Status message

The course description for the semester you wanted is not published yet. Showing you instead the latest version available.

SKDK4006 Perspectives on Artificial Intelligence

    • Course code
      SKDK4006
    • Number of credits
      10
    • Teaching semester
      2026 Spring
    • Language of instruction
      Norwegian/English
    • Campus
      Hamar
    • Required prerequisite knowledge

      None.

Course content

The course will look at the field of artificial intelligence from different cultural, historical, philosophical, political, didactic and ethical perspectives. Students will immerse themselves in current critical debates on the use of artificial intelligence in a wide array of social arenas, such as bureaucracy, school, medicine, and economy. The course will thematize the use, history and societal impact of artificial intelligence, as well as give an introduction to the practical aspects of machine learning, algorithmic thinking and natural language processing. The course will be grounded in a critical perspective from the humanities and social sciences.  

Other important concepts we will be working with include:

  • legitimacy
  • transparency
  • democracy
  • privacy
  • the nature of work
  • the nature of consciousness
  • algorithmic bias

Learning Outcome

A candidate who has completed the course has the following total learning outcomes, defined by knowledge, skills and general competence: 

Knowledge

Students

  • have a conceptual understanding of AI and ML technologies
  • have an in-depth knowledge of the history and present use of artificial intelligence and machine learning within diverse fields
  • have knowledge of the possibilities and challenges of the use of AI in diverse fields
  • have an understanding of the resources used and created by artificial intelligence
Skills

Students

  • can reflect on the challenges and possibilities of the use of artificial intelligence in diverse fields
  • can use theoretical perspectives from the humanities and social sciences to analyze the use of machine learning in different fields
  • can describe and differentiate key concepts of AI, critically evaluate its applications in educational settings, and reflect on its ethical, societal, and pedagogical implications through discussion and oral presentations
General competence

Students

  • can think critically about the key ethical issues inherent in the use of artificial intelligence
  • can write coherently and lucidly about issues pertaining to artificial intelligence
Teaching and working methods

Working methods will include lectures, seminars, group work, student presentations, self-study, written assignments. Online learning platforms will be used in teaching, as well as a range of digital platforms and programs, specifically programs based on machine learning and large language models.

All courses are subject to evaluation. The time, date and method of this evaluation is decided by the course coordinator in consultation with student representatives. The course coordinator is responsible for ensuring that the evaluation is carried out.

Required coursework

Attendance of minimum 75% and participation in class is mandatory. In order to take the exam, two individual obligatory assignments must be approved:

  • one assignment created using AI/ML tools, and
  • one oral presentation on a course-relevant topic of the student’s own choosing.

The obligatory assignments can be performed and written in either English or one of the two written forms of Norwegian.

Assessments
Form of assessmentGrading scaleGroupingDuration of assessmentSupport materialsProportionComment
Home exam
ECTS - A-F
Individual
3 Day(s)
100
Form of assessment

The examination with be an individual written home exam with a duration of three days. Performance is assessed using a grading scale from A-F, where E is the lowest passing grade.  The language of the exam is either English or one of the two written forms of Norwegian.

Permitted examination support material

  • Syllabus literature
  • All printed and written resources
  • Generated text and content is to be clearly marked and academically justified 
Faculty
Faculty of Education
Area of study
Programmer som ikke passer i noen av de nevnte kategoriene ovenfor
Programme of study
Master's Degree in Digital Communication and Culture
Course level
Second degree level (500-HN)