About this course
This course is aimed at higher education educators. It provides a structured introduction to the opportunities, challenges and implications of using generative artificial intelligence (GenAI) in teaching and learning at university level. Following the ADDIE model, you will engage with concepts, examples and practical activities designed to encourage critical reflection and responsible experimentation with GenAI. Throughout the course, the TaLAI Guy will help you navigate your learning journey and the Ethics and Knowledge Guys will prompt you to reflect on ethical, pedagogical and knowledge-related questions. Designed by a team of European educators and researchers, the course combines English-language content with multilingual summaries to facilitate transfer into various institutional contexts, helping you to develop the confidence, insight and informed judgement necessary for working with GenAI in your own practice.
Course structure, language, and accessibility
This course is structured according to the ADDIE (Analysis, Design, Development, Implementation, Evaluation) model. PDF summaries in German, French and Dutch accompany each section to support accessibility and transfer into local teaching contexts. As this is a European, multi-partner course, the core learning content is in English to provide a shared reference point across institutions, maintain consistency and minimise the risk of meaning shifts that can occur through translation, particularly with regard to rapidly evolving terminology in AI and higher education.
Curriculum
- The ADDIE model: what does the first D stand for?
- GenAI as a lesson plan developer
- Reflective exercise
- Written assignment in the age of GenAI: A profession at a crossroads
- Reflective exercise
- The importance of constructive alignment
- The importance of constructive alignment (visual)
- Constructive alignment paper
- GenAI & assessment
- Reflective exercise
- Around the world
- Take a moment to reflect
- The ADDIE model: What does the I stand for?
- The critical debate on autonomy, trust, ...
- Critical debate on AI in Higher Education: Embrace or resist?
- Reflective exercise
- GenAI as a debating partner
- Custom GPT
- Reflective exercise
- GenAI as a project partner
- Custom GPT
- Reflective exercise
- GenAI as a personal learning assistant
- Custom GPT
- Reflective exercise
- GenAI as a research assistant
- Custom GPT
- Reflective exercise
- GenAI as a lab assistant
- Custom GPT
- Reflective exercise
- Take a moment to reflect
- What is GenAI?
- Reflective exercise
- How do GenAI systems work?
- Knowledge exercise
- How do Large Language Models work?
- Knowledge exercise
- Ethical issues and limitations of GenAI
- Ethical issues with GenAI
- Reflective exercise
- Three rules of thumb for responsible use of GenAI
- Reflective exercise
- Legal and ethical foundations of responsible GenAI in higher education
- Reflective exercise
- Prompt engineering (text)
- Reflective exercise
- Prompt engineering (gamification)
- Running open source GenAI models locally
- Reflective exercise
- How to create your own locally run model
- GenAI detection tools and their (un)reliability
- Reflective exercise
- Ethically responsible use of GenAI in higher education
- Reflective exercise & checklist
- Raising awareness for the environmental and social impact of GenAI
- Reflective exercise
- Ethical decision making
- Technostress & implications of GenAI on cognitive development
- Reflective exercise
- Take a moment to reflect
ADDIE model
The course is structured around the ADDIE model, a systematic framework for instructional design that ensures strong alignment between learning objectives, activities, and assessments. It is organised into five stages - Analyse, Design, Develop, Implement, and Evaluate - each guiding educators through a different phase of course creation and delivery, from understanding learner needs to assessing outcomes. Throughout these stages, the course builds a coherent and engaging learning experience while also encouraging reflection on the ethical use of Generative AI in teaching.
Below you will find concise summaries of each section, along with translations into German, Dutch, and French to support accessibility and multilingual learning.
Project partners
