BPC-DP: Coding Like a Data Miner: A Culturally Relevant Data Analytics Intervention for High School Students

With the advent and increased use of the internet, social media has become an integral part of people’s lives. Platforms such as Facebook, Twitter, and TikTok generate a large volume of data that can be analyzed for a range of insights. This underscores the need for educational opportunities in which students can explore big data approaches to extract, visualize, and critically analyze complex algorithms and data structures.

This demonstration project will develop a big data curriculum that uses cutting-edge social media data mining techniques via Twitter and a culturally relevant design to engage students from underrepresented groups in the West Texas/El Paso region. The curriculum will be co-designed by a team of teachers and students, and then piloted in El Paso high schools, which have a large population of students who are underrepresented.

The outcomes of this project have the potential to transform models of computing and data literacy in which students access their own personal interests to participate in the creation of computational artifacts and navigate the products of others.

This BPC Demonstration Project aims to provide evidence-based insights on “Big Data”-centric computer and data science teaching and learning with underrepresented pre-college student populations. The team will iteratively develop and pilot a culturally relevant data mining and analytics curricular unit with groups of teachers and students who, respectively, serve or come from underrepresented groups.

The team will leverage mixed-methodological approaches to examine learning outcomes for CS education and the learning sciences. This research is guided by two research questions: (1) What critical learning and instructional resources are needed to productively sustain a CS curricular intervention that emphasizes culturally relevant data mining and analytics?, (2) What learning experiences and outcomes result when implementing a CS education program that emphasizes culturally relevant data mining and analytics?

This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.