Diary studies

Methodology courses and philosophy of science

Course information

ECTS: 2.5 
Number of sessions: 4
Hours per session: 3
Course fee:

  • free for PhD candidates of the Graduate School
  • €525,- for non-members
  • consult our enrolment policy for more information


Telephone: +31 (0)10 4082607 (Graduate School)

Session 1
June 5 (Friday) 2020
Mandeville building (directions), room T19-01

Session 2
June 12 (Friday) 2020
Mandeville building (directions), room T19-01

Session 3
June 19 (Friday) 2020
Mandeville building (directions), room T19-01

Session 4
June 26 (Friday) 2020
Mandeville building (directions), room T19-01


Diary studies are aimed at systematically capturing the experiences, feelings and thoughts of participants in their daily life over a prolonged period of time. In this course we will deal with the quantitative approach to diary studies, which is also known as “Experience Sampling” or “Momentary Assessment”. We will discuss the background and epistemological foundations of the method, but also (and primarily) how to do the method practically.

Working method

There are four sessions of three hours. These sessions include a mix of instructions and exercises.

Learning objectives

After completion of this course you will be able to:

  • Understand the background of and varieties in diary studies;
  • know how to practically conduct quantitative diary studies, and
  • to reflect on the pros and cons of this method in relation to other approaches.

Session descriptions

Session 1: Background of and approaches of Diary Studies

Sessions 2-4: How to do Diary Studies

About the instructor

Joran Jongerling is a lecturer at the EUR Department of Pedagogical and Education Sciences, where he convenes courses in research methodology, SPSS skills and applied multivariable data analysis. In addition, he is in the final stages of his PhD project at Utrecht University on 'Modelling individual differences in intra-individual change and variability'. In his research he applies and analyses principles from Bayesian statistics, Multilevel analysis, and Structural Equation Modelling.