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The Quantitative Methods Boot Camp: Teaching Quantitative Thinking and Computing Skills to Graduate Students in the Life Sciences

机译:量化方法新手训练营:向生命科学研究生教授量化思维和计算技能

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The past decade has seen a rapid increase in the ability of biologists to collect large amounts of data. It is therefore vital that research biologists acquire the necessary skills during their training to visualize, analyze, and interpret such data. To begin to meet this need, we have developed a “boot camp” in quantitative methods for biology graduate students at Harvard Medical School. The goal of this short, intensive course is to enable students to use computational tools to visualize and analyze data, to strengthen their computational thinking skills, and to simulate and thus extend their intuition about the behavior of complex biological systems. The boot camp teaches basic programming using biological examples from statistics, image processing, and data analysis. This integrative approach to teaching programming and quantitative reasoning motivates students’ engagement by demonstrating the relevance of these skills to their work in life science laboratories. Students also have the opportunity to analyze their own data or explore a topic of interest in more detail. The class is taught with a mixture of short lectures, Socratic discussion, and in-class exercises. Students spend approximately 40% of their class time working through both short and long problems. A high instructor-to-student ratio allows students to get assistance or additional challenges when needed, thus enhancing the experience for students at all levels of mastery. Data collected from end-of-course surveys from the last five offerings of the course (between 2012 and 2014) show that students report high learning gains and feel that the course prepares them for solving quantitative and computational problems they will encounter in their research. We outline our course here which, together with the course materials freely available online under a Creative Commons License, should help to facilitate similar efforts by others.
机译:在过去的十年中,生物学家收集大量数据的能力迅速提高。因此,至关重要的是研究生物学家在培训过程中获得必要的技能,以可视化,分析和解释此类数据。为了满足这种需求,我们为哈佛医学院的生物学研究生开发了定量方法的“训练营”。这门简短而密集的课程的目的是使学生能够使用计算工具来可视化和分析数据,增强他们的计算思维能力,并模拟从而扩展他们对复杂生物系统行为的直觉。新手训练营会使用来自统计,图像处理和数据分析的生物学示例教授基本编程。这种用于编程和定量推理的综合方法通过证明这些技能与他们在生命科学实验室中的工作的相关性来激发学生的参与度。学生还有机会分析自己的数据或更详细地探索感兴趣的主题。该课程的授课内容包括短期演讲,苏格拉底讨论和课堂练习。学生们在课堂上花费大约40%的时间来解决短期和长期问题。高的师生比率使学生在需要时可以获得帮助或其他挑战,从而增强了各个精通水平的学生的体验。从课程的最后五门课程(2012年至2014年)的课程结束时调查收集的数据表明,学生报告了很高的学习成就,并认为该课程为他们解决研究中遇到的定量和计算问题做好了准备。我们在这里概述我们的课程,并根据知识共享许可在网上免费提供课程材料,这将有助于促进其他人的类似努力。

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