Naser Al Madi of Colby College

Eye movements provide a window into the cognitive processes that underlie how people understand written language and source code. While reading and programming both involve interpreting symbolic information, the demands they place on attention, memory, and reasoning differ in important ways. This talk explores empirical findings from eye-tracking studies that compare natural language reading with program comprehension. By understanding the processes involved in reading code, we can gain new insights into the design of programming languages, developer interfaces, and coding best practices. Similarly, lessons from natural language reading research, coupled with advances in large language models, open opportunities to create more adaptive and supportive reading interfaces.

Biography:

Naser Al Madi is an Assistant Professor of Computer Science at Colby College. His research integrates eye tracking and software engineering, with a focus on enhancing source code comprehension by analyzing user behavior and eye movement during software development. In 2023, he spent a year at Harvard University as a visiting research scholar at the School of Engineering and Applied Science and the Schepens Eye Research Institute, where he contributed to projects in Human-Computer Interaction and the application of eye tracking in clinical rehabilitation. He earned his PhD from Kent State University in 2020 and began his full-time teaching career at Hamilton College, where he taught courses such as Operating Systems and Wearable Technology. His research interests include eye tracking, program comprehension, and software engineering.

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