Basic ICT required.Read more
Basic computer proficiency courses are designed for individuals who have limited experience with technology. Participants will learn fundamental skills such as navigating the web, and using basic programs.
Targeted to Intermediate English (B1+) speakers.Read more
This is the standard requirement for most courses. Participants at this level can participate actively in discussions and manage everyday and professional situations. If they are unsure about their English level, they can test it here or explore our courses facilitated in Basic English.
Higher Education Staff.Read more
The listed audiences are those for whom the course is especially recommended, but courses are not exclusive to them and are open to everyone. In fact, most of our workshops are built around the collective sharing of participants’ experiences and having a variety of profiles enriches the learning process and is highly encouraged!
Description
Most teaching staff and lecturers have stopped asking whether AI belongs in education.
They are now asking a harder question: who does what?
Banning it pretends the world has not changed. Handing everything over to it hollows out the teaching.
Between those two mistakes sits the thoughtful educator, who wants neither, and who has no clear way to decide where to lead and where to let AI help.
This course introduces a practical model for teaching that is human-led and AI-supported, so that educators stay in charge of the decisions that matter while AI carries out the work it genuinely does well.
It is built for people who are neither afraid of AI nor dazzled by it, and who want a considered way to make the partnership work.
During the course, participants will map the parts of their teaching that must stay human, find the places where AI can genuinely support them, and apply a simple method for deciding, task by task, who leads.
They will rebuild one of their own courses around a deliberate human and AI partnership, learn how to show students the difference between using AI and outsourcing their thinking to it, and prepare to explain the approach openly to students, colleagues, and their institution.
By the end of the course, participants will be able to decide with confidence where they lead and where AI assists, design teaching in which that partnership is deliberate rather than accidental, and keep human judgement at the centre of their practice.
They will leave with one of their own courses rebuilt around a clear, defensible partnership they can put to use straight away.
What is included
Learning outcomes
The course will help participants to:
- Understand the principle of human-led, AI-supported teaching, and why a partnership works better than banning AI or surrendering to it;
- Identify the parts of teaching that must stay human, such as judgment, relationship, motivation, and care;
- Recognize where AI can genuinely support their work, and apply a human check to everything it produces;
- Apply a practical method for deciding, task by task, what is human-led and what is AI-supported;
- Design a lesson or unit in which the handover between lecturers and AI is deliberate and transparent;
- Help students work with AI without outsourcing their own thinking;
- Explain their approach to AI clearly to students, colleagues, and their institution.
Tentative schedule
Day 1 – Introduction to the course
- Introduction to the course, the school, and the external week activities;
- Icebreaker activities;
- Presentations of the participants’ schools.
The partnership question
- What human-led, AI-supported teaching means in practice;
- The co-intelligence idea: AI as the assistant, the educator as the one who decides;
- The two ways teaching goes wrong: banning AI, and surrendering to it;
Day 2 – What only humans should do
- Mapping the parts of teaching that must stay human: judgement, relationship, motivation, and care;
- Why quietly handing these to AI weakens both teaching and learning;
- Spotting automation creep and drawing your own lines;
- Auditing your chosen course for what must remain yours.
Day 3 – What AI can genuinely support
- The work AI can take on: preparation, drafting, adapting, and generating options;
- Keeping a human check on what it produces: accuracy, bias, and fit;
- Using AI to free time for the human work that matters most;
- Mapping AI support into your course on purpose, not by default.
Day 4 – Designing the partnership
- A simple method for deciding, task by task, what is human-led and what is AI-supported;
- Designing a unit where the handover between lecturers and AI is intentional;
- Showing students how to work with AI without offloading their thinking;
- Building your own partnership plan.
Day 5 – Making it work, and keeping it honest
- Being open with students and colleagues about how and when AI is used;
- Ethics and equity: access, bias, and who risks being left behind;
- Talking about AI in a way that reassures the cautious and steadies the enthusiastic;
- Finalize your plan and a one-page summary for your department.
Day 6 – Course closure and cultural activities
- Course evaluation: round-up of acquired competences, feedback, and discussion;
- Awarding of the course Certificate of Attendance;
- Excursion and other external cultural activities.
This course uses AI tools as part of the learning experience and may include a dedicated session on GDPR compliance and responsible data use, depending on participants’ interests.
Participants are encouraged to verify that the use of AI tools is permitted under their national regulations and institutional policies before registering.
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