GESIS Training Courses

Scientific Coordination

Verena Kunz

Administrative Coordination

Claudia O'Donovan-Bellante
Tel: +49 621 1246-221

Using Smartphone Sensors, Apps, and Wearables

Online via Zoom
General Topics:
Course Level:
Software used:
Students: 220 €
Academics: 330 €
Commercial: 660 €
Additional links
Lecturer(s): Bella Struminskaya, Florian Keusch

About the lecturer - Bella Struminskaya

About the lecturer - Florian Keusch

Course description

Smartphone sensors (e.g., GPS, camera, accelerometer), apps, and wearables (e.g., smartwatches, fitness bracelets) allow researchers to collect rich behavioral data, potentially with less measurement error and lower respondent burden than self-reports through surveys. Passive mobile data collection (e.g., location tracking, call logs, browsing history) and respondents performing additional tasks on smartphones (e.g., taking pictures, scanning receipts) can augment or replace self-reports in surveys. However, there are multiple challenges to collecting these data: participant selectivity, (non)willingness to provide sensor data or perform additional tasks, privacy concerns and ethical issues, quality and usefulness of the data, and practical issues of implementation. This course will address the challenges by reviewing state-of-the-art practices of smartphone sensors, apps, and wearables data collection, ranging from small-scale studies of hard-to-reach populations to large-scale studies to produce official statistics, and discuss design best-practices for this type of measurement. Recommendations provided will include:
  • What research questions can be answered using smartphone sensors, apps, and wearables?
  • What are participants' concerns, and how to address them?
  • How to ask for consent for sensor measurements and ensure participation?
As part of this course, participants will have the chance to work on practical issues of implementing smartphone sensors, apps, and wearables into social science research. Participants will discuss their own research study designs using new technology and have the opportunity to present the scenarios of combining survey data with data from health, accelerometery, and location sensors. Participants will be able to conduct first analyses of data collected through smartphone sensors. The exercise is designed to be conducted in R and can be followed by those without extensive R experience. Participants may use their own software of choice (e.g., Python, Stata, or SAS), but we do not provide the code/syntax for these programs. The course will not demonstrate how to program smartphone sensor apps.

Target group

Participants will find the course useful if:
  • they are survey practitioners, researchers, or students who want a practical introduction to smartphone sensors, wearables, and app-based research.

Learning objectives

By the end of the course participants will:
  • know what smartphone sensors, apps, and wearables are available and what they can measure to facilitate and enhance surveys.
  • be able to identify potential applications of sensor and app measurement for their own data collection.
  • be able to anticipate practical issues when implementing sensor-based data collection.
  • understand the strengths, weaknesses, and practical implementation of combining self-reports with passive mobile data collection.
    Organisational structure of the course:
    The workshop will include a mix of lectures, short exercises, and question-based discussions of use cases. The exercises are usually group-based and will be done in breakout rooms. Participants who are currently collecting or plan on collecting data with smartphones, apps, and wearables are encouraged to discuss their study designs in the course. You might want to prepare a short presentation (5-7 min) that we can discuss on Day 1. Please email the instructors if you have questions about the presentation. It would be handy for participants to have their smartphones and any wearables (e.g., fitness bracelets, smartwatches) nearby during the course, if available.


  • No prior knowledge of smartphone sensors, wearables, and apps is required, but a basic understanding of survey data collection practice and survey errors is helpful.
  • To conduct some basic analysis of sensor data, a basic understanding of R is helpful.
    Software and hardware requirements
    For the exercise on data collected through smartphone sensors, participants need to have R ( installed and the ability to download packages on their computer.


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