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Clark Quinn’s Learnings about Learning

What makes a good book?

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I was in contact with a person about a potential book, and she followed up with an interesting question: what’s the vision I have for publishing? She was looking for what I thought was a good book. Of course, I hadn’t really articulated it! I responded, but thought I should share my thinking with you as well. In particular, to get your thoughts!  So, what makes a good book? (I’m talking non-fiction here, of course.)

My first response was that I like books that take a sensible approach to a subject. That is, they start where the learner is and get them realizing this is an important topic. Then the book walks them through the thinking with models and examples. Ultimately, a book should leave them equipped to do new things. In a sense, it’s the author leading the reader through a narrative that leaves them with a different and valuable view of the world.

I think these books can take different forms. Some shake up your world view with new perspectives, so for example Don Norman‘s Design of Everyday Things or Todd  Rose‘s The End of Average. Another types are  ones that provide deep coverage of an important topic, such as Patti Shank‘s  Write Better Multiple-Choice Questions.  A third type are ones that lead you through a process, such as Cathy Moore‘s Map It. These are rough characterizations, that may not be mutually exclusive, but each can be done to fit the description above.

To me the necessary elements are that it’s readable, authoritative, and worthwhile. That is, first there’s a narrative flow that makes it easy to process. For instance, Annie Murphy Paul’s The Extended Mind takes a journalistic approach to important phenomena.  Also, a book needs an evidence-base, grounding in documented experience and/or science. It can re-spin topics (I’m thinking here about Lisa Feldman Barrett’s  How Emotions Are Made), but must have a viable reinterpretation. Finally, it has to be something that’s worth covering. That may differ by reader, but it has to be applicable to  a field. You should leave with a new perspective and potentially new capabilities.

That’s what came off the top of my head. What am I missing in what makes a good book?

The Performance Ecosystem and L&D

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On LinkedIn recently, a survey in a post asked whether L&D should simply become performance consulting (Y/N). In the ensuing discussion, a comment was made that the binary discussion was flawed, and that a richer picture was possible. I was extremely pleased when she referred to my  Revolutionize Learning & Development book, and posted a diagram from it. I backed her comment, but it occurs to me that there’s more here, and of course I have a connection. So here’re some thoughts on the Performance Ecosystem and L&D.

To start, she cited how I wanted to move to Performance and Development. Indeed, I’ve posted about it, and included a diagram. In it, performance consulting  is represented, but as she noticed, there’s more. I think performance consulting is great, but…it’s not everything. To me, it only addresses the ‘optimal execution’ side of the picture, and ignores the ‘continual innovation’ opportunity.

To be fair, suggesting that L&D take responsibility for informal learning could be considered a stretch. My argument is simply that informal learning has practices and policies that can optimize outcomes,  and that it’s a necessary component of success going forward. (I note that problem-solving, design, research, and innovation all start without a known answer, so they’re learning too!) It’s not necessarily L&D’s role,  but who else (should) know more about learning?

So, innovation is an opportunity. A big one, I suggest. It’s a chance to move to the most valuable role in the organization, going forward. Orgs  need to innovate, and facilitating the best innovation is going to be a critical role. Why  not L&D? Yes, we have to get out of our comfort zone, start working with other business units, and most importantly know learning. So? We should anyway!

The infrastructure necessary is what I call the performance ecosystem. It’s about formal learning, but also more. That includes social, and information and learning resources. It includes facilitation as well as performance interventions. It’s about technology, but how to use it in ways that align with our brains.

The interesting issue for me is how to awaken this awareness. I  suggest  mobile is a gateway to the appropriate thinking. I wrote about mobile before writing the Revolution book (as my then-publisher required), but even there I laid out the case how mobile was not (just) about formal learning. Indeed, when you look at the way people use mobile, it’s very different. It’s also a digital platform, which means that it supports multiple outcomes.

Thus, mobile thinking is a way to break through the mindset of courses, and start looking at the bigger picture of technology supporting how we think, work, and learn to the success of our organizations. Which is why I’m happy to say that I’ll again be running the mobile course with Allen Academy, starting next week. Through 18 Jan, they’re offering this as a two-fer, so you get both the mobile and the learning science course for one low price! Together, you’re addressing my silly clip about L&D, both doing courses well  and going beyond them.

If you want to get your mind around the performance ecosystem and L&D, I suggest that mobile learning is a effective vehicle. You get both some deep advice about mobile, but it also generalizes to digital technology overall. The course itself looks at formal learning, performance support, informal learning, and more, as well as strategic issues. Coupled with learning science, this is a real grounding in the most important opportunities and necessities facing L&D today. Whether you call it P&D or L&D, these are core concepts. Hope to see you there!

 

Relevant and anchored

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In reviewing my forthcoming book on Make It Meaningful, I’m poring over my Education -Engagment Alignment (EEA). I’m rewriting part to revisit it. Which I’ve done, but in doing so I had a revelation. I’ve maintained that they’re independent elements. However, I now see Relevant and Anchored as complementary components.

‘Anchored’, in my terminology, is ensuring the learning outcome meets a real need. It’s about the relationship between the learning objective and the performance gap. If you’re trying to get better at something, for instance, the objective is specifically related. If you’re learning about dealing with customer objections, you’ve got a specific objective to use a particular approach. It is not  ‘understand’ but ‘do’. You’re not anchoring if your root cause of the performance gap isn’t a lack of skill. If the learning covers information that’s ‘nice to know’, you’re not anchored. This is determined, by the way, by a performance consulting process.

‘Relevant’, again the way I term it, is about whether the learner  cares about that learning objective. If learners don’t care about being a repair tech, having an objective about the problem-solving process can’t matter. This is something we should design into the experience. That is, we should be helping learners ‘get’ that the consequences of acquiring this skill matter to them. We can use curiosity, or consequences, or…but we should  not leave it to chance!

Using the usual present/absent two-factor diagram, it looks like this:

That is, if you have neither the effort is worthless. Which is like a lot of what we see! When you’re anchoring, but not being relevant, the solution is likely to be moderately effective (tho’ not as much as it could be). People stay away if possible! If it’s relevant but not anchored, it’ll be engaging, but not effective and not meaningful. This is the typical tarted up stuff, aka well-produced but not well-designed and produced. However, if you get both in there, you’ve truly made it meaningful.

I suggest you want relevant  and anchored. If we’re putting in the effort, we should be aligning both. I suggest LXD means the elegant integration of learning science with engagement. It sticks better!  We know how to do this, reliably and repeatedly. Our learning doesn’t have to be dull nor ineffective, and we owe our learners this.

The case for good timekeeping

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It occurs to me that maybe not everyone has the same view of timekeeping that I do. So I thought I’d make the case for good timekeeping. To me, it’s about  coping with change.

To me, it starts with respect. This includes respect for the audience, the speaker, topic, and context. There are times when timekeeping  should be lax, I believe. My first take is that the defining circumstances are when there are no people involved who aren’t already part of it, there’s not a fixed time agenda, speaker times aren’t set, and the outcome is more important than punctuality.. In other words, rare for a public event.

When an event is public, there tend to be some other constraints. Most importantly, there’s liable to be a schedule. People need to know when to arrive. If it’s a more than one event in the schedule, extending beyond 1 hour, and the audience is diverse (e.g. not just one company), time becomes increasingly important.

Why should we care? Back to the starting point, people might be coming in to see someone in particular. If the schedule isn’t adhered to, folks who were counting on a particular time could be disappointed. If there’s a start and end time, and block, speakers further down the agenda could be impacted if someone runs long. Neither is fair.

I have experienced folks who seem to be unaware of time. In my personal experience as a speaker, I was on a joint presentation where the leadoff presenter seemed to forget that there was anyone else on the agenda! He was gracious once it was pointed out, but it was uncomfortable for me to have to break in and remind him. I’ve also seen people unaware that they were running long, and others unable to amend their presentation on the fly when they  did become aware. I’ve literally seen someone have to stop where they are instead of finding a way to wrap up!

Having had early experience  being  a moderator, after being the victim of such sessions, I made a commitment (in line with the event organizer’s intent) to be rigorous. I’ve now no qualms about, after giving fair warning, stopping someone who hasn’t maintained control. To the contrary of a possible position, I think it’s rude  not to! It’s the speaker’s fault, no one else’s. They aren’t being professional and respectful of the audience and the other speakers. That also includes getting out of the way in a timely manner if it’s a scheduled room, leaving time for the next person to set up.

So my guidelines for timekeeping:

  1. Designate someone as the timekeeper; there can’t be a question over who’s job it is.
  2. Warn speakers ahead of time about the rigor and practices. No excuses!
  3. Have a practice for signaling if things are getting close, e.g. signs for # of mins left, colored lights, messages in chat (tho’ some people seem unable to process them; beware), what have you.
  4. As a presenter, if you don’t have a good basis for assessing your likely length (e.g. I’m about a slide a minute, though with some quick builds it can be faster), practice and check your timing! Realize that live it’s likely to go a bit longer than your practice. Trim if necessary.
  5. Also, have enough awareness of your material that you can adapt on the fly. Sometimes other things happen (once the power went out in a presentation), and you have to adjust.
  6. Be firm; interrupt and stop speakers when it’s time.

That’s off the top of my head; I’m sure there are more comprehensive and thorough lists. My point is to be aware, and prepared. As a speaker, I appreciate it. As an audience member as well. That’s my case for good timekeeping.  What do you think?

Coping with change

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It’s an  interesting  time for Quinnovation. New things are afoot business wise, and some personal changes are underway as well. All end up being natural and/or for the good, but…seldom are things as easy as you’d hope and expect. So here are some reflections on coping with change.

First, there are some changes afoot for Quinnovation. If all comes together as planned, there’ll be some updates come the new year. Yet these changes, welcomed as they are, will require me to adopt some new work practices. For instance, my attempts at project management will need to become more effective. I’ve been working on it, but I need to instill some new habits. I’m putting in place some steps, but…not everything works as well as you’d hope. Useful watchwords here are concepts like acceptance and agility.

Which is also true for some expected, but significant personal things. Of course, these are more complicated. They entail large bureaucracies, not just leveraging interpersonal relationships with the principals. Thus, you run into all the flaws of complicated systems, and things fall through the cracks. They’re also largely immovable objects, so remedying problems is an exercise in calm. Watchwords here might be patience and persistence.

Of course, some are just new events in familiar guises, such as new clients, e.g. Quinnovation as usual. Here the mechanisms are familiar, but details are different. This requires reliance on updating familiar patterns to new circumstances. Useful watchwords here are adaptation and execution.

I’m reminded of April Rinne’s Flux, which I recently reviewed. It’s a good time for me to review her 8 superpowers for coping with change. I’m positive and committed, but I also have to acknowledge the shift from my comfort zone. However, that’s what learning’s all about, right? It’s partly formal and partly informal learning, yet this is what I  do. So here’s to more learning!

Beyond Industrial Age Thinking

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I’ve long maintained that our organizational practices are too often misaligned with how our brains really work. I’ve attributed that to a legacy from previous eras. Yet, I realize that there may be another legacy, a cognitive one. Here I’ll suggest we need to move beyond Industrial Age thinking.

The premise comes from business. We transitioned from a largely agricultural economy to a manufacturing economy, of goods and services. Factories got economic advantage from scale. We also essentially treated people as parts of the machine. Taylorism, aka scientific management, looked at how much a person could produce if they were working as efficiently as possible, without damage. So few were educated, and we didn’t have sufficiently sophisticated mechanisms. Times change, and we’re now in an information age. Yet, a number of our approaches are still based upon industrial approaches. We’re living on a legacy.

Now I’m taking this is to our models of mind. The cognitive approach is certainly more recent than the Industrial Age, but it carries its own legacies. We regularly take technology as metaphors for mind. Before the digital computer, for instance, telephone switching was briefly used as a model. The advent of the digital computer, a general purpose information system, is a natural next step. We’re information processing machines, so aren’t we like computers?

It turns out, we’re not. There’s considerable evidence that we are not formal, logical, reasoning machines. In fact, we do well what it’s hard to get computers to do, and vice-versa. We struggle to remember large quantities of data, or abstract and arbitrary information, and to remember it verbatim. Yet we also are good at pattern-matching and meaning-making (sometimes  too good; *cough* conspiracy theories *cough*). Computers are the opposite. They can remember large quantities of information accurately, but struggle to do meaning-making.

My concern is that we’re still carrying a legacy of formal reasoning. That is, the notion that we can do it all in our heads, alone, continues though it’s been proven inaccurate. We make inferences and take actions based upon this assumption, perhaps not even consciously!

How else to explain, for instance, the continuing prevalence of information presentation under the guise of training? I suggest there’s a lingering belief that if we present information to people, they’ll logically change their behavior to accommodate. Information dump and  knowledge test are a natural consequence of this perspective. Yet, this doesn’t lead to learning!

When we look at how we really perform, we recognize that we’re contextually-influenced, and tied to previous experience. If we want to do things differently, we have to  practice doing it differently. We can provide information (specifically mental models, examples, and feedback) to facilitate both initial acquisition and continual improvement, but we can’t just present information.

If we want to truly apply learning science to the design of instruction, we have to understand our brains. In reality, not outdated metaphors. That’s the opportunity, and truly the necessity. We need to move beyond Industrial Age thinking, and incorporate post-cognitive perspectives. To the extent we do, we stand to benefit.

Quip: Systematic Creativity

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I’ve documented some  quips in the past, but apparently not this one yet. Prompted by a nice article by Connie Malamed on creativity, I’m reminded of a saying, and the underlying thinking. Here’s both the quip and some more on systematic creativity. First, the quip:

Systematic creativity is  not an oxymoron!

In her article, Connie talks about what creativity is, why it’s important, and then about steps you can take to increase it. I want to dig a wee bit further into the cognitive and formal aspects of this to backstop her points. (Also, of course, to make the point that a cognitive perspective provides important insight.)

As background, I’ve been focused on creating learning experiences. This naturally includes cognition as the basis for learning, experiences,  and design. So I’ve taken eclectic investigations on all three. For instruction, I continue to track for insights from behavioral, social, cognitive, post-cognitive, even  machine learning. On the engagement side, I continue to explore games, drama, fiction, UI/UX, roleplay, ‘flow’, and more. Similarly, for design my explorations include architecture, software engineering, graphic, product, information, and more.

One of the interesting areas comes from computer science, searching through problem-spaces for solutions. If we think of the solution set as a space, some solutions are better than others. It may not be a smooth continuum, but instead we might have local maxima that are ‘ok’, but there’s another elsewhere that’s better. If we are too lax in our search, we might only find the local maxima. However, there are ways to increase the chances of exploring a broader space, making a more global search. (Of course, this can be multidimensional.)

Practically, this includes several possibilities. For one, having a diverse team increases the likelihood that we’ll be exploring more broadly. (On the flip side, having folks who all think alike mean all but one are redundant. ;). For another, brainstorming properly keeps the group from prematurely converging. We can use lateral random prompts to push us to other areas. And so on. I wrote a series of four posts about design that included a suite of heuristics to increase the likelihood of finding a good solution. Connie’s suggestions do likewise.

I also suppose this is a mental model that we can use to help think about designing. Mental models are bases for predictions and decisions. In this case, having the mental model can assist in thinking through practices that are liable to generate better design practices. How do we keep from staying localized? How do we explore the solution space in a manner that goes broad, but not exhaustively (in general, we’re designing under time and cost constraints).

Creativity is the flip side of innovation. It takes the former to successfully execute on the latter. It’s a probabilistic game, but we can increase our odds by certain practices that emerge from research, theory, and practice. We also want to include emotion in the picture as well, in our design practices as well as in our solutions. When we do, we’re more likely to explore the space effectively, and increase our chances for the best solution. That’s a worthwhile endeavor, I’ll suggest. What are your systematic creativity approaches?

 

 

 

Where’s Clark This Time?

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Already this year I’ve done, in addition to podcasts and webinars, The L&D Conference, ATD ICE, and DevLearn. What else? Coming up before the end of the year are a couple more things. So here’s “where’s Clark this time?”.

  • First up is the ATD Core 4 conference in Nashville Nov 15 & 16. There’s a real all star lineup in the concurrent sessions. I’ll be speaking on learning science, of course. This event is in person (with masks).
  • I’m also part of the Symposium on the Economics of Ignorance on 30 November. I’ll be talking about myths here with Matt Richter, but the overall premise is interesting in several ways. One is considering what ignorance costs us!  The other is the approach of interviewing experts to to generate actionable ideas. Virtual.
  • Then, on 1 Dec, I’ll be starting my ‘Make It Meaningful’ workshop with the Learning Development Accelerator. I think this is the missing element in our design, and I’ve spent the past 1.5 year getting it designed. (Or the past 40, if you consider my work understanding engagement from when my career got started by designing learning games!). Emotions matter in learning, and we can systematically take our learning from didactic to transformational. Online.
  • Finally, I’ll be the opening keynote for ATD’s Japan Summit  Dec 6-10, talking about new cognition and organizational implications. Virtual, at least for me!

Those are the biggies, there’s at least one more webinar on the calendar this year too. All but Core 4 are virtual, so it’s easy to attend (though the timing of the Japan Summit will be awkward!). If you’ll be at any of these, say ‘hi’! (I’m an introvert and a ham; I may appear social when presenting, but normally I’m not aloof, just shy. At least until I get to know you. ;) So the answer to “Where’s Clark this time” is online and in person.

Aligning and enabling transformation

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In what was my last Quinnsights column for Learning Solutions, I wrote about how the transformation wasn’t (or shouldn’t) be digital. In many ways we aren’t aligned with what’s best for our thinking. Thus,  digitizing existing approaches doesn’t make sense. Instead, we should be fixing our organizational alignment first,  then  digitizing. The opportunity is in aligning  and enabling transformation.

First, we should be looking at  all  the levels of organizational alignment. At the individual level we can be doing things like implementing federated search, to support individual learning. This should be coupled with providing development of writing good search strings and evaluating search outcomes. This also means curating a suite of resources aligned with learning directions and future opportunities. The point being that we should be supporting evidence-based methods for individual development, then supporting digitally. For instance, supporting learning-to-learn skills. Taking them for granted is a mistake! It’s also about ongoing support for development, e.g. coaching. Good practices help, and tools that document approaches and outcomes can assist.

At the group level, there are again ways in which we can be fostering effectiveness. This includes having good collaboration tools, and assisting people in using them well. It can also be about policies that make ‘show your work’ safe. Then you can augment with ‘show your work’ tool. Again, having the right practices and policies makes the digital transformation investment more valuable. You could pick the wrong tools if you’re instituting the old ways instead of doing the process work first.

This holds true at the organizational level as well, of course. The policies and practices cross the organization. Thus, what works for teams comes from an organizational focus on learning. Then, the digital investments are focused on the most optimal outcomes. The alternative, digitizing unaligned practices, can only hinder improvement to be a successful organization.

There are a lot of myths about what works. This includes learning myths, but also bad HR practices. Many stem from maintaining approaches that are carryovers from industrial age business. Instead, we should be leveraging our knowledge of thinking to be strategic. L&D can be critically contributing to organizational success! Or not. There’s a big opportunity to shift practices in a positive direction, with upsides for outcomes. However, it takes the understanding and the will. What will you do?

This is related to the talk I’ll be giving as the opening keynote for the ATD Japan Summit in December (though I’m filming it for virtual delivery). I get my thinking done here first ;).  

Tech Thoughts

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I’m late with a post this week, owing to several factors, all relating to technology. I hadn’t quite pulled together a complete lesson, but by writing down these tech thoughts, I got there. (A further argument for the benefits of reflection.)

It started with upgrading our phones. We needed to (I tend to hand mine down, but really we both needed an upgrade this time). Of course there are hiccups, particularly since m’lady’s was so old that it couldn’t do the amazing thing mine had done. What happened with mine was that you just put the old phone and the new phone together and the new one just sucks the data off the old one and then the old one asks if you want to wipe it clean!  That’s some serious user experience. Something we should look more to in our LXD, so that we’re doing proper backwards design and we have the right combination of tools and learning to make performance relatively effortless.

Then another thing was quite interesting. An individual linked to me on the basis of a citation in a book. I didn’t know the book, so he sent me a picture of the page. He also asked if I could read Dutch. Sadly, no. However, I had recently upgraded my OS, and when I opened the picture, I noticed I could click on the text. Of. The. Picture!  I could select all the text (my OS was doing OCR on the picture live!), and then I could paste into Google Translate (another amazing feat) and it recognized it as Dutch and translated it into English. Whoa!

On the flip side, owing to the unusually heavy rain (for California), first our internet went out, and then the power. Fortunately both were working by the next morning. However, after that my backup drives kept dismounting and I couldn’t execute a backup reliably. I thought it might be the laptop, and I did a couple of increasingly difficult remedial measures. Nope. Had the drives been damaged by the power outage? Power outages aren’t quite new around here (we’re a bit up a hillside, and squirrels regularly blow the transformer), yet it hadn’t happened before.

Then I was on a Zoom call, and I started having hiccups in the microphone and camera. Even typing. What? When I switched to the laptop camera, it was all good.  All the things, drives, microphone, external monitor, are connected by a external hub. The hub had gone wonky! Instead of having to replace drives, I picked up a new hub last nite, and all’s good now. Phew!

I guess my take home tech thoughts is that we’re making true a promise I’ve mentioned when talking mobile: we really do have magic. (Asimov famously said any truly advanced technology is indistinguishable from magic.) We can do magical things like talk at distance, have demons do tasks on our behalf (picture text transcribing and translation), etc. On the other hand, when it doesn’t work, it can be hard to identify the problem!  Overall, it’s a win. Well, when it’s designed right! Which involves testing and tuning. As Dion Hinchcliffe put it: “Seamless #cx is now table stakes.” So let’s get designing, testing, and tuning, and make magical experiences.