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Teaching Biologists to Compute using Data Visualization

机译:教生物学家使用数据可视化进行计算

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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 Fexas at San Antonio.
机译:在科学的各个方面加速使用计算,继续扩大了学生技能与期望之间的差距。当前,计算是使用以下两种方法之一进行的:教学生一种标准的编程语言(例如FORTRAN,JAVA或C),也许可以通过诸如Alice之类的支持工具加以扩充,或者通过制定和解决数学问题来教他们使用诸如MATLAB的程序。两种方法对于因数学培训差和逻辑技能薄弱而受阻的学生而言,失败率很高。本文介绍了一种替代方法,该方法将学生引入使用MATLAB进行数据分析和可视化的上下文中。我们的目标是通过在大学生涯的早期就讲授高度相关的计算机课程,培养出具有计算能力的年轻科学家。该课程集写作,解决问题,统计学,视觉分析,模拟和建模于一体,旨在培养具有可用数据分析技能的学生。该课程是实施的第三年,是位于圣安东尼奥的Fexas大学的所有生物学专业的必修课。

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