Kindergarten – Grade 2
Computers follow instructions; machines can sort and match; humans decide. Voice assistants and pattern games, always supervised.
FutureTech & Computing
Artificial Intelligence Literacy
Grade bands served: Kindergarten through Grade 12 (age-appropriate)
AI Literacy is a signature strand of Stars Ablaze FutureTech. Learners progress from the playful idea that computers follow instructions, to understanding pattern recognition and training data, to prompting, evaluating and applying AI systems responsibly. The strand is honest about limitations: hallucination, bias, data privacy, environmental cost and the weak representation of African languages and contexts in most models. Learners are taught to verify, disclose and take responsibility for anything they produce with AI assistance.
Why this subject matters
AI is already shaping hiring, information and services. Learners who understand it become builders and informed users rather than passive or misled consumers.
Overall learning goals
- • Explain in age-appropriate terms what AI is and is not.
- • Understand data, training, patterns and prediction.
- • Use AI tools effectively and ethically for learning and work.
- • Detect bias, error and fabricated output.
- • Apply AI to real problems with human judgement in control.
Core competencies & skills
- • Conceptual understanding of machine learning
- • Prompting and iteration
- • Output verification
- • Bias and ethics analysis
- • Responsible disclosure of AI use
Scope by grade band
Grades 3–5
What AI is in simple terms, training by examples, where AI appears in daily life, honest use in schoolwork, and never sharing personal information.
Grades 6–8
How models learn from data, prompting basics, hallucination and bias, academic-honesty rules, and simple classification demonstrations.
Grades 9–12
Applied AI for research, analysis, media and productivity; prompt engineering; evaluation and verification methods; AI ethics, governance and career implications.
Typical learning activities
- • Guided AI tool sessions with teacher supervision
- • Prompt-and-critique exercises
- • Bias hunts in AI output
- • Human-versus-AI comparison tasks
- • Ethics debates
Project examples
- • Classify a small teacher-provided dataset and explain the result
- • AI-assisted research report with a source-verification log
- • Build a study assistant workflow for a subject
- • Senior project applying AI to a real community problem
Assessment methods
- • Verification logs and disclosure statements
- • Written concept examinations
- • Applied project rubrics
- • Ethics case-analysis essays
Real-world & career connections
- • AI-assisted roles across every profession
- • Data and machine-learning support roles
- • Product and research roles
- • Digital entrepreneurship
FutureTech & AI integration
This subject defines the AI progression used across the whole FutureTech pathway and connects to Coding, Data Literacy and Cybersecurity.
Expected learner outcomes
- • Graduates use AI tools productively and disclose their use honestly.
- • Graduates identify fabricated or biased AI output.
- • Graduates complete an applied AI project with human oversight documented.
Prerequisites
Applied AI in Grades 11–12 assumes prior coding and data-literacy coursework.
Where it appears by grade
Related subjects
Computer Science
How computers work, from instructions to algorithms and systems.
Coding & Software Development
Block coding to Python, web development and real software projects.
Robotics & Engineering
Design thinking, build challenges, mechanisms, sensors and control.
Digital Literacy & ICT
Practical device, productivity and internet skills for school and work.