Welcome to the STEM Writing Project

We want to help STEM faculty make scientific writing a bigger part of their teaching toolbox. We have built a collection of guidelines, training materials, class activites, student assessments, and program evaluation tools that make scientific writing instruction more evidence-based, systematic, and scalable.

We have TWO homes on the web.

Our Main Home is the BioQUEST/QUBES Hub

QUBES Hub is where you can learn about our Six Elements Model for teaching scientific writing, download our training and teaching resources, and collaborate with us on non-coding projects. It’s the best place to see how the strands of our different projects come together.

Our Second Home Is Here on GitHub!

This is where we store and share code and data files from research and development projects. These are some of the repositories associated with our project.

Our open-source Student Writing Guide for teaching scientific writing to undergraduates. The repo contains all text and supporting files required to publish the Guide in print and digital formats. A second repo from the ABLE 2022 Workshop details how to revise the Resource Guide.

The SAWHET v2.0 repo contains an R Shiny application that collects and validates student lab reports. The code is released under a GNU GPL3 license for others to modify and extend. A free public version of the application is available here.

The Biology Student Reports Archive is our published dataset for research in text mining and computational linguistics. It contains >4400 anonymized student reports plus metadata, licensed for non-commercial academic uses.

The GTA Comment Classifier is a proof-of-concept project testing whether instructor comments on laboratory reports can be extracted and categorized on a mass scale. Link to the project web site; link to data repository

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The STEM Writing Project is funded in part by NSF IUSE Program Award #1712423: “Improving Scientific Writing In Undergraduate STEM Classrooms: A Training Program for Students and Teaching Assistants Aided By Information Extraction Technology”. All contents are the opinion of the project team, and are not endorsed by NSF or other supporting agency.

Except where noted, all content is licensed for reuse under Creative Commons CC BY-NC-SA 4.0