Instructional design, as is well documented, has it roots in meeting the needs for training in WWII. User experience (UX) came from the Human Computer Interaction (HCI) revolution towards User Centered Design. With a vibrant cross-fertilization of ideas, it’s natural that evolutions in one can influence the other (or not).  It’s worth thinking about the trajectories and the intersections that are the roots of LXD, Learning eXperience Design.

I came from a background of computer science and education. In the job for doing the computer support for the office doing the tutoring I had also engaged in, I saw the possibilities of the intersection. Eager to continue my education, I avidly explored learning and instruction, technology (particularly AI), and design. And the relationships, as well.

Starting with HCI (aka Usability), the lab I was in for grad school was leading the charge. The book User-Centered System Design  was being pulled together as a collection of articles from the visitors who came and gave seminars, and an emergent view was coming. The approaches pulled from a variety of disciplines such as architecture and theater, and focused on elements including participatory design, situated design, and iterative design. All items that now are incorporated in design thinking.

At that time, instructional design was going through some transitions. Charles Reigeluth was pulling together theories in the infamous ‘green book’  Instructional Design Theories and Models.  David Merrill was switching from Component Display Theory to ID2.  And there was a transition from behavioral to cognitive ID.

This was a dynamic time, though there wasn’t as much cross-talk as would’ve made sense. Frankly, I did a lot of my presentations at EdTech conferences on implications from HCI for ID approaches. HCI was going broad in exploring a variety of fields to tap in popular media (a lot was sparked by the excitement around  Pinball Construction Set), and not necessarily finding anything unique in instructional design. And EdTech was playing with trying to map ID approaches to technology environments that were in rapid flux.

These days, LXD has emerged. As an outgrowth of the HCI field, UX emerged with a separate society being created. The principles of UX, as cited above, became of interest to the learning design community. Explorations of efforts from related fields – agile, design thinking, etc, – made the notion of going beyond instructional design appealing.

Thus, thinking about the roots of LXD, it has a place, and is a useful label. It moves thinking away from ‘instruction’ (which I fear makes it all to easy to focus on content presentation). And it brings in the emotional side. Further, I think it also enables thinking about the extended experience, not just ‘the course’.  So I’m still a fan of Learning Experience Design (and now think of myself as an LXD strategist, considering platforms and policies to enable desirable outcomes).

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As a side note, Customer Experience is a similarly new phenomena, that apparently arose on it’s own. And it’s been growing, from a start in post-purchase experience, through Net Promoter Scores and Customer Relationship Management. And it’s a good thing, now including everything from the initial contact to post-purchase satisfaction and everything in between. Further, people are recognizing that a good Employee Experience is a valuable contributor to the ability to deliver Customer Experience. I’m all for that.

As one of the things I talk about, I was exploring the dimensions of difficulty for performance that guide the solutions we should offer.  What determines when we should use performance support, automate approaches, we need formal training, or a blend, or…?  It’s important to have criteria so that we can make a sensible determination. So, I started trying to map it out. And, not surprisingly, it’s not complete, but I thought I’d share some of the thinking.

So one of the dimensions is clearly complexity.  How difficult is this task to comprehend? How does it vary? Connecting and operating a simple device isn’t very complex. Addressing complex product complaints can be much more complex. Certainly we need more support if it’s more complex. That could be trying to put information into the world if possible. It also would suggest more training if it  has to be in the head.

A second dimension is frequency of use. If it’s something you’ll likely do frequently, getting you up to speed is more important than maintaining your capability. On the other hand, if it only happens infrequently, it’s hard to try to keep it in the head, and you’re more likely to want to try to keep it in the world.

And a third obvious dimension is importance. If the consequences aren’t too onerous if there are mistakes, you can be more slack. On the other hand, say if lives are on the line, the consequences of failure raise the game. You’d like to automate it if you could (machines don’t fatigue), but of course the situation has to be well defined. Otherwise, you’re going to want lot of training.

And it’s the interactions that matter. For instance, flight errors are hopefully rare (the systems are robust), typically involve complex situations (the interactions between the systems mean engines affect flight controls), and have big consequences!  That’s why there is a huge effort in pilot preparation.

It’s hard to map this out. For one, is it just low/high, or does it differentiate in a more granular sense: e.g. low/medium/high?  And for three dimensions it’s hard to represent in a visually compelling way. Do you use two (or three) two dimensional tables?

Yet you’d like to capture some of the implications: example above for flight errors explains much investment. Low consequences suggest low investment obviously. Complexity and infrequency suggest more spacing of practice.

It may be that there’s no  one answer. Each situation will require an assessment of the mental task. However, some principles will overarch, e.g. put it in the world when you can. Avoiding taxing our mental resources is good. Using our brains for complex pattern matching and decision making is likely better than remembering arbitrary and rote steps. And, of course, think of the brain and the world as partners, Intelligence Augmentation, is better than just focusing on one or another. Still, we need to be aware of, and assessing, the dimensions of difficulty as part of our solution.  Am I missing some? Are you aware of any good guides?

Of late there’s been a resurrection of a long term problem. While it’s true for our field as a whole, it’s also true for the specific job of those who design formal learning. I opined about the problem of labels for what we do half a year ago, but it has raised its head again. And this time, some things have been said that I don’t fully agree with. So, it’s time again to weigh in again.

So, first, Will Thalheimer wrote a post in which he claims to have the ultimate answer (in his usual understated way ;). He goes through the usual candidates of labels for what we do – instructional designer, learning designer, learner experience designer – and finds flaws.

And I agree with him on learning designer and instructional designer. We can’t actually design learning, we can only create environments where learning can happen. It’s a probabilistic game. So learning designer is out.

Instructional designer, then, would make sense, but…it’s got too much baggage.  If we had a vision of instruction that included the emotional elements – the affective and conative components – I could buy it. And purists will say they do (at least, ones influenced by Keller). But I will suggest that the typical vision is of a behavioristic approach. That is, with a rigorous focus on content and assessment, and less pragmatic approaches to spacing and flexibility.

He doesn’t like learning engineer for the same reason as learning designer: you can’t ‘engineer’ learning. I don’t quite agree. One problem is that right now there are two interpretations of learning engineer. My original take on that phrase was that it’s about applying learning science to real problems. Just as a civic engineer applies physics…and I liked that. Though, yes, you can lead learners to learning, but you can’t make them think.

However, Herb Simon’s original take (now instantiated in the IEEE’s initiative on learning engineering) focused more on the integration of learning science with digital engineering. And I agree that’s important, but I’m not sure one person needs to be able to do it all. Is the person who engineers the underlying content engine the same one as the person who designs the experiences that are manifest out of that system? I think the larger picture increasingly relies on teams. So I’m taking that out of contention for now.

Will’s answer: learning architect. Now, in my less-than-definitive post last year, I equated learning experience designer and learning architect, roughly. However, Will disparages the latter and heaps accolades on the former. My concern is that architects design a solution, but then it gets not only built by others, but gets interior designed by others, and… It’s too ‘hands off’!  And as I pointed out, I’ve called myself that recently, but in that role I may have been more an architect ;).

His argument against learning experience designer doesn’t sit well with me. Ignoring the aspersions cast against those who he attributes the label to, his underlying argument is that just designing experiences isn’t enough. He admits we can’t ensure learning, but suggests that this is a weak response. And here’s where I disagree. I think the inclusion of experience does exactly what I want to focus on: the emotional trajectory and the motivational commitment. Not to the exclusion of the learning sciences, of course. AND, I’d suggest, also recognizing that the experience is  not an event, but an extended set of activities. Specifically, it will be across technologies as needed.

The problem, as Jane Bozarth raised in a column, is more than just this, however. What research into the role shows is that there are just too many jobs being lumped under the label (whatever it is). Do you develop too? Do you administer the LMS? The list goes on.

I think we need to perhaps have multiple job titles. We can be an instructional designer, or a learning experience designer, or an instructional technologist. Or even a learning engineer (once that’s clear ;). But we need to keep focused, and as Jane advised, not get too silly (wizard?). It’s hard enough as it is to describe what we do without worrying about labels for it. I think I’ll stick with learning experience designer for now. (Not least because I’m running a workshop on learning experience design at DevLearn this fall. ;) That’s my take, what’s yours?