Moderated by: Ben Baumer
Assistant Professor, Statistical & Data Sciences at Smith College
This presentation is a report on an experiment I ran in my introductory statistics labs in the spring and fall 2020 semesters. It was an attempt to determine which of two R syntaxes was better for introductory teaching and learning: formula or tidyverse. One lab was conducted fully in the formula syntax, while the other was conducted in tidyverse syntax. Both groups of students used RStudio Cloud. The instruction took a flipped classroom approach, with pre-lab videos and associated RMarkdown documents provided to students ahead of synchronous class time. While quantitative analyses show limited differences between the two labs, there are certain qualitative differences that can be derived, which are relevant both to future R teaching, as well as more generally for quantitative analysis and reproducibility.
Amelia McNamara is an assistant professor in the Department of Computer & Information Sciences at the University of St Thomas, where she teaches statistics. Previously, she taught in the Program in Statistical and Data Sciences at Smith College. Dr. McNamara holds a bachelor's degree in English and mathematics from Macalester College, and a PhD in statistics from UCLA. She is an international keynote speaker and researcher at the intersection of statistics education and statistical computing, with the goal of making it easier for everyone to learn and do data science. Her work encompasses elements of statistical computing pedagogy and theory of human-computer interaction, as it relates to data.