TITLE: SIGCSE Day One -- Computation and The Sciences AUTHOR: Eugene Wallingford DATE: March 11, 2010 7:04 PM DESC: ----- BODY:

[A transcript of the SIGCSE 2010 conference: Table of Contents] I chose this session over a paper session on Compilers and Languages. I can always check those papers out in the proceedings to see if they offer any ideas I can borrow. This session connects back to my interests in the role of computing across all disciplines, and especially to my previous attendance at the SECANT workshops on CS and science in 2007 and 2008. I'm eager to hear about how other schools are integrating CS with other disciplines, doing data-intensive computing with their students, and helping teachers integrate CS into their work. Two of these talks fit this bill. In then first, Ali Erkan talked about the need to prepare today's to work on large projects that span several disciplines. This is more difficult than simply teaching programming languages, data structures, and algorithms. It requires students to have disciplinary expertise beyond CS, the ability to do "systems thinking", and the ability to translate problems and solutions across the cultural boundaries of the disciplines. A first step is to have students work on problems that are bigger than the students of any single discipline can solve. ( Astrachan's Law marches on!) Erkin then described an experiment at Ithaca College in which four courses run as parallel threads against a common data set of satellite imagery: ecology, CS, thermodynamics, and calculus. Students from any course can consult students in the other courses for explanations from those disciplines. Computer science students in a data structures course use the data not only to solve the problem but also to illustrate ideas, such as memory usage of depth-first and breadth-first searches of a grid of pixels. They can also apply more advanced ideas, such as data analysis techniques to smooth curves and generate 3D graphs. I took away two neat points from this talk. The first was a link to The Cryosphere Today, a wonderful source of data on arctic and antarctic ice coverage for students to work with. The second was a reminder that writing programs to solve a problem or illustrate a data set helps students to understand the findings of other sciences. Raw data become real for them in writing and running their code. In the second paper, Craig Struble described a three-day workshop for introducing computer science to high school science teachers. Struble and his colleagues at Marquette offered the workshop primarily for high school science teachers in southeast Wisconsin, building on the ideas described in A Novel Approach to K-12 CS Education: Linking Mathematics and Computer Science. The workshop had four kinds of sessions:

This presentation echoed some of what we have been doing here. Wisconsin K-12 education presents the same challenge that we face in Iowa: there are very few CS courses in the middle- or high schools. The folks at Marquette decided to attack the challenge in the same way we have: introduce CS and the nebulous "computational thinking" through K-12 science classes. We are planning to offer a workshop for middle- and high school teachers. We are willing to reach an audience wider than science teachers and so will be showing teachers how to use Scratch to create simulations, to illustrate math concepts, and even to tell stories. I am also wary of one of the things the Marquette group learned in follow-up with the teachers who attended their workshop. Most teachers likes it and learned a lot, but many are not able to incorporate what they learn into their classes. Some face time constraints from a prescribed curriculum, while others are limited by miscellaneous initiatives external to their curriculum that are foisted on them by their school. That is a serious concern for us as we try to help teachers do cool things with CS that change how they teach their usual material. -----