I’m a fan of models. Good models that are causal or explanatory can provide guidance for making the right decisions. However, there are some approaches that are, I suggest, less than helpful. What makes a good or bad model? My problem is about distinguishing when to talk about each: simple models and complex problems.
A colleague of ours sent me an issue of a newsletter (it included the phrase ‘make it meaningful‘ ;). In it, the author was touting a four letter acronym-based model. And, to be fair, there was nothing wrong with what the model stipulated. Chunking, maintaining attention, elaboration, and emotion are all good things. What bothered me was that these elements weren’t sufficient! They covered important elements, but only some. If you just took this model’s advice, you’d have somewhat more memorable learning, but you’d fall short on the real potential impact. For instance, there wasn’t anything there about the importance of contextualized practice nor feedback. Nor models, for that matter!
I’m not allergic to n letter acronym models. For instance, I keep the coaster I was given for Michael Allen’s CCAF on my desk. (It’s a nice memento.) His Context-Challenge-Activity-Feedback model is pretty comprehensive for the elements that a practice has to have (not surprisingly). However, learning experiences need more than just practice, they need introductions, and models, and examples and closings as well as practice. And while the aforementioned elements are necessary, they’re not sufficient. Heck, Gagné talked about nine elements.
What I realize as I reflect is that I like models that have the appropriate amount of complexity for the level of description they’re talking about. Yet I’ve seen far too many models that are cute (some actually spell words) and include some important ideas but they’re not comprehensive for what they cover. The problem, of course, is that you need to understand enough to be able to separate the wheat from the chaff. I’ll suggest to look to vetted models, that are supported by folks who know, and there are criticisms and accolades to accompany them. Read the criticisms, and see if they’re valid. Otherwise, the model may be useful.
Ok, one other thing bothered me. This model supposedly has support from neuroscience. However, as I’ve expressed before, there have yet to be results that aren’t already made from cognitive science research. This, to me, is just marketing, with no real reason to include it except to try to make it more trendy and appealing. A warning sign, to me at least.
Look, designing for learners is complex. Good models help us handle this complexity well. Bad ones, however, can mislead us into only paying attention to particular bits and create insufficient solutions. When you’re looking at simple models and complex problems, you need to keep an eye out for help, but maybe it needs to be a jaundiced eye.
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