We moved :)

Please find the updated FORRT Website here where you can find what we are up to these days. Check out the self-assessment learning tool, FORRT’s Manuscript, FORRT’s curated resources, and FORRT Code of Conduct.

FORRT’s educational NEXUS

When making prescriptive claims, it is also important to supply stakeholders & interested parties the necessary tools for implementation. In this section we conceptualize FORRT as a source for reproducible and open-science teaching materials so that FORRT can also act towards the implementation and improvement of this research training. This is of fundamental importance because teachers’ and researchers’ time constraints are significant and implementing the necessary changes under these conditions would not be a trivial matter - no matter how sympathetic they may be to cause. As to address this, FORRT provides examples and links to existing resources and modules for each principle in the following way: for each principle FORRT provides a curated list of resources that have been vetted as suitable and fitting towards FORRT prescriptions. The goal of this curated list is to allow incremental improvements with a minimal informational encumberment. In other words, FORRT’s curated list is designed such as small time commitments can yield meaningful improvements in reproducible and open-science teaching. In addition, FORRT also provides a wider array of crowd-sourced teaching resources which can address sub-field specificities and peculiarities. For this we provide a google form that feeds a live database of resources which is open to the community’s input. The form is straightforward and can be easily filled in with modifiers so that the entered resources are appropriately categorized for easier retrieval. In doing so, we hope to sponsor general and specific contributions in terms of field/sub-field and FORRT principles, provide an always updated database, and promote integrative and cumulative scientific principles.

Note from authors: the list of curated resources presented here are - to the best of our knowledge - good representations & emblematic of each principle. However, we are not committed to them, and would very much like suggestions for others we may have ignored or were unable to find.

Pedagogical resources


This is a placeholder for our key pegagogical resources. Here we aim to host teaching materials that can be adapted and used by other teachers. Please contact us with any resources you would like to submit.

Curated list of resources

Principle 1 - Reproducibility knowledge

Principle 2 - Conceptual and Statistical Knowledge

Principle 3 - Reproducible Analysis

Principle 4 - Open-data & open-materials

Principle 5 - Pre-registration

  • “The Preregistration revolution” by Nosek, Ebersole, DeHaven, & Mellor (2018) https://doi.org/10.1073/pnas.1708274114

  • “Instead of ‘playing the game’ it is time to change the rules: Registered Reports at AIMS Neuroscience and beyond” by Chambers, Feredoes, Muthukumaraswamy, & Etchells (2014). https://orca.cf.ac.uk/59475/1/AN2.pdf An introduction to registered reports in AIMS, with answers to 25 questions about registered reports.

  • Registered reports resources on the Centre for Open Science website https://cos.io/rr/

Principle 6 - Replication Research

Additional Materials

Introductory Materials

Existing syllabi

  • Rigorous & Reproducible Research Practices (by Heather Urry) - syllabi covering replicability, preregistration, power, open data, and so on. Includes a comprehensive reading list https://osf.io/8bxau/

  • Good science, Bad science (E. J. Wagenmakers) - syllabi covering reproducibility, a registered report assignment, bayesian statistics, questionable research practices, and more. http://www.ejwagenmakers.com/GSBS/GSBS.html

  • Transparent and Open Social Science Research; a free online course from Berkeley Initiative for Transparency in the Social Sciences https://www.bitss.org/mooc-parent-page/

  • List of Course Syllabi for Open and Reproducible Methods https://osf.io/vkhbt/

Existing Online Courses

Other relevant resources:

  • Comprehensive crowdsourced resources on Meta-Analysis by John Sakaluk, Patrick Forscher, Katie Corker, Jin Goh, et al.

  • Comprehensive crowdsourced resources on Psychometrics by Eiko Fried & Jessica Flake

Crowdsourced list of resources

FORRT recognizes the importance to democratize the access and development of teaching materials for open and reproducible science. For this, we conceive FORRT a centralized plataform containing a rich, diversified and update-able collection of teaching resources. These live, editable & crowdsourced resources should - in time - be able to provide a comprehensive and plural online library of teaching materials, as well as cater to the specificities of a variety of departments/universities. We also have verified - and will continue to - links, added relevant tags, and kept it organized as a mean to maximize and fulfill its supportive potential.

To check out the resources we currently have, please see the spreasheet below, or visit the downloadable database directly.

If you would like to contribute to this database, please add the intended teaching resource(s) via this Google Form.