The growing importance of reproducibility and responsible workflow in the data science and statistics curriculum

Tuesday, December 13th, 20224:00 pm – 4:45 pm ET

Presented by: Aneta Piekut (University of Sheffield), Colin Rundel (Duke University), Micaela Parker (Academic Data Science Alliance), Nicholas J. Horton (Amherst College), and Rohan Alexander (University of Toronto)


Many new principles and standards have been developed to facilitate cultural changes in fostering reproducible research, but less so has been done in teaching. To highlight work in this important and developing area, the Journal of Statistics and Data Science Education invited papers related to "Teaching reproducibility and responsible workflow". The November 2022 issue of the journal is devoted to this topic (see We are excited by the opportunities and options brought forward in these 11 papers. This webinar will include an overview of the special issue that is intended to provide motivation, guidance, and examples that help the data science and statistics education community better inculcate these increasingly important research-based practices. The webinar will include an opportunity for Q&A with the audience focused on next steps and ways to move forward.