Good results with AI tools depend less on the model than on the question you put to it. prompting.schule teaches exactly that — in modular self-study courses, freely available as open educational resources.
The courses are published as open educational resources (OER) under CC BY 4.0 (external site) and can be used free of charge. They are modular: learners set their own pace and timing, and decide for themselves how deep to go into a topic.
Who the courses are for
No prior knowledge is required. The courses address:
- newcomers with no prior experience of AI tools
- students
- working professionals who want to integrate AI into their day-to-day tasks
- teachers
The foundations course
The foundations course comprises four lessons and can be completed in roughly four times 60 minutes. The strategies it teaches draw on recommendations from OpenAI and UNESCO as well as on the research literature.
- writing clear, unambiguous instructions
- supplying reference texts and examples to raise the quality of answers
- splitting complex tasks into comprehensible steps
- formulating prompts so that the model reasons step by step
Alongside explanations and examples, every lesson contains exercises in which learners send their own prompts straight to a language model — the difference between an imprecise and a considered formulation becomes visible in their own result. Each lesson ends with a quiz; passing it earns a digital badge.
Start a course
The courses are free of charge; tracking progress and earning badges requires signing in.
A dedicated course for TU Graz staff
The course “Foundations at TU Graz” was developed in close cooperation between Human Resources Development and the Educational Technology unit, and is tailored to the requirements and fields of work of TU Graz general staff. Staff sign in with their TU Graz account rather than a separate password.
Course for TU Graz staff
For TU Graz staff only. Sign-in works through single sign-on with your TU Graz account.
Further links
- Open the platform (external site)
- Sign-in for TU Graz staff (SSO) (external site) TU Graz staff
- Source code on GitHub (external site)
Joint projects
- Future Learning
- AI for Teaching
- Analytics
A joint doctoral programme of TU Graz and the University College of Teacher Education Styria: what can digital education in computer science look like today and in the future?
Publications
-
Prompting.School: A Design-Based Research Approach to Teaching AI Literacy Through Guided Prompt Engineering Practice
Conference paper · Innovation via Collaborative Learning in Engineering Education. ICL 2025. Lecture Notes in Networks and Systems, Vol. 1848
The logos of the partners and the projects are protected by copyright and trademark law and are excluded from this site’s CC BY licence. They appear here solely to identify the cooperation; all rights remain with the respective organisations.