Understand key concepts and current perspectives
Explain the main ideas, opportunities and limitations connected to AI ethics, fairness, privacy and governance.
Erasmus+ teacher training course
Ethical AI in Education and Society
What does ethical AI practice look like in everyday educational decisions?
Examine who benefits, who may be excluded and how human responsibility can remain central.
Target group: Teachers, adult educators, school leaders, public-service professionals and other education professionals from all educational levels.
- Activity type
- Physical mobility
- Duration
- 1 week
- Language
- English
- Equipment
- Laptop required
Ethical AI Decision-Making in Education and Society
Decisions about educational AI affect learners, educators, families and institutions. An AI system may save time or provide useful support, but it may also use personal data, repeat unfair patterns or make decisions that are difficult to explain. Ethical use therefore requires more than accepting a list of general principles.
Participants work with realistic cases, identify the people affected and compare the possible results of different choices. They examine bias, data use, transparency, responsibility and meaningful human control. The course encourages respectful discussion because ethical questions do not always have one perfect answer. Participants learn how to turn broad values into practical questions and safeguards.
Each participant develops a clear ethical decision-making guide and a realistic action plan for responsible AI use in their own classroom, team or educational organisation.
Learning outcomes
What You Will Learn
Analyse professional practice
Identify strengths, barriers and development priorities in relation to AI ethics, fairness, privacy and governance in a real educational context.
Use practical tools and methods
Apply ethical case analysis, policy reflection and safeguards through guided activities, collaborative tasks and structured reflection.
Design an adaptable learning response
Create a classroom, team or organisational activity that can be adapted to participants’ own learners and setting.
Use technology responsibly
Make informed choices about safety, inclusion, privacy and human oversight when using tools related to AI ethics, fairness, privacy and governance.
Six-day programme
Course Schedule
Day 1Digital starting points and responsible use
Welcome, needs mapping and course compass
Participants introduce their contexts, identify their goals and map current experiences connected to AI ethics, fairness, privacy and governance.
Shared vocabulary and key questions
Participants build a common language through short inputs, pair dialogue and a visual question wall.
Practice snapshot
Participants analyse a short case or example and identify what they would keep, question or change.
Day 2Exploring tools and evaluating value
Method gallery
Participants rotate through concise examples, models and tools connected to AI ethics, fairness, privacy and governance, recording practical possibilities.
Guided skill lab
Participants practise ethical case analysis, policy reflection and safeguards in small groups with trainer guidance and structured prompts.
Reflection and transfer notes
Participants capture what feels relevant, challenging or adaptable for their own learners and setting.
Day 3Hands-on creation and classroom application
Collaborative challenge
Small international groups work on an authentic challenge and apply selected tools in a purposeful task.
Create, test and revise
Participants develop a short activity, resource or approach, then improve it through testing and feedback.
Learning dialogue
Participants discuss different educational contexts and identify adaptations that make the work more realistic.
Day 4Safety, inclusion and critical judgement
Case clinic
Participants examine a complex scenario, identify assumptions and consider inclusive, responsible responses.
Perspective exchange
Participants use structured dialogue to explore different learner, colleague and community perspectives.
Practical safeguards
Participants identify boundaries, risks and support strategies relevant to AI ethics, fairness, privacy and governance.
Day 5Design studio and peer testing
Design your own application
Participants create a classroom, team or organisational plan using ethical case analysis, policy reflection and safeguards.
Peer feedback studio
Participants share work-in-progress, ask focused questions and receive practical feedback from colleagues.
Improve for implementation
Participants revise their design for feasibility, inclusion and clear evidence of learning.
Day 6Course Closure & Cultural Activities
- Reflecting on learning outcomes and key takeaways
- Awarding of Certificates of Attendance
- Cultural excursion and local heritage experience
- Informal networking and exchange of best practices
Course foundations
Recommended Reading and Theoretical Influences
- UNESCO (2021). Recommendation on the Ethics of AI.
- European Commission (2019). Ethics Guidelines for Trustworthy AI.
- European Commission (2024). AI Act.
- OECD (2019). AI Principles.
Completing the course
Evaluation, Recognition and Practical Information
Learning is supported throughout the week through participation, reflection, practical activities and constructive feedback.
Evaluation of Learning Outcomes
- Format
- Continuous assessment based on class participation, practical work and self-assessment.
- Criteria
- Active participation in discussions, reflection, collaborative activities and practical course tasks.
- Procedures
- Trainer observation, participant reflection, feedback and attendance.
Recognition of Learning Outcomes
- Conditions
- Attendance at a minimum of 80% of the course and active participation in the learning activities.
- Recognition
- Learning outcomes are recognised through participant reflection, trainer feedback and completion of the course activities.
- Documentation
- A Certificate of Attendance documenting the course title, dates, venue and learning outcomes.
Learning approach
Practical, Collaborative and Learner-Centred
The course combines hands-on workshops, real-world examples, simulations, guided reflection and collaborative activities. Participants exchange good practices, work in international groups and develop ideas that can be adapted to their own professional context.
Optional cultural, social and networking activities support local engagement, intercultural learning and professional collaboration.
Before you travel
Practical Details
Duration
One week, normally comprising 25 academic hours.
Weekly Schedule
Classes take place from Monday to Friday, in the morning or afternoon. Saturday is reserved for cultural activities.
Final Timetable
The detailed timetable will be sent at least two weeks before the beginning of the course.
Preparation
No special preparation is required unless stated in the course programme. Any required materials or equipment will be communicated before the course.
Certification
Participants who meet the attendance requirements receive a Certificate of Attendance.
Course Fee
The standard fee is €480. See what the course fee includes.
Alternative arrangements: Other course durations and schedules may be arranged on request.
Erasmus+ funding: Course fees and mobility costs may be supported through an eligible sending organisation's Erasmus+ grant. Eligibility and final funding decisions remain with the beneficiary organisation and its National Agency. Read our Erasmus+ KA1 funding guide.
Administrative support: Understanding Academy provides course programmes, learning outcomes, registration documentation and certificates. Participants and sending organisations remain responsible for transport, accommodation and grant management.
Plan your Erasmus+ mobility
Ready to Join This Course?
Check the upcoming confirmed dates or register your interest. We will contact you with information about availability and the next steps.
Need funding information? Read our Erasmus+ KA1 funding guide.