Michael Alan Chang
Assistant Professor
Assistant Director, Earl Center for Learning & Innovation
Dr. Michael Alan Chang is an assistant professor at Boston University Wheelock College of Education & Human Development, a faculty fellow in the Faculty of Computing & Data Sciences (CDS), and an assistant director at the Earl Center for Learning & Innovation. Dr. Chang is a learning scientist and computer scientist who envisions AI-supported possibilities for teaching and learning that go outside the dominant, status quo instructional practices of schooling. He builds on ethical, relational, and speculative approaches to participatory design and closely partners with students, their families, and their teachers.
Before coming to BU Wheelock, Dr. Chang was a postdoctoral researcher at the University of California Berkeley where he worked with two major projects: the NSF Institute for Student-AI Teaming (iSAT) and the Center for Integrated Research on Computing and Learning Sciences (CIRCLS). He led the development of the Learning Futures Workshops, a 3-years co-design effort that worked with youth, teachers, and families. His design work has directly led to the design and implementation of novel AI-based collaborative learning tools that support equitable and democratic outcomes of schooling. This tool, the Community Builder (CoBi), has been deployed in public middle and high schools across the country.
As a doctoral student, Dr. Chang designed and implemented privacy-preserving computing systems, studied system-level support for large scale training of deep neural networks, and developed approaches to automatically deploy and maintain “microservice” computing clusters. He publishes to a variety of different fields, spanning the learning sciences, AI for Education, human-computing interaction (HCI), artificial intelligence, and distributed systems and privacy preserving computing. His work has appeared in many publications, including Conference on Human Factors in Computing Systems (ACM CHI), International Society of the Learning Sciences (ISLS), Artificial Intelligence in Education (AIEd), and Operating Systems Design and Implementation (OSDI).
pronouns: he/him
Recent News
- The Case for High School Interns on Campus
- Scholarly Accomplishments September 2025
- BU Wheelock Announces 2025 Faculty Awards
- BU Wheelock Welcomes New Faculty for 2024
In the Media
Education
PhD, Computer Science, University of California, Berkeley
BSE, Computer Science, Princeton University
Research
NSF Institute for Student AI Teaming (iSAT): The U.S. National Science Foundation AI Institute for Student-AI Teaming (iSAT) is an interdisciplinary research community dedicated to transforming classrooms into more effective, engaging and equitable learning environments. We team with diverse groups of students and teachers to develop the next-generation of collaborative learning environments. Learn more.
Selected Publications
Chang, M. A., Rajala, A., Philip, T. M., Cortez, A., Shaw, M., Lehtinen, J., Taimela, I., Garcia, J. E., Vishwanath, A., Pea, R., & Mirra, N. (2025). Constructions of feasibility within expansive designs for justice with communities. In A. Rajala, A. Cortez, R. Hofmann, A. Jornet, H. Lotz-Sisitka, & L. Markauskaite (Eds.), Proceedings of the 19th International Conference of the Learning Sciences – ICLS 2025 (pp. 2460–2468). International Society of the Learning Sciences.
Chang, M. A., Penuel, W. R., & Philip, T. M. (2025). “It goes both ways”: Envisioning mutually compassionate relations between teachers and students. In A. Rajala, A. Cortez, R. Hofmann, A. Jornet, H. Lotz-Sisitka, & L. Markauskaite (Eds.), Proceedings of the 19th International Conference of the Learning Sciences – ICLS 2025 (pp. 547–555). International Society of the Learning Sciences.
Chang, M. A., & Philip, T. M. (2025). Caught between expansive world-building and the status quo: Using figured worlds to understand world-building in AI for educational co-design contexts. Journal of the Learning Sciences, 1–49. https://doi.org/10.1080/10508406.2025.2490514
Chang, M. A., Tissenbaum, M., Philip, T. M., & D’Mello, S. K. (2025). Co-designing AI with youth partners: Enabling ideal classroom relationships through a novel AI relational privacy ethical framework. Computers and Education: Artificial Intelligence, 100364. https://doi.org/10.1016/j.caeai.2025.100364
Chang, M. A., Wong, R. Y., Breideband, T., Philip, T. M., McKoy, A., Cortez, A., & D’Mello, S. K. (2024). Co-design partners as transformative learners: Imagining ideal technology for schools by centering speculative relationships. Proceedings of the CHI Conference on Human Factors in Computing Systems. Presented at the Honolulu, HI, USA. doi:10.1145/3613904.3642559
Chang, M. A., Roschelle, J., Dickler-Mann, R., & Bush, J. B. (2024). Using adapted conjecture maps to foster interdisciplinary collaboration between Learning Scientists and Novice AI-Ed Researchers. In Lindgren, R., Asino, T. I., Kyza, E. A., Looi, C. K., Keifert, D. T., & Suárez, E. (Eds.), Proceedings of the 18th International Conference of the Learning Sciences - ICLS 2024 (pp. 1542-1545). International Society of the Learning Sciences.