Official course description, subject to change:
Preliminary info last published 16/06-22

Data-Driven Design & Development

Course info
Language:
English
ECTS points:
7.5
Course code:
KGDADDD1KU
Participants max:
75
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 Games
Staff
Course manager
Paolo Burelli
Associate Professor
Teacher
Miruna Vozaru
Part-time Lecturer
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

In this course, students learn how to work in data-driven design and development processes and what changes data analysis brings to the design and maintenance of games.

Description

Data analysis has become one of the driving forces of game design and development. This course teaches data analysis methods, and how they affect design and development. Students learn how user data is gathered, and how data analysis can be used in order to support the design and development of games and other interactive systems. They also learn how to develop, use, and analyse different game industry related metrics (e.g. customer metrics, community metrics, performance metrics, gameplay metrics) and how to use those to balance and optimise different aspects of games, informing the design process.

Formal prerequisites
The students need to have attended a introduction to programming course.
Intended learning outcomes

After the course, the student should be able to:

  • Describe the impact of data analysis on game design, production, and marketing.
  • Identify the stages of game design, production, and marketing in which analytics support decision making.
  • Classify the key performance indicators relevant in each of the design, production and post production stages.
  • Relate qualitative properties of the game experience with quantitative measures.
  • Outline and apply relevant statistical measures for testing and evaluation
  • Design tests and experiments, and evaluate their results in relation to the expected player experience.
  • Construct effective visualisations from collected metrics that can inform game design, production, and marketing.
  • Describe the challenges connected to the collection and analysis of large amount of in-game data.
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.