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Dimensions of difficulty

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As one of the things I talk about, I was exploring the dimensions of difficulty for performance that guide the solutions we should offer.  What determines when we should use performance support, automate approaches, we need formal training, or a blend, or…?  It’s important to have criteria so that we can make a sensible determination. So, I started trying to map it out. And, not surprisingly, it’s not complete, but I thought I’d share some of the thinking.

So one of the dimensions is clearly complexity.  How difficult is this task to comprehend? How does it vary? Connecting and operating a simple device isn’t very complex. Addressing complex product complaints can be much more complex. Certainly we need more support if it’s more complex. That could be trying to put information into the world if possible. It also would suggest more training if it has to be in the head.

A second dimension is frequency of use. If it’s something you’ll likely do frequently, getting you up to speed is more important than maintaining your capability. On the other hand, if it only happens infrequently, it’s hard to try to keep it in the head, and you’re more likely to want to try to keep it in the world.

And a third obvious dimension is importance. If the consequences aren’t too onerous if there are mistakes, you can be more slack. On the other hand, say if lives are on the line, the consequences of failure raise the game. You’d like to automate it if you could (machines don’t fatigue), but of course the situation has to be well defined. Otherwise, you’re going to want lot of training.

And it’s the interactions that matter. For instance, flight errors are hopefully rare (the systems are robust), typically involve complex situations (the interactions between the systems mean engines affect flight controls), and have big consequences!  That’s why there is a huge effort in pilot preparation.

It’s hard to map this out. For one, is it just low/high, or does it differentiate in a more granular sense: e.g. low/medium/high?  And for three dimensions it’s hard to represent in a visually compelling way. Do you use two (or three) two dimensional tables?

Yet you’d like to capture some of the implications: example above for flight errors explains much investment. Low consequences suggest low investment obviously. Complexity and infrequency suggest more spacing of practice.

It may be that there’s no one answer. Each situation will require an assessment of the mental task. However, some principles will overarch, e.g. put it in the world when you can. Avoiding taxing our mental resources is good. Using our brains for complex pattern matching and decision making is likely better than remembering arbitrary and rote steps. And, of course, think of the brain and the world as partners, Intelligence Augmentation, is better than just focusing on one or another. Still, we need to be aware of, and assessing, the dimensions of difficulty as part of our solution.  Am I missing some? Are you aware of any good guides?

Engaging Learning and the Serious eLearning Manifesto

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Way back in ’05, my book on games for learning was published. At its core was an alignment between what made an effective education practice and what makes engaging experiences. There were nine elements that characterized why learning should be ‘hard fun’. More recently, we released the Serious eLearning Manifesto. Here we had eight values that differentiated between ordinary elearning and serious elearning. So, the open question is how do these two lists match up? What is the alignment between Engaging Learning and the Serious eLearning manifesto?

The elements of the Serious eLearning Manifesto (SeM) are pretty straightforward. They’re listed as:

  • performance focused
  • meaningful to learners
  • engagement driven
  • authentic contexts
  • realistic decisions
  • real-world consequences
  • spaced practice
  • individualized challenges

The alignment (EEA: Effectiveness-Engagement Alignment) I found in Engaging Learning was based upon research I did on designing games for learning. I found elements that were repeated across proposals for effective education practice, and ones that were stipulated for engaging experiences. And I found a perfect overlap. Looking for a resolution between the two lists of elements looks something like:

  • clear goals
  • balanced challenge
  • context for the action
  • meaningful to domain
  • meaningful to learner
  • choice
  • active
  • consequences
  • novelty

And, with a little wordsmithing, I think we find a pretty good overlap!  Obviously, not perfect, because they have different goals, but the important elements of a compelling learning experience emerge.

I could fiddle and suggest that clear goals are aligned to a performance focus, but instead that’s coming from making their learning be meaningful to the domain. I suggest that what really matters to organizations will be the ability to do, not know.  So, really, the goals are implicit in the SeM; you shouldn’t be designing learning unless you have some learning goals!

Then, the balanced challenge is similar to the individualized challenge from the SeM. And context maps directly as well. As do consequences. And meaningfulness to learners. All these directly correspond.

Going a little further, I suggest that having choice (or appearance thereof) is important for realistic decisions. There should be alternatives that represent misconceptions about how to act. And, I suggest that the active focus is part of being engaging. Though, so too could novelty be. I’m not looking at multiple mappings but they would make sense as several things would combine to make a performance focus, as well as realistic decisions.

Other than that, on the EEA side the notion of novelty is more for engaging experiences than necessarily specific to serious elearning. On the SeM side, spaced practice is unique to learning. The notion of a game implies the ability for successful practice, so it’s implicit.

My short take, through this exercise, is to feel confident in both recommendations. We’re talking learning experience design here, and having the learning combine engagement as well is a nice outcome. I note that I’ll be running a Learning Experience Design workshop at DevLearn in October in Las Vegas, where’ll we’ll put these ideas to work. Hope to see you there!

The ITA Jay Cross Memorial Award for 2019: Michelle Ockers

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Over a decade ago, my friend Jay Cross invited me to join the Internet Time Alliance. He had been touting the value of Informal Learning, and realized he was doing it alone. I was honored to join Jane Hart, Harold Jarche, and Charles Jennings, and have come to know and value them as colleagues and friends. When Jay passed away, we determined to honor his ideas by recognizing those who continue to carry the banner for informal learning. We announce the ITA memorial award on 5 July, Jay’s birthday. This year’s winner is Michelle Ockers.

I’ve only met Michelle once, when I was visiting Australia to deliver a keynote. She was kind enough to ask me to sign a copy of Revolutionize L&D. I didn’t know much about her work then, but have subsequently seen it in a variety of places. She’s active in social media, for instance. She also coordinated the Learning & Performance Institute capability map exercise that occurred last summer. She’s systematically demonstrated broad ranging interests and abilities around organizational learning.

I’m pleased that we can honor her and her work helping organizations work more productively and fluidly. The official announcement is on the ITA site. Congratulations, Michelle on the 2019 ITA Jay Cross Memorial Award!

 

Reconciling Cognitions and Contexts

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In my past two posts, I first looked at cognitions (situated, distributed, social) by contexts (think, work, and learn), and then the reverse. And, having filled out the matrixes anew, they weren’t quite the same. And that, I think, is the benefit of the exercise, a chance to think anew. So what emerged? Here’s the result of reconciling cognitions and contexts.

Situated/Distributed/Social by Think/Work/LearnSo, taking each cell back in the original pass of cognitions by contexts, what results? I took the Think row to, indeed, be Harold Jarche’s Seek > Sense > Share model (ok, my interpretation). We have in Situated, the feeds you’ve set up to see, and then the particular searches you need in the current context. Then, of course, you experiment and represent as ways to externalize thinking for Distributed. Finally, you share Socially.

For Work, not practices but principles (and the associated practices therefrom) as well as facilitation to support Situated Work. Performance support is, indeed, the Distributed support for Work. And Socially, you need to collaborate on specific tasks and cooperate in general.

Finally, for Learning, for a Situated world you need (spread) contextualized practice to support appropriate abstraction of the principles. You want models and examples to support performance in the practice, as Distributed resources. And, finally, for Social Learning, you need to communicate (e.g. discussions) and collaborate (group projects).

What’s changed is that I added search and feeds, and moved experiment, in the Think row. I went to principles from practices to support performance in ambiguity, left performance support untouched, and stayed with collaborations and cooperation instead of just shared representations (they’re part of collaborate). And, finally, I made practice about contexts, went from blended learning to support materials for learning, and interpreted social assignments as communicating and collaborating.

The question is, what does this mean? Does it give us any traction? I’m thinking it does, as it shifts the focus in what we’re doing to support folks. So I think it was interesting and valuable (to my thinking, at least ;) to consider reconciling cognitions and contexts.

Contexts By Cognitions

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So, in my last post, I talked about exploring the links between cognitions on the one hand (situated, distributed, social), and contexts (aligning with how we think, work, & learn).  I did it one way, but then I thought to do it another, to instead consider Contexts by Cognitions, to see if I came to the same elements. And they weren’t quite identical!  So I thought I should share that thinking, and then come to a reconciliation. Thinking out loud, as it were.

Considering thinking, working, and learning by situated, distributed, and social.So in this one, I swapped the headings, emptied the matrix, and took a second stab at filling them out, with a relatively clear mind. (I generated the first diagram several days ago and had been iterating on it, but not today. Today I was writing it up and was early in the process, so I came to it relatively free of contamination. And of course, not completely, but this is ‘business significance’, not ‘statistical significance’ ;). The resulting diagram appears similar, but also some differences.

When we consider Thinking by Situated, we’re talking about coping with emergent situations. I thought being guided by best principles would be the way to cope, abstracted models. I thought representation was key for distributing one’s thinking, and sharing of course for social.

Working Situatedly suggested having in-house practices and facilitation. Of course, Distributed support for Work is performance support. And working socially suggests shared representations.

Finally, learning situated suggests the need for much practice (across contexts, I now think). Distributed support for learning are models and examples. And social learning suggests communicating (e.g. discussions) and collaboration (group projects).

Interestingly, these results differ from my previous post. So, I think I’ll have to reconcile them. The fact that I did get different results, and it sparked some additional thinking, is good. The outcome of considering contexts by cognitions improved the outcomes, I think. And that’s worth thinking about!

Graham Roberts #Realities360 Keynote Mindmap

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Graham Roberts kicked off the 2nd day of the Realities 360 conference talking about the Future of Immersive Storytelling. He told about their experiences and lessons building an ongoing suite of experiences. From the first efforts through to the most recent it was insightful. The examples were vibrant inspirations.

Cognitions By Contexts

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I have, in the past, talked about the three cognitions: situated, distributed, and social. Similarly, I talk about aligning with the contexts: how we think, work, and learn. I then wondered about how they interacted. Naturally, I diagrammed it (surprise, right?). I created the 3 x 3 matrix, and then tried to fill the boxes.  So here’s some preliminary thoughts (ok, they’ve already been processed a few times) on considering cognitions by contexts.

The intersections do point to some implications.  Cutting through the contexts by cognitions, we can make some prescriptions. When we think of Situated by Think, I suggested experimentation as a mechanism to help resolve unclear outcomes. Situated by Work suggested the ambiguity inherent in new situations, and suggested supporting addressing that. Finally, Situated for Learning suggests the need for meaningful practice.

Similarly, when we look at Distributed by Thinking, I considered the need to represent understanding concretely. For Work, it’s about using external tools to support effective performance, e.g. performance support. For Learning, it’s about blending learning across a variety of elements: technologies, interaction methodologies, etc, to support successful outcomes.

Social is a bit of a conflict, because I often mean that as a reflection of ‘work’. Here, however, I’m considering Work as ‘getting stuff done’. (Note to self: reconcile this!). So Social and Think is the notion of sharing the results (hmm, pondering in next paragraph). Social and Work is collaboration & cooperation, working together specifically on projects and also more broadly a willingness to contribute when/where/ever. Finally, Social for learning is social assignments.

Which makes me think that the whole ‘Think’ line could be Harold Jarche’s Seek > Sense > Share model, and then we’re talking about the Situated Thinking would be continually seeking new information to help settle ambiguity. Which is a nice idea I might put in, but then I have to consider where I put experiment. That may have to go in with ‘represent’ in Distributed and Think.

I also, as an experiment, decided to swap the labels (horizontal for vertical), and see if I came up with the same inputs. And, no, I didn’t. That’s my next post, the swapped version. It won’t be ’til the beginning of July, because next week I’m speaking at the Realities 360 conference, and will be posting mindmaps of the keynotes, if all things go per usual. And there’ll be a reconciliation after that, as the above paragraph suggests. Stay tuned! But here you see me ‘think out loud’ as I try to consider Cognitions By Contexts. I welcome any thoughts of yours!

Working virtually

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Of late, I’ve been involved in two separate initiatives that are distributed, one nationally, one internationally. And, as with some other endeavors, I’ve been using some tools to make this work. And, finally, it really really is. I’m finding it extraordinarily productive to be working virtually.

In both endeavors, there’s trust. One’s with folks I know, which makes it easy. The other’s with folks who have an international reputation for scholarly work, and that generates an initial acceptance. Working together quickly generates that.

Working

The work itself, as with most things, comes down to communication, collaboration, and cooperation. We’ve got initiatives to plan, draft, review, and execute. And we need to make decisions.

We’re using one social media tool to coordinate. In both cases, we’re using Slack as the primary tool for asynchronous communications. We’re setting up meetings (sometimes with the help of Doodle), asking questions, updating on occurrences, and sharing thoughts.

We’re using different tools for synchronous sessions. In one, we’re using Zoom, Blue Jeans in the other. I like Zoom a bit better because when you open the chat or the list of participants, it expands the window. In Blue Jeans, it covers a bit of the screen. Both, however, handle video streams without a problem.

And, for both, we’re using Google tools to create shared representations. Documents, and occasionally spreadsheets, mostly. I’m experimenting with their draw tools; while they’re not as smooth as OmniGraffle, they’re quite robust. It’s even fun to be working together watching several of us editing a doc at the same time!

There are always the hiccups; sometimes one or another can’t attend a meeting, or we lose track of files, but nothing that doesn’t plague co-located work. One problem that’s unique is those folks who aren’t regular users of one or the other tools. But we’ve enough peer pressure to remedy that. And, of course, these are folks who are in tech…

Reflecting

One key element, I think, is the ‘working out loud’. It’s pretty easy to share, and people do. Thinking is largely out in the open. There’re subcommittees, for instance, that may work on specific issues, and some executive discussions, but little you can’t see.

And we’re unconsciously working in, and consciously working on, a desirable learning culture. We’re sharing safely, considering ideas fairly, taking time to reflect, and actively seeking diversity. We experiment, and we do serendipitously review our practices (particularly when we onboard new folks).

Most importantly, this is beginning to not only feel natural, but productive.  This is the new world of work. Using tools to handle collaboration, coordination, and cooperation (the 3 c’s?).  We’re working, and evolving too!

And, a key learning for me, is that this doesn’t preclude being co-located. Though I wonder if that would actually hurt, since hallway conversations can progress things but there’re no trails. Unless, I suppose, if you commit to immediately capture whatever emerges. That’s a cultural thing.

This working virtually is a direction I think will be productive for organizations going forward. It’s social, it’s augmented, and it’s culturally sound. It’s not to say that I won’t welcome the chance to be co-located with these folks at some point. There might even be hugs between folks who’ve never met before (that happens when you interact in a safe space online). But the important thing is that it works, well. And what else needs to be said, after all?

 

Cognition external

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reading outsideI was thinking a bit about distributed cognition, and recognized that there as a potentially important way to tease that apart. And I’ll talk it out first here, and maybe a diagram will emerge. Or not. The point is to think about how external tools can augment our thinking. Or, really, a way that at least partly, we have cognition external.

The evidence says that our thinking isn’t completely in our head. And I’ve suggested that that makes a good case for performance support. But I realize it goes further in ways I’ve thought about it elsewhere. So I want to pull those together.

The alternative to performance support, a sort of cognitive scaffolding, is to think about representation. Here we’re not necessarily supporting any particular performance, but instead supporting developing thinking. I shared Jane Hart’s diagram yesterday, and I know that it’s a revision of a prior one. And that’s important!

The diagram is capturing her framework, and such externalizations are a way to share; they’re a social as well as artifactual sharing. It’s part of a ‘show your work‘ approach to continuing to think. Of course, it doesn’t have to be social, it can be personal.

So both of these forms of distributed cognition are externalizing our thinking in ways that our minds have trouble comprehending. We can play around with relationships by spatially representing them. We can augment our cognitive gaps both formally through performance support, and informally by supporting externalizing our thinking. Spreadsheets are another tool to externalize our thinking. So, too, for that matter, is text.

So we can augment our performance, and scaffold our thinking. Both can be social or solitary, but they both qualify as forms of distributed cognition (beyond social). And, importantly, both then should be consciously considered in thinking about revolutionizing L&D. We should be designing for cognition external. The tools should be there, and the facilitation, to use either when appropriate. So, think distributed, as well as situated, and social. It’s how our brains work, we ought to use that as a guide. You think?