I’ve been thinking a lot about processing in learning of late; what processing matters, when, and why. I thought I’d share my thinking with you and see what you think.  This is  my processing!  :)

We know processing is useful. You can consider Craik & Lockhart’s Levels of Processing model, or look to the importance of retrieval practice as highlighted in Brown, Roediger, and McDaniel’s Make it Stick. The point is that retrieving information from memory and doing things with it increases the likelihood of learning. One of the questions is  “what sort of retrieval (or processing)?”

I’ve always advocated for  applying the information, doing something with it.  But there are actually a variety of useful things we can do:

• representing information (a form of reflection) whether rewriting, or mindmapping, or…
• connecting to other known information, personal or professional
• considering how it would be applied in practice
• applying it in practice, real or simulated

Of course, we want there to be scrutiny and feedback for the learning to be optimized, etc.

Now, this is in the individual instance, but I’m also looking at the sequence of processing. What would be a series of activities that would develop understanding. So, for instance, for a problem-solving practice like trouble-shooting a process, what might you do? You might have  (say, after a model of the process, and examples) a sequence of :

• critique someone else’s performance
• try a simple example of performing
• try a more complex example (perhaps in a group)
• …(more examples of performing)
• try a very complex (read: typical) example

We could throw in related tasks as well either during or as a summary:

• create a checklist to follow
• draw a flow diagram
• create a representation

On a more categorical task, say determining whether a situation qualifies as this or not (with shades of grey in between), we would have a similar structure, but with different types of tasks (again, after initial content such as definition and examples):

• review a case where it clearly is (white)
• review a case where it clearly isn’t (black)
• group review a case of grey (but not too bad)
• group review a case of grey (more shady)
• …

Again, we could have interim or summary tasks:

• summarize the constraints
• document a proposed process
• make a plan for how to do it in the future
• …

What I’ve explicitly added here is when and why to go ‘social‘.  There are benefits for the same, but should they all be social?  I’ll argue that there’s some initial prep that’s individual, to get everyone on the same page. Since all are different, it helps if this is individual. Then there’s often value in doing it socially, for the reasons in the linked post.  Then, I reckon there’s value in doing  something independently, to consolidate the learning. And, of course, to determine what capability the individual has acquired.

The point I want to make is that the processing  flow, the progression from activity to activity, matters. We want to introduce, diverge, and then converge.  We do need to elaborate across contexts to support transfer, and of course increase complexity until they’ve developed the ability to deal with the typical difficulty of cases.

I’m thinking that, too often, we forget the consolidation phase.  And we’re often doing processing that’s somewhat like what we need them to do, but ultimately tangential. There are multiple constraints here to be acknowledged, cognitive such as depth and breadth as well as pragmatic such as cost and time, but we want to find the right intersection.

And my practical question is: where does this fall apart? Are their situations where this doesn’t make sense?  I realize there are other types of outcomes that I haven’t represented (I’m being indicative, not exhaustive ;), but is this a useful way to think about it?

 

I’ve called out a number of myths (and superstitions, and misconceptions) in my latest tome, and I’m grateful people appear to be interested.  I take this as a sign that folks are beginning to really pay attention to things like good learning design. And that’s important. It’s also  important not to minimize the problems myths can create. I do that in my presentations, but I want to go a bit deeper.  We need to care about why myths matter to limit our mistakes!

It’s easy to think something like “they’re wrong, but surely they’re harmless”.  What can a few misguided intentions matter?  Can it hurt if people are helped to understand if people are different?  Won’t it draw attention to important things like caring for our learners?  Isn’t it good if people are more open-minded?

Would that this were true. However, let me spin it another way: does it matter if we invest in things that don’t have an impact?  Yes, for two reasons.  One, we’re wasting time and money. We will pay for workshops and spend time ensuring our designs have coverage for things that aren’t really worthwhile. And that’s both profligate and unprofessional.  Worse, we’re also not investing in things that might actually matter.  Like, say,  Serious eLearning. That is, research-derived principles about what  actually works. Which is what we should be getting dizzy about.

But there are worse consequences. For one, we could be undermining our own design efforts. Some of these myths may have us do things that undermine the effectiveness of our work. If we work too hard to accommodate non-existent ‘styles’, for instance, we might use media inappropriately. More problematic, we could be limiting our learners. Many of the myths want to categorize folks: styles, gender, left/right brain, age, etc.  And, it’s true, being aware of how diversity strengthens is important. But too often people go beyond; they’ll say “you’re an XYZ”, and people will self-categorize and consequently self-limit.  We could cause people not to tap into their own richness.

That’s still not the worst thing. One thing that most such instruments explicitly eschew is being used as a filter: hire/fire, or job role. And yet it’s being done. In many ways!  This means that you might be limiting your organization’s diversity. You might also be discriminatory in a totally unjustifiable way!

Myths are not just wasteful, they’re harmful. And that matters.  Please join me in campaigning for legitimate science in our profession. And let’s chase out the snake oil.  Please.

A number of years ago, now, Brenda Sugrue posited that Bloom’s Taxonomy was wrong. And, she proposed a simpler framework. I’ve never been a fan of Bloom’s; folks have trouble applying it systematically (reliably discriminating between various levels). And, while it pushed for higher levels, it left people off the hook if they decided a lower level would do it. Sugrue first proposed a simpler taxonomy, and also an alternative that was just performance. In her later version, she’s aligned the former to the work of the Science of Learning Center’s KLI (knowledge-learning-instruction) framework. But I want to go back to her ‘pure performance’ model, and make a the case that decisions are key, that they  are necessary but also sufficient.

So her latest model discriminates between concept, process, fact, principle, etc.  And, I would agree, there are likely different pedagogies applied to each.  Is that a basis enough?  Let me suggest a different approach, because I don’t see how they differ in one meaningful way. For each, you need to take some action, whether it’s to:

• classify as a fact (is it a this or a that)
• perform the steps (which action to take now)
• trouble shoot the process (what experiment now)
• predict an outcome (what will happen)

Note, however, that for each, there’s an associated decision. And that, to me, is core.  Now, I’m not claiming that they all require the same approach.  For instance, to help people deal with ambiguous decisions, I suggested a collaborative approach to discuss the parameters and unpack the thinking. To teach trouble-shooting, I would give some practice making conceptual decisions about the systems that could cause the observed symptoms. In internal combustion engines (read: cars), if it’s not running, is the air/fuel system or the electricity? How could you narrow that down?  In a diesel, you could eliminate the electrical ;).

Van Merriënboer, in his Four Component Instructional Design, talks about the knowledge you need and the complex decisions you apply that to. I agree, and so it’s not  just  about decisions. However, even the knowledge needs to be applied to stick.  To test that learners have acquired the underpinning knowledge, you can hav them exercising the models in decisions.

Ok, so you might want to short-circuit the mapping from decision to practice. I think a good heuristic (ala Cathy Moore’s Action Mapping) is just to have them do what they need to do, and give them the necessary information. However, if you want to create a ‘cheat sheet’ to accelerate performance and success, with learning goals and associated pedagogies, I won’t quibble.

Now, you can’t provide all the situations, so you need to choose the right ones that will help facilitate abstraction and transfer. You may need to also ensure that they know the requisite information, so you may need to determine that, but I think exercising the models in simpler situations helps develop them more than just a presentation.

I’m suggesting that focusing radically on decisions is the best way to work with SMEs, and is the best guide for designing practice (e.g. put learners in situations to make decisions). Everything else revolves around that. Now, are these categories reliable  types of decisions?  Will ponder. Your thoughts?

I’ve talked about examples before, and have long suggested that examples for learning should be in the form of stories. Today I thought a little deeper about  how those stories can be told. And I thought of a particular entailment about video. But let me go through the whole  story.

So, first, an example needs to do several things.  Foremost, examples show how a concept is used in context to guide performance and achieve a solution. To put it another way, examples illustrate how a model is used to make decisions in a specific situation.  It could be situational coaching, a sales process, how to run a brainstorming session, or the basis of a good presentation. Importantly, examples need to show the underlying thinking behind what aspects of the situation made this model relevant, how it was mapped to the situation, how  it stipulated as actions to take, and what the outcomes were. It can also show mistakes, backtracking, and repair.

So how does this map to media?  There are (at least) three good ways to tell such a story. One, obviously, is prose. It’s easy to show the underlying thinking or discussions as “dialog” (internal or otherwise).  You can even illustrate model with a diagram, and convey context with a picture.  And this works.  However, for variety, you could use more visual treatments.

I’ve argued in the past that graphic novel formats also make sense. They strike a balance between conceptual and contextual,  and tell a story nicely. You can use thought bubbles to show the underlying thinking, include diagrams as a separate panel. And you can include necessary context but simplify the unnecessary context.

Finally, there’s video. This can be an animated cartoon (e.g. dynamic graphic novel), a narrated slideshow (think: Ken Burns), or a documentary style.  The question: how do you represent the model? Is it a separate narrated animation, or an overlay on the video (or both)?  I don’t think it matters as long as it’s explicit, and the underlying thinking is shown linking the concept to the context.

The point is that the nuances matter. It’s not just ‘content’; the elements that we provide have specific roles and we need to understand those.