Teaching Integrity in Empirical Research

These workshops will introduce attendees to Project TIER’s principles and practices of integrating reproducible methods into teaching and research. Attendance is limited to instructors and staff whose institutions are members of the UK Reproducibility Network.

Check out Richard Ball's latest article, published in the Harvard Data Science Review.

Matthew Platt's reproducibility exercise built on R/RStudio/R Markdown is now available in the Soup-to-Nuts Exercises section of the web site.

"Teaching project organization at the start of the course has made it easier for my students to troubleshoot errors, communicate results, and develop good habits for their future careers."

- Jenna Krall, 2017-18 TIER Fellow

"This course taught me to make sure I'm always checking in my data analysis scripts as source code into a repository that can be repeated by anyone."

- Gabe Rybeck, Haverford College class of 2016

"I require all my students to fully document their data sources and data manipulation... Investing in teaching documentation and coding has very high returns."

- Tomas Dvorak, 2015-16 TIER Fellow

"The TIER program has helped me advocate for open science change in my institutional and professional environments."

- Chris Conway, 2019-20 TIER Fellow

"All of my students have benefited greatly from having specific guidelines in order to make their research reproducible and transparent."

- David Vera, TIER Executive Committee