Today's students are tomorrow's researchers, and so intentionally integrating reproducibility into the curriculum will be crucial in promoting reproducible practices in the long term. Teaching students to work reproducibly starts with providing them with the skills to document their work so that any other researcher can reproduce their results with the materials provided by the student.
Incorporating Reproducible Practices
One way to accomplish this is to design an assignment that minimally requires students to submit their final report, the data files they used in their analysis, and the code files (e.g. R or Python) that they used to generate the results contained in their report.
Describes a protocol the authors developed for teaching Economics and Statistics undergraduates to document their statistical analyses for empirical research projects so that their results are completely reproducible and verifiable.
Citation: Baumer, B., Cetinkaya-Rundel, M., Bray, A., Loi, L., & Horton, N. J. (2014). R Markdown: Integrating A Reproducible Analysis Tool into Introductory Statistics. Technology Innovations in Statistics Education, 8(1).
Reproducing Others' Work
Another popular method for teaching reproducible research is to have an assignment that requires students to reproduce or replicate some or all of the results of a published journal article.
From the University of Glasgow, materials for teaching reproducible research using R across all undergraduate and postgraduate levels. Includes links to repos on two courses: Data Skills for Reproducible Science and Teaching Reproducible Data Analysis in R.