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AI at School

Artificial intelligence (AI) is extensively covered in the media. Popular topics include chatbots, self-driving cars, virtual assistants, and job displacement. AI systems are increasingly permeating our world.

AI at School is a project that originated from the concern that students should understand artificial intelligence (AI) and the realization that there is a gap in the secondary education curriculum to address this. We create teaching materials for secondary education related to AI, aligned with the end goals and existing curriculum objectives.

AI at School is a project by dwengo vzw. Within the project, we developed both the teaching materials and the necessary tools to work with machine learning and artificial intelligence in the classroom. All content that was available on aiopschool.be (and much more) is now available on dwengo.org.

Scientific Research

AI

AI is a branch within computer science. Providing a definition for AI, something used in so many different domains, is not an easy task. Within AI, knowledge-based and data-based systems are distinguished. The chatbot Eliza and the chess computer Deep Blue are examples of knowledge-based systems. The rules the computer follows are carefully programmed. Facial recognition is an example of a data-based system. This system has learned: based on the given data, it has adjusted the parameters in the programmed algorithm. This is also referred to as machine learning.

A distinction is made between general AI and narrow AI. General AI refers to computer systems with the same capabilities as a human being. Currently, we do not have the knowledge to design such systems. For now, AI is still at the level of narrow AI: AI systems that perform specific tasks for which they were designed.

At School

As students surf the internet, post photos on Instagram, use Google Docs, have an email sent by a virtual assistant like Siri, or walk through the city, data is captured. What if an AI system correlates all that big data? Are these AI systems objective when making decisions? Should students leaving secondary education not have an understanding of our digitized world? Is this insight not necessary for them to make informed decisions in their adult lives? The 'AI at School' team believes it is. We create teaching materials for secondary education related to AI, aligned with the end goals and existing curriculum objectives. We believe that all young people should know and understand the fundamentals of AI. The best way to reach all young people is through school. Moreover, school is the ideal place to make students aware of the ethical aspects of AI systems.

Our teaching topics

AI and Climate

Students in the third grade (SO) investigate how plants adapt to climate change through their stomata. They use artificial intelligence and image recognition to count these stomata.

Social Robot

While first-year students (secondary education) build and program a social robot, they learn to solve complex problems through computational thinking. They playfully work on the new end terms for digital competencies.

AI in Agriculture

Removing rotten tomatoes during harvest? Artificial intelligence can help with that. But how? Students in the second and third grades (SO) get hands-on experience with AI. Perhaps a vibrating conveyor belt can improve the system even more?

AI in Art

Can we create art with artificial intelligence? Students in the second and third grades (SO) express their creativity with AI and reflect on the result. Is this art? They also discover how AI can protect our cultural heritage.

Computational Thinking

How can we solve complex problems with the help of a computer? Thanks to computational thinking! You can learn this through various activities with or without a computer. We'll help you get started.

AI in Healthcare

Hospitals are already using artificial intelligence today. Students in the second and third grades (SO) discover the existing systems and how they help doctors make decisions. This way, students learn the principles of the decision tree, a commonly used technique in machine learning.

Language Technology at School

Where language and technology come together, the domain of Natural Language Processing emerges. Can a computer understand, translate, or even write texts? Can a computer recognize emotions? Students in the second and third grades (SO) learn all about it in this package.