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Clark Quinn’s Learnings about Learning

Update on my webinars

19 January 2021 by Clark Leave a Comment

I know, I know, I’ve been doing a lot of updates: books, workshops, and now webinars. I promise I’ll get back to my regular posting on learning things, but the benefit of these, unlike books or courses, is that they’re free. And several are coming up! So I thought I’d at least let you have a chance. So, here’s an update on my webinars.

First, I’ll be talking for eLearning Learning on the 27th of January at 11AM PT (2PM ET). They were interested in discussing about the impact on Covid, and of course I’m taking it in an aspirational direction. I’m presenting about how we’re not well aligned with how we think, work, and learn, and what that looks like in general, and in particular online.

Then, I’m doing a ‘make it meaningful’ presentation for iSpring on 25 Feb at 9AM PT (noon ET). The coordinates to sign up are here.   It aligns with their theme and I’ll get into some top-level issues.

Then, on 18 March, at 10AM, I’ll talk with Barbara Covarrubias Venegas on facilitating innovation. Since here topic is on virtual space, I suspect we’ll focus there. It’s a LinkedIn Live event, you can see it as one of her list of interviews.

Finally, at 10 AM PT (1PM ET) on Thursday the 13th (not Friday), I’ll be talking learning science for ATD.  That, as yet, doesn’t have a page AFAIK. More info as it emerges.

(BTW, there’s a recording of my webinar last week on learning science.)

This actually presents a pretty fair coverage of my areas of focus, so if any one (or more) is of interest, here’s a chance to see my thoughts. My general focus, as I like to quip, is on those things L&D isn’t doing, and what they’re doing badly. Which is most everything! 😁  I’m sure more webinars will eventuate, but that’s it for now. So there you go, an update on my webinars. Hope to see you there!

Update on my workshops

13 January 2021 by Clark Leave a Comment

Just as I did an update on my books, it’s time to also let you know about some workshop opportunities. Together, I think they create a coherent whole. They’re scattered around a bit, so here I lay out how they fit together, how they’re run, what they cover, and how you can find them. They’re not free, but they’re reasonably priced, with reputable organizations. So here’s an update on my workshops.

First, they’re three pieces of the picture. I talk about two things, generally. It comes from my cheeky quip that L&D isn’t doing near what it could and should, and what it  is doing, it’s doing badly. So, that first part is about the larger performance ecosystem, and the second part is about learning experience design (LXD). And, that latter part actually pulls apart into two pieces.

I see LXD as the elegant integration of learning science with engagement. Thus, you need to understand learning science (and the associated elements). Then, you  also  need to understand what makes an engaging experience. So, two workshops address each of these.

The learning science workshop is being run under the auspices of HR.com (brokered through the Allen Academy). It’s under their professional education series, called Effective Learning Strategies. It’s a five week course (with a delayed sixth week). There are readings, a weekly session, and assignments. You can earn a certificate. In it I cover the basics of cognitive science, the learning outcomes, social/cultural/emotional elements, and the implications for design. It’s just what you need to know, and very much aligned with my forthcoming book!

The second part of the story is about the engagement side. While I’ve tried to boil down learning science into the necessary core, there are other resources. This isn’t well covered. And note, I’m  not talking about tarted-up drill-and-kill, gamification, ‘click to see more’, etc. Instead, I’m going deep into building, and maintaining: motivation, reducing anxiety, and more. Formally, it’s the Make It Meaningful workshop. This is a four week course, with videos to present the information, then live sessions to practice application, and takeaway assignments from the Learning Development Accelerator. It’s based upon the learnings from my book on designing learning games,  Engaging Learning,  but I’ve spent months this past summer making it more general, going deeper, validating the newest information, and making it accessible and comprehensible.

The final story is the performance ecosystem workshop. In what may seem a silly approach, it manifests as a course on mobile! However, once you recognize that mobile is about pretty much everything but courses (and can do contextual, which is an important new direction). It makes sense. When I was writing the mobile book, the intent was that it be a stealth approach to shift the L&D mindset away from just courses. Which, of course, was made more clear with my Revolutionize L&D book. So I hope you can see that this course, too, has a solid foundation. It’s about courses, performance support, informal and social learning, contextual opportunities, and strategy, in six weeks of online sessions, with a tiny bit of reading, and interim assignments. It’s by the Allen Academy directly.

Together, I think these three workshops provide the knowledge foundations you need to run a L&D operation. Two talk about what makes courses that are optimally engaging and effective, and one looks at the rest of the picture. Evidence suggests there’s a need. And I’ve worked hard to ensure that they’ve got the right stuff. So that’s an update on my workshops. I welcome your thoughts and feedback.  (And, yes, I’d like to pull them all together in one place, but I haven’t found a platform I like yet; stay tuned!)

 

Habits and variety

6 January 2021 by Clark Leave a Comment

Having heard it’s good for maintaining cognitive ability, I like to vary things. And, to keep doing things right, I like habits. Are these mutually exclusive? Maybe, but here’re some thoughts on habits and variety.

It’s been touted that a great way to fend off the diminishment of cognitive capability is to do things differently. So, for instance, turning off the hall light before going down the hall on your way to bed. That is, finding your way in the dark. And, in general, trying things different ways. The notion is, this continual active cognitive challenge keeps your thinking ability from decaying. And that’s a good thing.

On the other hand, habits are helpful. For instance, having a regular approach to brushing your teeth. If you’ve established a good approach regularly, muscle memory can carry you through a late bedtime. And, in general, habits can help us make sure we do certain things that are good for us.

Is there a reconciliation? Here’s my just brainstorming, but I think that  when you have a good awareness of the habit, varying it is a good procedure. You’re actively problem-solving, versus throwing yourself off balance at a bad time. So, taking on a challenge clear-headedly is good.

Now, we know that, for instance, training for emergencies and unexpected situations leads to better learning. That’s why varying practice is helpful. So wouldn’t unexpected challenges be even better? Probably, but I reckon we get enough of these in life anyway!  That time you find out that you’re out of tea unexpectedly. Or when your car won’t start. Then we have challenges. And despite our best habits, the world seems to find ways to thwart our plans.

Now, changing bad habits to good ones is even harder. And then there’s the difference between habits and ritual. But those’er topics for another time.

So there are my thoughts on habits and variety. Do it, when you can devote enough cognitive resources to still be successful. That’s my approach, at least. There’s enough randomness in my life otherwise!

(And, yes, I’m not filming this one. Got to it too late! The world, thwarting my plans…)

Updates on my books

1 January 2021 by Clark Leave a Comment

At this calendar inflection, it’s interesting to note how time flies. I was somewhat amazed to find out that my first three books were already out of print! And there are two reasons to keep them out there. For one, because there’s still some interest (I get pinged occasionally). Two, I wrote them based on principles of how our brains work, to be technology-independent (e.g. mobile still is changing so  fast). So I reckon they’re still relevant. (A review of one I came across said just that.) As a consequence, I sought the return of the rights. Here’re updates on my books.

You could get two of the expired books as ebooks, but now Amazon also has a paperback option. I’ve been able to put all three up as both! The covers have changed, of course, since I don’t know as to rights for the images used. And, I’ve priced them way down (Happy New Year! :)  Anyways, here’re links (they literally came through over the past couple of days) that take you to both options:

The Mobile Academy: mLearning for Higher Education

Designing mLearning: Tapping into the Mobile Revolution for Organizational Performance

Engaging Learning: Designing e-Learning Simulation Games

Of course, two of my books aren’t yet out of print. You can still get them both:

Millennials, Goldfish, and other Training Misconceptions: Debunking Learning Myths & Superstitions

Revolutionize Learning & Development: Performance and Innovation Strategy for the Information Age

And my forthcoming one is now available for pre-order!

Learning Science for Instructional Designers: From Cognition to Application

So those are the updates on my books.

For the record, these are all Amazon Associate links, for which I get a cut: support your friendly and helpful consultant!

Separate content from description

29 December 2020 by Clark 3 Comments

Once again facing folks who aren’t using styles, I was triggered to think more deeply about the underlying principle. That is, to separate content from description. It’s a step forward in what we can do with systems to bring about a more powerful human-aligned system.

And, as always, here’s the text, in case you (like me) prefer to read ;).


I‘ve ranted before about styles, but I want to make a slightly different pitch today. It‘s not just about styles, it‘s about the thinking behind it. The point is to separate content from description.

So, the point about styles is that they‘re a definition of formatting. You have elements of documents like headings at various levels, and body text, and special paragraphs like quotes, and so on. Then you have features, like font size, bolding and italics, color, etc. And what you see, too often, is people hand-formatting documents, choosing to do headers by increasing the font size, bolding, etc. And, importantly, having to go through and change them all manually if there‘s a desire for a change in look.  

The point of styles is instead merely to say this is a heading 1, this is a figure, this is a caption, and so on. Then, you separately say: heading 1s will be font size 16 bold and left-justified. Figures and captions will be centered, in font size 12. And so on. Then, should someone want to change how the document‘s formatted, you just change the definition of heading 1, and all the heading ones change.  

It goes further. You can define that all heading ones have a page break before (e.g. a new chapter in a book). And you can define new styles, like for a callout box (e.g. colored background), etc. You can have different heading ones for a book than for a white paper. And some styles can be based on others. So your headings can use the same font as your body text, and if you want it all to change, you change the source and the rest will change.  

Which is wonderful for writing, but the concept behind this is what‘s really important to get your head around. That is, separating out role from description. That‘s what‘s led me to be keen on content systems. The notion of pulling up content by description instead of hardwiring together content into an experience is the dream.  

It‘s all about beginning to use semantics, that is the meaning of things, as a manipulable tool. Many years ago, I led a project creating an adaptive learning system. We were going to have content objects defined by topic, and learning role, and tagged in terms of media, difficulty, and more. So you could   say: “pull a video on an example of diversity set in a sales office”. Our goal, with a suite of rules about what when to move up or back in difficulty, was to specify what learning content the learner should see next, etc.  

This is how adaptive platforms work. When Amazon or Netflix make a recommendation for you, there‘s not someone watching your behavior, instead it‘s a set of rules matching your particular actions to content recommendations. If you‘ve ordered a lot of British mysteries, and you haven‘t seen a particular series that lots of other people like, it‘ll be likely to be offered to you.  

This is the opportunity of the future. We can start doing this with learning (and coaching)!   We can start pulling together your learning goals, job role, current progress, current location (in time and space), etc, and offer you particular things that are appropriate for you. And, like our learning system, it might be recommendations of content, but you can choose others, or ignore, or…As Wayne Hodgins used to say, present the ‘right stuff‘: the right content to the right person at the right time in the right way….

The point being, just like styles, if we stop hardwiring things together, hand-formatting learning experiences, we can start offering personalized and even adaptive learning. Yes, there are technical backend issues, and more rigor in development, but this is the direction we can, and should, go. At least, that‘s my proposal, what say you?

Performance Ecosystem Maturity Model

22 December 2020 by Clark 3 Comments

Someone on LinkedIn asked about a way to evaluate orgs on their learning infrastructure. And I had developed a Performance Ecosystem Maturity Model as part of Revolutionize Learning & Development, but…I hadn’t presented it. At least not in full.  Here I rectify that; my holiday gift to you!

(A bit over 5 mins.)  And, of course, if you want help with it, let me know! Also, the prose (and the diagram):


Script

Hi, I‘m Clark Quinn, of Quinnovation. Recently, someone asked about an organizational learning maturity model. And, coincidentally, I had one. However, it was locked away in my book from 2018. So I want to present that model, and hope it‘s of use.  

In my book, Revolutionize Learning & Development, I pushed for the performance ecosystem, going beyond ‘the course‘ to talk about all the ways that L&D that could assist organizational learning. I posit that optimal execution is only the cost of entry, and the only sustainable differentiator is continual innovation. And I argued for what that meant. I want organizations to have a concrete picture of what this looked like.

In the book I had a set of six categories, each with two components. So I created a ‘maturity model‘. The intent is to provide a tool whereby organizations can understand what the possibilities are, assess themselves, and prioritize directions to move and improve. Let‘s be clear, this is conceptual, not empirical. This is a proposal about what should be the elements, and an effort to consider what fits in each stage of each component.  

The first area is culture. How we‘re learning, and what our orientation is. And you‘ll see as we fill out the table, what this means. Starting with learning, we transition from a competitive environment, (which is unhealthy), through being willing to cooperate (say for team projects), to where we‘re collaborating of our own initiative, ending up where we‘re working to also improve our processes as well as our outcomes. And our orientation shifts from learning for our own benefit, to learning as an organization, then to where we consider the impacts on society, ending up where we‘re looking to ensure this works across those elements.

Then we look at the formal learning elements, how we design and who‘s using the learning. We start with the traditional knowledge dump, then on making it more engaging and lean, to where we‘re focusing on making it meaningful to the org and the individual, and finally creating transformative experiences. And we look at who‘s using the learning. It starts with taking orders for courses, through having some times where the effort is to truly address a need, to where our efforts are aligned with key organizational needs, and finally where we‘re being discerning about methods, measures, and outcomes.

We then consider going beyond the course to times when knowledge can be in the world, not in the head. We worry about resources and the ways people can get access to them. Instead of idiosyncratic aids, we move to having L&D creating support, and then recognizing the value of curation, and finally with a mixed initiative with everyone contributing. And we move from the siloed access to these resources, through an intermediate stage of some focused development, to a user-centric access based upon the users needs (not the originators location), ending at a dynamic matching of need to resource.  

We also start looking at informal learning, the continual innovation. This includes both the status of networks and the usage of those networks. It starts where if there‘s network usage, it‘s not org-originated, through some units having a system, to having an organizational focus on communication, and then actively facilitating social learning. And we move from the Miranda organization (where anything you say can and will be used against you), to where some folks are experimenting, to where people are comfortable contributing, and finally where folks recognize that active engagement is key to organizational thrival.

We also consider the use of metrics in the organization, both to evaluate and to improve. We should move from just looking at the cost of a butt in a seat for an hour to whether that time is benefiting the org. Then we incorporate informal learning, and finally where measurement‘s naturally part of our practices. We move our focus from internal to a broader picture, and start evaluating our processes themselves, and move to looking at these as a synergistic whole  

Finally, we look at our infrastructure, our underlying approach and our systematicity. We move from handcrafted solutions to systemic approaches, then looking to incorporate semantics, and finally looking at systems with emergent capabilities. And we move to look at our approaches as platforms, and then integrate those platforms, and finally allow our systems to adapt as conditions change.  

This is an updated version of the model in the book, and I think provides a useful framework for thinking about L&D. I hope this made sense, and is of interest. And I welcome feedback! Thanks for listening. You can find out more at Quinnovation.com, and at revolutionizelnd.com.  

Five trends for 2021

15 December 2020 by Clark 2 Comments

As frequently happens, I get asked for my predictions. And, of course, I have reservations. Here’s a video that provides the qualifications, and five trends for 2021 that I’d expect, or like, to see.

And the script:


Hi, I‘m Clark Quinn, of Quinnovation (a boutique learning experience design strategy consultancy). I was recently asked about what trends I thought would be seen next year.  

Two relevant quotes to set the stage. For one, Alan Kay famously said “the best way to predict the future is to invent it.” So I tend to talk about trends we should see. The other is “never predict anything, particularly the future.” I heard an expert talk about having looked at predictions and outcomes, and the noticeable trend is that it went as expected, with one unforeseen twist. So, expecting I‘ll get it wrong, here are some trends I‘m either expecting or keen to see:

The first trend I‘m seeing and think will continue is an emphasis on learning science. And that‘s all to the good! Admittedly, I‘m part of this, what with running a course on learning science and having a forthcoming book on the topic. But I‘m seeing more and more people talking about it, and not all hype and even mostly right! There are more books, the Learning Guild‘s regular research reports are good, the launch of an event past summer and an associated new society focused on evidence-based learning (the Learning Development Accelerator) are all signs of growing momentum.

Second, when there‘s a lot of hype about something, it tends to be followed by a backlash.  This may be farther out than 2021, but with all the buzz about AI, I think we might see some more awareness of limitations. Yes, it can do some very useful things, but it also isn‘t a panacea. We‘re seeing a growing awareness of the problems with bias in data sets, the limitations of ungrounded knowledge, and concerns about the human costs.  

Three. On a related note, then, I expect more emphasis on the importance of meaningful practice. This comes from learning science, but also the focus on engagement. Thus, the push for Short Sims, and better written multiple choice questions, and in general a focus on ‘do‘, not know.   Hopefully, we‘ll see tool vendors aligning their content and assessment capabilities towards designing scenarios and contextualized practice, along with specific feedback for each wrong answer and support for reflection.

Fourth, I hope for a push towards content systems as well. This, too, may not be in the short term, but ultimately we have to realize that hardwiring experiences may make sense for formal systems, but not for adaptive learning.LXPs are a good move here, even if misnamed (really, they‘re smart portals, not learning experience platforms). Ultimately, we‘ll be better off if we can deliver content by description and rules, like recommendation system, rather than by having to handcraft content to create a ‘one-size fits all‘ solution.  

Finally, I think that our collaboration tools haven‘t lived up to the promise of technology. They‘re very much oriented towards particular modes, instead of supporting really rich interaction. This, too, is more long term, but we really should be able to talk together while working to create representations that capture our evolving thinking. Easily and elegantly! There‘s real opportunity here to engage multiple representations in an elegant suite.  

So there you have it, a wishful list of five trends for 2021. So what do you expect, or hope, to see?

Foundations of Learning Science

8 December 2020 by Clark 1 Comment

Another video, this time (ok, again ;) about learning science.

They like me to do this to push the course, but I did hear the feedback on LinkedIn that the video format works. Nice to know. As always, also the script.

And, announcing one other thing…


I‘ve argued in an earlier post for the value of learning science, but I want to go a little deeper. I want to talk a little about the evolution, and a little bit about what‘s involved. It‘s about establishing the foundations of learning science.

And I‘ve mentioned in a previous post  that learning science is interdisciplinary, and relatively new. While education had been proceeding for a long time, the approaches were ad hoc. Experimental science itself didn‘t emerge ‘til the medieval ages at the earliest. My take is that most of school still replicated what had been done since the Prussians invented school, somewhat modeled on religious lectures. The notion of scientific education had yet to emerge.

The first real systematic study of learning came from the field of educational psychology. Here, the focus was on schooling, and included cultural and motivational factors.

A different approach came from behavioral psychology roots. During World War II, the military was faced with training many soldiers, and behavioral psychologists created the field of instructional design. Here, the focus was more on training, including the influence of media and elements of instruction.

Learning science as a field was arguably created when the International Society for the Learning Science was created in the 1990s, perhaps sparked by the creation of the Institute of the Learning Sciences at Northwestern University. This is an integrative approach that looks beyond schools and training to more forms of learning including informal learning and even machine learning.

Having been involved in one way or another with all of these, I tend to create a synthesis. I think the care is cognitive science: how we process information. While there are neural underpinnings, most of the results and prescriptions operate at the cognitive level, or above. Within the information processing cycle we cover core processes like attention, elaboration, and retrieval. This is our core mental architecture.

Interesting results for learning emerge from this architecture, including the role of models and examples, and the core importance of practice. A post-cognitive perspective reflects that our thinking isn‘t formally logical, but instead is emergent, distributed, and social.

Two other important areas are the emotional aspects of learning, and meta-learning. The former is more the conative area of intent to learn, e.g. motivation and anxiety, rather than the affective area of personality. The latter has to do with learning to learn, including looking at our own learning processes.

All these affect the elements that contribute to learning. Our introductions, concepts, examples, practice, and closings should reflect what‘s known about learning. And the components of science and engagement need to be elegantly integrated to yield the best outcomes.

Of course, these foundations of learning science are what I cover in the learning science courses I‘m offering through HR.Com and the Allen Academy. Stay tuned for more ;).

Measuring Impact (or not)

1 December 2020 by Clark 6 Comments

So I saw a twitter thread pointing to an argument about how ROI is dead. And, well, that’s largely okay with me. However, the trigger for the post was from the results of Chief Learning Officer 2020 State of Learning report.  And, when I saw them, I saw some problems. The question is whether we’re measuring impact, or not. I’d like to go through them and evaluate each.

(Back to my usual prose, as I need visual support for this. ;)

So, in the report, they indicated that the respondents indicated the demonstrated impact of training in these ways:

  • General training output data
  • Training output data aligned with corporate initiatives
  • Learner satisfaction with training
  • Employee satisfaction with training availability
  • Employee engagement
  • Business impact
  • Employee performance data
  • Planned to actual budget, expense, revenue data for training group
  • Stakeholder satisfaction with training data
  • ROI measures
  • Net promoter score
  • Employee satisfaction with company data

Yikes!  Some of these are problematic at best.  Let’s look at why some of these might not be good measures of impact. And, let’s be clear; impact should be about positively affecting the organization in a meaningful way. Moving needles like fewer errors, more revenue, reduced costs, happier employees and customers, etc.

So, first, what  is  general training output data? If it’s like what I saw in (then) ASTD’s State of the Industry report, it’s metrics like employees served per L&D employee or cost/seat/hour for training. Which might a useful measure of efficiency, if you can come up with a principled basis for what a good number would be, and then see if you’re above or below that. Unfortunately, what people do is just compare themselves to the industry average. Is that a good indicator? How do you know? Do you want to be just ‘better than average’?

Then, training output data  aligned with corporate  initiatives.  Again, hard to say what this means (and I can’t seem to find the report). However, it sounds like it’s still efficiency, just doing that for things the business thinks are important.

And we go worse: learner satisfaction with training? Er, research I’ve read and heard cited (I think it’s from Salas, et al, but memory fails)  says that’s not valid. There’s a .09 correlation between what learners think of learning impact, and it’s actual impact. That’s zero with a rounding error. That’s all about making learning ‘fun’ (instead of ‘hard fun’). Yes, you do want them to think it’s  also been a good experience if you’re focusing on LXD, but that’s secondary.

Similarly, with satisfaction with training availability. What’s that matter? That’s not  impact!

Some good things buried here: employee engagement should be good; more engaged employees is a good thing. As long as it’s not at the cost of something else, like, say, impact?  And business impact is obviously good, as is employee performance data. Presumably positive business impact, and employee performance improving.

Planned to … stuff is all about efficiency again. And that’s ok, but only  after impact. Otherwise, well, we’re not  costing too much…?!?

Satisfaction again not good.

And, to the original point of the article. ROI?  Yes, what it costs you to move a needle should be less than the cost of what the needle was costing you.  However, I could be doing things that return the biggest ROI without doing the most important things. They can be different (e.g. a small program with a better ROI but less overall impact). So it’s only secondary.

Finally, employee satisfaction with company data? I have no idea what that means? But, again, ‘satisfaction’ isn’t really meaningful unless it’s based on real impact.

I’ve complained before about L&D measurement. Here it is, right in front of us. The answer to the question of whether we’re measuring impact or not appears to be ‘mostly not’.  We’re still (largely) measuring the wrong things. And we wonder why we don’t have credibility. Please, please, start designing to improve measurable gaps, and then actually improve the outcome. Otherwise, you’ve no idea whether that bum in that seat for an hour is doing the organization any good, versus just not costing too much relative to the industry average.

AI and Meaningful Practice

24 November 2020 by Clark 3 Comments

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!

 

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