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Artificial Intelligence in Education
Last Updated: 2026-02-05 15:48:25
Abstract
Artificial Intelligence (AI) methods have shown to have a profound impact in educational technologies, where the great variety of tasks and data types enable us to get benefit of AI techniques in many different ways. We will review relevant methods and applications of AI in various educational technologies, and work on problem sets and projects to solve problems in education with the help of AI.
Objective
The course will be centered around exploring methodological and system-focused perspectives on designing AI systems for education and analyzing educational data using AI methods. Students will be expected to a) engage in presentations and active in-class discussion, b) work on problem-sets exemplifying the use of educational data mining techniques, and c) undertake a final course project with feedback from instructors.
Content
The course will start with a general introduction to AI, where we will cover supervised and unsupervised learning techniques (e.g.,classification and regression models, feature selection and preprocessing of data, clustering, dimensionality reduction and text mining techniques) with a focus on application of these techniques in educational data mining. After the introduction of the basic methodologies, we will continue with the most relevant applications of AI in educational technologies (e.g., intelligent tutoring and student personalization, scaffolding open-ended discovery learning, socially-aware AI and learning at scale with AI systems). In the final part of the course, we will cover challenges associated with using AI in student facing settings.
Resources
Lecture Notes
Lecture slides will be made available at the course Web site.
Literature
No textbook is required, but there will be regularly assigned readings from research literature, linked to the course website.
Learning Materials (Links)
- Main link
- Information
General Information
- Language
- English
- Levels
- MSC , WBZ
- Frequency
- Yearly recurring
Examination
- Type
- graded semester performance
Registration & Places
- Max Places
- 60
Course Components
| Type | Title | Time & Place | Hours |
|---|---|---|---|
| lecture |
Artificial Intelligence in Education
Online lecture: This lecture will take place online. Reserved rooms will remain blocked on campus for students to follow the course from there.
|
|
2 h weekly |
| exercise |
Artificial Intelligence in Education
Online exercises: Will primarily take place online. Reserved rooms will remain blocked on campus for students to follow the exercises from there.
|
|
1 h weekly |
| independent project | Artificial Intelligence in Education | No time listed | 1 h weekly |