AI and the Developing Child: Research Practicum

EDU T596 Subject & Catalog Number

Description

This is a petition-based course with a maximum enrollment cap of 15 students. To enroll in this course, you must complete both of the following steps by Thursday, August 20, 2026, at 5:00 p.m: (1) Complete this Google Form; and (2) Submit a petition on my.harvard. Please read the information below carefully before completing these steps.

Course Structure

This research practicum has two components:  

A required seminar on Tuesdays at 9:00 a.m. during Fall 1 only, for six weeks. (combined with T595–you do NOT need to register T595 separately if you are enrolled in T596)

Hands-on research experience in one of the projects you selected, lasting throughout the entire semester. Students are expected to complete 8–12 hours of research work, including a weekly one-hour project meeting scheduled at a time that is convenient for all project team members, likely on Tuesday afternoons.

Why This Research Practicum

The rationale for offering this research practicum is to increase the breadth and depth of students’ understanding and knowledge of AI, youth, and learning. The seminar component emphasizes “thinking” through reading and discussing cutting-edge research, while the practicum component emphasizes “doing” through hands-on participation in active research projects. This course may be particularly relevant for students who are interested in pursuing research careers in either academia or industry.

Research Projects

Students will join one of three projects from Professor Xu’s active research agenda. Each project focuses on a different age group, research question, and dimension of how AI is shaping learning, development, and everyday life for young people.

AI, Curiosity, and Information Seeking: This project examines how children use AI and other digital tools to ask questions, seek information, and pursue curiosity-driven learning.

Critical Thinking and Responsible AI Use Among Teens: This project explores how secondary students, teachers, and administrators understand and support responsible AI use in school settings. We are especially interested in how students question, verify, regulate, or limit AI’s influence as they use these tools for learning.

AI-Enabled Toys and Young Children: This project explores how young children interact with AI-enabled toys and how these interactions may shape play, learning, social connection, and development.

For more details about the project, please read here.

Mentorship and Research Community

Students will be supported by the course TFs, who are members of Professor Xu’s research team, including postdoctoral researchers and PhD students. They will provide guidance, mentorship, and feedback throughout the semester.

Students will also become part of a collaborative, cross-functional research community through weekly team meetings, working alongside peers with different areas of expertise, including data collection, data analysis, design, and software development. Together, they will share progress, learn from one another, and help move real research projects forward.