Tag Archives: writing advice

Introducing the hard stuff

My class this quarter has gotten used to us talking about the “topography” of any piece of writing. It seems to be a helpful word in many situations, but now I want to discuss the varying levels (or altitudes) of difficulty as one moves through the landscape of the text. Sometimes the writing is hard, and sometimes it’s got to be easy (or the reader will give up). This variation is mandatory in public science writing, but you might be kind enough to give your readers a break in your academic writing, too.

In his (public-focused but pretty difficult) 2017 book Behave: The Biology of Humans at Our Best and Worst, Robert Sapolksy writes these two paragraphs as part of the introduction to an early chapter:

This chapter is one of the book’s anchors. The brain is the final common pathway, the conduit that mediates the influences of all the distal factors to be covered in the chapters to come. What happened an hour, a decade, a million years earlier? What happened were factors that impacted the brain and the behavior it produced.

This chapter has two major challenges. The first is its god-awful length. Apologies; I’ve tried to be succinct and nontechnical, but this is foundational material that needs to be covered. Second, regardless of how nontechnical I’ve tried to be, the material can overwhelm someone with no background in neuroscience. To help with that, please wade through appendix 1 around now.

(pp. 21-2)

Notice several things here:

1. He offers “metacommentary” that communicates these messages: “What I’m about to say is important.” “This is complicated, but I’m doing my best to make it as easy and clear as possible.” “If you have not taken neuroscience, then go read Appendix 1.”

2. He offers motivating questions for this section: “how does the brain work?” and “how did the brain get the way it is?”

3. That last question is attached to the book’s overall argument in that first paragraph above: he is trying to explain all the factors that go into our behavior, factors that are immediately present and factors that happened long ago. If you’re going to make readers work hard at something, they need to know that there’s a really important reason for them to do so!

4. He uses numbers. Imagine that second paragraph without the numbers, and you will be seeing a less clear paragraph. It’s very satisfying for readers to know exactly how many ideas they are about to get, and then to tick them off. “Two. Okay: One, Two. Done!”

5. He uses the word “distal.” I probably would have avoided that. I had to look it up. It basically means “distant,” but it’s more specific to anatomy.

If you actually go read the rest of Sapolky’s book, you’ll see him describing the way that our emotional experience influences our intellectual decisions. If your readers get frustrated—especially if they think that this is more your fault than theirs—then they are going to be less likely to make positive evaluation. Their emotions, not just logic, will influence their decisions.

Freedom within expectations

If you tell someone you’re an engineer, you might then get the feeling that they think that they know a lot about you already. Engineers—like people in many careers—have to contend with all sorts of presumptions about their personalities. That’s one reason why #ilooklikeanengineer was popular and important. That movement emphasized that women are engineers, but the presumptions can work against everyone. Engineers are not just (and not always) introverted and analytical. That’s just a stereotype. Engineers are all sorts of other ways, too: active, athletic, enthusiastic, assertive, creative, instinctive, chatty, disorganized, artistic, and friendly–and they have as many individual interests as there are individuals.

What this means is that you are always contending with a stereotype. If you are aware of it—and how could you not be?—you are always deciding if you want to conform to peoples’ assumptions or not. And you probably make different decisions in different situations. It’s sometimes easier just to let others think you are brilliant and quiet: they are giving you the benefit of the doubt, and you don’t have to explain yourself. Other times, it’s convenient and even maybe fun to break the stereotype: surprising people can get their attention. If you think back, you can probably think of many examples of yourself doing one or the other.

And here’s why I said all this: the same goes for genres of writing. Each type or category of text shares characteristics. Academic journal articles in electrical engineering are (1) about EE, (2) written in formal English using some language only known to people in the specific field (but not exclusively this type of language), and (3) follows a certain structure (AIMRaD, and then similar structures within each of those sections). If you were to look at a single journal article, you could define that journal’s genre of academic writing even more specifically. And then you could mimic it, structuring your own ideas in an article that fit the expectations of that journal.

But then think about your identity again. How much do you want to conform? If you looked at several articles in that journal, you would notice a range of acceptable writing choices. You would see characteristics they all share (posing a problem, giving a result, etc.) and you’d see variation (in how much context is offered, perhaps, or how many field-specific terms are defined, or the clarity of the figures and captions). Seeing this variation enables you to stop just mimicking a genre. Instead, you can take into account your own goals and values, and then make the decisions that allow you to stay within the general range of the journal’s expectations but still express yourself as you choose.

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:

Screen Shot 2016-04-18 at 8.57.42 AM

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:

Screen Shot 2016-04-18 at 8.57.55 AM

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:

Screen Shot 2016-04-18 at 9.19.08 AM

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:

Screen Shot 2016-04-18 at 9.20.34 AM

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.

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”:

Screen Shot 2015-10-27 at 2.10.30 PM

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.”

Screen Shot 2015-10-27 at 12.56.56 PM

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:

Screen Shot 2015-10-27 at 12.59.09 PM

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.

Researching without writing is like chewing without swallowing (or swallowing without chewing)

by SV

As scientists, we love to get caught up in our work. We spend countless hours in our own heads, sporadically jotting down notes on the back of an envelope or a nearby white board only to throw the envelope away or erase the board the next day. The most common justification for this sort of behavior is that ”science takes time” and ”research should never be publication focused.”

The truth of the matter is: We are lazy. It is very easy to justify a day spent doing nothing if we can blame it on this one problem we have been stuck on for months. Rather than focus our thoughts and put them on paper, we prefer to leave them as evasive thoughts in our head. Every paper I have ever written began a couple of weeks before the deadline. There was always some problem that I had been struggling with for months, but given that the due date was mere days away, I had no choice but to start writing, in the hopes that the issue would resolve itself through some sort of miracle.

And it always did. Only it wasn’t a miracle. After a couple of these kinds of occurrences, I realized that my ability to perfectly align solutions with deadlines had nothing to do with luck, faith, or countless hours spent in the middle of the night. It was the very motion of writing. See, by typing out my thoughts, pouring my heart and frustration onto a piece of paper, I suddenly had a new perspective.

So my advice to every one who is struggling with that one detail in their proof is: Write it out. Not on the back on envelope. Not on the white board. Type it up like you’re about to submit it to your dream journal. Get the template. Make nice figures. You will soon feel like a reviewer rather than an author. And that perspective might just be all it takes.

Your writing process

What is your writing process?

When and where do you like to write, and why?

What sort of on-going writing to do you, as you think and do research?

How do you know that it’s time to start writing a more formal article (a conference paper or journal article)?

How do you prepare to write?

What do you work on first?

As you’ve gotten more experience, what are the most important things you’ve learned about writing or your particular writing process?