Official course description, subject to change:
Basic info last published 29/10-19

Data-Driven Design & Development

Course info
Language:
English
ECTS points:
7.5
Course code:
KGDADDD1KU
Participants min:
1
Participants max:
75
Offered to guest students:
yes
Offered as a single subject:
yes
Price (single subject):
10625 DKK (incl. vat)
Programme
Level:
MSc. Master
Programme:
Master of Science in Information Technology (Games)
Staff
Course manager
Assistant Professor
Teacher
PhD student
Course semester
Semester
Forår 2020
Start
27 January 2020
End
31 August 2020
Abbreviation
20201
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.

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 experiment and evaluate their results in relation to the game design and development
  • 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-trinsskala)
Exam variation:
D22: Submission of written work with following oral exam supplemented by the work submitted.