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Clark Quinn’s Learnings about Learning

Archives for October 2019

Templates for good

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In terms of the various ways in which we can support the gaps in our cognition, one of the terms is ‘templates’. And it’s worth discussing what a template is, and considering them at a variety of levels. I want to suggest we should have templates for good.

What is a template? Merriam-Webster defines it as “a gauge, pattern, or mold used as a guide to the form of a piece being made”. In terms of software and business, templates are forms with some of the elements already completed. Instead of starting from scratch, pieces are already done, and there are slots for various information.

Why use templates?  With them, it’s easier to do design. They make it easy to accomplish particular goals. They can make it easy to build particular types of outputs, and make them more systematic and consistent. For better or worse.

How does that change for learning? Here, a template tends to be a framework for particular interactions. For example, there are the tarted-up quiz show formats. With more depth, we can provide guides for learning, suggesting quality elements. We might have a place in our examples for the underlying thinking. Or we could  structure practice as decision making.

But we can have templates at higher levels, too. For instance, we can ask that the objective include elements of measurable evaluation, and carry that forward through the final practice design. We can go beyond that, and have structures to guide doing good curricula design.

If I have to choose, of course, I’ll go for substance over style. I’d rather your templates suggest good design than flashy but insubstantial experience. It’s time to be doing evidence-based learning instead of gaudy but rote experiences. If we’re going to have templates, let’s have templates for good.

Helen Papagiannis #DevLearn Keynote Mindmap

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Helen Papagiannis kicked off the second day of the DevLearn conference. She explored the possibilities of AR with exceptional examples. She went through a variety of concepts, helping us comprehend new opportunities. Exposing the invisible and annotating the world were familiar, but collaborative editing of spatial representations resurrected one of the most interesting (and untapped) potentials of virtual worlds.

Sophia the Robot #DevLearn Keynote Mindmap

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DevLearn opened with a keynote from Sophia the Robot. With an initially scripted presentation, and some scripted questions from host David Kelly, Sophia addresses the differences between AI and robots, with a bit of wit. The tech used to make the illusion was explored, but the technology was put to the test with some unscripted questions, and the responses were pretty good. An interesting start!

Play to Learn

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Tic Tac Toe gameThinking more about Friston’s Free Energy Principle and the implications for learning design prompted me to think about play. What drives us to learn, and then how  do we learn?  And play is the first answer, but does it extend? Can we play to learn beyond the natural?

The premise behind the Free Energy principle is that organisms (at every level) learn to minimize the distance between our predictions and what actually occurs. And that’s useful, because we use our predictions to make decisions. And it’s useful if our decisions get better and better over time. To do that, we build models of the world.

Now, it’d be possible for us to just sit in a warm dark room, so our predictions are right, but we have drives and needs. Food, shelter, sex, are drives that can at least occasionally require effort. The postulate is that we’ll be driven to learn when the consequences of not learning are higher than the effort of learning.

At this level, animals play to learn things like how to hunt and interact. Parents can help as well.  At a higher level than survival, however, can play still work? Can we learn things like finance, mathematics, and other human-made conceptions this way? It’d be nice to make a safe place to ‘play’, to experiment.

Raph Koster, in his  A Theory Of Fun,  tells us that computer games are fun just because they require learning. You need to explore, and learn new tricks to beat the next level.  And computer games can be about surviving in made-up worlds.

The point I’m getting to is that the best learning should be play; low stakes exploration, tapping into the elements of engagement to make the experience compelling. You want a story about what your goal is, and a setting that makes that goal reasonable, and more.

To put it another way, learning  should be play. Not trivial, but ‘hard fun’.  If we’re not making it safe, and providing guided discovery to internalize the relationships they need, to build the models that will make better decisions, we’re not making learning as naturally aligned as it can be. So please, let your people play to learn. Design learning experiences, not just ‘instruction’.

 

Writing ongoing

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I’ve been doing this blog now for 13.5 years (started in January 2006 with my first post), and have generated over 1600 posts in that time. My intentions about productivity started, perhaps, more ambitious, but they settled down a number of years ago. And, I’m finding, they’ve settled again of late. So it’s time to reflect on my status of writing ongoing!

So, while I started with hoping for one every biz day, I was always happy to get 2 or 3 per week. And I’d pretty much settled on meeting a self-imposed goal of 2 per week. Which I’ve kept that up for years; sometimes, like at confs, I’d do 3 per week because of my mind maps, and  occasionally  I’d only get 1. Yet more weeks than not of late (say, the past few months), I’ve struggled to come up with even 1. What’s going on (he asks himself)?

Ok, during that time, I’ve written four more books (the first one came out before the blog started). And I’ve worked, and written articles, and traveled and spoken, and more. And that’s still status quo. So why have I slipped of late? What’s changed?

Well, for one, I’ve gone from occasional articles, to a monthly column for the Litmos blog for the past 4.5 years, and now to a second monthly column for Learning Solutions for the past 2.5 years. Yet, I’ve been keeping up until the past months.

One thing  has  changed. M’lady started working part time, and now is full time. Which is fine, because I am quite capable of some household tasks. The planning meals and cooking haven’t really changed in their demands, but I find I  am spending more time on shopping in particular.  Though that shouldn’t be such a barrier. And it started a year ago.

I’m likely to have another big writing task upcoming (stay tuned ;), and that tends to generate insights. But overall, I’m not feeling positive I’ll be able to continue achieving two posts a week. At least ’til I understand better what’s going on.  I’ll shoot for 2, of course, but I feel like I should be open and say that I may only get to 1 a week. That’s where my writing ongoing seems to be headed. We’ll see.

Endorsements, rigor, & scrutability

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I was recently asked to endorse two totally separate things. And it made me reflect on just what my principles for such an action might be. So here’s an gentrified version of my first thoughts on my principles for endorsements:

First, my reputation is based on rigor in thought, and integrity in action. Thus, anyone I‘d endorse both has to be scrutable both in quality of design and in effectiveness in execution.

So, to establish those, I need to do several things.

For one, I have to investigate the product. Not just the top-level concept, but the lower-level details. And this means not only exploring, but devising and performing certain tests.

And that also means investigating the talent behind the design. Who‘s responsible for things like the science behind it and the ultimate design.

In addition, I expect to see rigor in implementation. What‘s the development process? What platform and what approach to development is being used? How is quality maintained? Maintainability? Reliability? I‘d want to talk to the appropriate person.

And I‘d want to know about customer service. What‘s the customer experience? What‘s the commitment?

There‘ve been a couple of orgs that I worked with over a number of years, and I got to know these things about them (and I largely played the learning science role ;), so I could recommend them (tho‘ they didn‘t ask for public endorsements) and help sell them in engagements. And I was honest about the limitations as well.

I have a reputation to maintain, and that means I won‘t endorse ‘average‘. I will endorse, but it‘s got to be scrutable at all levels and exceptional in some way so that I feel I‘m showing something unique and exceptional but will also play out favorably over time. If I recommend it, I need people to be glad if they took my advice. And then there’s got to be some recompense for my contribution to success.

One thing I hadn‘t thought of on the call was a possibility of limited or levels of endorsement. E.g. “This product offers a seemingly unique solution that is valuable in concept”, but not saying “I can happily recommend this approach”. Though the value of that is questionable, I reckon.

Am I overreaching in what I expect for endorsements, or does this make sense?