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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!

Part 4 of the 4 part series:

Here‘re the final suite of heuristics I came up with many years ago as a result of looking at our design process and the barriers our cognitive architecture can put in our own way.

Full Spectrum Design: One of the most insidious problems observed in educational multimedia is a tendency to incorporate all the solution into the computer.   The system will be the repository of all the text, sound, graphics, etc, and the instruction.   Unfortunately, this does not properly reflect what’s known about reading text on screen and the role of the teacher.   In conjunction with the No Limits Analysis, another way to get the best design is to consider the full spectrum of media, particularly considering delivering text on paper, having the instruction accomplished by an instructor, etc.   The proper use of the term multimedia is to consider all the available media and their use and to distribute the instructional task across all of them.

No Limits Analysis: After assembling a team, the first step in the design process is analysis, and an important component is proper information gathering to ensure that all relevant possible sources of inspiration have been considered.   However, before we consider what others have done in the same, we should see what we come up with when we think as if there were no limits.   This occurs after the pedagogical problem has been identified but before other examples are considered.   The step is to consider how the problem would be addressed if there were no technological limitations, as if anything could be accomplished as if by magic. Arthur C. Clarke said “any truly advanced technology is indistinguishable from magic”, and we‘re really at the stage where the barriers are our imaginations, not the technology.   So stop and think what an ideal solution would be.   You may not be able to achieve what you imagine, but you certainly can‘t if you don‘t identify that option, and you‘ll prematurely limit the solution space.

Kitchen Sink Analysis: After the No Limits Analysis, comes the systematic consideration of other corners of the design space or other relevant prototypes for modification.   Lewis & Reiman suggested that “plagiarism” is an appropriate design strategy (as far as your lawyers would let you, as they cautioned), where ideas are lifted from existing designs rather than reinventing the wheel.   An expansion to this concept is to not only look at what others have done but to also consider how instruction might proceeded without computer support, what theory suggests as an approach, etc.   In short, the suggestion is to exhaustively search all potential sources of input into the design process, including the proverbial ‘kitchen sink’.   This process is both to help populate the design space and discover all constraints.

And let me add one other that I didn‘t explicitly include before:
Lateral input:   Research on brainstorming and creativity (cf D Bono), has shown that besides being systematic and covering all the known or plausible solutions, lateral thinking is valuable. After you‘ve been exhaustive within the box, find ways to get ‘outside the box‘.   Use random inspirations: play a game, doodle, get some random input!   Get silly!   It may not be politically correct anymore, but back when I worked for a learning game company, the CEO (hi, Sky!), used to bring in pizza and beer on Friday afternoon and have some idea sessions!   There are lots of tools and approaches, just make sure you make some concerted effort here.

OK, that‘s it for this series on design.   I hope these past few posts give you some useful guidance or ideas.   I welcome your own!

First: https://blog.learnlets.com/2008/09/design-design-as-search/

Second: https://blog.learnlets.com/2008/09/design-our-barriers/

Third: https://blog.learnlets.com/2008/09/design-the-first-heuristics/