ERIC Number: EJ1371485
Record Type: Journal
Publication Date: 2022
Pages: 8
Abstractor: As Provided
ISBN: N/A
ISSN: N/A
EISSN: EISSN-2693-9169
Available Date: N/A
Teaching for Large-Scale Reproducibility Verification
Vilhuber, Lars; Son, Hyuk Harry; Welch, Meredith; Wasser, David N.; Darisse, Michael
Journal of Statistics and Data Science Education, v30 n3 p274-281 2022
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. Supplementary materials for this article are available online.
Descriptors: Statistics Education, Data Science, STEM Education, Social Sciences, Undergraduate Students, Information Management, Data Analysis, Replication (Evaluation), Documentation, Training, Learning Laboratories, Outcomes of Education
Taylor & Francis. Available from: Taylor & Francis, Ltd. 530 Walnut Street Suite 850, Philadelphia, PA 19106. Tel: 800-354-1420; Tel: 215-625-8900; Fax: 215-207-0050; Web site: http://www.tandf.co.uk/journals
Publication Type: Journal Articles; Reports - Research
Education Level: Higher Education; Postsecondary Education
Audience: N/A
Language: English
Sponsor: N/A
Authoring Institution: N/A
Grant or Contract Numbers: N/A
Author Affiliations: N/A