Data Miners Group

BPC-DP Coding Like a Data Miner

A Culturally Relevant Data Analytics Intervention for High School Students

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Project overview


Modernizations in computer science (CS) have had indelible impacts on contemporary society—shaping not only how we interact, but also innovation and public discourse. For education, this underscores a critical need to support education efforts and best-practices that provide broadened opportunities to not only participate in the production of computational artifacts (e.g., computer programs, programmable circuits), but also the ability to critically navigate the productions of others (Gilbert, 2020). An increasingly prominent example is “big data” fields (e.g., including data yielding social media platforms such as Facebook, Twitter, TikTok, etc.) where productive participation can yield a slew of economic, social, and educational benefits. These developments underscore a need for CS education opportunities that support the development of both computational and data science literacies—the knowhow to extract, visualize, and critically analyze complex algorithms and data structures (Wilkerson & Polman, 2020).

However, learners who come from groups traditionally underrepresented (e.g., women, people of color, economically disadvantaged, etc.) in CS education (Sax et al., 2020; Code.org, 2021) and careers are placed at exceptional risk of marginalization in these areas. This is of concern in high school where many learners are forming decisions about their future education and career pursuits (Bieri Buschor et al., 2014; Castellanos, 2018; Murcia, Pepper & Williams, 2020; Khan, Robbins & Okrint, 2020). These disparities are also evident in the West Texas/El Paso region high schools where Hispanics and females out populate other groups yet represent significantly fewer enrollees in computer science coursework.

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Data Miners Group, University of Texas at El Paso