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

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Τίτλος: Some Pedagogical Elements of Computer Programming for Data Science: A Comparison of Three Approaches to Teaching the R Language
Γλώσσα: English
Συγγραφείς: David Shilane (ORCID 0000-0001-5528-1506), Nicole Di Crecchio, Nicole L. Lorenzetti (ORCID 0000-0001-8381-1471)
Πηγή: Teaching Statistics: An International Journal for Teachers. 2024 46(1):24-37.
Διαθεσιμότητα: 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
Ημερομηνία έκδοσης: 2024
Τύπος εγγράφου: Journal Articles
Reports - Research
Descriptors: Programming, Data Science, Programming Languages, Coding, Syntax, Computer Software, Teaching Methods, Curriculum
DOI: 10.1111/test.12361
ISSN: 0141-982X
1467-9639
Περίληψη: 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.
Abstractor: As Provided
Entry Date: 2024
Αριθμός Καταχώρησης: EJ1408944
Βάση Δεδομένων: ERIC
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  Data: Some Pedagogical Elements of Computer Programming for Data Science: A Comparison of Three Approaches to Teaching the R Language
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  Data: <searchLink fieldCode="AR" term="%22David+Shilane%22">David Shilane</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-5528-1506">0000-0001-5528-1506</externalLink>)<br /><searchLink fieldCode="AR" term="%22Nicole+Di+Crecchio%22">Nicole Di Crecchio</searchLink><br /><searchLink fieldCode="AR" term="%22Nicole+L%2E+Lorenzetti%22">Nicole L. Lorenzetti</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0001-8381-1471">0000-0001-8381-1471</externalLink>)
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  Data: 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
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  Data: 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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