BIBV3040 Digital media and culture Emneplan

The course offers a case- and discussion-based approach to the current digital media landscape. In the course, we read and discuss academic articles and books on digital media and culture and debate critical issues in digital media, ranging from social media to streaming to theories of digitalization and data. The course has three parts: Culture and entertainment, Communication and power, and Digitalization and data. For each part, an introductory lecture will be given. An introductory lecture will also be provided. All other class activities are based on student participation. The instructor will provide cases for discussion. Students will, individually and in groups, be tasked with presenting and discussing texts from the curriculum.

Case discussions will deal critically with issues such as the political impact of social media, the sustainability of streaming services, the power of digital communication platforms, datafication and the power of metrics, and the characteristics of digitalization.

The teaching language is in English

An essay of 8-10 pages must be written in connection with the course. The essay shall take the candidate's project as its point of departure and be related to the course content. The essay must be handed in for assessment by the teacher responsible for the course no later than two months after the end of the course. A passed essay is a precondition for being awarded the 5 ECTS credits. If the essay is awarded a fail grade, the candidate can submit a revised essay once, by a specified deadline.

No formal requirements over and above the admission requirements.

Upon successful completion of the course:

Knowledge

• Students will gain valuable insights into why, when and how to use AI methods in realistic problems that they may encounter in their technical careers, as well as the necessary expertise to produce necessary documentation and project management.

Skills

• The students learn to work in a large group with a vaguely defined problem statement.
• The students learn to assess different frameworks and tools for artificial intelligence in given contexts.
• The students will build systems that realises aspects of intelligent behaviour.
• The students will gain hands-on experience designing and implementing a relatively large AI project.
• The students learn debugging their applications and bug correction at a system level (integration).

General competence

• The students learn to work in a project within their specific expertise. This includes making decisions based on limited information, tolerating these decisions when they turn out to be suboptimal and evaluating them when better information becomes available.

The project work will be carried out in groups of a size suited for the assignment and focused around the relevant laboratories at OsloMet. The groups are relatively large, with 5-20 students.

The essay will be graded by the course lectures.

Project report (between 10000 and 25000 words) (100%)

The exam grade can be appealed.

New/postponed exam

In case of failed exam or legal absence, the student may apply for a new or postponed exam. New or postponed exams are offered within a reasonable time span following the regular exam. The student is responsible for applying for a new/postponed exam within the time limits set by OsloMet. The Regulations for new or postponed examinations are available in Regulations relating to studies and examinations at OsloMet.

For the final assessment a grading scale from A to E is used, where A denotes the highest and E the lowest pass grade, and F denotes a fail.

Two internal examiners. External examiner is used periodically.