A Framework for Introductory Data Science Experiences for Non-Computer Science Majors

Document Type

Conference Proceeding

Publication Date

2024

Abstract

The surge in data science courses highlights an educational shift towards incorporating data skills as a fundamental component of a well-rounded academic curriculum. This growth indicates a recognition of the critical role that data plays in shaping our understanding of complex issues in today's data-driven society. It also underscores the need for data science education to be accessible, representative, and tailored to a wide array of learners and professionals. The work to date to establish a data science foundational knowledge framework represents a pivotal step in formalizing and enhancing data science education. Yet, these frameworks have been largely designed for those pursuing data science careers. The field is in need of a data science framework that focuses on the essential introductory knowledge and skills for non-CS students to build a solid foundation in data science. This paper provides a description of the literature review process and experiences the research team has drawn from to develop such a framework. It also positions this framework for future research in studying effectiveness and alignment to the K-12 space. © 2024 Elsevier B.V., All rights reserved.

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