Teaching biologists to compute using data visualization

Abstract

The accelerating use of computation in all aspects of science continues to widen the gap between student skills and expectations. Currently, computation is taught using one of two approaches: teach students a standard programming language (e.g., FORTRAN, JAVA or C) perhaps augmented by support tools such as Alice or teach them to use a program such as MATLAB by formulating and solving math problems. Both approaches have high failure rates for students hindered by poor mathematics training and weak logic skills. This paper describes an alternative approach that introduces students to computing in the context of data analysis and visualization using MATLAB. Our goal is produce computationally qualified young scientists by teaching a highly relevant computational curriculum early in their college career. The course, which integrates writing, problem-solving, statistics, visual analysis, simulation, and modeling, is designed to produce students with usable data analysis skills. The course is in its third year of implementation and is required of all biology majors at the University of Texas at San Antonio.