Description

Students will be introduced to a range of conceptual and technical tools for generating and visualizing data and analyzing complexity. Throughout the course students will experiment with different techniques for generating data and visualizing complexity. Based on case work, students will be learn to reflect on how visualizations work as simplifications and can inform decision-making.

Students will learn a variety of qualitative approaches to quantitative data, focusing on inductive, exploratory inquiry.

After the course, students will be capable of dealing with, communicating, and acting constructively in situations faced by complex challenges without straightforward solutions. The course will cover topics such as complexity thinking, storytelling with data, data and digital methods, situational analysis, problematization, data politics and technical tools for data-visualization and exploration.

Intended learning outcomes

After the course, the student should be able to:

  • Develop research questions that allow for exploratory and inductive inquiry into an empirical case through an iterative process of data collection, analysis, and storytelling.
  • Apply selected methods and conceptual tools to analyze complexity in an empirical case.
  • Interpret data visualizations generated using the technical and conceptual tools provided in the course.
  • Reflect upon the decisions made in the research process relating data visualizations to the development of the research question or focus.
  • Discuss the relationship between chosen methods, theories, and data, and their implications for the findings

Learning activities

14 weeks of teaching consisting of lectures, exercises and supervision. Each week students have 4 hours of lecture and 4 hours of exercises. During exercises students will be divided into groups of 40 working with TAs to practically engage with the exercises and topics of the week.

Literature

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Berinato, Scott. ‘Data Science and the Art of Persuasion’. Harvard Business Review, 1 January 2019. https://hbr.org/2019/01/data-science-and-the-art-of-persuasion.

Bigo, Didier, Engin Isin, and Evelyn Ruppert. ‘Data Politics’. edited by Didier Bigo, Engin Isin, and Evelyn Ruppert, 1 edition., 304. London ; New York: Routledge, 2019.

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Zuboff, Shoshana. The Age of Surveillance Capitalism: The Fight for a Human Future at the New Frontier of Power. 1 edition. New York: PublicAffairs, 2019.