Duda Marlena, Sovacool Kelly L, Farzaneh Negar, Nguyen Vy Kim, Haynes Sarah E, Falk Hayley, Furman Katherine L, Walker Logan A, Diao Rucheng, Oneka Morgan, Drotos Audrey C, Woloshin Alana, Dotson Gabrielle A, Kriebel April, Meng Lucy, Thiede Stephanie N, Lapp Zena, Wolford Brooke N
Department of Computational Medicine & Bioinformatics, University of Michigan.
Michigan Center for Integrative Research in Critical Care, University of Michigan.
J Open Source Educ. 2021;4(46). doi: 10.21105/jose.00138. Epub 2021 Dec 17.
We are bioinformatics trainees at the University of Michigan who started a local chapter of Girls Who Code to provide a fun and supportive environment for high school women to learn the power of coding. Our goal was to cover basic coding topics and data science concepts through live coding and hands-on practice. However, we could not find a resource that exactly met our needs. Therefore, over the past three years, we have developed a curriculum and instructional format using Jupyter notebooks to effectively teach introductory Python for data science. This method, inspired by The Carpentries organization, uses bite-sized lessons followed by independent practice time to reinforce coding concepts, and culminates in a data science capstone project using real-world data. We believe our open curriculum is a valuable resource to the wider education community and hope that educators will use and improve our lessons, practice problems, and teaching best practices. Anyone can contribute to our Open Educational Resources on GitHub.
我们是密歇根大学的生物信息学学员,成立了“编程女孩”的当地分会,为高中女生提供一个有趣且能给予支持的环境,让她们了解编码的力量。我们的目标是通过现场编码和实践操作来涵盖基础编码主题和数据科学概念。然而,我们找不到完全符合我们需求的资源。因此,在过去三年里,我们利用Jupyter笔记本开发了一门课程和教学形式,以有效地教授数据科学的入门Python。这种方法受到The Carpentries组织的启发,采用短小精悍的课程,随后是独立练习时间以强化编码概念,并以一个使用真实世界数据的数据科学顶点项目作为结束。我们相信我们的开放课程是更广泛教育社区的宝贵资源,并希望教育工作者能使用并改进我们的课程、练习题和教学最佳实践。任何人都可以在GitHub上为我们的开放教育资源做出贡献。