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Introducing Students to Research and Reproducibility with Open Science Tools

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Conference

2024 ASEE Annual Conference & Exposition

Location

Portland, Oregon

Publication Date

June 23, 2024

Start Date

June 23, 2024

End Date

June 26, 2024

Conference Session

Engineering Libraries Division (ELD) Technical Session 2

Tagged Division

Engineering Libraries Division (ELD)

Page Count

16

DOI

10.18260/1-2--47683

Permanent URL

https://peer.asee.org/47683

Download Count

87

Paper Authors

biography

Chasz Griego Carnegie Mellon University Orcid 16x16 orcid.org/0000-0002-2051-7491

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Chasz Griego is a Science and Engineering Librarian at Carnegie Mellon University (CMU) Libraries. He started at CMU as an Open Science Postdoctoral Associate with the Open Science and Data Collaborations Program. His interests include reproducibility in computational research, Python programming for data science, and advocating open science.

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Cheng Zhang Carnegie Mellon University

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Wenchao Hu Carnegie Mellon University

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Ziyong Ma Carnegie Mellon University

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Andy Ouyang Carnegie Mellon University

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Abstract

The adoption of transparent, reproducible, and open research can result in increased credibility and quality of research outputs for peers to confidently reuse. There are many digital open science tools and platforms that help organize lab notes, protocols, and code for open dissemination, but how confident can students or new researchers practice reproducible research with these tools? This presentation outlines how open science tools were integrated into a short summer course for undergraduate students. In this course, students were introduced to research first through the basics of the scientific method, the specific stages of the research lifecycle, and how open science practices can be applied at each stage. Simultaneously, students practiced research skills through Python exercises with data in Jupyter Notebooks. The course culminated with a reproducibility study, where students attempted to reproduce and build on samples of computational research, where outputs were prepared with and without open science tools. By doing this, students could experience and evaluate two different approaches to research dissemination. The reflections and products of students that participated in the course offered insight into how students adopt these tools and how these tools impact reproducibility of computational research.

Griego, C., & Zhang, C., & Hu, W., & Ma, Z., & Ouyang, A. (2024, June), Introducing Students to Research and Reproducibility with Open Science Tools Paper presented at 2024 ASEE Annual Conference & Exposition, Portland, Oregon. 10.18260/1-2--47683

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