Previous Series Post | Next Series Post

This is one in a series of thoughts on some broken areas of ID that I‘m posting for Mondays.   The intention is to provide insight into many ways much of instructional design fails, and some pointers to avoid the problems. The point is not to say ‘bad designer‘, but instead to point out how to do better design.

At some point (typically, after the introduction) we need to present the concept.   The concept is the key to the learning, really.   While we‘ve derived our ultimate alignment from the performance objective, the concept provides the underlying framework to guide one‘s performance.   We use the framework to provide feedback to help the learner understand why their behavior was wrong, both in the learning experience and ideally past the learning experience the learner uses the model to continue to develop their performance.   Except that, too often, we don‘t provide the concept in a useful way.

What we too often see is a presentation of a rote procedure, without the underlying justification.   In business, we‘ll teach a process.   In software, we‘ll see feature/function presentations (literally going item by item through the menus!).   We‘ll see tutorials to achieve a particular goal without presenting an underlying model.   And that‘s broken.

We need models! The reason why is that people create mental models to explain the world.   People aren‘t very good at remembering rote things (our brains are really good at pattern matching, but not rote memorization).   We can fake it, but it‘s just crazy to have people memorize rote things unless it‘s something we have to absolutely know cold (medical terminology is an example, as are emergency checklists for flights).   By and large, very little of what we need to know needs to be memorized.

Instead, what people need are models.   Models are powerful, because they have explanatory and predictive power.   If you forget a step in a procedure, but know the model driving the performance, you can regenerate the missing step.   With software, for instance, if you present the model, and several examples where the way to do something is derived from the model, and then you have the learner use inferences from the model to do a couple of tasks, you might be saved from having to present the whole system.

People will build models, so if you don‘t give them one, it‘s quite likely that the one they do build will be wrong.   And bad models are very hard to extinguish, because we patch them rather than replace them.   It requires more responsibility on the designer to get the model, as, for reasons mentioned before, our SMEs may not be able to help us, but get them we must.   Realize that every procedure, software, or behavior has a model that drives the reason why it should be done in a particular way, and find it. Then we need to communicate it.

Multiple models help! To communicate a model most effectively, we should communicate it in several ways.   Models are more memorable than rote material, but we need to facilitate internalization.   Prose is certainly one tool we can and should use (carefully, it‘s way too easy to overwrite), but we should look at other ways to communicate it as well.

Multiple representations help in several ways.   First, they increase the likelihood that a learner will comprehend the model, and then have a path to comprehend the other representations.   Second, the multiple representations increase the number of paths to activate a model in a relevant context.   Finally, multiple representations increase the likelihood that one can map closely to the problem and facilitate a solution.

Multiple representations are, unfortunately, sometimes difficult to generate (more so than finding the original model).   However, we should always be able to at least generate a diagram.   This is because the model should have conceptual relationships, and these can be mapped to spatial relationships.   There‘s some creativity involved, but that‘s the fun part anyways!

Yes, doing good instructional design does take more work, but anything worth doing is worth doing well.   On a related, but important, note, unfortunately the difference between broken ID and good ID is subtle.     You may have to explain it (I have literally had to), but if you know what you‘re doing and why, you should be able to.   And having developed a powerful representation increases the power, and success of the learning, and consequently the performance.   Which is, of course, our goal. So, go forth and conceptualize!

First Series Post | Next Series Post

This is one in a series of thoughts on some broken areas of ID that I‘m posting for Mondays.   The intention is to provide insight into many ways much of instructional design fails, and some pointers to avoid the problems. The point is not to say ‘bad designer‘, but instead to point out how to do better design.

One of the first things learners see is the introduction to the content; it‘s the first place that they can be disappointed, and all too often they are.   They are given objectives that don‘t matter to them, they‘re told what they‘re going to see in dull terms, it‘s all aversive rather than interesting.   Which is a wonderful way to start a learning experience, eh?

What we want to do is bring in the emotion! Almost all of instructional design is about the cognitive part, yet the motivational part is often just as important.   And we‘ve got to go beyond simplistic views of what that means.

Even cognitive science recognizes that there‘s more to the mind that the cognitive aspect, and includes the affective and conative as well.   Affective are your learning characteristics, your learner‘s styles.   Whereas conative is the interesting bit: the intention to learn, which includes things like motivation to learn, anxiety about learning, etc.

I‘ve gone off before about learning styles, and the short answer is to a) use the right media for the message, and b) to provide help for learners.   However, addressing motivation and anxiety is a different, and important, thing.   We want to assist their motivation, which happens by helping the learner connect this experience to themselves and their goals.   And we want to reduce their anxiety to an appropriate level (people perform better under a little pressure), by helping manage their expectations.

To help with motivation, there are a couple of things to do.   We know that learners learn better when we activate relevant information up front (it helps associate the new information to existing information).   I maintain that we want to extend that, and open them up emotionally too. And, I believe that it should be done first.   I think we need to indicate the consequences of the knowledge, either negative for not having the information, or positive for having the information.   I think the consequences can be exaggerated, to increase the emotional impact, within bounds, and it can be done dramatically (see Michael Allen‘s Flight Safety video) or humorously.   I‘ve used comic strips to begin elearning sections (we don’t use comics enough)!

There are nuances here: it has to be specific to the situation, not just a non-related exaggeration.   Done well, it can incorporate the cognitive association activation as well!   But hook them emotionally, and the information will stick better.   Too often in the learning I see, there‘s not just little, but essentially no addressing why this information is important to the learner, and that‘s got to be job number 1, or we risk wasting the rest of the effort.

Then we come to objectives, and here I nod in the direction of Will Thalheimer, who‘s said this better than I: the objectives we show to the learner are not the ones we use to design!   Too often, there‘s a section in the cookie-cutter template for objectives, and we slap in the ones we‘re designing to.   Wrong, bad designer, no Twinkie ™.   We (should) use objectives [previous post] to align what we‘re doing to the real need, but the learners don‘t want to know about our metrics.   The objectives for them need to be rewritten in a WIIFM (What‘s In It For Me) framework. They should get objectives that let them know what they‘ll be able to do that they can‘t do now, that they care about!

Another thing that helps, and now we‘re onto anxiety more, is addressing expectations.   Stephanie Burns showed that of people who set out to accomplish a goal, those that succeeded were those who managed their expectations appropriately.   Similarly, when I run workshops, I find I get less concerns when I help lay out what‘s going to happen and why rather than just barging ahead.   If people don‘t know what to expect, or expect it‘ll be X (e.g. entertaining) and there‘s some Y (e.g. hard work), they get frustrated or concerned with the mismatch.   They can get upset in particular if one aspect is difficult and they feel like they‘re floundering.   Making sure that the expectations are set appropriately helps learners feel like they‘re in synch with what‘s happening, and maintains their confidence.

A role that‘s cognitive as well as motivational is that we don‘t do enough has to do with contextualizing what‘s happening.   Too often, learning is conduced in a vacuum.   Yet Charles Reigeluth‘s Elaboration Theory suggests drilling down, and I say contextualize the learning in the larger context of what‘s happening in the world. Even if we‘re learning about some minor medical procedure, we can talk about how health care is a major issue, and getting it right is one of the components to make it effective and efficient.   Or somesuch, but you can quickly connect what they‘re learning to the real world, and you should.   It‘ll help again associate relevant knowledge and increase the effectiveness of the message by connecting what‘s happening now to what‘s really important.

And, I‘ll finally add, no pre-tests, unless it‘s to let the learners test out. I‘ve talked about that before, so I‘ll merely point you to my previous screed.

So, introduce your learners appropriately to the learning, get them cognitively and emotionally ready for the learning experience, and you won‘t be throwing away all the effort to develop what follows the introduction, you‘ll be maximizing it.   And that‘s what you want, at the end, is for that learning to stick.

Next series post

This is the first in a series of thoughts on some broken areas of ID that I will be posting for Mondays.   The intention is to provide insight into many ways much of instructional design fails, and some pointers to avoid the problems. The point is not to say ‘bad designer‘, but instead to point out how to do better design.

The way I‘ve seen many learning solutions go awry is right at the beginning, focusing on the wrong objective.   Too often the objective is focused on rote knowledge, whether it‘s facts, procedures, or canned statements.   What we see is knowledge dump, or as I‘ve heard it called: show up and throw up.   Then, the associated assessment is similarly regurgitation of what you‘ve just heard.   The reasons this happens, and why it doesn‘t work, are both firmly rooted in the way our brains work.

First, our brains are really bad at rote remembering.   We‘re really good at pattern-matching, and extracting underlying meaning.   That‘s why we use external aids like calendars.   Heck, if it‘s rote knowledge, don‘t make them memorize it, let them look it up, or automate it.   OK, in the rare case where they do have to know it, we can address that, but we overuse this approach.   And that‘s due to the second reason.

Experts don‘t know how they do what they do, by and large.   Our brains ‘compile‘ information; expertise implies becoming so practiced that the process is inaccessible to conscious thought (ask an expert concert pianist to describe what they‘re doing while playing and their performance falls apart).   We found this out in the 80‘s, when we built so-called ‘expert systems‘ to do what experts said they did,   When the systems didn‘t work, we went back and looked at what the experts were really doing, and there was essentially zero correlation between what they said they did, and what they actually did.

What happens, then, is that our Subject Matter Experts (SMEs) do recall what they studied, and toss that out.   They‘ll dump a bunch of relevant knowledge on the designer, and the good little designer will develop a course around what the SME tells them.   So, we see objectives like:

Be able to cite common objections to our product.

What‘s needed is to focus on more meaningful outcomes.   Dave Ferguson has written a nice post defending Bloom‘s skill taxonomies, and he‘s largely right when saying that focusing on what people actually do with the knowledge is critical. However, I find it simpler to distinguish, ala Van Merrienboer, between the knowledge the learner needs, and the complex decisions they   apply that knowledge to, with the emphasis on the latter.   So, I’d like to see objectives more like:

Be able to counter customer objections to our product.

The nuances may seem subtle, but the difference is important.

How does a designer do that?   SMEs are not the easiest folks to work with in this regard.   I‘ve found it useful to turn the conversation to focus on the things that the learner needs to be able to do after the learning experience.   That is, ask them what decisions learners need to be able to make that they can’t make know.   Not what they need to know, but what do they need to be able to do.

And, I argue, what will likely be making the difference going forward will be skills: things that learners can do differently, not just what they know.   I recall a case where an organization was not just looking for the learners to understand the organizational values, but to act in accordance with them (and that that meant).   That‘s what I‘m talking about!

When it comes to capturing objectives, I‘m perfectly happy with Mager‘s format of specifying who the audience is, what they need to be able to do, and a way to determine that they‘re successfully performing.   From there, you can work backwards to the assessment, to the concept, examples, and practice that will develop the skills to pass the assessment.

There‘s another step, really, before this, and that‘s determining what decision learners need to make differently or better to impact the bottom line, e.g. choosing objectives that will affect the organization in important ways, but that‘s another topic for another day.

Doing good objectives is both a skill that can be learned, and a process that can be supported.   You should be doing both.   Starting from the right objective makes everything else flow well; if you start on the wrong foot, everything else you do is wasted.   Get your objectives right, and get your learning going!