@inproceedings{c7f2ac3c59ca487db2e5049361ef8be3,
title = "Towards the Design of a Culturally Relevant Curriculum for Equitable, Data Mining-Based CS Education",
abstract = "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.",
author = "Amanda Barany and Sayed Reza and Michael Johnson and Alan Barrera and Omar Badreddin and Crystal Fuentes and Walker, \{Justice Toshiba\}",
note = "Publisher Copyright: {\textcopyright} ISLS.; 17th International Conference of the Learning Sciences, ICLS 2023 ; Conference date: 10-06-2023 Through 15-06-2023",
year = "2023",
language = "English (US)",
series = "Proceedings of International Conference of the Learning Sciences, ICLS",
publisher = "International Society of the Learning Sciences (ISLS)",
pages = "1498--1501",
editor = "Paulo Blikstein and \{Van Aalst\}, Jan and Rita Kizito and Karen Brennan",
booktitle = "ISLS Annual Meeting 2023",
}