I’ve already said that you should not host it at your university, for that may be snatched away, with links where you don’t want them. Also, you have more control elsewhere. We use WordPress because it is easy enough to keep up-to-date, even for a PI. Yes, you should be able to update your own web page. It isn’t that hard with WordPress, or probably with other sites designed for bloggers. If you don’t want to blog from it, just turn off comments, and add in lots of pages.

We have just spent a lot of time updating our web page in preparation for the prospective graduate students that will show up tomorrow, and for the ones from last week that are still deciding. It is not done, but it is much better. I learned from Andrew Read That it is really important to have sections on the questions you are asking, and sections on what you have figured out. Not everyone is going to be reading those papers. A lot of people just want to know what you have done, and what you are up to. We added a section on research questions, and on research achievements, just today. The research achievements are broken down into areas since we have been at this so long. It was a lot of fun to write. The Dictyostelium section is not yet broken into subjects. The social insect part is not done by any means. I hope I get time soon to finish it since it is very nostalgic to remember all those wonderful days in the field. Dave had fun going back to his earliest days, and putting in a section on plant sociobiology.

If you get a good web page that you can update going now, you won’t be in our position of creating a webpage that represents 30 plus years of work.

Some people have videos of them giving lectures. This is an excellent idea, for we need to know someone can give a great talk before we invite them. Maybe you were taped somewhere you could link to.

I know you have a lot else to do. So do I. But this is important. Enjoy.

For me, graduate school in the Zoology department at the University of Texas at Austin was, the most intense and glorious learning and discovery period of my life. It felt so good to discover that my paint-dotted wasps had done something completely unexpected. I paced those trails of the Brackenridge Field Laboratory thousands of times, patrolling from nest to nest, taking roll call and learning. It was not a solitary experience because UT made it easy to involve undergraduates in research. It was not a confusing experience because my fellow graduate students and my professors were always interested in my stories. My work would have suffered without their, usually gentle, criticisms. My cohort of grad students and my major professors have become life-long friends. I also learned well what others have discovered, that I should keep up with the literature, attend seminars, hear and share new ideas. There were some things I did not learn well, mostly because of my own devotion to field work, and impatience to finish. I did not learn how to write effectively. I did not learn much about the whole business of being a professor. I did not learn how to collaborate extensively, though I think that was less common then. But I managed to pick these things up later.

Should I get a Master’s Degree? Don’t get one, or at least don’t apply for one. The M.A. or M.S. is not a necessary degree on the way to a Ph.D.. It is something you might get with a thesis, or you might get after you’ve passed to candidacy, the stage in getting a Ph.D. where you’ve finished all exams and coursework. We do not generally offer funding to people that apply to get a Master’s, and you want funding. This degree can be very useful in more applied fields where it is a terminal degree for going into industry. It is not the terminal academic degree, so just go straight for the Ph.D.. I usually think that people applying to us for an M.A. or M.S. are simply poorly informed, and encourage them to switch to a Ph.D.

Can I restrict my choice to a certain part of the country? Wherever you did your undergraduate work, moving to the East Coast or the West Coast might be enticing. Staying close to home might be attractive or necessary. You may have a spouse or other family considerations that keep you in a certain area. This kind of limitation is acceptable, since there are numerous excellent programs. But I caution against this kind of limitation if you don’t have to make it. In particular, there are a lot of fabulous programs in the middle of the country. In my own broad field of evolution and ecology, going right down the middle, Minnesota, Wisconsin, Michigan, Iowa, Chicago, Washington University in St. Louis (my home and the best!), Illinois at Urbana Champaign, Indiana, Oklahoma, Texas, and Rice University (my longest home) are all outstanding, to name just a few. One of these or others in the heart of the country might be your best choice.

Should I consider a Ph.D. outside the U.S.? Most European universities teach and learn largely in English these days, so they can be considered. Make sure you can get funding since many places have limitations to EU citizens, but maybe you have dual citizenship. The Ph.D. degree is also often very different from an American one. It can be a contract to do a specific project in three years, with no course work at all and little freedom to choose your project. There are quite a few great programs, so look into this if there is a professor in Europe whose work enthralls you. I have less experience with Ph.D. programs outside Europe and so cannot competently tell you about them.

What do I look for in an advisor? The ideal advisor guides you through all phases of your Ph.D., then supports you through the rest of your life as you apply for jobs, fellowships, or special opportunities. She or he is also a leader or a rising leader in the field, teaches expertly, and has assembled a great group of other grad students, post-docs, and undergrads. You will learn from these people as much as from the advisor. You should of course absolutely love the research questions and approach of this advisor. The advisor should give you freedom to make your own discoveries, yet guide you when you need guidance. Often your first projects will be in areas suggested by the advisor, while later ones will be more independent. Your advisor should be happy and funded. The lab group should meet regularly to discuss articles, present research results, and for fun.

Why are the other grad students so important? The other grad students are the people you will learn from. They are likely to be better at the statistical package R than your advisor. They are likely to know the ins and outs of the program. They will help you with your grant proposals. They will discuss journal articles informally. They will collaborate. The program you choose should have a lively bunch of fun, very smart, very hard working, very creative grad students. These will be your friends for life.

What should I choose for my research? At the stage of applying to graduate school, you probably won’t know exactly what you want to study. If you do, you will probably change your mind. I sure did. I was always interested in social behavior, but this has varied a lot in terms of specific questions, organisms, tools. Who knew 20 years ago that I would be studying genes for cooperation in amoebae? You should choose a dynamic area that is at least somewhat popular. This might be something for which tools for advancement have recently become available. You should balance breadth with depth. This is hard to do, so you need to read and keep reading, deep and broad.

Isn’t there a single best university in my program? No. Undergraduate programs are broad and can be ranked, though this is not easy either. Ph.D. programs do not have expertise in all areas. You should choose one that is good in what you are interested in. This is as likely to be Wash U, Nebraska, or Arizona State as it is to be Harvard, Princeton, or Yale.

What about coursework? I view courses as a great way to get the tools you want, or the breadth in another area you couldn’t easily pick up on your own. I love discussion groups, seminars, readings, whether or not they are for credit. I am not a fan of long lists of required courses for graduate students. A semester-long survey taught by all the people in your immediate program to introduce you to the opportunities in your department can be good, as we did at Rice. Courses in experimental design and statistics, or techniques like genomic analysis are also great. I would avoid any program with more than a few required courses. I would completely rule out any place that has two years of courses that take most of your time. After all, you were well educated as an undergraduate, have already begun research, and that is why you want to go to graduate school.

Do programs differ that much in their requirements? Yes, they do. Coursework varies enormously. The form and rigor of exams varies. You should work hard, learn the material, and we should in turn respect that with collaborative learning, not weed-out exams. Make sure when you matriculate that you print out the requirements for the degree down to the details of exams and be sure this will be honored even if the department changes the requirements later. I have heard of places that change the rules in the middle, and then force the old students to follow the new rules. Make sure that does not happen to you.

How will I pay for my graduate education? You will get a fellowship. You will teach. You will apply for an NSF predoctoral fellowship, or HHMI funding if you are not a US citizen or Greencard holder. Talk to the students about how their funding goes. Some universities will give you a letter guaranteeing funding for four or five years. This is best. But even schools that don’t do that may fund you well. Find out exactly what teaching entails, whether it is enriching or grueling and how many hours it takes. Your undergrad loan payments are usually deferred during grad school, but you don’t want to take out any more loans.

What kind of teaching experiences should I look for? Most of us spend a lot of time teaching. It can be fun and exciting, or a total burden. Which it is depends on a lot of factors. One of them is how well you are educated in the teaching process. Some universities are paying a lot of attention to this, helping graduate students to become effective teachers. Washington University in St. Louis has an excellent teaching center, lots of workshops, and specific teaching opportunities in addition to the traditional teaching assistantships. We have the CIRTL network, and a teaching center with lots of opportunities. We also have the Gephardt Institute for Public Service that facilitates outreach teaching at various levels. Other universities have similar programs, but this varies a lot, so be careful.

Why is a focus on teaching so important? You may think it is research alone that motivates you, but teaching is a part of everything we do. It is a part of running an effective laboratory. It is involved in clear publishing. It is a part of all careers at higher levels, since teaching includes training others. Excellent teaching requires that you put yourself in the place of someone else who does not know what you know. So many poor teachers imagine that they are teaching themselves at an earlier age, and so do not reach most students. Good teaching requires good listening, a talent that will help you throughout your academic career. Finally, if you decide the frustrations of research are not what you want to have central to your career, the joy of teaching can take a more central place. To get those jobs, you need to demonstrate that you know how to teach. I would worry about any Ph.D. program without direct access to undergraduates and teaching them. This is the case at some Ph.D. granting independent institutes, and for many medical schools.

How about health insurance? If you are not still on your parent’s health insurance look hard at the graduate student health insurance policies of the universities you are considering. Some are better than others. This is unlikely to be the key deciding factor, but could help you decide if you are really torn between two places.

How long should I plan on taking to finish? Once you get your Ph.D., you should plan on having a job within 5 years. There are kinds of post doctoral funding that end at 5 years. So, you want to be poised for success when the Ph.D. is done. Have your papers published or submitted. There should be several of them, some with you as first author, some with you as collaborative lower author, some that are reviews of a specific area you love. So, the Ph.D. period is more flexible than the postdoc period, but still try to finish in 5 years. Choose advisors that agree with this goal and help you attain it.

What if I do not like the program I have joined? If you hate the program, you can leave. This might be immediately, or after getting a Master’s degree. Try not to alienate people since they may be good reference writers in the future, though it that were the case you many not be wanting to leave. Try to decide if the problem is your advisor, the program in general, or you at this stage in your life. Maybe a local move to another advisor or program can help. Most of us want you to be doing what you most love, therefore wanting you to switch programs or advisors if that helps.

How do I choose? Visit all the universities you are considering. They should fly you in for a visit on a day when others also come. Otherwise go at a different time. Weigh all the things above, and see what feels best. Odds are, you’ll love your Ph.D. years.

Owen Gilbert, my Ph.D. student, with David Queller, me, and Larry Gilbert, my Ph.D. advisor.

Alan Templeton, my other Ph.D. advisor.

What exactly is the process of acquiring and disseminating scientific knowledge? Who pays for each step? Here is the process as I see it.

1. Discover. This complex process often also involves teaching others how to discover for themselves, avoiding bias and thinking broadly.

2. Analyze the data from the discovery with statistically robust methods.

3. Write up the discovery and analysis so others can clearly understand what you did and what you found. Include the actual data in a supplement or deposit it somewhere accessible.

4. Give the write-up to a mediator, the editor and editorial board, who will arrange for neutral people, unrelated to the researchers, to review the work.

5. Revise the work according to the advice of the referees and editors. This may require more discovery. It may require sending the work to a new editor for more review.

6. Share the work worldwide so others can learn from it. This is usually in the form of an electronic document discoverable by search engines like Google Scholar.

Where are the expenses in this process? In Europe, a lot of taxes are based on value added, so let’s think that way and go back through the list. The values I put on these categories are necessarily somewhat inexact and vary with discipline. You should feel free to replace them with your own values. Just remember that they are not about importance, but about cost if the item were charged at some hourly rate commensurate with skill.

1. Discover. 60

2. Analyze. 15

3. Write. 10

4. Review. 3

5. Revise. 6

6. Share 8

Who pays for these steps? Federal funding pays most for Discover, Analyze, Write, and Revise, or 95% according to this scheme. Our non-profit universities also pay a substantial share of these areas. Private foundations pay a small fraction. Review can be broken down into two general categories, first, the work done by professionals that evaluate papers, along with the editors who choose who evaluates, then make the final decision, and, second, the entities that choose the editors and provide the software for the reviewing process. The first category is generally performed by academic professionals who do not get extra pay for editorial and reviewing work, so we can say it is paid for by their universities and their research grants, whoever is paying their salaries. The editors are chosen either by academic societies or by publishing houses, for profit, or not. At some publishing houses there is a step of copy-editing which improves writing for clarity. This is increasingly rare. Sharing involves both bringing an electronic form of the article to the search engines and making it available. This is partly the role of the publishing houses who use software to format the final manuscript, and largely the role of university libraries who pay for access to the publishing house material.

Under this scenario, the publishers like Elsevier only set up editors who choose editorial boards, choose reviewing software like manuscript central, then copy-edit accepted manuscripts (sometimes) and release them, bundled into issues and volumes reminiscent of their paper antecedents. Why then, should Elsevier make hundreds of millions of dollars in profit for its tiny slice of the research pie? What do we get from them? Well, they are riding on a historical wave where publishing was expensive because of paper. Now they ride on our need to validate our research by publishing in respected places. Ancient journals where historic discoveries have been published give our work credibility. Who wouldn’t want to publish in Cell? Journals are evaluated in ways that are more plastic than they once were, since impact factors can be calculated so easily.

The sad fact is, we are draining our budgets to support for-profit journals that give us credibility. If we were starting afresh, clearly a new system would emerge, one that did not let the publishers take so much money. But we are not starting from nothing, so change will be gradual. We can publish in one of the PLoS journals. We can invent new ways of peer review that are much more independent, perhaps like the lenses that Connexions uses. But change is slow, though recognition of the problem has been quite fast.

One of the consequences of understanding who really pays for research is the decision by NIH that research it pays for must be made available through PubMedCentral when the work is accepted for publication. This wise policy gives the main funder of the research the power to disseminate it, though the publishers are still allowed to have a role.

The Research Works Act seeks to change that, to unfairly maintain the obscene profits publishing houses make on the backs of workers not paid by them. This act says NIH cannot insist that research it pays for be released to the public. This act is heavily supported by publishers like Elsevier and their organizations. It will inhibit the sharing of scientific data, sharing that is so necessary to scientific progress, sharing that is clearly in the public interest. It is a terrible piece of legislation, one that affects us directly, one that we should oppose.

The thing is, I’m not necessarily against for-profit journals if they make their profit on the fraction of value-added that they contribute. We need these structures for now, as we gradually move away from them. So, what should we do now? 1. Boycott Elsevier as the most egregious offender, though I am not sure what to do about the society journals they publish. 2. When you choose a journal look at both impact factors, and how much profit they are making, and choose the more modest journals. 3. Publish as much as possible in journals of academic societies and non-profit PLoS journals. 4. Do not review for, or serve on editorial boards of whatever publishing houses make you most uncomfortable, starting with Elsevier.

We are the ones that add nearly all the value in this process. We review and edit for others who profit from our unpaid work. Stop doing it!

Meetings are important for stretching your perspective. You can learn things that you didn’t even know you wanted to know, but, once learned, change everything. I felt that way from just an hour talking to Adam Kuspa about Dictyostelium sociality yesterday. He challenged my view of a lot of really basic things. I know this may not be anything you care about, but at meetings you can find people that share your arcane interests. Adam made it clear that you are what you eat, even for a social amoeba. A weak immune system can change you. What seems dead may not be. These are big ideas, cool directions from one of the biggest thinkers in Dictyostelium biology, really exciting. What he said made two impressions on me. First, it will change how we do things. Second, the generosity of sharing unpublished ideas is something I love about the best scientists. We would never violate that trust. We will be careful to see to it that our experiments complement his and return the favor should we find something cool.

If you are a struggling student, you may find meetings a tough expense. I say you cannot afford not to go. Pay the student rate for registration. Get a group to drive if it is close, or buy your plane ticket early. For lodging try airbnb, couchsurfing, or camping if the rooms are too expensive. Buy food at a grocery store, or find cheap places to eat. Apply for all possible funding from the meeting, from your university, from your advisor, even from your family. But go, give a talk, or a poster, and talk with people you know and people you don’t know. You might even want to go to two meetings, one very close to your interests, the other in a stretch direction.

Try to have some goals as to what you want to learn before you go to the meeting. Look at the roster to see who will be there. If there are luminaries in your field, read the abstracts of some of their papers again so they are fresh. If you are timid about contacting those people, seek out their grad students and postdocs. Ask them questions about their work and they will talk. You could go to a meeting and learn nearly nothing, or have it change your life. It is up to you.

Have the 1 minute, 5 minute, even 10 minute version of what you do ready. Keep in mind the big reason you do what you do. Don’t talk about the methods at all. If they are in a close field, they will ask. Make sure you spend as much time talking about their research as talking about yours.

But it is all dependent on some fast actions now. If you missed the signup for a meeting presentation, American Society of Microbiology, for example, put it on your calendar for next year so it doesn’t happen again.

Have fun!

Just by writing the letter, you validate the person and their application. The way it works in the US these days, if your letter cannot be positive, then you should not agree to write it. But that does not mean all letters are the same, by any means. I know at least one very famous person in my field that writes letters of one or two sentences. They are positive, without true content, and only fulfill the stamp-of-approval side of letters. This person writes enough of those, that even that is of little value. But I sympathize. I imagine this person is inundated with letter requests, making this a reasonable compromise.

Besides validation, one of the things people want is help interpreting the data, as when we are instructed to tell whether we think that a student’s grades are not reflective of their true abilities, perhaps because of an outside job, a sport, or an ill relative needing care. If the stipend offered by a graduate program lifts the need to work, the reasoning goes, the person will perform much better. If you have information on this, share it.

Another kind of data interpretation is that surrounding multiple author papers. It may be hard for evaluators to tell what a certain person did on a project. Tell them.

More importantly, evaluators want to know who this person is, and what they will be like should they be hired, or admitted. This is very difficult to convey. I think the best way to do this is by anecdote, since the data are elsewhere. If you can tell a few short stories that capture the person in a number of different dimensions, do so. It is good if these stories can be interesting and show the person in a variety of ways, particularly involving important things like coming up with new ideas, showing leadership by organizing something new, or helping others.

Be very careful that you don’t fall into the trap of describing women and men of equivalent abilities differently. Research says you probably do this, so be careful. I have seen things in letters that would dumbfound you. The study by Hebl, Martin, and Madera linked to above indicated that people rate letters lower if they have tons of communal characteristics. So make it clear your letters show strength and action for all your students.

I write three kinds of recommendation letters, those for undergraduates who may have taken a course or two from me, but did not work in my lab, those for high school students, undergraduates, grad students, and postdocs who did work in my lab, and those for colleagues whose work I know and whom I’m also likely to know personally. The three kinds of letters are different. I’ll try to give more detail on each kind in later entries. This is just an overview.

For the student that I know from class and did not work in my lab, I write a short letter that still tries to capture them. Since my classes all involve papers or projects, I can talk about their project, how they approached it, what its strengths were, how much teamwork they showed. That gives some fun information, and sets the student apart. It also gives a framework for the praise you will want to give the student.

The other two kinds of letters will have much more information. They should have several paragraphs about the actual work, giving what is most important, perhaps pointing to a key paper or two. Put the work in a broader context. Teach the reader why it is important, since they may well be from a different specialty. This is especially true of tenure letters that can go to committees that are very far from the specialty. I’ve often heard that a good letter explains why someone’s work is important and what it is all about better than the actual subject does.

I often ask people for whom I write letters to provide me with a few paragraphs on their best work, why it is important, and what special challenges they had in doing the work. I may or may not use the information they give me, but it can be very helpful.

In general, adjectives are not helpful in letters, except maybe in the first paragraph. Even though the letter is a stamp of approval, the readers also want a little meat. This is not the place for generic word-salad or kind-to-pets letters that could be written about anyone.

My standard letter formula begins with a short summary paragraph. The second paragraph tells exactly how I know the person. I try to put in the date of first meeting, or classes etc. This helps in future years more than relative times like “last year.” The next one to five paragraphs are the meat and consist of the anecdotes, interpretations of the research, and special information that helps interpret the data. The concluding paragraph is the endorsement: Hire this person; interview this person; admit this person; tenure this person, or something weaker, “enthusiastically”, “most highly”, and the like.

I do not put negative information in letters, because it is so hard to know how it will be read. Is someone who is stated to be “slightly shy” actually pathologically withdrawn? It is hard to know. But I do not put untruths. If someone is not at all creative, needing to be told exactly what to do, I will not say they are creative. I think a lot of other people write letters this way, so, if you are an evaluator, scan them for what people don’t say, as well as for what they do say. I say scan, because most letters are only scanned quickly. Only if a hard decision needs to be made, or someone is about to be interviewed or hired in a highly competitive search, are letters read closely. Letter-writing conventions vary with the country, so be sure when you read them you take this into account.

Whenever possible, I give the letters to my assistant and let her send them out. I forward the requests to her, and she handles them. I do not personalize letters in detail for each application, though if I have a student applying for research jobs and teaching jobs, I’ll have two different letters. If other specialization is needed, my assistant alerts me. If I know someone well at a place one of my people has applied, I might send a brief email to that person, alerting them of the opportunity.

Writing these letters can take too much time. I write letters for a lot of people: 28 in 2011, 53 in 2010, 50 in 2009. I try to do them quickly, in scraps of time between other tasks. I like to do them when asked, so they don’t hang over me. I estimate that a new letter for someone takes between 20 minutes and 2 hours, no more. I might spend longer reading papers if they are interesting enough.

Oh, another thing. I do not reiterate the data. I do not repeat grade points, numbers of publications, dates of degrees or any of that. I don’t see the point. Maybe I should do this.

There are a number of places you can get more specific advice on letter writing. Here’s one on getting a great letter. Here’s one from someone who reads a lot of letters quickly. Here is the standard kind of stuff they tell undergraduates. I would say that you should email your professors copies of any papers or projects you did for their classes, but the other stuff can also be useful.

What we want to hear is that this is a great person, full of brilliance and grit, hard working, but always taking time to help others. Let such people shine. But also help the ones that are not so stellar socially, but may be even more brilliant. OK, let’s be honest, even the non-brilliant, honest, fairly hard working, fairly smart people need those letters too.

Oh, I should say something about those horrible buttons where you have to say if someone is the best in 10 years, best ever, or mediocre in each of 20 different ways. I hate them. I never know what to put. They are inflated, but how much? When I look at results of these, I pay more attention to relative than absolute values. If someone is high in everything except writing, then that tells me something. Maybe. I just fill out quite high values on these things. They are asking us to quantify something that can’t be quantified, and I resent it. For this, look at the data. For opinions, read the letters.

As a final note, I’ll say that letters are much more important for people still living with parents who may squeeze performance out of uninterested children. There strong school support in the form of letters can be extremely informative.

For better or worse, these letters are a part of our system. I know plenty of people have taken the time to write letters for me, using their precious time. All I can say is thank you. Maybe I can return the favor, or at least pass it on.

- Madera, J., Hebl, M., & Martin, R. (2009). Gender and letters of recommendation for academics: Agentic and communal differences. Journal of Applied Psychology. 94, 1591-1599

But how might blurry vision help scientists with goals much greater than identifying that bird in the Spanish moss? Jay Odenbaugh told us at an excellent seminar in the History and Philosophy of Science and Medicine series at Wash U last Wednesday. Jay’s talk (or paper, as the philosophers call them) was entitled “Searching for Patterns, Hunting for Causes: Robert MacArthur, the Mathematical Naturalist.” MacArthur is the legendary ecologist who died in 1972 of renal cancer at the height of his career, catapulting him instantly to god-like status. MacArthur worked on warblers, on the competitive exclusion principle, and with Ed Wilson invented perhaps the first null model in ecology, island biogeography, though he didn’t call it a null model. In this talk, Jay said that MacArthur claimed the best ecologists had blurry vision so they could see the big patterns without being overly distracted by the contradictory details.

This immediately made a huge amount of sense to me. Biology is so full of special cases, of details that don’t fit theories, that it is easy to despair of advancing with broad, general theories. But we need those theories, for they tell us where to look next, what data to collect, and even what theory to challenge. I am a details person, but love the big theories. When Dave proposed that we graph organisms on two axes according to how cooperative or competitive they are I felt very uncomfortable. What are the units to the axes? How can we put a whale and a Dictyostelium slug in the same graph, and then add in lichen and an angler fish and its mate? And that is just the organism side. A lion eating a gazelle fits on the same graph, just on the negative side? It made me uncomfortable, until I embraced it. For these organismality graphs, which we have published in a couple of places, help define organisms in a simple and elegant way. I hope they will point research towards the interesting organisms towards the borders of organismality. It is our big idea and it took very blurry glasses.

Maybe blurry vision is one of the things we contribute to our own lab group. We can help pull the students out of the details of their project to the big picture, showing them when a project is finished, or when another direction needs to be taken. This blurry vision comes naturally to us, since we are not the ones pouring the plates, staining the cells, counting the spores. There is probably always a tension between detail and one more replicate, versus wrapping it up and moving ahead. It is probably always harder to stop doing what you are doing and writing it up, than doing another replicate, another field season. So, students and postdocs, thank us for our blurry vision, and we’ll try to turn it on you frequently and help.

I took away a few other lessons from Jay’s excellent talk. One is that I always learn from philosophers. I’m so happy to have philosophy and history of biology as part of our faculty and curriculum, with Gar Allen in our biology department. Philosophers do not think like we do, and we ignore them to our peril. Want to have big ideas? Pay attention to the back stories behind the big ideas already out there.

An interesting thing about philosophy talks is that they are full of long quotes, fortunately, these days, in powerpoint, not just read. It seems strange, but to philosophers getting the language exactly right is important. In some ways seeing the actual words can bring you back. But the style is certainly a surprise. I’m glad they seem to have come away from reading the talks, for only a trained dramatic reader can read in a way to hold my fickle attention.

There were also a couple of other interesting points that Jay brought out about MacArthur, one scientific, one social. MacArthur did a lot of theoretical work, but he was also a field ecologist who looked at how five warbler species divided up their habitat. The species were yellow-rumped, black-throated green, Cape May, bay-breasted, and blackburnian warblers. He found some patterns in their feeding habits that supported the competitive exclusion idea for species co-existence. It reminded me of the narrowness of looking at only the most easily visible. Maybe not for this example, but for many, interactions with microbes are critical for finding the big patterns. How slow plant ecologists have been to come to this view, as Nancy Collins Johnson explained to us. Fungal partners in nutrient acquisition should not be ignored. Even behavior can be influenced by parasites, making them more or less shy, according to the needs of their parasites. Another unseen thing might be what the birds do in other habitats. How do their tropical roots constrain what they do on their breeding grounds?

The final lesson I took away from Jay’s talk was the exclusive clubbiness of science. Robert MacArthur met with his buddies Ed Wilson, and Marxists, Dick Lewontin, and Dick Levins, at the MacArthur summer cottage at Marlboro. I suppose women were there, cooking and cleaning for these guys, but they weren’t mentioned, certainly not as scientists. Those of us who live and breathe scientific excitement are inevitably going to talk about cool ideas at private locations. But it is so important, whenever possible, to make scientific excitement public. That is why I’m so happy about the flowering of public science, from blogs to TED talks, to Science Cafes. Let’s keep talking and share our newest ideas.

At other times knowledge seems to be an uneven quilt pieced by a madman, here shimmering silk, sewn to an improbable shard of jagged tin, stuck to a simple fold of wet cardboard. I might fix this corner or that, in easy ways, but improving the whole overwhelms me. This might be a more realistic view of information, but how can it be accessed?

Here I make the case for small scientific meetings, preferably in workshop format. You may think the large meeting will have all the choicest morsels for you to choose. But a large meeting is full of private banquets, discussions that might change your life, but you are not there. The best meetings include all meals, so you can sit next to anyone and learn from them.

When we began to explore the wonderful world of social amoebae, the annual Dictyostelium meetings proved crucial. We went to talks, but did not understand them. We could not tell the silk from the cardboard. We hardly noticed the scientific conflicts. We could not identify the true advances. Only at dinner, lunch, or breakfast, could we learn these things. Rich Kessin, Chris Thompson, Gadi Shaulsky, Jeff Williams, Pauline Schaap, Adam Kuspa, Rob Kay, Salvo Bozzaro, and many others educated us, piece by piece, at meals. We learned what to look for, what was well-known, what was controversial, where a true advance might be made. We formed collaborations that extended for years, even branching from one generation to the next. Now, after more than a decade with this lovely system, we hardly remember where the cardboard was, or the silk, the quilt is so changed.

Right now I am at an even smaller meeting, called Cooperation in multi-partner settings: biological markets & social dilemmas, organized by Ronald Noë and Mark van Vught at the Lorentz Center at the University of Leiden, in the Netherlands, just 20 minutes by train from Schiphol airport. There are 52 names on the list, perhaps half young grad students and postdocs. Of these, 17 people are local, from the Netherlands. The others come from 16 different countries. There are 11 women. There are economists, anthropologists, psychologists, and biologists. There are empiricists working on primates, on bacteria, on plants, on amoebae, on insects, and on humans. Theoreticians are heavily represented. This is a meeting that is now closed, but it was open to anyone who cared to come, if they registered in time. It represents the best possible chance for a young graduate student to spend a week with people whose books they have read, whose ideas they have pondered. You can look for yourself at the people who have created knowledge who are here. When you meet these people, you can hear in their speech the cadence of their writing. You can see where those great thoughts came from.
At a small meeting, you get time to discuss ideas, even if the structured time is entirely devoted to talks. But this meeting is even better than that. It is a workshop where nearly all the time is devoted to discussion. Maybe we’ll come up with something new.

The first day we listened to people propose areas within the general theme. Some were detailed, seemingly suggesting both questions and answers. Others were more exploratory. We ended with a quick plea for more ideas, and suggestions for several. Then Ronald combined several, according to suggestions from us. Finally, we chose which area to join. Each group had about 6 members except for one, with 12. Here are what the groups are about: 1. Context in cooperative markets, 2. Strategies in markets, 3. Public goods, 4. Co-evolution, 5. Biological markets in animals, and 6. The role of information in markets. Each group is separate, with separate people, in separate rooms, though we gather at breaks and meals. We also have offices, three people per office, young and old mixed together.
On the second day there has been a lot of casual discussion. In our group we spent some time defining context, defining markets, defining trade. Enough of the initial discussion was about arbuscular mycorrhizae that Nancy Collins Johnson shared a powerpoint on the topic, showing how plants and mycorrhizae track each other and how relationships change under different kinds of soils and fertilizers. We thought about whether we could write a paper on trade markets of humans with insights from microbes, just to turn things around. Principles like know your partners, or parcel your goods, or have a diverse set of commodities to trade came up as possible themes, along with about 7 more. But some of the theoreticians feared this would be too gimmicky. Others worried that we did not know enough microbial systems to be complete. We broke for lunch and will discuss more this afternoon, sacrificing a sunny day.

As we talk, we learn different perspectives. We meet new people. We see young scientists get to know each other. The next time they meet, these shared experiences will make ready collaboration that much easier. I can’t tell yet what the sum of the meeting will be, but so far, I’m learning. So, try to discover the small meetings in your field, or in fields close to yours. They are worth it.

At lunch with the famous Peter Hammerstein.

Grad student, Gijsbert Werner gets to chat with Rufous Johnstone from Cambridge.

Toby Kiers notices that even at coffee we can collaborate, filling two cups at once.

We learned a lot about arbuscular mycorrhizae from Nancy Collins Johnson.

Our fearless leader, Ronald Noë, puts marketplaces to work in the workshop.

We pay attention, but most of the workshop involved discussion.

We had offices, keys, and officemates, additional new friends and colleagues.

Our small group gets to work, with Toby Kiers, Chris Hauert, Peter Hammerstein, and Yoh Iwasa.

Aniek Ivert explains her cool ants to our small group. They farm aphids right inside the nest!

We eat well! Everyone competed for Hanna Kokko! Maybe because they knew about her Good Food Society in addition to her sharp mind!

We needn’t have worried. Our son was as deliriously happy as I had ever seen him when we picked him up. He was glad to see us, but could not stop chattering about all that he had seen and learned. He took us through the landscape at a near run, up and down muddy trails, first to this waterfall, then to that one. He know what to expect at each. He showed us the large black-and-yellow salamanders right out on the gleaming wet rock surface. He showed us dark ones that lurked in the pools at the bottom and which ones hid behind the fringing waterfall. Clearly the snakes and salamanders were a highlight, but he knew other things too. He knew who had lived in these hollows, from native Americans to the hardy Scots and others who replaced them. He knew what they feared too, in the form of ghost stories, told around the campfire. From those stories he might have learned what some of the worst of them actually did. He learned not only from exploring along the trails. He learned from all the stories the councillors told around the campfire and in the classroom.

He never did go back to that camp, but I see traces of what he learned there affected him in central ways, affirmed repeatedly in other field experiments, following experts, finding, and studying snakes and amphibians on countless jungle night walks. I think that week, lectures and field work combined, had the kind of lasting learning impact we want for our students.

Can a day of learning how to teach from lectures at iTeach have a similar impact? I’ve been mulling over the things we covered, wondering how my opinions have changed since I first wrote right after the euphoria of the day. I could rewrite that entry, but I won’t. The changes will be reflected here instead.

First, I pondered a lot the irony of being lectured at about how lecturing is not a good way to teach. Of course it is. If you have been struggling with a problem, have read about it, but it still is not coming together, get someone to explain it. It helps. These days, if you don’t follow the instructions that came with your new burr coffee grinder, you can find a YouTube video that explains how to put it together. Odds are, it will have one of those square codes you just photograph and go straight there.

So explaining helps and that is what a lecture is, an explanation. Is there anything better than a great talk? Doesn’t it tie to the earliest ways we humans learned, from Songlines, to long narratives, going back to before we humans could even write? Aren’t lectures the first abstract step we humans took past direct showing, which even many animals do? So why if we use them all the time, even in workshops about teaching, do we find they so often fail in teaching?

Is there another problem with lecturing? Yes, I think so. The other problem can be understood from the above examples. What if we don’t have an object to put together, but we are being told how to put it together anyway, and we will be tested on those instructions in words, not by actually assembling anything. What if we won’t be walking the Songlines and so don’t need to know when water will appear? What if the lectures our son heard on salamanders and where they occur were not accompanied by trips to waterfalls? True grit lets some people learn these things anyway, but most of us will find the overnight cram, the plug and chug, whatever solution puts it in for the test, and then lets it out rapidly. It is knowledge we do not want and will not keep.

So, lectures are great when you want and need the information. They are nearly pointless when you do not. This means our challenge is not to stop transmitting information by lecturing, but to entice our students to desperately want and need that information. Wanted information may tie to things you already know. It may let you build something you want to build. It may let you know something you need to know. I knew our credit cards would not work in the train station in Schiphol airport without that special European chip, because Rick Steves said so in an article I had read just for this purpose. Will I retain this information? Probably, but the information I really need to retain is to check on using money in whatever country I’m visiting right before going, if I haven’t been in awhile.

So, lectures are not the problem. Their context is. How can we change our teaching so students want and need the information we give them in lectures? Why would we even want to lecture them on information they do not need? That we are assigned to teach this class, need to fill 15 weeks and will be judged at the end is not a good answer. That we were taught irrelevant information, and it didn’t harm us is not a good answer. That it is not our place to decide what students do outside our classroom and so cannot make the lectures relevant is not a good answer. This is the hard question, and in iTeach we got some answers. Some others I already knew.

Some subjects are just naturally fascinating. Students will want to know about them because they tie to things they have experienced in everyday life easily. I teach behavior, and this is one of those areas of natural curiosity. I can teach central principles through examples like why hermaphrodite snails chew each other’s penises off after sex. It just gets a student’s attention. The trick is to not drone through the answer, but to make the students grapple with it first.

Sometimes meaning can come from across the curriculum. This can be very effective but tricky to work out. Say a student is taking both introductory chemistry and introductory technical writing and film. If the goal of the writing class were to produce a better lab manual for the chemistry class, or a series of YouTube videos on doing the lab procedures, both classes would be enriched. This would be most true if the products of the writing class were actually used in the chemistry class. Scale this up, and all our teaching could be a lovely network of meaningful actions.

But I’m not an advocate of extreme class networking because I fear it can dampen autonomous creativity of individual professors. It is easiest to make those lectures matter with things done for that same class. Exactly what those things are is the subject for another entry. Here, I’ll just say, that we should use the evidence-based tricks of repetition at intervals, recall on blank paper, or with tests, and group work to help with retention. But our biggest ace in the hole is that the students badly want the information we are transmitting at least partly by lecture because of what we are about to ask them to do with it. Stay tuned!

(P.S. This lecture-based workshop was effective because it was voluntary, because we will take what we learned and apply it to our own teaching, because we will discuss what we learned with our colleagues, because we will read the papers cited, because once you want the information, lectures, especially when interruption is encouraged as Gina Frey did, are very efficient ways of transmitting information. I suppose I’ll retain because of this, my blank sheet.)

I suppose after decades in the classroom, more than half a century, if you count both sides of the podium, I am hard to surprise. But I always learn something I can use when I go to teaching workshops, so I keep going. Today Wash U held its biannual iTeach workshop, from 9 to 4:30, feeding us well, as I have come to expect.

We started with a great plenary by Wash U’s own Keith Sawyer, an expert on creativity. What a great place to begin! He didn’t hit on exactly the points on creativity I usually cover (see the proposal-writing blog). Instead, he focused a lot on collaboration, drawing on his experience as a part-time jazz pianist. He summarized the standard teaching, which I call lecture-test, but he called instructionism.

With instructionism there are some assumptions that he said are not always spelled out: that knowledge is a collection of facts, that schooling has the goal of getting facts into the students’ heads. We teachers know these facts and so need to transmit them, beginning with the easy stuff. Then we evaluate them, and others evaluate us, according to how many facts got into those heads.

Keith didn’t think much of instructionism. He said the knowledge acquired is superficial; it is poorly retained; it is not easily connected or integrated with other learning experiences and so does not educate the whole person, or allow for much creativity. Instead, he would like us to teach the innovative learner who will have deep understanding of complex concepts which they can manipulate, relate to other areas, and generally make shine. But of course, I think we would all say we want this. Keith says group projects are the way to get this. Hey – did you ever have a lab partner where you had to do all the work?

Seriously, he had some good ideas on group projects. One was that the problems they had to solve had to be too hard for one person to solve alone. He also acknowledged that what he was proposing was difficult. He suggested we learn continually, work collaboratively, engage in “mutual tinkering” and switch it up with new partners frequently.

He said creativity is more important to our students and society than at any time in history. Such statements always make me queasy. How about when we humans were figuring out agriculture, or moving to the far, far north out of homey, warm Africa.

This may seem really, really funny, but to some degree you could characterize the entire rest of the workshop sessions I went to (except the one on how to use Blackboard) as how to get to be better at pounding those facts into those lovely undergrad brains.

Those of us who teach of course know that we do have to get the students to learn some facts and that with these facts they can build lovely intellectual constructs. For example, the undergrads in my research lab must learn the important fact that there is only one way to turn off a Bunsen burner: at the tap. If you forget that fact and blow it out (yes, this really did happen once), catastrophe could result (it didn’t).

There was a series of really cool talks about how to best get the facts in, by Carolyn Dufault, someone whose name I didn’t get, and Gina Frey, all of the Teaching Center. If we want to pound in some facts, we are best off having some repetition. That repetition should be spaced out over time of up to a month for best retention after 6 months, according to a paper by Cepeda et al. in Experimental Psychology in 2009.

But the best way to pound that information into their heads is to make them take charge. Reading material is good. If you want to keep it and make it your own, have the students own it by being tested on it, according to Wash U’s own Roediger and Karpicke in Psychological Science, 2006. Even just writing down everything they remembered from a passage was better than reading it over again for information retrieval after a week. This was true for both fact-based questions and questions that required a little more thinking.

One of the really cool things is that the students with the blank piece of paper that actually did the best with recall had the least confidence in their abilities. It turns out their assessment of how much they would remember was quite accurate. The other methods, reading things twice, or four times, or making a concept map, erroneously were overconfident. I hope I am getting this right! It reminds me of a study whose source currently eludes me, that indicated that depressed people actually had a more realistic view of life, but it still is terrible to be depressed.

There was tons more material on what to do in class, how to make it more interactive, how to get students to talk, that you need to cover less material, that facts and concepts actually can be introduced to each other.

So, what was the tidbit that was really new for me? It came from Gina Frey, at the very end, when she was talking about in-class group work, something I do a lot. She backed it up with no data at all. It was that in the groups of students everyone should have a role, and these should rotate often. The roles she suggested were facilitator, scribe, and spokesperson. The latter has to use the notes of the scribe. I could see this system might solve some issues I saw with group work.

Oh, there was one other thing. I finally figured out how I could do a study of some of my teaching techniques in an experimentally robust way with controls, without boring everyone to death, but that is the subject for another day.

iTeach was on our first snowy day! Should I move back to Texas?

Keith Sawyer gave the plenary address.

Gina Frey deep in conversation after her talk.

Doug Chalker and Eric Herzog, both biology professors and excellent teachers.