Universität Wien

053927 VU Applications of Emergent Technologies in the School Context (2026S)

3.00 ECTS (2.00 SWS), SPL 5 - Informatik und Wirtschaftsinformatik
Continuous assessment of course work
KPH-W-NÖ
Moodle

Registration/Deregistration

Note: The time of your registration within the registration period has no effect on the allocation of places (no first come, first served).

Details

max. 20 participants
Language: German

Lecturers

Classes (iCal) - next class is marked with N

  • Tuesday 03.03. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 10.03. 16:45 - 18:15 Digital
  • Tuesday 17.03. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 24.03. 16:45 - 18:15 Digital
  • Tuesday 14.04. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 21.04. 16:45 - 18:15 Digital
  • Tuesday 28.04. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 05.05. 16:45 - 18:15 Digital
  • Tuesday 12.05. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 19.05. 16:45 - 18:15 Digital
  • Tuesday 26.05. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 02.06. 16:45 - 18:15 Digital
  • Tuesday 09.06. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 16.06. 16:45 - 18:15 Digital
  • Tuesday 23.06. 16:45 - 18:15 Seminarraum 7, Währinger Straße 29 1.OG
  • Tuesday 30.06. 16:45 - 18:15 Digital

Information

Aims, contents and method of the course

Course objectives
Students will
• develop didactic strategies to convey the basic functioning of emerging technologies, especially AI systems, in an age-appropriate and understandable manner.
• plan learning processes that integrate technical, ethical and social perspectives and promote critical thinking and reflective skills.
• take cognitive, motivational and legal requirements into account in a targeted manner when planning lessons and justify their decisions from a technical and didactic perspective.
• select and use AI literacy models as a framework for orientation and derive competence-oriented learning objectives and task formats from them.
• Interpret current research findings on the use and impact of AI in a school context and transfer findings into teaching concepts.
• Address ethical dimensions such as bias, discrimination and educational equity in the classroom and design appropriate learning arrangements.

Course content
• Human-machine interaction and its influence on educational processes
• Legal framework in a school context
• Teaching technical basics and economic and ecological implications
• Models of AI literacy and didactic approaches
• Current research on the use and impact of AI in schools and teaching
• Teaching ethical dimensions in the classroom
• Didactic models for teaching

Course method
• Interactive lecture
Structured inputs with short activations, concept checks and mini analyses using examples from school and everyday life.
• Group work and case-based analysis
Work on realistic scenarios, analysis of teaching materials, evaluation of AI applications according to technical, legal and ethical criteria.
• Practical experimentation and didactic testing
Testing of selected tools and settings. Development of short learning sequences, scaffolds and task formats, including reflection and consolidation phases.
• Presentation and discussion
Short presentations of teaching modules, reasoned decisions, discussion of risks, limitations and prerequisites. Transfer to different school levels and learning groups.

Assessment and permitted materials

The course is completed by four compulsory assignments in the practical part and a written examination. The compulsory assignments serve to deepen the application-oriented understanding of the lecture content and aim at analysing, planning, testing and reflecting on didactic concepts for teaching emerging technologies, in particular AI. The exam tests the understanding of central concepts, models, legal and ethical aspects, as well as their transfer-oriented application.

Permitted aids
• For the compulsory assignments, course materials, personal notes and the specialist literature used in the course are permitted, as well as AI tools, depending on the assignment.
• Aids are only permitted for the exam if this is expressly announced. Otherwise, the exam is considered to be without aids.

Minimum requirements and assessment criteria

The following minimum requirements must be met in order to receive a positive assessment:
• Regular and active participation in lectures and exercises, in particular participation in work phases, tests and feedback sequences.
• Submission of all four compulsory assignments in full and on time.
• Participation in the written examination.

If one of the above minimum requirements is not met, the course cannot be successfully completed.

Distribution of points (100 points)
• Compulsory assignments total: 60 points
Compulsory assignment 1: 15 points
Compulsory assignment 2: 15 points
Compulsory assignment 3: 15 points
Compulsory assignment 4: 15 points
• Written examination: 40 points

Pass mark: at least 51 points in total; in addition, all minimum requirements must be met.

Grading scale
Very good: 91 to 100 points
Good: 81 to 90 points
Satisfactory: 66 to 80 points
Sufficient: 51 to 65 points
Insufficient: 0 to 50 points

Examination topics

The exam covers topics such as:
• Human-machine interaction and its consequences for educational processes.
• Age-appropriate teaching principles for the fundamentals of emerging technologies, limitations and typical misconceptions.
• Legal framework conditions in the school context and didactic consequences.
• Models of AI literacy and didactic implications.
• Research findings on the use and impact of AI in the school context and transfer to teaching decisions.
• Teaching ethical dimensions such as bias, discrimination and educational equity.
• Didactic models for teaching.

Reading list

Will be announced in the lecture and the accompanying moodle-course.

Association in the course directory

Last modified: Mo 27.07.2026 09:30