Study Guide

Objectives

After the course, students can
- critically evaluate the role, opportunities, and pitfalls of automated data collection and analytics in content creation and audience research
- understand how recommendation systems work and how they are applied
- compare and point out prominent data technologies in content creation
- develop content concepts that utilize data technologies

Content

During the course, the participants study the basic concepts and processes of data analysis and information visualization. They critically analyze and experiment with the role, opportunities, and pitfalls of data technologies in content creation and audience research. They examine how automated data collection and user analytics impact on content creation. They explore how emerging data technologies, such as machine learning (ML) and artificial intelligence (AI), are used in content creation. As a synthesis of the exploration, students create and demonstrate an art and media concept that utilizes or reflects data technologies.

Topics
- Data analytics and information visualization
- Ethics of data analytics
- Audience metrics and content creation
- Machine learning and artificial intelligence
- Recommendation systems
- Personalization of services
- Emerging data technologies and content creation

Assessment criteria, satisfactory (1-2)

The student defines the basic concepts related to data analysis and discusses the ethics of data analysis. S/he describes different ways data analysis influences content creation in her/his working field. S/he knows the common means of data analysis related to content creation and applies at least one of them in a practical case. S/he demonstrates ideas for applications that integrate content and data analysis. The student takes responsibility for her/his work.

Assessment criteria, good (3-4)

The student knows the basic concepts of data. S/he critically analyzes and provides various examples of how data analysis influences content creation in her/his field – now and in the future. S/he critically discusses the ethics of data analysis. S/he demonstrates creative ideas for applications that integrate content and data analysis. The student develops committedly her/his knowledge and skills in emerging media.

Assessment criteria, excellent (5)

The student critically analyzes and provides alternative scenarios of how data analysis influences content creation in her/his field – now and in the future. S/he compares the situation across different industrial sectors and points out inter-dependencies and connections between them. S/he demonstrates creative and attractive ideas for applications that integrate content and data analysis.The student demonstrates excellent and open-minded attitude to her/his work, as well as towards fellow students’ knowledge and skills.

Assessment criteria, pass/fail

The student critically analyzes and provides alternative scenarios of how data analysis influences content creation in her/his field – now and in the future. S/he critically discusses the ethics of data analysis. S/he compares the situation across different industrial sectors and points out inter-dependencies and connections between them. S/he demonstrates creative and attractive ideas for applications that integrate content and data analysis. The student demonstrates an excellent and open-minded attitude to her/his work, as well as towards fellow students’ knowledge and skills.