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Clark Quinn’s Learnings about Learning

Archives for November 2020

AI and Meaningful Practice

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Again, a video of an idea I want to talk about. This time about AI and Meaningful Practice (just around 2 minutes). I welcome your thoughts.

By the way, I’m experimenting with video as a blog mechanism. A colleague mentioned that no one remembers the author of an article or post, but they do remember the speaker in a video. And much as I hate to do it, I do want people to associate my ideas with me! I welcome, very much, your feedback on this too!

Script:

Hi, I‘m Clark Quinn, Executive Director of Quinnovation (my vehicle for learning experience design strategy).    Today I want to talk about an insight I had, sparked in a conversation I had with a colleague.  We were talking about learning (of course), and the difference between knowledge versus practice.

I was reminded that we‘re now seeing AI technologies that can parse content and then answer questions about it.  We even see ones that can ask you questions about the content!  Which is part of learning.  But not all.

My realization was that, increasingly, these systems will take over this form of content presentation.  That is, we‘ll write a white paper, and an AI will parse it, then present it, and drill it.  Which is, after all, way too much of corporate learning.  See, for instance, the Serious eLearning Manifesto as a response.

Now, I‘ve always maintained that such systems aren‘t sufficient for real learning.  Meaningful learning includes more: motivation and contextualized practice.  Content presentation and quiz questions may be necessary, but by no means are they sufficient.  And that for now and the foreseeable future, AI will not be able to create those elements.  

This is the job of LXD: integrating learning science and deep engagement into experiences that transform us.  Which means that what L&D needs to do is stop doing information dump and knowledge test,  and learn how to do real learning experience design!  That, I suggest, is a noble pursuit (and, to be fair, what we should have been doing all along).  

Of course, there‘s also the necessary new role, per my last post/video, of being a facilitator of informal learning.  Coupling the optimal execution with continual innovation.  But, for now, I‘m suggesting we truly have to master everything that makes learning work, in particular meaningful practice.

That‘s my take, I welcome hearing yours.  Thanks for watching!

 

The Future of L&D? A pitch

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I was talking with a colleague the other day, and got a wee bit dramatic. I also thought it was an important point. So here, for your dining enjoyment, I’ve roughly recreated the pitch (in 3 mins and 30 secs):

I hope this makes sense. I welcome your thoughts and feedback.

The Script:

Hi, I‘m Clark Quinn, of Quinnovation, and I‘ve been around the elearning for well-nigh forever, and around L&D for the past couple of decades.  So…I joke that:

L&D isn‘t doing near what it could and should, and what it is doing, it‘s doing badly.  Other than that, it‘s fine.  

Seriously, I think there‘s the obviously important role for L&D,  but also a really important opportunity.  

Things aren’t getting any simpler.    We‘re facing increasing complexity and uncertainty.  And, going forward, I suggest, optimal execution is only the cost of entry.  Continual innovation will be the necessary differentiator.  That is, we will have to do well what we know we have to do,  but we also have to become agile, nimble, and able to pivot in the face of change.  So that means doing courses right, when courses are the answer.  That‘s the optimizing role, going beyond being efficient to being effective.

And it also means that organizations will have to get good at problem-solving, research, design, and more.The thing is with those things, when you start you don‘t know the answer.  That is: They. Are. Learning!  And that is the important opportunity.

Going back to being effective, that means that when we design courses, we need to effectively integrate learning science with true engagement.  Deep LXD,  not tarted up quiz shows and ‘click to see more‘. And, we should only do that when it‘s the right answer!  It‘s not ‘we need a course on this‘, but instead  “we can identify that we have a skills gap and we need to improve our performance”.

And then, it‘s about facilitating social and informal learning:  tapping into the power of our people, creating a learning culture, assisting the organization in systematic in good practices.  

How do we get there?  I argue there are two major steps.  First, we need to measure,  and here I mean more than just efficiency.  It‘s not how much it costs to have a bum in a seat for an hour,  but instead whether that bum in that seat for that hour does the organization any good.  Right now, we don‘t know whether our efforts are really moving any needles.  It‘s a matter of faith that if it look like school, it must be learning.

Second, it means we have to start practicing those principles within L&D: smart experimentation; collaborating; and learning continually and out loud.  We can‘t have credibility if we haven‘t walked the walk.It won‘t happen overnight.  We‘ll have to build back our reputation as scrutable practitioners.  We‘ll have to continually educate.  And likely have to do the ‘better to seek forgiveness than permission‘.

Here‘s the vision I see.  When we‘re not only ensuring good execution on what we know we have to do,  but are responsible for the ongoing success of the organization,  we‘ve moved to an indispensable position.  We‘re key to success in the toughest times!  As key as IT and Finance.  Other groups can and will take it on if we don‘t  but we‘re supposed to be the ones who understand how we learn.  And learning, going forward, is the key to not just surviving, but thriving.  Our orgs need it, the employees need it, and our professional standards demand it.  So let‘s do it.    Let‘s reengineer our status in, and value to, the organization.

Thanks for listening.

Flow, workflow, and learning

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On LinkedIn, a colleague asked “Why do people think that integrating content in the flow of work equals learning in the flow of work?” An apt question. My (flip) response was “because marketing”. And I think there’s a lot to that. But, a comment prompted me to think a little bit deeper, because ‘flow’ is its own meaningful concept and we need to be careful about meaning. So here are some reflections on flow, workflow, and learning.

The response that triggered my reflection was:

I can’t recall the last time I told someone that I was in the “flow” of work today and learned so much!!

Flow state(Which is pretty funny!) The comment was a bit pointed, but it made me think about being in the ‘flow’ state, and the relationship with learning. I’ve previously pointed out how Csikszentmihalyi’s Flow and Vygotsky’s Zone of Proximal Development  (ZoPD) are essentially the same. If the difficulty is too far above your skill level, the experience is frustrating. If it’s too easy, it’s boring. And in between is the flow state, and where learning happens.

Now, when we’re in the ‘flow’ at work (which is different than being in the workflow), we’re performing optimally. And I’m not sure learning happens there. Similarly with the ZoPD. You’re working and I’m not sure learning happens  then. When I state that learning is action and reflection, I think reflection is a necessary component.

Now, the original complaint talked about learning in the workflow, and opined that content in the workflow won’t necessarily equal learning. Another comment pointed out what I believe is often conflated with “workflow learning”, and that’s performance support. There are lots of reasons that we might want content in the workflow to help us succeed, but it may have nothing to do with learning. If, indeed, learning is to happen, it might need some content, and feedback, and so actually break the flow!

Now, I also recognize that many times we’re in the flow of work, but not in the ‘flow’  zone. So, we could definitely be learning in the workflow. And it happens by deciding to look up the answer to some contextually relevant question. Or from a comment from a person. But it’s a bit different than being in the zone, and we’d like to be there in our work too!

And, I wonder whether Vygostky’s ZoPD really aligns with the Flow Zone, or if it needs to be coupled with some offline reflection. It’s certainly possible. Maybe the flow zone is a superset of the ZoPD. More to ponder.

There isn’t a real revelation here about flow, workflow, and learning, other than we have to keep our concepts straight. We need to recognize when we’re supporting performance, and when we’re learning. And we need to be clear about workflow, and being in the flow zone. And there may be more here to unpack. Thoughts?

 

In Defense of Science

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I previously wrote in defense of cog psych. Here, I want to go broader. Not my usual topic, but… I feel the need to rail in defense of science.

When I’m talking about science, I’m talking about the systematic exploration of how things work. It’s about theorizing, and testing, and refining. It’s about having rigor in that, being systematic and principled. And, importantly, it’s about sharing the results and building on the works of others. Interestingly, it’s  not a human universal, but instead emerged relatively recently. However, there’s a reason it’s been so successful.

And, let’s be honest, science has flaws. There have been recent problems in replicability. Another problem is academic politics; new ideas can struggle to get recognized. Pressure to publish can lead to fake data. Folks with money can influence what research gets done, and the outcomes. Similarly, politics can play a role. Like democracy, it’s not perfect, but…and this is an important  but…there’s nothing better.

The evidence for science are the things that we’ve come to count on: sanitation, transportation, medicine, the list goes on. Your ability to read this depends on science. Most of what we use all day every day has been improved by science. So, too, some bad things, like how successful marketing can be at snagging your attention. Yes, we need to use it wisely. Science can help there, too! And, importantly, most scientists are ethical, caring, diligent individuals. They do what they do  for science, not for wealth, not for fame (except amongst their colleagues, which goes back to doing it  for science), and most certainly not to support conspiracies.

So, trying to pick and choose what science to believe isn’t a great bet. Unless you have a deep background in a particular domain, trying to ascertain the validity is challenging. You may listen to disparate voices, but not if they’re flying the face of a concerted viewpoint of people who have spent the requisite time to be true experts. In my mind, you’re either for science, or not. Saying “well, I’m not for  this science because someone said it’s controversial”, then, is just not on.

Yes, there are controversies around most science:  that’s how it advances. But there’s also essential truths that most every reputable scientist in the field will agree to. And that’s how we build products, services, and ultimately societies.  I was trained as a scientist (though I’m more of an engineer, tracking it and applying it to solve real problems). I know, in my field, what makes sense and what’s silly. And then, in other fields, I look to what the received wisdom is. And I know what sorts of people to listen to, and it’s not politicians, or pundits. Unless they listen to science.  The best guidance comes from the folks who know the field in question. And that holds true for medicine as well as meteorology.

And sure, I too could wish I lived in a world where magic worked. But if you think about it, they, too, use systematic experimentation to find out what works. Whether Earthsea or Hogwarts, they go to schools to learn and there the professors are studying. But here, magical thinking doesn’t work. Science is what has let us knock back polio, generate electricity from sunlight, and walk on the moon.

So, if you do want to go against what the scientists or reliable interpreters tell you, don’t do it piecemeal. Abandon all the science, because you’re unlikely to get it right in a domain that’s not your expertise. If  anyone is telling you contrary to what’s known, question their motives! People mislead for lots of reasons, from money to mischief. If you let them, they’ll hurt you in ways that may be stark or subtle.

If they’re steering you away from something that has been shown to be better than the alternative, you should be wary. Their tricks are myriad: lack of context, distortions, selected subsets, and outright lying. For instance, our brains are wired to see patterns. If we’re pointed to them, we’ll see them. We’re also biased to look for evidence that confirms our beliefs, and avoid what contradicts it. Thus, it’s easy to gin up potential conspiracies, despite the incredible challenge in actually pulling them off!

I’m putting it out there. I can say that, in defense of science, it’s better than any other approach. That’s my stance, what’s yours?