By exploring intersectionality as a concept and as a practice, students use data storytelling to understand their lives and experiences.
Our self-paced curriculum is a three-part activity that explores intersectionality as a concept and as a practice. We apply data storytelling to help students understand their lives and experiences. In the first part, we introduce Michelle, an African American girl in high school, via an interactive Scratch animation. Through learning about the idea of intersectionality, Michelle finds hope in hearing how amazing people who look like her are computing pioneers and discovers her love for data science. She invites students to join her. In the second part of our curriculum, we explore data storytelling. Intersectionality data storytelling is visualizing identities and the structures of dominance through adding an emotional resonance to information. Students are introduced to the concept of data science through historical examples, such as DuBois’ data portraits of Black America in the early 1900s. Finally, we invite students to take what they have learned from Michelle’s story about intersectionality and data science to apply it to their own lives through projects. They can choose to discuss intersectionality further with friends and family, explore careers in computing, or learn more about the stories of the women in part 1. We also offer multiple pathways to get started including making data visualizations with at home crafts, creating with Scratch, and using Python programming. Black girls will be empowered to see themselves in this curriculum, positively impact their communities, and have a new language to describe their lived experiences.
This project was developed in Fall 2021 as a collaboration in Harvard Graduate School of Education's Designing for Learning by Creating (T550) course led by Media Lab alum Karen Brennan.