EXPANDING ACCESS AND REMOVING BARRIERS: DATA SCIENCE EDUCATION WITH THE OPEN CASE STUDIES DIGITAL PLATFORM
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Date
2021-12-10
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Johns Hopkins University
Abstract
Open Case Studies (OCS) is a data science education platform created to provide examples of best practices for the next generation of data scientists. The aim of this thesis project is to enhance the case studies and expand the services provided by the platform to further meet the needs of data sci- ence education today. The case studies were made accessible to non-English speakers with the addition of a feature that can toggle between translations with more than 100 languages. An RStudio "shiny" app was created to allow nontechnical users to create their own custom case studies. Interactive versions of the case studies were created that incorporate live tutorials using R packages "learnr" and "gradethis". This introduced the ability for case study readers to check their understanding along the way with feedback from interactive quizzes in the case study itself. Finally, an R package called "OCSdata" was developed to provide easy access to case study data and en- able modular use of the case studies. In tandem with these developments, the platform itself was analyzed with the help of user feedback and Google Analytics traffic data. The results of this assessment indicate that OCS is already providing essential material for data science education globally. The new developments detailed in this report will expand the reach and quality of the platform even further.
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Keywords
data science, open source, public health, R programming, data, case studies, statistics