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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?

 

 

 

I recently mentioned that one of the problems with research is that things are more interconnected than we think. This is particularly true with cognitive research. While we can make distinctions that simplify things in useful ways (e.g. the human information processing system model*), the underlying picture is of a more interactive system.  Which underpins why it makes sense to talk about Learning Experience Design (LXD) and not just instructional design. We need to accommodate complexity in learning design.  (* Which I talk about in Chapter 2 of my learning science book, and in my workshops on the same topic through the Allen Academy.)

We’re recognizing that the our cognition is more than just in our head. Marcia Conner, in her book  Learn More Now  mentioned how neuropeptides passed information around the body. Similarly, Annie Murphy Paul’s  The Extended Mind talks about moving cognition (and learning) into the world. In my Make It Meaningful workshops (online or F2F at DevLearn 19 Oct), I focus on how to address the emotional component of learning. In short, learning is about more than just information dump and knowledge test.

Scientifically, we’re finding there are lots of complex interactions between the current context, our prior experience, and our cognitive architecture. We’re much more ‘situated’ in the moment than the rational beings we want to believe. Behavioral economics and Daniel Kahneman’s research have made this abundantly clear. We try to avoid the hard mental work using shortcuts that work sometimes, but not others. (Understanding when is an important component of this).

We get good traction from learning science and instructional design approaches, for sure. There are good prescriptions (that we often ignore, for reasons above) about what to do and how. So, we should follow them. However, we need more. Which is why I tout LXD  Strategy! We need to account for complexity in learning design approaches.

For one, our design processes need to be iterative. We’ll make our best first guess, but it won’t be right, and we’ll need to tune. The incorporation of agile approaches, whether SAM or LLAMA or even just iterative ADDIE, reflects this. We need to evaluate and refine our designs to match the fact that our audience is more complex than we thought.

Our design also needs to think about the emotional experience as well as the cognitive experience. We want our design processes to systematically incorporate humor, safety, motivation, and more. Have we tuned the challenge enough, and how will we know?  Have we appropriately incorporated story? Are our graphics aligned or adding to cognitive load? There are lots of elements that factor in.

Our design process has to accommodate SMEs who literally can’t access what they do. Also learner interests, not just knowledge. We need to know what interim deliverables, processes for evaluation, times when we shouldn’t be working solo, and tools we need. Most importantly, we have to do this in a practical way, under real-world resource constraints.

Which is why we need to address this strategically. Too many design processes are carry-over from industrial approaches: one person, one tool, and a waterfall process. We need to do better. There’s complexity in learning design, both on the part of our learners, and ourselves as designers. Leveraging what we know about cognitive science can provide us with structures and approaches that accommodate these factors. That’s only true, however, if we are aware and actively address it. I’m happy to help, but can only do so if you reach out. (You know how to find me. ;) Here’s to effective and engaging  learning!

I’ve argued before about the need for evaluation in our work. This occurs summatively, where we’re looking beyond smile sheets to actually determine the impact of our efforts. However, it also should work formatively, where we’re seeing if we’re getting closer. Yet there are some ways in which we go off track. So I want to talk about iterating and evaluating our learning initiatives.

Let’s start by talking about our design processes. The 800 lb gorilla of ADDIE has shifted from a water flow model to a more iterative approach. Yet it still brings baggage. Of late, more agile and iterative approaches have emerged, not least Michael Allen’s SAM and Megan Torrance’s LLAMA. Agile approaches, where we’re exploring, make more sense when designing for people, with their inherent complexity.

Agile approaches work on the basis of creating, basically, Minimum Viable Products, and then iterating.  We evaluate each iteration. That is, we check to see what need to be improved, and what is good enough. However,  when are we done?

In my workshops, when talking about iteration, I like to ask the audience this question. Frequently, the answer is “when we run out of time and money”. That’s an understandable answer, but I maintain it’s the  wrong answer.

If we iterate until we run out of time and money, we don’t know that we’ve actually met our goals. As I explained about social media metrics, but applies here too, you  should be iterating until you achieve the metrics you’ve set. That means you know what you’re trying to do!

Which requires, of course, that you set metrics about what your solution should achieve. That could include usability and engagement (which come before and after, respectively), but most critically ‘impact’. Is this learning initiative solving the problem we’re designing it to achieve?  Which also means you need to have a discussion of why you’re building it, and how you know it’s working.

Of course, if you’re running out of time and money faster than you’re getting close to your goal, you have to decide whether to relax your standards, or apply for more resources, or abandon your work, or…but at least you’re doing so consciously. Yet this is still better than heuristically determining that three iterations is arbitrarily appropriate, for example.

I do recognize that this isn’t our current situation, and changing it isn’t easy. We’re still asked to make slide decks look good, or create a course on X, etc. Ultimately, however, our professionalism will ask us to do better. Be ready. Eventually, your CFO should care about the return on your expenditures, and it’ll be nice to have a real answer. So, iterating and evaluating  should  be your long term approach. Right?

I volunteer for our local Community Emergency Response Team (CERT; and have learned lots of worthwhile things). On a call, our local organizer mentioned that she was leading a section of the train-the-trainers upcoming event, and was dreading trying to make it interesting. Of course I opened my big yap and said that’s something I’m focusing on, and offered to help. She took me up on it, and it was a nice case study in making it meaningful.

Now, I have a claim that you can’t give me a topic that I can’t create a game for. I’m now modifying that to ‘you can’t give me a topic I can’t make meaningful’.  She’d mentioned her topic was emergency preparedness, and while she thought it was a dull topic, I was convinced we could do it. I mentioned that the key was making it visceral.

I had personal experience; last summer our neighbor was spreading the rumor that we were going to have to evacuate owing to a fire over the ridge. (Turns out, my neighbor was wrong.) I started running around gathering sleeping bags, coats, dog crate, etc. Clearly, I was thinking about shelter. When I texted m’lady, she asked about passports, birth certificates, etc. Doh!

However, even without that personal example, there’s a clear hook. When I mentioned that, she mentioned that when you’re in a panic, your brain shuts down some and it’s really critical to be prepared. However, she mentioned that someone else was taking that bit, and her real topic was different types of disasters. Yet my example had already got her thinking, and she started talking about different people being familiar with an earthquake (here in California).

I thought of how when talking with scattered colleagues, they disclaim about how earthquakes are scary, and I remind them that  every place has its hazards. In the midwest it could be tornados or floods. On the east coast it’s hurricanes. Etc. The point being that everyone has some experience. Tapping into that, talking about consequences, is a great hook.

That’s the point, really. To get people willing to invest in learning, you have to help people see that they  do need it. (Also, that they don’t know it now,  and that this experience will change that.). You need to be engaged in making it meaningful!

Again, in my mind learning experience design (LXD) is about the elegant integration of learning science with engagement. You need to understand both. I’ve got a book and a workshop on learning science, and I’ve a workshop at DevLearn on the engagement side. I’ve also got a forthcoming book and an online workshop coming for more on engagement. Stay tuned!

As has become all too common, someone decided to point me to some posts for their organization. Apparently, interest was sparked by a previous post of mine where I’d complained about  microlearning. While this one  does a (slightly) better job talking about  microlearning, it is riddled with other problems. So here’s yet another post about  more marketing malarkey.

First, I don’t hate microlearning; there are legitimate reasons to keep content small. It can get rid of the bloat that comes from contentitis, for one. There are solid reasons to err on the side of performance support as well. Most importantly, perhaps, is also the benefit of spacing learning to increase the likelihood of it being available. The thing that concerns me is that all these things are different, and take different design approaches.

Others have gone beyond just the two types I mention. One of the posts  cited a colleague’s more nuanced presentation about small content, pointing out four different ways to use microlearning (though interestingly,  five were cited in the referenced presentation). My problem, in this case, wasn’t the push for microlearning (there were some meaningful distinctions, though no actual mention how they require different design). Instead, it was the presence of myths.

One of the two posts opened with this statement: “The appetite of our employees is not the same therefore, we must not provide them the same bland food (for thought).” This seems a bit of a mashup. Our employees aren’t the same, so they need different things? That’s personalization, no? However, the conversation goes on to say: “It‘s time to put together an appetizing platter and create learning opportunities that are useful and valuable.”  Which seems to argue for engagement. Thus, it seems like it’s instead arguing that people need more engaging content. Yes, that’s true too. But what’s that got to do with our employees not having the same appetite? It  seems to be swinging towards the digital native myth, that employees now need more engaging things.

This is bolstered by a later quote: “When training becomes overwhelming and creates stress, a bite-sized approach will encourage learning.” If training becomes overwhelming and stressful, it  does suggest a redesign. However, my inclination would be to suggest that ramping up the WIIFM and engagement are the solution. A bite-sized approach, by itself, isn’t a solution to engagement. Small wrong or dull content isn’t a solution for dull or wrong content.

This gets worse in the other post. There were two things wrong here. The first one is pretty blatant:

There are numerous resources that suggest our attention spans are shrinking. Some might even claim we now have an average attention span of only 8 seconds, which equals that of a goldfish.

There are, of course, no such resources pointed to. Also, the resources that proposed this have been debunked. This is actually the ‘cover story’ myth of my recent book on myths! In it, I point out that the myth about attention span came from a misinterpreted study, and that our cognitive architecture doesn’t change that fast. (With citations.) Using this ‘mythtake’ to justify microlearning is just wrong. We’re segueing into tawdry marketing malarkey here.

This isn’t the only problem with this post, however. A second one emerges when there’s an (unjustified) claim that learning should have 3E’s: Entertaining, Enlightening, and Engaging. I do agree with Engaging (per the title of my first book), however, there’s a problem with it. And the other ones. So, for Entertaining, this is the followup: “advocates the concept of learning through a sequence of smaller, focused modules.” Why is smaller inherently more entertaining? Also, in general, learning doesn’t work as well when it’s just ‘fun’, unless it’s “hard fun”.

Enlightening isn’t any better. I do believe learning should be enlightening, although particularly for organizational learning it should be transformative in terms of enhancing an individual’s ability to  perform. Just being enlightened doesn’t guarantee that. The followup says: “Repetition, practice, and reinforcement can increase knowledge.” Er, yes, but that’s just good design. There’s nothing unique to microlearning about that.

Most importantly, the definition for Engaging is “A program journey can be spaced enough that combats forgetting curve.” That is spacing! Which isn’t a bad thing (see above), but not your typical interpretation of engaging. This is really confused!

Further, I didn’t even need to fully parse these two posts. Even on a superficial examination, they fail the ‘sniff test’. In general, you should be avoiding folks that toss around this sort of fluffy biz buzz, but even more so when they totally confound a reasonable interpretation of these concepts. This is just more marketing malarkey. Caveat emptor.

(Vendors, please please please stop with the under-informed marketing, and present helpful posts. Our industry is already suffering from too many myths. There’s possibly a short-term benefit, however the trend seems to be that people are paying more attention to learning science. Thus, in the long run I reckon it undermines your credibility. While taking them down is fun and hopefully educational, I’d rather be writing about new opportunities, not remedying the old.  If you don’t have enough learning science expertise to do so, I can help: books, workshops, and/or writing and editing services.)