Associazione Eduimpact Italy

Topic / Theme

Integrating Artificial Intelligence into teaching and learning to enhance personalisation, efficiency, collaboration and student engagement, while ensuring ethical, responsible and inclusive use aligned with teachers’ digital competences.

Sending partners

Educational organisations involved in formal, non-formal and informal learning: kindergartens, schools, VET providers, adult education centres, training organisations, resource centres, NGOs and other institutions active in the education and adult learning field, established in Erasmus+ programme countries.

Participants

20–25 adults involved in education.

Course fee

According to the Erasmus+ Programme Guide: 80 EUR per participant per training day, including course preparation, training delivery, training materials, organisational and administrative costs, and 24-hour emergency support during the mobility.

Languages used

Working language: English.
Training materials are provided in English. Upon request, support or materials may be available in Spanish or French, depending on the group composition.

Profile of the participants

The course is designed for teachers, school staff and adult trainers working in the sending organisation who are interested in integrating Artificial Intelligence into their educational practice.

Participants:

  • Work with learners of different ages, abilities or educational contexts
  • May have basic or intermediate digital skills; no advanced technical background is required
  • Are interested in improving teaching efficiency, personalisation and student engagement through AI
  • Are willing to actively participate in hands-on exploration, experimentation and collaborative tasks
  • Are open to intercultural learning and exchange of practices
  • Are motivated to implement AI-supported strategies and to engage in preparatory and follow-up activities
  • Aim to strengthen the European dimension of their institution through digital innovation and responsible technology use

Objectives

  • Understand key concepts and current applications of Artificial Intelligence in education
  • Explore practical AI tools for lesson planning, content creation and classroom support
  • Use AI to personalise learning and support diverse student needs
  • Improve assessment and feedback processes through AI-assisted solutions
  • Develop awareness of ethical issues such as bias, data protection and responsible use
  • Strengthen teachers’ digital competences in line with DigCompEdu
  • Design and plan the implementation of AI-enhanced learning activities

Learning outcomes

By the end of the course, participants will be able to:

  • Explain basic AI concepts and their relevance for education
  • Select and use appropriate AI tools for teaching, content development and classroom management
  • Design AI-supported learning activities adapted to different learner needs
  • Use AI to generate assessments, feedback and differentiated materials
  • Apply AI to support collaboration, communication and virtual learning environments
  • Identify ethical risks related to AI and apply responsible use principles
  • Develop and present an AI-enhanced lesson or module with an implementation plan
  • Plan follow-up actions to monitor impact and support sustainable integration at institutional level.

Day 1 

– Course launch: expectations, intercultural icebreakers, group norms

– Needs assessment: how participants currently use (or avoid) AI / technology

– Exploring attitudes, fears, and potentials of AI in education

– Introduction to AI concepts: machine learning, neural nets, LLMs, data, training

– Walkthrough of the DigCompEDU AI supplement and linking it to teacher competences

Day 2

– Hands-on exploration: discovering free AI tools (chatbots, content generators, summarizers, auto-quiz makers)

– Small-group challenge: pick a teaching problem and test AI tools for solutions

– Case studies: real-world AI in classrooms; successes, failures, lessons

– Ethical debate: bias, data privacy, surveillance, algorithmic fairness

Day 3

– Personalization with AI: adapting content, scaffolding, learning paths

– AI and assessment: automating quizzes, error detection, feedback generation

– Using AI in language learning (e.g. practice, translation, vocabulary)

– Mid-course reflection & peer sharing

Day 4

– Collaborative learning aided by AI: group projects, discussion moderators, peer feedback

– Virtual / hybrid spaces: AI facilitating virtual collaboration

– AI-powered simulation, games, or immersive activities

– Reflection: balancing AI assist / teacher control

Day 5

– Final presentations: participants present their AI-enhanced lesson / module plus implementation plan

– Peer feedback and refinement

– Planning follow-up: monitoring, scaling, peer support

– Evaluation, certification and closing reflections