PhD course: experience sampling methods

Opening the black box of daily life

Course information

  • ECTS: 2
  • Number of sessions: 3
  • Hours per session: 3
  • Course fee: free for PhD candidates of the Graduate School € 450,- for non-members

Consult our enrolment policy for more information


Enrolment-related questions:
Course-related questions: Marleen de Moor,
Telephone: +31 (0)10 4082607 (Graduate School)

In the academic year 2023-2024 this course will take place offline.

  • Session 1
    November 28 (Tuesday) 2023
    Theil building (campus map), room C1-4
  • Session 2
    November 30 (Thursday) 2023
    G building (campus map), room G3-26
  • Session 3
    December 12 (Tuesday) 2023
    Theil building (campus map), room C1-4

More information and application here.

Aims and working method

People can be asked to share information about their daily life through their smartphones. For instance, users can be asked to fill out micro-questionnaires or enable GPS tracking. Such data collection methods are called Experience Sampling Methods (ESM).

With ESM, it is possible to assess exciting new research questions, but these data collection methods also come with challenges and questions. What research questions can I answer? How do I design an ESM-based study? How do I analyse obtained data? This workshop aims to help researchers explore these questions.

The workshop begins with a lecture about why it is relevant and useful to study daily life processes with ESM. Subsequently, participants follow two modules. Module A focuses on designing an ESM study, for instance with regard to developing sampling schemes, monitoring protocols and measurement instruments. Module B is about analysing ESM data in R.

Learning objectives

After completing module A (designing an ESM study) of the workshop, participants will know how to:

  • choose a sampling scheme for their study;
  • monitor and increase compliance by participants;
  • select and design measurement instruments.

After completing module B (analysing ESM data) of the workshop, participants will know how to:

  • calculate intra-class correlations;
  • estimate whether survey questions form a consistent scale;
  • do multilevel regression with ESM data.

Entry level and relevance

The workshop is relevant for researchers from all disciplines who apply quantitative research techniques. Participants will be invited to bring data and discuss examples from their own research.

Module A (designing an ESM study) does not require specific entry skills or knowledge. Module B (analysing ESM data) requires basic knowledge of R. If you doubt whether you have the proper entry level for module B, please contact Marleen de Moor at


More information and application here.