Our brains are good at certain things, and not so good at others. We’re good pattern-matchers and meaning-makers, but not so good at doing things by rote. We make mistakes, almost by necessity (evolutionary advantage: if you do something a little different by chance and it’s better, it can get rewarded and more likely). And we simplify the world, partly to save energy for what we care about, but also because complexity is taxing.
And, in general, this is good. Our simplifications help us cope, make us more effective. However, given our nature, at times this can fail us. We may think we’ve taken a necessary step when we haven’t. Henry Petroski, in To Engineer is Human, helps us understand that we continue to push boundaries and take consequent risks. Atul Gawande, in The Checklist Manifesto, helps us understand the usefulness of support if we’re not going to make mistakes.
But sometimes this expediency can mask complexities and lead us astray. For a simple example, the term ‘learning management system’ can actually lead us to believe we’re achieving learning, instead of courses. And just because you have a course doesn’t mean something was learned.
There are many ways we can mislead ourselves. We can talk about a concept that we all realize has to be true, that learners differ, and then believe we can identify how someone learns. We may eventually be able to do so, but existing instruments aren’t valid, and learners change in different contexts. Plus, if we label learners as X or Y, we may limit them. When I humorously compared the ‘generational differences’ argument to age discrimination, someone deeply involved in that field corrected me that real age discrimination is a serious problem not to be taken lightly!
It may seem like an ‘angels dancing on the head of a pin‘ type of argument, but we have to be careful of the words we use and their import. We have to carefully consider the ways in which phrases can be used, or misused, and perhaps structure our use of language appropriately. It’s branding, and perhaps we need to treat it as such. At least, be careful of what terms you use and what inferences you’re making easy and which you might be inadvertently making hard.