Leveraging Eye-Tracking Data for Assessing Different Reader Characterisitcs

Supervisor(s): Prof. Dr. Lena Jäger & Deborah Jakobi

In this project you will work with the already existing eye-tracking corpus PoTeC. This corpus contains eye-tracking data of participants reading different types of text while their eye-movements were tracked. The goal of your thesis is to develop and implement machine learning models for reader inference. This means that you will come up with ideas of how to predict, for example, the reader expert level based on the eye-movements when a reader is reading a specific text. You will compare different approaches to find out how we can best leverage eye-tracking data for reader inference.

• Solid background in machine learning
• Python