Social Science
Artificial Intelligence, Natural Language Processing

Ying Xu

Assistant Professor

Marsal Family School of Education

Assistant Professor, Marsal Family School of Education

Xu’s research is focused on the educational applications of artificial intelligence, in particular, natural language processing and speech technologies. She explores how these conversational technologies play the role of social partners or learning companions for children, and leverages AI to empower teachers to co-create learning resources to support their instructional goals. In addition, Xu’s research also aims to identify and actively challenge biases inherent in AI technologies used for educational purposes, with the goal of making these technologies more responsive and responsible to children, parents, and teachers from diverse backgrounds. To carry out her research, Xu closely collaborates with national media producers, including PBS KIDS and Sesame Workshop, as well as industrial partners and local community organizations. Her work has been supported by funding from the National Science Foundation, Schmidt Futures, and the Corporation for Public Broadcasting.

What are some of your most interesting projects?

Most of my work has been focused on partnering with public media to explore how AI can facilitate more active and educationally beneficial ways for children to engage with digital media. For instance, I collaborated with PBS KIDS to develop interactive television shows that allow children to talk to their favorite characters as they watch STEM-related programs. Think about children spending nearly two hours every day watching television. And considering that public media programs are valuable and also accessible learning resources, especially for children from less privileged backgrounds. If we could transform these hundreds of hours of screentime into active STEM learning experiences, that could have profound implications. We’ve carried out multiple studies to test whether these interactive videos indeed help children learn. One consistent finding is that when having interactions with the media character, children comprehend the science concepts better and are also more motivated to think about science problems than the children who watched the broadcast version that does not have the AI-assisted interactions. I remember testing this interactive program with preschoolers and observing their enthusiastic conversations with Elinor, which is the main character of a show. We also found that, when children used our interactive videos at their homes, their parents were more likely to participate in the discussion with their children. This heightened parent involvement could potentially have lasting impact on children’s STEM learning in the long run. With the support from the National Science Foundation and the Corporation for Public Broadcasting, we are working on making our interactive television shows publicly available on PBS KIDS platforms.

What is the most significant scientific contribution you would like to make?

I hope that my research can clarify some of our questions regarding how AI might impact child development. Specifically: How do children interact with, perceive, and learn from conversational technologies or non-human entities in general? Can these technologies actually become social partners for children? Ultimately, I hope my research can unpack the complex interplay among children, their social contexts, and technology. Only then will we be able to harness the unique learning experiences conversational agents can provide and ensure that this technology is integrated into children’s existing social contexts and relationships in ways that enhance their development.

Accomplishments and Awards