Developing and deploying an integrated workshop curriculum teaching computational skills for reproducible research.

Autor:	Lapp Z; Department of Computational Medicine & Bioinformatics, University of Michigan., Sovacool KL; Department of Computational Medicine & Bioinformatics, University of Michigan., Lesniak N; Department of Microbiology & Immunology, University of Michigan., King D; BRCF Bioinformatics Core, University of Michigan., Barnier C; Department of Computational Medicine & Bioinformatics, University of Michigan., Flickinger M; Department of Biostatistics, University of Michigan., Krüger J; Center for Political Studies, Institute for Social Research, University of Michigan., Armour CR; Department of Microbiology & Immunology, University of Michigan., Lapp MM; Independent educator., Tallant J; Biological Station, University of Michigan., Diao R; Department of Computational Medicine & Bioinformatics, University of Michigan., Oneka M; Department of Computational Medicine & Bioinformatics, University of Michigan., Tomkovich S; Department of Microbiology & Immunology, University of Michigan., Anderson JM; Department of Microbiology & Immunology, University of Michigan., Lucas SK; Department of Microbiology & Immunology, University of Michigan., Schloss PD; Department of Microbiology & Immunology, University of Michigan.
Jazyk:	angličtina
Zdroj:	The Journal of open source education [J Open Source Educ] 2022; Vol. 5 (47). Date of Electronic Publication: 2022 Jan 08.
DOI:	10.21105/jose.00144
Abstrakt:	Inspired by well-established material and pedagogy provided by The Carpentries (Wilson, 2016), we developed a two-day workshop curriculum that teaches introductory R programming for managing, analyzing, plotting and reporting data using packages from the tidyverse (Wickham et al., 2019), the Unix shell, version control with git, and GitHub. While the official Software Carpentry curriculum is comprehensive, we found that it contains too much content for a two-day workshop. We also felt that the independent nature of the lessons left learners confused about how to integrate the newly acquired programming skills in their own work. Thus, we developed a new curriculum that aims to teach novices how to implement reproducible research principles in their own data analysis. The curriculum integrates live coding lessons with individual-level and group-based practice exercises, and also serves as a succinct resource that learners can reference both during and after the workshop. Moreover, it lowers the entry barrier for new instructors as they do not have to develop their own teaching materials or sift through extensive content. We developed this curriculum during a two-day sprint, successfully used it to host a two-day virtual workshop with almost 40 participants, and updated the material based on instructor and learner feedback. We hope that our new curriculum will prove useful to future instructors interested in teaching workshops with similar learning objectives. Competing Interests: Conflicts of Interest None.
Databáze:	MEDLINE
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