Malcolm Gladwell makes a good point that should be kept in mind whether we are talking about neural networks, decision support systems, social network choices, or the wisdom of crowds– much of the time, being good enough is, well, good enough! It’s easy to poke holes in the decisions of artificial systems and to find flaws in the choices made through group consensus… but it’s easy to find exceptions to most real-world rules, and there is some truth to the old adage that those exceptions prove the rule.
This applies in many areas for educators. A few days ago I posted about race, class, digital natives and education… before that on connectivism. In all these cases, finding contrary examples to the theories and practices means little if those examples don’t directly address the utility (or not) of those theories. Like most learning theories, connectivism is full of “holes”– but in many ways, it’s good enough. We’re better off using it than not. Similarly, while I believe the general theory of Net Gen has enough utility to keep in mind when devising learning experiences, I’m not sure that in most situations the generalized concept of “race” does.
Of course the flip-side of having things good enough is lethargy or even outright resistance to innovation. If it’s good enough, why change? If education by transmission and replication is good enough for an educator, why undertake the (admittedly) hard work of changing their practice? In that scenario it’s not just a matter of counter-example, but of persuasion… and more than a little faith. It’s a tough nut to crack.
