When you penalise wrong answers, you build in a sense of shame and failure to being wrong that most people never get over. It leads to cheating, to covering up of mistakes, and to avoiding doing things where being wrong is a possibility. How about, instead, we make it the default that you assume that you will be wrong in numerous ways. We make it a fundamental part of the process to figure out those ways, and even reward the finding of those mistakes. In doing so, we give people the freedom to explore, to try new things, and, above all, to learn without fear.
Tag: stem education
Andrew Leigh on Data & Politics
"The rise of populism has been substantial across the advanced world, indeed across developing countries as well. So those of us who believe in data need to be strong proponents of the publication of those data even when it produces results that make us uncomfortable.
Michael Brand, on the Science of Data Science
"We do not teach people that making mistakes is not just right, but it's the only way of learning. It's the only way of becoming better." Honestly, I want to turn this whole episode into pull quotes! Go listen!
When simple values are complex
How do you measure temperature? It's more complicated than you expect.
Axes of awful
This is another example of how there are no absolute rules in data science (except for: there's no such thing as a perfect dataset - that one holds inviolable!). Everything is context. The y-axis not starting at 0 is sometimes ok. Pie charts are sometimes a great way to compare values. A line graph is sometimes useful for discrete data.