Using Mathlink Cubes to Introduce Data Wrangling with Examples in R

This article explores an innovative approach to teaching data wrangling skills to students through hands-on activities before transitioning to coding.Data wrangling, a critical aspect of data analysis, involves cleaning, transforming, and restructuring data.We introduce the use of a physical tool, mathlink cubes, to facilitate a tangible understanding of datasets.This approach helps students grasp the concepts of data wrangling before implementing them in coding languages such as R. We detail a classroom activity that includes hands-on tasks paralleling common data wrangling processes such as filtering, selecting, and mutating, followed by their coding equivalents using R's dplyr package.

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Publication Details

Journal
Journal of Statistics and Data Science Education
Published
2025-03-29
DOI
https://doi.org/10.1080/26939169.2025.2485234
Citations
1
Primary Topic
Evolutionary Algorithms and Applications
Type
article
Field-Weighted Citation Impact
2.48

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article

Using Mathlink Cubes to Introduce Data Wrangling with Examples in R

Lucy D’Agostino McGowan
1 citations
Journal of Statistics and Data Science Education
Evolutionary Algorithms and Applications
2.48
article

Using Mathlink Cubes to Introduce Data Wrangling with Examples in R

Lucy D’Agostino McGowan
article en
1 citations

Abstract

This article explores an innovative approach to teaching data wrangling skills to students through hands-on activities before transitioning to coding.Data wrangling, a critical aspect of data analysis, involves cleaning, transforming, and restructuring data.We introduce the use of a physical tool, mathlink cubes, to facilitate a tangible understanding of datasets.This approach helps students grasp the concepts of data wrangling before implementing them in coding languages such as R. We detail a classroom activity that includes hands-on tasks paralleling common data wrangling processes such as filtering, selecting, and mutating, followed by their coding equivalents using R's dplyr package.

Journal of Statistics and Data Science EducationVol. 33(3)
Wake Forest University (US)
Wake Forest University
Openalex Percentile: Top 11%
Evolutionary Algorithms and Applications
2.48
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