I'm back to working on my class on Experimental Design and Data Analysis. One of my goals for the course is to have students work in groups to write an NSF-style proposal. So I sat down this morning to think about the steps it takes to write a research proposal. When I turned to google, I found a lot of tips on the writing of proposals, but not a lot of tips about how to actually generate the content that goes into the proposals. Since my course focus is how-to-do-science, I'm more interested in the content than the style. (Yes, I'm sure style can make or break a borderline proposal, but if your science isn't good enough or isn't spelled out clearly enough, style is not going to matter.)
I'm also intentionally leaving out the very-important-and-very-time-consuming bits about wrangling with forms, working out budget details and justifications, and paying appropriate attention to the broader impacts of the work. These are things that my students will have to deal if they become a PI or if they are writing and managing student grants, but they are not where I want my students spending effort in my class. With that for a preamble, I present...
ScienceWoman's Guide to Writing a Research Proposal in Eight Easy Steps
- Select your collaborators based on shared research interests and complementary expertise.
- Brainstorm some general research topics that build on what you already know. (Read some recent reviews or research papers to help you identify open questions in the field.) Gradually narrow your focus to a few related possible research questions.
- Identify your funding source and read the solicitation carefully.
- Identify one major goal for your project.
- The next steps should proceed simultaneously and iterate until your research plan is coherent, if not fully fleshed out. All subsequent steps should also be accompanied by actually writing of drafts of text for your proposal.
- Define a set of objectives (or specific aims) in support of your goal. These objectives could be built around hypotheses to be tested or specific questions to be answered.
- Define the possible methods you could use to reach your objectives, given the limitations of expertise, time, funding, and your institutional resources.
- Collect, compile, and analyze any preliminary data that you can use to support your proposal.
- Add details to your research plan, making sure to consider (1) whether your experimental design will provide the appropriate data for the data analysis you intend to do and (2) the limitations listed above.
- Read more literature related to your research questions (and related questions). Start to write the introductory/background material. Tinker with your research plan as you learn from those that have gone before.
- Polish your proposal text until it is coherent, cohesive, concise, and correct in both content and style.
There you have it, how to go from a conversation over coffee to a ready-to-submit collaborative research proposal in just eight easy steps - albeit steps best taken with lots of iteration. OK, so who wants to
rip it apart constructively criticize before I inflict enlighten my students with it?
Oh, and see also Alice's thoughts on the special responsibilities of a PI on a collaborative proposal.
very useful. Thanks.
This is completely backwards from how my kind of science proceeds. First we get an idea, then we perform preliminary experiments, and then we look at the results of the preliminary experiements. Based on those results we see what collaborators we might want to enlist, if any, and then we figure out what sort of funding we should apply for.
I wouldn't in a million years start spending time writing a proposal before I have enough preliminary data to predict whether the shit is gonna work, whether it is gonna be interesting, and whether it is gonna be fundable.
Sure, in theory, we all build our proposals (unless they are a totally new research directions) based on preliminary data we've collected off the backs of our old grants (even though that's theoretically unethical). But, if we are going in a new research direction, like I am currently or like these students are, then we don't have that previously collected preliminary data to go upon. Instead we read the literature to get our ideas and we collect our preliminary data simultaneously with crafting the proposal.
BUT at the same time, when I forced myself to come up with this linear list of how to develop a proposal, I was distressed by how late in the list preliminary data showed up. I think I'd prefer a less linear process in which objective development, research planning, preliminary data collection, and background reading/writing were all happening in parallel and simultaneously.
How do the rest of you do it?
preliminary data we've collected off the backs of our old grants (even though that's theoretically unethical)
Wrong. If the preliminary data that supports the specific aims of a new grant was obtained while pursuing the aims of a previously funded grant, then this is perfectly ethical and legal.
shouldn't there also be a step where one asks why a particular bit of research matters?
consider Hilbert's list of 23 open problems in math
shouldn't one try to identify what are the 23 (or 47, or 192...) open problems in one's field (problems which, if solved, would advance the work of a very large number of people) and try to work on one of those?
and if such a list does not exist in one's field, what does that mean for the field and one's research goals?
Great comment, Stefano. (But I am ScienceWoman and not Alice.)
Asking why a particular bit of research matters is really important - that's part of why I want my students to be reading recent papers and reviews related to their interests (step 2). Not every field might have as formalized a list as you link to for math, but review papers and forward-looking vision papers do a great job of highlighting research needs. And for the fields where my students come from, couching our research in terms of societal or environmental impact is second nature to most people, since that's often what motivates our study of geosciences and related disciplines.
Perhaps this is a more cynical view (coming from a grad student that is struggling with NSF revisions to re-apply; I have preliminary data in some areas, some of the pilot work is still ongoing and I don't have results yet--but waiting for those results, given the long timetable of big grants, would result in majorly delaying my fieldwork), but does the question of whether the research matters "really matter" in terms of funding and the general system of academic rewards? Don't get me wrong, I don't want to pursue a research question unless I really believe that it matters, but it seems to me, particularly for students, its safer to go with a topic that is not too far in one of those open gaps of knowledge--because that makes feasibility and gathering sufficient preliminary data much more difficult. And regarding demonstrating that it "matters" in terms of intellectual merit and broader impacts honestly seems to me to be more of an issue of how well you can "spin" things rather than what's truly meaningful.
I remember reading somewhere that if science always proceeded in the model set by funding agencies, then we would never truly learn anything new... I'll have to think a while and figure out where I remember that from.
Also, I think the preliminary data thing is very frustrating--while I understand it's purpose, and think pilot work is important, it poses a bit of a conundrum--you must first obtain funding to do preliminary work, and do part of the project, in order to get funding--it's very circular.
Hi, I think one key thing that you have left out is "have others, who will 1) not be afraid to offer constructive criticism and 2) actually READ your proposal, do so, and give them the proposal plenty of time prior to the deadline to do so. This is what I consider "internal pre-peer review" and of great merit. Also, I think that when the idea is nascent, it is worth giving a ten slide max "grant test drive" (grant roast) of the hypothesis, SAs, approach, and timeline to a room full of people. People who may not take the time to read the grant as a "pre-reviewer" may give very helpful feedback in such a forum.
KGwinn - Those are great ideas! One of the things I am doing in my class is having students read sections of each other's proposals at various stages along the way. But it's a good reminder that I need to line up some friends to read my various proposals-in-progress before I submit them. And I love the idea of the grant roast.
Looking back over my history of generating grant applications (this is NIH focused in large part) I have to say that the specific ordering of points is unimportant.
I've had proposals that started from a really kewl new observation that just cried out for a spinoff from the parent project.
I've had proposals that started from reading a funding solicitation.
I've had proposals that started from a long time of being interested in a general research question and a very gradual coalescence of ideas into a plan.
I've had proposals that started from "I need to write a grant for this upcoming date, what should I write on this time?".
So to contrast with PhysioProf, I think the ordering of events is not strictly dependent on specific subfield. In my case it has to do with ongoing specific circumstances in the laboratory and my ongoing research findings and interests.
I was interested in Stefano's response to ScienceWoman. His comment brought to mind Leonard Mlodinow's wonderful book "Feynman's Rainbow". Mlodinow's take-away message from Feynman's life was that we should all do something that we deeply care about, and are excited about, which may, or may not, be on anyone else's importance list. To me, Mlodinow's message (as exemplified by Feynman's work and life) rings true.
I also think that ScienceWoman's initial step is important, and resonates with Jim Collins' work on team building in the corporate world, documented in his famous book "Good to Great". One of his take-aways from studying successful companies, is that the founders assembled a capable and complementary team with at shared goal of excellence BEFORE they decided what they wanted to do. I do not think that graduate science education does a good job of teaching this path, although I think that many successful scientists discover it for themselves.