Secrets of Success: Speed Up Your Learning with Triangulation

One of the secrets of being a really great grant writer is developing the ability to write quickly about things you know nothing about. Personally, I find this business challenges me to learn new things quicker than a meteor. Luckily, my training as a political scientist gives me unusual advantages when it comes to high speed learning. These advantages have been important to my success, since so much of what I do tends to take place on an emergency basis.

Ironically, I did not get good at learning until I was already half-way through my graduate career at Cornell University.  It was only then that I started to receive higher quality instruction from professors who were paid to share practical tips, useful advice, and easy-to-follow templates.

For much of my life, I had assumed that learning was supposed to be hard, confusing, and solitary. I had come to believe that enduring poor quality teaching was actually good for me. The big break-through for me occurred after I earned my Ph.D. At that point, I started taking post-graduate classes in statistics and something inside of me snapped. I realized that if the professors explained something to me and I did not understand them, then that was their problem not mine.  

One of the best ideas I picked up at the University of Michigan while I was studying statistics was the idea that I should read at least three statistics textbooks at a time.

This way, I found it a lot easier to make sense of a topic. In my experience, reading just one textbook makes study difficult, in part, because it does not give me any sense of what was crucial to know, good to know, or simply useless detail. By reading about the same topic in three different textbooks, I found that I started getting a better fix on the priorities attached to any given topic. This approach made it easier for me to concentrate on the important stuff I really needed to know immediately and to only memorize the details that I would need to hold on to for the future. Looking back, I wish I had an instructor in high school who might have suggested this same idea to me while I was studying physics or mathematics. (I also wish I would have had a high school teacher who explained that learning math and science was a long road to follow, but that it was quite beautiful when it all came together during graduate work.)

As a grant writing consultant, I use triangulation to help me quickly understand the client's field of interest.

Typically, I start by reading the client's literature, reviewing their website, and interviewing their staff. Then, I search on-line to see what other experts have to say about the topic and then supplement this with my own library research.

I have found that this technique of using multiple sources makes me a much more knowledgeable participant in the grant writing process. For example, I have found that the federal government keeps track of role-model programs, measurement techniques, and other things that will improve your grant application. There are resources out there on the issues of responsible fatherhood, healthy marriage, and substance abuse.  

The main thing, in my experience, is to not rely on a single source of information. There is safety and insight in accessing multiple sources of information on the same topic. At the very least, you quickly learn what it is okay to forget.

Up Your Game: How to Identify the Most Convincing Research

As you may know, I have had a lot of success in winning large federal government grants. In retrospect, I think that my background as a political scientist and as a published author gave me unusual advantages with federal government grant applications because so many of them are based on evidence derived from previous government studies. 

Since I had experience doing my own research and creating literature reviews as a political scientist, it was relatively easy for me to pick through federal websites and identify prospective interventions, programs, and practices that would most likely make a difference for the clients of the charities that hired me to work as a grant writer. 

As such, I apply certain internal standards to help me determine whether or not a particular study will present strong evidence in support of the program that I am trying to get funded. I will share some of these standards that I look for in the section below:  

1. Peer-Reviewed Articles: In general, I know to look for articles printed in peer-reviewed journals. This is just a fancy way of saying that an article in the journal will not be published unless a jury of independent researchers determined that it met their field's standards for academic research. In most fields there are the prestigious and the less prestigious journals. I look for ones that have been around a long time and for individual articles in those journals that have been cited by other researchers.  
2. Random Assignment: Next, I am particularly interested in finding studies which use random assignment to establish test and control groups to test whether or not a particular program or intervention works or not. A test group is simply the group of people - or animals, I suppose - who will be treated differently by the experiment. The control group, on the other hand, is supposed to be a group of very similar people who will not be exposed to the treatment variable. What is crucial is that the assignment to either the test or the control group must be random. This is a fundamental assumption behind the statistical methods used to determine whether or not there is a significant difference between the test and control group after the experiment is done. 
3. Quasi-Experimental Studies: Sometimes, it is not possible to simply assign people at random. In these cases, we might create test and control groups by recruiting volunteers or testing the same people before and after they were exposed to the treatment. These studies are called quasi-experimental studies. 
4. Population Similarities: The strongest studies are experimental and quasi-experimental studies that are based on populations similar to the one you are looking to serve. For example, you should not justify an experiment on college students, based on a study that looked at elementary school students. 
5. Multi-Site Studies: You will also be better off in picking larger studies that included multiple sites, meaning that the research was conducted at a number of different college campuses or in different cities around the nation. The problem with single site studies is that the single site might be contaminated statistically with unique people who respond to the intervention in the same way simply because they already have so much in common.
6. Attrition Rates: You need to pay attention to the little details in the study like how many of the participants dropped out of the study before it was done. This is because the people who dropped out will influence the final results of the study. 

Finally, you should be aware of the possibility for "experimenter bias" which is the tendency of the researcher to confirm their own suspicions in their own study. Sometimes this happens on purpose when the researchers fudge their results or manipulate their data to match their own conclusions. Other times there is an error in the study itself, but the research fails to notice this error because the overall study supports their conclusions. Since the results break their way, the researcher sees no need to double (or triple) check their own results. To guard against experimenter bias, I like to find studies where the researcher(s) appear to be sincerely surprised by their own results. To me, this is at least one indication that they are being honest with themselves and their readers. 

Dusting Off the Classics: Hot Tips for Recycling Grant Proposals

One of the best ways to speed up the grant writing process is to have readily available templates based on earlier, successful grant applications. Frankly, even copies of previous losing grant applications are immensely helpful whenever you sit down to write a new grant. 

The challenge is that the grant reviewers can often tell that you are simply recycling a previous grant rather than preparing a new, fresh, cohesive application for their benefit. 

Despite this difficulty, I have had a lot of success in recycling earlier grant applications into successful contemporary grants. Part of the reason is that I implement some key changes that insure the revised proposal still looks fresh and relevant. 

First, I am very careful about updating all of the dates in the document related to program goals and objectives. Leaving in a prior date is a powerful signal to the funder that you are simply recycling an old version of a previous grant.

Second, I make sure to update the research used to support the grant application so that the footnotes indicate that we are using the most recent articles in the field. These articles may still have the same information as the earlier articles, but they look sharper with a more recent publication date. 

Third, if I do add some new information to the existing grant, I make sure to balance that additional information out by referring to this new information in three or four other locations in the grant application. This makes for a more consistent application. It also creates the impression that you have thoughtfully revised the proposal rather than simply recycled an existing one. 

Finally, I am also careful to revise the grant so that it reflects a single voice. We all have slightly different, habitual writing styles. The reviewers can often tell that a grant has been recycled simply by noticing the abrupt changes in writing style that sometimes appear in a grant application. My favored technique is to rewrite each line of a previous grant so that it reflects my voice and not the style of the previous grant writer.