Building upon the knowledge and skills acquired in the introductory course, this advanced course delves deeper into the analytical dimensions of process tracing and eye-tracking data. Students will learn to scrutinize the underlying assumptions of data, sharpen their analysis techniques, and emphasize reproducibility in data analysis. By cultivating a critical understanding of the complexities involved in eye-tracking studies, students will be positioned to conduct innovative, robust, and reproducible research.

Learning outcomes

By the end of the course, students will be able to:

  1. Critically assess and identify the assumptions underlying process tracing data.
  2. Apply advanced data analysis techniques to eye-tracking data.
  3. Understand and implement strategies for reproducible data analysis.
  4. Evaluate the reproducibility of existing studies in the domain of process tracing.
  5. Develop and execute a high-quality eye-tracking study with a focus on reproducibility.
Attendance requirements

For this lecture participation is obligatory. Students are allowed to miss a maximum of 20%

Teaching/learning method(s)



  1. Critical Review of a Peer's Experiment (20%)
    • Review a peer's pre-registration and experimental design, identifying potential weaknesses and areas for improvement in terms of reproducibility.
  2. Advanced Analysis Report (30%)
    • Conduct a more detailed analysis of your eye-tracking experiment, considering deeper elements such as data assumptions and limitations.
  3. Final Project: Reproducible Eye-Tracking Study (50%)
    • Develop, execute, and report on a reproducible eye-tracking study, taking into consideration the feedback and learnings from earlier assignments.
Prerequisites for participation and waiting lists

Successful completion of the introductory course on decision-making processes, eye-tracking methodology, and data analysis techniques.


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Recommended previous knowledge and skills

To benefit from the class, you need to be at least in the design stage of your research project. 

Last edited: 2023-09-08