There’ve been a recent discussions about misinformation. One question is, what does it hurt? When you consider myths, superstitions, and misconceptions (the breakdown in my book on L&D problems), what can arise? Let’s talk about the damage done.

So, let’s start with myths. These, I claim, are things that have been shown not to have value by empirical research. There are studies that have examined these claims, and found them to not have data to support them. For instance, accommodating learning styles is a waste. Yes, we know people differ in learning, but we don’t have a reliable base. Moreover, people’s choices to work for (or against) their style don’t make a difference in their learning. Some of the instruments are theoretically flawed as well as psychometrically invalid.

What’s the harm? I’ll suggest several ways in which myths harm us. For one, they can cause people to spend resources (money & time)  addressing them that won’t have an impact. It’s a waste! We can also characterize people in ways that limit them; for instance if they think they learn in a particular way, they may avoid a topic or invest effort in an inappropriate way to learn it. Investing in unproven approaches also perpetuates them, propagating the beliefs to others.

Superstitions, as I define them, are beliefs nobody would claim to believe, yet somehow persist in our practices. For instance, few will claim to believe that telling is sufficient to achieve behavior change. Yet, we continue to see information presentation and knowledge test, such as “awareness” training. Why? This is a waste of effort. There aren’t outcomes from these approaches. Typically, they are legacies of expectations from previous decades, yet business practices haven’t been updated. Still, to the extent that we continue these practices, even while decrying them, we’re again wasting time and money. Maybe we tick boxes and make people happy, but we can (and should) do better.

The final category is misconceptions. These are beliefs that some hold, and others decry. They aren’t invalid, but they only make sense in certain circumstances. I suggest that those who defy them don’t have the need, and those who tout them are in the appropriate circumstance. What matters is understanding when they make sense, and then using them, or not, appropriately. If you avoid them when they make sense, you may make your life harder. If you adopt them when they’re not appropriate,  you could make mistakes or waste money.

At the end of the day, the damage done is the cost of wasting money and time. Understanding the choices is critical. To do so best, you can and should understand the underlying cognitive and learning sciences. You should also track the recognized translators of research into practice who can guide you without you having to read the original academese. To be professional in our practice, we need to know and use what’s known, and avoid what’s dubious. Please!

I’ve been reading Amy Edmondson’s Right Kind of Wrong, and I have to say it’s very worthwhile. I’ve been a fan of hers since her book Teaming introduced me to the notion of psychological safety. It’s an element I’ve incorporated into my thinking about innovation and learning. This new book talks about how we have beliefs about making mistakes, and how we can, and should, be failing right.

In this book, she uses examples to vibrantly talk about failure, and how it’s an important part of life. She goes on to talk about different types of failure, and the situations they can occur in, creating a matrix. This allows us to look at when and how to fail. Along the way, she talks about self, situational, and systemic failure.

One of the important takeaways, which echoes a point Donald Norman made in Design of Everyday Things, is that failure may not be our fault! Too often, bad design allows failure, instead of preventing it. Moreover, she makes the point that we have a bad attitude towards failure, not recognizing that it’s not only part of life, but can be valuable!  When we make a mistake, and reflect, we can learn.

Of course, there are simple mistakes. I note that there’s some randomness in our architecture, e.g. To Err is Human. But also, there can be factors we haven’t accounted for, like bad design, or things out of our control. At the most significant level, she talks about complex systems, and how they can react in unpredictable ways. Along the way, what counts as ‘intelligent’ failure is made clear. Some fails are smart, others are not justified.

She also talks about how experiments are necessary to understand new domains. This is, in my mind, about innovation. She also gives prescriptions, at both the personal and org level. Dr. Edmondson talks about the value of persistence, taking ‘good enough’, but also not taking it too personally. She also talks about sharing, as Jane Bozarth would say: Show Your Work. This is for both calling out problems and sharing failure.

Along with a minor quibble about the order in which she presents a couple things, a more prominent miss, to me, is a small shift in focus. She talks about celebrating the ‘pivot’, where you change direction. However,  I’d more specifically celebrate the learning. That is, whether we pivot or not, we say that learning something is good. Of course, I’m biased towards learning, but I’d rather celebrate the learning. Yes, we possibly would do something different, and celebrating action is good, but sharing the learning means others can learn from it too. Maybe I’m being too pedantic.

Still, this is another in her series of books exploring organizational improvement and putting useful tools into our hands. We can, and should expect to not get everything right all the time, and instead should be focusing on failing right. Recommended.

In my regular questing, one of the phenomena I continue to explore is design. Investigating, for instance, reveals that, contrary to recommendations, designers approach practice more pragmatically. That’s something I’ve been experiencing both in my work with clients and recent endeavors. So, reflecting, are and should folks be diving or surfacing?

The original issue is how designers design. If you look at recommendations, they typically recommend starting at the top level conceptualization and work down, such as Jesse James Garrett’s Information Architecture approach (PDF of the Elements of User Experience; note that he puts the highest level of conceptualization at the bottom and argues to work up). Empirically, however, designers switch between top-down and bottom-up. What do I do?

Well, it of course depends on the project. Many times (and, ideally), I’m brought in early, to help conceptualize the strategy, leveraging learning science, design, organizational context, and more. I tend to lead the project’s top-level description, creating a ‘blueprint’ of where to go. From there, more pragmatic approaches make sense (e.g. bringing in developers). Then, I’m checking on progress, not doing the implementation. I suppose that’s like an architect. That is, my role is to stay at the top-level.

In other instances, I’m doing more. I frequently collaborate with the team to develop a solution. Or, sometimes, I get concrete to help communicate the vision that the blueprint documents. Which,  in working with an unfamiliar team, isn’t unusual. That ‘telepathy’ comes with getting to know folks ;).

In those other instances, I too will find out that pragmatic constraints influence the overarching conceptualization, and work back up to see how the guidelines need to be adapted to account for the particular instance. Or we need to deconnect from the details to remember what our original objective is. This isn’t a problem! In general, we should expect that ongoing development unearths realities that weren’t visible from above, and vice versa. We may have good general principles, (e.g. from learning science), but then we need to adapt them to our circumstances, which are unlikely to exactly match. In general, we need to abstract the best principles, and then de- and re-contextualize.

I find that while it’s harder work to wrestle with the details (more pay for IDs! ;), it’s very worthwhile. What’s developed is better as a result of testing and refining. In fact, this is a good argument about why we should iterate (and build it into our timelines and budgets). It’s hubris to assume that ‘if we build it, it is good’. So, let’s not assume we can either be diving or surfacing, but instead recognize we should cycle between them. Start at the top and work down, but then regularly check back up too!

Someone reached out to me for a case study on addressing a workplace problem. I was willing, but there’s a small problem; I’ve never had to address a workplace learning problem. At least, in the way most people expect. Instead, I provide an outside perspective. What’s that mean?

So, first of all, I don’t come from an instructional design (ID) background. I did get some exposure to educational approaches when I designed my own undergraduate degree in Computer-Based Education. Yet, there weren’t any ID courses where I was a student. As a graduate student, I took psychology courses on learning. I also read Reigeluth’s survey of ID design approaches. Further, I got a chance to interview the gracious and wise David Merrill. But, again, no formal ID courses were on tap.

On the flip side, I was in a vibrant program that was developing a cognitive science degree, and read everything on learning I could find: behavioral, cognitive, social, neural, even machine learning! I was in my post-doc as they were forming the learning science approach, too, and I was at a relevant institution. Still, no ID. So, I do have deep learning roots, just not ID.

Then, after the post-doc, I taught. That is, practiced learning design, and continued reading and talking ID, and attending relevant conferences. Just not a formal ID course. Then I joined a small startup to design an adaptive learning platform, and then started consulting, but never a workplace learning role inwardly faced.

What that means is that I bring an ‘outside’ perspective to L&D. Which, I think, isn’t a bad thing. I’ve helped firms meet realistic goals in innovative ways, courtesy of not having my thinking pre-constrained. I’ve been able to interpret learning science in practical terms, and infer what ID says (also, I’ve read it and reflected in context on it). So, I’ve talked L&D design, and ID improvements, but from the view of an outsider.

Many times outsiders can bring new perspectives. And, they can be ignorant of all the contextual details. Thus, it’s really important to ask and establish those constraints, and then to be sensitive to the ones that they didn’t mention. (One of the benefits of the court jester was to reframe things in ways that showed the humor in the hidden assumptions.) Still, I’m not apologizing. I think the background I’ve acquired is useful to people who need to meet real goals, and have a decent track record in doing so. I welcome your thoughts on whether an outside perspective is of benefit.