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Autor/inFriedman, Alon
TitelVisualizing Protein Data Sets in R through a Student Peer-Review Rubric
QuelleIn: Biochemistry and Molecular Biology Education, 50 (2022) 5, S.453-456 (4 Seiten)Infoseite zur Zeitschrift
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ZusatzinformationORCID (Friedman, Alon)
Spracheenglisch
Dokumenttypgedruckt; online; Zeitschriftenaufsatz
ISSN1470-8175
DOI10.1002/bmb.21648
SchlagwörterVisual Aids; Peer Evaluation; Scoring Rubrics; Programming Languages; Biological Sciences; Data Analysis; Data Interpretation
AbstractThe R programming language and computing environment is a powerful and common platform used by life science researchers and educators for the analysis of big data. One of the benefits of using R in this context is its ability to visualize the results. Using R to generate visualizations has gained in popularity due to the increased number of R packages available to convert data to graphic display. In this paper, I ask the following question: how can student engagement with protein analysis be promoted using R-based visualizations in the classroom? During the 2021 IUBMB/ASBMD workshop "Teaching Science with Big Data", I presented a teaching strategy that used R for the visualization of protein data. In this report, I provide a teaching procedure and a summary of how students engaged with these data in our Introduction to R for Professional Data Science class. This report is based on a case study methodology by reviewing student peer comments for protein analyses conducted in R. The results indicated that students were active participants in the peer-review process and that they learned to take a critical view of data visualization. (As Provided).
AnmerkungenWiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us
Erfasst vonERIC (Education Resources Information Center), Washington, DC
Update2024/1/01
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