This project supports the development and assessment of curricular materials for a unique Computation for Scientists and Engineers course that uses MATLAB to teach programming to biologists through data analysis and visualization. Three teaching innovations form the central core of this development effort: (1) Teach computation by working with data rather than by working with formulas. MATLAB and other computational science courses generally target advanced students with some mathematical training. Such courses typically begin by explaining how MATLAB performs vector and matrix operations - an approach that is obviously inappropriate for many students, especially those with limited math and logic skills. A more engaging alternative is to ask these students to use MATLAB to visualize and explore meaningful data sets that are presented as simple lists and tables. By working with real data instead of abstract mathematical equations, students quickly appreciate the practical benefits and central role of computing in their discipline. (2) Use a hybrid approach to teaching programming. The course focuses on programming tasks that can be easily mastered in a single semester course and are useful in subsequent courses. Facilities such as MATLAB's plottools are exploited to teach programming skills in a hybrid fashion. MATLAB's plottools allow students to examine and plot data through an intuitive "point and click" GUI interface, and show them the programming code that produced the plot. Students are asked to modify this code in order to visualize the data differently or to explore completely different data sets. (3) Integrate real science to highlight relevance, interaction and discovery. The materials rely on real data as much as possible, and several significant case studies are developed in support of the curriculum. Important scientific papers are used for examples. Side notes are created to explain how the paper is structured, what the results are, and how the data supported the results. These materials are generated in web format with links to the references and notes.
By emphasizing hands-on data analysis and being required early in their program of study, this course has a significant impact on the quantitative skills of science students. Furthermore, the curricular content and teaching materials are made broadly available to other institutions using an open source model and linkage to the National Science Digital Library (NSDL).
