Ten simple rules for teaching applied programming in an authentic and immersive online environment

Hooley, Frances; Freeman, Peter; Davies, Alison

doi:10.1371/journal.pcbi.1009184

Cited by 2 publications

(2 citation statements)

References 13 publications

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“…By focusing on the environment and how we organise interaction, our 10 simple rules provide a unique toolkit to complement what is already known about optimising platforms for training [ 14 ] or the scientific content in short courses [ 15 ]. Carefully planned interactive elements, indeed, open up new avenues for content—such as focused discussion of individual needs, troubleshooting as its own skill set to learn, or inclusive exploratory projects.…”

Section: Discussionmentioning

confidence: 99%

Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses

Bacon

Holinski²,

Pujol³

et al. 2022

PLoS Comput Biol

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Section: Discussionmentioning

confidence: 99%

Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses

Bacon

Holinski²,

Pujol³

et al. 2022

PLoS Comput Biol

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“…Where possible, we point to published recommendations and draw on work from the field of software architecture and development practices. The vast majority of this literature focuses on team processes for complex projects, with only a modest discussion of software development Formal publications in this area include: Beck et al (1983), Feller et al (2007, Hooley et al (2021), andPoppendieck &Poppendieck (2003). In addition, detailed guidance is available in numerous blog posts (Postan, 2021) and Stack Overflow replies (Stack, 2022), but the provenance of this advice is often limited.…”

Section: R Software Engineering Practicesmentioning

confidence: 99%

Software Engineering Practices in Academia: Promoting the 3Rs—Readability, Resilience, and Reuse

Connolly

Hellerstein

Alterman

et al. 2023

Harvard Data Science Review

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Over the past decade as data science has become integral to the research workflow, we, like many others, have learned that good data science requires high-quality software engineering. Unfortunately, our experience is that many data science projects can be limited by the absence of software engineering processes. We advocate that data science projects should incorporate what we call the 3Rs of software engineering: readability (human understandable codes), resilience (fails rarely/gracefully), and reuse (can easily be used by others and can be embedded in other software). This article discusses engineering practices that promote 3R software in academia. We emphasize that best practices in academia may differ from those in industry because of substantial differences in project scope (most academic projects have a single developer who is the sole user) and the reward systems in place in academia. We provide a framework for selecting a level of software engineering rigor that aligns well with the project scope, something that may change over time. We further discuss how to improve training in software engineering skills in an academic environment and how to build communities of practice that span across disciplines.

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Ten simple rules for teaching applied programming in an authentic and immersive online environment

Cited by 2 publications

References 13 publications

Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses

Ten simple rules for leveraging virtual interaction to build higher-level learning into bioinformatics short courses

Software Engineering Practices in Academia: Promoting the 3Rs—Readability, Resilience, and Reuse

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