Learnlets
Clark Quinn's Learnings about Learning
(The Official Quinnovation blog)

2 February 2016

Organizational Knowledge Mastery?

Clark @ 8:05 am

I was pointed to a report from MIT Sloan Management talking about how big data was critical to shorten ‘time to insight’. And I think that’s a ‘good thing’ in the sense that knowing what’s happening faster is clearly going to be part of agility.  But I  must be missing something, because unless I’m mistaken, big data can’t give you the type of insights you really need.

Ok, I get it. By the ‘test and learn’ process of doing experiments and reading reactions, you can gather data quickly. And I’m all for this.  But this is largely internal, and I think the insights needed are external. And yes, the experiments can be outside the firewall, trying new things with customers and visitors and reading reactions, but that’s still in the realms of the understood or expected. How can such a process detect the disruptive influences?

Years ago, with friend and colleague Eileen Clegg, we wrote a chapter based upon her biologist husband’s work in extremophiles, looking for insight into how to survive in tough times.  We made analogies from a number of the biological phenomena, and one was the need to be more integrated with the environment, sensing changes and bringing them in. Which of course, triggered an association.

If we adapt Harold Jarche’s Personal Knowledge Mastery (or PKM), which is about Seek-Sense-Share as a mechanism to grow our own abilities, to organizations, we can see a different model.  Perhaps an OKM?  Here’s organizations seek knowledge sources, sense via experiments and reflection, and share internally (and externally, as appropriate ;).

This is partly at the core of the Coherent Organization model as well, where communities are seeking and sharing outside as ways to continue to evolve and feed the teams whose work is driving the organization forward. It’s about flows of information, which can’t happen if you’re in a Miranda Organization. And so while big data is a powerful tool, I think there’s something more required.

I think the practices and the culture of the organization are more important.  If you don’t have those right, big data won’t give big insights, and if you do, big data is just one of your tools.  Even if you’re doing experiments, it might be small data, carefully instrumented experiments targeted at getting specific outcomes, rather than big data, that will give you what you need.  But more importantly, sensing what’s going on outside, having diverse interests and a culture of curiosity is going to be the driver for the unexpected opportunities.

So yes, use the tools to hand and leverage the power of technology, but focus on motivations and culture so that the tools will be used in the important ways.  At least that was my reaction.  What’s yours?

14 January 2016

10 years!?!?

Clark @ 8:08 am

A comment on my earliest blog post (thanks, Henrik), made me realize that this post will mark 10 years of blogging. Yes, my first post came out on January 14th, 2006.  This will be my 1,200th post (I forced one in yesterday to be the 1199th so I could say that ;), yow!  That’s 120 a year, or just under every 3rd day.  And, I am happy to add, 2,542 comments (just more than 2 per post), so thanks to you for weighing in.

It’s funny, when I started I can’t really say it was more than an experiment.  I had no idea where it would lead, or how.  It’s  had some challenges, to continue to find topics, but it’s been helpful.  It’s forced me to deliberately consider things I otherwise might not have, just to try to keep up the momentum.

I confess I originally had a goal of 5 a week (one per business day), but even then I was happy if I got 2-3. I’m gobsmacked at my colleague Harold who seems to put out a post every day.  I can’t quite do that. My goal has moderated to be 2 a week (very occasionally I live with 1 per week, but other weeks like when I’m at conferences I might have 3 if there are lots of keynotes to mind map).  Typically it’s Tuesday and Wednesday, for no good reason.

I also try to have something new to say every time. It’s hard, but forcing myself to find something to talk about has led to me thinking about lots of things and therefore ready to bring them to bear on behalf of clients.  I think out loud relatively freely (particularly with the popularity of Work and Learn Out Loud and Show Your Work).  And it’s a way to share my diagrams, another way to ‘think out loud’.  And I admit that I don’t share some things that are either proprietary (until I can anonymize them) or something I’m planning on doing something with.

And I’ve also resisted commercializing this.  Obviously I’ve avoided the offers to exchange links or blog posts that include links for SEO stuff, but I’ve even, rightly or wrongly, not allowed ads.  While it is the official Quinnovation blog, it’s been my belief that sharing my thinking is the best way to help me get interest in what I have to offer (extensive experience mapping a wide variety of concepts onto specific client contexts to yield innovative yet practical and successful solutions).  I haven’t (yet) followed a formula to drive business traffic, and only occasionally mention my upcoming events (though hopefully that’s a public service :).  There’re other places to track that.

I’m also pretty lax about looking at the metrics. I do weekly pop by Google Analytics to see what sort of traffic I get (pretty steady), but I haven’t tried to see what might improve it.  This is, largely, for me.  And for you if your interests run this way. So welcome, and here’s to another 10 years!  Who knows what there will be to talk about then…or even next week!

12 January 2016

Working wiser?

Clark @ 8:03 am

Noodling:  I’ve been thinking about Working Smarter, a topic I took up over four years ago.  And while I still think there’s too little talk about it, I wondered also about pushing it further.  I also talked in the past about an interest in wisdom, and what that would mean for learning.  So what happens when they come together?

Working smarter, of course, means recognizing how we really think, work, and learn, and aligning our processes and tools accordingly. That includes recognizing that we do use external representations, and ensuring that the ones we want in the world are there, and we also support people being able to create their own. It means tapping into the power of people, and creating ways for them to get together and support one another through both communication and collaboration.  And, of course, it means using Serious learning design.

But what, then, does working ‘wiser’ mean?  I like Sternberg’s model of wisdom, as it’s actionable (other models are not quite specific enough).  It talks about taking into account several levels of caring about others, several time scales, several levels of action, and all influenced by an awareness of values.  So how do we work that into practices and tools?

Well, pragmatically, we can provide rubrics for evaluation of ideas that include considerations of others inside and outside your circles of your acquaintances, and in short- and long-term timeframes, and the impacts on existing states of affairs, ultimately focusing on the common good. So we can have job aids that provide guidance, or bake it into our templates.  These, too, can be shown in collaboration tools, so the outputs will reflect these values.  But there’s another approach.

But, at core, it’s really about what you value, and that becomes about culture.  What values does the organization care about?  Do employees know about the organization’s ultimate goal and role?  Is it about short-term shareholder return, or some contribution to society?  I’m reminded about the old statements about whether you’re about selling candles or providing light.  And do employees know how what they do fits in?

It’s pretty clear that the values implicit in steps to make workplaces more effective are really about making workplaces more humane, that is: respecting our inherent nature.  And movements like this, that provide real meaning, ongoing support, freedom of approach, and time for reflection, are to me about working not just smarter but also wiser.

We can work smarter with tools and practices, but I think we can work better, wiser, with an enlightened approach to who we are working with and how we work to deliver real value to not only customers but to society.  And, moreover, I think that doing so would yield better organizational outcomes.

Ok, so have I gone off the edge of the hazy cosmic jive?  I am a native Californian, after all, but I’m thinking that this makes real business sense.  I think we can do this, and that the outputs will be better too, in all respects.  No one says it’d be easy, but my suspicion is it’d be worthwhile.

5 January 2016

Meta-Learning Manifestations

Clark @ 8:01 am

I recently mentioned that one of my reflections on the past year was that learning to learn, aka meta-learning, is emerging.  And this has come about in several ways recently, and I think it’s a relatively ‘meta’ thing to do ;) to look at the principles across these areas.

So, yesterday I was talking with a colleague about libraries. And one of the things that I noted was that in talking about the future of libraries, I hadn’t discussed a particular role they could and should play.  The reflection was that even in the future role, librarians are more than just the conduits to the information (or people or equipment), but also demonstrating how they served that role. That is, don’t just show me the results of the search, show me how you thought about the search, and why you chose the search tool you used, and how you created your query, and…

And he assured me that indeed librarians were being taught this. Moreover, at San Francisco Public Libraries they actually had dual monitors where the staff member could look, but the patron could also view the activity, and the staff member could work ‘out loud‘.

And this is important.  Because until our schools start doing a better job of this, we’re not going to be able to assume that our employees and citizens are actually good at learning.  You can only teach meta-learning on top of real goals, and we (should) have those in schools, so it’s the ideal place and arguably the best contribution schools can provide in this rapidly changing environment.

And it’s not like the investments in learning technology are addressing this either.  As I mentioned when I talked about AI for learning, we’re not really seeing the extra layer that will address that (though it’s doable).  As it is, we’re creating adaptive systems that replicate the existing curricula, which would be ok if our curricula were defensible (hint: it isn’t). Advanced pedagogy can be great, but it is wasted on the existing curricula.

So, there’re are opportunities for learning to learn (which have real benefits) to be enabled across organizational work, library work, schools, and systems.  And we’re really not seeing anywhere near the uptake that would benefit our efforts.

However, we are seeing more discussion. And I’m imploring you to start thinking about it, talking about it, and beginning to do it! It’s doable, and arguably the best investment we could and should be making.  Are you ready?

31 December 2015

2015 Reflections

Clark @ 8:02 am

It’s the end of the year, and given that I’m an advocate for the benefits of reflection, I suppose I better practice what I preach. So what am I thinking I learned as a consequence of this past year?  Several things come to mind (and I reserve the right for more things to percolate out, but those will be my 2016 posts, right? :):

  1. The Revolution is real: the evidence mounts that there is a need for change in L&D, and when those steps are taken, good things happen. The latest Towards Maturity report shows that the steps taken by their top-performing organizations are very much about aligning with business, focusing on performance, and more.  Similarly, Chief Learning Officer‘s Learning Elite Survey similarly point out to making links across the organization and measuring outcomes.  The data supports the principled observation.
  2. The barriers are real: there is continuing resistance to the most obvious changes. 70:20:10, for instance, continues to get challenged on nonsensical issues like the exactness of the numbers!?!?  The fact that a Learning Management System is not a strategy still doesn’t seem to have penetrated.  And so we’re similarly seeing that other business units are taking on the needs for performance support, social media, and ongoing learning. Which is bad news for L&D, I reckon.
  3. Learning design is rocket science: (or should be). The perpetration of so much bad elearning continues to be demonstrated at exhibition halls around the globe.  It’s demonstrably true that tarted up information presentation and knowledge test isn’t going to lead to meaningful behavior change, but we still are thrusting people into positions without background and giving them tools that are oriented at content presentation.  Somehow we need to do better. Still pushing the Serious eLearning Manifesto.
  4. Mobile is well on it’s way: we’re seeing mobile becoming mainstream, and this is a good thing. While we still hear the drum beating to put courses on a phone, we’re also seeing that call being ignored. We’re instead seeing real needs being met, and new opportunities being explored.  There’s still a ways to go, but here’s to a continuing awareness of good mobile design.
  5. Gamification is still being confounded: people aren’t really making clear conceptual differences around games. We’re still seeing linear scenarios confounded with branching, we’re seeing gamification confounded with serious games, and more.  Some of these are because the concepts are complex, and some because of vested interests.
  6. Games  seem to be reemerging: while the interest in games became mainstream circa 2010 or so, there hasn’t been a real sea change in their use.  However, it’s quietly feeling like folks are beginning to get their minds around Immersive Learning Simulations, aka Serious Games.   There’s still ways to go in really understanding the critical design elements, but the tools are getting better and making them more accessible in at least some formats.
  7. Design is becoming a ‘thing’: all the hype around Design Thinking is leading to a greater concern about design, and this is a good thing. Unfortunately there will probably be some hype and clarity to be discerned, but at least the overall awareness raising is a good step.
  8. Learning to learn seems to have emerged: years ago the late great Jay Cross and I and some colleagues put together the Meta-Learning Lab, and it was way too early (like so much I touch :p). However, his passing has raised the term again, and there’s much more resonance. I don’t think it’s necessarily a thing yet, but it’s far greater resonance than we had at the time.
  9. Systems are coming: I’ve been arguing for the underpinnings, e.g. content systems.  And I’m (finally) beginning to see more interest in that, and other components are advancing as well: data (e.g. the great work Ellen Wagner and team have been doing on Predictive Analytics), algorithms (all the new adaptive learning systems), etc. I’m keen to think what tags are necessary to support the ability to leverage open educational resources as part of such systems.
  10. Greater inputs into learning: we’ve seen learning folks get interested in behavior change, habits, and more.  I’m thinking we’re going to go further. Areas I’m interested in include myth and ritual, powerful shapers of culture and behavior. And we’re drawing on greater inputs into the processes as well (see 7, above).  I hope this continues, as part of learning to learn is to look to related areas and models.

Obviously, these are things I care about.  I’m fortunate to be able to work in a field that I enjoy and believe has real potential to contribute.  And just fair warning, I’m working on a few areas in several ways.  You’ll see more about learning design and the future of work sometime in the near future. And rather than generally agitate, I’m putting together two specific programs – one on (e)learning quality and one on L&D strategy – that are intended to be comprehensive approaches.  Stay tuned.

That’s my short list, I’m sure more will emerge.  In the meantime, I hope you had a great 2015, and that your 2016 is your best year yet.

29 December 2015

Starting a revolution?

Clark @ 8:03 am

In thinking a bit about the Future of Work, one of the issues is where to start.  If we take the implications of the Coherent Organization to heart, we realize that the components include the work teams, the communities of practice (increasingly I think of it as a community of improvement), and the broader network.  But where to begin?

A couple of principles fall into place for me.  The first is the notion of  ‘trojan mice’, e.g. small steps rather than a epic change. That, coupled with the notion of scaling up from the small, leads me to believe that the best place to start is to start small. This follows on the advice about change in general that changes should be strategic and leveraged.

So, a natural place to start small is the team itself.  The goal would be to draw upon a diverse team meeting a real need, but facilitating their tool use. I remember an engagement with a Scandinavian oil company that I was brought in on, where they started out establishing teams for new projects that crossed geographies (and, implicitly, cultures), scaffolded them using collaboration and communication tools, and then released them back to other projects. The goal was to skill up teams and have the team members become viral influences.

Another approach, as there are already likely communities in existence, would be to migrate and facilitate communities online. I recall that the Defense Acquisition University took this approach.  However, I might like to get some project teams going with tools and then migrate out to the communities, where those team members that had participated were familiar with the tools and could be drawn upon by the community.

In fact, after the initial team work, I might facilitate a team not only working together, but working out  loud back to their respective communities.  And while it makes practical sense to be sequential, at some point it might make sense to go parallel, and be having the working out loud from the teams being worked on at the same time as the community development. But for resource reasons, I might make it sequential. Ultimately, you want to be facilitating the communities participating in and outside the organizations, and looking to other communities both inside and outside for inspiration.

The point is to be finding a small way to begin, and maybe take several tries until you work out how to do it well, then start scaling up and out.  You want to build need, awareness, and ability steadily.  It can effect a change in culture too, if the principles that make this work in teams and communities begins to be made aware as well.

And this is not independent of work on going to more performance consulting and performance support in the organization, but instead is a complement.  In previous exercises, different organizations have prioritized different elements, where you begin will be dependent on your context.

So, in the social space, this is my instinct and experience, but welcome hearing alternate viewpoints.

#itashare

27 October 2015

Showing the World

Clark @ 8:03 am

One of the positive results of investigations into making work more effective has been the notion of transparency, which manifests as either working and learning ‘out loud‘, or in calls to Show Your Work.  In these cases, it’s so people can know what you’re doing, and either provide useful feedback or learn from you.  However, a recent chat in the L&D Revolution group on LinkedIn on Augmented Reality (AR) surfaced another idea.

We were talking about how AR could be used to show how to do things, providing information for instance on how to repair a machine. This has already been seen in examples by BMW, for instance. But I started thinking about how it could be used to support education, and took it a bit further.

So many years ago, Jim Spohrer proposed WorldBoard, a way to annotate the world. It was like the WWW, but it was location specific, so you could have specific information about a place at the place.  And it was a good idea that got some initial traction but obviously didn’t continue.

The point, however, would be to ‘expose’ the world. In particular, given my emphasis on the value of models, I’d love to have models exposed. Imagine what we could display:

  • the physiology of an animal we’re looking at to flows of energy in an ecosystem
  • the architectural or engineering features of a building or structure
  • the flows of materials through a manufacturing system
  • the operation of complex devices

The list goes on. I’ve argued before that we should expose our learning designs as a way to hand over learning control to learners, developing their meta-learning skills. I think if we could expose how things work and the thinking behind them, we’d be boosting STEM in a big way.

We could go further, annotating exhibits and performances as well.  And it could be auditory as well, so you might not need to have glasses, or you could just hold up the camera and see the annotations on the screen. You could of course turn them on or off, and choose which filters you want.

The systems exist: Layar commercially, ARIS in the open source space (with different capabilities).  The hard part is the common frameworks, agreeing what and how, etc.   However, the possibilities to really raise understanding is very much an opportunity.  Making the workings of the world visible seems to me to be a very intriguing possibility to leverage the power we now hold in our hand. Ok, so this is ‘out there’, but I hope we might see this flourishing quickly.  What am I missing?

21 October 2015

Learning by experimenting

Clark @ 8:14 am

In some recent work, an organization is looking to find a way to learn fast enough to cope with the increasing changes we’re seeing.  Or, better yet, learn ahead of the curve. And this led to some thoughts.

As a starting point, it helps to realize that adapting to change is a form of learning. So, what are the individual equivalents we might use as an analogy?  Well, in known areas we take a course. On the other hand, for self-learning, e.g. when there isn’t a source for the answer, we need to try things.  That is, we need a cycle of: do – review -refine.

In the model of a learning organization, experimentation is clearly listed as a component of concrete learning processes and practices.  And my thought was that it is therefore  clear that any business unit or community of practice that wants to be leading the way needs to be trying things out.

I’ve argued before that learning units need to be using new technologies to get their minds around the ‘affordances’ possible to support organizational performance and development.  Yet we see that far too few organizations are using  social networks for learning (< 30%), for example.

If you’re systematically tracking what’s going on, determining small experiments to trial out the implications, documenting and sharing the results, you’re going to be learning out ahead of the game. This should be the case for all business units, and I think this is yet another area that L&D could and should be facilitating.  And by facilitating, I mean: modeling (by doing it internally), evangelizing, supporting in process, publicizing, rewarding, and scaling.

I think the way to keep up with the rate of change is to be driving it.  Or, as Alan Kay put it: “the best way to predict the future is to invent it”.  Yes, this requires some resources, but it’s ultimately key to organizational success, and L&D can and should be the driver of the process within the organization.

7 October 2015

AI and Learning

Clark @ 8:10 am

At the recent DevLearn, Donald Clark talked about AI in learning, and while I largely agreed with what he said, I had some thoughts and some quibbles. I discussed them with him, but I thought I’d record them here, not least as a basis for a further discussion.

Donald’s an interesting guy, very sharp and a voracious learner, and his posts are both insightful and inciteful (he doesn’t mince words ;). Having built and sold an elearning company, he’s now free to pursue what he believes and it’s currently in the power of technology to teach us.

As background, I was an AI groupie out of college, and have stayed current with most of what’s happened.  And you should know a bit of the history of the rise of Intelligent Tutoring Systems, the problems with developing expert models, and current approaches like Knewton and Smart Sparrow. I haven’t been free to follow the latest developments as much as I’d like, but Donald gave a great overview.

He pointed to systems being on the verge of auto parsing content and developing learning around it.  He showed an example, and it created questions from dropping in a page about Las Vegas.  He also showed how systems can adapt individually to the learner, and discussed how this would be able to provide individual tutoring without many limitations of teachers (cognitive bias, fatigue), and can not only personalize but self-improve and scale!

One of my short-term problems was that the questions auto-generated were about knowledge, not skills. While I do agree that knowledge is needed (ala VanMerriënboer’s 4CID) as well as applying it, I think focusing on the latter first is the way to go.

This goes along with what Donald has rightly criticized as problems with multiple-choice questions. He points out how they’re largely used as knowledge test, and I agree that’s wrong, but while there are better practice situations (read: simulations/scenarios/serious games), you can write multiple choice as mini-scenarios and get good practice.  However, it’s as yet an interesting research problem, to me, to try to get good scenario questions out of auto-parsing content.

I naturally argued for a hybrid system, where we divvy up roles between computer and human based upon what we each do well, and he said that is what he is seeing in the companies he tracks (and funds, at least in some cases).  A great principle.

The last bit that interested me was whether and how such systems could develop not only learning skills, but meta-learning or learning to learn skills. Real teachers can develop this and modify it (while admittedly rare), and yet it’s likely to be the best investment. In my activity-based learning, I suggested that gradually learners should take over choosing their activities, to develop their ability to become self-learners.  I’ve also suggested how it could be layered on top of regular learning experiences. I think this will be an interesting area for developing learning experiences that are scalable but truly develop learners for the coming times.

There’s more: pedagogical rules, content models, learner models, etc, but we’re finally getting close to be able to build these sorts of systems, and we should be  aware of what the possibilities are, understanding what’s required, and on the lookout for both the good and bad on tap.  So, what say you?

30 September 2015

Connie Yowell #DevLearn Keynote Mindmap

Clark @ 4:58 pm

Connie Yowell gave a passionate and informing presentation on the driving forces behind digital badges.

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