Abstract
Rapid technological advances in the past decades have enabled molecular biologists to generate large-scale and complex data with affordable resource investments, or obtain such data from public repositories. Yet, many graduate students, postdoctoral scholars, and senior researchers in the biosciences find themselves ill-equipped to analyze large-scale data. Global surveys have revealed that active researchers prefer short training workshops to fill their skill gaps. In this article, we focus on the challenge of delivering a short data analysis workshop to absolute beginners in computer programming. We propose that introducing R or other programming languages for data analysis as smart versions of calculators can help lower the communication barrier with absolute beginners. We describe this comparison with a few analogies and hope that other instructors will find them useful. We utilized these in our four-hour long training workshops involving participatory live coding, which we delivered in person and via videoconferencing. Anecdotal evidence suggests that our exposition made R programming seem easy and enabled beginners to explore it on their own.
Highlights
Rapid technological advances in the past decades have enabled molecular biologists to generate large-scale and complex data with affordable resource investments, or obtain such data from public repositories
Multiple surveys with participants from around the globe have recognized a lack of basic data science skills among graduate student researchers, postdoctoral researchers, senior academics, technical staff, and industry researchers.[9]
Global surveys have revealed that the majority of postgraduate learners prefer short face-to-face training workshops.[9]
Summary
“The stepwise introduction into R from the simple explanation of the system as a calculator was very approachable and I felt that I was able to move into the system with a lot less trepidation and more curiosity to explore on my own.”— Anonymous feedback from an attendee of our R workshop in March, 2019. With a knowledge of how to interface with the “smart” version of calculators that we view R to be, intuition underlying its design, and hands-on analysis experience that we were able to integrate in one 4-hour-long workshop, we found that our trainees felt equipped to explore R for their practical research purposes. A popular advice is to treat a program as a piece of literature, addressed to human beings rather than to a computer.[23] Such practice facilitates reproducible research and enables open access, which are achievable goals in the digital age To this end, R provides the option to include text and analysis results along with blocks of code in the same document, e.g., as RMarkdown documents. These provide students with a concrete direction to continue learning and exploring R after the workshop
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