Designing Artistic Computing Learning Environments: A Lens for Equity with Technology
Abstract
Participation in computing across gender, race/ethnicity, and socio-economic status is far from equitable. This equity matters because it determines who gets to develop technology. Artistic computing environments is one lens to explore inequities that exist within the design of learning experiences. Artistic practices offer reflective processes that can enable learners to draw on their own values and cultures within the learning experience; while computing technology provides various new media for learners to express themselves. In this talk, Dr. DesPortes will present her research investigating these interdisciplinary spaces that span across poetry, photography, dance, data science, electronics, civic engagement, and programming. She will discuss insights from co-designing these spaces with artists, working with learners across these disciplines, and report on the challenges and opportunities within these domains.
Bio
Dr. Kayla DesPortes is an Assistant Professor of Human-Computer Interaction and the Learning Sciences at New York University. Her research vision is to use computing education to empower learners who are typically marginalized by technology. In her work, she applies a variety of participatory methods to design and study artistic computing learning environments and the technology that supports them. She works in collaboration with educators, learners, artists, and community organizations. This work has led her to explore ways for learners to leverage their cultures and values as they build expressive designs with computing. She received her PhD in Human-Centered Computing from Georgia Institute of Technology in 2018 and a B.S. in Electrical Computer Engineering from Cornell University in 2010. Dr. DesPortes has received funding from the National Science Foundation to support the exploration of physical computing, data science, machine learning, and dance learning environments (STEM+C #1933961), as well as funding to investigate the co-design of data science curriculum with art and math teachers (DRK12 #1908557).