Being a great science teacher is not so different from being a great science writer. You have to convince your audience to pay attention to you, rather than to the myriad other potential sources of entertainment and engagement out there. You have to maintain their attention: at any time, a reader can click over to a different website or turn the page of the magazine or newspaper. You have to break down complex ideas into understandable chunks.
The writer is making an unstated contract with the reader. The writer says to the reader: I will value you and your time, because I know that you are just two boring sentences away from reaching for your cell phone and playing Angry Birds, and in return you will spend some amount of time reading my sentences, equal to only a small fraction of the time that I spent crafting those sentences in the first place.
As yet another semester winds down, I realize there are many things I've learned from being a science writer that transfer extremely well to teaching. Here are three of them: (1) a student is a complete person, and the class he or she is taking is but one part of his or her life; (2) if I am not excited about something, I can not hope to excite a student about something; and (3) no matter how exciting something is, it needs to be accessible.
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Nicely put.
words are a powerful tool
One of the things I like about writing, though, is that it's easy to revise. It's much easier to delete a bad paragraph than to ask a class to forget a bad lecture or discussion.
I guess the revisions in teaching really happen over semesters rather than hours - you learn from your mistakes, run the next discussion a little better, and revise your future lectures. Both writers and teachers get better with practice.
I'm not sure. I remember one hilarious day in upper sixth chemistry when we'd managed to tie ourselves and our teacher into phys-chem knots so tight we were forgetting really basic maths. The teacher after about half-an-hour just said "sod this", promised us a properly revised lesson next week, and set us playing at quantative analysis of whatever was on the shelf for the rest of the lesson. Then, next class, we did manage to sort out the theoretical stuff too.
I like the sentiment, although I'd add that students are largely obliged to go to classes, while readers are never obliged to read.
True, although even if attending in body is obligatory, attending in mind is hard to enforce.
Anecdotally, the percentage of students attending large lecture classes with their laptops seems to be hovering around 65-70%. Surely some of them are taking notes, but sit in the back of such a lecture hall, and you'll quickly notice that the majority of them are on facebook, doing online shopping, reading the news, emailing, and so on. (Some, of course, think they can multi-task. They're usually wrong.)
The brain emits a signal as soon as it sees something interesting, and that "aha" signal can be detected by an electroencephalogram, or EEG cap. While users sift through streaming images or video footage, the technology tags the images that elicit a signal, and ranks them in order of the strength of the neural signatures. Afterwards, the user can examine only the information that their brains identified as important, instead of wading through thousands of images. No existing computer vision systems connect with the human brain, and computers on their own don't do well at identifying unusual events or specific targets. "You cannot take a system that is intended to recognize faces and apply it to recognizing handwriting or identifying whether one object in a photo is behind another. Unlike a computer, which can perform a variety of tasks, a computer vision system is highly customized to the task it is intended to perform. They are limited in their ability to recognize suspicious activities or events."