University of Otago

This is a project-centered course, in which students will choose and research a topic of their own choice (subject to approval), with the aim of producing a popularly-oriented non-fiction text which exhibits the fruits of sound scholarship. It examines the structures and strategies of a number of published texts, examining their structure and style, and the variety of sub-genres that can be deployed in writing creative non-fiction.

This course examines key ideas and concepts about the family, as well as looking at how issues like poverty and disability impact upon the family. This course will help students consider multiple perspectives on the family; engage in key debates about the family and its construction; and reflect on their own personal experiences and reactions to the family in all its forms in the broader structural contexts of Aotearoa/New Zealand society.

This course examines the scientific basis for, impacts of, and law and policy responses to climate change.

This course examines how social, political, cultural and material conditions shape scientific work and how science, in turn, shapes society. Because of the central role of science, technology and medicine in driving modern developments, understanding the relationships among science, technology and society is crucial for understanding the history of humanity and the contemporary world. 

This course examines how the concepts and techniques of chemical science can be used to gain an understanding of the synthesis, structure and reactivity of inorganic and organometallic molecules. It covers basic coordination chemistry emphasizing structure and bonding in coordination complexes, as well as an introduction to lanthanides and to symmetry in chemistry.

This course provides a study of the techniques used to prepare, integrate, manage, and visualize complex data using modern software environments. It introduces the fundamental concepts of data science through practical use of the industry-standard software environment R. It covers how to program in R, how to effectively manage and manipulate data in R, and the "round trip" of data science (import, tidy, transform, visualize, model, and communicate).