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flashr: An R package that creates flashcards
A Preprint
Jeffrey R. Stevens ∗
Department of Psychology, Center for Brain, Biology & Behavior
University of Nebraska-Lincoln
Lincoln, NE 68588
jeffrey.r.stevens@protonmail.com
August 10, 2022
Abstract
Flashcards can be an effective way to learn new material, including vocabulary, spoken
languages, and computer programming languages. The
flashr
R package creates decks
of flashcards from sets of terms and descriptions built around learning R. This package
draws from a repository of decks based on existing books and resources. New decks are easy
to build, and users can create new decks either for their own use or to contribute to the
repository. Moreover, the decks do not have to be about R or even programming languages.
Users can develop their own decks for whatever material they would like to learn.
Keywords R·rstats ·open education
1 Statement of need
Learning a new language—either spoken languages or computer programming languages—can require a lot
of time to map new vocabulary words to their meaning. Repetition is critical to learning new vocabulary
(Laufer, Meara, and Nation 2005; Larsen-Freeman 2012), and the repeated use of flashcards can provide
an effective way to learn technical vocabulary (Yüksel, Mercanoğlu, and Yılmaz 2020). It is not clear how
frequently flashcards are used to help computer language learners to learn programming syntax, but it seems
likely that flashcards could be a useful tool in this endeavor (Hermans 2021).
The goal of the
flashr
package is to provide a system to easily use and make flashcard decks. While digital
flashcard creators exist,
flashr
already has built-in flashcard decks in place for learners to solidify their
knowledge of R-specific syntax and concepts. In particular, it has decks for the chapters of a popular book
used to learn R and the tidyverse, R for Data Science (Wickham and Grolemund 2017). So learners can
practice remembering the functions as they work their way through the book. The built-in decks not only
have terms and descriptions but also links to the documentation for each term. This allows users to easily
follow up to get more information about the terms.
In addition to built-in decks, users can create their own decks. First, they may create CSV files with columns
of terms and descriptions, along with optional package names and links to documentation for each term.
Users can then contribute their decks to the
flashr_decks
repository as a community resource. And, of
course, they do not have to restrict their own decks to R or even programming languages. Alternatively, they
may draw functions from a list of functions used by decks in the
flashr_decks
repository to build their own
deck. This is easy to use because users do not have to construct their own descriptions. However, they are
limited to using functions already in the list. Combining the creation of CSV files and drawing from the
function list allows users to customize the decks to match their needs.
∗
Use footnote for providing further information about author (webpage, alternative address)—not for acknowledging
funding agencies. Optional.
A preprint - August 10, 2022
The
flashr
package provides an educational resource that can supplement other systems and techniques
to help users learn R. It is also highly customizable, allowing users to create flashcards to learn whatever
content they would like. Learners can harness the power of repetition to take the next step in their learning.
2 Acknowledgments
This work was funded by US National Science Foundation grant NSF-1658837.
References
Hermans, F. 2021. The Programmer’s Brain. Manning.
Larsen-Freeman, Diane. 2012. “On the Roles of Repetition in Language Teaching and Learning.” Applied
Linguistics Review 3 (2): 195–210. https://doi.org/10.1515/applirev-2012-0009.
Laufer, Batia, Meara, and P Nation. 2005. “Ten Best Ideas for Teaching Vocabulary.” The Language Teacher
29 (7): 3–6.
Wickham, Hadley, and Garrett Grolemund. 2017. R for Data Science. O’Reilly Media.
Yüksel, H. Gülru, H. Güldem Mercanoğlu, and M. Betül Yılmaz. 2020. “Digital Flashcards Vs. Wordlists
for Learning Technical Vocabulary.” Computer Assisted Language Learning.
https://doi.org/10.1080/
09588221.2020.1854312.
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