Resources

Python re-implementation of the working memory capacity (WMC) battery described by Lewandowsky at al. here. This implementation is a minute reproduction of the original MATLAB implementation and uses the same file output format for compatibility with accompanying scripts of the original implementation.

Various labs participating in the MultiplEYE COST Action already use this software, check it out!

The Python package pymovements allows for easily preprocessing and working with eye-tracking data. It features different preprocessing algorithms that can be freely chosen and parametrized by the user, integrates an interface to download and work with existing datasets, and many other features. Check it out!

A naturalistic eye-movements-while-reading corpus of 107 native English speakers reading machine-generated texts.

Click here for more details on how to use and how to cite this corpus!

A naturalistic eye-tracking-while-reading corpus containing data from 75 participants reading 12 scientific texts.

Click here for more details on how to use and how to cite this corpus!

We're aiming at sharing our knowledge and making it accessible for other researchers or lay people. This is why we contribute and create tutorials to be shared with everyone!

Our labs has lead or contributed to a variety of different eye-tracking datasets. Find all of our datasets below:

We have created an overview on existing eye-tracking-while-reading datasets. You can find the overview neatly presented in a filterable table!