Official course description:
Full 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
Associate Professor
Teaching Assistant
Teaching Assistant (External)
Course Academic Responsible
Assistant Professor
Course semester
Semester
Forår 2022
Start
31 January 2022
End
31 August 2022
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
Learning activities

  • short in-class excersises related to the topic of day
  • group work with either own or pre-selected data samples
  • practising data collection methods and tools in exercise sessions

Mandatory activities

There will be two mandatory activities during the semester:

  1. In the first hand-in, the students will write a short 2-4 pages report with an analysis of the user experience extracted from a dataset provided by the teachers (or proposed by the students).
  2. The second hand-in will consist of a short written paper 2-3 pages in which students critically reflect on their data collection process and on what the data shows them, drawing on insights from course literature.

The student will receive the grade NA (not approved) at the ordinary exam, if the mandatory activities are not approved and the student will use an exam attempt.

Course literature

There will no basic book(s) for this course. We will instead use up-to-date relevant research articles in the field and select book chapters which will be made available on LearnIT when the course starts.

Student Activity Budget
Estimated distribution of learning activities for the typical student
  • Preparation for lectures and exercises: 20%
  • Lectures: 20%
  • Exercises: 20%
  • Assignments: 20%
  • Exam with preparation: 20%
Ordinary exam
Exam type:
B: Oral exam, External (7-point scale)
Exam variation:
B22: Oral exam with no time for preparation.
Exam duration per student for the oral exam:
20 minutes

Time and date
Ordinary Exam Mon, 13 Jun 2022, 09:00 - 21:00
Ordinary Exam Tue, 14 Jun 2022, 09:00 - 21:00
Ordinary Exam Wed, 15 Jun 2022, 09:00 - 21:00
Reexam Fri, 19 Aug 2022, 09:00 - 21:00