Official course description, subject to change:
Preliminary info last published 15/11-21

Critical Data Analysis

Course info
Language:
English
ECTS points:
7.5
Course code:
KAKRDAT1KU
Participants max:
40
Offered to guest students:
yes
Offered to exchange students:
yes
Offered as a single subject:
yes
Price for EU/EEA citizens (Single Subject):
10625 DKK
Programme
Level:
MSc. Master
Programme:
MSc in Digital Design and Interactive Technologies
Staff
Course manager
Associate Professor
Teacher
Assistant Professor
Course semester
Semester
Forår 2023
Start
30 January 2023
End
25 August 2023
Exam
Exam type
ordinær
Internal/External
ekstern censur
Grade Scale
7-trinsskala
Exam Language
GB
Abstract
This course focuses on the analysis and production of data. Students gain an overview of data-driven design work and critical thinking about the use of data, and the challenges and opportunities that data brings to the design of interactive systems. They will be introduced to technical concepts in data production and data analysis, and reflect on these from an ethical, social and cultural perspective. Doing so, the course bridges technical and human perspectives in data-driven design.
Description

Data analysis has become one of the driving forces of digital design. This course teaches data analysis methods and tools, and how they affect the design of interactive systems. Students learn how to produce and analyse data, to reflect on the role of data in design  and how data in a productive way can support the design of interactive systems. The course will introduce students to all aspects of data-driven design cycles, including collecting data, analysing data, and creating data-informed designs or re-designs, while being aware of the ethical, legal and cultural challenges in the production and use of data.

Formal prerequisites
Intended learning outcomes

After the course, the student should be able to:

  • The student should be able to describe and reflect on insights from course literature in a critical assessment of the data gathered either by the students or in cases discussed in class
  • The students should be able to hypothesise what data will show and critically evaluate these hypotheses based on actual findings in their data analysis
  • The students should be able to reflect on the relation between tools used for data collection and the quality of the data gathered, including ethical issues and protection of personal data
  • The students should be able to apply the appropriate statistical tools to analysis the data collected
  • The students should be able to identify the data necessary to describe the desired user behaviour
Ordinary exam
Exam type:
B: Oral exam, External (7-point scale)
Exam variation:
B22: Oral exam with no time for preparation.