Expanding Data Science Education Through Open Source Tools and Equitable Access
By
Steven Azeka
A bagel-shaped object. The form is there, the soul isn't.
Summary
This article examines the current state of data science education in the U.S., highlighting the lack of access to curriculum, tools, and infrastructure for many students. It reviews existing tools and emerging technologies, concluding that broadening data science education requires a multifaceted approach addressing technological accessibility, instructional equity, curricular relevance, and long-term sustainability.
Key quotes
· 3 pulledAs data plays a more integral part to our daily lives, there is a growing need for data science education.
Access to curriculum, tooling, and infrastructure is not readily available to many students in the U.S.
Broadening data science education requires a multifaceted approach, involving technological accessibility, instructional equity, curricular relevance, and long-term sustainability.
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