a picture showing an abacus

An abacus- as relevant to today’s math as some of the classical genetics experiments to bioinformatics

My itinerary of the ASCB conference was guided by the Education string, which spread across Sunday and Monday. There were talks and symposia for K-12, undergrad, and graduate education. The main poster session was on Monday.

By the way- the website for the Meeting is extremely well organized, with links to abstracts, program pages, videos, and other goodies.

Among the most memorable talks from an undergrad perspective was David Botstein’s “Integrated introductory science curriculum for undergraduates at Princeton.”  He started with the observation that education of biologists have become less quantitative over the past years (decades?), and many biologists lack the math and computer science background very much needed for current biological research. (The importance of physics was a recurring theme in the meeting, illustrated by the variety of high level microscopy techniques).  To address that, Princeton developed an Integrated science curriculum. Basically, it covers a variety of fundamental topics in biology, math, physics, chemistry, and computer science; which should provide undergrads with a solid foundation to embark on any scientific discipline. One of the golden nuggets I took from his talk was the “Just in time principle,” meaning only teach what is needed at the moment to avoid student confusion. He did mention how difficult was to develop the curriculum to make it so streamlined. The other was the importance to teach only “fundamental,” not “traditional” topics, and as example mentioned some of the classic molecular biology experiments from the 1950s.  And one that really hit home was the comment ‘it is crazy to teach statistics without computers.” In fact, I have taught some statistics without computers- but quickly incorporated programs as it felt, in fact, that it did not make sense to show students how statistics is done in the real world.

Now I want to make it clear that he did not deem useless to teach the history of science experiments in general, but in the case of this particular compressed curriculum.

Another beauty of this curriculum is that computer programming is taught from day 1, including Java and Mathlab. These are very useful tools, and students feel empowered; not to mention that those tools help them to find internships or even jobs.

The next presentation was from Stanford, “Beyond the cookbook: a rigorous, research-based lab course for all.” The Bio44 lab course by Tim Stearns and his team used p53 as an attractive target for student research: to identify mutant alleles of p53 in tumors and figure out what is wrong with them. The presentation started with their goal: to offer a lab course with real experiments, leading edge tools, and modern technology. The techniques used were quite impressive for a student lab: from bioinformatics to western blots including GFP tagging. And the student evaluations made the audience chuckle- some students expressed their frustration at the amount of troubleshooting and repetition that had to be done for success- something scientists are very familiar with.

A common theme of both presentations was the amount of resources and funding needed for such programs and courses. Throughout the education string of the conference it was evident that without generous funding by (among others) the Howard Hughes Institute, NSF, or the Bill and Melinda Gates Foundation, many educational innovations could not have happened.

However, there are options open to less privileged institutions….coming in part 3.

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