Erin Barno, Ph.D. candidate

Bio: Erin Barno, Ph.D. candidate, bridges her mathematics education background with educational technology design, development, and research. Erin’s research informs how educational technology can create opportunities to learn how teachers develop an awareness of their choices and changing critical consciousness. Due to the persistent message that mathematics teaching and learning is politically neutral, her work is pivotal towards analyzing mathematics teacher learning to make sense of if and how equitable mathematics teaching is taken up before and while in the classroom. As part of this project and the MIT Teaching Systems Lab, Erin is currently exploring applications by which artificial intelligence can be coupled with the knowledge and collaboration brought by teacher experts to create generated feedback for novice teachers engaging in digital clinical simulations.

Project Title: ASCEND: Automation in Simulations to Cultivate Equitable Novice Decision-Making in Mathematics Classrooms

Project Summary: Barno, Ph.D. candidate, will lead the design, training, and development of infrastructure to incorporate user feedback within the Teacher Moments platform that is generated by a fine-tuned AI agent. By collaborating with local mathematics teacher educators, the project will delineate instructional goals and train a large language model (LLM) to provide feedback for novice mathematics teacher responses within a Teacher Moments simulation to better enact ambitious and equitable mathematics teaching.

Research Mentorship Team:

Greg Benoit , Assistant Director of the Earl Center of Learning and Innovation and Lecturer in the Wheelock College of Education and Human Development, Boston University

Justin Reich, Educational Researcher and Director of the Teaching Systems Lab, Massachusetts Institute of Technology