Bridging the Educational Gap between Emerging and Established Scientific Computing Disciplines
Bridging the Educational Gap between Emerging and Established Scientific Computing Disciplines
复制标题
弥合新兴和成熟科学计算学科之间的教育差距
DOI：
10.22369/issn.2153-4136/10/1/1
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发表时间：
2019
期刊：
影响因子：
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通讯作者：
D. Gruner
中科院分区：
文献类型：
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作者：
Marcelo Ponce;Erik Spence;R. Zon;D. Gruner
在本文中，我们描述了我们的经验，在开发课程，针对研究生在新兴的计算领域，包括生物学和医学科学。我们主要专注于计算数据分析和统计分析，同时教授学生编码和软件开发的最佳实践。我们的方法结合了理论背景和概念的实际应用。到目前为止，我们获得的结果和反馈揭示了几个问题：这些特定领域的学生缺乏这样的指导，尽管他们会从中受益匪浅;我们发现了学生形成的几个弱点，特别是在统计基础方面，但也在分析思维能力方面。我们在这里介绍我们在教学和开发这类课程时使用的工具，技术和方法。我们还展示了这一举措的几个成果，包括富有成效的多学科合作的潜在途径。
In this paper we describe our experience in developing curriculum courses aimed at graduate students in emerging computational fields, including biology and medical science. We focus primarily on computational data analysis and statistical analysis, while at the same time teaching students best practices in coding and software development. Our approach combines a theoretical background and practical applications of concepts. The outcomes and feedback we have obtained so far have revealed several issues: students in these particular areas lack instruction like this although they would tremendously benefit from it; we have detected several weaknesses in the formation of students, in particular in the statistical foundations but also in analytical thinking skills. We present here the tools, techniques and methodology we employ while teaching and developing this type of courses. We also show several outcomes from this initiative, including potential pathways for fruitful multi-disciplinary collaborations.