Supporting and Studying Collaborative Data Analysis and Writing in Statistics and Data Science Using the Integrated Statistics Learning Environment

• Activity Number: 60 - Invited E-Poster Session II
• Type: Invited
• Date/Time: Sunday, August 8, 2021 : 6:45 PM to 7:30 PM
• Sponsor: Section on Statistics and Data Science Education
• Author(s): Rebecca Nugent* and Philipp Burckhardt and David Brown and Mike Laudenbach
• Companies: Carnegie Mellon University and Carnegie Mellon University and Carnegie Mellon University and Carnegie Mellon University
• Keywords: e-learning platform; collaborative data analysis; communication; science of data science; remote learning

Abstract

While the importance of engaging our students in problems that apply statistical and data science methodology to real world contexts has never been in question, the related challenges have only grown with the seemingly constant increase in demand for our classes and the constraints of our new virtual modality. In addition, the need for teaching best practices for group collaboration and communication (written or oral) has never been greater. But how do we fit all this in? How do we provide feedback? What actually are the best practices for collaborative data analysis and writing about data?

We present our experiences and lessons learned from incorporating student-driven inquiry, collaborative data analysis, and writing across our programs with an emphasis on the introductory Statistics and English courses. Through the use of ISLE - an interactive browser-based platform that supports standard graphics, descriptive statistics, models, group collaboration, and written work in both in-person and remote environments - we track and analyze student actions to provide detailed personalized feedback and adaptive instruction for both the statistical analysis and the written argument.