What We Teach About Race and Gender: Representation in Formal, Informal, and Non-Traditional Educational Content

Emileigh Harrison

Curricular materials used to teach children not only impart academic knowledge but also prepare children for citizenship by teaching them about societal values. As a result, it is vital that we understand the messages that are conveyed in the educational content we present to our children. This dissertation focuses on both applying and improving methods of computer-driven content analysis to measure how different topics such as climate change or slavery and different groups such as women or Asian Americans are portrayed in education materials. I will document temporal changes in curriculum content and compare differences across multiple sets of influential curricula including state-adopted textbooks from Texas and California as well as curricula used in non-traditional educational settings such as religious private schools and homeschooling families. I will also examine informal educational curriculum including children?s books commonly found in school libraries and within households across the United States. Using face detection, skin segmentation, and other computer vision tools, I will measure the representation of different genders, races, and skin colors in images. By applying natural language processing tools like named entity recognition and word embeddings I will measure not only which groups and topics are represented in text, but the context in which they are discussed. This work will contribute to our knowledge of what messages are conveyed in the content we use to teach our children and expand the set of tools available for social scientists to measure representation in a variety of contexts.

About Emileigh Harrison

Emileigh Harrison is a PhD student studying Public Policy at the University of Chicago. Her research is focused on understanding barriers to education and the role that education policy can play in eliminating them. Emileigh?s recent work focuses on applying natural language processing and computer vision tools to measure changes in gender and racial representation in educational content over time. She also examines the impact of higher education policies on promoting social mobility for students from low-income and historically marginalized backgrounds. Her work evaluates a range of policies, such as financial aid program design, articulation agreements, and remedial coursework placement policies.