The affordances of R for analysing student learning data

Conference: FLIE Conference 2025

Abstract:

R is a free, BU-supported (via Apps AnyWhere), open-source programming language and software environment designed for data analysis, statistical computing and visualisation. Widely used in academia, research, and industry, R offers a comprehensive suite of tools for data manipulation, modelling, and graphical representation. Its extensive package ecosystem enables users to perform complex analyses with concise, readable code. R supports reproducible research through tools like R Markdown and Quarto, allowing seamless integration of code, results, and narrative.

Affordances of R?

Rich ecosystem for data analysis: With extensive packages like those in the tidyverse, R supports a wide range of statistical, machine learning, and data visualisation tasks commonly used to analyse student learning data.

Reproducible research: Tools like R Markdown and Quarto allow researchers to integrate code, results, and narrative in a single document, promoting transparency, reusability and reproducibility.

Active academic community: R has strong support in the research and academic communities, with frequent package updates, peer-reviewed contributions, and academic resources tailored to higher education needs.

Customisable tools: R integrates well with tools like Shiny for building interactive web apps making it suitable for dynamic, student-centred applications.

The poster shows examples of student learning data analysed in R.

Source: Manual