From the computer screen to the lab bench: A physicist learns to do wet-lab biology

As Kenneth described in a recent post, the Center for Integrated Proteomics Research and the BioMaPS Institute for Quantitative Biology at Rutgers recently held a two-week “boot camp” program to cover a range of basic topics in molecular biology and biophysics.  The program was intended to serve the increasingly diverse community of scientists — with backgrounds ranging from physics and chemistry to computer science and mathematics — working in quantitative biology.

As a physics graduate student who works in the BioMaPS Institute, I was definitely in the target demographic.  In my undergraduate days I was mainly interested in particle physics and cosmology, so my coursework focused entirely on physics and mathematics.  I haven’t taken a biology or chemistry course since high school.  While I’ve certainly picked up a great deal of the necessary biology throughout my graduate research in biophysics, I could still use more breadth.

But I was primarily interested in gaining a very specific kind of breadth from the boot camp.  Besides having a background in physics, I am also a theorist by training, and I’d never had any experience doing “wet-lab” biology experiments.  (In physics, there is a very clear divide between theorists and experimentalists.)  But recently I’ve become interested in gaining some experience with wet-lab biology, both because it’s helpful for collaborating with experimentalists and understanding experimental papers, but also because there is a serious possibility I will pursue a combination of theoretical and experimental work next year as a postdoc.  Luckily, the boot camp included a week-long experimental lab for complete beginners like me, so it seemed like the perfect opportunity to try it out.

The best thing about having zero experience with something is that you can learn a whole lot really quickly.  So even the most basic, mundane aspects of doing the lab were new and exciting for me, things I had heard about in talks or read in papers but never really understood.  So this is how you pipette…and “streak a plate”…and purify proteins…and run a gel…and so on.  Here’s some photographic evidence (credit to Gail Ferstandig Arnold):

As someone who has worked only on the other side of research until now, it has been really eye-opening to have concrete experience doing experiments and generating data that previously existed only as abstractions in my theorist’s mind.  While I recognize that a week’s worth of exposure isn’t enough for me to jump right into doing all my own experiments as a postdoc — undoubtedly I’ll have to relearn all the stuff from last week again later — getting that first experience definitely gives me confidence for the future.

Conferences in Mathematics

Attending conferences is an important part of academic work. Conferences help us share our research with one another, find new collaborators and research topics, and keep up to date on our fields of interest.

I recently attended a bi-annual conference hosted by Integers (The Electronic Journal of Combinatorial Number Theory). I should say that my travel was generously supported by the conference organizers (i.e. the journal, via the NSF I believe) and my department & advisor, although I should say that one part of the conference experience is waiting with bated breath to get reimbursement forms processed. The government shutdown doesn’t help with that long wait either.

Rather than talk about the math, which isn’t really the point of this blog, I wanted to share some of the peripherals — the details of the conference, its format, what the experience is like. I have heard stories from other fields of study, and conferences seem to be very different from place to (figurative) place.

The departure is usually a bit of a rush of packing and preparing slides for presentations. Beamer (or equivalent) have become the de facto presentation method at math conferences, having (somewhat recently…) displaced the long-reigning overhead projector. After a day of travel, including a bit of a drive to Carrollton GA (home of UWG), I got some sleep before the first long day of presentations. I don’t travel much, and it is certainly stressful and tiring, but in the end I do enjoy it, especially driving.

Conference presentations are usually split into short (20 min) and long (50 min) talks, the later being given by specially designated (invited, plenary, keynote etc.) speakers of the conference. Most talks aim to communicate some new results, ideas, or insights into some type of research, and even for a specialized conference, there is a great deal of diversity in the subject matter. Some speakers speak to the general conference audience, while others speak to the very best experts in their slice of the research world. Many of the most interesting talks, to me at least, don’t probe into the depth of the subject, but give a gentle introduction or overview, and then outline or sketch the major new results or ideas. I’m more of a breadth-first guy.

The conference lasts for several days, as many conferences do, with talks back-to-back from about 9 to 5 every day. There are breaks for meals and coffee, and many conversations — professional and social — branch out from the main group during and after the sessions. Conferences are a great way to meet, re-meet, or quasi-meet people. I re-met Brian Hopkins, who has done some work related to my talk, and Bruce Landman, who has also worked in a related area (and is one of the conference organizers). Both of them (and several other audience members) had interesting questions and comments following my talk — one of the best parts of a conference is getting insightful feedback from colleagues. But I also met a few people more socially. I had a short chat about hockey with Cam Stewart after overhearing him talking about the sport, and sat at a table during the conference banquet with Steve Butler, Mel Nathanson, and Neil Hindman. Mel proposed an interesting problem at the conference that provided stimulating discussion and that I’ve found to be an interesting diversion even after the conference ended.

I also met other grad students like myself, many from closer to UWG (from schools like UGA, Georgia Tech, etc.), including Kate Thompson, whose advisor Jon Hanke  spoke here at Rutgers (by coincidence) only a few weeks after the conference (he was not at the conference). Making acquaintances can be quite beneficial — in this case, Kate and Jon know quite a bit about quadratic forms, which is something that is at least tangentially related to some long-term research ideas I’ve kicked around for a little while (but quadratic forms, on the whole, is a foreign subject to me). One day, if it comes up, I know somebody I can email if I stumble across questions or ideas I can’t wrap my head around.

Conferences in other fields can (apparently) be very different — my friends in the humanities tell me that conferences sometimes (often? always?) consist of reading papers aloud and asking prepared questions, while I have seen that some (many? most?) scientific conferences revolve around poster sessions and other such media. But for us in math, at least in my experience, it is a long sequence of presentations aimed (usually) at general information for the research-level audience, describing research ideas and perspectives and leaving technical details for the published page. I like this format, especially because it promotes dialog, discussion, and feedback — and helps people like me reach out a bit and meet others with similar interests and ideas in mathematics.

First-year Fears

The transition to graduate school is an exciting time in the life of a first-year graduate student, but it can also be a terrifying experience.  As a first-year graduate student, I will admit that the first couple of weeks of my graduate career were extremely overwhelming.  I found myself in an unfamiliar city surrounded by students who seemed to be more comfortable in this environment than I would ever be.  Many students already held advanced degrees, while I was making the transition straight from undergraduate.  Doubts arose and I asked myself the most daunting question that a graduate student can pose: “Do I really belong here?” Amidst the panic and feelings of discouragement, I hadn’t noticed that I had fallen victim to a prevalent phenomenon known as the “Impostor Syndrome.”

The Impostor Syndrome is characterized by feelings of inferiority that may be coupled with the idea that you are a “fake” or that everything you have accomplished thus far can be attributed to luck or any external factors not related to your own abilities.  These feelings can be quite debilitating and may interfere with your school work.  However, as graduate students we need to keep one important idea in mind: These feelings are absolutely unfounded.

So how can we overcome these feelings?  Well, one of the answers is in the question.  It is important to realize that you are not alone.  Other students have undoubtedly been through a similar experience.  Graduate students belong to a unique community, and it’s important to reach out to the other members of the community.  So talk with your fellow peers about their experiences as graduate students.  You may find that they share or have shared the same concerns as you, and they can help you find ways to resolve them. 

 It is also important to realize that none of us are perfect.  Most of us will encounter a moment in which we may start to question our competence.  At this point, it’s important to take a step back and recognize how far you have come.  This will give you a different perspective and will help you to realize how much you already know.  Keep in mind your moments of success and the steps you took to achieve this success.  At the same time, it is beneficial to identify potential areas of improvement.  Categorizing your weaknesses is a key step in working past these barriers in order to grow as a person and as a student.

Finally, take care to remember that you do belong.  You were accepted at Rutgers because your professors were impressed by you and believed that you would succeed in your program.  We are all talented and bright intellectuals that have the potential to make an impact in our respective fields.  When you are struggling with negative feelings, do not quit.  Be persistent in your efforts to overcome these feelings.  Have confidence in yourself and believe that you can accomplish great things – a positive attitude will yield a world of possibilities.

Never Alone in Graduate School

Feeling lonely and being alone are two different things in life and the lines can be blurred especially in graduate school. As graduate students we are surrounded by people with various backgrounds and skill levels from expert to beginner. On our journey we come across invaluable lab technicians, seasoned post-docs, crucial admin, fellow students, excitable undergrads, inspirational faculty and the tireless food and maintenance crews that help the university thrive. From choosing an adviser to “What I am going to do today?”, the range of graduate school decisions we must make for ourselves can be daunting without a continuous stream of affirmations gotten from within, “I am enough”, or an occasional “great job” from a colleague.

No matter the stage of our graduate life, it is important to separate loneliness from being alone and to put each in perspective. For example, I can easily feel lonely while I’m surrounded by labmates due to language barriers and/or thoughts such as “I am not on that project”, “Ugh, no one understands me,” or “Do I belong here?” On the other hand, I can be in lab at 10PM on a Saturday when no one else is around, not even the janitors, and not feel lonely. The longer I am in graduate school, the more I realize that I am not the only one who acts or thinks in this manner.

Graduate school is a training expedition of which we were chosen to be a part. We do belong. Spending time by ourselves or having “alone time” to delve into our projects is necessary and maybe uncomfortable. This uncomfortability can be devastating to our progress and heightened by numerous factors. It is through being social, as pointed out by a previous post, that we overcome hardships.

It is our choice whether we seek support or remain reclusive during our struggles and accomplishments. Sharing our feelings with the ones we trust allows emotional freedom, the formation of stronger relations throughout life and the possible entrance of a significant other. There are several social outlets on campus that can help impart a sense of belonging such as becoming a member of the Graduate Student Association (GSA), the outdoors club, or enrolling in a fitness class at the gym. Additionally, we can seek one-on-one help with a Rutgers counselor or read a book written by a Rutgers professor on how to obtain a graduate degree. Most importantly, helping others by listening, providing constructive feedback, and offering several high fives and a few “You’re the best!” to those around you is an excellent way to practice selflessness and build relations. These activities have helped me to stay inspired and rational.

It is imperative that we are involved in the graduate community to help build the self-esteem needed to withstand the solitude sometimes needed for thought and discovery. We are responsible for our graduate outcome and the actions we take. We should not do this alone. Let us take this moment to “start over,” as suggested by a previous blog, and get involved so we can become motivated, productive graduate students regardless of the hardships that pass our way together.

I can live for two months on a good compliment.” – Mark Twain

Welcome from GSNB Dean Harvey Waterman

And So It Begins…

With its perennial mix of enthusiasm and anxiety, the academic year begins.  For some of you it’s the beginning of graduate school, for others the return of routine or the continuation of ongoing work.  In any case, here we are again.

Unfortunately, graduate study resembles “school” (we even call it “graduate school”), with its suggestion of tasks being set by others and students dutifully completing them (or not).   This is terribly misleading.  For master’s students, the resemblance is particularly close, and disguises the importance of shifting the control of what’s going on toward the student, not the taskmaster—er, professor.  For doctoral students it’s all the more urgent that the student start creating his or her own box in or out of which to think.

Like weddings and bar mitzvahs, graduate study is the beginning of the rest of one’s life.  From the start, the student needs to figure out where she or he wants to go.  Not just how to get to the degree, but what it is for and what needs to happen in pursuing the degree so that the longer-term goal is reached in good shape.  This is not just the choice of which subject matter to emphasize or which courses to take.  It also means thinking about which relationships to cultivate, to whom to reach out beyond the faculty members of the one’s degree program, what skills are needed to complement the standard ones of the field of study.

For doctoral students, it means thinking early on about the kind of research that will best prepare for the career goals chosen.  And, therefore, the mentor(s) best suited to supporting those goals.

The risk is drift.  Take courses, read a lot of stuff, spend time working in the most convenient lab, postpone the real decisions, let fate unroll its verdict.  These are childish things.

Be, as the French say, sérieux.  It’s your life you are beginning.

At the same time, do remember to smell the roses.

Happy Year!

Harvey Waterman

Grad Student Experiences in Leadership

scrollThis will be a different type of blog post. This is actually a blog post from 14 graduate students who are about to graduate (or graduated) from the Rutgers Pre-Doctoral Leadership Development Institute (PLDI). This post is composed of short notes about their experiences and serves to thank the Faculty and Staff involved in PLDI.

What is PLDI?

Rutgers’ Pre-Doctoral Leadership Development Institute program (PLDI)  is designed to teach doctoral students aspiring to careers in academia how to navigate the challenges of academic leadership and thrive in the university environment. In this two-year certificate program, our professors shared a very precious gift with us – their experience. We created this blog in order to share our experience with them, with respect and appreciation for the gift they have so graciously given us. We hope that this will continue to serve as a reflective space for affiliates and future cohorts to share their perspectives.

-The PLDI Class of 2013

Tara Coleman: Program in Comparative Literature

When I first started the PLDI program and told my Dad about it, he looked at me strangely and asked why I needed leadership training if I was going to be a professor. He doesn’t know it, but I have already benefitted from my training a great deal, in ways as simple as being able to participate meaningfully in debates among my family and friends about Rutgers, the challenges facing higher education, and how I see my future in this field.

Continue reading “Grad Student Experiences in Leadership”

What are community land trusts, anyway?

For the last five years, I’ve been reading, studying, and working with a form of tenureship called the community land trust (CLT).  I’ve become very personally involved, serving both on the research and policy development committee for the National Community Land Trust Network and as a board member for the Essex Community Land Trust in Essex County. But what are they, you might ask?

A CLT is a participatory, community-based nonprofit organization that owns and holds land in trust for the common good. It leases that land to households that purchase the improvements (houses and whatnot) located on the trust’s land. When these households sign the ground lease, they are granted all the rights of more traditional homeownership. The main limitation in the lease comes with the resale of the home. They can only realize a certain percentage of any increase in the home’s value (usually between 10-15%), and can only sell the home to a household that falls within a certain income range. This allows them to realize a certain amount of equity while keeping the home affordable for the next low- to moderate-income household.

It was originally created in the late 1960s as a means for black farmers in rural Georgia to gain and control land. While it remained on the fringe of the affordable housing scene for a few decades after that, its star has been on the rise for the last ten years or so. It has attracted the attention of HUD, the Ford Foundation, and a few other major players on the community development scene. Why did I get interested in it? After spending time walking through neighborhoods in Essex County that had been hit hard by the housing/foreclosure/credit crisis, I became interested in forms of tenureship that would prevent housing from being entwined in the volatility of finance markets and speculative ownership. CLTs and another form of tenureship called limited equity cooperatives caught my eye, and the rest is history. My research is currently focusing on how CLTs are handling their emerging popularity and whether or not their radical ideological heritage as the means to fundamentally altering property relationships will survive the attempt at making them a viable alternative to traditional homeownership.

Any questions? Feel free to leave a comment! I love talking about this stuff.

Educational Jargon

As I have moved through my career as an educator and student of education, I have encountered numerous terms that, though unfamiliar at first, are now a part of my everyday vocabulary. Unlike terms associated with specific scientific disciplines, or even with other areas in the social sciences, educational jargon is present, at some point, in all of our lives. However, it is rarely explained and educators often forget that these are terms that they once did not know either.

When I teach Introduction to Education, I am constantly reminded that many educational terms are specific to the discipline rather than universal. One of the most commonly used terms is “pedagogy”, which I often explain as fancy way of saying “teaching style”, although it also involves a person’s philosophical beliefs about education and how children learn. In recent years, many terms related to the No Child Left Behind Act of 2001 (NCLB) have entered into everyday educational talk. For example, educators regularly refer to the ability of a school to make AYP, or adequate yearly progress. This refers to whether or not the required percentage of students in a given school have passed the state exams. It also refers to whether the correct number of students in each subgroup have passed the exams. This term “subgroup” is another piece of the jargon and refers varius groups present in schools, including racial/ethnic groups, English Language Learners, students with IEPs (individualized educational plans), and economically disadvantaged students. Whether or not a school meets AYP has an immense impact on how schools are run and the funding they receive, and it is often used without explanation. Other commonly used terms, like “tracking” and “inclusion”, refer to specific practices that are often debated in education. In order to make sense of what is written and said about education in the United States today, it is important to understand these terms.

In writing this post, I found two useful websites that give an overview of some common educational jargon. The Dictionary of Educational Jargon (http://www.teachervision.fen.com/pro-dev/new-teacher/48466.html) provides two pages of commonly-used terms defined for those entering the educational profession. The Glossary of Educational Terms (http://www.schoolwisepress.com/smart/dict/dict.html) provides a more extensive list of educational terms defined to assist parents in navigating the educational world. Both sites are useful if you would like to learn more about educational jargon, or, like many of us, simply understand what everyone is talking about!

The Nonsense of Birds and Whispers of Thieves: Reclaiming Jargon

Wading through the nonsense of jargon
Wading through the nonsense of jargon

The Online Etymology Dictionary’s definition of jargon is a far cry from its usage in common academic parlance: “[U]nintelligible talk, gibberish; chattering, jabbering,” the definition begins, derived both from either a cacophony of animal sounds (the gibberish of birds), or the guilded secret language of thieves. To accuse an academic of speaking in a jargoned tongue then is to level upon them the slander of either origin. As academics we are either like animals in a pen honking “nonsense” at one another, or, perhaps even worse, like rogues cloistered in our reclusive sanctuaries, using a shadow language to communicate when pressed to appear in public. If these beginnings can be taken as part of jargon’s connotation, how come neither seems to adequately reflect what I do at my job?

Fortunately, the word seems to have lapsed from its clearly derogatory beginnings. Jargon amongst academics is read as more of an inversion of its historical qualities than a literal recasting. Is the gibberish of the birds nonsense because they are animals, or because we refuse to soar to their heights? Did brigands adopt a shadow language to vex the common-folk, or was it instead a way to identify others within their community (who embodied a shared set of values)? The accusation of jargon smacks of anti-intellectualism. In other words, regardless of our accomplishments, we academics still trade in secrets; jargon suggests that we publish esoteric and oblique papers in obscure journals. Which we do, don’t we?

I think the reality of the situation is closer to cackling of birds, and buzz of thieves than we might realize. When I use jargon, at least, it is because no other word will do. Be it one of Foucault’s dispositifs of surviellance, Deleuze’s rhizomatic formations, or one of Bourdieu’s four-thousand (I joke, I joke…) categories of capital, jargon is the dirt that this little piggy likes to sleep in. Jargon points to a gap in my sense-making intuitions and the all too familiar failing of language to capture and categorize an increasingly complex world. The crutch of jargon reminds me, partly, of how little I know, and it protects me, almost totally, from critics who would attempt to reduce the nuance of my thought.

To be sure, I believe that jargon is neither a blessing nor a curse – instead it is something in-between. And although I do not like the simplistic equating of jargon with haughty ivory tower values, I also appreciate the ways it is, in fact, used as an insider language providing us academics a sense of intellectual freedom. Because there is a barrier to entry, and jargon laden language is frequently hyper-specific, jargon disrupts the posturing of crude argumentative critique by assuming some degree of prior knowledge is essential for healthy discourse. And, unlike the shadow tongues of yesterday, it takes little more than a dictionary to participate in most academic discussion and discourse. Maybe the trick is just to explain things a little better – to make the point that this pig’s dirt is also soil, fertile with ideas.

Teaching can equal lots and lots of grading…

As I have stated in a previous blog post I find that there are many advantages to being a teaching assistant, however, a major disadvantage is all the grading.  For me, leading a three hour lab class twice a week is the easy and usually fun part of being a TA.  It’s the hours of grading that puts a damper on the whole experience.  Students hearing any TA, professor, or instructor complain about grading will always suggest that students don’t need to take tests or complete homework.  However, tests and assignments allow instructors to gauge students’ understanding of the material and to assign grades.  So for those of you that are new to teaching, I have a few tips for making grading easier.

First, make sure to warn students about legible handwriting.  I have a strict policy: If I can’t read it, it is wrong.  There is no reason in a college level course for a TA to be straining to decipher a student’s chicken scratch.  Some students figure if they write badly enough the TA will just give up and assume they had the correct answer for a question that they didn’t actually know.  I make sure to remind students at the beginning of every test so no one can dispute legibility requirements.

Secondly, make sure the general guidelines for writing/completing an assignment are very clear and accessible to the students.  The better you formulate the assignment or questions, the easier it will be for you to grade.  Ambiguity allows students the opportunity to debate with you about the “correct” format, length, and depth of the assignment.  Having the guidelines posted on a course website prevents students from making excuses about not understanding your in-class explanation.

For the actual questions, make sure there are not multiple correct answers.  Instead of just one correct answer, you’ll end up with your expected perfect answer, a few good ones and five mediocre versions.  Additionally, make sure that other questions in the assignment do not answer each other.  It helps to develop a grading rubric before you start, so that you know exactly which answers you are accepting for each question and how any partial credit will be given out.  The grading rubric is especially important if there are multiple TAs grading for the course.  The rubric makes it much easier for everyone to be consistent and significantly cuts down on complaints of there being an “easy” or “hard” TA.

As with any skill, developing good test and assignment questions takes practice and knowledge, so make sure to ask other experienced TAs about their techniques.  I also suggest taking advantage of the many seminars and certificates offered through the Teaching Assistant Project (TAP) to hone your teaching skills.

What do we study in Library and Information Science?

Library and Information Science (LIS) owes a considerable portion of its genesis to the concept of the document and to the process of organizing these unwieldy creatures.  The relationship between a document and the concept of information (the all-knowing “I” within “LIS”) is difficult to fully articulate.  Philosophers, such as Mikel Dufrenne have tried to distinguish between aesthetic objects and signifying objects, with signifying objects, first and foremost, responsible for dispensing knowledge, even if they “engage us in an activity” (Buckland, 1997, p. 807).  It seems that this definition could be combined with the semiotic understanding of signs as artificial constructs with the result being that our designation and understanding of a document depends both on a process of social construction (framing the object as a document and arranging it within a context of other objects), and on the whole range of its evidence-bearing properties (text, watermarks, images, etc.) relevant to the mode of inquiry.  What is at stake with this definitional argument is not just the scope of “acceptable” phenomena of study within this field, but by extension, the other human activities that are appropriate areas for LIS-brand inquisition.  For instance, if deer tracks could be considered a document, then it would be quite appropriate to study the information seeking activities and cognitive processes that allow a hunter to track an animal.  I imagine few hunters would be impressed by the results of this study, but given a broad definition of document, our discipline could extrapolate from these results additional insights into human information behavior, generally speaking.  In this sense, our fundamental assumptions about the types of phenomena to be studied helps to determine the possible avenues of research that we might consider as researchers within the field of Library and Information Science.

One of the important lessons to be learned from this discussion is that understanding a discipline’s initial assumptions is critical to understanding what one is, in fact, studying, and why scholars make the decisions that they do when select topics and methodologies.  Indeed, it becomes ever clearer that the LIS field cannot be completely unified, theoretically or methodologically, because a plethora of different types of researchers are coming to the field with very different metatheoretical assumptions.  Considering the field’s multidisciplinary pedigree (ranging from linguistics, to cognitive science, to computer science, to psychology, to the humanities, and on and on), it is not surprising that scholars working in LIS are carrying a diverse array of metatheoretical assumptions.  Thus, within the methods of this field, we should really not be that surprised to see an eclectic mix of quantitative, qualitative and interpretive approaches at work.

Buckland, M. K. (1997). What is a “document”? Journal of the American Society for Information Science, 48(9), 804-809.

Research in Mathematics

Working in mathematics, I’ve found myself often asked the question “What do you do?” Sometimes the expected response is my “elevator pitch” (the short blurb about my area of expertise). But sometimes the question is more basic: “What is it you do, though? Do you just sit all day and think?”

Thinking [cc]

Now, to a large extent, many people in research spend all day thinking. However, mathematics is not simply the art of staring at a problem until the solution materializes in one’s head. (It’s worth a try, but often solutions do not come from epiphany alone.) I would like to discuss a few of the ways in which research is conducted in mathematics, with emphasis on the parallels and similarities that may exist between mathematics and other fields, perhaps to somewhat debunk that notion there may not be any such similarities.

Nature [cc]

Mathematics research revolves around proving new theorems — mathematical statements that can be deduced from the fundamental axioms of mathematics and from preexisting theorems. Generally, though, the procedure is not to make a big pile of the existing statements and to try to string them together randomly until one forms a coherent deduction that results in something meaningful. That would be pretty rough sailing! Mathematics relies on conjectures, put forth as believed to be true and hopefully proven by someone at some later time. While there are conjectures (e.g. Goldbach’s conjecture) which remain unsolved for long periods of time (sometimes resulting in notoriety), most theorems start out as rough ideas or propositions that are developed with increasing structure and refinement until they are proven. In addition to proving new theorems, other steps forward in research include constructing examples of mathematical structures and verifying theorems by re-proving them in new ways. Computational work is also done to improve theorems in the case that a theorem is quantitative (or sometimes, to prove that a quantitative result is best-possible).

El. J. Comb. logo

Know the literature: As in most fields, the mathematical literature is vast, and perhaps especially in mathematics, it is easily accessible. Increasingly, mathematics journals are available online — not just through the library system, but free for instant download on the Web. Having less concern for the preservation of intellectual property, many editorial boards have shifted to such open/free publication. (Indeed, I myself have a publication in The Electronic Journal of Combinatorics, which is precisely such a journal.) There is also the arXiv (the X is pronounced sort of like χ, the Greek chi), which hosts preprints of papers and other works of mathematics (and many other fields).

Being familiar with the body of literature, both seminal papers and other older works as well as the current cutting-edge work (as it appears first, usually on the arXiv), is an important part of conducting research in mathematics. Jacob Fox came to Rutgers in 2009, when he was at Princeton, to speak at a seminar. He noted during his talk the importance of being familiar with the literature, mentioning in particular how his knowledge of a certain publication helped him and his coauthors solve a problem.

Mathematics [cc]

Crafting and Proving Good Conjectures: One of the more important questions is where to start — if we’re going to prove a statement is true, what is that statement? Generating good conjectures is not a matter of guesswork or divine inspiration, at least not entirely (although the former may have helped from time to time, and the latter is open to some debate at least). Increasingly, experimentation is a common way to generate conjectures. It is also often useful to test conjectures in small, typical, or special cases (where “small,” “typical,” and “special” depend on the problem at hand). Usually a conjecture applies to too many cases to test them all (sometimes, infinitely many cases), so this methodology is often used to verify that the conjecture is sometimes true, but not to verify the conjecture exhaustively. (Conversely, experimentation may lead to a disproof of a conjecture by identifying, constructing, or otherwise elucidating a counterexample.) Experimentation may also help unearth components of the proof of the conjecture at hand.

It is also crucial to have a firm understanding of the big picture in the field where these questions are being asked. There is a substantial amount of context and content that guides someone to the right kinds of conjectures and the proofs of those conjectures. Mathematics is a field in which the objects of study are highly structured, and knowing these structures helps eliminate some of the technical clutter that can obfuscate the underlying truths that one wishes to prove and the bits and pieces that go into proving them. Many proof techniques can be adapted to different situations, so in some sense theorems may be proved by matching a generalized proof to a statement you would like to prove specifically.

Proof [cc]

Building Theories and Solving Problems: Tim Gowers is famously credited for roughly dividing mathematicians into the two categories problem-solvers and theory-builders (or rather, he is credited for noting this division in his oft-quoted The Two Cultures of Mathematics). I won’t discuss this dichotomy, but these two activities characterize much of the research done in mathematics. Proving single, unrelated theorems one-by-one is not usually how research goes. Rather, the enterprise involves longer strands of investigation — a dozen theorems sometimes collapses into a single stronger and better statement after enough exploration and refinement. Meanwhile, single ideas branch into many avenues of investigation. But generally, the aim is not to knock down one theorem, then turn around π radians and start over, but to work on larger-scale investigations. I could make a metaphor about bowling pins or dominoes, but I think the idea is clear. An important aspect here is also collaboration, which is a major element of research for many mathematicians. Working on papers is one part of collaboration, but other important activities include seminars & conferences (as participants and as organizers), expository writing, editorial work, and many other collaborative activities.

Structure [cc]

So the venture is to find good lines of research and establish some clear, path along that line. There are the two approaches. The first is to identify important problems and build up theory to solve them. One famous example is Fermat’s last theorem, which conjectured centuries ago and recently proved by Andrew Wiles. During those centuries, large swaths of mathematics were developed in large part as attempts to prove this conjecture (including Schur’s theorem, one of my personal favorites). This “problem solver” work weaves what might be the leading strands of the theory, loose and rough but pushing outwards farther than neighboring strands. Such work often moves mathematics in innovative or interdisciplinary directions, building bridges between fields of mathematics, and may also connect with work in applied mathematics. The “theory builders” weave strength and cohesion into the fabric (to extend the metaphor). To this end, they focus their research on developing and enriching the theory. They may work to classify all types of a particular structure, for example. Such work includes that of several Rutgers faculty in classifying the finite simple groups. This theory-building reinforces others’ work as they develop and solve conjectures, as it makes the underlying theory more robust.

Images used in this entry are used under fair-use and/or under licensing guidelines set forth by the copyright holder that allow use in this blog, as presented for educational or critical commentary. Images are copyright their respective holders and credit or source is indicated in each caption or in the text of this entry, as applicable. Thanks to Yusra Naqvi for her helpful comments and suggestions.

Research Methodologies in Laboratory Sciences- The Joys of Analytical Instrumentation

Obtaining a graduate degree would be so much easier if the analytical instrumentation would just work…For those of you would don’t have to run various chromatography instruments (ICs, HPLCs, GCs), thermo-cyclers, spectrophotometers, or any of the other numerous finicky pieces of laboratory equipment, I envy you.  You haven’t had to start your day thinking you would be able to run 100+ samples and get another figure for your thesis, only to spend not just a day but a whole week troubleshooting a mysterious problem, eventually determining you’ll have to order a part that will be delivered in three more weeks just to determine the concentration of your chemical of interest.  This of course holds up all the other experiments you had planned to set up.  I welcome you all to the joys of basic wet science research.

When I find myself in these situations I take a deep breath and think of all the reading I’ll be able to get done while I wait.  In my experience these situations usually arise from a few common problems and are a major part of the experimental process.  First, make sure you really read the instrument manual before you attempt to use anything or try to fix it.  Many times an instrument isn’t working because someone else, who had no idea what they were doing, decided to make a “repair.”  This is one reason it is important for senior members of the lab to instruct the new lab members on proper usage.  Secondly, remember to perform routine maintenance, as neglected instruments are like high maintenance boyfriends and girlfriends.  They will not work solely out of spite if ignored for too long.  Instruments work best when used and maintained on a regular basis. Third, always remember that this is part of the “learning” process.  You never really understand how something works until you have taken it apart and put it back together a million times.   Now not only are you an expert on the instrument, but you can also understand and interpret your data better since you know the limitations of the measurement. Your advisor and other graduate students will agree that this is a large part of the experimental process.

Lastly, if all else fails, blame an undergraduate and take a long weekend or a mental health day.  Delays are only to be expected when relying on group used equipment and if you are lucky someone else will have fixed it by the time you get back.  Plus working this hard makes obtaining the data that much sweeter.  So the next time an instrument, computer, or your “favorite” piece of equipment gives you a strange error message remember that you are not alone and that this is all part of the process.

Collaborative Hunting and Gathering

When I try to describe Comparative Literature to those unfamiliar with my field, I think back to the way one of my undergraduate professors put it. Comp Lit, she said, is like a mad scientist’s laboratory, except for the humanities.  Working and thinking in such an interdisciplinary field means that I am encouraged to think outside of the traditional boundaries of thought (in my case looking to Sociology, Caribbean Studies, critical theory, novels, film, and medicine). So how do I conduct research? The short answer is “Read a lot and write a lot”, but thinking about how I’m going to approach writing a paper on Ralph Ellison this semester, I intend to:

  1. Ask myself questions: What are the key themes and issues that have come up for the authors? What do I find most confusing/interesting? This is an important step, since the last thing I want to do is impose my theories onto a text or author. In the case of Invisible Man, I’m really interested in how the trope of invisibility is linked to blackness, and I wonder about the way the author portrays history.
  2. Make connections: This is what brought me to Comp Lit in the first place! How does what I am reading relate to my larger research interests? How can I make this useful as I think ahead to my dissertation? Is there a particular theoretical model that is useful in thinking about the topic? I’ve also noticed some similarities and differences between this novel and writing by authors from the same time period in the Caribbean.
  3. Meet with my professor: Our professors are an incredible source of knowledge and experience, and the earlier you meet to discuss you ideas, the more focused your ideas will become: they can steer you toward key texts and theorists and advance your thinking before you begin to dig in the stacks.
  4. Hunting and gathering: Sometimes I prefer to do more free-writing (my idea of “gathering”) to really hone in on what I care about;  other times, I really need to dig in and find out (“hunting”) what has been said and done on a topic first. With my Ellison paper, I’ll probably  go the library route first: a) the Rutgers library website, b) the MLA Bibliography, c) my subject librarian, d) Google Scholar, e) for larger projects, traveling to archives to access relevant original documents.
  5. Writing! One of my mantras is “writing is thinking.” The only way I can really know what I think about something is to write about it, so after completing steps 1-4, I’ll begin writing my paper.

Although there are certainly times when my work revolves around my own relationship with the texts I’m exploring, the process really is collaborative…having a conversation with the authors and filmmakers I’m working with. As the conversation gets larger and the stakes higher, the sources you tap into may take you farther than you expect.

Educational Research

In the field of education, there are many opportunities for research using a variety of methods. As part of the doctoral program, all students are required to take 4 courses in research methods divided between qualitative and quantitative methods. Depending on the research interest of the student, they may select either methodology, or a combination of both. Quantitative research is research that uses numerical data analysis to support a hypothesis. This type of research is done when conducting program evaluation or when looking for statistical support for a position. Qualitative research is done when the researcher is looking to explain a particular phenomenon. This includes case studies, ethnographies, narrative descriptions, etc.

As part of the research sequence, many doctoral students in the field of education conduct a pilot study. These studies, although they are conducted as part of the qualitative methods course, tend to combine qualitative and quantitative methods to some extent. The pilot study allows students to go into a setting similar to that in which they hope to conduct their dissertation research and get a first-hand sense of what conducting qualitative research is like. In this study, students may take field notes, conduct interviews, analyze documents, survey individuals, and practice any other techniques that they may find useful in their future research. Overall, the research methodologies sequence at the Graduate School of Education is extremely useful in identifying the methods that will be most helpful in conducting dissertation research.