commonalities, and try to make my understanding explicit by continuing to diagram and write about my reflections. I immodestly think I draw upon a broad swath of areas. And I particularly push learning to learn and meta-cognition to others because it’s been so core to my own success.

What I thrive on is finding situations where the automatic solutions don’t apply. It’s not just a clear case for ID, or performance support, or… Where technology can be used (or used better) in systemic ways to create new opportunities. Where I really contribute is where it’s clear that change is needed, but what, how, and where to start aren’t obvious. I’ve a reliable track record of finding unique, and yet pragmatic solutions to such situations, including the above named areas I’ve innovated in. And it is a commitment of mine to do so in ways that pass on that knowledge, to work in collaboration to co-develop the approach and share the concepts driving it, to hand off ownership to the client. I’m not looking for a sinecure; I want to help while I’m adding value and move on when I’m not. And many folks have been happy to have my assistance.

It’s hard for me to talk about myself in this way, but I reckon I bring that polymath ability of a broad background to organizations trying to advance. It’s been in assisting their ability to develop design processes that yield better learning outcomes, through mobile strategies and solutions that meet their situation, to overarching organizational strategies that map from concepts to system. There’s a pretty fair track record to back up what I say.

I am deep in a lot of areas, and have the ability to synthesize solutions across these areas in integrated ways. I may not be the deepest in any one, but when you need to look across them and integrate a systemic solution, I like to think and try to ensure that I’m your guy. I help organizations envision a future state, identify the benefits and costs, and prioritize the opportunities to define a strategy. I have operated independently or with partners, but I adamantly retain my freedom to say what I truly think so that you get an unbiased response from the broad suite of principles I have to hand. That’s my commitment to integrity.

I didn’t intend this to be a commercial, but I did like his perspective and it made me reflect on what my own value proposition is. I welcome your thoughts. We now return you to your regularly scheduled blog already in progress…

Natalie Panek #DevLearn Keynote Mindmap

2 October 2015 by Clark Leave a Comment

To close off the DevLearn conference, Natalie Panek (@nmpanek) told of her learning journey to be a space engineer with compelling stories of challenging experiences. With an authentic and engaging style, she helped inspire us to keep learning.

Revolution Roadmap: Assess

23 September 2015 by Clark 3 Comments

Last week, I wrote about a process to follow in moving forward on the L&D Revolution. The first step is Assess, and I’ve been thinking about what that means. So here, let me lay out some preliminary thoughts.

The first level are the broad categories. As I’m talking about aligning with how we think, work, and learn, those are the three top areas where I feel we fail to recognize what’s known about cognition, individually and together. As I mentioned yesterday, I’m looking at how we use technology to facilitate productivity in ways specifically focused on helping people learn. But let me be clear, here I’m talking about the big picture of learning – problem-solving, design, research, innovation, etc – as they call fall under the category of things we don’t know the answer to when we begin.

I started with how we think. Too often we don’t put information in the world when we can, yet we know that all our thinking isn’t in our head. So we can ask :

Are you using performance consulting?
Are you taking responsibility for resource development?
Are you ensuring the information architecture for resources is user-focused?

The next area is working, and here the revelation is that the best outcomes come from people working together. Creative friction, when done in consonance with how we work together best, is where the best solutions and the best new ideas will come from. So you can look at:

Are people communicating?
Are people collaborating?
Do you have in place a learning culture?

Finally, with learning, as the area most familiar to L&D, we need to look at whether we’re applying what’s known about making learning work. We should start with Serious eLearning, but we can go farther. Things to look at include:

Are you practicing deeper learning design?
Are you designing engagement into learning?
Are you developing meta-learning?

In addition to each of these areas, there are cross-category issues. Things to look at for each include:

Do you have infrastructure?
What are you measuring?

All of these areas have nuances underneath, but at the top level these strike me as the core categories of questions. This is working down to a finer grain than I looked at in the book (c.f. Figure 8.1), though that was a good start at evaluating where one is.

I’m convinced that the first step for change is to understand where you are (before the next step, Learn, about where you could be). I’ve yet to see many organizations that are in full swing here, and I have persistently made the case that the status quo isn’t sufficient. So, are you ready to take the first step to assess where you are?

Biz tech

22 September 2015 by Clark 2 Comments

One of my arguments for the L&D revolution is the role that L&D could be playing. I believe that if L&D were truly enabling optimal execution as well as facilitating continual innovation (read: learning), then they’d be as critical to the organization as IT. And that made me think about how this role would differ.

To be sure, IT is critical. In today’s business, we track our business, do our modeling, run operations, and more with IT. There is plenty of vertical-specific software, from product design to transaction tracking, and of course more general business software such as document generation, financials, etc. So how does L&D be as ubiquitous as other software? Several ways.

First, formal learning software is really enterprise-wide. Whether it’s simulations/scenarios/serious games, spaced learning delivered via mobile, or user-generated content (note: I’m deliberately avoiding the LMS and courses ;), these things should play a role in preparing the audience to optimally execute and being accessed by a large proportion of the audience. And that’s not including our tools to develop same.

Similarly, our performance support solutions – portals housing job aids and context-sensitive support – should be broadly distributed. Yes, IT may own the portals, but in most cases they are not to be trusted to do a user- and usage-centered solution. L&D should be involved in ensuring that the solutions both articulate with and reflect the formal learning, and are organized by user need not business silo.

And of course the social network software – profiles and locators as well as communication and collaboration tools – should be under the purview of L&D. Again, IT may own them or maintain them, but the facilitation of their use, the understanding of the different roles and ensuring they’re being used efficiently, is a role for L&D.

My point here is that there is an enterprise-wide category of software, supporting learning in the big sense (including problem-solving, research, design, innovation), that should be under the oversight of L&D. And this is the way in which L&D becomes more critical to the enterprise. That it’s not just about taking people away from work and doing things to them before sending them back, but facilitating productive engagement and interaction throughout the workflow. At least at the places where they’re stepping outside of the known solutions, and that is increasingly going to be the case.

Aligning

25 August 2015 by Clark 2 Comments

I’m realizing that a major theme of my work and the revolution is that what we do in organizations, and what we do as L&D practitioners, is not aligned with how we think, work, and learn. And to that extent, we’re doomed to failure. We can, and need to, do better.

Let’s start with thinking. The major mismatch here is that our thinking is done rationally and in our head. Results in cognitive science show, instead, that much of our thinking is irrational and is distributed across the world. We use external representations and tools, and unless we’re experts, we make decisions and use our brains to justify them rather than actually do the hard work.

What does this mean for organizations and L&D? It means we should be looking to augment how we think, with tools and processes like performance support, helping us find information with powerful search. We want to have open book learning, since we’ll use the book in the real world, and we want to avoid putting it ‘in the head’ as much as possible. Particularly rote information. We should expect errors, and provide support with checklists, not naively expect that people can perform like robots.

This carries over to how we work. The old view is that we work alone, performing our task, and being managed from above with one person thinking for a number of folks. What we now know, however, is that this view isn’t optimal. The output is better when we get multiple complementary minds working together. Adaptation and innovation work best when we work together.

So we don’t need isolation to do our work, we need cooperation and collaboration. We need ways to work together. We need to give people meaningful tasks and give them space to execute, with appropriate support. We need to create environments where it’s safe to share, to show your work, to work out loud.

And our models of learning are broken. The trend to an event comprised of information dump and knowledge test we know doesn’t work. Rote procedures are no longer sufficient for the increasing ambiguity and unique situations our learners are seeing. And the notion that “practice ’til they get it right” will lead to any meaningful change in ability is fundamentally flawed.

To learn, we need models to guide our behavior and help us adapt. We need to identify and address misconceptions. We need learners to engage concretely and be scaffolded in reflection. And we need much practice. Our learning experiences need to look much more like scenarios and serious games, not like text and next.

We’re in an information age, and industrial models just won’t cut it. I’m finding that we’re hampered by a fundamental lack of awareness of our brains, and this is manifesting in too many unfortunate and ineffective practices. We need to get better. We know better paths, and we need to trod them. Let’s start acting like professionals and develop the expertise we need to do the job we must do.

#itashare

Teasing apart cooperation and collaboration

4 August 2015 by Clark 6 Comments

There have been a couple of recent proposals about the relative role of cooperation and collaboration, and I’m trying to make sense of them. Here are a couple of different approaches, and my first take at teasing them apart.

Dion Hinchcliffe of Adjuvi tweeted a diagram about different types of working together that shows his take. He has coordination as a subsidiary to cooperation and on to collaboration. So coordination is when we know what needs to be done, but we can’t do it alone. Cooperation is when we’re doing things that need to have a contribution from each of us, and requires some integration. And collaboration is when we’re working together with a goal but not clear how we’ll get there. I think what’s core here is how well defined the task is and how much we contribute.

In the meantime, Harold Jarche, my ITA colleague, as a different take. He sees collaboration as working together to achieve a goal that’s for the organization, whereas cooperation goes beyond. Cooperation is where we participate and assist one another for our own goals. It’s contribution that’s uncoupled from any sense of requirement, and is freely given. I see here the discussion is more about our motives; why are we engaged.

With those two different takes, I see them as different ways of carving up the activities. My initial reaction is closer to Dion’s; I’ve always seen cooperation as willingness to assist when asked, or to provide pointers. To me collaboration is higher; it’s willing to not just provide assistance in clearly defined ways such as pointers to relevant work, answering questions, etc, but to actively roll up sleeves and pitch in. (Coordination is, to me I guess, a subset of cooperation.) With collaboration I’ve got a vested interest in the outcome, and am willing to help frame the question, do independent research, iterate, and persist to achieve the outcome.

I see the issue of motivation or goal as a different thing. I can cooperate in a company-directed manner, as expected, but I also can (and do) cooperate in a broader sense; when people ask for help (my principles are simple: talk ideas for free; help someone personally for dinner/drinks; if someone’s making a quid I get a cut), I will try to assist (with the Least Assistance Principle in mind). I can also collaborate on mutual goals (whether ITA projects or client work), but then I can also collaborate on things that have no immediate outcome except to improve the industry as a whole (*cough* Serious eLearning Manifesto *cough*).

So I see two independent dimensions: one on the effort invested, just responding to need or actively contributing; and the other on the motivation, whether for a structured goal or for the greater good.

Now I have no belief that either of them will necessarily agree with my take, but I’d like to reconcile these interpretations for the overall understanding (or at least my own!). That’s my first take, feedback welcome!

SME Brains

30 June 2015 by Clark 1 Comment

As I push for better learning design, I’m regularly reminded that working with subject matter experts (SMEs) is critical, and problematic. What makes SMEs has implications that are challenging but also offers a uniquely valuable perspective. I want to review some of those challenges and opportunities in one go.

One of the artifacts about how our brain works is that we compile knowledge away. We start off with conscious awareness of what we’re supposed to be doing, and apply it in context. As we practice, however, our expertise becomes chunked up, and increasingly automatic. As it does so, some of the elements that are compiled away are awarenesses that are not available to conscious inspection. As Richard Clark of the Cognitive Technology Lab at USC lets us know, about 70% of what SMEs do isn’t available to their conscious mind. Or, to put it another way, they literally can’t tell us what they do!

On the other hand, they have pretty good access to what they know. They can cite all the knowledge they have to hand. They can talk about the facts and the concepts, but not the decisions. And, to be fair, many of them aren’t really good at the concepts, at least not from the perspective of being able to articulate a model that is of use in the learning process.

The problem then becomes a combination of both finding a good SME, and working with them in a useful way to get meaningful objectives, to start. And while there are quite rigorous ways (e.g. Cognitive Task Analysis), in general we need more heuristic approaches.

My recommendation, grounded in Sid Meier’s statement that “good games are a series of interesting decisions” and the recognition that making better decisions are likely to be the most valuable outcome of learning, is to focus rabidly on decisions. When SMEs start talking about “they need to know X” and “they need to know Y” is to ask leading questions like “what decisions do they need to be able to make that they don’t make know” and “how does X or Y actually lead them to make better decisions”.

Your end goal here is to winnow the knowledge away and get to the models that will make a difference to the learner’s ability to act. And when you’re pressed by a certification body that you need to represent what the SME tells you, you may need to push back. I even advocate anticipating what the models and decisions are likely to be, and getting the SME to criticize and improve, rather than let them start with a blank slate. This does require some smarts on the part of the designer, but when it works, it leverages the fact that it’s easier to critique than generate.

They also are potentially valuable in the ways that they recognize where learners go wrong, particularly if they train. Most of the time, mistakes aren’t random, but are based upon some inappropriate models. Ideally, you have access to these reliable mistakes, and the reason why they’re made. Your SMEs should be able to help here. They should know ways in which non-experts fail. It may be the case that some SMEs aren’t as good as others here, so again, as in ones that have access to the models, you need to be selective.

This is related to one of the two ways SMEs are your ally. Ideally, you’re equipped with stories, great failures and great successes. These form the basis of your examples, and ideally come in the form of a story. A SME should have some examples of both that they can spin and you can use to build up an example. This may well be part of your process to get the concepts and practice down, but you need to get these case studies.

There’s one other way that SMEs can help. The fact that they are experts is based upon the fact that they somehow find the topic fascinating or rewarding enough to spend the requisite time to acquire expertise. You can, and should, tap into that. Find out what makes this particular field interesting, and use that as a way to communicate the intrinsic interest to learners. Are they playing detective, problem-solver, or protector? What’s the appeal, and then build that into the practice stories you ask learners to engage in.

Working with SMEs isn’t easy, but it is critical. Understanding what they can do, and where they intrinsic barriers, gives you a better handle on being able to get what you need to assist learners in being able to perform. Here are some of my tips, what have you found that works?

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