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TIER is changing the culture of research in the classroom

"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

TIER is changing the culture of research in the classroom

"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

TIER is changing the culture of research in the classroom

"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

TIER is changing the culture of research in the classroom

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

- Chris Conway, 2019-20 TIER Fellow

TIER is changing the culture of research in the classroom

"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

Symposium on Instruction in Reproducible Research

The 2021 TIER Spring Symposium was a ten-part virtual event exploring the educational purposes of teaching students transparent and reproducible methods of quantitative data analysis, featuring keynote presentations by Nicole Janz and Nick Horton.

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Welcome 2020/2021 TIER Fellows

We are delighted to announce the 2020/21 cohort of TIER Fellows: Alex Coppock, Aneta Piekut, and Ingo Rohlfing. Each brings exceptional talent and dedication to promoting transparency in empirical research.

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Share your experience

The RDA CURE-FAIR Working Group (Subgroup 3 - Challenges) is gathering user stories to better understand the particular challenges for all those who are involved in making computational reproducibility possible or attempting computational reproducibility (i.e., the ability to repeat the analysis and arrive at the same results). The goal is to provide a set of guidelines for preparing materials to better achieve this.

We invite you to submit your pain-point stories relating to computational reproducibility by using this user-friendly short form. Please pass on the link to anyone who may be interested.

Join the TIER Network

The TIER Network is a forum for exchange of ideas among instructors, researchers, and data support specialists working to integrate transparency and reproducibility into the training of students in quantitative research methods.

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