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What is the most effective way to negotiate for more time while waiting for other offers?
Suppose you've interviewed for two post-doc positions.  The first position has just been offered, but you really want to see if the second one offers a position as well.  Clearly, it would be best to press the second one to make a decision sooner.  But it may also be a good idea to press the first one to give as much time as possible to make a decision.
What are the most effective strategies to negotiate for more time to make a decision on the first offer?  How should one phrase it in the most positive and constructive way so as to maximize the possibility of gaining more time to make a decision?

You should consider how "in-demand" you are, both in general and for the positions in question. For the second position, if you have reason to believe that they will indeed make you an offer, you can approach them along the lines of "I would like to be able to consider your opportunity alongside my other current offers; could you give me some guidance as to when you expect to make a decision on my application?"
For the first position, they've made you an offer, so you need to judge whether they want you there enough to give you some extra time. You'll get differing advice on this point, but I would not mention that you're waiting for another offer (unless you are confident that they will wait). Again, this depends on whether you're in a buyer's or seller's market, so to speak. No harm in asking for extra time straight out, though.
If you need more time to decide once you have both offers in hand, I think it's best to be upfront that you're choosing between offers at that point.
In general though I think you have to be much more careful about pressing the first institution unless you really think you have leverage.


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How to encourage faculty involvement as judges in a local research exposé?
Our university has a an annual event showcasing graduate student research projects and has a competition for best presentation.  However, faculty involvement (as judges for the event) was very sparse and we had a difficult time getting enough faculty to volunteer as judges.  I know that faculty time is very precious and this event did demand a lot of time and provided little incentive other than free food.  How else can I encourage more faculty involvement in this event?

We have the same kind of event, and we get reasonable faculty involvement. A few things that help:

Faculty are likely to show up and get involved if their students participate. Make sure students of many different faculty participate and remind the professors of this fact.
Remind, remind, remind. Send regular (but not daily) reminders to the faculty. Keep the emails short, and let them know what's expected of them - show up at this place, at this time, and encourage students.
Get different people involved in different aspects: some might review the presentations, some might help with pre-screening, and so on. The more people are involved, the more they feel part-ownership, and the more likely they are to participate in other ways.
Do this regularly. It's often hard to do this the first time, but once it's a regular occurrence, people get used to the rhythm of it and how it fits into the calendar.

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How to invite yourself to present at another university?
I am a PhD student right now, and I'm looking towards doing a post-doc in the future.  There is a research laboratory where I want to do my post doc, primarily because there are scientists engaged in very similar topics to my dissertation work.  I've never met any of them personally, and I know that the standard approach is to network with them at conferences first.  Someone had suggested to me that it is possible to target an individual in that institution, and somehow invite yourself to their lab to meet them, potentially giving an unofficial (non-departmental) talk in their lab.  I know that this is not a standard approach, and I think that if I'm not careful I might give a bad impression in the process.  How can I invite myself to the lab if I don't have a personal connection to a researcher in that institution?

Have you checked whether your advisor knows any of them?  (If their work is that close to yours, this would seem pretty likely.)  He or she could probably let them know about your interest.

My advisor/committee doesn't know them personally either, just vaguely by name.

I'm assuming there's no chance you'd "be in the area" any time in the near future ?

@Suresh: I was thinking of taking a trip out there, but I'd really like to coordinate it to meet the people in the lab as well.

Often grad students and postdocs don't realize that many seminar organizers are actively looking for speakers for their weekly seminars.  As an organizer, I have frequently "cold-called" (via email) potential speakers for our seminar, often with success.  As a speaker, I've rarely called someone I don't know at all, but it takes only a very weak relationship before your offer seems appropriate (even having talked with the seminar organizer once at a conference for 10 minutes 2 or 3 years ago can be enough).

Is there any distinction between official and unofficial talks?

@gerrit: 'official' means that the host department is sponsoring the talk.

If they call security when you show up, you're doing it wrong.

One thing that sometimes works is the following:

Hi, I'm so and so, working with Prof. X on topic Y (my webpage). I was
  going to be in the area during (vague period) and was wondering if I
  might stop by to chat with your group about your fascinating work in
  Y'.

While this is a little passive-aggressive, I've found that more often than not, they'll ask you to give a talk, and even if not, you might get a chance to meet with the lab folks, which is the real purpose in any case. Make sure that the PI is around though.

I always tell my students to include the line "My advisor Jeff Erickson suggested that I write to you." and to CC me on the email, so that the recipient sees that I can see that the student is name-dropping me, strongly implying that the student is telling the truth.  (Also, I have spent the last several years building up an immunity to iocaine powder.)

@JeffE: +1 for the iocaine powder reference :-)

It seems like you are worried about it, so you might want to ask your advisor to do the intro. PIs generally appreciate getting a a heads-up on good potential postdocs.
I think it would make a better impression if you were comfortable to do it yourself. I would start off pretty light by sending the PI an electronic "reprint" of something related to a conference you attended/are attending. Something like: "I was hoping to meet you at the basket weaving conference, but I didn't see you. I have attached my poster/talk/reprint." This works for either a recent past conference or an upcoming conference. For an upcoming conference, if they have an abstract tailor the email appropriately.
Hopefully the PI responds, but if not, then go a little harder. Send them your CV and tell them you are looking for a post doc.

I'm also doing a PhD and have a 'target institution' for a post-doc. I visited it already, but my supervisor knew the guy there and he made first contact.
I got the impression that it's common practice to have people from other labs just visit, and that the stuff you can do while there is entirely flexible. My visit (two weeks) consisted of me sitting at a computer surrounded by local lab members, doing my own work, and talking to all of them about their work during lunch breaks. I also arranged to do a joint experiment with the PI there, which will now become part of my PhD, and we roughly agreed on a research design while I was there. I didn't mention the post-doc idea yet, as I think it's best if I prove my worth through this joint experiment first.
On the first day there, I was asked if I would give a talk (which I did). I could even choose how big an audience would be invited.
While visiting, I also discovered another lab at the same university, which does related stuff to mine. I just e-mailed them, saying I'm in town (from lab so-and-so) and asking if I could come talk to them a bit. I googled their web page and came up with a few names of people I told them I'd like to talk to, although I didn't know much about any of their work. I did not ask to talk to the big names, in that lab, just PhD students and post-docs. What did they do? They immediately asked me to give a talk (which I did).
Overall, my impression is that this is standard practice. People like to hear about related work. I would suggest that you just e-mail someone there, tell them you find their stuff interesting (it's best to mention some specific result of theirs, so that they see you're really into it), tell them you're working on something similar and ask whether you could visit their lab. I would guess that you'll end up giving a talk. You can also suggest it yourself, once you've established communication and exchanged a few e-mails.

That makes a lot of sense.

I was just at the JMMs in Baltimore and was out to lunch with a past supervisor.  We eventually had several people join us, one from a nice Middle Eastern Country (which I had also incidentally applied to and he recalled my name ... which is nice!).
Anyway, he made a specific point to indicate to me (and the others at our table) that their department had some funding to bring in some candidates for talks.
I know that this question was more for how to get invited to a talk at a specific institution, but there are many ways that this can happen!
I think you're best bet is indeed representing yourself.  It shows initiative.  Especially if you've met the person at the conferences / talks within your community.  The other thing is that if you ask them in person, or mention something in passing, they might make an offer to have you come visit and talk.  Otherwise, a nice polite email indicating you would like to talk at some point would be good.

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What is the difference between research intensive vs. research extensive universities?
I keep hearing these terms being thrown around at conferences, but I'm not really sure what they really mean, if there is any difference between them.

"Research intensive" and "research extensive" are obsolete terms from the Carnegie classification of research universities.  They are terrible, confusing terms that should never have been introduced (see page 5 of Rethinking and reframing the Carnegie classification).  The idea was that "research extensive" means there's an extensive research program covering many areas at a high level, which "research intensive" means there's just a narrowly focused, intensive research program in certain areas.  Basically, extensive is supposed to be better than intensive.  Of course the problem is that this really isn't what they sound like.  For example, most people would say Harvard is a research intensive university, but in this classification it's not.  Because of massive confusion, the Carnegie classification was updated to use other terms, but the old terms still persist.  One reason is that some people just got used to them and found it hard to develop new habits; another is that every time the classification changes, some universities end up moving to a less prestigious category than they used to be in, so they have a strong incentive to describe themselves using the old terms.


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What are the elements of an effective elevator pitch?
When I go to conferences and try to network, I want to be able to explain my research in a clear and concise manner while still effectively communicating what I do.  What are the most effective ways of doing this?

Check out Elevator Pitches for Scientists: What, When, Where and How from The Postdoc Way, as well as two links related to science below. They are all very interesting.

An effective elevator pitch is between 30 and 60 seconds in length. Based on how most people speak, that's between 60 and 120 words. That's not a lot of time or verbiage, as this corresponds to about one paragraph in length.
If you look at the challenge as answering the six fundamental questions (Who?, What? Where?, When?, Why?, and How?), several of them have already obvious answers (these would be Who?—You!, When?—Now!, and Where?—My PhD project!). That leaves the three remaining questions: What?, Why?, and How?
Basically, I'd format the pitch as follows:

What is the basic problem?
Why is solving this problem important?
How are you solving this problem in an original way?

The other thing is to rehearse it until you can tell it without thinking about it—either because you have a rehearsed script, or because the key points have become ingrained and recallable without much thought.
======
POSTSCRIPT: As Artem mentions in a comment below, you should have different elevator pitches for different audiences. At a minimum, you should have one for experts in your specific field, one for other members of your profession but outside your field, and then a third for "general" audiences. Having one for family and friends who want to know "what exactly is is that you do?" probably isn't a bad idea, either.

but don't have just one pitch. Have a different one for different audiences.

As a point of comparison, @aeismail's answer is about 150 words long.

@ArtemKaznatcheev: What kinds of audiences should I prepare it for?

@Paul - three audiences: (1) those expert in your subfield, (2) those expert in your field but not subfield, and (3) everyone else.


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How to teach a class that I've never taken?
I have the opportunity to teach an undergraduate class in statistics.  However, I've never taken statistics and the material and concepts are a little foreign to me.  I'm concerned, as a graduate student, that it may take up a lot of my personal time just to learn the material, much less teach it.  I really don't want to turn the opportunity down because I know its a good learning experience, but I don't want to become overwhelmed by it.  What are some effective strategies to teach a class that you've never taken before without overloading yourself?

"I really don't want to turn the opportunity down": I warn you against this kind of thinking, especially if you are interested in a research postdoc. You will have many, many opportunities in grad school and beyond, and regrettably you will have to turn most of them down.

See also "Teaching What You Don't Know" by Therese Huston, helpfully mentioned in ff524's answer to another question.

It will be a huge timesaver if you can get lecture notes from someone who has taught the class before.  There's a big difference between understanding the material well enough to solve problems and answer questions and understanding it well enough to find the clearest, most succinct way to present it.  If you get someone else's lecture notes, you will only have to attain the first level of mastery, rather than the second; this will save you a lot of time.
Before the class starts, you should sit down with the syllabus (presumably you can get one from someone who's taught it before; typically, the first time I teach a class, I don't change much unless I have a good reason to) and try to understand the structure ("story arc") of the class.  What are the big ideas?  For example, in Calculus I, some of these are: limits, derivatives, integrals, applications.  That gives you a sense of where you're going and helps you to know what may be important.
Don't feel like you have to know every little detail perfectly.  The stuff that will likely stump you will be the obscure corner cases.  The stuff that most of your students will struggle with will be much more basic, like the limit definition of a derivative, and precalc and algebra.  If a student asks you a question that you can't answer right away, learn to be comfortable saying "that's a great question"; it's a little outside of the scope of this lecture, but I'd be happy to talk with you about it after class.
Thinking on your feet in front of an audience (especially about unfamiliar material) can be really tough.  Most of the time, you can avoid it.  Usually the student will be happy to talk with you after class.  The reduced pressure of not being in front of the other students will help you to think more clearly.  If you still can't answer the question after a reasonable amount of time, say "This is a good question.  Let me think about it some more and get back to you in class next time."  At that point, feel free to ask your colleagues.  Often one of them will have encountered the question before, and will know the answer off the top of their head.
tl;dnr Get lots of help from colleagues who have taught the class before.  Typically, it won't take much time from them, but it will save you a lot of time (later, when roles are reversed, be willing to do the same for someone else).  You don't have to be perfect.  If you have decent lecture notes, and you really engage with the students and answer their question, you'll be fine.

That's really awesome advice!  I never thought there was a difference between knowing it well enough to "solve problems" versus "explain things succinctly".  How should I approach answering students' questions during office hours when I don't know the answer... should I rely only on the "i'll get back to you on that" approach or is there another way to go about it?

@Paul A great all-purpose response in office hours is: "What did you try?  And where did you get stuck?"  This won't solve everything, but it will help you pinpoint where to focus your explanation.  It will also buy you time to think while you listen to the student's answer.  Another good approach is to verbalize your thought process: "Let's try such and such, and see what happens?"  This has at least two benefits.  First, it allows you to think through things, without feeling like you have to know the answer ahead of time.  Second, it teaches students how to problem solve.  Both are valuable.

@Paul In regards to "solving problems" versus "explaining".  The first requires you to have a decent understanding of the technique.  The second requires you to have that same understanding and to know your students well enough to know what will be easy and what will be hard for them.  For the second, it's helpful to be able to look at the subject matter from multiple perspectives.  In particular, when you're answering a student's question, you should try to step into their viewpoint.  This is often easier said than done.  Fortunately, detailed lecture notes do some of this work for you.

these are really great suggestions.  Thank you so much, DanC

Regarding "What did you try? And where did you get stuck?" I've used this tactic to guide students through solving problems without actually telling them anything substantive, and even without having any idea how I would solve the problem myself! It can be surprising how much most students will fill in for themselves if you just keep prompting them. And in the cases where that doesn't work, it often comes down to incorrect knowledge of some fact which is a trivial thing to correct.

Dan C gave a tremendously good response to this question, but I thought I'd add one more idea:
with the preponderance of online classes, it is very much possible to follow a set of lectures online as you teach a class for the first time (especially for introductory classes), and many times you can find full semester classes for free on YouTube, or Khan Academy, or MIT OpenCourseWare.  I've done this for an Astronomy class that I taught, and I not only learned a lot from watching the class, but I was able to set up my own classes with a good idea of class-long topics.  Furthermore, I've said it at least once on Academia.SE before: observing other teachers teach is one of the best professional development methods around; you learn the good and the bad, and you see what works and what doesn't work.
The reality is that sometimes, staying one step ahead of the students is the best you can do, even if it isn't ideal from a pedagogical perspective. As DR famously said, You "go to war with the army you have, not the army you might want.".

I'm not sure, but wouldn't this be considered plagiarism? How much would you be allowed to "copy" or take away from one of these courses when constructing your own?

@ciri You would still be teaching your own course, but you would be modifying the material from the lectures. You are free to teach a course however you'd like, and if it is like another teacher's classes, so be it.

This question is ancient history for the site, but the following may be helpful to some. I assume that the scale of the class is relatively small, probably no more than 20 students, with about 10 being better. It won't work for large lecture sections.
The main idea is to turn the class into a seminar, rather than a lecture. Admit to the students that this isn't your specialty and that you will all learn the material together. Some students will balk at this, but it can be made to work. The idea is that face time in the course is used for discussion and exploration, rather than lecture. You assign some work one day and let them work on it over night. Then you have small groups develop solutions together. You can also assign topics to students who will then, a few days later, give their best explanation of the ideas.
I asked a very similar question at CSEducators here.
This technique probably works best with somewhat sophisticated students. It is, in fact, how a lot of learning at the research edge takes place. People discuss topics then work individually and together on the ideas. But the group work aspect of it can, perhaps, entice beginners into participating and developing better study habits along the way.
Note that it doesn't depend on "staying one day ahead of the students" nor developing sophisticated teaching materials. But it does require some creativity in keeping discussions moving along.

I know this answer might be controversial, but I think it is important to mention it. The solution is to not teach the class.

Teaching is a huge responsibility: you are responsible for the enthusiasm (and possibly the career) of a lot of students. If you do not feel ready you are not ready.
Good teaching takes a lot of preparation. You indicate that you are concerned about the time it will take you. My conclusion: you do not have the time to prepare properly. This is a good reason not to teach the class.
You are looking for effective strategies. There is no such thing; teaching is not some kind of "trick". The next two points explain why.
You need to have good (if not excellent) knowledge of the field: "If you can't explain it simply, you don't understand it well enough" can be reversed as well: if you do not understand the material well enough you will not be able to explain it simply. Reading a few course materials in the short time before the course will not be sufficient.
Teaching takes planning. Planning takes time and experience (even if you are using existing course materials, you need to be very familiar with them and what they are meant to achieve).

Don't take the responsibility of teaching when you are not ready. But you can start preparing for next year, or ask to teach subjects you are more familiar with.

I disagree strongly with many of these points.  The first time I teach a course, I rarely do it as well as the third or fifth or... time I teach it.  But the reason I get better is that I learn from the mistakes I make.  I also don't always have the choice of which classes I will teach.  Finally, I think there are many "tricks" that significantly improve teaching (start with an example; more generally, work from concrete to abstract; use pictures wherever possible; follow a clear outline; find a style that suits your personality; etc.).  No one of these fixes everything, but they all help.

These "tricks" you mention strongly depend on the content and goals of the course. It is fine to make mistakes (it happens  that mistakes made by the teacher are the most educational part of the course), but is is not fine to teach a course if you admit in advance that you do not have time to prepare adequately.

The way that you implement the trick depends on the course, but the idea of drawing a picture (for example) is useful in a very wide range of courses.

Precicely. And this implementation requires skill and experience. Incomplete ("simplified") pictures may do more harm than good. And so do confusing images that are quickly cobbled together. GOOD pictures help, not ANY picture. Similarly, finding a style that suits your personality takes time. The question from OP states that they do not have time: not to make good quality pictures, and certainly not to find their own teaching style. I think you missed the point of the question.

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On the definition of research
I'm writing a proposal to acquire funding for a competition to be hosted at my university.  The competitors are restricted to graduate students who are engaged in research under the auspicies of a faculty advisor from my university.  In the process of making my proposal more clear and precise, I find myself struggling with the problem of defining what exactly is (and more importantly, what isn't) research.
At first, I equated research with publishable in a peer reviewed journal, but I soon realized that the terms publishable and peer reviewed would have to be defined... And even if I do that, then I would have to define the words that I used to define those words, et cetera ad nauseam.
I want to approach it the same way I would approach mathematical set theory:  it's either research or it's not, and there should be no room for ambiguity.  But I suspect that any attempt to define research this way will certainly either circumscribe or inscribe the set of all things we call research.
I don't think this is necessarily the best way to approach defining what is research, especially for my purposes.  Is there another way I can approach clarifying what constitutes research as opposed to other publishable works in the context of academia?

How helpful is the Wiki page?

I want to approach it the same way I would approach mathematical set theory: it's either research or it's not, and there should be no room for ambiguity. — Good luck.  While you're out, could you get me a pony?

For purposes like this, I would define research as loosely, broadly, and generically as possible. If your definition is too strict, then you exclude valid efforts, and you will likely be bound by the language in your proposal.
For example, if you define research to be "scientific investigation," then you exclude the humanities. If you define research as "investigative work leading to a peer-reviewed publication or conference presentation," then you may inadvertently exclude unpublishable and unpublished results.
If the requirements of the agency do not specify the need for a definition of research, then do not supply one. If you are writing to an agency that regularly supports research proposals, then there is no need to define research - they know what it is. If you are writing to an atypical funding source, like a business, local government, or charity, then they would probably rather you be inclusive (and thus generic) unless you have specific instructions otherwise. Leave the job of deciding whether an entry is qualified research to the judges of the composition.
If you feel that you absolutely need a definition, then "investigative work" is probably generic enough. Your institution's Office of the Provost may also have an "official" definition of research for your institution.

And in the spirit of things, but not asked, leave the selection criteria/methods for judges, judging criteria, application procedure, etc., as vague as possible in case you need to change them. "The judges shall be a committee of faculty selected for this purpose."

I suspect that, for your question to be properly answerable, you'd first need to define what you want to mean by "research".  In particular, from what you write:

"The competitors are restricted to graduate students who are engaged in research under the auspicies of a faculty advisor from my university."

I gather that your university also has some graduate students who don't do anything you would call research, or you wouldn't feel the need to be so specific.
So, what is it that these students, which you want to exclude from the competition, do instead?  Just coursework?  If so, why not just write "research (not merely coursework)" or something like that?
(If you do want a fancy definition of "research", I'd go with something like "original work intended to contribute to the body of academic knowledge".  But you'd probably be better served by just explicitly stating what kinds of student activities you want to include or exclude from your admission criteria.)

Have you verified that the definition isn't provided by the competition itself? Typically, there are pretty well-defined guidelines as to who is and is not eligible to apply for a given contest (i.e., "only full-time students", or "only students currently funded under a research grant"). I would definitely either contact the competition sponsor or check their website to ensure that they haven't already defined what does and does not count as research.

I am both the organizer and sponsor.

@Paul - I'm sorry, I see that now; I didn't read the question correctly. I was going to edit my answer, but I re-read Ben's answer, and I would basically write what he wrote, so I just upvoted his answer instead :)

How about trying to define research would it help to spcify "Scientific Research". Since research is a search for new knowledge it is thus a wide term. Since Science is defined as "the body of reliable knowledge itself, of the type that can be logically and rationally explained" (shamelessly stolen from the wiki page for Science) the word scientific would exclude everything not included in the definition. Or, is there any academic research that does not qualify as science?

And some would say that "Scientific Research" may inadvertently exclude "Humanities Research". I favor as generic a definition as possible.

@BenNorris Yes, I guess that was what I was afraid of


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How to replicate others' results quickly?
Lately, I've been getting the impression that before I can conduct cutting edge research, I have to first master state of the art methods/techniques.  Often, this requires spending (i.e. wasting) lots of time trying to replicate the results that others have already established (i.e. make sure that I can do what others have done first before moving on to other territory).  When I try to master a new technique, I often find that it is extremely difficult because

Research papers don't seem to disclose enough details to replicate their results easily.
There are no advisors/colleagues that are familiar with these methods
Emailing the corresponding authors with questions about specific details about their research tend to go unanswered.

The only advice i've been given thus far is simply to read and re-read the research paper and dissect every little detail until I figure it out.  But are there any other general strategies I can use to replicate others' results more quickly?  In particular, I'm looking for strategies for replicating numerical results that require very careful implementations of mathematical algorithms.

I've been in the same boat, as I'm sure many people have. Personally, if I can't get hold of the code, I don't attempt a reimplementation. For something non-trivial, it takes too long, and life is too short. Also, as you said, 1-3 apply. Certainly, 1 and 3 seem to apply nearly all the time. I'm tempted to ask another question along the lines of "is it reasonable to be expected to duplicate another's research if no implementation and not enough detail is provided"?

That is not wasting time.  Hopefully this painful process teaches you, among other things, to write your own papers/code better than the papers/code you're trying to replicate.

As a side note, it is why a publication based on numerics but without (attached or linked) working code shouldn't be consider real science...

As JeffE points out, trying to reproduce existing results before embarking on new endeavors is not a waste of time. It can be particularly useful, especially in tracking down issues that you have within your own code—or, perhaps, in the existing literature. My most-cited paper, and much of the research work currently ongoing within my group, came about precisely because I could not replicate an existing paper. As it turned out, there were some significant methodological problems in the existing literature, and this led to a fair bit of digging around, plus a lot of careful analysis to demonstrate what had happened and why. As I've also said, the issues we uncovered there indirectly led to a different line of inquiry that has already led to half a dozen additional manuscripts.
If you are determined to speed up the process, however, you might try to consider simplified versions of the research cases presented that can validate what you're working on. For instance, can you find a "prototype" problem whose solution would be known with your method as well as the existing methods? Can you find one or two test cases which can test most of what you're looking for? Can you devise a new problem that compares the two better than the existing cases, and is also simpler to execute?

The fact that you can't quickly and effortlessly do this is exactly why this is not wasting lots of time, assuming that you do in fact mean to build upon this very same research.  You're learning how to solve problems in this arena, given an outline that you know works, but insufficient detail to actually implement it fully.
Other than that, for numerical results you simply need to do lots of testing to make sure at each stage the calculation comes out to be what you expect (and tests any important corner cases).  For example, if something's piecewise polynomial, and you drop three points at random into every piece, and it's accurate to within machine precision, you've almost surely got it right, and if it's not you've almost surely got it wrong.
Now, once you're already well-versed in a field, you may write a paper which referees want you to compare to some other new result in the field.  Replicating someone else's poorly-described new methods really can be a waste of time; you don't learn anything except that they left out a lot of fiddly details.  (Editors may be sympathetic and let you skip it or e.g. use a common dataset instead.)


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Which licence choose for a new academic computing language?

Disclaimer: I am not sure this is the right place to ask the question, but since it is directly related to academic work, I though I'll give it a try. If it is not, please feel free to redirect

Together with colleagues from different institutions (all academic), we have been developing a new information language (more precisely a format), based on XML, to store a specific type of information. This format is primarily directed to the academic world and will be open source
My question is: do we need to attach a licence to this new format and, if yes, what type of licence is suitable for that?

Seeing as the question is not about academia, but rather something that has the slightest connection to academia, I think it might be a better fit for Programmers.SE

I know it's maybe a bit late to do this and I know this is not the question (and I apologize for the offtopic) but I've to get this out of my chest. Have you considered RDF?

Oh, no, yet another format!
Now seriously, you can legally register a format, but I don't see a big benefit from doing it.  For what I see, licensing is essentially a copyright of the actual text. In most practical purposes, having a public, freely available document explaining it, should suffice.
To support my feeling, I have been digging in some academic examples I am familiar with and they don't specify any.
If you want to be sure, you could see what other people have done, for example, OpenDocument format.


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How does the acceptance rate affect papers decisions?
Some conferences do maintain a percentage for the number of accepted papers to the total number of submissions.
Does this mean some good papers will be inevitably rejected just to maintain the acceptance rate? How conference chairs deal with the acceptance rate? or it is not related at all to the acceptance/rejection process.

Interesting question! In my field I have not heard of such limits at conferences. In most cases it seems many drop out during th eprocess so volumes end up "thinner" than expected. I look forward to see the answers to your question.

I think the total number rather than the percentage is the more common constraint.  There is only so much time and space at the conference.

Yes.
But it would be more accurate to say that conferences have a fixed budget of papers that they can accept, due to scheduling constraints.
At most computer science conferences, every accepted paper is presented in a 20-minute talk; for a three-day conference with no parallel sessions, this practice imposes an upper bound of about 50 accepted papers.  Of course larger conferences have parallel sessions, but program committees generally do not have complete freedom to add another parallel track, partly because of space constraints at the conference venue (which is planned long before the submission deadline), and partly because major changes to the conference organization usually require input from the community.
So inevitably, if a conference attracts a large number of strong submissions, it must reject some of them.  This is generally considered better than the alternative, which is that the conference must necessarily accept some bad papers.
This answer is specific to computer science.

What about posters?

As theoretical computer scientist, I am required to give the following ritual answer: What's a "poster"?  More seriously, poster sessions also have physical constraints.  Moreover, people who publish in conferences with poster sessions are fond of reporting which of their papers were accepted for presentation, which leads others to ask what percentage of submissions were accepted for presentation, which brings us back to square one.

Many conferences in CS have gone to poster mode, but that doesn't change the fact that space and time limitations determine the total capacity, rather than quality.

In very large number of conferences, acceptance rate is not really important since authors are paying high for getting their works published. In general, acceptance rate is used as a metric to claim/show reputation and popularity to encourage authors for more submission. I came a cross situations where authors write to the program committee to inquire if the paper is in the scope or not and they are encouraged to submit. Once submitted, they get quick rejection. By doing so, the conference is getting lower acceptance rate which is likely collecting more credits for future. The more submission, the better visibility, the less acceptance rate and higher competition for the next year. I personally believe the acceptance rate is more like a business trick to tempt researchers to submit. Because, if the conference organizers are bound to certain number of publication, they can simply - in plain language- announce the number of papers acceptable for publication rather than saying, we have only 10% acceptance rate. By putting rate, authors are encouraged to submit. If the limit exceeds, the organizer rejects the likely good works and the authors of rejected paper have an excuse that the acceptance rate was very low and nothing wrong with my paper!!! So try harder for next year and this circle goes infinite. Who wins? orgaznier ;)


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How to address the lack of seminars in my department
My CS department greatly lacks invited talks hosted by faculty members and/or seminars organised within/by the department. Except for the seminars done by graduate students as a requirement for their degree, during the last year there was no seminar organised by the department/faculty member. If curious, the department size is relatively small (around 20 faculty members) and some faculty members are well-known figures in their areas. As a PhD student I like seminars and wondered how to address this to the department.

"Seminar" can mean a couple different things. In one sense it's a small conference, where many speakers come to visit at once. In another sense it's a regular (usually weekly) event, where each week a single speaker gives a talk (either a visitor or a local). Since they are rather different organizationally, could you clarify what you're looking for?

@NateEldredge I mean the second one. Weekly events where one speaks for 50 minutes or so.

It's hard to change the culture of a department as a student.  You should definitely tell your advisor, and the department chair, that you wish there were more lectures.  You might also talk to other students and encourage them to express their feelings if they feel the same.
Then you should take action.  Is there a student chapter of the ACM at your school?  If not, organize one.  Then organize monthly seminars by inviting faculty and students in your department and from nearby schools to present their work.  If you can get a little funding, invite one of the world leaders in your area to give a seminar at your school.  You might be able to get funding through the department or through the ACM (I know SIAM gives funding for such things).
It requires work, but it sounds like it will be worthwhile to you.  It is also a great excuse to meet important people in your field.

Your faculty isn't huge but, at the same time, it's bigger than many research groups that have successful seminar series.
The first thing you need to do is to establish why there aren't already seminars. If the reason is just that nobody has bothered to organize any, you can deal with this; if the reason is that the faculty members aren't interested in attending seminars, you might be wasting your time.
One important piece of information that's lacking is your location. If your university is in, say,  the middle of North Dakota, it's going to be difficult and very expensive to organize a seminar series with external speakers. Every speaker will need flights and a hotel and, even when you pay expenses, speakers are unlikely to take a 2-3 day trip just to give a seminar to 20-30 people. On the other hand, if you're in, say, England, and there are several other universities within two or three hours' travel from you, things are much more practical.
A good way to get the ball rolling might be to organize informal lunch-time seminars. Start with the grad students and try to get a few faculty on-board. The idea would be to have a 30-45-minute whiteboard talk while people eat lunch. No slides, so people don't have to spend hours preparing; lunch-time so it's not taking time out of people's days; typical topic would be "What I've been working on recently", so things stay relevant. Once you have a seminar culture started, you can think about doing something bigger.

This might be field dependent.  In my field (mathematics) it's totally normal to travel 2-3 days to speak in a seminar, and an audience of 10 for a specialized talk would be considered pretty good.

@NateEldredge It might be location-dependent, too. In the UK, there are plenty of people close enough that they'd have to spend at most one night away from home to give a seminar but we have 7.5x the population density of the US (and England has 20x the population density of Colorado).

Yes, that's even more likely.  A US seminar visit is typically one full day, with informal discussions before and after the talk, and dinner at the end.  Since most US city-pairs require air travel, you kind of have to arrive the day before the talk and depart the day after, so it's 2 nights minimum.

@NateEldredge Yeah, here the usual deal is travel during the morning, chat and give the seminar in the afternoon, have dinner and either travel home during the late evening or stay the night and travel home the next day.

We have somehow the same problem (not that we don't have seminars - but we don't have enough in my opinion). The graduate student association in our department (CS as well) tried once to organize such seminars. There were many interested professors and students, especially when it comes to topic that are not very technical [a professor told me that such lectures are more useful for the students].
However, to make these seminars frequent, it was found that the best thing is to do is to make the seminars specific to one topic. In order to do this, there is a need for a group of researchers led by a professor (or more) - all working on the same area. Some professors tried to do something like that, however, only the big labs were successful in this mission (i.e. labs with many professors and students). Issues are:
1) finding large number of speakers,
2) intellectual property, some researchers simply do not want to share their ideas with others. [in fact, the association tried to do a conference each year, but the fear of IP theft was the biggest obstacle and the lack of motivation for researchers to publish in an non-indexed conference].
Conclusion, you need a lot of support in order to organize frequent seminars in your department, but it is not impossible. Talk to young professors, they are the most motivated.


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Why do PhD students volunteer at conferences?
Other than the possibility of waiving registration fees, What is the objective of graduate students volunteering at conferences?
For instance, I am considering volunteering at IJCAI these days and wish to do it at least once (never done it before) but do not really have  a clear motivation for it.

tl;dr No registration fees, networking and attending relevant sessions.
There has been some talk and background information about this already. See this, this, this and this for some background. With this background, IMHO, the primary reasons why PhD students should be volunteers for major conferences in their line at least once are:

First up, no registration fees. Yay! Primary reason one.

Networking with other PhD student volunteers who are likely to be PhD students in similar departments working on similar stuff. For instance, most student volunteers at CHI 2013 are PhD students from HCI/CS/IS schools working on HCI stuff. It's great to meet with peers and bond with them. [Yay for student volunteer party!]

Possible networking with relevant faculty. This could be someone from the organizing committee or the program committee or someone else who you come in close contact with for the duration of the conference. There might be a certain someone who is a good researcher in your line and whom you might want to keep in touch with in the future. Getting in touch as a student volunteer in a conference might be one such strategy.

Picking and choosing conference sessions/tracks to attend. You could, with some dexterity be the student volunteer in charge of a track or a session or a panel which you are really really interested in watching. As a student volunteer pretty much, you stand and assist and you do get one of the best seats in the house, albeit by standing. :)

Good answer. Few missing points: often these are local students who thus get access to the conference, but often also students receiving a student (travel) grant, or other financial support from the conference are asked to give a helping hand in return for the money. Then, they have to pay the regular fee, but get reimbursed for either the fee, or part of the travel costs.

Thanks for the insights. From my limited knowledge in HCI/information science, in the big conferences, student volunteer calls go out to different mailing lists and it is thus, rarely local students who are student volunteers. In fact, there are student volunteer lotteries which take place in the big conferences to determine who will be selected.

Volunteering can be fun, it's a change, you get to meet new people. Volunteering is good for you - you feel a part of something bigger, and like you've achieved something useful and immediate (unlike, say, a thesis or a paper).
It's probably good for your career in the long term - getting a reputation as a person who says "Yes" to things is always going to help.

From the IJCAI link you provided, I found the following on the travel grant application web page,

In the event that travel grant applications exceed available funds, preference will be given to students who have an accepted technical paper, and then to students who are actively participating in the conference in some way.

I take it to mean that you have more chances to get the grant if you volunteer.
Send the application form now before it's too late if you did not get support from your department and you don't have an accepted paper. I would run to register for volunteering if I were you.


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Publishing policies for conference papers
I got two papers accepted and I am just wondering how to know their policy towards publishing my papers also on CoRR. is it fine to publish the same paper in CoRR and in the conference?

This is entirely a function of the publisher of the conference paper; CoRR does not impose any restrictions itself.

In addition to Charles's answer, it depends on how the conference papers are published. If they're published as a special issue of a journal, then it may very well depend on the policies of the journal, as well as those of the conference. (And some conferences may have special restrictions on publications; in those cases, you should check with the conference organizers.)


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Transferring knowledge from one field to another
A professor once said to me: publication is about intelligent copy paste from one field to another. His claims were right in a sense that he knew what results already exist in one field and apply it to the other non-mature yet field. Ofcourse he didn't mean a literal copying.

If you are working in a cut-edge research (a new obscure area) and
  already familiar with another stable mature-enough area, is utilizing
  one's techniques to the other is a good approach for making
  contributions to the field?

is it count as a good contribution?
is it common in Academia? (specifically for Computer Science field)

“The secret to productivity is getting dead people to do your work for you.” —Robert J. Lang

Computer Science has many subfields, I remember that there was a running gag in NLP that people just took algorithms from the 1980's and pushed papers out like a treadmill.
Other fields like Statistical Machine Learning has a more math oriented approach and you do have to come up with novel stuff most of the time.
However, when you do interdisciplinary research, it is very often that many good techniques just don't get tested because many people do not know how to use them, or do not have the time to understand them very well.
But to answer your question, I think is a pretty valid practice, very good researchers have great papers where what they did was basically apply a widely known math tool to a novel problem that few people were working on.
An example that comes to mind is how Factor Analysis, a widely known CS method (1993) was just applied in 2007 for the problem of discovering Connections in Gene Networks, not only that, people were using linear regression on that just 10 years ago.

In addition to that also certain methods that were previously too computing intensive, can now be applied to huge datasets at a low cost.

What is important in each scientific work is that it adds to the knowledge that already exists, i.e. there needs to be a new element. Applying a known method from another field into a new field, if this has not already been done before, can be a valid new element. In my view, this is a good contribution. Also, this happens quite a lot in research in general. For example, copula's where very populor already in Financial modelling, but only recently got attention for spatial interpolation.
People who come up with radically new ideas, e.g. Einstein, are very rare. Most of us researchers can be happy to add our little addition to the large pool of knowledge, mainly building on existing material.

...not even to mention that Einstein applied Riemannian geometry in physics. :)

So even he copied stuff ;)


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What does "Publish or perish" really mean?
In this site, I quite often see answers containing this "Publish or perish" sentence.
What does it really mean?  Is it limited to a particular academic system (i.e. U.S.) or it is the general case all over the world?
Lastly, is it possible to be a researcher without concerning about "Publish or perish"?

Note that this can not be reversed.  It's quite common to publish and perish.

First a disclaimer: I personally do not agree with some "ways of life" I am going to describe and already upvoted other answers :-).

is it possible to be a researcher without concerning about "Publish or perish"?

YES, albeit probably only in atypical settings.

firstly, at this site, we tend to forget that academia is not only the first league of the few top-notch research universities, but includes a MASS of smaller universities and research institutes in all sorts of small, hidden corners of the world which tend either not to produce academic output in terms of journal articles, books, conference papers, etc., but at which they live and breath by e.g., primarily education, local politics, etc. Yet, on paper they claim to do research, so working there, you would be officially a researcher. I am speaking for instance about universities in countries, where rigorous science and high education, for whatever reasons, does not have a very strong tradition. At such places, doing research would resemble a kind of a cargo cult. Most often, at least at some stage in the career, you still need to publish something. E.g. a dissertation would probably suffice. But often an interview with such a researcher in a local newspaper would count at the place more than a first-class academic journal. Being coined an expert on X by the local media a single time would allow you to survive at such a university for a decade (at any level from a PhD student to a Full Professor) without being concerned with perishing. If there is a desperate lack of teaching staff, then you do not have to care even for being any good teacher either and you wouldn't perish. I know personally people who are are doing some research  (or at least everybody around says so) for decades without moving from a place and without publishing even a technical report and do not perish.
to a more optimistic note, though being pedantic now, you can easily be a researcher and not publish in the industry. Many  industrial researchers do not primarily work for the benefit of the humankind (as you could see said in academia), but for the benefit of a company.
finally, I speculate there could be some special professorship positions where you do not have to worry about publishing anymore, because you are not about to perish anymore.

This is such a great and informative answer, I liked how you described different perishing levels... Thanks!

Honestly, I do not understand why my answer got so many upvotes. IMHO, JeffE's answer is the right one.

For graduate students, it means "Publish or you won't get an academic job."  In many parts of academia, not getting an academic job is considered equivalent to death.
For assistant professors, if means "Publish or you won't get tenure."  In many parts of academia, not getting tenure is considered equivalent to death.

Lastly, is it possible to be a researcher without concerning about "Publish or perish"?

Sure, of course.
If you're publishing.

In many parts of non-academia, academia is considered a kind of death, and academic is used as a pejorative word for solutions built on assumptions of a simplified, idealized reality. At other times it is a synonym for nitpicking over what is not relevant ("the difference is academic"). So, maybe it should be publish or get a real job.

@Kaz if it would be an answer and not a comment you would down-voted to the ground ;) I strongly agree with you, people that are related to academia talk about it like it something sacred. In real life, it just means getting grants and make students work on some academic-bubble projects (90% of the time).

I couldn't agree more @Kaz

@Kaz is absolutely right — Lots of non-academics have no respect for academics, just like lots of academics have no respect for non-academics.  Humans are apes; we do apey things.

@NPcompleteUser: Can you elaborate on what you mean by "academic-bubble projects"?

@Kaz - that's a humorous corollary, but it lacks the nifty alliteration of the original.

"So, maybe it should be publish or get a real job. " --- actually, most "real-jobs" outside academia are less "real" than doing research. Doing research is doing really-really hard work, and for mostly good or neutral causes. Most jobs are not concerned with either producing anything (desk jobs), or are not producing valuable things (facebook, twitter..what are they producing that is valuable?). Apart from being a farmer, physician, nurse, carpenter, and similar jobs, most jobs are not "real", but made-up.

facebook, twitter..what are they producing that is valuable? — Human communication.

I will add to JeffE's answer by stating:
For researchers, it means "publish or you will not get more funding". Funding is evaluated based on the strength of a proposal but if you are not showing a strong regular publicationr record, the interpretation might be that "you use money but do not produce", hence a risk not worth taking.

Lastly, to answer JeffE's question (thereby emphasizing his implicit statement): No!

It is possible to be a researcher without worrying about PoP only if you're not being paid to be a researcher. If you are being paid to do research, then publication is the most basic way of measuring whether you're doing anything.

In addition to prior answers, the Publish or Perish application can be mentioned, which is a software program that retrieves and analyzes academic citations. It uses Google Scholar to obtain the raw citations, then analyzes these and presents the following statistics:

Total number of papers
Total number of citations
Average number of citations per paper
Average number of citations per author
Average number of papers per author
Average number of citations per year
Hirsch's h-index and related parameters
Egghe's g-index
The contemporary h-index
The age-weighted citation rate
Two variations of individual h-indices
An analysis of the number of authors per paper.

The results are available on-screen and can also be copied to the Windows clipboard (for pasting into other applications) or saved to a variety of output formats (for future reference or further analysis). Publish or Perish includes a detailed help file with search tips and additional information about the citation metrics.

From Wikipedia:

"Publish or perish" is a phrase coined to describe the pressure in academia to rapidly and continuously publish academic work to sustain or further one's career.

I'd like to add just one point to the fantastic answers already posted. Publish or perish often tends to favour quantity over quality, so a researcher who publishes 5 papers per year in mediocre journals may be seen, on paper, as being more productive than a researcher who produces an actual groundbreaking work once in two years.
This is common in places where the assessment of performance is done centrally, such that the assessors are not necessarily experts in one's field, and may not know the value/quality of different journals. In such a case, the number of publications becomes an easy metric to use. Over time, this incentivises low quality, high quantity work.
The perish could mean denial/delay of tenure, promotions or salary hike.

You have two choices or paths ahead of you as an academic researcher: Publish or Perish. By Publish it is meant in relatively high impact factor journals. This builds a reputation in the field and hopefully citations in subsequent publications by other labs. Next, you apply for grants in which the reviewer gauges your investigator value in the field. The more grant funding you get, the more freedom you have to explore and expand your lab. If you don't publish, no one can cite your work except in a cumbersome not generally accepted way (i.e. personal communication). Therefore not publishing in academia is similar to not existing at all and doing nothing to advance science, thus the Perish.

This is a misunderstanding of what the "perish" means


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How to know whether my PhD advisor knows the area of research?
Ok here is the situation: My advisor gave me a paper about new model X. After reading and researching in X, I became very familiar with X and had many interesting ideas to extend its capabilities.
One thing I noticed with my advisor is the lack of deep analysis over my ideas. By this, I mean a roadmap on how to get these ideas published, what are the things I need to polish/sharp/add to get it (most likely) accepted in top conference/journal.
I handed him one draft of a paper, he didn't even doubt its findings; all his concern is to get it published somewhere in ranked C conferences; all he did was praising my writing (which is poor IMHO). What makes it even worse is the fact that I have seen some papers published in top conferences/journals with the same ideas I have (actually three ideas).

This makes me wonder: Does he really know X?

if yes, then why he did not provide constructive ways to sharp the ideas to get it published in a top conference? or maybe I am asking for something that he can't offer!

Does it matter? (Part of) The point of a PhD is for you to become an expert on your question. You should expect to know more about it than your supervisor, particularly if you devised the project from a paper you read (as you seem to imply, which is a great thing for you to be doing).

@JessicaB There is a 2 years learning curve here. I do not think I can publish in top venues on my own (I do have my own limitations which I think its the advisor's job to help me strengthen my skills).

Keep in mind that people can become faculty without any training in how to be a good adviser.  For this reason, I recommend having multiple mentors with different strengths.

@JessicaB Yes, it matters. If your supervisor doesn't have any idea about the work you are doing then all sorts disagreement will begin to pop up.

I suppose it is rather hard to give a satisfying answer to this question with the amount of information available. I mean, it's hard to estimate all the unknowns in this particular case.

if yes, then why he did not provide constructive ways to sharp the ideas to get it published in a top conference?

One could speculate in so many different ways; that he does not have the necessary grasp of the field to give meaningful critique is one speculation. Here's another plausible explanation; maybe he wants you to try flying on your own a bit, as a sink-or-swim approach. My supervisor did (and still does) this very often, I have almost too much freedom as to how I write, and what I write and to where I submit, then when the replies and reviews come in we sit down and improve on what I have done. Could be a similar approach
But to come back the question of how to know whether the supervisor is knowledgeable in a particular subject, here are some things that could be useful in the general case:

checking your supervisors publication record. Maybe the s/he has published articles on about this model before you even came to the group. Or maybe he was involved with an older but related model Y?
inquire you supervisor for his interest in the subject. If s/he gives you a paper about model X, all of a sudden then there is certainly a goal with that. To-the-point, effective communication might help you figure out his/her grasp of the field.

EDIT: In reply to the comment:

if I have too much freedom as to how I write, and what I write and to where I submit, then whats the point of supervision!

My supervisor often says that his job is to teach me how to do research, not provide me with knowledge or make sure I become successful/famous/rich... Your supervisor has ZERO responsibility in providing you the means to publish in top venues, IMHO. He merely has a responsibility to make sure you get the tools you need to be able to do the research you want to carry out, later on in life.
As a side comment, I think your perspective to research might cause your frustration with your supervisor. Getting published in top venues is not a birth-right to all hard working grad students; and quite frankly, as a grad student where your articles get published have little to do with you or your work (at least in biomedical research).

He had never published on the area. He never worked on something closely related. "I have almost too much freedom as to how I write, and what I write and to where I submit" then whats the point of supervision!

I said part of the point of a PhD is for you to become an expert in your field. Another point is for you to learn how to be a researcher (which includes the process of creating and answering questions yourself). While it is generally helpful to learn that from someone who knows well how your field works, it is not entirely necessary. It's not unreasonable for your supervisor not to know about one of your research interests (or to have misjudged where you would end up). If you think your supervisor can't help you enough, perhaps ask someone else for guidance eg the author of the original paper?

@seteropere if you wanted an expert in some area to be your supervisor, then why did you pick someone who has never published on the area or even something closely related?  That being said, if you want to publish something on topic X, then it's entirely expected and normal that you should know more about X than your supervisor and not the other way around; and the input of the supervisor would be about the general academic process, style, contents; about research process and the wider field, but not on the actual topic of your paper.

@Peteris Answering your question: I knew nothing about the area before starting my PhD. For your comment, when I read a theoretic IJCAI or AAAI paper, I can't imagine its the student who did it, at least not 100%

@seteropere if you're not the #1 most informed person in the world about the narrow particular topic of your paper, then either you're not ready to write the paper, or the topic of the paper isn't scientifically novel and thus not worthy of publishing in most venues. If you're co-authoring a paper where the main contribution is from your supervisor, then it's resonable for him/her to drive the scientific agenda; but otherwise the point of PhD (and an absolute requirement for graduation) is to get to a stage where you can be the main author of papers and inform others, not vice versa.

This is more an extended comment, but here goes.
My PhD advisor had me work on a topic (in applied probability) that he knew little about. I survived and got a PhD, but it was not pleasant.
He's seems to have thought that the area was much more interesting/useful/productive than it was, and had wildly unrealistic/inflated expectations about applying it to mathematical finance, which unsurprisingly came to nothing in the end. I suppose in part because he didn't know much about it. It is a pretty obscure branch of applied probability that enjoyed a brief wave of popularity in the 90s, and quickly went cold again because, as it turns out, the area has formidable and (thus far) largely unsurmountable technical difficulties. At any time this area has had a handful of people working on it worldwide. I think with some breakthroughs it could become a useful area, but nothing like this has happened so far.
I learned later from other people (I was pretty naive about how academia worked) that faculty may try to use their students to try to learn about new areas. I've no idea how common a practice this is, but I have no reason to believe it is uncommon. I recall that the people I talked to seemed to think it was quite reasonable. I think it is wildly irresponsible.
In any case, I suggest you don't let your advisor do your thinking for you. If you like the field you are working in, and think you can be productive in it, then by all means continue. However, if you think your advisor doesn't know what is going on, it is quite possible he doesn't. Researchers are only flesh and blood, they are not omnipotent. If he doesn't know what is going on, he will probably be of little help to you. It is possible for your advisor to learn about the topic alongside you, but you are the best judge of whether he is doing that. If he doesn't seem to be, he probably isn't. And frankly, it is not a good thing for a graduate student to have an advisor who views his PhD as a learning experience. Ideally a PhD topic should be well within the advisors area of expertise. If he does not seem inclined to go into details and talks about generalities, that is a bad sign, in my experience.
Bear in mind that finding a auxiliary advisor who knows more about the topic is a possibility, but if want to go in that direction, I'd do something about it sooner rather than later.
Other people have commented here that it is reasonable for you to end up knowing more about the topic than your advisor does. That is a fair point, but that should not be the case at the outset. Maybe that is Ok after a few
years of you digging into the topic. And really, it depends on you. If you are comfortable going it mostly alone in the topic, perhaps communicating occasionally with other researchers, then that is Ok. If you are not, then it could end up being a bit of a baptism of fire. We don't know what your topic is, exactly, so we can't say anything more about that. And research topics vary wildly in level of difficulty, of course.

"faculty may try to use their students to try to learn about new areas" I think it is absolutely essential for a lab to reach out to new subfields, topics and techniques, and the only way this realistically happens is by getting PhD students and postdocs that work on this. Why do you consider this problematic?

@xLeitix: I should think that is obvious. If the researcher is not knowledgeable in the area, he may not be competent to guide the student. This depends on cases, of course. As they say, the devil is in the details. As I described in my answer, my own experience is that this can go badly wrong. This approach with postdocs is less problematic than students. They have more experience, for one thing. Also, you use the term "subfields". We aren't necessarily talking about
"subfields", but possibly entirely different fields.


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Is it acceptable practice to list solitary courses on an academic CV?
I took some solitary graduate-level courses as a non-degree student at some US schools and plan to take further modules in England. These courses relate to my other degrees and certificates, but are from more elite institutions and provide more advanced, specialized training not easily found elsewhere. Is it acceptable practice to list solitary courses on an academic CV? What section and in what format might this appear in?

Acceptable?  Sure.  Useful?  Probably not.
If you're applying to graduate programs, then listing these courses would be appropriate.  On the other hand (at least for US schools), you need to submit official transcripts for those courses anyway.  Also, if you expect those courses to play a significant role in your admission, you need to make that case in your application statement.
If you're applying to an academic position that is primarily teaching, then listing the courses might be appropriate to show that you have at least taken courses on the topics you intend to teach.  But if you expect those courses to play a significant role in your hiring, you need to make that case in your application statements.
If you're applying to an academic position that is primarily research (including most postdocs and tenure-track faculty positions), there's no point in listing what courses you've taken.  With rare exceptions, your research record (as listed in your CV, described in your research statement, and judged in your letters) is essentially the only thing that matters for such positions.  Teaching experience might play a role, but classes that you've merely taken won't.  If you think specific courses significantly strengthen your case—making you one of those rare exceptions—you need to to make that case in your application statements.

The long form of my CV used to include a few example courses to indicate what I'd learned on my various degrees (after the degree I said "courses included: ...").  I have no idea whether that helped, but I don't see how it can hurt, unless it makes the CV too long & people miss something more significant.  But I think it does show something about your specific interests and level of commitment to academia.


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Where to find easy research topics any student could write about?
I teach a writing course designed to prepare international students for graduate school, mostly social science majors. The students have no experience writing academic papers. I have found that lists of sample TOEFL and GRE writing topics, such as this list of sample writing topics found at ETS, serve as good essay topics for these students so that they can practice organizing their ideas in writing. These topics are: (1) simple; (2) can be addressed by students from any major or culture; (3) and can be supported by the students' opinions, not research.
Next term, the course will focus on introducing research methods. Were can I find topics that are: (1) similarly simple; (2) can be handled by students from any major; but that (3) will require students to rely on academic journals for support? I need students to practice gathering information, evaluating the credibility of sources, and assembling their ideas and evidence without getting bogged down in the complexity of the subject.

As far as I am concerned research methods are disciplinary in nature.  Even restricting your topics to social sciences, and your research skill focus to literature reviews, I'm not sure you're going to be able to craft topics suitable for all social science disciplines.

When I have taught research methods for undergraduate work, I find that it is best to give the students a lot of freedom while still requiring acceptance for the topics. I do not think giving a list of acceptable topics is the way to pique the interest of students.
It is better in my experience to guide them and let them know that they know their field better than anyone outside of that field, so they are capable of finding a suitable topic by themselves.
I have had students who choose "I want to study the effect of someone smiling at you." It could be an interesting topic but, since my students are all business majors, I give them the restriction is that it must be related to business. When they submit this topic, I hand it back and ask them "How does this relate to business as I said all research in this module must?"
I guess I could provide them a list but I really think that will just end up limiting them. Better to coax them out of their shell and get them to really start thinking and choosing and living with the consequences of their decisions.

As far as I am concerned research methods are disciplinary in nature. Even restricting your topics to social sciences, and your research skill focus to literature reviews, I'm not sure you're going to be able to craft topics suitable for all social science disciplines.


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How to identify the lead scholars for a particular research subject?
I watched a lecture answering the question "How did Native Americans arrive in North America?" During the presentation, the presenter put up a slide showing the "5 major scholars" working on answering that question, and which theories each scholar supported.
Were it not for those slides, looking at JSTOR or Google Scholar, I'd be lost to know which papers were written by the top scholars. There are so many scholars studying that question.
Finding names on faculty pages isn't so useful...a professor could work at a small state university, yet be very highly regarded in their field, the leaders aren't all at Ivy League schools.
Starting with a research question or specific subject area, how can I identify who are the major scholars in the area?

This doesn't really answer your question so I'll do it as a comment - if I'm looking into a new topic, the first thing i do is a google scholar search for a recent review of the topic. A good review will orient you to the field and ideas and will also cite many good papers

How do you wish to define 'major scholars'? Some definitions are inherently more quantifiable than others (e.g., it is pretty straightforward to work out who is getting the most citations; but much harder to determine whose views are most respected).

Starting with a research question or specific subject area, how can I identify who are the major scholars in the area?

The usual method is to start with some kind of literature search to see who has written books or papers on the subject.  This will usually lead you to a number of authors (some of whom may be dead but others who are alive), and you can then start looking them up and reading their university profiles to see how heavily they specialise in that area, and what credentials they have in the area.  If you can identify research institutions or journals that specialise in the subject area of interest then you can usually find a list of their personnel (e.g., editors of a journal), and these people would usually be experts in the field.  If you can identify important prizes in the field then you can also look at lists of prize winners to try to identify the top experts.
This process is similar to the standard literature review process, insofar as it usually starts with some small leads, which then snowball into bigger leads, and so on, until you get a good overview of the big names in a field and you find out more and more details about their writings and credentials.  If you can identify one big name in a field you can also write to that person (assuming it is important enough that you are not wasting their time) to see if they can recommend other experts.

I'll limit this to those fields for which national and international conferences are an important part of the life of a typical scholar.
Who are the invited and "featured" speakers at large conferences? Usually they will have a long and important place in driving the field in recent (but perhaps not the most recent) years.
If possible, go to several conferences and see who creates "buzz". Who gets asked questions? Who has an "entourage"?
Sometimes, however, the time of the superstars is a bit past. Look, then, to their students and to those who have extended their work. Unfortunately, however, you will come up with a large group. But if a lot of people are looking to learn the current thinking of the wise old folk, they are probably still relevant.
Another way to learn of the up and comers is to see who is given the "best paper" award at a conference. No guarantees, but that might indicate a bright future at the edge.
Caveat: "Field" is pretty nebulous. Math and CS are both highly balkanized, for example. I suspect Physics and some others are too. The specialties and the specialties within specialties have their own superstars. If the specialty is narrow enough, there may be only a few people contributing significant work. The technique here works better for those more widely known than narrowly, unless you can find conferences with a narrow focus.

When looking for leading scholars in computer science I typically start by (1) looking for leading conferences on the concrete field. After having a set of well recognized conferences I (2) start looking for authors that appear in more than in one edition of the conference. After that just search on Google Scholar or Scopus and confirm if they indeed do research in the topics that you are interested in.
The same process can be used for journals, just check for authors that appear in more than one issue of the journal.
However, this is the way I use to find lead scholars in computer science field, so maybe it does not generalize well for all the research fields. Also, sometimes there is some bias in authors that always submit to the same conferences, so take everything with a grain of salt.

That brings us to the beauty of quantification. Change everything into numbers. Make them measurable. One among many ways to do this would be checking the index scores, be that h-index or i10-index or some other indicator.

license: Creative Commons - Attribution Share-Alike - https://creativecommons.org/licenses/by-sa/4.0/


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How to motivate students to complete work that I cannot frequently check?
I assign my undergraduate students assignments from a workbook as homework. The homework amounts to about 30-minutes per day.
It is impractical for me to collect these workbooks at each lesson, or even weekly, as any days when I am checking the work are days when the students don't have their workbooks in hand. Furthermore, I cannot constantly collect, carry, and redistribute hundreds of workbooks each week.
As such, I've limited my collections of these to twice per term. The results, however, have not been good. A great many students save many weeks of work until the last minute, only to discover then that the task is far more difficult than they anticipated.
How can I motivate my students to complete work daily when it is impractical for me to frequently assess it?

Try visibly rolling a 20-sided die at the start of every class.  If it comes up 20, collect and grade the workbooks.  Alternatively, put numbers on each workbook, and then only collect and grade the workbooks that match today's die roll.

Are these undergrads freshmen?  Many colleges treat non-freshman undergrads as adults and let them learn from their own mistakes instead of hand holding them...

@JeffE: I had a professor do that, but the die had far fewer sides. I'd be afraid 1:20 odds wouldn't provide enough motivation. Of course, 1:6 odds might instill more motivation, but the instructor would have to do more grading, too. It's a tough nut to crack.

@J.R.You could always use a six-sided die and then use "professors's discretion" to decide not to collect them if six happens to come up more often than you'd like to grade.

The other answers are excellent. Without knowing your field or the nature of the workbook assignments, I'll give the following answer:
I have become a big fan of automated online homework systems (although I know some students hate them). If you happen to be in a field where these systems exist (e.g., Physics, Math, Chemistry--WebAssign, MyMathLab, etc.), consider this for a future semester.
The reason I bring up these systems is that (1) they provide a forcing function for the students to do the work, (2) the grading is automatic and immediate, (3) the better systems provide guidance on problem solving, and (4) the math-related problems can be randomized so students can't copy of another student's work (as easily...).

Ideas for your current system:

Do a cursory check of the books every week. By cursory, I mean "check that there is writing on the required pages," and give a check or not. This doesn't preclude them from not putting in much work, but at least they will see that you've got eyes on them each week.
Give them a daily 1-question quiz that is straight from the homework (if it is the kind of work that has "correct answers").
Reassess why it matters that they do the work, and lay it out to them plainly. Do the students who procrastinate on the homework really do more poorly with the material? If the answer isn't an emphatic "yes," then why do you care? If the answer is "yes," then lay this out to them on the first day of class: "I assign the workbook material because it helps you get a better grade in the class. It's up to you to do the work, and your grade will almost certainly reflect the amount of work you put into the workbooks. I don't collect it because I expect you to do it on your own, and it's your grade that matters." In the end, your job is to give them the tools to learn the material, and their job is to use those tools. At the collegiate level, you can expect them to take their education seriously. I.e., "You can lead a horse to water..."

Assuming adulthood (point 3) only works in isolation if you're willing (and known to be willing) to actually fail people who do poorly despite your warning, even if that ends up being half the class.  That's harder than it sounds.

@JeffE it may be hard, but a teacher owes it to their students to let them learn from their mistakes. A teacher who passes students that don't deserve it sets those students up for greater failure, later - even if half the class.

Can you elaborate on these online systems? Automated grading does not really sound like a good idea, especially if the system is even more cheat-able than the classical grading

@TobiasKienzler I'd urge you to look into WebAssign and MyMathLab for more details, but I'll say two things: (1) I consider it much harder for a student to cheat -- numbers for problems are randomized, and answers need correct units. Students can't simply copy from each other. Work can be shown to some extent. A human (i.e., you, TA, etc.) does have to grade any answers that require text responses. (2) If you teach a class where cranking through example problems is important, these tools are fantastic b/c of the practice for students.

@TobiasKienzler I should add--these tools are not so good for classes where answers don't boil down to a number, or for classes where the result is less important than the method used. Obviously, that weeds out many classes, but if there are "workbook" problems, there may be an automated solution.

@ChrisGregg I see, using randomization makes it interesting - assuming the generator is fair or one can request a "re-roll" in case of unintended singularities... Of course one could still convince (pay) someone else to login on one's behalf, that's what I meant with cheating, i.e. impersonation.

@TobiasKienzler There are ways to cheat, but you could also pay someone to write out the answers for paper homework.  In the cases where the system isn't perfect (warning:swear word onscreen, and, as you can see, students give it mixed reviews...) or here, it's pretty easy to handle each case individually.

For some of my computer science-y courses we wrote scripts which could automatically grade homework - which was usually code files. I recognize that this isn't possible in many, many fields but wanted to put  my $0.02 in.

I'd go further than saying some students hate automated online homework systems - in my experience as a TA (physics) talking with students, these systems are almost universally despised. They offer no chance for partial credit and little to no guidance as to what a student might be doing wrong when their answer is incorrect. Of course, I understand why they're necessary for large classes.

@DavidZ Absolutely agreed - and who can hold that against students, when like in Chris' first example π is not treated as the correct answer, since "the correct answer is π/1" m-/ And indeed the most important part of good exercises is not the end-result (which in really good exercises is even provided) but the way to get there. And I have yet to encounter an automated system that manages to actually teach a student instead of such a silly black&white system with too little tolerance. But yes, it may be a necessary evil in large classes, though that suggests a different problem altogether

@TobiasKienzler I'm going to disagree with DavidZ's opinion that all students dislike the system--it's a matter of setting expectations with the students. The first thing I tell them is that if there is an issue, they shouldn't spend more than a few minutes trying to figure it out, and then talk to me about it. It's a simple matter to adjust the grade. If the students have a problem with the system, I partially blame the professor for not understanding the limitations, or for not being flexible.

@TobiasKienzler Also, MyMathLab does teach the student -- it explicitly has an option to walk through a problem, then the student gets a chance to try alone on another problem. Also, I give the students the option to keep trying problems until they get them correct--every student has the opportunity to get 100% on every assignment. Again, it's about using the system effectively--professors who blindly assign problems without the willingness to work within the system's limitations is not using the system appropriately.

I see - yes, if it is not used as a replacement for teacher-student-interaction but rather as an "assistant" that pre-filters the less-complicated problems, it might work fine. I can't speak for David (though he's also a Physicist) but at least in my Physics study the classes were never that large that five PhD students couldn't adequately take care of "manually", so I didn't collect any experience with such systems. Then again, it might be difficult to have a computer review Feynman diagrams...

@TobiasKienzler Your point is well taken--I doubt you're going to find a decent automatic system for advanced classes. Also, if you have TAs, that changes things -- I assume the OP does not have TAs who can grade assignments, but with grading manpower, you can be much more flexible with the types of work you can assign.

That changes a lot indeed. And if OP has to teach a large class all by themselves something is rotten. And indeed their other question from yesterday (the one about their supervisor requesting them to remove their name from a paper) suggests that truly is the case. Sounds like a place I'd try to get away from as far and quickly as possible...

Intrinsic motivation is always a better motor than threats and coercion. They are, after all, adults. So, try to make them understand that doing this is important for their progress, and thus completion of the course. Also, be open to suggestions from them on how to make it less cumbersome (for example, by skipping a week if they are really hard-worked at that particular time).
You can, however, combine this with extrinsic motivation forces, in order to help them see very concretely how the benefits of doing the homework regularly. For example, collect 5 of them at random every week. Another idea would be to tell them in advance that 50% of the final exam will be on problems taken from the workbook: they will understand very easily that, if they have done the homework correctly, it will really help them secure a good grade.

The emphasis on intrinsic/extrinsic motivation reminds me of the goals behind much of the recent team based learning teaching orientation. The extrinsic motivation comes from interactions with the group, not only from the teacher.

Intrinsic motivation will be a much different matter in a required math class than in an elective creative writing class. I completely agree that its better, but there are students who will, in almost no circumstances, choose to be intrinsically motivated in e.g. a compulsory math course.

Also, the 50% of the final exam will work fine as long as it is OK if they do the entire workbook in the week before the final. Those who do may even do better on those problems as they will recall difficult details better. However, if they really need the knowledge from the workbook to understand material during the semester, many of them won't have learned any of the workbook material until just before the final which can be problematic.

@JohnRobertson then introduce half-term exam, or something like that… also, they might believe that doing the work at the last minute is better, but we know it ain't so.

While I'd like to recommend the on the test one, I've seen that lead to either people brute-force memorizing all the solutions, without doing the questions, or, at the other end of thespectrum,  just not doing them anyway.
On the other hand, it got me to do a lot of questions when I was an undergrad, so it might work.

Some ideas:

[reward] Give some exam bonus to volunteers who will correct the homework on the board
[threat] Randomly pick a student to correct the homework on the board and give him/her malus if he/she has not done it
[threat ++] Make an exam (each week first, then each two weeks or randomly) in class on the given exercises, collect and evaluate the work

I usually give short quizzes based on the homework assignments. You do not need to include the exact homework questions there (though you can do it too) but they should satisfy the condition that whoever can do the current homework problems should be expected to pass them and whoever who can not should be expected to fail. I find this system more encouraging and revealing than grading a random subset. For completely routine things (like basic arithmetic, trigonometry, etc.) various automatic online systems are really good. You need to be very careful with how you set up the questions there and it can take a full day for one course but you can do it just once and never think about it again until the time to print out the student scores comes. Just don't forget to make those scores a noticeable portion of the grade. The other advantage here is that you may (but aren't obliged to) allow the students  several attempts before they fail an online test, so they can really learn in the process, not just be evaluated.

I had a prof who marked us on completion. He taught 3rd year quantum physics for chemistry and would give out a page of reasonably easy questions that he marked, then several pages of really hard questions he wouldn't, but if you brought him each sheet completed he added 1 to your total grade. So whereas before you were out of 100, now you are out of 101. (Roughly,  his marking system was out of more then 100 I think).
You could also complete previous years worksheets for the same thing, or textbook questions, anything like that. One page of questions (not answers) was one mark, or one of his old worksheets was one mark (Since the solutions were online).
This sounds like a lot, but someone worked it out that the first one you did added 0.4% to your final grade or something like that, but each one you did after that added less and less. The class perfectionist misunderstood the system and did 40 pages of textbook questions, and managed to raise her final mark by something like 4%. I just did all the old worksheet questions and got a percent or two, which really isn't much, but damn, did having done all those worksheets really help on the final.

Ask the students to photocopy or photograph their completed work from the workbook each week and email them to you as PDFs/JPEGs.  (You may want a dedicated email to receive such files.)
Even if you don't grade the electronic copies, you can make submission a portion of the homework grade, e.g. 10-20%, depending on what your rules are about later changes.

As a slight variation to this keen idea, depending on what LMS is used, students may be be able to submit the scanned work to the LMS. A potential advantage to that approach is that it becomes easier to see who submitted something, and who didn't.

@J.R. Your idea is solid, except if you are doing this, then that means your LMS is lame.

@emory - I'm sorry, I'm missing your meaning here. I don't understand how students submitting electronic copies of an assignment to an LMS makes said LMS "lame."

@J.R. I thought you were asking students to do their workbook exercises, scan them, and then submit the scanned copy to the LMS.  If the LMS was cool, the students would just do the workbook exercises in the LMS itself - making things easier for everyone.  The LMS could grade many of the questions itself providing students instant feedback.  The LMS could populate the teacher's gradebook.  If your LMS does not support these features, then your suggestion is pretty good:  it is your LMS - not you - that is lame.

@emory - Sure, but that might depend on the nature of the assignments, and not just the capabilities of the LMS. Not every assignment can be graded automatically (like proofs, e.g.); not every exercise can be easily imported into an LMS (such as those with many mathmatical symbols and equations); lastly, for some assignments, scanning may indeed be the best way to upload (as when students have to do large-scale diagramming). Exactly how the problems and solutions get loaded into the LMS is immaterial; I was merely suggesting using the LMS as the main collection mechanism, as opposed to email.

(cont.) I'm assuming these exercises can't be easily graded by an LMS answer key; otherwise, that would be the obvious solution to the problem.

Although there are other answers here which get to this point, I would look at making required things required. If you need the students to do it every week, then make them do it by tying their grade to submitting it every week.
The problem is that you don't have time to assess their work every week. I think everyone here can appreciate that. However, you need to at least partially solve that issue. One key for that is the proper use of technology. Either a Virtual Learning Environment, email, or other online homework systems.
If you cannot assess all of the students, then a random assessment might get what you need. After all, as a teacher, you should be providing feedback to your students. So, have them submit their work electronically (yes, this requires a change from a paper workbook approach) and each week randomly select a few for assessment. If you see some are stars, skip their assessments for several weeks. If you see some are struggling then assess them more often. The students don't know who will be assessed but their grade might not be based on the assessment of the homework, just that they attempted it for that, you can simply scan a list of submissions. Again, you could do this with email if you have no other solution.
Ideally, the students would be intrinsically motivated and you would not have to do any prodding but in my experience some students do need a little prodding to get them to overcome the inertia  of laziness. For that, submission might be enough. However, in the end, you will need to assess some. You should assess as much as you can but you have to balance this with your other needs. There's a lot more to teaching that assessment but assessment is a pretty important aspect of what we do.