Official course description:

Full info last published 24/09-19
Course info
Language:
English
ECTS points:
7.5
Course code:
KGDADDD1KU
Offered to guest students:
-
Offered to exchange students:
Offered as a single subject:
-
Programme
Level:
MSc. Master
Programme:
M.Sc. in IT, Games
Staff
Course semester
Semester
Forår 2019
Start
28 January 2019
End
31 May 2019
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 science 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 to gather user data, and how data analysis can be used in order to support the design and development of games and other interactive systems. In this course, students learn about game architectures for data-driven games, design implications and how to employ data-driven techniques in various areas of game development. They also learn how to develop, use, and analyse different game analytics (customer metrics, community metrics, performance metrics, gameplay metrics) and using those to balance and optimize different aspects of games, informing the design process.

Formal prerequisites
.
Intended learning outcomes

After the course, the student should be able to:

  • Describe the impact of data analytics 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.
  • Outline testing and evaluation procedures and relevant statistical measures.
  • Relate qualitative properties of the game experience with quantitative measures.
  • Evaluate analytics solutions in relation to development in business needs.
  • Describe the challenges connected to the collection and analysis of large amount of in-game data.
  • Construct effective visualisations, from collected metrics, that can inform game design, production, and marketing.
Learning activities

Students are responsible for attending weekly lectures, participating in the group activities and engaging withe the teaching staff for supervision and feedback.

Mandatory activities
Der er ingen obligatoriske aktiviteter. Vær venlig KUN at ændre denne tekst når der er obligatoriske aktiviteter./ There are no mandatory activities. Please, change this text ONLY when there are mandatory activities.

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

The course literature is published in the course page in LearnIT.

Ordinary exam
Exam type:
D: Submission of written work with following oral, external (7-trinsskala)
Exam description:
The hand-in will be a collection of 5 written reports. Each of the assignment will cover a specific topic presented during the course, allowing the students to put the theory into practice and specialise within the broader scope of the course on either the design or technological aspects of the course. During the oral exam the students will be asked to discuss one or more assignments and other course topics. The length of the oral exam will be 20 minutes, including deliberation and feedback.