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I’ve argued both that Learning Experience Design (LXD) is an improvement on Instructional Design (ID), and that LXD is the  elegant integration of learning science with engagement. However, that doesn’t really unpack what are the critical ID/LXD differences. I think it’s worth looking at those important distinctions both in principle and practice. Here, I’m talking about the extensions to what’s already probably in place.

Principle

In principle, I think it’s the engagement part that separates the two. True, proper ID shouldn’t ignore it. However, there’s been too little attention. For instance, only one ID theorist, John Keller, has really looked at those elements. Overall, it’s too easy to focus purely on the cognitive. (Worse, of course, is a focus purely on knowledge, which really  isn’t good ID).

I suggest that this manifests in two ways. First, you need an initial emotional ‘hook’ to gain the learner’s commitment to the learning experience. Even before we open them up cognitively (though, of course, they’re linked)! Then, we need to manage emotions through out the experience. We want to do thinks like keep challenge balanced, anxiety low enough not to interfere, build confidence, etc.

We have tools we can use, like story, exaggeration, humor, and more to assist us in these endeavors. At core, however, what we’re focusing on is making it a true ‘experience’, not just an instructional event. Ideally, we’d like to be transformational, leaving learners equipped with new skills and the awareness thereof.

Practice

What does this mean in practice? A number of things. For one, it takes creativity to consider ways in which to address emotions. There are research results and guidance, but you’ll still want to exercise some exploration. Which also means you have to be iterative, with testing. I understand that this is immediately scary, thinking about costs. However, when you stop trying to use courses for everything, you’ll have more resources to do courses right. For that matter, you’ll actually be achieving outcomes, which is a justification for the effort.

Our design process needs to start gathering different information. We need to get performance objectives; what people actually need to do, not just what they need to know. You really can’t develop people if you’re not having them perform and getting feedback. You also need to understand  why this is needed, why it’s important, and why it’s interesting. It is, at least to the subject matter experts who’ve invested the time to  be experts in this…

Your process also needs to have those creative breaks. These are far better if they’re collaborative, at least at the times when you’re ideating. While ideally you have a team working together on an ongoing basis, in many cases that may be problematic. I suggest getting together at least at the ideating stage, and then after testing to review findings.

You’ll also want to be testing against criteria. At the analysis stage, you should design criteria that will determine when you’re ‘done’. When you run out of time and money is  not the right answer! Test usability first, then effectiveness, and then engagement. Yes, you want to quantify engagement. It doesn’t have to be ‘adrenaline in the blood’ or even galvanic skin response, subjective evaluations by your learners is just fine. If you are running out of time and money before you’re achieving your metrics, you can adjust them, but now you’re doing it on consciously, not implicitly.

I’m sure there more that I’m missing, but these strike me as some critical ID/LXD differences. There are differences in principle, which yield differences in practice. What are your thoughts?

It’s become obvious (even to me) that there are a host of teachers moving to L&D. There are also a number of initiatives to support them. Naturally, I wondered what I could do to assist. With my reputation as a cynic apparently well-secured, I’m choosing to call out some bad behaviors. So here are some superstitions for new practitioners to watch out for!

As background, these aren’t the myths that I discuss in my book on the topic. That would be too obvious. Instead, I’m drawing on the superstitions from the same tome, that is things that people practice without necessarily being aware, let alone espousing them. No, these manifest through behaviors and expectations rather than explicit exhortation.

• Giving people information will lead them to change. While we know this isn’t true, it still seems to be prevalent. I’ve argued before about why I think this exists, but what matters is what it leads to. That is, information dump and knowledge-test courses. What instead we need is not just a rationale, but also practice and then ongoing support for the change.
• If it looks like school, it’s learning. We’ve all been to school, and thus we all know what learning looks like, right? Except many school practices are only useful for passing tests, not for actually solving real problems and meeting real goals. (Only two things wrong: the curriculum and the pedagogy, otherwise school’s fine.) It, however, creates barriers when you’re trying to create learning that actually works. Have people look at the things they learned outside of school (sports, hobbies, crafts, etc) for clues.
• People’s opinion is a useful metric for success. Too often, we just ask ‘did you like it’. Or, perhaps, a ‘do you think it was valuable’. While the latter is better than the former, it’s still not good enough. The correlation between people’s evaluation of the learning and the actual impact is essentially zero. At least for novices. You need more rigorous criteria, and then test to achieve.
• A request for a course is a sufficient rationale to make one. A frequent occurrence is a business unit asking for a course. There’s a performance problem (or just the perception of one), and therefore a course is the answer. The only problem is that there can be many reasons for a performance problem that have nothing to do with knowledge or skill gaps. You should determine what the performance gap is (to the level you’ll know when it’s fixed), and the cause.  Only when the cause is a skill gap does a course really make sense.
• A course is always the best answer. See above; there are  lots  of reasons why performance may not be up to scratch: lack of resources, wrong incentives, bad messaging, the list goes on. As Harless famously said, “Inside every fat course there‘s a thin job aid crying to get out.” Many times we can put knowledge in the world, which makes sense because it’s actually  hard to get information and skills reliably in the head.
• You can develop meaningful learning in a couple of weeks. The rise of rapid elearning tools and a lack of understanding of learning has led to the situation where someone will be handed a stack of PPTs and PDFs and a rapid authoring tool and expected to turn out a course. Which goes back to the first two problems. While it might take that long to get just a first version, you’re not done. Because…
• You don’t need to test and tune. There’s this naive expectation in the industry that if you build it, it is good. Yet the variability of people, the uncertainty of the approach, and more, suggest that courses should be trialed, evaluated, and revised until actually achieving the necessary change. Beware the ‘build and release’ approach to learning design, and err on the side of iterative and agile.

This isn’t a definitive list, but hopefully it’ll help address some of the worst practices in the industry. If you’re wary of these superstitions for new practitioners, you’ll likely have a more successful career. Fingers crossed and good luck!

There’s some overlap here with messages to CXOs  1 and 2, but a different target here.  

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!