Description

The complex challenges of digitalisation often demand the professional use of both qualitative methods and data-exploration to diagnose issues and to act upon them.

In Navigating Complexity, students will be introduced to a range of conceptual and technical tools for generating and visualizing data and analysing complexity. Throughout the course students will experiment with different techniques for generating data and visualising complexity. Based on case work, students will be learn to reflect on how visualisations 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, problematisation, data politics and technical tools for data visualisation 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 the data and the visualizations generated using the technical and conceptual tools provided in the course.
  • Reflect upon the decisions made in the research process relating the data and the visualizations to the development of the research question or focus.
  • Discuss the relationship between chosen methods, theories, data, and their implications for the findings in a concise manner.

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. Lectures will likely be divided into 2 hour sessions: one auditorium lecture and one online interactive lecture. The auditorium lecture introduces the theme of the week’s content and relates closely to the week’s readings and written submissions. The online interactive lecture takes the form of ‘Navcom Radio’, a two hour live program where teaching staff are in conversation about how the themes and theories of Navigating Complexity can be put into practice.

During exercises students will be divided into groups of approximately 40 working with TAs to practically engage with the exercises and topics of the week.

Literature

Week 02

  • Bryman 2021 - Interviewing in qualitative research
  • Michael 2004 - On making data social

Week 03

  • Hammersley and Atkinson 2007 - Field relations (Ethnography chapter 4)
  • Erikson 2019 - Global Health Futures

Week 04

  • Venturini and Munk 2021 - Collecting and curating digital records
  • Marres 2017 - Are we researching society or technology?

Week 05

  • Cho and Lee 2014 - Reducing confusion about grounded theory and qualitative content analysis
  • Allen 2018 - Why exchange values are not environmental values

Week 06

  • Mills 2004 - Discourse (Introduction)
  • Willig 2008 - Foucauldian discourse analysis (Chapter 7 excerpts)

Week 10

  • Hacking 1990 - The taming of chance (chapter 1)
  • Marquardt 2016 - Counting the countless

Week 11

  • Wood 2010 - Rethinking the power of maps (chapter 2)
  • Correll 2018 - Ethical dimensions of visualization research

Week 12

  • Kjær Ojala Henriksen 2021 - Absent data
  • Haraway 1988 - situated knowledges

Week 13

  • D’Ignazio and Klein 2020 - Why data science needs feminism
  • D’Ignazio 2015 - What would feminist data visualization look like?