We teach foundational coding and data science skills to researchers worldwide.

Assessment

Analysis of Data Carpentry Workshop Impact

Data Carpentry workshops have made a meaningful impact on the way learners view their ability to complete computational tasks.

This post originally appeared on the Data Carpentry website It’s funny. When I first started working for Data Carpentry, I had never heard the phrase, “reproducible research”. I can tell you now that having attended a Software Carpentry workshop, Data Carpentry workshop, and a Software/Data Carpentry instructor training, I wish I had learned the skills we teach when I first began my PhD program.

I even confessed to my colleagues that the data I left behind for up and coming grad students is so disorganized, I sent them an e-mail to apologize! This community has made a believer out of me, and for good reason: Our workshops work.

See for yourself. Read the report of the recent analysis of Data Carpentry’s post-workshop surveys.

You can run your own analysis, too! The data is available in the assessment repo on GitHub.

Data Carpentry workshops have made a meaningful impact on the way learners view their ability to complete computational tasks. Learners have expressed satisfaction with workshop content and appreciation for the caliber of their instructors. Learners self-reported improved levels of data management and analysis skills following Data Carpentry workshops.

As Data Carpentry continues to offer more workshops, we hope to see a continued shift in the perspective of how researchers view and use computational skills. Data Carpentry will continue to develop and teach fundamental data skills to expand the community of data literate researchers.

If you missed our assessment community call, check out the slidedeck.

Comment below, and tweet us your thoughts @datacarpentry and @drkariljordan.

Dialogue & Discussion

Comments must follow our Code of Conduct.

Edit this page on Github