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Program Overview

The program in question is "A Crash Course in Data Handling with R," a Learning Enhancement project funded by the HEA and the National Forum for the Enhancement of Teaching and Learning.

Program Details

Module Information

• Module Title: A Crash Course in Data Handling with R
• Module Coordinator: Dr. Adam Kane
• Module Code: BIOL30030, BIOL40360, ZOOL40500
• Student Cohort: Third & Fourth Year Undergraduate Students, UCD School of Biology and Environmental Sciences
• Collaborator(s): Willson Gaul and Jon Yearsley

Background

The R statistical programming language is widely used in scientific fields, including ecology, biology, and environmental sciences. It is also a valuable tool for data visualization. Quantitative skills, including R skills, are highly valued by employers and are essential for students pursuing graduate degrees in biology and environmental sciences.

Goals

The primary objective of the workshop is to provide additional support to students in overcoming technical barriers to using R, enabling them to engage with the statistical and data analysis content of other modules. Specifically, the goals include:

• Identifying the steps of the data importing and data cleaning process that students find challenging
• Teaching solutions to the technical challenges identified
• Teaching students how to effectively search for and read help forums and other online resources when troubleshooting coding issues

The Innovative Approach

Before the workshop, students are asked to work through an R-based task and email a one-sentence description of where they became stuck. The workshop focuses on breaking tasks into small, sequential steps, clearly stating each task in normal language before attempting to write it in computer language. The "live code-along" format is used, where the instructor types a line of code, explains what it does, and then each student types the same line of code and runs it on their own computer.

Results

The program has delivered:

• 2 in-person workshops to 21 attendees in 2020
• 5 live workshops online via Zoom to more than 35 attendees Three step-by-step instruction documents have been created, covering setting up the R working environment, loading data, and thinking like a computer, sub-setting data, and doing logical tests in R. These documents, along with Rmarkdown files and example datasets, are available in a publicly accessible online GitHub repository.

Conclusion

The "A Crash Course in Data Handling with R" program is designed to support students in overcoming technical barriers to using R, enhancing their ability to engage with statistical and data analysis content in other modules. Through its innovative approach and comprehensive resources, the program aims to equip students with essential quantitative skills valued by employers and necessary for graduate studies in biology and environmental sciences.