Presentation
Building a Data Science Education Ecosystem Resource Collection
Event Type
Workshop
W
Education
HPC
Training
TimeSunday, 17 November 201911:45am - 11:50am
Location702
DescriptionPurdue University is creating a Data Science Education Ecosystem (DSEE) to prepare students for an increasingly data-driven world. Projects include The Data Mine, an undergraduate community of learning communities from many disciplines united by an interest in data science; disciplinary credit courses in digital humanities, microbiome analysis, and GIS; and modular courses and workshops on data science skills. These activities have created a need for innovative instructional material to support and disseminate these projects.
Our project was funded to create a Data Science Education Ecosystem Resource Collection (DSEERC) leveraging the expertise of faculty in the Purdue University Libraries and School of Information Studies (PULSIS), the expertise and infrastructure of Research Computing, and the students and instructors of The Data Mine. The scope of the collection will be curated instructional material produced by and for DSEE efforts on campus. Formats will include interactive tutorials, videos, lessons and datasets with an emphasis on modular content that can be used in courses or as needed by students. The DSEERC will lower the barrier to data science education because learners will have access to material even if they are not currently enrolled in class. Instructors can use the resource to explore new ways of teaching data science, minimize duplication of effort by reusing resources, and to grasp the DSEE landscape. This resource is critical for Purdue if we hope to build data literacy and fluency for all learners and to promote best practices in data science education.
Our project was funded to create a Data Science Education Ecosystem Resource Collection (DSEERC) leveraging the expertise of faculty in the Purdue University Libraries and School of Information Studies (PULSIS), the expertise and infrastructure of Research Computing, and the students and instructors of The Data Mine. The scope of the collection will be curated instructional material produced by and for DSEE efforts on campus. Formats will include interactive tutorials, videos, lessons and datasets with an emphasis on modular content that can be used in courses or as needed by students. The DSEERC will lower the barrier to data science education because learners will have access to material even if they are not currently enrolled in class. Instructors can use the resource to explore new ways of teaching data science, minimize duplication of effort by reusing resources, and to grasp the DSEE landscape. This resource is critical for Purdue if we hope to build data literacy and fluency for all learners and to promote best practices in data science education.
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