Learnlets

Secondary

Clark Quinn’s Learnings about Learning

Learnnovators Deeper eLearning Series

by Leave a Comment

For the past 6 months, Learnnovators has been hosting a series of posts I’ve done on Deeper eLearning Design that goes through the elements beyond traditional ID.  That is, reflecting on what’s known about how we learn and what that implies for the elements of learning. Too often, other than saying we need an objective and practice (and getting those wrong), we talk about ‘content’.  Basically, we don’t talk enough about the subtleties.

So here I’ve been getting into the nuances of each element, closing with an overview of changes that are implied for processes:

1. Deeper eLearning Design: Part 1 – The Starting Point: Good Objectives
2. Deeper eLearning Design: Part 2 – Practice Makes Perfect
3. Deeper eLearning Design: Part 3 – Concepts
4. Deeper eLearning Design: Part 4 – Examples
5. Deeper eLearning Design: Part 5 – Emotion
6. Deeper eLearning Design: Part 6 – Putting it All Together

I’ve put into these posts  my best thinking around learning design. The final one’s been posted, so now I can  collect the whole set  here for your convenience.

And don’t forget the Serious eLearning Manifesto!  I hope you find this useful, and welcome your feedback.

AI and Learning

by Leave a Comment

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?

Mobile Time

by 1 Comment

At the recent DevLearn conference, David Kelly spoke about his experiences with the Apple Watch.  Because I don’t have one yet, I was interested in his reflections.  There were a number of things, but what came through for me (and other reviews I’ve read) is that the time scale is a factor.

Now, first, I don’t have one because as with technology in general, I don’t typically acquire anything in particular until I know how it’s going to make me more effective.  I may have told this story before, but for instance I didn’t wasn’t interested in acquiring an iPad when they were first announced (“I’m not a content consumer“). By the time they were available, however, I’d heard enough about how it would make me more productive (as a content  creator), that I got one the first day it was available.

So too with the watch. I don’t get a lot of notifications, so that isn’t a real benefit.   The ability to be navigated subtly around towns sounds nice, and to check on certain things.  Overall, however, I haven’t really found the tipping-point use-case.  However, one thing he said triggered a thought.

He was talking about how it had reduced the amount of times he accessed his phone, and I’d heard that from others, but here it struck a different cord. It made me realize it’s about time frames. I’m trying to make useful conceptual distinctions between devices to try to help designers figure out the best match of capability to need. So I came up with what seemed an interesting way to look at it.

Various usage times by category: wearable, pocketable, bag able.This is similar to the way I’d seen Palm talk about the difference between laptops and mobile, I was thinking about the time you spent in using your devices.  The watch (a wearable)  is accessed quickly for small bits of information.  A pocketable (e.g. a phone) is used for a number of seconds up to a few minutes.  And a tablet tends to get accessed for longer uses (a laptop doesn’t count).  Folks may well have all 3, but they use them for different things.

Sure, there are variations, (you  can watch a movie on a phone, for instance; phone calls could be considerably longer), but by and large I suspect that the time of access you need will be a determining factor (it’s also tied to both battery life and screen size). Another way to look at it would be the amount of information you need to make a decision about what to do, e.g.  for cognitive work.

Not sure this is useful, but it was a reflection and I  do like to share those. I welcome your feedback!

Natalie Panek #DevLearn Keynote Mindmap

by Leave a Comment

To close off the DevLearn conference, Natalie Panek (@nmpanek) told of her learning journey to be a space engineer with compelling stories of challenging experiences.  With an authentic and engaging style, she helped inspire us to keep learning.

Adam Savage #DevLearn Keynote Mindmap

by Leave a Comment

Adam Savage gave a thoughtful, entertaining, and ultimately moving talk about how Art and Science are complementary components of what makes us human. He continued telling stories that kept us laughing while learning, and ended on a fabulous note about being willing to be vulnerable as a person and a parent.  Truly a great keynote.

David Pogue #DevLearn Keynote Mindmap

by Leave a Comment

David Pogue addressed the DevLearn audience on Learning Disruption. In a very funny and insightful presentation, he ranged from the Internet of Things, thru disintermediation and wearables, pointing out disruptive trends. He concluded by talking about the new generation and the need to keep trying new things.  

Tech travails

by 1 Comment

Today I attended David Pogue’s #DevLearn Keynote.  And, as a DevLearn ‘official blogger’, I was expected to mindmap it (as I regularly do). So, I turn on my iPad and have had a steady series of problems. The perils of living in a high tech world.

First, when I opened my diagramming software, OmniGraffle, it doesn’t work. I find out they’ve stopped supporting this edition! So, $50 later (yes, it’s almost unconscionably dear) and sweating out the download (“will it finish in time”), I start prepping the mindmap. 

Except the way it does things are different. How do I add break points to an arrow?!?  Well, I can’t find a setting, but I finally explore other interface icons and find a way. The defaults are different, but manage to create a fairly typical mindmap.  Phew.

So, I export to Photos and open WordPress. After typing in my usual insipid prose, I go to add the image. And it starts, and fails.  I try again, and it’s reliably failing. I reexport, and try again. Nope. I get the image over to my iPhone to try it there, to no avail.

I’ve posted the image to the conference app, but it’s not going to appear here until I get back to my room and my laptop.  Grr. 

Oh well, that’s life in this modern world, eh?

  

    
  

Looking forward on content

by 5 Comments

At DevLearn next week, I’ll be talking about content systems in session 109.  The point is that instead of monolithic content, we want to start getting more granular for more flexible delivery. And while there I’ll be talking about some of the options on how, here I want to make the case about why, in a simplified way.

As an experiment (gotta keep pushing the envelope in a myriad of ways), I’ve created a video, and I want to see if I can embed it.  Fingers crossed.  Your feedback welcome, as always.

 

Revolution Roadmap: Assess

by 3 Comments

Last week, I wrote about a process to follow in moving forward on the L&D  Revolution. The first step is  Assess,  and I’ve been thinking about what that means.   So here, let me lay out some preliminary thoughts.

The first level are the broad categories.  As I’m talking about aligning with how we think, work, and learn, those are the three top areas where I feel we fail to recognize what’s known about cognition, individually and together. As I mentioned yesterday, I’m looking at how we use technology to facilitate productivity in ways specifically focused on helping people learn. But let me be clear, here I’m talking about the big picture of learning – problem-solving, design, research, innovation, etc – as they call fall under the category of things we don’t know the answer to when we begin.

I started with how we think. Too often we don’t put information in the world when we can, yet we know that all our thinking isn’t in our head.  So we can ask :

  • Are you using performance consulting?
  • Are you taking responsibility for resource development?
  • Are you ensuring  the information architecture for resources  is  user-focused?

The next area is working, and here the revelation is that the best outcomes come from people working together.  Creative friction, when done in consonance with how we work together best, is where the best solutions and the best new ideas will come from. So you can look at:

  • Are people communicating?
  • Are people collaborating?
  • Do you  have in place a learning culture?

Finally,  with learning, as the area most familiar to L&D, we need to look at whether we’re applying what’s known about making learning work.  We should start with Serious eLearning, but we can go farther.  Things to look at include:

  • Are  you practicing  deeper learning design?
  • Are you  designing  engagement into learning?
  • Are you developing  meta-learning?

In addition to each of these areas, there are cross-category issues.  Things to look at for each include:

  • Do you have infrastructure?
  • What are you measuring?

All of these areas have nuances underneath, but at the top level these strike me as the core categories of questions.  This is working down to  a finer grain than I  looked at in the book (c.f. Figure 8.1), though that was a good start at evaluating where one is.

I’m convinced that the first step for change is to understand where you are (before the next step, Learn, about where you could be).  I’ve yet to see many organizations that are in full swing here, and I have persistently made the case that the status quo isn’t sufficient.  So, are you ready to take the first step to assess where you are?