Good science communication is hard. This handy guide from SMBC Comics helps distinguish the good from the bad.
Jargon (that is, specialised or technical language) is a common problem in poor science communication. Randall Munroe, of xkcd and what if?, took the idea of cutting out jargon to the extreme. (If you haven’t checked out either xkcd and what if?, go do it now. I’ll wait.)
Munroe’s book, Thing Explainer, uses only drawings and a vocabulary of the 1,000 (or “ten hundred”) most common words to explain complicated idea such as: “computer buildings (datacenters), the flat rocks we live on (tectonic plates), the things you use to steer a plane (airliner cockpit controls), and the little bags of water you’re made of (cells)”.
This sparked a movement amongst scientists and non-scientists to explain ideas using the most common ten hundred words. This Tumblr blog collected around 300 entries in the first week. The twitter hashtag is #UpGoerFive. Read the explanatory article in the Scientific American to find out why. To help determine whether the words you pick are in the ten hundred most used words, check out the Up-Goer Five Text Editor.
Explaining my research with the ten hundred most used words
I thought I’d take the challenge, and explain my group’s mathematical research in energy-efficient train operations without, it turns out, using the words ‘energy’, ‘speed’, ‘mathematics’, ‘train driver’, ‘destination’. See if you can find their replacement words below.
It takes a lot of train-food to move a train, but less food for each person on the train than in cars or on buses. If we can work out how to use less train-food, we can help our world live longer.A train-driving person can drive the train in four ways: full power (train goes faster), some power (train goes no faster and no slower), no power (train slows down), or counter-power (train slows down fast).If we can tell the train-driving person when to change between the four driving ways, we can lower the train-food needed to get to each stop on time. In real life we can save ten to twenty parts in one hundred bits of train-food.Our team uses numbers, letters and other strange marks to work out the least train-food needed to move a train to each stop on time. We show this to the train-driving person with a computer picture. The picture might change if the train-driving person is not doing what we told them, and so the train is going faster or slower than it should.We also study how the train should be driven if there are very high or low parts on the track, how more than one train should be driven, and how to decide the best time that each train should be at each stop to use least total train-food.
I’m not sure if this makes our research any clearer (!), but I had to work quite hard to carefully choose my words, and that was the whole point of the exercise.
Will you take the challenge? Explain: what you do, your teaching philosophy, your research, a book or movie, a mathematical concept — anything, really — and share it in the comments below.
Thanks for sharing a math-journal version of the train work with me. I learned that the funny symbols you use are very important because they capture lots of ideas in a very small set of markings! For example, I noticed math ideas about how if you know the speed at which something is adding up, you can use that directly to find out how much stuff there is at any time. And math ideas about how if you want to know when something is the best (uses least train food) you only have to think about some of the parts of the journey — mainly where you switch from one idea bossing how fast you should go to another idea bossing how fast you should go.
There was lots of math that I don’t know well enough to explain how you used it to know what speed the drivers should go to use the least train food when two trains are trying not to get too close together, or when is the best time to check that the drivers are safely far apart from each other.
One other thing I noticed was how mathematicians use each other’s ideas and think of new ideas to write about!
You read what other people who think about trains and train food and making the trains be fast and on time and safe and cheap. You try to understand what they did to come up with their ideas about the best ways to drive the train. Each group of people makes a list of all the things that make it hard to figure out the best speeds to go, and they write which things that make it hard they are going to leave out of their ideas. For example, it’s hard to know how fast a train should go when it has to go up and down hills. So some of the group’s only think about the best speeds when the train doesn’t have to go up and down. Then, when you and your group want to work on a new idea, they think: what if we didn’t leave that out? Could we add a new idea so that we can find the best speed when the train has to go up and down? Or when there are two trains and the boss says this train has to stay this far behind the other train? And then you use the math ideas the other groups already used (and you don’t have to explain those very much because they already did) plus you add your own ideas… But your own ideas have a lot of parts borrowed from other people who use the same symbols and ideas but use those ideas to solve different kinds of problems!
How’s that for an UpgoerFive version of what (applied?) mathematicians do?
I *love* this post, Max! A very thoughtful explanation of how we did this.
We like to call ourselves ‘industrial mathematicians’ to emphasise the applied connection to industry-inspired problems. But ‘applied mathematician’ works just as well!