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Clark Quinn’s Learnings about Learning

Archives for August 2018

Transparency isn’t enough

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wet foggy windowOf late, there has been a number of articles talking about thinking and mental models (e.g. this one). One of the outcomes is that we have a lot of stories about how the world works.  Some of them are accurate. Others, not. And pondering this when I should’ve been sleeping, I realized that there was a likelihood that our misinterpretations could cause problems. It made me think that maybe transparency isn’t enough. What does that mean?

We build models, period. We create explanations about how the world works. And they may not be right.  If we aren’t given good ones up front, it’s likely. It’s also the case that they seem to come from previous models we’ve seen. (And diagrams. ;)

Now, it’s easy to misattribute an outcome to the wrong model if we don’t have better explanations. And this comes into play when we’re trying to figure out what has happened, or why something happened. This includes decisions made by others that may affect us, or even just lead to outcomes such as product designs, policies, or more.

Where I’m going is this: if we don’t see the thinking that explains how we got there, not just the process followed, we can infer wrongly about  why it happened. And this is important in the ‘show your work’ sense.

I’m a fan of transparency. I like it when politics and other decisions are scrutable; we can see who’s making the decision, what influences they’ve had, what steps they took to get there. That’s not enough, however. Particularly when you disagree or have a problem. Take LinkedIn, for example; when I connect to someone using the app on the qPad, I can then send them a message, but when I do it through the web interface on my computer, it wants to use one of those precious ‘InMail’s.  It’s inconsistent (read: frustrating). Is there a rationale?

So I’m going to suggest that just transparency is necessary, but not sufficient. You can’t just show your work, you need to show your thinking. You need to see the rationale!  Two reasons: you can learn more when you see the associated cogitation, and you can provide better feedback as well.  In short, we want to see  why they believe this is the right solution. Otherwise, we could question their decision because we misattribute the reasoning.

Transparency is great, but if you can’t see the thinking behind it, you can make wrong inferences.  It’s better if you can see the thinking  and the result. Is this transparent enough on both?

Realities: Why AR over VR

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In the past, I’ve alluded to why I like Augmented Reality (AR) over Virtual Reality. And in a conversation this past week, I talked about realities a bit more, and I thought I’d share. Don’t get me wrong, I like VR  alot, but I think AR has the bigger potential impact.  You may or may not agree, but here’s my thinking.

In VR, you create a completely artificial context (maybe mimicking a real one).  And you can explore or act on these worlds. And the immersiveness has demonstrably improved outcomes over a non-immersive experience.  Put to uses for learning, where the affordances are leveraged appropriately, they can support  deep practice. That is, you can minimize transfer to the real world, particularly where 3D is natural. For situations where the costs of failure are high (e.g. lives), this is  the best practice before mentored live performance. And, we can do it for scales that are hard to do in flat screens: navigating molecules or microchips at one end, or large physical plants or astronomical scales at the other. And, of course, they can be completely fantastic, as well.

AR, on the other hand, layers additional information on  top of our existing reality. Whether with special glasses, or just through our mobile devices, we can elaborate on top of our visual and auditory world.  The context exists, so it’s a matter of extrapolating on it, rather than creating it whole. On the other hand, recognizing and aligning with existing context is hard.  Yet, being able to make the invisible visible where you already are, and presumably are for a reason that makes it intrinsically motivating, strikes me as a big win.

First, I think that the learning outcomes from VR are great, and I don’t mean to diminish them. However, I wonder how general they are, versus being specific to inherently spatial, and potentially social, learning.  Instead, I think there’s a longer term value proposition for AR. There’s less physical overhead in having your world annotated versus having to enter another one. While I’m not sure which will end up having greater technical overhead, the ability to add information to a setting to make it a learning one strikes me as a more generalizable capability.  And I could be wrong.

Another aspect is of interest to me, too. So my colleague was talking about mixed reality, and I honestly wondered what that was. His definition sounded like  alternate reality, as in alternate reality games. And that, to me, is also a potentially powerful learning opportunity. You can create a separate, fake but appearing real, set of experiences that are bound by story and consequences of action that can facilitate learning. We did it once with a sales training game that intruded into your world with email and voicemail. Or other situations where you have situations and consequences that intrude into your world and require decisions and actions. They don’t have  real consequences, but they do impact the outcomes. And these could be learning experiences too.

At core, to me, it’s about providing either deep practice or information at the ‘teachable moment’. Both are doable and valuable. Maybe it’s my own curiosity that wants to have information on tap, and that’s increasingly possible. Of course, I love a good experience, too. Maybe what’s really driving me is that if we facilitate meta-learning so people are good self-learners, having an annotated world will spark more ubiquitous learning. Regardless, both realities are good, and are either at the cusp or already doable.  So here’s to real learning!

Question: values?

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So, I’m wrestling with how to characterize useful changes in an organization. I’ve been compiling a list of different tactics (e.g. implement coaching, show-your-work, support curation, etc), and want to map them to the changes you’ll get in the organization. I’ve wanted to tie them to another set of various outcomes: improved participation, innovation, etc. But, while I have the strategies, I’m looking at what breakdowns of outcomes are some minimal useful set. I’ll lay out my  very preliminary set of thoughts around the values we’re trying to develop/influence, and I welcome input, pointers, what have you.

My goal, I should be clear, is to try to take specific changes we want in an organization, and have them linked to specific tactics.  And, of course, a new school approach.  That is, tactics that move organizations into directions that create learning organizations.

I start with the three elements Dan Pink talks about in his book  Drive.  In it, he lists three core motivators of employees: Purpose, Autonomy, and Mastery (this is my order, not his).  Purpose is  why what you’re doing matters.  What does this do for the org, and that what the org is doing also matters. Then, autonomy is when you’re given the freedom to pursue your purposes.  Now, you may not be completely capable of that, so there’s support for mastery, to develop the capabilities to succeed. I think these are all great, but are they sufficient in and of themselves? Are these the right things to want to impact?

I’m also a fan of Amy Edmondson’s quadrant model of psychological safety and accountability. Without either, you’re loafing. With just safety, you’re happy. With just accountability, you’re fearful. But if you’ve accountability  and  safety, you get results.  This draws upon the richer work of Garvin, Gino, and Edmondson on the components of innovation.  That model adds time for reflection, diversity, and openness to new ideas. Is this a better way to think about it?

There’re also personal values (which might be organizational, too).  Barack Obama, in his keynote to ATD 2018, had two very simple ones: be kind, and be useful.  I’ve extended that out one notch, to include three: responsibility (do the right thing, and  do something [useful]), integrity (honesty, do what you promise), and compassion (respect, helping, etc [kind]).  Is that a full set? Or is responsibility derivable from integrity? I’ve a collection of a suite of value proposals (five, with entries ranging from 5 – 8 core values).  Can you derive some of the others from the three I have? E.g. does courage come from integrity and responsibility? Does fairness come from compassion and integrity?  I don’t know.

And so, I’m not sure what the  right core set is.  Trust has to be in there somehow, but is that derivative from integrity?  And do I frame it from the change we want in the org, or the change in the people?  I’m inclined to the former.  And are they unitary, or can the tactics impact more than one? (Preliminary: more than one.)

Obviously, I’m at an early stage in formulating this.  I can beaver away on it on my own, but I’m happy to hear pointers, thoughts, etc.  Yes, I’m trying to diagram it too, but nothing coherent has  yet emerged.  So, once again, this is me ‘thinking out loud’.  Care to do similarly and share?

Complex thinking

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An interesting article I came across brings up an interesting issue: how do we do complex thinking?  Are some people just better at it?  The short answer appears to be ‘no’.  Instead, a couple of tools play a role, and I think it’s an interesting excursion.

The article says that our brains are limited in thinking about complex situations. Yet, experts can do this.  How? The article cites metaphors as the key, grounding our thinking in models that we’ve developed from our experiences. They draw upon George Lakoff’s work on metaphor (a core aspect of my grad school experience) to explain how our understanding advances.  At core, there’s a fundamental requirement that our knowledge builds upon previous knowledge, which ultimately is grounded in our physical activities.

My PhD thesis topic was thinking with analogy, which shares much with this model. The point being that we use familiar frameworks to make inferences in new areas. We map the familiar to the points in the new that match, and then we extrapolate from the familiar to explain things in the new. And using familiar models as explanatory frameworks are essentially the same process as metaphors. Metaphors tend to be more literal, with a shared point, while analogies go further, and share  structure. The latter is, I’ll suggest, more useful.

Note that the frameworks are built of conceptually-related causal relationships, e.g. models. Thus, when we want to communicate models, we can detail them, but using metaphors or analogies are short-cuts.  When we want someone to be able to understand, particularly to be able to use the reference as a tool to support  doing, we can use them to facilitate comprehension. We want to leverage, as much as possible, pre-existing knowledge.  And people aren’t necessarily great at coming up with analogies (research shows), but they’re good at using them.

Another short-cut that the article cites is diagrams.  Here, we’re making visible the relationships, supporting the understanding. Equations can get specific, but conceptual understanding is facilitated by seeing the connections.

The important outcome is that we all have our cognitive limitations to overcome, but we’ve also developed powerful tools to support these limitations. To the extent we understand how these tools support learning, we can use them to help achieve the outcomes we need.  We  can do complex thinking, with the right tools. Are you facilitating success by leveraging these tools?

User-experienced stories

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Yesterday I wrote about examples as stories. And I received a comment that prompted some reflection. The comment suggested that scenarios were stories too. And I agree!  They’re not examples, but they  are stories. With a twist.

So, as I’ve said many times, simulations are just a manipulable model of the world. And a motivated, self-capable learner  can learn from them. But motivated and self-capable isn’t always a safe bet. So, instead, we put the simulation in an initial state, and ask the learner to take it to a goal state, and we choose those such that they can’t get there until they learn the relationships we want them to understand. That’s what I call a scenario.  And we can tune those into a game. (Yes, we turn them into games by tuning; making the setting compelling, adjusting the challenge, etc.)

Now, a scenario needs a number of things. It needs a context, a setting. It needs a goal, a situation to be achieved. And, I’ll suggest, it should also have a reason for that goal to make sense. If you see the alignment that says why games  should be hard fun, you’ll see that making it meaningful is one of the elements. And that,  I say, is a story. Or, at least, the beginning of one.

In short, a story has a setting, a goal, and a path to get there. We remove boring details, highlight the tension, etc.  We flesh out a setting that the learner cares about, provide a sense of urgency, and enable the goal achievement.  But it’s not all done.

The reason this isn’t a complete story is we don’t know the path the protagonist uses to accomplish the goal, or ultimately doesn’t.  We’ve provided tools for that to happen, but we, as designers, don’t control the protagonist. The learner, really,  is the the protagonist!

What I’m talking about is that the story, certainly for the learner, is co-created between the world we’ve developed, and their use of the options or choices we provide. Together, a story is written for them by us  and them.  And, their decisions and the feedback are the story  and the learning!  It’s, voilà, a learning  experience.

Learning is powerful. Creating experiences that facilitate learning are creative hard fun for the designer, and valuable hard fun for the learner. Learning is about stories, some told, some c0-created, but all valuable.

Telling stories

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I’ve talked about examples before, and have long suggested that examples for learning should be in the form of stories. Today I thought a little deeper about  how those stories can be told. And I thought of a particular entailment about video. But let me go through the whole  story.

So, first, an example needs to do several things.  Foremost, examples show how a concept is used in context to guide performance and achieve a solution. To put it another way, examples illustrate how a model is used to make decisions in a specific situation.  It could be situational coaching, a sales process, how to run a brainstorming session, or the basis of a good presentation. Importantly, examples need to show the underlying thinking behind what aspects of the situation made this model relevant, how it was mapped to the situation, how  it stipulated as actions to take, and what the outcomes were. It can also show mistakes, backtracking, and repair.

So how does this map to media?  There are (at least) three good ways to tell such a story. One, obviously, is prose. It’s easy to show the underlying thinking or discussions as “dialog” (internal or otherwise).  You can even illustrate model with a diagram, and convey context with a picture.  And this works.  However, for variety, you could use more visual treatments.

I’ve argued in the past that graphic novel formats also make sense. They strike a balance between conceptual and contextual,  and tell a story nicely. You can use thought bubbles to show the underlying thinking, include diagrams as a separate panel. And you can include necessary context but simplify the unnecessary context.

Finally, there’s video. This can be an animated cartoon (e.g. dynamic graphic novel), a narrated slideshow (think: Ken Burns), or a documentary style.  The question: how do you represent the model? Is it a separate narrated animation, or an overlay on the video (or both)?  I don’t think it matters as long as it’s explicit, and the underlying thinking is shown linking the concept to the context.

The point is that the nuances matter. It’s not just ‘content’; the elements that we provide have specific roles and we need to understand those.

Old and new school

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As I mentioned in yesterday’s post, I was asked for my responses to questions about trends.  What emerged in the resulting article, however, was pretty much contrary to what I said. I wasn’t misquoted, as I was used to set the stage, but what followed wasn’t what I said. What I saw was what I consider somewhat superficial evaluation, and I’d like to point to new school thinking instead.

So the article went from my claim about an ecosystem approach to touting three particular trends. And yet, these trends aren’t really new and aren’t really right!  They were touting mobile, gamification, and the ‘realities. And while there’s nothing wrong with any of them, I had said that I didn’t think that they’re the leading trends.

So, first, mobile is pretty much old news. Mobile first?  Er, it‘s only been 8 years or so (!) since Google declared that! What‘s cool about  mobile, still, is sensors and context-awareness, which they don‘t touch on.  And, in a repeated approach, they veered from the topic to quote a colleague. And my colleague was spot on, but it wasn’t in the least about mobile!  They ended this section talking about gamification and AR/VR, yet somehow implied that this was all about mobile. That would be “no”.

Then they talked about users wanting to be active.  Yay!  But, er, again they segued off-topic, taking personalization before going to microlearning and back to gamification and game-based learning(?).  Wait, what?  Microlearning is an ill-defined concept, and conflating it with game-based learning is just silly.  And games are real, but it‘s still hard to do them (particularly do them right, instead of tarted up drill-and-kill).  Of course, they didn‘t really stay on topic.

Finally, the realities. Here they stayed on topic, but really missed the opportunity. While AR and VR have real value, they talked about 360 photography and videography, which is about consumption, not interaction. And, that‘s not where the future is.

To go back to the initial premise – the three big trends – I think they got it wrong.  AI and data are now far more of a driver than mobile. Yes, AR/VR, but interaction, not just ‘immersion‘.  And probably the third driver is the ecosystem perspective, with systems integration and SaaS.

So, I have to say that the article was underwhelming in insight, confused in story, and wrong on topic. It’s like they just picked a quote and then went anywhere they wanted.   It’s old school thinking, and we’re beyond that. Again, my intention is not to continue to unpack wrong thinking (I’m assuming that’s not what you’re mostly here for, but let me know), but since this quoted me, I felt obliged.  It’s past time for new school thinking in L&D, because focusing on content is, like,  so last century.

Trends in L&D

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I agreed to be interviewed for an article, and was sent questions. And I wrote what I thought were cogent answers.  I even dobbed in a couple of colleagues to also be interviewed. However, the resulting article isn’t what I expected at all. Now, I don’t  intend to make all my posts critiques of what’s being said, but sometimes I guess I just can’t help myself!  So first, here’re my original answers.  In my next post, I’ll document the article’s claims, and my rejoinders about what I think are the driving trends in L&D.

The original questions and responses:

How has our thinking evolved on using technology to assist in learning and development?

Thinking around technology for Learning & Development has shifted from delivering ‘courses‘ to looking at the entire learning and performance ecosystem where technology can not only help us perform in the moment but also develop us over time. This adds performance support, resources and portals, and communication and collaboration tools to support learning alone and together from formal through to informal learning. We‘re recognizing that to move forward, organizations that can learn fastest are the ones most likely to not just survive but thrive. However, this goes beyond the tools and the people to the structures, values, and culture that underpin practices.

Do you think the current systems in use for L&D are adequate? If not, why so?

The legacy of the training mentality is keeping us mired in the past. I think that adding portal and social media capabilities to systems with a ‘course‘ DNA isn‘t the path forward. Instead, we should be looking to integrate capabilities from the best instances in every area. We want flexibility to switch tools if we find better solutions to specific needs, not one overworked legacy system. An LMS (learning management system; misnamed because you don‘t manage learning) may well still be of use to manage courses and signups, but it‘s the wrong foundation for the more agile future we need. Supporting curation and creation, and negotiating shared understandings are the learning that‘re going to be most valuable, and that requires not just different tools, but a different mindset. It‘s time to shift from delivery to facilitation.

What technology-assisted learning tools do you think hold the most potential?

Collaborative tools are the most important tools: the ability to collectively generate and manipulate representations that document how our thinking evolves are important. Such tools that support simultaneous and asynchronous work and communication will be key to the ongoing learnings that will propel organizations forward. New tools like VR can lead to deeper formal learnings, and AR will help both as performance support and annotating the world, but collaborative immersion and annotation fit into that first category. When we‘re developing an understanding together, we‘re creating the richest outcome. There are nuances in doing that right, and that‘s part of L&D‘s role too, but it‘s about tapping into the power of people. Technology that facilitates learning together is what will have the biggest impact.

What do you think is next for learning tech? Is there a huge shift coming?

I think the biggest thing coming for learning tech isn‘t the tech. The ICICLE initiative from IEEE that is defining ‘learning engineering‘ is a big move to start getting smarter about integrating the two components: learning science and technology design and development. Too often learning science is ignored (c.f. ‘rapid elearning‘) or the technical sophistication is missing (e.g. tracking done only at the ‘course‘ level). I think that once we get our minds around the importance of the integration, we‘ll be far better positioned to tap into the advancements we‘re seeing. While I think the hype about Artificial Intelligence is overblown, ultimately I believe that we‘ll have more powerful tools to automate what doesn‘t require the sophisticated capabilities of our brains, freeing us up to do the important work. And that work will be collaborating to generate new understandings. I do think there‘ll be a big shift, but it‘ll be coming along slowly. I hope this shift happens, but I think it‘s evolutionary, as change is hard.

Ok, so that’s what I said about the trends in L&D. What you will see is that what they presented is somewhat contrary to what I said here!

Mobile Malarkey

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I was called out on a tweet pointing to an article on mobile. And, I have to say, I thought it was pretty underwhelming. It was the ‘old school’ view of mlearning, and I think that the post largely missed the point. So I thought it’d be valuable to walk through the claims. What I’m trying to accomplish is share how my thinking works, and perhaps contaminate you with a wee bit of it too ;). We need to get better at cutting through the hype (part of the debunking skills), and that includes microlearning and mobile malarkey as well.

The post makes four claims for why mobile is on the rise:

  • the advancements in mobile technology
  • the desire for small content
  • more engaging content
  • consumption ‘on the go’

So let’s go through these.  However, first I’m going to challenge the assumption!

Mobile is not ‘on the rise’.  That’s so 2012.  Mobile is well past the ‘new’ stage.  Heck, Google was arguing ‘mobile first’ back in 2010!  Even here in the US, it’s mainstream, and it’s been the ‘goto’ mode in other countries for much longer.

Now, the advancements in mobile technology  are continuing, and impressive.  Things like sensors for contextual information, networking for social connections, new interaction capabilities like pressure-sensitivity, and higher resolution screens and faster processors mean new capabilities.  What the article is talking about, is cutting edge content. Yes, video can be useful ‘on demand’, and interactivity can be powerful.  In context.  But they’re not picking up on that. This is still the ‘get training wherever you are’ mentality.  Mobile is really not about courses!  But maybe they’ll get better..

Next is the chunks. Ok, so I’ve already weighed in on ‘microlearning’.  Yes, small is better. It  does matter whether you’re talking performance support or spaced learning, but small is good. However, this article touts that we prefer smaller chunks (er, yes, and that’s not a good indicator).  And that we benefit from smaller. Yes, but this is still about ‘content consumption’.  Mobile can, and should be more than that.

On to engagement. Here the claim is that these small bits are more engaging, but that we can do interactive things as well. And this is good: mini-scenarios (better written multiple choice), even branching scenarios can lead to better. However, here they’re talking quizzes and infographics. Again, mostly content, and also focused on knowledge, not skills. This isn’t where the emphasis should be. Spaced learning yes, but reactivation – reconceptualization, recontextualization, and reapplication – not content dump and knowledge test.

Finally, it’s about remote workers. Yes, again, contextualization to give the right thing, to the right person, at the right time and place. But no, they’re talking about accessing training where/when/ever. Yes, that’s nice.  But not intrinsically exciting, and definitely not really capitalizing on mobile’s promise.

Look, the real mobile opportunity is about performance support and contextualized learning. Spaced learning is good (though not unique to mobile).  But to argue mobile’s on the rise, and it’s about content, is to misconstrue the state of the industry  and the opportunity. This is obviously a sales pitch for their mobile content delivery, but get clear about what you want from mobile. It’s a platform, so once you start people will expect more. It’s best if you need to think strategically about all that you can do and ensure you’ve seen the full picture before you settle on any one solution.