The Physics Department and Center for Teaching and Learning are pleased to announce that Dr. Eric Mazur, Ph.D. will present two lectures on Friday, October 16th in the Tyler Tallman Recital Hall in the Sloan Music Center. The first, Confessions of a Converted Lecturer, will begin at 6 p.m. The second, Flat Space, Deep Learning, will begin at 7:30 p.m. Refreshments and a meet and greet session will occur between the two lectures.
Mazur is the Balkanski Professor of Physics and Applied Physics and Area Dean of Applied Physics at Harvard University. An internationally recognized scientist and researcher, he leads a vigorous research program in optical physics. Mazur has founded several companies and plays an active role in the industry.
"I thought I was a good teacher until I discovered my students were just memorizing information rather than learning to understand the material," said Mazur. "Who was to blame? The students? The material? I will explain how I came to the agonizing conclusion that the culprit was neither of these. It was my teaching that caused students to fail! I will show how I have adjusted my approach to teaching and how it has improved my students' performance significantly."
The teaching of physics to engineering students has remained stagnant for close to a century. In this novel team-based, project-based approach, we break the mold by giving students ownership of their learning. This new course has no standard lectures or exams, yet students' conceptual gains are significantly greater than those obtained in traditional courses. The course blends six best practices to deliver a learning experience that helps students develop important skills, including communication, estimation, problem solving, and team skills, in addition to a solid conceptual understanding of physics. This showcase will discuss the course philosophy and pedagogical approach and participants will take part in a new form of collaborative assessment. While the course we are piloting is an engineering physics course, the methods described in this talk are applicable to STEM and other fields.