Eye Tracking Course

We are pleased to announce that from April 9 to 13, Prof. Bernhard Angele will hold a course about eye tracking, each morning from 10 am to 12. The course will be about how an eye tracker works, setting up an experiment for data collection, data cleaning and aggregation, and data analysis and reporting. A more detailed syllabus will be posted soon on our website. 

All the SISSA PhD students (especially those in the first year) and Trento master students are strongly encouraged to attend. 

Day 1 (Monday)
Introduction to eye movement research
We will discuss the characteristics of eye movements and eye movement control. We will also examine some models of eye movement control in reading and scene perception.

Day 2 (Tuesday)
Planning an eye-movement experiment
We will talk about how modern eye-trackers work and lay out the structure of a simple eye-movement experiment. We will also address best practices for data collection and storage. An overview of the OpenSesame software will be given.

Day 3 (Wednesday)
Implementing an eye-movement experiment in OpenSesame
We will see how the simple eye-movement experiment we talked about on Day 2 can be implemented in OpenSesame. We will also address issues of testing an experiment before deploying it and measuring participant behaviour at the same time as eye-movements.

Day 4 (Thursday)
Cleaning, preparing, and summarising eye-movement data
We will examine how eye-tracking data files can be read, cleaned, aggregated, and summarised in the R software. We will use Eyelink data files as an example and will address issues such as how to compute common eye-movement measures such as first fixation duration and gaze duration/dwell time, how to remove outliers, and how to store the cleaned data.

Day 5 (Friday)
Statistical analysis of eye-movement data
Most eye-movement data have a relatively complex random effects structure, making it necessary to use advanced statistical methods such as Linear Mixed Models (LMMs). We will go through an analysis of an example data set and how to report the results. We will also address issues of Reproducible Research and Open Science.