ASDK20016U Climate change: Opinion and behavior

Volume 2026/2027
Education

Elective course offered by the MSc in Social Data Science.

 

The course is open to:

  • Exchange and Guest students from abroad
Content

This course will cover data-driven perspectives on public opinion and behavior related to climate change. We will mostly focus on the attitudes and behaviors of ordinary people in the global North; and we will be looking mostly at mitigation (cutting emissions) with only limited attention to adaptation (dealing with the consequences of climate change). The methods discussed in the course will be largely quantitative, with minor journeys into qualitative approaches.

We will build on students’ existing knowledge of (quantitative) methods, applying those methods to problems in climate social science.The focus of this course is therefore on understanding applications of methods (ranging from basic to advanced) in practice, rather than on teaching new methods.

We will investigate psychological topics such as: barriers and drivers of pro-environmental behavior, behavioral change interventions, environmental communication, and the behavioral economics of climate change. We will also cover topics from political science and sociology, including: measuring climate change opinion via polls, the effects on climate attitudes of norms and social identities, media and social media; and the causes and effects of climate movement participation.

Guest lecturers will bring in state-of-the art data science research in climate psychology and other related disciplines.

 

Learning Outcome

Knowledge:

  • know how to measure climate change attitudes and behaviors
  • know what are the main correlates and drivers of these attitudes and behaviors
  • know what are the main approaches to promoting pro-environmental behavior
  • be able to discuss climate attitudes and behaviors from a psychological, political and sociological perspective

 

Skills:

  • be able to select and evaluate  tools and methods to use in the study of climate psychology, such as questionnaires and experiments
  • be able to select and evaluate tools and methods to use in the study of climate politics and sociology, such as observational studies

 

Competences:

  • be able to critically read and assess state-of-the art research in behavioral science, public opinion studies, and political psychology in the area of climate change.

 

 

Berger, Sebastian, Andreas Kilchenmann, Oliver Lenz, Axel Ockenfels, Francisco Schlöder, and Annika M. Wyss. 2022. “Large but Diminishing Effects of Climate Action Nudges under Rising Costs.” Nature Human Behaviour 6 (10): 1381–85. https:/​/​doi.org/​10.1038/​s41562-022-01379-7.

 

Bergquist, Parrish, Clara Vandeweerdt, Matto Mildenberger, Peter Howe, Jennifer Marlon. Measuring global concern about climate change with a dynamic, group-level item response theory model. Working paper.

 

Floyd, Donna L., Steven Prentice-Dunn, and Ronald W. Rogers. 2000. “A Meta-Analysis of Research on Protection Motivation Theory.” Journal of Applied Social Psychology 30 (2): 407–29. https:/​/​doi.org/​10.1111/​j.1559-1816.2000.tb02323.x.

 

Mackay, Caroline ML, Michael T. Schmitt, Annika E. Lutz, and Jonathan Mendel. "Recent developments in the social identity approach to the psychology of climate change." Current Opinion in Psychology 42 (2021): 95-101.

 

Maki, Alexander, Amanda R. Carrico, Kaitlin T. Raimi, Heather Barnes Truelove, Brandon Araujo, and Kam Leung Yeung. 2019. “Meta-Analysis of pro-Environmental Behaviour Spillover.” Nature Sustainability 2 (4): 307–15. https:/​/​doi.org/​10.1038/​s41893-019-0263-9.

 

Mildenberger, Matto, and Dustin Tingley. "Beliefs about climate beliefs: the importance of second-order opinions for climate politics." British Journal of Political Science 49, no. 4 (2019): 1279-1307.

 

Nisa, Claudia F., Jocelyn J. Bélanger, Birga M. Schumpe, and Daiane G. Faller. 2019. “Meta-Analysis of Randomised Controlled Trials Testing Behavioural Interventions to Promote Household Action on Climate Change.” Nature Communications 10 (1): 4545. https:/​/​doi.org/​10.1038/​s41467-019-12457-2.

 

Simpson, Brent, Robb Willer, and Matthew Feinberg. "Radical flanks of social movements can increase support for moderate factions." PNAS Nexus 1, no. 3 (2022): pgac110.

 

Valkengoed, Anne M. van, and Linda Steg. 2019. “Meta-Analyses of Factors Motivating Climate Change Adaptation Behaviour.” Nature Climate Change 9 (2): 158–63. https:/​/​doi.org/​10.1038/​s41558-018-0371-y.

Basic statistics (linear regression, ANOVA) are a prerequisite.
A familiarity with applied quantitative research methods (experimental design and analysis, causality in observational studies) is strongly recommended.
Interactive lectures
  • Category
  • Hours
  • Lectures
  • 28
  • Preparation
  • 102
  • Exam
  • 76
  • Total
  • 206
Continuous feedback during the course of the semester
Feedback by final exam (In addition to the grade)
Credit
7,5 ECTS
Type of assessment
Home assignment
Type of assessment details
A witten take-home assignment, written either in a group, or individually, on a subject pertaining to the course content and prescribed literature. The subject must be pre-approved by the course lecturer(s). The essay must be structured like a standard academic written assignment based on an explicitly defined research question, include the application of multiple methods taught in the course, and relate the use of these to relevant course readings.

The exam can be written individually or in groups of max. 4 students and must be a maximum of 10 standard pages (when written individually) + 5 standard pages per additional student in a group.
Aid
All aids allowed

ChatGPT and other large language model tools are permitted as a dedicated source, meaning text copied verbatim needs to be quoted, the tool cited, and generally the specific use made of them needs to be described in the submitted exam.

Marking scale
7-point grading scale
Censorship form
No external censorship
Re-exam

Same as ordinary exam.

Criteria for exam assesment

The exam will be assessed on the basis of the learning outcome (knowledge, skills and competencies) for the course.