2015 CoE Towner Prize for Outstanding Graduate Student Instructors

Each year the College of Engineering awards the Towner Prize for Outstanding Graduate Student Instructors (GSIs) to the top graduate student instructors throughout the College of Engineering. In 2015, three of the four awards went to students in the Department of Electrical Engineering and Computer Science.

These students received the award for their exceptional ability, creativity or innovation as an instructor, their thorough understanding of the course content, and for their remarkable dedication to student success. We thank them for their commitment to excellence in teaching our students!

Jonathan Beaumont

Jonathan is a graduate student in the Computer Science and Engineering program. He was a GSI for EECS 470: Computer Architecture.

Jonathan was a thoughtful teacher, reworking his discussion on memory disambiguation by inventing an assignment that revealed fundamental misunderstandings rather than relying on students to self-identify as needing help. He also worked with his professor and one other GSI to transition the class into using a new programming language, increasing accessibility and reducing student “busy work.” In the process, he added new discussion material and rewrote many of the course’s labs and projects.

Michael Benson

Michael is a doctoral student in the Electrical Engineering degree program. He was a GSI for ENGR 101: Thriving in a Digital World.

He rewrote his course’s autograders such that students could use it to assess their coding projects before turning it in. This directly led to better student understanding of debugging and more advanced student questions in labs and lectures. During each lab session, Michael reviewed ideas presented in the lecture before addressing practical aspects of the material, tailoring assignments and explanations to student learning styles and interests. Students noted his exceptional willingness go out of his way to meet with them and help them understand course material.

Mai Le

Mai is a doctoral student in the Electrical Engineering:Systems degree program. She was a GSI for EECS 451: Digital Signal Processing and Analysis.

She designed her own discussion material to address multiple learning styles in class, creating new diagrams and interactive demos. Mai developed new active learning activities specific to the course material, including creating interactive Matlab graphical user interfaces, demonstrating circular convolution with paper rings, and coordinating a physical reenactment of Fast Fourier Transform algorithm. Rather than dictating what was reviewed in class, Mai allowed students to choose review topics. She modified her teaching to accommodate issues of diversity in the classroom, particularly those related to language and to the wide variety of student experience levels in the course. Mai provided individualized guidance on student projects, connecting some students to new research fields.