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263-5005-00L 5 Credits MSC , WBZ D-ITET , D-INFK , D-MATH
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Artificial Intelligence in Education

Number of participants limited to 75.
VVZ CR 5.0

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)

General Information

Language
English
Levels
MSC , WBZ
Frequency
Yearly recurring

Examination

Type
graded semester performance
The final assessment will be a combination of classroom participation, paper presentations, problem sets and the project.

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.
  • Thu 16:15-18:00 (RZ F 21)
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.
  • Thu 18:15-19:00 (RZ F 21)
1 h weekly
independent project Artificial Intelligence in Education No time listed 1 h weekly

Offered In