Utrecht University

This public health course provides an exciting opportunity to strengthen understanding of the role of social and structural factors in health and how more distal drivers of inequity interact with more proximal individual determinants of health outcomes and behaviors. In addition to highlighting contemporary theories and research that take an ecological approach to public health, the course showcases key examples of contemporary health issues affected by broader social and structural factors, such as social stigma of specific groups. The course also encompasses an overview of social and structural approaches to public health and health promotion, such as through social policy and environmental change, complementing well-known education and counselling approaches.

This course examines how we use language to perform our own identities, to recognize others' identity performances, and represent identity behaviors in speech and writing. Students read contemporary research and theory in the fields of sociolinguistics and linguistic anthropology to gain the theoretical tools and research methods for describing and analyzing language behaviors linked to identity. Topics to be covered include language ideology, critical race theory, ethnography, and discourse analysis to enable self-reflection about students' own language attitudes and identity practices. Students produce preliminary ethnographically informed research and writing by collecting and examining original data in this domain. They formulate a relevant research question and use one or more of the following methods of data collection and analysis to answer their question: participant observation, sociolinguistic interview, transcription, discourse analysis, and ethnographic writing. Students report on these analyses in spoken and written English appropriate for the fields of study introduced here. Lectures and tutorials are interactive requiring participation in games and game-derived elements as practice-based research for understanding key course concepts.

This course examines the main psychological phenomena at play in economic decisions including how knowledge about psychology and economic behavior can be used in practice.

Responsible Data Science is examined through the lens of four introductory dimensions: data dimension; algorithm dimension; human dimension, including psychology of human biases and ethics or moral philosophy; design dimension, including data visualization and interaction design and explainable artificial intelligence (XAI).

Throughout this course, students follow lectures and workshops, read literature, engage in class discussions, give presentations, critique, and conduct an investigation on a topic related to a (self-chosen) real-world ethical problem related to data science in a particular domain. The project also contains a practical solution to the problem illustrated in a low-fidelity prototype.

This course familiarizes students with fundamental issues in the area of self-regulation, motivation, and emotion. Topics include basic self-regulatory processes such as goal setting and goal striving, self-control, and self-knowledge and facilitating and disruptive factors that influence self-regulatory processes, such as motivation, emotion (regulation), habits, and automatic influences. Strategies for improving self-regulation are also discussed. These topics are focused on four specific themes of interest: health, education, finance, and sustainability. The course consists of lectures and tutorials with assignments.