Graduate Student Teaching: What Cell Biology and Statistics Have in Common

Illustration by Chenshu Liu

Illustration by Chenshu Liu

Most career paths in academia will at some point require teaching responsibilities. Expectations vary in terms of teaching responsibilities between large research universities/medical schools and small universities/colleges. Unlike some focused training resources available for postdoctoral scientists, resources and early exposure to teaching for graduate students interested in academic career paths are relatively rare. Teaching experience for graduate students training at research universities mostly entails working as teaching assistants (TAs) for one or more courses. However, TAing a course does not inherently provide a full picture of undergraduate/graduate-level teaching. Therefore other opportunities that include de novo design, development, and execution of a course are important for those interested in diversifying their academic career goals and gaining early exposure to, and first-hand experience with, “real” teaching. Here I will share my experiences in exploring such an opportunity by developing an interdisciplinary undergraduate course that brought together statistics and cell biology.

The rationale

Today’s biomedical sciences are becoming more and more quantitative. However, despite the gigantic volume of quantitative data being generated each day, the relevance of “big data” appears elusive to a student who just started noticing the quantitative aspects of biology. It has been shown that incorporating learning experiences with quantitative analysis into biology curricula can increase interdisciplinary learning performance. But before running into complex and data-heavy problems, one fundamental aspect when conducting interdisciplinary teaching is the establishment of a good sense of basic logic and clear understanding of statistical concepts. During my two terms TAing a graduate-level statistics course, I have observed numerous cases where students struggled with formulas and numbers before they could even truly understand the basic principles. A cell biologist by training, I believe empirical evidence and biological contexts constitute a great vehicle for driving home the nuts-and-bolts concepts in statistics. Having always wanted to be innovative in statistics teaching, I finally got the chance by participating in the 2014 to 2015 Summer Medical and Dental Education Program (SMDEP) and MedPrep Program hosted at Columbia University Medical Center, where I designed and implemented an undergraduate course, Statistics for Quantitative Biology, that integrated cell biology contexts into the teaching of statistics.

Interdisciplinary course design: How can cell biology and statistics benefit each other in the classroom?

This was an intensive summer course that aimed to cover fundamental concepts and basic methods in statistics, focusing on the impact of chance and variability when interpreting research findings by applying statistical inference. Not surprisingly, the busy schedule and the abstract topics presented a tremendous challenge to many students. Luckily, the introduction of cell biology provided palpable contexts in conveying abstract ideas of inferential statistics. During the pre-test, I noticed that the propositional logic of “sufficiency” and “necessity,” familiar to all practicing scientists, was alien to the students. Because propositional logic forms the very basis of most probability concepts and abstract ideas like hypothesis testing, I decided to introduce up front propositional logic and Venn diagrams with a cell biology background. For instance, students were confronted with a question rooted in real-world research: given a conditional statement—“if a gene called CENP-E is depleted then there will be errors in mitosis”—what can you reliably infer? Students were encouraged to draw Venn diagrams to visualize the logical relationships. With the visual aids from Venn diagrams, it was more intuitive for them to learn how to make reliable inference from scratch, which is the basis for more complex issues when dealing with data-heavy inferential statistics.

On the other hand, inferential statistics also enables valid deduction in understanding particular biological problems. The realization that “having CENP-E alone is not sufficient to ensure error-free mitosis” motivated students to look a little further into the unfamiliar cell biology contexts to appreciate the many factors essential for mitosis. When it comes to tail probability and hypothesis testing, real-world data on mitosis were analyzed so that students could make interpretations and predictions by themselves (in press—Liu C. et al. CBE Life Sci Educ, 2016). Therefore, by combining cell biology contexts with the training in inferential statistics’ paradigm, the course design has managed to ease away some “math anxiety” in the classroom and has underscored the relevance of mathematical skills and statistical concepts in solving real-world, data-rich cell biology problems.

Practical tips for expanding your grad school teaching experience

As an instructor, my experiences in implementing an interdisciplinary course have been quite rewarding. Developing my own course and carrying it all the way through in the classroom changed the way I thought about teaching. Unlike when TAing a course, you now have full freedom and total control of the coverage, depth, and pace of your course. Accordingly, you will have to decide on the best way to convey the topics while targeting them to the right level. While TAing a course usually requires one-on-one interactions with some students, teaching a course requires a holistic view of the entire class over time. Based on the dynamics of the classroom and how well the students are doing, your pace of lecturing, the depth and coverage of your materials, as well as your teaching techniques need to be modified from time to time. Directing a course also means compartmentalizing workload and working synergistically with your TAs. Moreover, directing your own course gives you the power to implement a fair assessment system, which calls for individualized achievement even in the “active learning” setting. Last but not least, while teaching the course I was for the first time introduced to pedagogy and had a front-row view of the diversified academic career paths by interacting with wonderful teaching faculties. All of the above are great experiences and lessons, which would have been unimaginable to me if I had only TAed a course.

Finally, my experience is only one of many ways to be creative when communicating essential scientific principles in undergraduate teaching. Following are some general but practical tips I have for fellow graduate student interested in expanding the grad school teaching experience.

  • Look for the opportunities. Apart from SMDEP and MedPrep, other, similar opportunities exist (e.g., the Teaching Scholars Program and Science Honor Program). Most of the positions are readily available and will be announced every time the program starts. Interviews might be required for positions with multiple applicants.
  • Prepare for the interviews. Requirements may vary depending on particular programs, but the key is to showcase your passion and your teaching styles, sometimes through a 10-minute micro-teaching session where faculty interviewers pretend to be students. Be prepared with the take home message to pitch in that 10 minutes, as well as with anything you might want to use in your class (e.g. handouts, blackboard diagrams, etc.).
  • Design (and redesign) your course. Have a pre-test to help you plan how far and deep you should go with the course. Keep in mind that it is totally natural that the course sometimes doesn’t go as you planned. Students’ background could vary a lot. It is important to readjust accordingly as the course goes.
  • Active learning in the classroom. Try to engage active class participation with slide handouts that can be filled in, pop quizzes, and grouped tables and intermittent breakout sessions in a problem-solving-oriented classroom. It is important to assess outcomes fairly with proctored tests/exams.
  • One picture/simulation is worth a thousand words. Multimedia can be very effective to convey complex and abstract ideas. I used simulations to demonstrate the Central Limit Theorem and was told by many that it totally blew their minds.
  • Students’ feedback. It is important to know how the students feel as the course goes (through short surveys or meetings with your TAs) to fine tune your pace (e.g., have an extra mini-review session on topics of shared confusion). Although it’s important to try to keep every student on board, sometimes priority has to be given to the middle 68% of the class.

Hopefully this post will be useful to fellow graduate students interested in teaching their own courses. Innovative interdisciplinary teaching, I believe, is effective in bringing strengths from distant fields into the classroom. With extra emphasis on scientific methods in STEM education, teaching has the potential to inspire more talented young minds to appreciate, or to join the workforce in, basic research! Ultimately, “by teaching we learn”—taking the initiative to explore varied teaching opportunities constitutes tremendous fun in graduate school.

About the Author:


Chenshu Liu is a postdoctoral fellow in Abby Dernburg’s lab at University of California Berkeley investigating chromosome dynamics in C.elegans. He earned his PhD with Yinghui Mao at Columbia University studying centromere maintenance in cultured human cells. Chenshu co-organized the ‘New York Symposium on Quantitative Biology of the Cell’ in Jan 2016, and has been a COMPASS member since March 2016. His email address is lcs@berkeley.edu
Christina Szalinski is a science writer with a PhD in Cell Biology from the University of Pittsburgh.

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