Treffer: Some Pedagogical Elements of Computer Programming for Data Science: A Comparison of Three Approaches to Teaching the R Language

Title:
Some Pedagogical Elements of Computer Programming for Data Science: A Comparison of Three Approaches to Teaching the R Language
Language:
English
Authors:
David Shilane (ORCID 0000-0001-5528-1506), Nicole Di Crecchio, Nicole L. Lorenzetti (ORCID 0000-0001-8381-1471)
Source:
Teaching Statistics: An International Journal for Teachers. 2024 46(1):24-37.
Availability:
Wiley. 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
Peer Reviewed:
Y
Page Count:
14
Publication Date:
2024
Document Type:
Fachzeitschrift Journal Articles<br />Reports - Research
DOI:
10.1111/test.12361
ISSN:
0141-982X
1467-9639
Entry Date:
2024
Accession Number:
EJ1408944
Database:
ERIC

Weitere Informationen

Educational curricula in data analysis are increasingly fundamental to statistics, data science, and a wide range of disciplines. The educational literature comparing coding syntaxes for instruction in data analysis recommends utilizing a simple syntax for introductory coursework. However, there is limited prior work to assess the pedagogical elements of coding syntaxes. The study investigates the paradigms of the dplyr, data.table, and DTwrappers packages for R programming from a pedagogical perspective. We enumerate the pedagogical elements of computer programming that are inherent to utilizing each package, including the functions, operators, general knowledge, and specialized knowledge. The merits of each package are also considered in concert with other pedagogical goals, such as computational efficiency and extensions to future coursework. The pedagogical considerations of this study can help instructors make informed choices about their curriculum and how best to teach their selected methods.

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