David Kwong wowed the Learning Solutions audience with amazing tricks and a bit of insight into the nature of magic based upon our brains.
Bill Nye (Science Guy) #LSCon Keynote Mindmap
As the opening keynote for the always excellent Learning Solutions conference, Bill Nye gave an entertaining talk on the benefits of science and learning, drawing on his experience. I really liked how he paid tribute to his father’s fascination with sundials to get one put on the Mars rovers.
Context Rules
I was watching a blab (a video chat tool) about the upcoming FocusOn Learning, a new event from the eLearning Guild. This conference combines their previous mLearnCon and Performance Support Symposium with the addition of video. The previous events have been great, and I’ll of course be there (offering a workshop on cognition for mobile, a mobile learning 101 session, and one on the topic of this post). Listening to folks talk about the conference led me to ponder the connection, and something struck me.
I find it kind of misleading that it’s FocusOn Learning, given that performance support, mobile, and even video typically is more about acting in the moment than developing over time. Mobile device use tends to be more about quick access than extended experience. Performance support is more about augmenting our cognitive capabilities. Video (as opposed to animation or images or graphics, and similar to photos) is about showing how things happen in situ (I note that this is my distinction, and they may well include animation in their definition of video, caveat emptor). The unifying element to me is context.
So, mobile is a platform. It’s a computational medium, and as such is the same sort of computational augment that a desktop is. Except that it can be with you. Moreover, it can have sensors, so not just providing computational capabilities where you are, but because of when and where you are.
Performance support is about providing a cognitive augment. It can be any medium – paper, audio, digital – but it’s about providing support for the gaps in our mental capabilities. Our architecture is powerful, but has limitations, and we can provide support to minimize those problems. It’s about support in the moment, that is, in context.
And video, like photos, inherently captures context. Unlike an animation that represents conceptual distinctions separated from the real world along one or more dimensions, a video accurately captures what the camera sees happening. It’s again about context.
And the interesting thing to me is that we can support performance in the moment, whether a lookup table or a howto video, without learning necessarily happening. And that’s OK! It’s also possible to use context to support learning, and in fact we can provide least material to augment a context than create an artificial context which so much of learning requires.
What excited me was that there was a discussion about AR and AI. And these, to me, are also about context. Augmented Reality layers information on top of your current context. And the way you start doing contextually relevant content delivery is with rules tied to content descriptors (content systems), and such rules are really part of an intelligently adaptive system.
So I’m inclined to think this conference is about leveraging context in intelligent ways. Or that it can be, will be, and should be. Your mileage may vary ;).
The Quinnovation Spring ’16 Itinerary
As usual, there’re a number of events queued up for the coming months:
I’ll be at Learning Solutions doing a couple sessions, one on measurement, one on culture, next week March 16-18 in Orlando. Both key issues in the ‘revolution‘.
And I’ll be at FocusOn Learning June 7-10 in Austin, with a workshop on mobile cognition, an introductory mlearning session, and a talk on context.
I’ll also be keynoting the International Conference on eLearning in the Workplace June 15-17 in New York.
There’re a couple more that may be showing up, and of course there’re some special events for clients happening in various places as well. If you’re going, say ‘hello’!
Metacognitive Activity?
So, as another outcome of the xAPI base camp a few weeks back, I was wondering about tracking not only learning, but meta-learning. That is, not only what activity might mean ‘learning’, but what might mean ‘meta-learning’ is happening? I started wondering about a vocabulary, but realized that you’d have to have activity that you could actually detect that was evidence of meta-learning. And I didn’t know what that was. Naturally, I started diagramming.
I started with Harold Jarche’s Personal Knowledge Mastery model of Seek-Sense-Share. This is about how you continue to learn in manageable ways, and it served as an organizing framework. To each of the elements, I attributed activities that would constitute learning in that model, and then above it I was thinking what would constitute meta-learning.
So, for seek, we start with reading what comes into your feeds, searching about particular topics, and asking questions of your network. Sensing is about reconciling what’s found with your own knowledge. So you could write or present, diagram (see what I did there?), or experiment. And then to share you can post, or comment, or send a pointer to something.
So what are actions that reflect on those actions? For seeking, you can adjust your feeds of what you follow, you can try a different search mechanism, or you can follow new people. These are all detectable, I reckon.
For sensing, I see it as a little harder. How do we know when you’re annotating a document with the underlying thinking, not just documenting your progress? How do we know when you’re explaining the thinking behind a diagram (here it’d be about my choice of vertical dimension, and spreading things below and above)? How do we know when you’re actually reviewing your experimental approach or the results?
For sharing, it’s a mixed bag. If you choose to use a different media (perhaps it’s relative, like when I created an animation after blogging for > 10 years ;), we might know. If you try out a new social media platform/channel, we can probably note that. If you’re reflecting on your comments from others, how would we know?
And this is just one way of carving it up. The point being, meta is good, but detecting and tracking it is hard. We might ask people to annotate it with tags, but that’s problematic too. I have no obvious answers, but it’s a question I had, and I’m thinking out loud about it. I welcome your thoughts, too.
Mindmapping
So, if you haven’t figured it out yet, I do mindmaps. As I’ve recited before, I started doing it as a way to occupy my brain enough so I could listen to keynotes, but occasionally I use it to other purposes, such as representing structure or even planning. And thru my esteemed colleague Jane Hart (who’s Modern Workplace Learning book I’m going through and thoroughly impressed), I’m giving a mindmapping webinar today for a group of several universities in Ireland. I thought I’d share what I’m presenting.
Mindmaps are a visual way of representing knowledge. You use links to show connections between concepts (represented as nodes), developing a structural relationship. A true semantic network would have those links labeled, as there are many different types of relationships (causal, precedence, hierarchical), but mindmaps typically have unlabeled links. Still, mindmaps capture structural information in a visual way, that supports tapping into our powerful visual processing system. (This is the one I created for them to advertise the talk, it’s neither the order I ended up for them or am using here. ;)
You can add information to them; as a visual tool, you can add extra graphical information, like tables or charts, to augment the map. You can similarly add color as a way to layer additional semantic information such as similarity. And the links can be plain or directional. Importantly, while a mindmap can be essentially equivalent to an outline if you maintain a strict tree structure, you can create a graph by having more complex links that generate loops.
The process of mindmapping is fairly straightforward: you have a central node, and then generate additional nodes and link them. I tend to go counter-clockwise, and include an arrow indicating that, because I’m capturing a linear presentation, but generating a static representation of information doesn’t have any directional requirement. I find that I have to frequently rearrange to fit the mindmap appropriately to the image, but that’s part of the benefit.
The evidence appears to show that mindmapping is superior to note-taking. I don’t do it all the time, but there are reasons to think you should. The reasons, I believe, that it is better is that you’re not just transcribing a presentation, but you’re actively parsing it to represent the structure. If you do take notes, you should be paraphrasing what you hear in your own words, to have active processing of the information. The additional effort to extract the structure as well is a form of valuable cognitive processing that elaborates the information. Doing both, paraphrasing and extracting structure, would be a great way to really comprehend what you’re hearing.
As suggested, it’s helpful to mindmap talks, but it can also be a thinking tool, to analyze situations and sort out your thoughts or plan activities and add elements as you think of them. No real advantage over an outline, potentially (though the ability to add other graphics and to make non-strict maps may counter that), though I suspect some find the drawing and rearranging to be a nice physical overhead to facilitate reflecting. And, of course, it can be an evaluation tool, asking someone to create their maps to see their understanding.
While there are dedicated tools for mindmapping, both applications and in the cloud, which will make creating and rearranging easier (I presume), you can use almost any drawing package (I use OmniGraffle). You could use Powerpoint or Keynote, and even pencil and paper (if it’s just for the processing) though it can be harder to revise.
So, that’s my riff on mind mapping. I welcome your thoughts.
Content isn’t a silo
I mentioned in my previous post that I was talking at the xAPI camp about content strategy, and on the way in I created a new diagram to convey a concept I wanted to discuss. Of course one of the things I agitate about for the revolution is that L&D can’t hide away but has to start engaging across the business. And, let me add, that’s only increasing. Our silos are breaking down. To wit:
Here I was trying to think of activities that cross silos. So, of course, the overall role of the business aligns and integrates the separate actions of sales, marketing, IT, etc. And, to suit my campaign, I looked for others.
Obviously, data is coming out across the organization. As I mentioned in that last post, we can only look at the impact of L&D on performance if we can start working with data from the business units, but data from customer service influences marketing, and so on.
The web, too, is a channel for many activities. Units that reach customers, for instance, include customer service, customer education, sales & marketing, and more. Heck, the supply chain is increasingly connected by the web, and data.
Consequently, so too is content. Content is used in many ways, whether via apps, through the web, or print. And for many purposes: sales, marketing, tech support, and of course learning. And there’s a point to all this.
L&D, with it’s hard-wired content, needs to pull on the big kids pants, and start getting with content systems: content engineering, governance, and strategy. Truly, if you want to be part of the strategic picture going forward, you have to work with information tools. Industrial age methods won’t cut it. So, are you thinking about how to move to a content strategy?
xAPI conceptualized
A couple of weeks ago, I had the pleasure of attending the xAPI Base Camp, to present on content strategy. While I was there, I remembered that I have some colleagues who don’t see the connection between xAPI and learning. And it occurred to me that I hadn’t seen a good diagram that helped explain how this all worked. So I asked and was confirmed in my suspicion. And, of course, I had to take a stab at it.
What I was trying to capture was how xAPI tracked activity, and that could then be used for insight. I think one of the problems people have is that they think xAPI is a solution all in itself, but it is just a syntax for reporting.
So when A might demonstrate a capability at a particular level, say at the end of learning, or by affirmation from a coach or mentor, that gets recorded in a Learning Record Store. We can see that A and B demonstrated it, and C demonstrated a different level of capability (it could also be that there’s no record for C, or D, or…).
From there, we can compare that activity with results. Our business intelligence system can provide aggregated data of performance for A (whatever A is being measured on: sales data, errors, time to solve customer problems, customer satisfaction, etc). With that, we can see if there are the correlations we expect, e.g. everyone who demonstrated this level of capability has reliably better performance than those who didn’t. Or whatever you’re expecting.
Of course, you can mine the data too, seeing what emerges. But the point is that there are a wide variety of things we might track (who touched this job aid, who liked this article, etc), and a wide variety of impacts we might hope for. I reckon that you should plan what impacts you expect from your intervention, put in checks to see, and then see if you get what you intended. But we can look at a lot more interventions than just courses. We can look to see if those more active in the community perform better, or any other question tied to a much richer picture than we get other ways.
Ok, so you can do this with your own data generating mechanisms, but standardization has benefits (how about agreeing that red means stop?). So, first, does this align with your understanding, or did I miss something? And, second does this help, at all?
When to gamify?
I’ve had lurking in my ‘to do’ list a comment about doing a post on when to gamify. In general, of course, I avoid it, but I have to acknowledge there are times when it makes sense. And someone challenged me to think about what those circumstances are. So here I’m taking a principled shot at it, but I also welcome your thoughts.
To be clear, let me first define what gamification is to me. So, I’m a big fan of serious games, that is when you wrap meaningful decisions into contexts that are intrinsically meaningful. And I can be convinced that there are times when tarting up memory practice with quiz-show window-dressing makes sense, e.g. when it has to be ‘in the head’. What I typically refer to as gamification, however, is where you use external resources, such as scores, leaderboards, badges, and rewards to support behavior you want to happen.
I happened to hear a gamification expert talk, and he pointed out some rules about what he termed ‘goal science’. He had five pillars:
- that clear goals makes people feel connected and aligns the organization
- that working on goals together (in a competitive sense ;) makes them feel supported
- that feedback helps people progress in systematic ways
- that the tight loop of feedback is more personalized
- that choosing challenging goals engages people
Implicit in this is that you do good goal setting and rewards. You have to have some good alignment to get these points across. He made the point that doing it badly could be worse than not doing it at all!
With these ground rules, we can think about when it might make sense. I’ll argue that one obvious, and probably sad case, would be when you don’t have a coherent organization, and people aren’t aware of their role in the organization. Making up for effective communication isn’t necessarily a good thing, in my mind.
I think it also might make sense for a fun diversion to achieve a short-term goal. This might be particularly useful for an organizational change, when extra motivation could be of assistance in supporting new behaviors. (Say, for moving to a coherent organization. ;) Or some periodic event, supporting say a philanthropic commitment related to the organization.
And it can be a reward for a desired behavior, such as my frequent flier points. I collect them, hoping to spend them. I resent it, a bit, because it’s never as good as is promised, which is a worry. Which means it’s not being done well.
On the other hand, I can’t see using it on an ongoing basis, as it seems it would undermine the intrinsic motivation of doing meaningful work. Making up for a lack of meaningful work would be a bad thing, too.
So, I recall talking to a guy many moons ago who was an expert in motivation for the workplace. And I had the opportunity to see the staggering amount of stuff available to orgs to reward behavior (largely sales) at an exhibit happening next to our event. It’s clear I’m not an expert, but while I’ll stick to my guns about preferring intrinsic motivation, I’m quite willing to believe that there are times it works, including on me.
Ok, those are my thoughts, what’ve I missed?
The magic question
A number of years ago, I wrote a paper about design, some of the barriers our cognitive architecture provides, and some heuristics I used to get around them. I wrote a summary of the paper as four posts, starting here. I was reminded of one of the heuristics in a conversation, and had a slightly deeper realization that of course I wanted to share.
The approach, which I then called ‘no-limits’ design, has to do with looking at what solution you’d develop if you had no limits. I now think of it as the ‘magic’ approach. As I mentioned in the post series, this approach asks what you’d design if you had magic (and referred to the famous Arthur C. Clarke quote). And while I indicated one in the past, I think there are two benefits to this approach.
First, if you consider what you’d do if you have magic, you can help prevent a common problem, premature convergence. Our cognitive architecture has weaknesses, and a couple of them revolve around solving problems in known ways and using tools in familiar ways. It’s too easy to subconsciously rule out new options. By asking the ‘magic’ question, we ask ourselves to step outside what we’ve known and believe is possible, and consider the options we’d have if we didn’t have the technological limitations.
Similarly, using the notion of ‘magic’ can help us explore other models for accomplishing the goal. If design is not just evolutionary, but you also want to explore the opportunities to revolutionize, you need some way to spark new thinking. The ability to remove the limitations and explore the core goals facilitates that.
Using this at the wrong time, however, could be problematic. You may have already constrained your thinking too far. If you consider the design process to be a clear identification of the problem (including the type of design thinking analysis that includes ethnographic approaches) before looking for solutions, and then considering a wide variety of input data about solutions including other approaches already tried, you’d want this to come after the problem identification but before any other solutions to explore.
Pragmatically, per my previous post, you want to think about your design processes from a point of view of leverage. Having worked through several efforts to improve design with partners and clients, there are clear leverage points that give you the maximum impact on the quality of the learning outcome (e.g. how ‘serious‘ your solution is) for the minimal impact. There are many more small steps that can be integrated that will improve your outcomes, so it helps to look at the process and consider improvement opportunities. So, are you ready to ask the ‘magic’ question?