In the 2018 "Data Science for Undergraduates" consensus report, the National Academies of Science, Engineering, and Medicine outlined components of data acumen that were needed by all undergraduate students. Traditional topics in computation, statistics, mathematics were augmented by less traditional data analysis related concepts. As one example, workflow and reproducibility were identified as important components of data acumen that require repeated exposure to develop sufficient depth and mastery.
In this keynote talk, I will take a step back and discuss how transparent and reproducible research methods reinforce key aspects of critical thinking and provide a valuable framework for all students, not just those who are preparing for research careers. I will share insights and reflections from initiatives including introductory statistics and data science courses, capstone experiences, and the NSF-funded Data Science Corps Wrangle-Analyze-Visualize project.
Questions to be addressed in the talk include:
Why are these methods so important for all students to learn?
What are the capacities we want them to develop?
What are the skills that we need them to master to fluently utilize these methods?
What are best practices for teaching these methods?
Where can these methods be incorporated into the K-12 and college curricula?
How do we assess how effectively students are using these methods?
Nicholas J. Horton is Beitzel Professor of Technology and Society (Statistics and Data Science) at Amherst College. Nick is a biostatistician and data scientist focused on helping students "think with data" during the entire data analysis cycle. He has published more than 180 papers, co-authored a series of four books on statistical computing and data science, and was co-PI on the NSF funded MOSAIC and DSC-WAV projects. Nick received the ASA's Waller Education Award in 2009, the William Warde Mu Sigma Rho Education Award in 2014, the MAA Hogg Award for Excellence in Teaching in 2015, and the Concord Consortium Tinker Fellow in 2020. He is a Fellow of the ASA and the AAAS, was the past-chair of COPSS and co-chairs the National Academies Committee on Applied and Theoretical Statistics.