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Clark Quinn’s Learnings about Learning

Archives for November 2021

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 ;).