#751: Coloniality in Data Science Education: Marginalization and Absorption of Indigenous Perspectives

This study examines how middle school students engaged with the sociopolitical dimensions of data when learning about Indigenous food sovereignty through a social studies unit integrating data science. Drawing on Lee et al. (2021) and Sabzalian (2019), we analyze interview and artifact data to explore how Indigenous perspectives were centered or erased in the enacted curriculum. We found students engaged with data through deficit-based orientations and proposed solutions positioning Indigenous communities as problems requiring outsider intervention. Even an Indigenous student's insider perspective was reinterpreted by the teacher through narratives of individual transformation, reproducing colonial logics. These findings extend the sociopolitical layer of data engagement to address colonial dimensions and highlight the need for anticolonial frameworks in data science education to challenge erasure of Indigenous perspectives in seemingly equity-oriented learning contexts.