OIT is seeking to better understand how faculty use data science notebooks and computational environments, for statistics, collaborative calculations, or machine learning (ML) models in their classes. These data science workflows can include tools such as Jupyter, Python, R, and more. OIT aims to improve service offerings and support to the university in a scalable way.
OIT is reviewing ServiceNow tickets relevant to Cloud Computing in the Classroom and Research Computing, with data compiled by Research Computing during the semesters from Fall 2020 to Spring 2022. Our team is also distributing a Qualtrics survey to faculty users from these months, in addition to a wider distribution to gauge broader demand. Further insights will be gleaned from research into peer institutions and trends in data science, computational environments, and the wider use and adoption of statistical methods across the university.
Project Team & Partners
- Research Computing: Andy Monaghan, RC SME
- Labs: Dilan Weerasinghe, Labs SME
- Academic Technology: Louis Cohen, Research SME
- Academic Technology: Shane Schwikert, Research Methods SME
- Academic Technology: Alyssa Strickler