Tips on communicating science to a class

Yes, I am still alive.

My wife and I just returned from a long hiking and climbing trip out in the western states. It's tough readjusting to normal life after having been on the road for a month, but I've managed to slowly get back into the world of science while I wait out the visa application process for Switzerland.

Today I came across an interesting article in Wired called "A Media Guide for Physics" by Rhett Allain. In the article, Rhett gives a few tips for producers of science TV shows that would help them communicate science better. His tips are

1. don't be wrong;
2. it's better to say nothing than to be wrong;
3. don't be misleading;
4. [don't focus] on comparisons and numbers;
5. don't get out of control crazy.

I agree with Allain on all these points, especially the last one. Though this example is not from TV, I've noticed that graduate students (myself included) will tend to describe the minutiae of their research to lay people because they don't want to be wrong and because they've been so immersed in it that they forget what other people know and don't know.

The article also got me thinking about what tips teachers and educators should use when communicating science to their students. The list must necessarily be different because the audience is different. What follows is my own list of tips that I think are valuable to college professors when communicating concepts to a class.

1. Don't assume that students are well-grounded in the "background" material and concepts.
2. Don't gesture too much while lecturing. When you gesture, you're referring to an image in your head that only you can see. At least put that image on the board.
3. Present ideas visually and verbally before going into derivations.
4. Include a little history behind the concept you're about to teach if there's time. The reasons for why a concept is important are often found in the history of the development of the idea. For example, Newton's laws seem obvious now, but philosophers had some very muddy ideas about motion before Newton formulated them. And all of thermodynamics arose out of a need to understand how newly invented engines and devices worked. If you start a class by talking about molecules in a box, the relevance is lost.

The list is obviously not exhaustive, but I've seen many professors violate one or more of these to the detriment of their students' understanding. What other tips might be included?

How do you teach what polarization is?

Today is Optics Day at CREOL, our annual public open house where we present demonstrations of various optical phenomena and technologies, speakers, and pizza. :)

During this year's Optics Day I am charged with explaining the phenomenon of polarization to visitors. Now, I find polarization incredibly difficult to explain to non-scientists, and here's why: the usual treatment of optical polarization in physics involves describing the direction of the electric field vector of an electromagnetic wave. If I were to start with this definition while speaking with somebody not trained in physics, I would then have to explain electromagnetic waves. This would be followed by an explanation of the equivalence of light and electromagnetic waves, wave phenomena in general, linear, circular and the more general elliptical polarization states, etc. etc. until the poor person who has come to see a cool demonstration and learn something new has completely been befuddled because it takes so much background understanding to comprehend what polarization even means.

This year, I am determined to find an explanation of polarization that is more intuitive to a non-scientist. A rough outline that I intend to give for polarization's foundation in observation goes as follows:

1) Our sense of sight is perhaps the most obvious sense we have. We see objects and from these objects we discern shape, size, color and other properties.

2) There are physical quantities that cannot be sensed by our eyes. For example, flowers have fragrance that our noses can detect. Wind is another example. We feel its effects or we see its effects on other things, but we don't directly see "wind." Therefore, there are physical quantities that cannot be seen but nevertheless may be sensed.

3) There are still more phenomena that exist but cannot be sensed by any of our sense organs. For example, a compass points north because the needle experiences a magnetic force. Additionally, small objects all fall towards the earth because of gravity. Magnetism and gravity require tools that sense things that we cannot: magnetic and gravitational fields. Where our senses fail us, we use tools to measure some quantity.

4) Polarization lies in this last classification of phenomena. It cannot be sensed by us (which isn't strictly true), but can be determined by appropriate tools. These tools are things that are found in nature, like quartz crystals, and man-made objects like polarizers and waveplates.

From this foundation, I will explain some of the consequences of the polarization of light, what it can be used for, and may even digress into the physicist's model if the visitors are interested enough. My hope is to build the concept of polarization up from a basis of observation, not to start with our model first, followed later by how we observe polarization.

What is a good description for entropy?

"Insight into Entropy," by Daniel F. Styer, is a nice paper that appeared in the American Journal of Physics in 2000. In the paper, he argues for a qualitative explanation of entropy that involves two ideas: disorder and freedom.

Entropy as disorder is a common analogy given to students who are learning about thermodynamics, but Styer provides several arguments for why this qualitative description fails to adequately explain the idea. One such argument involves a glass of shredded and broken ice. Despite the fact that the ice has been shattered into many pieces, the entropy of the bowl of ice is less than that of an identical bowl filled with water. The water may seem to be more ordered because it is homogeneous, but it does not possess a lower entropy.

Styer's idea of entropy as freedom attempts to explain how systems can possess multiple classes of states (commonly known as macrostates) and how entropy limits the microscopic details of each class. In the game of poker, the probability of getting a royal flush is identical to any other five-card selection without replacement. However, the number of configurations that form a royal flush is extremely small, so the entropy of the class of hands forming a royal flush is low. This very low entropy class of poker hands restricts the possible configurations of the microstate—the description of what five cards are in one's hand—and completes the analogy with freedom. High entropy macrostates have greater freedom in choosing their microstate by having a larger number of microstates to choose from; low entropy macrostates (royal flushes, for example) have less freedom.

Styer does propose retaining the "entropy as disorder" description by suggesting that both the freedom and disorder analogies be presented simultaneously to negate any emotions commonly associated with either word. His example of such an analogy goes as "For macrostates of high entropy, the system has the freedom to choose one of a large number of microstates, and the bulk of such microstates are microscopically disordered."

Finally, on a different train of though: teaching ideas by analogy apparently must be done with sensitivity to the common emotions associated with a word. I've never considered this idea before, but will surely be mindful of it in the future.

Thoughts on Trends in PhD's in Physics

There's an interesting article on The Back Page of APS News (Vol. 21, No. 4) written by Dr. Geoff Potvin from Clemson University. The article discusses the current plight of physics PhD's—trends in graduation rate, factors for success, and inherent biases against women and minorities. I'm not offering a full analysis here, just jotting down the first things that came to my head as I read the article.

Dr. Potvin states that the growth in the number of PhD's in physics is stagnant and that this is a problem for the US as it tries to remain scientifically competitive in an increasingly global community. However, other STEM fields have grown at much faster rates. Claiming that the stagnant growth in PhD's awarded in physics is bad for US technological competitiveness seems to be a weak argument for enhancing physics graduate education. After all, the number of independent STEM fields has grown enormously (for example I am working on my degree in optics), so any argument along these lines should look at the total trend in all STEM fields.

Dr. Potvin's research has shown that students' motivations for attending graduate school often determine their level of success as measured by publication rates and funding. All too often, graduate advisors assume that their students inherently possess the interest and motivation to perform research. However, the interests and goals of the advisor and student often differ. Dr. Potvin suggests that proper attention paid to graduate students' motivations would enhance their productivity.

There is an inverse relationship between doctoral completion time and future salary for men; higher pay goes to those who took less time to complete their PhD. Unfortunately, completion time is almost entirely uncorrelated with factors that students can control, and is instead determined by things such as the riskiness of research topics or becoming involved in multi-group projects. The pay for women PhD's is uncorrelated to almost all factors in their graduate education and is lower than their male counterparts, on average.

Faculty mentors tend to replicate their graduate school experiences. In my opinion, this keeps them out of touch with their students since they do not adapt to changing attitudes towards work, social life, and career choices for their students. As managers of new work-force members, it would behoove the greater community to adapt their advising style towards these new attitudes.

A focus on statistics

My biology colleagues know a lot about statistics. They routinely perform hypothesis tests, ANOVA, and perform Box-Cox analyses to be sure that the residuals of a fit to data are normally distributed. Ask many physicists and chemists about these tools and you'll likely be met with a blank stare. It could be argued that this points to a problem in physics and chemistry education. To some extent I agree that we (physicists) are not well trained in the art of proper data analysis.

On the other hand (and based on my limited knowledge of the biological sciences), I wonder if biologists place too much emphasis on statistics. If a student's first thoughts in a data analysis are about which type of regression is valid for the data, then I fear that they may miss obvious trends that may answer that question for them.

My belief is that data analysis is best approached intuitively first and formally second. I'm also afraid that a biology curriculum that focuses on the technicalities of statistics may under-emphasize this "human aspect" of analysis. Likewise, there is a point where rigor must be included and I see many physical scientists unable to provide it.

Again, these thoughts are based on my own limited understanding of the biological sciences. There are biologists, physicists, and chemists who excel in all areas. But differences in curricula and courses may bias us towards one aspect or another when in reality good scientists are capable of both.

Teachers vs. students: when interests don't coincide

I recently had a discussion with a close friend who is not a physicist by training but is very interested in many popular physics ideas. I was attempting to explain several paradoxes and non-intuitive scenarios such as Schroedinger's cat, the twins paradox, and the relativity of simultaneity. However, my friend was not impressed by some of these ideas, like Schroedinger's cat, and proclaimed them as "stupid."

I was of course exasperated by her failure to appreciate these concepts. Out of frustration I refused to explain any further ideas despite her questioning. As you could imagine, my refusal angered her; she interpreted my actions as pompous and arrogant. Fortunately, we are both open-minded to our own faults and quickly apologized to one another.

This bout made me realize that a teacher can't always convey why a topic is interesting. Interest is, after all, a personal attribute that varies between individuals. This mismatch of interests can cause a great deal of friction between a teacher and student and should be recognized by both sides for education to be successful.

Teachers must concede that sometimes students just aren't interested in a topic. A good teacher will be patient, even with difficult students, when they encounter a lack of interest. Eventually, the student will show interest in something that the teacher can help them learn about. Students should acknowledge when they are uninterested but still respect their teachers' enthusiasm. More importantly, they should not interpret their lack of interest as a failure to understand subtleties of a topic.

What's not so clear to me is with whom the greater responsibility for learning should lie. I'm inclined to place the greater burden on the student.

How best to view the internet as a learning tool

I work on some projects that require knowledge of basic biology, such as cell structure, biochemistry, and laboratory technique. However, I was trained as a physicist and engineer, and, as a result, have had an extremely limited education in the biological sciences. For example, my last biology class was anatomy during my junior year in high school.

The internet has been essential in bringing me up to speed in these topics. I've put resources such as MIT's OpenCourseWare and the independent OpenWetWare to good use. Companies such as Invitrogen provide valuable tutorials and explanations on laboratory practices as well. The best part about these resources is that I can find exactly the information that I need to know when I need to know it.

I believe that a very few doubt the usefulness of the web as a learning tool, but how to use it as a tool is certainly a topic of debate. Based on my own experiences, I think that internet learning is best used as an independent collection of bits of knowledge that are accessed as needed.

Let's break this definition down into parts. By independent, I mean that the value of internet resources is determined by the individual who needs to know something. A catalog of optical parameters of semiconductor materials will likely serve little purpose to a field biologist. The downside to this is that the web must contain an exhaustive amount of knowledge to be useful to everyone. If there's a possibility that someone may wish to know something, then it must be contained already on the web [1].

"Bits of knowledge" makes intuitive sense, but a formal definition may not exist. If I wish to know how to stain a cell using immunofluorescence, is each step considered a bit of knowledge, or is the entirety of the process considered one "chunk?" I don't think that this detail is particularly relevant to my discussion, but it is interesting to think about how one may quantify knowledge [2].

Finally, the ability to access knowledge as needed makes it efficient. The human brain can only hold on to a limited amount of data. Some details are best stored on machines; otherwise numerous human specialists would be required to perform complex tasks, each one intimate with one small part of the task. In my graduate work, I can learn about cytoskeletal filaments as needed, or my advisor could hire on a cell biologist to consult me on a small number of issues. The first option is decidedly cheaper. In addition, ease of access is important, and spans topics such as mobile devices, bringing the internet to developing countries, and search algorithms.

So, in my opinion, internet learning is best utilized as a user-valued collection of information that is accessed accordingly. Communications through the internet, such as e-mail correspondence with teachers, is important, and is compatible with my definition since I do not put limits on how knowledge is delivered. Failure to properly use the internet as a learning tool usually comes from poor access (e.g. bad search engine algorithms) or a user improperly identifying what they need to know. In the last case, the success of internet learning cannot be determined by machines; like many things it boils down to the human element.

[1] I can't get the thought of the internet as a causal knowledge database out of my head right now, since it can only contain knowledge that has already been generated. It will never contain knowledge from the future, unless, perhaps, new knowledge can be generated from data it already holds, but that opens the question of the definition of knowledge.

[2] Information theory comes to mind here. The information content of a signal is quantified as a logarithm of the number of symbols in the signal.

What I wish I had known about academia (before I entered graduate school)

I'm entering my fifth year of graduate school this upcoming semester and, accordingly, have been increasingly thinking about my life afterward. Moments of reflection and talks with other students have revealed that there are a good number of things that I was unaware of concerning a career in academia when I began my graduate studies. Most of these things have taken me a long time to learn because the points were subtle or I was too naive to honestly assess the matter. Though these thoughts may not be true by the actual numbers (e. g. I haven't looked at the availability of teaching positions or the average income of post-docs), they certainly have found other voices, such as a few of the authors in this April Nature issue. And since the thought of a large number of people holds a good deal of influence regardless of its validity, I will take these thoughts to be true and offer them as advice to those who are considering a career in academia.

Career Point Number One: A career in academia—specifically in science—requires more hard work and dedication than most careers. This is due to a number of reasons, including a saturation of workers in the field, competition over resources, and a career trajectory that is difficult to advance through. Too many people within academia could be considered the cause of the competition over resources, but it's significant in its own right since it dilutes the quality of work being done. And as for a difficult career trajectory: a colleague told me the scariest thing one could do of all career moves is enter upon an assistant professorship with a family and mortgage with no guarantee of tenure.


CPN Two: Teaching positions are sparse (this was a surprise to me!). Many tenured professors or industry veterans enjoy retiring into academic teaching positions. There will not be much leverage for new graduates in obtaining a desired teaching position against those more experienced in the field.

CPN Three: No matter how amiable your advisor, it is not in their personal interest to graduate students. Losing experienced and knowledgeable students hurts their ability to publish, obtain funding, and generally proceed through their own academic career paths.

CPN Four: A post-doc may not be the best option for advancing a scientific/academic career. Many advisors interpret the post-doc role as one similar to a graduate student's but unencumbered by educational burdens such as attending class. A move to industry following graduation, however, may provide better networking opportunities and more chances to evolve one's professional skill set. One can always return to academia.

CP Five: One need not work in academia to retain one's interest in science. This was in no way obvious to me from the start. After having identified my interest in physics, I proceeded through my education with the idea that physics would be my career. But herein lies the most important distinction of all: science is not a career.

Science is the pursuit of truth and the delight in discovering new things through experimentation. It need not be grand in scale or require a large amount of resources. It is an unfortunate development that a career in academia and science have assumed the same position in most people's minds.

I admit that this assessment may appear a bit bleak at first, but for me it is rather liberating. I'm OK finding a career that is not centered squarely within academia because the requirements of such a job are too demanding given my other interests. This in no way means that my life or work can not contribute significantly to science. But to conclude that academia alone is the only way to significantly impact science is to commit a fallacy that could launch one onto a difficult and unsatisfying career path.

Like cures like?

Yesterday some fellow CREOL students and I visited a high school in Sanford to discuss our roles as graduate students and to demonstrate some basic scientific principles of our research with the students. The high school is a special school that is administered by Seminole County for students who have been expelled from normal public high schools. The idea (at least how I understand it) is that placing students with similar behavioral problems in the same setting will allow them to receive more attention from teachers since they are no longer overshadowed by the well-performing students. Of course, the obvious objection to a school such as this is that packing many students who all have had disciplinary issues into the same classroom will prevent everyone from learning effectively since the teachers will be less likely to control the students given their nature.

After speaking with one of the teachers, the consensus seemed to be that the system was working and that the students were more eager to learn (on the average) than they were at a normal institution. Specifically she cited the personal attention that the students receive as a major cause for their better performance. Of course, the school still has a wealth of issues with discipline, but if a few students end up for the better, then I suppose that the school has served some good utilitarian purpose.

Keeping with a utilitarian discussion, it would be worthwhile to consider the cost per student that is paid by the government (and indirectly by taxpayers) to run such a school. Suppose only a small percentage of the students actually perform better academically at this school after having been expelled from a normal public high school. Would the additional costs of running this school justify the improvement in the education of this small percentage?

To be honest, I'm not quite sure what my opinion is on the matter. However, I sincerely respect the teachers, both here and at all schools, who have to deal with both the duty of educating the youth and the need to maneuver through an often hostile bureaucratic system of school administration.