Official course description, subject to change:

Basic info last published 15/03-24
Course info
ECTS points:
Course code:
Participants max:
Offered to guest students:
Offered to exchange students:
Offered as a single subject:
Price for EU/EEA citizens (Single Subject):
21250 DKK
MSc. Master
MSc in Digital Innovation & Management
Course manager
Associate Professor
Associate Professor
Part-time Lecturer
Assistant Professor
Course semester
Efterår 2024
26 August 2024
24 January 2025

The course will teach students to analyse complexity within an empirical case that explores a current topic or controversy within the field of science, technology, and innovation.


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.

Formal prerequisites
Please note that this course is targeted at students enrolled in the programme Digital Innovation & Management. Moreover the student must always meet the admission requirements of the IT University.
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.
Ordinary exam
Exam type:
D: Submission of written work with following oral, External (7-point scale)
Exam variation:
D2G: Submission for groups with following oral exam supplemented by the submission. Shared responsibility for the report.