Experience sampling: opening the black box of daily life

Methodology courses and philosophy of science

Introduction

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.
 

Key Facts & Figures

Type
Course
Duration
9 hours
Instruction language
English
Mode of instruction
Offline

What will you achieve?

  • 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.

Start dates

Session 1
November 28 (Tuesday) 2023
10.00-13.00
Theil building (campus map), room C1-4

Session 2
November 30 (Thursday) 2023
13.00-16.00
G building (campus map), room G3-26

Session 3
December 12 (Tuesday) 2023
10.00-13.00
Theil building (campus map), room C1-4

Aims and working method

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.

Session descriptions

  • Session 1: Lecture

  • Session 2: Module A

  • Session 3: Module B

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 demoor@essb.eur.nl.

Instructor

  • Prof. dr. Loes Keijsers is professor in Clinical Child and Family Studies at the Department of Psychology, Education and Child Studies. She is intrigued by the lives and relationships of teenagers, and how parents can optimally contribute to their child's positive development, mental health and well-being, despite their decreasing authority. Most likely, there is not a single answer to this question, as every child - and every family - is a unique dynamical system. To know what works for whom, Loes aims at empirically tapping into this heterogeneity of developmental processes, by relying on advanced methodological approaches. For instance, to obtain a 'photoalbum' of mood swings in the daily lives of teens, apps on mobile phones are used (i.e., Experience Sampling Methods). As theoretical inferences are only as good as our statistical models, Loes loves to keep up with and teach about statistical developments. To generate impact from these theoretical insights, Loes undertakes active efforts to implement research into practice (e.g., developing and implementing e-health applications to detect and prevent adolescent depression; TEDx speaker; Universiteit van Nederland). Also, Loes has written a book for the general public about the intriguing behaviors of teens: Waarom tieners zo irritant kunnen zijn. En hoe je daar als ouder mee kunt leren leven, 2013. Doing this, Loes aims at contributing to better health and well-being of future generations, by empirically studying the daily lives of teens and by collaborating interdisciplinary and transdisciplinairy to translate scientific knowledge into e-health tools and serious games.

Contact

Facts & Figures

Fee
  • free for PhD candidates of the Graduate School
  • € 450,- for non-members
  • Consult our enrolment policy for more information.
Tax
Not applicable
Application deadline
Tuesday 14 Nov 2023
Duration
9 hours
Offered by
Erasmus Graduate School of Social Sciences and the Humanities
Course type
Course
Instruction language
English
Mode of instruction
Offline

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