Showing posts with label education. Show all posts
Showing posts with label education. Show all posts

Friday, July 17, 2020

My favorite "high yield" guides to telling better stories

Guest post by Eric Sanford


In medical school, we usually have five lectures’ worth of new material to memorize each day. Since we can’t simply remember it all, we are always seeking “high yield” resources (a term used so often by med students that it quickly becomes a joke): those concise one or two-pagers that somehow contain 95 percent of what we need to know for our exams. My quest of finding the highest yield resources has continued in full force after becoming a PhD student.


A major goal of mine has been to improve my scientific communication skills (you know, writing, public speaking, figure-making… i.e. those extremely-important skills that most of us scientists are pretty bad at), and I’ve come across a few very high yield resources as I’ve worked on this. Here are my favorites so far:


Resonate, by Nancy Duarte:

  • The best talks are inspiring, but “be more inspiring” is not easy advice to follow.

  • This book teaches you how to turn your content into a story that inspires an audience.

  • I received extremely positive feedback and a lot of audience questions the first time I gave a talk where I tried to follow the suggestions of this book.

  • This was both the most fun and the most useful of all my recommendations.


The Visual Display of Quantitative Information, by Edward Tufte:

  • Tufte is probably the most famous “data visualization” guru, and I think this book, his first book, is his best one. (I’ve flipped through the sequels and would also recommend the chapter on color from “Envisioning Information.”)

  • This book provides a useful framework for designing graphics that convey information in ways that are easy (easier?) for readers to understand. Some pointers include removing clutter, repeating designs in “small multiples”, labeling important elements directly, and using space consistently when composing multiple elements in the same figure.


The Elements of Style, by Strunk and White, pages 18-25:


Words to Avoid When Writing, by Arjun Raj


Raj Lab basic Adobe Illustrator (CC) guide, by Connie Jiang


There are many other great resources out there that are also worth going through if you have the time (Style: Lessons in Clarity and Grace by Bizup and Williams is another excellent writing guide), but for me these ones above had the highest amount-learned-per-minute-of-concentration-invested. 



Guest post by Eric Sanford



Saturday, May 9, 2015

Thoughts on taking my first class in over a decade

Some folks in our lab (including myself) have embarked on a little experiment, which is semi-informally taking a machine learning class this summer. We’re taking a machine learning class over the summer in a self-directed manner, including doing all the homeworks. The rules are that the people who don’t do the homework have to pay for the lunches of the people who do do the homework. So far, everyone’s paid for themselves. For now… :)

Anyway, this is the first class I’ve taken in well over 10 years (although I’ve taught a bunch since then), and I’m enjoying it immensely! It also feels very different than when I took classes in the past. Firstly, I’m definitely slower. I’m taking way longer to get through the problems. At least partly, I think this is because my brain is not quite as quick as it used to be, for sure. Not sure if that’s just from having a lot of distractions or lack of sleep or just the aging process, but it’s definitely the case. Lame.

Also, I’m slower because my approach to every question is very different than it used to be. When I was an undergraduate taking a bunch of classes, a lot of the time I was just trying to get the answer. Now, with a lot more experience (and a very different objective function), I’m far less concerned with getting the right answer, and so I of course spend a lot more time trying to understand exactly how I arrived at the answer.

More interestingly, though, is the realization that beyond just trying to understand the answer, I’m also spending a lot more time trying to understand why the professor asked the question in the first place. For instance, I just worked through an example of a decision tree and entropy, and while I think my earlier self would have just applied the formulas to get the answer, now I really understand why the problem was set up the way it was and why it’s trying to teach me something. This is something I think I’ve come to appreciate a lot more now that I’ve taught a few courses and have designed homework and exam questions. When I write a question, I’m usually trying to illustrate a particular concept through an example (though I typically fail). As a student, I think I typically missed out on these messages a lot of the time both because I was more concerned with getting the answer and because I didn’t have the context in which to understand what the concept was in the first place. Now, I’m purposefully trying to understand why the question is there in the first place from the very get go.

(Note: it’s really hard to devise questions that reveal a concept to the student. Lots of reasons, but one of them is that I feel like concepts come across best through interaction. Problems for classes, though, typically have to be well defined with clear statements and solutions. In a way, that’s the worst way to get a concept across. Not sure exactly what the right way to do this is.)

Another thing I’ve noticed is that every mathematical operation I perform, from doing an integral to inverting an equation, seems far more meaningful than it used to. I think it’s because I feel like I have a much deeper understanding of why they come up and what they mean. That makes computations a bit slower but far more purposeful (and with less time spent on fruitless directions).

Which leads to another point, which is that I tend to make fewer mistakes than I used to, especially of the silly variety. I think this is because in our research, a mistake is a mistake, silly or not, and having the right answer is the only one that matters. So I’ll take it slow and get it right more often than before, which is a somewhat amusing change from the past.

Anyway, overall, a really fun experience, and one that I highly recommend if you haven’t taken a class in a while.

Saturday, November 8, 2014

“Edge of Tomorrow” and the case for better education

I just watched Edge of Tomorrow, a recent action movie with Tom Cruise, and it got me thinking about education. In case you haven’t seen it, it’s basically an action movie version of Groundhog Day, where Tom Cruise lives the same day over and over until he saves the world from alien invaders. Umm, well, that last sentence sounded pretty stupid, but I actually thought it was a pretty good movie.

Anyway, in the movie, Tom Cruise (Sgt. Cage) enlists the help of Emily Blunt (Rita Vrataski, super badass alien killer), and every time he relives the same day, he makes it a little further towards killing the aliens with her. He remembers everything that happened, but she remembers nothing. That means that he has to teach her everything that he has collectively learned every day, which is of course limited by the capacity that she has to absorb all that information. It occurs to me that our own lives are a lot like Rita’s day. Each of us is born knowing nothing, and we have exactly one lifetime to learn the collective knowledge of the world (and hopefully add to it) before we die. As our civilization’s knowledge burgeons, we have to get better at cramming this stuff into our kids' brains, because they still just have one lifetime to learn an ever increasing sum of knowledge and then to use it. Somehow, thinking about it this way makes me think that it’s really sad that we haven’t paid as much attention to how we educate as we should. I mean, I guess I already knew that, but it just seems to take on a bit more urgency for me when I think about it this way.

Hmm. I can’t believe I just made an analogy between Tom Cruise and the collective knowledge of the world. I need a drink.

Sunday, September 14, 2014

University admissions at Ivy Leagues are unfair: wah-wah-wah

Lots of carping these days about university admissions processes. Steven Pinker had some article, then Scott Aaronson had a blog post, both advocating a greatly increased emphasis on standardized testing, because the Ivy League schools have been turning away academically talented but not “well-rounded” students. Roy Unz (referenced in the Pinker article) provides some evidence that Asians are facing the same quota-based discrimination that Jewish people did in the early 20th century [Note: not sure about many parts of the Unz article, and here's a counter–I find the racial/ethnic overtones in these discussions distasteful, regardless of whether they are right or wrong]. Discrimination is bad, right? Many look to India, with its system of very hard entrance exams to select the cream of the crop into the IIT system and say, why not here?

Yeah. Well, let me let you all in on a little secret: life is not fair. But we are very lucky to live here in the US, where getting rejected from the Ivies is not a death sentence. Aaronson got rejected from a bunch of schools, then went to Cornell (hardly banishment to Siberia, although Ithaca is quite cold), then went on to have a very successful career, getting job offers from many of the same universities that originally rejected him. It’s hard not to detect a not-so-subtle scent of bitterness in his writing on this topic based on his own experience as a 15 year old with perfect SATs, a published paper and spotty grades, and I would say that holding on to such a grudge risks us drawing the wrong lesson from his story. Yes, it is ironic that those schools didn’t take him as an undergraduate. But the lesson is less that the overall system is broken, but more that the system works–it identified his talent, nurtured it and ultimately rewarded him for it.

Those who look elsewhere to places like India have it wrong, also. The IITs are rightly regarded as the crown jewels of Indian education. The problem is that the next tier down is not nearly so strong, thus not nurturing the talents of all those who were just below the cutoff for whatever reason. So all those people who don’t manage to do as well on that one entrance exam have far less access to opportunities than they do here. Despite these exams, India is hardly what one would call a meritocratic society. So again, I would not consider India a source of inspiration.

I understand the allure of something objective like an SAT test. The problem with it is that beyond a certain bar, they just don’t provide much information. There are tons of kids with very high SATs. I can tell you right now that my SATs were not perfect, but I’m pretty sure I’m not that much less "smart" than some of my cohort who did get perfect SATs. I did terribly on the math subject GRE–I’m guessing by far the worst in my entering graduate school class–which almost scuppered my chances of getting into graduate school, but I managed to get a PhD just fine. At the graduate level, it is clear that standardized tests provide essentially no useful predictive information.

I think we’ve all seen the kid with the perfect grades from the top university who flames out in grad school, or the kid from a much less prestigious institution with mixed grades who just nails it. Moreover, as anyone who has worked with underrepresented minorities will tell you, their often low standardized test scores DO NOT reflect their innate abilities. There are probably many reasons for why, but whatever, it’s just a fact. And I think that diversity is a good thing on its own.

So scores are not so useful. The other side of the argument is that the benefits of a highly selective university are immense–a precious resource we must carefully apportion to those most deserving. For instance, Pinker says:
The economist Caroline Hoxby has shown that selective universities spend twenty times more on student instruction, support, and facilities than less selective ones, while their students pay for a much smaller fraction of it, thanks to gifts to the college.
Sure, they spend more. So what. I honestly don’t see that all this coddling necessarily helps students do better in life. Also this:
Holding qualifications constant, graduates of a selective university are more likely to graduate on time, will tend to find a more desirable spouse, and will earn 20 percent more than those of less selective universities—every year for the rest of their working lives.
Yes, there is some moderate benefit, holding “qualifications constant”–I guess their vacations can last 20% longer and their dinners can be 20% more expensive on average. The point is that qualifications are NOT constant. The variance within the cohort at a given selective university is enormous, dwarfing this 20 percent average benefit. The fact is that we just don’t know what makes a kid ultimately successful or not. We can go with standardized testing or the current system or some other system based on marshmallow tests or what have you, but ultimately we just have no idea. Unz assembles evidence that Caltech is more meritocratic, but so far there seems to be little evidence that the world is run by our brilliant Caltech-trained overlords.

What to do, then? How about nothing? Quoting Aaronson:
Some people would say: so then what’s the big deal? If Harvard or MIT reject some students that maybe they should have admitted, those students will simply go elsewhere, where—if they’re really that good—they’ll do every bit as well as they would’ve done at the so-called “top” schools. But to me, that’s uncomfortably close to saying: there are millions of people who go on to succeed in life despite childhoods of neglect and poverty. Indeed, some of those people succeed partly because of their rough childhoods, which served as the crucibles of their character and resolve. Ergo, let’s neglect our own children, so that they too can have the privilege of learning from the school of hard knocks just like we did. The fact that many people turn out fine despite unfairness and adversity doesn’t mean that we should inflict unfairness if we can avoid it.
A fair point, but one that ignores a few things. Firstly, going to Cornell instead of Harvard is hardly the same thing as living a childhood of neglect and poverty. Secondly, universities compete. If another university can raise their profile by admitting highly meritorious students wrongly rejected by Harvard, well, then so be it. Those universities will improve and we’ll have more good schools overall.

Which feeds into the next, more important point. As I said, it’s not at all clear to me that we have any idea how to select for “success” or “ability”, especially for kids coming out of high school. As such, we have no idea where to apportion our educational resources. To me, the solution is to have as many resources available as broadly as possible. Rather than focusing all our resources and mental energy into "getting it right" at Harvard and MIT, I think it makes much more sense to spend our time making sure that the educational level is raised at all schools, which will ultimately benefit far more people and society in general. The Pinker/Aaronson view essentially is that this is a “waste” of our resources on those not “deserving” of them based on merit. I would counter first that spending resources on educating anyone will benefit our society overall, and second that all these “merit” metrics are so weakly correlated with whatever the hell it is that we’re supposedly trying to select for that concentrating our resources on the chosen few at elite universities is a very bad idea, regardless of how we select those folks. The goal should be to make opportunities as widely available as possible so that we can catch and nurture those special folks out there who may not particularly distinguish themselves by typical metrics, which I think is the majority, by the way. A quick look at where we pull in graduate students from shows that the US does a reasonably good job at this relative to other places, a fact that I think is related to many of this country’s successes.

As I said before in the context of grad admissions, if you want to figure out who runs the fastest, there are a couple ways of going about it. You can measure foot size and muscle mass and whatever else to try to predict who will run fastest a priori–good luck with that. Or you can just have them all run in a race and see who runs the fastest. And if you want to make sure you don’t miss the next Usain Bolt or Google billionaire, better make the race as big and inclusive as possible.

Thursday, July 10, 2014

Undergrad class FAQ

Every semester, I get some questions from my undergrads, and in the interest of efficiency, I thought I'd post the answers here as an FAQ.  Feel free to modify for your own use as you see fit.

Q: When is the midterm?
A: Feb. 14th.

Q: I have a [job interview/wedding/film festival (seriously, I got this)] during the quiz, but I'll have some time Wednesday at 2pm. Can I make it up then?
A: No.

Q: Is this going to be on the exam?
A: Most of the material I cover in class and assign homework on will be fair game for the exam, with emphasis on homework problems. I will probably not ask you to produce derivations.

Q: Is this class graded on a curve?
A: Yes, I will take into account the class average and overall performance when assigning grades.

Q: What is my grade?
A: It's hard to say, given that I don't yet have the complete picture of the class performance.

Q: Is this going to be on the exam?
A: Material from class is fair game for the exam except when explicitly noted.

Q: Is this class graded on a curve?
A: Yes, I will grade on a curve.

Q: What is my grade?
A: I don't know yet.

Q: Is this going to be on the exam?
A: Yes.

Q: Is this class graded on a curve?
A: Yes.

Q: What is my grade?
A: B.

Q: Is this going to be on the exam?
A: Yes.

Q: Is this class graded on a curve?
A: Yes.

Q: What is my grade?
A: B.

Q: Is this going to be on the exam?
A: Yes.

Q: Is this class graded on a curve?
A: Yes.

Q: What is my grade?
A: C.

Wednesday, July 2, 2014

I think the Common Core is actually pretty good

Just read this article on NYTimes.com about people pushing back on the Common Core, which is about how a lot of parents and educators are pushing back against the "Common Core", which emphasizes problem solving skills and conceptual understanding over rote application of algorithms, i.e., plug and chug. I can't say that I'm super familiar with the details of the Common Core, but I can say that I now that I have taught the undergrads at Penn who are the products of the traditional algorithmic approach, it is clear to me that the old way of teaching math was just not cutting it. Endless repetitions of adding and subtracting progressively longer numbers is not a way to train people to think about math, as though the ability to keep numbers ordered is a proxy for conceptual understanding. I think many of the critiques of Common Core actually show many examples that seem to highlight just how much better the Common Core would be at teaching useful math.

Take as an example adding two digit numbers. I don't know anybody who does math as a part of their job who does the old "carry the 1" routine from elementary school. To me, a far better way to add numbers (and is the basis for the algorithm) is realize that 62+26 is 60+20 + 2+6. This is exactly the object of ridicule #7 in the previous link. I've been teaching my son how to add and subtract this way, and now he can pretty easily add and subtract numbers like these in his head (and no, he is not a math genius). From there, it was pretty easy to extend to other numbers and different situations as well, like, say, 640+42 and the such. I see absolutely no point in him even bothering to learn the old algorithms at this point. I think that those of us who developed mathematical skills in the old curriculum probably succeeded more despite the system than because of it.

The results of decades of algorithmic learning are students who have little conceptual understanding, and even worse, are frankly scared to think. I can't tell you how many students come to my office hours who essentially want me to spoon feed them how to solve a particular problem so that they can reproduce it correctly on a test. The result is people whose basic understanding is so weak and algorithmic that they are unable to deal with new situations. Consider this quote from the NYTimes article from a child complaining about the Common Core:
“Sometimes I had to draw 42 or 32 little dots, sometimes more,” she said, adding that being asked to provide multiple solutions to a problem could be confusing. “I wanted to know which way was right and which way was wrong.”
Even at this young age, already there is a "right way" and a "wrong way". Very dangerous!

I'm sure this Common Core thing has many faults. Beyond the obvious "Well, if it was good enough for me, grumble grumble harrumph!" reactions, I think there are probably some legitimate issues, and some of it probably stems from the fact that teaching math conceptually is a difficult thing to systematize and formalize. But from what I've seen, I think the Common Core is at least a big step in the right direction.