Syllabus
Course structure
Introduction to Artificial Intelligence
Definition and basics of artificial intelligence: what is artificial intelligence? Difference between weak and strong AI.Historical development.
Programs and tools of artificial intelligence.
Text generation and processing: OpenAI GPT, Google Bard.Language processing and analysis: Grammarly, Ludwig, DeepL.Image generation and analysis: DALL-E, Canva, Adobe Spark.Learning Management Systems (LMS): Moodle with AI plugins, Google Classroom with AI extensions.Chatbots and virtual assistants: ChatGPT, Replika
Artificial Intelligence Applications in Education
Language exercises and games: Creating interactive language games and exercises with AI.Text creation and analysis: Using AI tools to create and analyse texts.Personalised learning: tailoring learning content to individual student needs.Feedback and assessment: automated assessment of assignments and exams.Interactive teaching: Use of chatbots for interactive question and answer sessions.
Ethics and data protection
Ethical considerations in the use of artificial intelligence: discrimination, bias, transparency.Data protection and security: How is data protected? Guidelines for data protection in schools.
Practical exercises and projects
Group work: Creating lesson plans incorporating artificial intelligence.Individual assignments: Creating and analysing teaching materials created using artificial intelligence.Presentation.Examples of the use of AI in German lessons*** Translated with www.DeepL.com/Translator (free version) ***
Annotation
The course introduces students to the possibilities and pitfalls of using artificial intelligence in teaching. It is intended for students of teaching, i.e. especially future teachers of German or foreign languages.
The course is based on the sharing of experiences, the willingness to experiment with artificial intelligence and the open-mindedness of the learners, who co-create the content and make a major contribution to the seminars.
