Tackling the dissertation proposal

Leonard Cassuto offers reasonably good advice on preparing for, and preparing, a dissertation proposal. Standards and expectations vary from field to field and department to department (even within a field) so take the advice with some caution, but as he says, “consult your advisor”!
In a commentary on Cassuto’s article, Daren Brabham adds this very important point:

I want to emphasize that the prospectus document is meant to get you to the meeting so you can talk about your project in front of a panel of experts. The meeting is meant to help clarify issues that may have occluded your view and to engage in a conversation with your committee about the work you plan on doing. Defense, may in fact be the wrong posture for these meetings. I found that my committee members asked tough and important questions, listened carefully to my responses, and pushed me–all of this was not to make me defensive about my project but to aid in widening my field of vision so that I could see important issues I was missing. What emerged is a set of lingering questions that I must attend to in my dissertation, but the tone of the meeting was never defensive. Instead, I found my meeting to be a rigorous and challenging conversation with experts in the field. This conversation model is important because as we progress beyond comps and through the dissertation process we emerge as colleagues instead of students. These meetings, as conversations, help facilitate that movement.

Deliberate practice, delaying automaticity, developing expertise

I wrote a blog entry in my music blog about what the “deliberate” part of “deliberate practice” means. The results of Ericsson and other psychologists on the role that deliberate practice has on expertise acquisition — possibly to the extent that “talent” is irrelevant — are fairly well known. But what is deliberate practice? It is assuredly not just lots of repetitive practice. See my entry in From the Bench.

Connective learning

I’ve been running into some discussions about “connectivist teaching”. The term apparently was coined by George Siemens [1]. Siemens and other refer to it as a “learning” theory, but Plon Verhagen points out that it is not so much a theory about how people learn, as it is a method of pedagogy for the digital age.
The central idea seems to be to teach through a process of having the learner build a network of nodes and connections, drawing together various resources and various ideas. In practice, the focus seems to be on “know-where” instead of “know-how” or “know-what”: learning where to find information, and how to move through a network of varied sources, assessing quality and reliability as you go.
Here is a simple class project presented as a YouTube video that illustrates the practice.
Siemens and Downes have offered an ongoing online course called “Connectivism and Connective Knowledge“. Siemens presents ideas and resources for e-learning at his elearnspace site.
[1] ”Connectivism: A Learning Theory for the Digital Age”, International Journal of Instructional Technology and Distance Learning, Vol. 2 No. 1, Jan 2005

Various suggestions for PhD students

Greg Mankiw, Harvard Econ professor, best-selling textbook author, and former Chair of President Bush’s Council of Economic Advisors, maintains a blog to communicate various ideas, mostly to his undergrad students. Last year he posted advice to undergrads; many then asked him to post advice to graduate students. He did…or rather, he posted links to the web pages of about 10 other economists who had already done so. I am now continuing the chain by pointing you to Greg’s listing of links to advice to grad students. Many of these are tailored for Econ Ph.D. students, but most are useful more broadly.
Greg was my classmate while I was getting my Ph.D. at MIT. In fact, when I took early prelims in February of my second year, the others sitting the prelims on the same day were Greg, Andrei Schleifer (Harvard prof.), Roland Benabou (MIT prof.) and Bruce Meyer (Northwestern prof.). I’ve often said my main glory at MIT was that I didn’t fail the prelim that day, given the competition.

Sleep and scholarship

I have been chronically sleep-deprived since college. Perhaps as a consequence, I have become interested in sleep research over the years (and I have been diligent about trying to teach my kids good sleep hygiene!).
Not a lot is known about the role of sleep for cognitive activities, but much more is known than a couple of decades ago. What does this have to do with scholarship? Many research studies indicate that long-term memory formation, learning, complex skill performance, and creativity are strongly affected by sleep patterns.
A good place to start learning about sleep research is Stanford Professor William Dement’s The Promise of Sleep. He explains the basic physiology of the sleep cycle and summarizes the state of sleep research (as of about 2000), with interesting results on memory, reaction time, learning, etc.
A lengthy article in today’s New York Times reports on research by Dement, recent work by Prof. Matthew Walker at Berkeley, and others, on the role of sleep in learning and memory. For example, there is a large body of evidence now that the period of deep sleep that occurs relatively early during a normal night of sleep is crucial for encoding and strengthening declarative memory (like memorized facts).
Stage 2 sleep, on the other hand, which mostly occurs during the second half of the night, seems critical for mastering motor tasks (like playing the piano).
A story on LiveScience.com reports on other research by Walker showing that emotional responses to negative stimuli dramatically intensify in the sleep-deprived.
Po Bronson wrote another lengthy journalistic article summarizing research on sleep and learning in New York Magazine (2007).
One piece of suggestive evidence that I find particularly compelling (because of my passion for playing the piano): In his famous studies on deliberate practice and expertise acquisition, K. Ericsson and co-authors reported that the best violinists got measurably more sleep than good violinists and teachers, and also took more naps (1993).

Should the digital revolution lower standards for truth?

Should students or scholars cite to Wikipedia as a reliable source? I admit that I have cited Wikipedia once or twice, though only to provide an informal definition and examples of a recent concept (for example, I recently pointed to it for emerging variants on spam such as spim, splog, spit, etc.).
The Middlebury College History Department has ruled that its
students may not cite Wikipedia in research papers or exams (via NY Times). This was prompted in part by six students who recently made the same error by relying on Wikipedia to study for a Japanese history exam.
My inclination is to agree. Rapidly decreasing costs of communications and computation gave us networked information resources, which provide much faster and cheaper access to vast quantities of information. A somewhat unexpected consequence has been that many people are confusing accessibility for reliability, and quote willy-nilly because “it’s on the Internet”. If more information is more readily available, wouldn’t we expect to see people become more selective in picking sources? Certainly, I think that is what I think we teachers and scholars should promote: a higher, not a lower standard.
The leaders of the Wikipedia project do not apparently disagree. Founder Jimmy Wales is quoted in the NYT article as saying that students shouldn’t rely on any encyclopedia as a citation for research. The following statement appears (at the moment!) on the meta-page Wikipedia:About,

While the overall [quality] trend is generally upward, it is important to use Wikipedia carefully if it is intended to be used as a research source, since individual articles will, by their nature, vary in standard and maturity.

Interestingly, one of the three core principles for Wikipedia content is that it be verifiable.

“Verifiable” in this context means that any reader should be able to check that material added to Wikipedia has already been published by a reliable source.

While, if scrupulously and professionally followed, this principle would ensure that we could rely on Wikipedia as a reliable source, I think the main point is different: every statement in Wikipedia, if correct, can be found in a more reliable source elsewhere. Careful students and scholars can search out the more reliable sources.
Indeed, many people I know (including me) advocate using Wikipedia primarily in this way: as an introduction or convenient overview of a topic, identifying facts or ideas that the scholar then verifies elsewhere, in more reliable sources.

Feynman on Problem Solving

I thought the following passage by Richard Feynman was a nice statement of problem-driven learning. Don’t read passively: try to figure out how to solve the problems yourself, using the book or article as a touchstone to check your ideas. (Feynman was one of the leading physicists of the last generation.)
In this quote, Feynman is initially referring to learning the basic theory of a computer as a set of commands that can perform operations. But the main point is how to learn from problem-solving.

Now there are two ways in which you can increase your understanding of these issues. One way is to remember the general ideas and then go home and try to figure out what commands you need and make sure you don’t leave one out. Make the set shorter or longer for convenience and try to understand the tradeoffs by trying to do problems with your choice. This is the way I would do it because I have that kind of personality! It’s the way I student — to understand something by trying to work it out or, in other words, to understand something by creating it. Not creating it one hundred percent of course; but taking a hint as to which direction to go but not remembering the details. These you work out for yourself.
The other way, which is also valuable, is to read carefully how someone else did it. I find the first method best for me, once I have understood the basic idea. If I get stuck I look at a book that tells me how someone else did it. I turn the pages and then I say ‘Oh, I forgot that bit’, then close the blook and caorry on. Finally, after you’ve figured out how to do it you read how they did it and find out how dumb your solution is and how much more clever and efficient theirs is.! But this way you understand the cleverness of their ideas and have a framework in which to think about the problem. When I start straight off to read someone else’s solution I find it boring and uninteresting, with no way of putting the whole picture together. At least, that’s the way it works for me!
Throughout the book, I will suggest some problems for you to play with. You might feel tempted to skip them. If they’re too hard, fine. Some of them are pretty difficult! But you might skip them thinking that, well, they’ve probably already been done by somebody else; so what’s the point? Well, of course they’ve been done! But so what? Do them for the fun of it. That’s how to learn the knack of doing things when you have to do them.

Richard P. Feynman, Lectures on Computation (Perseus Publishing: Cambridge, MA), 1996, p. 15.