"The job of educators should be to prepare students for a complex adaptive system, not to make them capable of operating only a narrow part of a complicated machine. We need to equip our youth for a world that isn’t about perfecting a machine but rather about achieving a balance—an endless journey of transitory improvements rather than definitive solutions. That is the only way we will produce the citizens that we need and the business executives and political leaders to pilot productively.
At present, the formal education system predominantly teaches certainty; that is, that there is one right answer and many wrong ones.
Despite humanity’s long and painful history of being shown to be wrong about what was previously held to be certain, we keep teaching models as if they are not models but rather reality—the true unshakeable reality, rather than what they are: the best interpretation of reality humanity has been able to come up with yet.
Instead, we need to teach students—at all levels—that all models are wrong, otherwise they wouldn’t be models in the first place. Rather than teaching students to uncritically adopt models, with all their implicit flaws, we need to teach students how to critically evaluate models. Even more important, we need to teach students how to build new ones. That is what human advancement is about: building better models.
Theorizing is important. It is what we do to make sense of the world around us and build models for taking action. But theorizing on the back of someone else’s interpretations is never going to be as powerful as theorizing on the basis of your own interpretations of real interactions with your subject—whatever that subject happens to be.
Rather than teaching students that data is restricted to numbers that appear mysteriously for the student to analyze, or teaching the accumulation of quantitative data via arms-length surveys, educators need to teach students that data, both qualitative and quantitative, gleaned from watching real people engage in real activities, is the most powerful tool for building better models for how the world works. Those models can be tested quantitatively to refine them. But the attempt to build models of our complex adaptive world purely on the basis of quantitative analysis of data will lead to narrow"
quinta-feira, setembro 10, 2020
"an endless journey of transitory improvements rather than definitive solutions"
A continuar a minha leitura de "When More Is Not Better" de Roger Martin encontro uns trechos que me fizeram recuar aos anos 80 e à descoberta de Karl Popper: