Erasmus+ teacher training course

Ethical AI in Education and Society

Illustration representing ethical artificial intelligence and human responsibility

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

This professional development course helps participants explore AI ethics, fairness, privacy and governance through hands-on, pedagogy-led practice. It balances experimentation with critical reflection, so digital choices remain purposeful, inclusive and guided by professional judgement.

By the end of the week, each participant will have developed a practical next-step plan using ethical case analysis, policy reflection and safeguards. The focus is not on one fixed method, but on thoughtful adaptation: choosing approaches that fit learners, colleagues, curriculum and local realities.

International education professionals discussing ideas during a classroom workshop
Ethical practice develops through dialogue, careful questions and accountable decisions.

What You Will Learn

Outcome 1

Understand key concepts and current perspectives

Explain the main ideas, opportunities and limitations connected to AI ethics, fairness, privacy and governance.

Outcome 2

Analyse professional practice

Identify strengths, barriers and development priorities in relation to AI ethics, fairness, privacy and governance in a real educational context.

Outcome 3

Use practical tools and methods

Apply ethical case analysis, policy reflection and safeguards through guided activities, collaborative tasks and structured reflection.

Outcome 4

Design an adaptable learning response

Create a classroom, team or organisational activity that can be adapted to participants’ own learners and setting.

Outcome 5

Use technology responsibly

Make informed choices about safety, inclusion, privacy and human oversight when using tools related to AI ethics, fairness, privacy and governance.


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

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.

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.

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.

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.

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.