KIUA2015 AI in education
- Course codeKIUA2015
- Number of credits10
- Teaching semester2026 Autumn
- Language of instructionNorwegian/English
- CampusHamar
- Required prerequisite knowledge
None
AI-driven pedagogy and education and learning methodologies are rapidly evolving. Algorithms, large language models and machine learning are challenging traditional working and learning methods. This course will prepare students to work with and evaluate AI-driven tools in education and reflect on the impacts on teaching and learning. Key issues include:
- Personalised learning using AI: How can AI tools help tailor teaching to meet the individual needs of students and optimise learning?
- Ethical implications: ethical implications such as privacy, security and systematic bias in AI-based learning tools
- AI in writing, reading and language learning
- AI as a tool for planning and preparation in education
- Knowledge production using generative AI
Learning Outcome
Upon successfully passing the course, students will have achieved the following learning outcomes:
The student will have
- incipient understanding of the underlying principles of artificial intelligence (AI), algorithms and machine learning
- in-depth knowledge of current practices, opportunities and challenges linked to the use of AI in schools and other educational contexts
- knowledge of the historic use of AI in general and in education specifically
The student will be able to
- independently experiment with and evaluate different AI-driven tools in an educational context
- apply theoretical perspectives from the field of education to evaluate and analyse possible consequences of machine learning and large language models in many different educational contexts
- evaluate and discuss ethical and legal issues, such as security and privacy in the educational use of AI
- argue in favour of how AI can be integrated in teaching in ways that promote learning
- critically analyse potential impacts of AI-driven automation on human relations in a broad range of educational contexts
The student will be able to
- independently use and discuss current AI-driven tools in a broad range of educational contexts
- communicate coherently, clearly and understandably on issues linked to the use of artificial intelligence in education
- think critically about the use of AI in education and schools
Working methods will include lectures, seminars, group work, student presentations, independent study and written assignments. The Canvas communication platform will be used in teaching, as well as a broad range of digital platforms and programs, specifically programs based on machine learning and large language models.
- attendance of at least 80% and active participation in teaching
- a task completed using AI/ML tools and
- an oral presentation on a relevant topic of the student’s own choosing
Coursework requirements have been specified in the course curriculum.
Compulsory assignments can be executed and written in Norwegian Bokmål, Nynorsk or English.
| Form of assessment | Grading scale | Grouping | Duration of assessment | Support materials | Proportion | Comment |
|---|---|---|---|---|---|---|
Home exam | ECTS - A-F | 3 Day(s) | 100 |
- written home examination over three days.
Performance is assessed using a grading scale from A to F, where E is the lowest passing grade.
Students are able to choose which language to use for their examination. The available options are Norwegian Bokmål, Nynorsk and English.
Permitted aids:
- Literature
- All printed and written resources
- AI-generated text and content must be clearly labelled and academically justified.