BIP

BIP courses

“Innovating School Informatics with AI"

Physical learning week in Tallinn University: 21 – 26 September, 2026

Target group: Master's and doctoral students interested in school informatics, mathematics education, STEM education, artificial intelligence, and computational thinking.

Maximum number of students: 22.

Total duration: 21–26 September, 2026.

Course description

This Erasmus+ Blended Intensive Programme (BIP) explores innovative approaches to integrating artificial intelligence, machine learning, and computational thinking into school informatics and STEM education. The course provides participants with practical methods for teaching AI-related topics, including machine learning, data science, modelling, and the ethical use of AI.

Using a problem-based and hands-on approach, participants will design lesson plans, digital learning resources, and assessment tools while exchanging experiences and good practices from different countries. The course also promotes creativity, learner autonomy, critical thinking, and collaborative problem-solving in the context of AI-driven digital transformation in education.

In-person sessions at Tallinn University, Estonia

The physical programme combines participation in the ISSEP 2026 (International Conference on Informatics in Schools) with workshops, school visits, and collaborative design activities.

During the first three days, participants will attend keynote presentations, paper sessions, and workshops as part of the ISSEP conference. The remainder of the programme includes practical workshops and visits to Estonian schools, where participants will explore contemporary approaches to AI and informatics education.

Hands-on activities include designing lesson plans, using unplugged activities to teach computational thinking, agile prototyping, training machine learning models with Teachable Machine, prompt engineering for large language models, developing CustomGPT applications, and creating assessment rubrics and adaptive tests.

Learning outcomes

After completing the course, participants will be able to:

  • apply innovative teaching strategies that integrate informatics, mathematics, artificial intelligence, machine learning, and computational thinking;
  • design interdisciplinary learning activities combining informatics, data science, and AI;
  • develop practical teaching materials, assessment tools, and AI-supported learning activities;
  • deepen their understanding of AI education in school informatics;
  • gain insights into classroom practice through visits to Estonian schools and adapt these approaches to their own educational contexts;
  • build an international professional network of peers and experts in AI education for future collaboration.

Contacts

With questions regarding the administrative side of the course, please contact the Departmental Erasmus Coordinator Kristel Viileberg (kristel.viileberg@tlu.ee).