Archives for May 2023

A placebo effect?

30 May 2023 by Clark 1 Comment

I was thinking about what too often we see as elearning. That is, the usual content dump and knowledge test. There’s good reason to believe that it isn’t effective. So, why are we seeing it continue? Is it a placebo effect?

I tend to view this as a superstition. That is, the belief that information presentation will lead to behavior change is held implicitly. I think it originates from a legacy perspective that we’re logical, and therefore new information will yield impact. (Not.) Regardless, it exists.

I was inclined to wonder if, really, it’s a placebo. That is, doing something with a hope that things change, but the onus is on the individual, not the intervention. There’s not going to be any actual effect, but it makes people feel better. Of course, the role is different here; the placebo makes the doctor feel better! (Or the health system? I’m muddling my metaphor…:)

It may not be that in practice, of course. There is a ‘faith’ that “if we build it, it is good”. So, biz units can ask for a course, and get one. They’ve provided content and access to SMEs. However, they push back when asked “what’s the actual problem”, let alone asked for measures. It’s like they think the job can be done with information. They are happy with the appearance of a solution, because it’s easy, and no one’s checking.

We, of course, have to change this perception. If we continue to let folks believe they can give us content and we’ll deliver meaningful change, shame on us. Of course they don’t care about the measures, and they want things to be easy. We have to, however. It may as well be a placebo effect, because the ultimate impact is a likely null as sugar pills, unless the patient wants to change. It’s probably not a great metaphor, but somehow it still seems apt. Thoughts?

The Role of a Storyboard?

23 May 2023 by Clark 1 Comment

In a recent conversation, the issue of storyboards came up. It was in the larger context of representations for content development. In particular, for communicating with stakeholders (read: clients ;). The concern was how do you communicate the content versus representing the experience. So, the open question is what is the role of a storyboard?

So, there are (at least) several elements that are important in creating a learning experience. One is, of course, the domain. What are the performance objectives? Moreover, how are you providing content support. Specifically, what models are you using, and what examples. Then, of course, there’s the practice. Ideally, practice aligns with the performance objectives, and the models and examples support the practice.

There’s also the experience flow. How are you hooking learners up front? We are concerned with balancing the quantity of content with the actual practice, keeping engagement throughout.

In both cases, we need to communicate these to the clients. Too often, of course, clients raise concerns about making sure ‘the content’ is covered. In many cases, they really don’t understand that less is better, and have a large amount they’ve heard from subject matter experts (SMEs). Not knowing, of course, that SMEs have access to what they know about the domain, but less about what they do! Thus, they’re looking to make sure the content’s covered.

There will also be concern about the experience. This, likely not ideally, comes after assurance about the content. I personally have experienced situations where stakeholders say ‘ok’ to a storyboard, but then balk at the resulting experience. Some (surprisingly high) proportion of folks can’t infer an experience from a storyboard. This has been echoed by others.

The question is what is the role of a storyboard. In game design, there is a (dynamic) design document that captures everything as it develops. Is this the right representation to communicate the experience? It communicates to developers, but is it good for clients? I argue that we want more iterative representations, for instance getting sign-off on what we’ve heard from the analysis and documenting what will be the focus of the design. We also want to separate out the domain from the experience.

Overall, I advocate representing the experience, for instance in (mocked up) screenshots with narration to represent a sample interaction. That can accompany the storyboard, but when folks have to sign-off on an experience, and they can’t get it from the usual representations, you’ll need an augment. I wonder whether we should fight against presenting the content that’ll be covered.

We should show the objectives, models, and examples, but fight against content ‘coverage’. Cathy Moore does a good job in her ‘Action Mapping’ to argue that what the minimum is to achieve success on appropriate performance tasks is a good goal. I agree, as does learning science. The role of a storyboard is to capture development for developers. It may not be the right communication tool for stakeholders. I welcome your thoughts.

Grounded in practice

16 May 2023 by Clark Leave a Comment

Many years ago, I was accused of not knowing the realities of learning design. It’s true that I’ve been in many ways a theorist, following what research tells us, and having been an academic. I also have designed solutions, designed design processes, and advised orgs. Still, it’s nice to be grounded in practice, and I’ve had the opportunity of late.

So, as you read this, I’m in India (hopefully ;), working with Upside Learning. I joined them around 6 months ago to serve as their Chief Learning Strategist (on top of my work as Quinnovation, as co-director of the Learning Development Accelerator, and as advisor to Elevator9). They have a willingness to pay serious attention to learning science, which as you might imagine, I found attractive!

It’s been a lot of marketing: writing position papers and such. The good news is it’s also been about practice. For one, I’ve been running workshops for their team (such as the Missing LXD workshop with the LDA coming up in Asia-friendly times this summer). We’ve also created some demos (coming soon to a sales preso near you ;). I’ve also learned a bit about their clients and usual expectations.

It’s the latter that’s inspiring. How do we bake learning science into a practical process that clients can comprehend? We’re working on it. So far, it seems like it’s a mix of awareness, policy, and tools. That is, the design team must understand the principles in practice, there need to be policy adjustments to support the necessary steps, and the tools should support the practice. I’m hoping we have a chance to put some serious work into these in my visit.

Still, it’s already been eye-opening to see the realities organizations face in their L&D roles. It only inspires me more to fight for the changes in L&D that can address this. We have lots to offer orgs, but only if we move out of our comfort zone and start making changes. Here’s to the revolution L&D needs to have!

Curriculimb

9 May 2023 by Clark 3 Comments

Ok, so I’m going to go out on a limb here, and talk a wee bit about what I’ve been learning about designing curricula. I care about doing it right (and probably haven’t always). It’s not the average course that’s the issue, but big ones, or multiple courses addressing skill gaps. It’s been challenging to find a systematic approach, which is why I’m teetering on a curriculimb.

So, the issue is how to develop a curriculum. I know in higher ed (I was there once) it tends to be a process of figuring out what content they need, and distributing across courses. It’s probably more art than science, where you move stuff around until it feels like you’ve got the right sized amount of content for each subject and it covers the ‘right stuff’. How people meet the criteria can vary. In a more research institution, I could design my HCI course my way. In more teaching-focused institutions, people may actually be given course syllabi to teach to!

My problem is when I have an uncertain amount of content, say for a large domain, and I want to develop specific capabilities. On principle, we should work backwards from the final performance. Which might include some very rich types of capabilities, so we might have a lot of concepts and practice involved. We’d need to create a large map. We might even break it up into conceptual stages (e.g. with programming: learning conditionals and then loops), and addressing them separately.

You probably also need to provide some practice to deal with misconceptions. That is, where are folks likely to get off track and maybe discouraged? Then you want to create practice for that. The things you’d rather they learned before it matters.

When I looked for good principles around this, it seemed like most of what I found basically said it’s iterative, there are no overarching principles (except work backwards and iterate ;). Which was less than satisfying, and some evidence-based practice would be nice.

Now, one of the things I was pondering in the dark of the night was how AI could help. I’ve been hearing how it can parse content and create maps. However, I also realized that to do so, it needs well-structured content. Kind of a circular argument. I think we need people to define it then AI can align it.

Again, right now it seems more like an art than a science. And I get that; it’s a lot like designing in engagement: create a first best guess and then test. Still, there are some solid results in engagement that give us some grounds for the first pass. I feel less like that at the next level up. So, I’m out on a curriculimb, and welcome help getting down!

Attention is underrated

2 May 2023 by Clark 1 Comment

Attention is a complex phenomena. Thinking that we can simply address is probably naive. Worse, there is at least one pervasive myth about it. Trivial attention is probably overrated, but meaningful attention is underrated.

Attention, I’ll suggest, is how we pay conscious awareness to our thinking. We pay attention to the sensory stream that’s available, and as working memory is has limits, our attention chooses what ends up being in working memory (which is where we see conscious thought). This is the picture I paint in Learning Science for Instructional Designers, my recent book on how we learn. That’s how I learned it in grad school, and little seemed to change that.

As an aside, I suggest that the basic human information processing loop is something that is critical to understand. This is true for learning designers, but I would suggest there’s broader applicability. Knowing how information flows:

from sensory store to working memory via attention
from working memory to long term memory via elaboration
back to working memory via retrieval
and to decision from working memory

as a simplified story, shows how humans work in many ways. It gets more complex in important ways, but this is a key basis. On top of it comes aspects of how we think, and learn, but this is the core. It benefits anyone dealing with people, basically: UI, marketing, etc. In short, most everyone.

Recent pictures of the information processing loop suggest, however, that attention has a bigger purview. They have it influencing most of the above. Which may be more accurate, in that if you need to attend to what’s in working memory, and manage the process of attending to information while evaluating what decision to make. You must maintain conscious focus on what you want to learn.

The myth, which still persists, is that our attention span has dropped to 8 seconds. Which folks tout as less than that of a goldfish. (How do we know what the attention span of a goldfish is?) The origin of this myth came from StatBrain misinterpreting a study, and was amplified since it was published by Microsoft Canada. Marketing, mind you, not their research group! A myth I busted in a previous book!

There is apparently some evidence that our attention span has dropped (to 4o-something seconds, not eight), but we can still disappear into movies, novels, and games for hours. I reckon it’s about how engaging it is. Which, not completely surprisingly, is the topic of my most recent book, Make It Meaningful.

So, please, avoid the myths, and learn the core. Attention is underrated, as is the whole human information processing loop. Learn it, and benefit.