Advice welcome!

I’m hoping to get advice on three points, all intersecting with EE and engineering writing and pedagogy.

First, the EE TAs are going to be trained next year (by me), and while I have a good idea of my plans, I’d like some input. What did you wish you knew when you started teaching? Now that some of you are faculty, you might have an even more urgent message about that, but anyone who was a struggling, hard-working, responsible TA probably wishes they’d been given a few ideas to work with. What are they??

Second, the School of Engineering has asked Writing Programs to teach first-year composition courses directed specifically at students who have entered as engineering majors. The one and only section (so far) of English 3E is this Fall, and we have some constraints on what we achieve in there, but I’d be interested to hear what you’d include in that class. The two new areas to be emphasized, in addition to what we already teach about college composition, are “the visual display of information” and “exposition/description” (contrast that with “argument” and you might get a sense of what it means and why it’s useful for engineers). I don’t want to focus just on engineering-related topics (engineering majors get enough engineering classes!), but I want to make sure that the course offers a helpful bridge between other disciplines, writing, and engineering. Any thoughts?

And third, I need to write on this website more often, so I’d be interested in hearing what topics you have questions about (or what stories or ideas you’d be interested in sharing here!). I will try to write a few posts in advance, so that there will be a more regular posting during the busy Fall quarter.

Thanks, in advance, for your help.

A book recommendation

I’ve just discovered a book by Robert Irish and Peter Eliot Weiss that I highly recommend. In fact, I intend to use it in EE 295 next year, instead of my EE 295 Sketchbook. It’s too bad that I can’t use both, but I don’t want students to have to make both purchases. I can always use some handouts from the Sketchbook and/or recommend that students borrow a copy from a friend for the quarter.

So what’s this great book: Engineering Communication: From Principles to Practice, 2nd edition.

I have not actually read the first edition, so it may not be that different, and you can get it for a few dollars (as opposed to $25-$65 for the second edition).

If you are working on improving your writing in engineering, I cannot recommend any book more than this one. More later–when I have time to tell you more about it.

Why a cow? I haven’t yet taken a picture of the book–and this is a beautiful cow!

Key words in key spots; paragraphs as musical movements

My class depends  on students bringing in and showing us models, and one student brought in “A Wideband Frequency-Shift Keying Wireless Link for Inductively Powered Medical Implants” by Maysam Ghovanloo and Khalil Najafi (IEEE Transactions on Circuits and Systems, 51.12, Dec 2004). The full title is here so you can access it yourself (I’d be happy to discuss these writers’ decisions in more detail with you), but I’ve tried to include examples of the two key features mentioned above so that you do not have to go find it yourself.

Key Words in Key Spots

Notice that the authors do not start with data and power transmission via inductive coupling alone. Since they are so intent upon biomedical implants, this idea goes into the first sentence of the introduction, too:

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Note that the sentence begins with “an inductive link” and ends with “prostheses”–both key words, and in the two prime spots in the sentence. Remember that the beginning and end of a sentence are the “prime real estate.”

And later, the first sentence of the last paragraph of the introduction reminds readers of these two important components of the article, (1) increasing bandwidth via the inductive method of FSK, and (2) using this to make biomedical prosthesis work better:

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Again, “FSK” is in one prime position, and “prostheses” is in the other.

Paragraphs as musical movements

The second and third paragraphs of the introduction are very clear, step-by-step discussions/explanations that boil down the problem to these authors’ point of attack. Here’s paragraph two:

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Notice how this paragraph moves from “need large amounts of data” to “a minimum of 625-1000 pixels” to specific numbers of bits in the stimulation commands, to how many bits per command frame, to  how many of those there are, to one piece of good news about lowering the required data rate, to the obvious conclusion that a high data rate is needed. It’s like the paragraph is reaching a crescendo in a musical piece, with one softening part near the end, and then a loud, loud final sentence.

Paragraph 3 does something similar with the data rates that have been achieved so far, although the data rate seems to be getting softer/lower as we add the costs/trade-offs, and then it ends with a strong determination to do better/the goal:

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If you are a musician, or if you just like to listen to music, then thinking about paragraphs as short movements in a musical composition might help you structure them so that they come across more powerfully.

An addition, to underline the importance of key words in key spots:

The American Scholar has a list of what it calls “the ten best sentences.” Here’s one, with the reasons that Roy Peter Clark gave for why it’s great:

Anger was washed away in the river along with any obligation.—Ernest Hemingway, “A Farewell to Arms”

Donald Murray used to preach the 2-3-1 rule of emphasis.  Place the least emphatic words in the middle.  The second most important go at the beginning.  The most important nails the meaning at the end.  Hemingway offers a version of that here. A metaphor of flowing water is framed by two abstractions Anger and Obligation.  That fact that the metaphor is drawn from the action of the narrative makes it more effective.

Miscellaneous Updates

I am newly committed to this website, now that the Non-Senate Faculty Grant that was to pay for it has finally been paid! Please do let me know what types of topics you’d like to see covered on here. I can just go ahead and write short entries about topics such as agency and verbs and word order and paragraphing (etc) but I’d also like to bring up broader issues that confront you now as a publishing engineer. And perhaps begin a conversation about these.

On another topic, I hope that this link to an article that I just got published will both (1) pleasantly surprise you by being on a completely different topic from usual, and (2) let you see how even a journal article in an interdisciplinary journal in the humanities and social sciences follows some similar structural rules as you engineering articles.

Here’s my publication: “New Terms of Worth”: The Inclusive Economics of Robert Frost’s Poetry. 

Even Oxford University Press has trouble with formatting. I’m hoping that this problem (the small print after the indented quotations of poetry) will be fixed soon!

Go read Edward Tufte’s books

These are not books you read in the normal way. They don’t offer lists of rules for visually displaying evidence. Instead, these books  beautifully reproduce and evaluate examples of graphs, tables, charts, diagrams, maps, “sparklines” (You’ll have to go find out what that means!), and more. They show examples from centuries of people–such as Galileo, Leonardo da Vinci, Henri Matisse, Richard Feynman, etc– trying to communicate their ideas clearly and beautifully.

Tufte also argues that producing visual representations of our ideas makes those ideas clearer to us, too. In other words–just as writing is thinking–sketching and drafting and moving visual elements around on the page are analytical tools. I can vouch for this myself. I went to Tufte’s day-long seminar last Friday, and I’ve been able to reconceive and clarify for myself the ideas in an article I finished writing two years ago but about which I am just now creating a poster. I thought I was pretty familiar with the ideas in my own completed article, and yet the sketches (and even watercolors!) have made me see the ideas more clearly and in ways that will make them much easier to talk about.

 

(The image shows Galileo’s sketch of the changing positions of Jupiter’s moons from one night to the next.)

Thomas Hager’s The Alchemy of Air

The subtitle of this book is “A Jewish Genius, a Doomed Tycoon, and the Scientific Discovery that Fed the World but Fueled the Rise of Hitler.” But if that’s not a broad enough net to grab you, let me tell you a bit more. This book describes a scientific and engineering feat on the scale of the Manhattan Project (p. 122). In achieving nitrogen fixation on a grand scale, engineer Carl Bosch turns chemist Fritz Haber’s table-top process into a huge city-size factory, and then a bigger one. In doing so, he and his many colleagues invent a whole new type of business model, solve a global crisis (starvation, by creating fertilizer to counteract inevitable soil depletion and thus a decrease in worldwide crop production), and address a national crisis (Germany’s lack of explosives with which to fight WWI).

The book is not only fascinating on the history of chemistry, especially the history of dyes, nitrogen fixation, and the development of synthetic fuels, but also incredibly moving on the human side. The two main scientists are fascinatingly contradictory characters, revealing just how inconsistent and flawed even very brilliant and hard-working humans are. The story of these two men is moving and thought-provoking. Shakespeare could have based a tragedy on these linked stories. The book reiterates the power of science to work for good and evil, but it does so in detailed and original ways, so that the lessons seem newly learned and spelled out more completely. For one, science is not just a double-edged sword: even the good edge has two edges.

These men’s ambitions, ideals, personal strengths and weaknesses, affinities, competition on a corporate or personal scale–and just their intense interests and special abilities–all combine as in a complex chemical reaction with the historical moment’s needs and the political atmosphere to create a unique result. We see how and when they control and lose control of what they create, and how they very differently react to their somewhat self-determined and somewhat uncontrollable fates.

I think an engineer would not only enjoy the book but also benefit from reading it. The story itself is interesting—the important scientific and industrial history—and it’s also  very well written. Hager demonstrates how to define terms in simple, subtle way; how to use a single sentence to clarify and re-emphasize a point that he’s discussed for pages; how to describe methods by describing the materials used; how to give scientific information in detail when needed and just sketchily when not so important; and how to link one boring-sounding topic (“nitrogen fixation” has to be one of the most off-putting nouns I can think of) to far-reaching consequences, important historical moments, philosophical questions, and global influence. The power to link your topic, whatever it is, to many other fascinating ones is worth learning!

 

Long names/nouns are easy to write but difficult to understand

First, a definition. A “noun phrase” is not the entire subject of a sentence. Your sentence might be

The brave, warmly dressed woman holding a saw and the large hawk with a rat in its mouth perch in the tree staring at each other.”

Then the subject has two noun phrases in it. It’s a collection of nouns and adjectives (or even phrases) that have been stuck together to form one long noun. Some other examples are:

power-controlled rate-adaptation interference graph and

wideband, high-resolution analog-to-digital converter.

Here are two places to find more examples: http://www.chompchomp.com/terms/nounphrase.htm and http://www.grammar-monster.com/glossary/noun_phrases.htm.

The common technique in engineering is to stick everything together in one set of adjectives and nouns, and then skip the (helpful, sometimes more explanatory) prepositional phrases. I often want you to unpack the set of adjectives and nouns and use phrases to clarify what you mean. Also, you might discover that you don’t need all that information about the noun; you might already have established this information earlier in the article, and you can just use a shorter name for this thing.

 Here’s example that a student brought in last week:

Understanding spin transport via collective magnetic excitations is currently gaining attention.

This is a refreshingly short sentence, but it’s a bit difficult to unpack (by which I mean, “interpret”). In other words, the reader has to turn the words around in his or her head in order to understand what it means. Here are some possible revisions:

Researchers are now trying to use collective magnetic excitations to understand spin transport.

Researchers are trying to understand spin transport by looking at collective magnetic excitations.

Researchers are trying to understand spin transport by looking at the way that collective magnetic excitations influence them.

But maybe none of these is  accurate. They might not be what the sentence means at all. I had to make up some possible relationships between the two topics, which would not have been necessary if the writer had clarified that relationship. Often, when I quiz students on what they mean by a sentence, we go though many revisions together before I suddenly realize what they meant, and how far that was from my guess!

Take-away message: beware the long noun phrase. If you find yourself writing one, determine if there’s some information in it that has already been clearly established; then take that part out. If it’s still ambiguous or just hard to figure out, explain the relationship between the various parts of the noun phrase.

Anything you can do to make your reader’s job easier will help assure that they are getting the message you intend to send. It will also get you more readers!

 

Short Notes Help

by Yikun Chang

According to my experience, writing is an effective way to help collect ideas, categorize them, and find logical relationships among them. Nowadays, Electronic Design Automation (EDA) tools are highly convenient. However, this fact is a double-edged sword. We become more and more dependent on simulation, and even overwhelmed by it. We sit in front of computers, set up all conditions, and then click “run.” After a while, we collect data and find something not that good. Then we adjust parameters slightly and re-run the simulation. This cycle repeats and repeats until we get lost in simulation and restart the whole flow. Fast simulation makes us little cherish the chances of running simulation, lazy to write down the simulation results, and barely spend time on carefully thinking about our design. Due to this kind of sad experience, I have learned to keep notes about research no matter how meaningless an idea or the data looks. Every time I feel lost in research, I look back at my notebook to re-organize my thoughts with some symbols like arrows or brackets. In this way, writing as well as thinking at the same time helps me figure out where the current problem comes from, and what I should focus on next. The record of the data that you previously think not important may help save a lot of time when you someday find it actually means something or need to compare it with new data.

Drama in an EE paper

I will first not-completely-but-somewhat-jokingly say that this article’s first author is a past student of EE 295, so of course he’d be doing lovely things with his writing! (I will add that he was a good writer when he started in EE 295, and that his advisor’s students are often excellent writers. The advisor is the third author on this paper. A culture of good writing, of valuing writing, seems to develop in some labs.)

This July 2015 article is “Variable-Length Convolutional Coding for Short Blocklengths With Decision Feedback” by Adam R. Williamson, Tsung-Yi Chen, and Richard D. Wesel. Since it is so recent, I will only photograph one short excerpt from the text, although somewhat more will be cited and described.

Drama is developed from the first sentence, when the authors write something along the lines, of “Although the founding father of our field found that feedback was not useful for x, feedback can be used for other purposes”:

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If that’s not dramatic, then what is? It’s dramatic when an important figure in the field is right, or wrong, or just missed noticing something important.

The way that Einstein’s thoughts on the cosmological constant have been cited and argued for and against is perhaps similar. He was right. He was wrong. (Maybe there we even some other back-and-forths, and certainly there were many amendments.) Then, a January 2013 Scientific American called “Right Again, Einstein!” starts, “A new study of one of the universe’s fundamental constants casts doubt on a popular theory of dark energy” (Moskowitz). Almost three years later (Sept 2015), “What Einstein Got Wrong” in that same magazine begins: “Like all people, Albert Einstein made mistakes, and like many physicists he sometimes published them” (Krauss). There’s something exciting and important about great thinkers having limitations, even if they might just be limitations caused by the moment of time in which they lived, and the development of their fields at that moment.

The extensive literature review of the Williamson et al. paper tells a story, too. It’s chronological: this idea was developed, and then that, and then this other one went further. It’s also got characters; the researchers are listed by their names, rather than the papers being listed by reference numbers. Once there are names, some intellectual drama can be introduced: all these authors did stuff in reaction to the work that came before: one name does “pioneering work,” another “formalizes it” or “demonstrates” something else, or “furthers” or “extends” the work. Others “study” or “show” or “provide an overview.” It’s complicated, but there are a lot of people doing stuff, cooperating even, and that’s interesting and appealing.

Storytelling Elements in EE Writing: Personification

My students give me at least as much homework as I give them.

In yesterday’s class, the elements of storytelling were doubted to be of importance in technical writing, or even academic engineering writing. So I’m looking for examples.

Here’s one, in the first article I brought up on my screen, an award-winning June 2000 article by Vítor H. Nascimento and Ali H. Sayed, “On the Learning Mechanisms of Adaptive Filters.”

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Notice the way that adaptive filters are personified in their introduction. They “adjust themselves to an ever-changing environment,” they have a “learning curve,” a “learning process,” and “learning capabilities.” An adaptive filter “reacts.” They are like humans or other species adapting to a habitat.

After seeming to personify adaptive filters, Nascimento and Sayed develop a nurturing relationship with them. The next paragraph of the introduction reads:

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Nurturing in their readers a warm feeling for adaptive filters, the authors say that “special care” must be taken with them (as with human children). “Interpreting learning curves” might be much more mathematical when it comes to adaptive filters, but these authors “care” for the slow and fast learners both, and, like a supportive and patient kindergarten teacher, they believe that slow learners end up “’smarter’” than they appear at first.

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