Materiais didáticos

Age group: 6–9 years
Duration: 20–30 minutes
Group size: 6–30 participants
Format: Movement and role-play activity
Difficulty: Easy

Children guide a “robot” through a simple task by giving clear, step-by-step instructions. When the robot misunderstands vague directions or follows instructions too literally, participants discover why computers and machines need precise information—and why human instructions influence what technology does.

Age group: 6–10 years
Duration: 25–35 minutes
Group size: 6–30 participants
Format: Card sorting and role-play activity
Difficulty: Easy

Participants become teachers for a pretend AI system. Using picture cards, they provide examples that help the “machine” learn how to sort objects or animals into categories. They then test the machine with new examples and discover that its results depend on the quality, variety and accuracy of the information used to teach it.

Age group: 7–11 years
Duration: 25–35 minutes
Group size: 6–30 participants
Format: Language game and role-play activity
Difficulty: Easy to moderate

Participants become a human language machine that builds sentences by predicting one word at a time. By choosing words that commonly appear together, they discover how language-based AI can produce fluent text through pattern recognition—without necessarily understanding its meaning or knowing whether the information is true.

Age group: 8–12 years
Duration: 30–40 minutes
Group size: 6–30 participants
Format: Observation, role-play and discussion activity
Difficulty: Moderate

Participants investigate how people recognize emotions through facial expressions, tone of voice, body language and situational context. They discover that the same signal can have different meanings and consider why an AI system may struggle to interpret subtle, mixed or culturally expressed emotions.

Age group: 8–13 years
Duration: 30–40 minutes
Group size: 6–30 participants
Format: Guessing game, investigation and discussion
Difficulty: Moderate

Participants examine short texts, pictures, jokes or creative ideas and guess whether each was produced by a person or generated with AI. After the sources are revealed, they discuss which clues influenced their decisions and discover that AI-generated content cannot always be identified reliably from appearance alone.

Age group: 9–14 years
Duration: 40–60 minutes
Group size: 6–30 participants
Format: Group creativity and prompting activity
Difficulty: Moderate
Technology required: Optional

Participants create a short story, joke, image concept or film continuation with the help of an AI tool or prepared AI-style responses. They improve an initial prompt, evaluate the generated result and transform it through their own creative decisions. The activity demonstrates that a clear prompt can guide an AI, but meaningful creative work still requires human intention, judgment and editing.

Age group: 10–14 years
Duration: 35–50 minutes
Group size: 8–30 participants
Format: Card game, investigation and discussion
Difficulty: Moderate

Participants investigate a fictional AI system that selects candidates for a space-rescue team. The system has learned from a limited set of previous examples and begins treating irrelevant characteristics as signs of ability. By testing and improving the system, participants discover how incomplete or unbalanced training data can produce biased and unfair results.

Age group: 11–16 years
Duration: 40–55 minutes
Group size: 8–30 participants
Format: Media investigation and group discussion
Difficulty: Moderate to challenging
Technology required: None; optional for extended verification

Participants investigate fictional social-media posts containing manipulated or misleading images, videos, audio and digital personalities. Instead of relying only on visible mistakes, they examine the source, context, supporting evidence and purpose of each post. They develop a practical verification checklist for responding to suspicious digital content.

Renewable energy project developers, economists, and financial analysts work out how to make clean energy projects affordable and profitable. They study costs, savings, and investment returns for solar panels, wind farms, and energy storage systems. These professionals also work with governments and communities to create incentives that encourage people to use renewable energy. Their work helps more people and businesses switch to clean energy, reducing pollution and supporting climate goals. Green jobs in energy finance are crucial because they make renewable energy a smart choice for companies, cities, and homeowners alike, helping grow the clean energy economy.
 

Age group: 10–16 years
Duration: 40–55 minutes
Group size: 8–30 participants
Format: Systems-mapping and decision-making activity
Difficulty: Moderate

Participants trace what happens behind the screen when an AI system receives a request. Using process cards and resource tokens, they investigate how devices, networks and data centres require electricity, water, raw materials and physical infrastructure. They then consider how AI can create environmental costs while also helping people use resources more efficiently and address environmental challenges.

Age group: 11–16 years
Duration: 45–60 minutes
Group size: 8–30 participants
Format: Card sorting, future planning and discussion
Difficulty: Moderate to challenging

Participants examine tasks from different professions and decide whether they are best performed by a person, an AI-enabled machine or a human–AI team. By redesigning a future job, they discover that AI often changes individual tasks rather than simply replacing entire professions. They also identify the human abilities and new skills likely to remain important in an AI-supported workplace.

Age group: 12–16 years
Duration: 50–75 minutes
Group size: 8–30 participants
Format: Design challenge, teamwork and presentation
Difficulty: Challenging

Participants design an AI-supported solution to a real social, scientific or environmental challenge. Beginning with the problem rather than the technology, teams decide whether AI is genuinely useful, what data the system would need, who might benefit or be harmed and what safeguards should be included. They present their proposal and receive feedback from other participants acting as an ethics and innovation panel.