Archives for May 2024

My Themes

28 May 2024 by Clark Leave a Comment

While there’s a high correspondence between my books and what I believe, it’s not one to one. While there’s overlap, there’s also unique (outsider?) perspectives. So as much for me as you, here’re my themes. It’s about applying what we know about cognition and learning. That also includes the emotional side. Moreover, we also need to apply it to the design process. That is, we, as designers, are applying, but also are subject to, what’s known about how we think, work, and learn. That’s led to a variety of things that are covered here.

It starts with a core focus on learning. Which starts with the core of cognition, the human information processing loop, but goes beyond. I think that core, by the way, is a critical thing that really everyone who designs for people (and that’s everyone) should know. (Made a video freely available to that end.) The phenomena that arise from and augment that architecture play a role here. It covers, by the way, material in two of my books: the learning science one and my myths one. It’s also the basis for my participation in the Serious eLearning Manifesto. It’s about us applying, correctly, what’s known about creating learning experiences that lead to real outcomes. I still think my focus on activity-based learning is an important way to think about creating experiences.

A complement to that is my focus on engagement in learning. Here I’m reflecting what’s been studied about making experiences engaging, across games, theatre and film, fiction, flow, and more. The first manifestation was in my book on designing serious games, but it’s morphed. My latest book is a complement to the learning science side and as a generalization of those early principles on games. I’ll be talking about this at LXDCon.

However, when we talk about performance, the picture broadens. (A topic I’ll be discussing for Upside Learning.) Marc Rosenberg talked about going beyond (e)learning, and Jay Cross wrote about informal learning. I like to think of an ecosystem approach to meeting the full suite of performance needs. This includes not just courses, but also performance support. However, it also goes further, talking about innovation as well. As I like to say, when you’re doing research, design, trouble-shooting, etc, you don’t know the answer when you begin, so it too is learning. I tried to capture this in my book on where L&D should go.

An older theme, about mobile, is in some sense no longer relevant. Mobile (for corporations and universities) has become ubiquitous and is part of the performance ecosystem. In fact, part of the recognition of the ecosystem perspective came from thinking about mobile with the recognition that it’s least about courses on a phone, and about so much more. The frameworks I created then – augmenting learning, performance support, social/informal, and context-specific – however, strike me as still worthwhile to consider. It’s really about the alignment of technology with our minds, which includes interface design and more.

Thus, implicit in the ecosystem perspective is technology. One thing we lag in is being smart about our systems. While web spinners have been using tagged content and rules, we typically still create experience hard coded in their delivery. We thus neglect content engineering, and similarly content management (e.g. the lifecycle). I was on this theme a number of years ago (content and context), but it’s sadly still relevant. I think the advent of generative AI may get folks to start thinking more about discrete content for adaptive delivery, but I’d still use a different approach to implement.

Again, it’s the application of how we think, work, and learn, to the design of solutions. In my case, for performance outcomes for individuals and organizations. Not sure what my next theme will be (or whether there’ll even be one, these are still all too relevant). I’m not sure this is comprehensive, so hopefully this first stab will give me time to think about it more!

About my books

21 May 2024 by Clark 2 Comments

So, I’ve written about writing books, what makes a good book, and updated on mine (now a bit out of date). I thought it was maybe time to lay out their gestation and raison d’être. (I was also interviewed for a podcast, vidcast really, recently on the four newest, which brought back memories.) So here’re some brief thoughts on my books.

My first book, Engaging Learning came from the fact that a) I’d designed and developed a lot of learning games, and b) had been an academic and reflected and written on the principles and process. Thus, it made sense to write it. Plus, a) I was an independent and it seemed like a good idea, and b) the publisher wanted one (the time was right). In it, I laid out some principles for learning, engagement, and the intersection. Then I laid out a systematic process, and closed with some thoughts on the future. Like all my books, I tried to focus on the cognitive principles and not the technology (which was then and continues to change rapidly). It went out of print, but I got the rights back and have rereleased it (with a new cover) for cheap on Amazon.

I wanted to write what became my fourth book as the next screed. However, my publisher wanted a book on mobile (market timing). Basically, they said I could do the next one if I did this first. I had been involved in mlearning courtesy of Judy Brown and David Metcalfe, but I thought they should write it. Judy declined, and David reminded me that he had written one. Still I and my publisher thought there was room for a different perspective, and I wrote Designing mLearning. I recognized that the way we use mobile doesn’t mesh well with ‘courses on a phone’, and instead framed several categories of how we could use them. I reckon those categories are still relevant as ways to think about technology! Again, republished by me.

Before I could get to the next book, I was asked by one of their other brands if I could write a mobile book for higher education. The original promise was that it’d be just a rewrite of the previous, and we allocated a month. Hah! I did deliver a manuscript, but asked them not to publish it. We agreed to try again, and The Mobile Academy was the result. It looks at different ways mobile can augment university actions, with supporting the classroom as only one facet. This too was out of print but I’ve republished.

Finally, I could write the book I thought the industry needed, Revolutionize Learning & Development. Inspired by Marc Rosenberg’s Beyond eLearning and Jay Cross’s Informal Learning, this book synthesizes a performance and technology-enabled push for an ecosystem perspective. It may have been ahead of its time, but it’s still in print. More importantly, I believe it’s still relevant and even more pressing! Other books have complemented the message, but I still think it’s worth a read. Ok, so I’m biased, but I still hear good feedback ;). My editor suggested ATD as a co-publisher, and I was impressed with their work on marketing (long story).

Based upon the successes of those books (I like to believe), and an obvious need in our field, ATD asked for a book on the myths that plague our industry. Here I thought Will Thalheimer, having started the Debunkers Club, would be a better choice. He, however, declined, thinking it probably wasn’t a good business decision (which is likely true; not much call for keynotes or consulting on myths). So, I researched and wrote Millennials, Goldfish & Other Training Misconceptions. In it, I talked about 16 myths (disproved beliefs), 5 superstitions (things folks won’t admit to but emerge anyways) and 16 misconceptions (love/hate things). For each, I tried to lay out the appeal and the reality. I suggest what to do instead, for the bad practices. For the misconceptions, I try to identify when they make sense. In all cases I didn’t put down exhaustive references, but instead the most indicative. ATD did a great job with the book design, having an artist take my intro comic ideas for each and illustrating them, and making a memorable cover. (They even submitted it to a design competition, where it came close to winning!)

After the success of that tome, ATD came back and wanted a book on learning science. They’d previously asked me to edit the definitive tome, and while it was appealing, I didn’t want to herd cats. Despite their assurances, I declined. This, however, could be my own simple digest, so I agreed. Thus, Learning Science for Instructional Designers emerged. There are other books with different approaches that are good, but I do think I’ve managed to make salient the critical points from learning science that impact our designs. Frankly, I think it goes beyond instructional designers (really, parents, teachers, relatives, mentors and coaches, even yourself are designing instruction), but they convinced me to stick with the title.

Now, I view Learning Experience Design as the elegant integration of learning science with engagement. My learning science book, along with others, does a good job of laying out the first part. But I felt that, other than game design books (including mine!), there wasn’t enough on the engagement side. So, I wanted a complement to that last book (though it can augment others). I wrote Make It Meaningful as that complement. In it, I resurrected the framework from my first book, but use it to go across learning design. (Really, games are just good practice, but there are other elements). I also updated my thinking since then, talking about both the initial hook and maintaining engagement through to the end. I present both principles and practical tips, and talk about the impact on your standard learning elements. In an addition I think is important, I also talk about how to take your usual design process, and incorporate the necessary steps to create experiences, not just instruction. I do want you to create transformational experiences!

So, that’s where I’m at. You can see my recommended readings here (which likely needs an update.) Some times people ask “what’s your next book”, and my true answer at this point is “I don’t know.” Suggestions? Something that I’m qualified to write about, that there’s not already enough out about, and it’s a pressing need? I welcome your thoughts!

An outside perspective

14 May 2024 by Clark 1 Comment

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.

AI as a System

7 May 2024 by Clark Leave a Comment

At the recent Learning Guild‘s Learning & HR Tech Solutions conference, the hot topic was AI. To the point where I was thinking we need a ‘contrarian’ AI event! Not that I’m against AI (I mean, I’ve been an AI groupie for literal decades), I think it’s got well-documented upsides. (And downsides.) Just right now, however, I feel that there’s too much hype, and I’m waiting for the trough of disillusionment to hit, ala the Gartner hype cycle. In the meantime, though, I really liked what Markus Bernhardt was saying in his session. It’s about viewing AI as a system, though of course I had a pedantic update to it ;).

So, Markus’ point was that we should separate out data from the processing method. Markus presented a simple model to think about AI that I liked. In it, he proposed three pieces that I paraphrase:

the information you use as your basis
the process you use with the information
and the output you achieve

Of course, I had a quibble, and ended up diagramming my own way of thinking about it. Really, it only adds one thing to his model, an input! Why?

So I have the AI system containing the process and data it operates on. I like that separation, because you can use the same process on other data, or vice versa. As the opening keynote speaker, Maurice Conti, pointed out, the AI’s not biased, the data is. Having good data is important. As is having the right process to achieve the results you want (that is, a good match between problem and process; the results are the results ;). Are you generating or discriminating, for instance? Then Markus said you get the output, which could be prose, and image, a decision, …

However, I felt that it’s important to also talk about the input. What you input determines the output. With different queries, for instance, you can get different results. That’s what prompt engineering is all about! Moreover, your output can then be part of the input in an iterative step (particularly if your system retains some history). Thus, thinking about the input separately is, to me, a useful conceptual extension.

It may seem a trivial addition, but I think it helps to think about how to design inputs. Just as we align process with data for task, we need to make sure that the input matches to the process to get the best output. So, maybe I’m overcomplicating thinking about AI as a system. What say you?