Artificial Intelligence in School Education

Key takeaways from the Learn ML Webinar on teaching AI in Schools

Jasper Schellekens
5 min readNov 9, 2020

An understanding of Artificial Intelligence (AI) and Machine Learning (ML) is critical to the development of Europe’s children and teenagers into responsible citizens and insightful thinkers that will be able to navigate the complex digital space and effectively contribute to its design.

The “Learn to Machine Learn” project — a three-year Erasmus+ Strategic Partnership in the field of Education — is how we are trying to address these challenges. The project introduces AI literacy to primary and secondary education and uses games to introduce students to the core principles of AI and ML. I already posted a number of games that can be used to teach and discuss AI with kids, the project also has developed a toolbox including a more extensive list and information on how teachers can use the games.

In the LearnML Webinar held on the 3rd November experts from Universities and Schools from Malta, Greece, and Norway who were involved in creating the toolkit explained the various aspects. Following a welcome by the President and CEO of the National Centre of Audiovisual Media and Communication — EKOME and an explanation of the project by the Project Coordinator we explained the various critical puzzle pieces that were being put in place for teaching and learning AI in schools.

New Games Being Developed to Specifically Teach AI

In the webinar, Prof. Yannakakis — Director of the Institute of Digital Games and project coordinator, provided an update on three game prototypes for learning about AI.

Prototype Training Neural Network in Minecraft

Minecraft Learns ML is a short game showcasing how videogames can be used to teach core principles of the architecture of Neural Networks using Imitation Learning.

A 3D dungeon game allows students to specify learning elements in the environment to gain a better understanding of supervised learning.

An art and culture oriented game where students classify paintings, sculptures, and the algorithm learns from the dataset provided by the child to be able to continue evaluating objects themselves.

These games teach the basic concepts of supervised learning and reinforcement learning, but the also stimulate them to think critically about the ethical choices involved in how they select data and how these can affect their agent as well as how they affect society at large.

Challenges to Teaching & Learning AI

The challenges to teaching and learning AI are covered by Dr. Vanessa Camilleri, Faculty of ICT, University of Malta. She identifies the following as key challenges:

  • Removing preconceptions and misconceptions
  • Relating concepts to real-life situations
  • Creating a guided structure that allows for critical thinking
  • Finding support materials

The LearnML project has developed scenarios for teachers to use, with existing free games in addition to the prototypes being developed. A book on AI in Education which will be available from the LearnML website specifically works as a guide for teachers and for students to use activities that teach AI in the classroom without digital devices. That way we can get concepts across without being limited by technology.

An Active Learning Experience — Learning Machine to Learn Framework

The LearnML framework is designed to provide students activities that will result in:

  • The ability to recognize AI applications in the real world
  • An understanding of ethical problems that might arise with the use of AI
  • A functional understanding of how Machine Learning works
  • An understanding the outcome of a simple Machine Learning Application
  • An understanding of what it means to ‘train data’

Research was conducted in the schools to find out both what students and teachers required and thought was needed in the classroom. This allowed the framework to fit the needs of actual educators.

Furthermore, LearnML has collated a range of AI games and tools into a single document to help teachers find them. Teachers and researchers were invited to try out the tools, both to inform and gather more information about their needs.

Dr. Sofia Papavlasopoulou, Norwegian University of Science and Technology

Prof. Michalis Giannakos used Kahoot a game developed by NTNU to elicit feedback from the participants, also providing an example how technology developed at Universities can be applied to improve teaching in schools.

Blockchain, AI, and the Future of Education

The webinar concluded with a invited guest Dr. Alex Grech — Director of the Commonwealth Centre for Connected Learning, who spoke about the impact and opportunities of using AI and Blockchain to revamp the education system. Importantly the one-size fits all model of education needs to be re-thought, as many people are already experiencing a large chunk of informal learning such as YouTube, edX, Stack Overflow, which aren’t really recognised. Emerging technologies still haven’t quite impacted education and in the case LearnML aims to change this.

Online Workshop — How to use LearnML Framework to teach in schools

After the presentations, a hand-on workshop was organised for Greek educators (in Greek) where they were introduced to the details of the LearnML framework, how to use the games, and how to use the proposed scenarios. Similar workshops had been done in the past in Greece, Norway, and Malta earlier in the project, but the webinar format did allow more educators to attend and participate.

The LearnML Speakers and Organisers from Greece, Malta, and Norway

This is only the start of the project and there are still 2 more years for it to develop and grow. The game prototypes will be released later on, so for more information and updates stay in touch on Facebook or Twitter!

Also see previous blog post about 7 FREE games you can start to use for learning and teaching AI and the range of educational games developed by the Institute of Digital Games.



Jasper Schellekens

Jasper Schellekens is part of the top-ranked Institute of Digital Games at University of Malta. Leading innovative research from Game AI to Game Philosophy.