What we aim to teach
We focus on practical, foundational concepts that build digital confidence and critical thinking. We design specifically for ordinary public schools — including schools with no computer labs, limited mobile data, and learners with zero coding background.
Programme status and planning note
“Programme formats, age groups, locations and schedules will be confirmed as activities are announced.”
AI Grassroots is a community initiative in its founding phase. We do not advertise fixed enrolment dates, fees, certificates, or guaranteed outcomes. All modules below represent our proposed educational framework.
A practical starting point for your school
Share our three-page school pack with your principal. It includes proposed session formats, a complete 30-minute facilitator guide and printable sorting cards. The classroom activity needs no devices, internet or learner accounts.
Proposed learning progression
A clear four-stage sequence taking learners from initial curiosity to practical creation.
Discover
An Engaging School Talk
An upbeat, interactive introductory talk in a school hall or regular classroom introducing artificial intelligence, modern technology, and real career possibilities. Requires zero computers or coding background.
Device: No devices needed (Visual presentation / Unplugged demos)
Connectivity: Offline friendly
Try
A Guided Practical Activity
A bite-sized, hands-on exercise that absolute beginners can complete in 45 minutes using physical paper cards, classroom games, or low-data mobile phones.
Device: Printable worksheets OR basic Android phone
Connectivity: Offline or Low-data Mobile
Build
A Small Community Project
Working in small teams to design a simple solution for a familiar neighbourhood or school problem (such as waste sorting, community notifications, or study guides).
Device: Shared computer, tablet, or physical prototype poster
Connectivity: Low-data or offline design phase
Continue
Teacher Support & Next Steps
Providing teachers with printable lesson guides and open resources, with age-appropriate next steps. Older learners can explore coding academies and youth opportunity networks when eligible.
Device: Flexible
Connectivity: Open resources
What learners will explore
A balanced foundation covering practical digital skills, AI literacy, and online safety.
Digital foundations
Using computers and smartphones with confidence, file management, and core digital literacy.
Key Concepts Covered
- Navigating operating systems, folders, and shared files with confidence
- Understanding how the internet connects phones, computers, and cloud services
- Strong password habits, avoiding malware, and keeping personal accounts safe
- Using digital productivity tools for schoolwork and creative expression
AI literacy & critical thinking
Understanding how AI models work, where they make mistakes, and how to verify answers.
Key Concepts Covered
- How pattern matching and machine learning models process datasets
- Why AI systems generate plausible-sounding false information (hallucinations)
- Checking and questioning AI-generated outputs rather than trusting them blindly
- Understanding how training data affects the quality and accuracy of results
Responsible AI use, scams & safety
Privacy, misinformation, algorithmic bias, online scams, and respectful digital behaviour.
Key Concepts Covered
- Identifying fake news, deepfakes, phishing scams, and automated social accounts
- Protecting family and personal privacy on social platforms and messaging apps
- Recognising bias and fairness issues in automated decision-making systems
- Ethical, safe, and respectful online communication
Coding, creativity & logic
Building simple games, interactive animations, and creative logic projects.
Key Concepts Covered
- Visual block-based logic (Scratch / block coding) without syntax barriers
- Sequencing, conditionals, loops, and modular algorithmic thinking
- Creating interactive animations, stories, and simple 2D games
- Explaining code logic and constructive debugging through iteration
Community problem-solving & careers
Applying technology to real challenges and exploring careers in the South African tech economy.
Key Concepts Covered
- Identifying local community challenges that information tools can address
- Collecting, organizing, and visualizing simple community information
- Demystifying careers: from helpdesk and IT support to cloud and cybersecurity
- Encouraging learners to present and explain their projects with pride
Designed for real South African classroom conditions
We clearly map activity requirements so teachers know exactly what is needed before planning a session.
The Human Sorting Algorithm (Unplugged)
Learners hold numbered cards and physically move through a chalk network on the ground to see how computers sort data without using any screens.
Phones: No
Computers: No
Connectivity: No (100% Offline)
Facilitation: Yes (Teacher or Mentor)
Duration: 30 mins
Spot the Hallucination & Fake News Detective
Learners examine pairs of AI-generated answers and real articles to spot factual mistakes, logical contradictions, and invented citations.
Phones: Optional (Can use printed cards)
Computers: No
Connectivity: No (Printed worksheet)
Facilitation: Yes (Adult guided)
Duration: 45 mins
My First Visual Animation (Block Coding)
Snapping visual blocks together to make a character introduce themselves in English, isiXhosa, or Afrikaans and dance to a beat.
Phones: No (Phone project creation is not supported by Scratch)
Computers: Computer or compatible tablet
Connectivity: Internet for web editor; offline after app installation
Facilitation: Yes
Duration: 45–60 mins
Local Challenge Problem Tree
Teams map a challenge in their area (e.g. recycling, neighbourhood library access) and brainstorm how an information tool or SMS alert could help.
Phones: No
Computers: No
Connectivity: No (Poster & markers)
Facilitation: Yes
Duration: 40 mins
Multilingual Learning Plans
We plan to support activities and worksheets in English, isiXhosa, and Afrikaans. Language-specific facilitation and translated materials will be introduced and announced as local community educators and volunteer mentors are confirmed for each school cluster.
Interactive Concept: How Computers Classify Patterns
This sample uses a rule-based algorithm: a person chooses which feature to inspect. Machine learning can instead learn patterns from examples. Try changing the rule below:
Want us to visit your school or community centre?
We arrange introductory talks and guided practical sessions for ordinary public schools across South Africa. Request a school session today.