Here is a brief presentation of that same talk that I give my students, which may be useful to prospective or continuing students; if you do read it, remember that it is a personal view. It also necessarily relates a little to my own research area, because in very different fields, the process may be different also (as in fields where empirical studies is a large component of research).
It is probably easier to view the material below if you resize your browser window to the widest possible size.
See also my tips on research reading after the presentation, or download it here.
As we go down the long road from first grade to Ph.D., the two basic changes
are: (a) we take more and more responsibility for our own learning, instead of
assuming it is on teachers and parents, and (b) more and more, the balance
of our learning shifts to how to learn, rather than learning specific
As many people have pointed out, a funny thing happens if you extend the definition of an expert to the logical extreme after the manner of the Dirac Delta function: the best expert is somebody who knows "everything" about "nothing"! Realistically, we would stop short of this ideal, while there is still something we actually are an expert on!
|The forward direction is obvious - you go through these stages successively. As the backward arrows indicate, it is often necessary to backtrack from the modeling to the problem definition or even the literture review stage. There is also a possible backtrack from the validation stage - if you find your wonderful new algorithm is 10 times worse than the well-known dumb one, you have to re-think your contribution. A particularly unpleasant backtrack is the one leading back from the archival stage, which can lead all the way back to square one, much like the biggest snake in "Snakes and Ladders". This happens when you submit your perfect paper to a conference or journal, and a reviewer points out some elementary mistake which invalidates the whole thing; or maybe they just say "this exact thing has already been published - see paper such-and-such." Unpleasant as it is, this happens on occasion; this is why we do not consider any research project finished until the results have been archived in some peer-reivewed forum.|
|There is a line just before the "Problem modeling" part because essentially the part of the paper before that is tutorial in nature. If you read several papers on the same topic, the content of each upto this point are going to be very similar to each other. This helps in understanding a research area, and saves on the reading effort.|
|See also the "Reading for Research" section just after this presentation.|
There are two basic considerations that must be honored in finding a research
A couple of techniques that can help are:
This is often the scary part. Many students back away from research because
of this very thing, that the "spark" is not possible produce on order. My
favorite example here is that of lawn mowing. Suppose you have to mow your
lawn, sometime in the next month. You cannot mow the lawn if it is raining,
or if it rained in the last 24 hours. You obviously cannot produce two
successive rain-free days on order. Will you despair?
The point is that things which are not possible to produce on order may nevertheless not be rare, especially if one puts oneself in a receptive position. In research, you can do this by reading in that area, and trying out simple ideas which you can produce without any "sparks". Remember the dictum that "luck" is just opportunity meeting preparednesss. Without a lot of preparation, you will always have bad luck. But hard work is guaranteed to change your luck. Abraham Lincoln is credited as having said: "If I had eight hours to cut a tree, I would spend six of them sharpening the saw." Whenever you think you have nothing to try, sharpen the saw, don't underestimate the role of perspiration, and the lightbulb will come on, sooner or later.
Very few of us are lucky enough to make intellectual advances that are so
pure and abstract that it stands by itself in the mathematical space. Most of
us engineers do things that require validation - the ultimate proof of the
pudding is in the eating.
Knowledge is not useful if it is not shared. Perhaps it is not even knowledge. Also, sharing provides a necessary step in validating - no matter how much validation you yourself carry out, you could be consciously or unconsciously fooling yourself. In science, we must honor the concept of experimental reproducibility - ideally, another researcher reading your paper should be able to reproduce your experiments just from the information in your paper.
People don't have as much time as they like. You yourself have very little
time for others. Some of the others have even less time than that for you.
If you will get only 20 minutes to present the research work that took you a
year, it is worth a week or two to get ready to utilize those 20 minutes
as best as possible.
Remember that in a technical presentation, the audience is expected to challenge you, and you are expected to address the issue raised clinically and correctly. Do not put anything on the slides or say anything that you cannot defend. You will be challenged and tested on your understanding of the topic you are presenting. In fact, if you get absolutely no questions during the presentation or at the end, this means you have completely failed, because nobody listened to what you said.
Note: Even the most experienced speaker flounders when trying to speak accompanying slides without preparation and practice. Plan what you will say for each slide you have; practice if possible. Have speaker notes and/or the source papers handy if you think they will help.
|Similar considerations as above. Language, grammar, spelling, all matter. It is not other people's privilege to read about your research - it is your privilege to have them read it. Make it as easy for them as possible, and as difficult to mis-understand as possible.|
The last few slides, starting with this one, is a general overview on the
scientific method. For a more detailed exposition, I can do no better than point to the book by Sagan that I have cited. I recommend it to anybody that has
anything to do with science.
I hope this helped you. If it did, feel free to point links to it or use the material otherwise; but please do credit the source.
For each paper, answer the question "Does this paper address the same research question (part c) as the seed paper?" For most papers on your list, you will only need to read the title, or a few sentences in the abstract or at most the entire abstract, before ruling them out. For papers which seem as if they might be related to the seed paper, you should delve deeper to decide. You will have to read beyond the abstract for these - you should definitely read the introduction section, and the context or background section is there is one. You may have to read the problem definition or problem formulation section, but try to avoid it. Under no circumstances should you read beyond the problem formulation section. At this time, you must have a definite "yes" or "no" answer for each of the papers on your list. For each paper you answer "no" to, enter them in a separate "reject" bibliography, and keep a one sentence description of your reason for so answering. For each "yes" paper (if any), enter them in your research bibliography.
Note: As a guideline to the effort you should be expending at this stage, I suggest you should not spend more than 2 to 5 minutes on considering any individual paper before deciding your answer.
Note: Retain all the intermediate lists you have made, and save all the keyword searches you performed.
(Note: For those interested: The questions below were obtained by consideration of the "Anatomy of a Research Paper" presented above, and Bloom's Taxonomy of the cognitive domain.)
When we take the effort to read a paper, we want to gain knowledge from the exercise. To test whether you have gotten your effort's worth from reading a paper, you can ask yourself the following questions - you should be able to answer these at satisfying level of details. If your answer is very general, and does not satisfy you, then you have some more reading to do. Perhaps you need to read other background material first, or just invest more effort in reading the paper itself. At times, going on to read other related papers can help, because you may understand something when it is explained by some other author in a slightly different way, or something else, perhaps a conversation with a colleague, might explain it for you. But be sure to keep track of what you have "skipped over" like this in any paper, so that you always know what you have and have not mastered in a given paper. (The annotated bibliography mentioned above is a good place to do this.) Be sure to come back to such unresolved questions, if the next few papers do not help you.
Answering these questions in sequence is a good way to develop a short precis of the paper:
As you develop answers to these questions while you are reading the paper, make sure to record them - writing in the margin with a pencil is okay, but nothing beats typing it into an annotated bibliography.