On the theme of “how to teach ‘teaching’” or “learning how (and what) to teach”
Earlier last year I decided to teach myself Arduino. I started off by trying to make an air quality monitor to measure CO, humidity, temperature, and PM. Very soon I realized there were multiple disciplines that I had to learn:
For starters, I had to know the concept of air quality. That would lead me to choose CO, hum/temp, and PM, but much of that choice was also driven by the availability of sensors. So, I had to start with environmental principles and then moderate them by market availability.
Then I had to know about the concept of converting these components of air quality to data, something that could be measured. And I had to understand that the sensors primarily generated electrical signals in response to what they were measuring, and these electrical signals were converted to the more familiar units that I would understand. Plug in a 33 ohms resistor, they said. Why 33? Why not 22? Who decided this? What is the logic?
There was, of course, Arduino to conquer. The “make an LED blink” tutorial was far behind me. I now had to find libraries for DHT22 and for ethernet. I had to learn how to import these. I had to even understand the concept of libraries and learn how to find them, let alone question why I needed them and why I couldn’t just write my own. (Well, I could, but “piano piano”). I could, of course, copy and paste existing sketches, but that is not learning, is it?
Finally, now that I had the whole set up working and the data displaying correctly on my serial monitor, I also had a rat’s nest of wires snaking around plugged into a precariously balanced bread board. I had to convert this mess into a neat box that could actually withstand the very elements it was going to measure. This is what you see, for example, in the high build quality of stuff that the Gaudi Lab produces. It is not easy, but it is worth learning (and teaching).
So, there we have: environmental science, data science, electrical engineering, programming, and industrial design.
When I set out to teach making air quality monitors, I have to pick and choose what I can and should teach, targeting my audience with the right lessons so that it doesn’t detract from their curiosity, but also doesn’t get killed by their curiosity. Above all, I want to teach bigger concepts: don’t take things for granted, ask questions, measure, learn to create your own instruments if you can’t afford commercial ones, share, help each other. I want to change the culture of both learning and teaching. But, to get there, I have to learn the interim steps. I have to learn everything from env science to industrial design.
I would like to join forces with whoever is interested in the above line of thought and wants to tackle any or all of the challenges involved therein.
update: To be clear, not every hardware project has to be based on a microprocessor board, and hence, involve complicated electronics and programming (though, having that enables automated and data collection). (Electro-)mechanical lab equipment (most all of the above disciplines except the computing part) is of main interest to me, but that too involves notions of science, engineering and design.