I’ve had my head down on a major project, a bunch of upcoming speaking engagements, some writing I’ve agreed to do, and…(hence the relative paucity of blog posts). That project, however, has been interesting for a variety of reasons, and one really is worth sharing: ID isn’t easy. We’ve been given some content, and it’s not just about being good little IDs and taking what they give us and designing instruction from it. We could do it, but it would be a disaster (in this case, that’s what we’re working from, a too-rote too-knowledge-dump course). And it’s too often what I’ve seen done, and it’s wrong.
SMEs don’t know how they do what they do. Part of the process of becoming expert is compiling away the underlying thinking that goes on, so it moves from conscious to subconscious. So when the time comes to work with SMEs about what’s needed, they a) make up stories about what they do, or b) resort to what they’ve learned (e.g. knowledge). It’s up to the ID to push back and unpack the models that guide performance. Yet that’s hard, particularly when they’re not domain experts, and SMEs have issues.
It takes a fair bit of common sense (remarkable by how uncommon it is), and willingness to continually reframe what the expert says and twist it until it’s focused on how they make decisions. There’re formal processes call Cognitive Task Analysis when you need them, but a ‘discount CTA’ approach (analogous to Nielsen’s ‘discount usability‘) would be appropriate in many cases.Such an approach includes getting some really good examples of both successes and failures of the task under consideration, and working hard to extract the principles that guide success. But SMEs can’t be order takers; they have to be willing to fight to understand what decisions do learners need to make that they can’t make now, and how to make those decisions.
It really helps to either have a deep background in the field, or a broad background. You can get the former by teaching ID to a SME, or having an ID work in a particular field for a long time. The latter works if you’re more in the ‘gun for hire’ mode. You then need, however, a broad knowledge that you can draw upon to make some reasonable inferences. That’s what I typically do, as my deep expertise is in learning design, but fortunately I’m eternally curious (used to lie on the floor with a volume of the World Book spread out in front of me). Model-based and systems thinking help immensely.
You really have to work hard, use your brain, draw upon real world knowledge and go to the mat with the material. If you’re not willing to do this, you’re not cut out to be a learning designer. There’s much more, understanding the way we learn, experience design, and more, but this is part of the full picture.