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Clark Quinn’s Learnings about Learning

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Foundations of Learning Science

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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)

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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

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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.

Ritual

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I’ve talked before about the power of ritual, but while powerful, it also seemed piecemeal. That is, there were lots of hints, but not a coherent theory. That has now changed. I recently found a paper by Nicholas Hobson & colleagues (Schroeder, Risen, Xylagatas, & Inzlicht; warning, PDF) titled  The Psychology of Rituals  that creates an integrated framework. And while my take simplifies it down, I found it interesting.

At core, what the model suggests is that there are two components that are linked together. The first element are things that involve the senses. The second element are the semantics we’re looking to create allegiance and adherence too. And there are important elements about this relationship.

There are a number of elements that are on tap for involving the senses. Certain movements, sounds, and words said or to be spoken can be used. There can also be food, drink, smells, and more. Objects also. Timing is an element; at the micro level of things in order, and at the macro level of the triggers for the ritual.

Semantics come, of course, from your needs. It can be about things you want people to believe, or a set of values you want people to subscribe to. Or, of course, both. From the design purpose, I’d suggest it’s about agreeing to be a member of a community of practice; to undertake certain actions when appropriate, and to uphold certain values.

Interestingly, according to their model, the relationship between the two is effectively arbitrary. That is, there is no intrinsic relationship between what you’re signifying, and how you do so. Rituals are about the practices. Which means you could in theory do just about  anything to make the relationship.

The other thing is that the ritual has to be invariable in its aspects. You define it, and so do it. Note that the execution can vary considerably; from several times a day to upon certain triggering conditions. So, for instance, having completed a course, or before engaging in certain activities.

While such a definition gives us lots of freedom, it also doesn’t necessarily serve as a guide for design. Still, thinking about it in this way does suggest the utility in developing deeply held beliefs and appropriately practiced behaviors. At least, that’s how I see it. You?

What is wrong with (higher) education?

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I was having a conversation with a colleague, sparked by dropping enrollments in unis. Not surprisingly, we ended up talking about flaws in higher education. He suggested that they don’t get it, and I agreed. He was thinking that they get the tech, but not the learning. I think it’s more complex. There are those that get some parts of the learning right. Just not enough, and not all of it right. Thinking further, post-convo, it occurs to me that there is a layer beneath the surface that matters. So I want to consider what is wrong with higher education.

And, let’s be clear, I’m  not talking about the problems with tuition and administration. Yes, tuition’s risen faster than the cost of living. And yes, there’s little commercial pressure to keep universities free from the persistent creep of increasing administration. I saw an interesting article talking about how universities without a solid financial foundation,  and ones without a good value proposition, will perish. It’s the latter I’m talking about.

I previously mentioned the three pillars I think create a valid learning offer:

  • a  killer learning experience,
  • being a partner in your success
  • and developing you as an individual.

I suggest that all three are doable, but it occurred to me that there’s a bit more to unpack.

The ‘being a partner in your success’ bit is most frequently seen. Here, it’s about looking for signs of trouble and being proactive about reaching out and assisting. It’s not ‘sink or swim’, but recognizing there can be troubles and helping learners cope. The Predictive Analytics work that Ellen Wagner did is the type of opportunity we have here.

The ‘developing you as an individual’ is really building your more general skills: communicating, working with others, a positive attitude, knowing how to search, etc. And, of course, knowing how to continue to learn. Given the rate of change, most of what you learn as the core of a degree may well be out of date in short order!  But you can’t address these skills on their own, they’re specifically about how you do domain things.  And that’s a layer I’ve yet to see.

And the ‘killer learning experience’ is a second area where I think folks still aren’t doing well. My short (and admittedly cheeky) statement about education is that they’re wrong on two things, the curriculum and pedagogy, other than that they’re fine. Most universities aren’t doing a good job of curriculum, focusing on knowledge instead of skills. And some are moving in a good direction. Startups are addressing this area as well.

The other problem is the pedagogy. There’re two elements here: the learning design, and engagement. Too often, it’s still the ‘information dump and knowledge test’. But even when that’s right, making it truly meaningful for the learners is sadly neglected. Even professors who care often forget to put the ‘why’ into the syllabus.

In short, what is wrong with higher education is the ability to successfully execute on  all these points. (It’s true for other education, too, but…) I’ve seen efforts that address one, or two (and plenty that get none right). However, as of yet, I have not seen anyone doing it the way it could be done.  It’s doable, but not without some serious attention to not only the elements, but their successful integration. And it’s important enough that we should be doing it. At least, that’s what I think. So, what do  you think?

Learner-centered, or…

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I saw a post the other day that talked about ’empathy’, and I’m strongly supportive. But along the way they cited another topic that I’ve had mixed feelings about. So I thought it was time to address it. I’m wondering about ‘learner-centered’, and it may seem churlish to suggest otherwise. However, let me make the case for an alternative.

First, ‘learner-centered’ (apparently also known as ‘student centered‘) is used to take the focus away from the teacher. And I approve. It’s too easy, without awareness, to put the emphasis on ‘teaching’, and you’re on a slippery slope to lectures and knowledge tests. I’m all for that. However, I’m worried about a down-side.

My worry, with learner-centered learning, is that we may become too accommodating. It could be too easy to cater to learners. For instance, one belief that persists is that learning should be ‘fun’. Which is wrong. We know that we need ‘desirable difficulty’ (ala Bjork). That’s why I’ve lobbied for ‘hard fun‘. We could also use learner-centered to make the case for adapting to preferred learning styles. Which, too, would be wrong.

Obviously, you can also argue that learners need meaningful learning, so a learner-centered approach would be appropriate. But I want to suggest another candidate. One that, I argue, leads to good outcomes without carrying any opportunity for baggage.

I’m arguing for ‘learning-centered’, not learner-centered. That is, the focus is on the learning needed, not on the learner. Which isn’t to say we leave the learner out of the equation, but the question then becomes: what does this mean?

I’m suggesting that the key is learning focused on:

  • meaningful outcomes
  • aligned design
  • addressing learners’ prior knowledge
  • addressing learners’ emotions: motivation, trust, anxiety, confidence

And, look, I get that folks talking about ‘learner-centered’ will argue that they’re talking about the same things. I just see it also carrying a greater potential for focusing on the learner  at the expense of learning. And, in general, I would expect to be wrong. That is, most folks aren’t going to go awry. But is there an alternative without the problems?

So, the question is whether ‘learning-centered’ has similar pitfalls, or is it more likely to lead to better outcomes? And I don’t know the answer. It’s just a concern that I’ve felt, and thought I’d raise. Now it’s your turn!  What are your thoughts on the phrase ‘learner-centered’?

Unpacking collaboration and cooperation?

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My colleague, Harold Jarche (the  PKM guy), has maintained that cooperation is of more value than collaboration. And for good reason, because cooperation comes from internal motivation instead of external direction.   But this has bugged me, so I naturally tried to make a diagram that helps me think about it. So here’s a stab an unpacking collaboration and cooperation.

His argument, most convincingly can be summed up in this quote (I’ve simplified) he takes from Stephen Downes:

collaboration means ‘working together‘. That‘s why you see it in market economies…
cooperation means ‘sharing‘. That‘s why you see it in networks…

That is, when you’re offering to work together without some recompense, it’s a higher order.   And I agree.

However, I like to think of collaboration as a higher form of thinking. That is, working together to generate a new, negotiated understanding richer than any we could generate on our own. Cooperation means I point to something or give you some feedback, but we’re not necessarily engaged in creation.

The question is how to reconcile this. And it occurred to me to pull it apart a bit. Because I’ve seen, heck I’ve  participated in exercises where we collaborate for the greater good. Sharing. So I wondered if I might tease out two dimensions.

I wondered whether there are two types of cognitive actions, e.g. collaboration and communication. That is, for one you’re just offering pointers or opinions, without necessarily having any skin in the game. In the other, you’re actively working with someone to generate a new interpretation.

That’s coupled with a second dimension, whether the goal has been dictated externally (e.g. here team, find a solution to this problem) or has emerged from the participant. It’s about locus of control.

You end up with different types of categories. If someone’s asked you to collaborate, it’s likely some sort of project team. Less intently, it may be a ‘show your work’ type of thing, where the organizational culture is supporting sharing, but it’s also an expectation.

On the other hand, you can be just contributing to others by commenting on their blog posts (hint hint, nudge nudge, wink wink). Or you could be part of a Community of Practice and actively trying to improve something.

And I could be totally missing the nuances he’s talking about.

I don’t know if this addresses the issue or not, but it’s my stab at unpacking collaboration and cooperation. And I share it, because I’m wrestling with it, and it’s how I learn out loud. I invite your thoughts.

 

Tips to Avoid Millennials Marketing Hype

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I received, in my email, a solicitation for a webinar titled 5 Tips to Engage Gen Z and Millennial eLearners in 2020 and Beyond.  And, as you might imagine, it tweaked my sensibilities for the worse. My initial reaction is to provide, as a palliative, tips to avoid millennials marketing hype.

The content starts off with this scintillating line: “if you‘re searching for current, new ways to engage people online and keep your business thriving, look to your youngest learners.” What? Why do you want current and new ways to engage people? How about the evidence-based ways instead? Tested and validated ones. And why your youngest learners? Organizations need to be continually learning across all employees. Why not just your  newest employees (regardless of age)?

So, your first tip is to look for phrases like ‘new’ as warnings, and look for “research-based” or “evidence-based” instead. “Science-based” is likely okay, as long as it’s not neuroscience-based (wrong level) or brain-based (which is like saying ‘leg-based walking’ as someone aptly put it.)

Second tip: don’t be ageist. Why focus on their age at all? Deal with people by their knowledge and background. It’s discriminatory, really.

The ad goes on: “To future-proof your learning program, make sure your content is designed with these young professional learners in mind.”   What’s different for these learners? Their cognitive architecture isn’t fundamentally different; evolution doesn’t work that fast. So why would you do something just for them (and discriminate against others) instead of doing what’s right for the topic?

Next tip: avoid any easy and inappropriate categorizations. Don’t try to divide content or experiences in trendy ways instead of meaningful ways.

You should already be leery. But wait, there’s more! “On one hand, they can be distracted, overwhelmed, and impatient. On the other, they are highly collaborative, technically-savvy, and driven by fairness and storytelling.”This is like a horoscope; it fits most everyone, not just young people. We all have distractions and increasingly feel overwhelmed. And our brains are wired for storytelling.   These describe human nature! And that ‘tech savvy’ bit is a clear pointer to the digital native myth. Doh!

They then go on. “With this in mind, how can you effectively engage this digitally dependent group to attract, train, and retain them?” Um, with what attracts, trains, and retains humans in general?  That would be helpful!

Thus, another tip: let’s not make facile attributions that falsely try to portray a meaningful difference. Let’s focus on design that addresses capturing and maintaining attention and motivation, and communicating in clear and compelling ways. And skip mashing up myths, ok?

We’re not  quite done with the pitch: “how to level up your existing learning strategy to meaningfully engage your Millennial and Gen Z learners.” This is just a rehash of the tips above. Meaningfully engage  all your learners!

There’s also this bullet list of attractions:

  • What motivates Millennials and Gen Z and how to tailor your learning strategy to keep them engaged
  • Ways in which traditional learning programs fail younger learners and how you can prevent these common mistakes
  • A step-by-step process for evaluating your instructional content, providing you with an actionable blueprint on transforming your content

This could easily be rewritten as:

  • What motivates Millennials and Gen Z learners and how to tailor your learning strategy to keep them engaged
  • Ways in which traditional learning programs fail younger learners and how you can prevent these common mistakes
  • A step-by-step process for evaluating your instructional content, providing you with an actionable blueprint on transforming your content

And, for all I know, that’s what they’re really doing. That would be actually useful, if they avoid perpetuating the myths about generational differences. But, as you can tell, they’re certainly trying to hit buzzword bingo in drawing you in with trendy and empty concepts. Whether they actually deliver is another issue.

Please, avoid the marketing maelstrom. Follow these tips to avoid millennials marketing hype, and focus on real outcomes. Thanks!

Curious about Curiosity

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Looking into motivation, particularly for learning, certain elements appear again and again.   So I’ve heard ‘relevance’, ‘meaningfulness‘, consequences, and more. Friston suggests that we learn to minimize surprise. One I’ve heard, and wrestled with, is curiosity. It’s certainly aligned with surprise. So I’ve been curious about curiosity.

Tom Malone, in his Ph.D. thesis, talked about intrinsically motivating instruction, and had curiosity along with fantasy and challenge. Here he was talking about helping learners see that their understanding is incomplete. This is in line with the Free Energy Principle suggesting that we learn to do better at matching our expectations to real outcomes.

Yet, to me, curiosity doesn’t seem enough. Ok, for education, particularly young kids, I see it. You may want to set up some mismatch of expectations to drive them to want to learn something. But I believe we need more.

Matt Richter, in his well-done L&D conference presentation on motivation, discussed self-determination theory. He had a nice diagram (my revision here) that distinguished various forms of motivation. From amotivated, that is, not, there were levels of external motivation and then internal motivation. The ultimate is what he termed intrinsic motivation, but that’s someone wanting it of their own interest. Short of that, of course, you have incentive-driven behavior (gamification), and then what you’re guilted into (technically termed Introjection), to where you see value in it for yourself (e.g. WIIFM).

While intrinsic motivation, passion, sounds good, I think having someone be passionate about something is a goal too far. Instead, I see our goal as helping people realize that they need it, even if not ‘want’ it. That, to me, is where consequences kick in. If we can show them the consequence of having, or not, the skills, and do this for the right audience and skills, we can at least ensure that they’re in the ‘value’ dimension.

So, my take is that while we should value curiosity, we may not be able to ensure it. And we can ensure that, with good analysis and design, we can at least get them to see the value. That’s my current take after being curious about curiosity. I’d like to hear yours!