Teaching Open, Transparent, and Reproducible Data Analysis: Lessons from FORRT Flavio Azevedo скачать в хорошем качестве

Teaching Open, Transparent, and Reproducible Data Analysis: Lessons from FORRT Flavio Azevedo

Teaching Open, Transparent, and Reproducible Data Analysis: Lessons from FORRT Flavio Azevedo (FORRT community) Abstract: Reproducibility and transparency are at the core of responsible research, yet many researchers struggle with implementing these principles in their teaching and practice. This talk will introduce the Framework for Open and Reproducible Research Training (FORRT), a global community dedicated to integrating open scholarship into higher education. I will highlight key strategies for fostering reproducibility in teaching, drawing from FORRT's extensive resources, such as lesson plans, collaborative initiatives, and its curated database of Open Science materials. Additionally, I will discuss practical challenges in promoting open and reproducible research in classrooms, including pedagogical barriers and institutional constraints. This session aims to equip educators with concrete approaches to making reproducibility a norm in data analysis training. Participants will also learn how they can engage with FORRT and contribute to shaping the future of open and transparent research education. This was recorded as part of the TALMO session on Teaching Open, Transparent, and Reproducible Data Analysis organised by Mark Andrews & Elinor Jones (RSS) Wednesday 12 March 2025 3-5pm (GMT). More details and slides can be found at http://talmo.uk/2025/dataanalysis.html