Teaching for large-scale Reproducibility Verification

TL;DR

This paper presents an educational environment where undergraduates learn data provenance and reproducibility, applying these skills to real manuscripts, thereby enhancing their research skills and contributing to large-scale reproducibility verification.

Contribution

It introduces a novel training approach for undergraduates that combines education with practical application in reproducibility verification.

Findings

Students gain practical skills in data provenance and reproducibility.

The program enhances undergraduate research education.

Application of skills to real manuscripts improves reproducibility efforts.

Abstract

We describe a unique environment in which undergraduate students from various STEM and social science disciplines are trained in data provenance and reproducible methods, and then apply that knowledge to real, conditionally accepted manuscripts and associated replication packages. We describe in detail the recruitment, training, and regular activities. While the activity is not part of a regular curriculum, the skills and knowledge taught through explicit training of reproducible methods and principles, and reinforced through repeated application in a real-life workflow, contribute to the education of these undergraduate students, and prepare them for post-graduation jobs and further studies.