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Towards the Design of a Culturally Relevant Curriculum for Equitable, Data Mining-Based CS Education
Conference proceeding

Towards the Design of a Culturally Relevant Curriculum for Equitable, Data Mining-Based CS Education

Amanda Barany, Sayed Reza, Michael Johnson, Alan Barrera, Omar Badreddin, Crystal Fuentes and Justice Toshiba Walker
ISLS Annual Meeting 2023: Building Knowledge and Sustaining our Community - 17th International Conference of the Learning Sciences, ICLS 2023, Proceedings, pp 1498-1501
2023
DOI: https://doi.org/10.22318/icls2023.614567
url
https://doi.org/10.22318/icls2023.614567View
Published, Version of Record (VoR) Open

Abstract

Computer Science
As both data science and computer science (CS) grow increasingly ubiquitous as a part of professional practice and daily life, efforts are needed to design and implement equity-driven CS curricula that can leverage the affordances of online platforms as valuable and engaging data sources. To this end, this work reports on the systematic design of a culturally relevant curriculum for pre-college students that uses the social media platform Twitter as a source of user-driven big data on real-world contemporary topics. Developed and refined through co-design with teacher and youth stakeholders, the design of the “Coding Like a Data Miner” curriculum consists of four iterative modules that apply an inquiry-based learning approach with different levels of support to guide students through the examination of topics of their choosing using computer and data science techniques. The paper concludes with implications of this work for future CS research and education initiatives.

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