Last updated: March 2026

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Dimension 1 of 9

Student AI Literacy

Student AI literacy encompasses far more than knowing how to use a chatbot. It includes understanding core AI concepts, using AI tools responsibly and effectively, critically evaluating AI-generated outputs for accuracy, bias, and appropriateness, and creating with AI tools to achieve meaningful learning outcomes.

Why this matters

Students are already using AI regardless of whether their school has a policy on it. Research consistently shows that the majority of secondary-age students have used generative AI tools, and the proportion is growing rapidly among primary-age students. The question is not whether students will encounter AI, but whether they will encounter it with the critical thinking skills, ethical awareness, and practical competency to use it well. Schools that do not address student AI literacy are not preventing AI use — they are ensuring it happens without guidance.

The 5 maturity levels

Schools progress through five maturity levels, from initial exploration to sector leadership. Each level builds on the previous one.

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Level 1: Exploring

Basic awareness

No mention of AI literacy in curriculum or policy. Students may be using AI tools independently but the school has no structured approach.

Key indicators

  • No curriculum references to AI
  • No student AI learning outcomes documented
  • No evidence of student AI projects or assessed AI work
  • Students may use AI but without guidance
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Level 2: Developing

Structured programme

AI mentioned but no structured approach to student literacy. Some teachers may reference AI in lessons but there is no coordinated programme.

Key indicators

  • Occasional AI mentions in lessons
  • No formal AI literacy programme
  • Inconsistent guidance between departments
  • Some student awareness of AI but no critical evaluation skills
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Level 3: Established

Cross-curricular integration

Structured AI literacy programme with clear learning outcomes. Students receive explicit teaching on AI concepts, responsible use, and critical evaluation.

Key indicators

  • Documented AI literacy learning outcomes
  • Timetabled or integrated AI literacy teaching
  • Students can articulate AI capabilities and limitations
  • Assessment of AI literacy included
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Level 4: Advanced

Student-led projects

Integrated AI literacy across subjects with assessment criteria. AI literacy is embedded across the curriculum, not siloed.

Key indicators

  • Cross-curricular AI integration with subject-specific applications
  • Students critically evaluate AI outputs for bias and accuracy
  • AI ethics explicitly taught and assessed
  • Student work demonstrates sophisticated AI use
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Level 5: Leading

Peer teaching and research

Student-led AI projects, peer teaching, and community engagement. Students are active participants in shaping the school's AI approach.

Key indicators

  • Student AI leadership roles or projects
  • Peer teaching programmes
  • Community engagement activities
  • Student voice in AI policy development

What we look for

When auditing this dimension, we examine your school’s documents for evidence across these key areas:

Structured teaching on AI concepts and terminology

Guidance on responsible and effective AI tool use

Evidence that students can critically evaluate AI outputs

AI ethics and societal impact in the curriculum

Students creating with AI tools for learning outcomes

Framework alignment

This dimension is benchmarked against leading international frameworks to ensure your audit reflects global best practice.

UNESCO AI Competency Framework for Students

Global framework defining the AI competencies students need across cognitive, practical, and ethical domains.

OECD/EC AI Literacy Framework

European framework for AI literacy encompassing knowledge, skills, and attitudes for responsible AI engagement.

AI4K12 Five Big Ideas

US-developed framework organising AI concepts into five big ideas: perception, representation, learning, natural interaction, and societal impact.

DigComp 2.2

European digital competence framework updated to include AI-specific competencies for citizens and learners.

Common gaps

These are the most frequent gaps we see when auditing schools in this dimension:

Teaching AI as a standalone subject rather than integrating across the curriculum

Focusing on tool skills without critical thinking — prompt engineering without understanding why AI produces certain outputs

Ignoring that students already use AI extensively outside school, leading to programmes that lose credibility

Age-inappropriate content that does not differentiate between primary and secondary student needs

Confusing 'using AI tools' with 'being AI literate' — usage and literacy are related but distinct

Banning AI entirely, denying students the opportunity to develop critical evaluation skills

How this connects to other dimensions

No dimension exists in isolation. Understanding these connections helps schools prioritise their improvement journey.

Depends on Teacher AI Competency — teachers must be competent to teach AI literacy

Depends on Professional Development — teachers need training first

Enables Assessment Integrity — AI-literate students understand appropriate AI use

Constrained by Policy & Governance — policy must permit student AI use

Constrained by Safeguarding & Risk — safety measures must be in place

Find out your school’s student ai literacy score

Upload your school’s policy documents and receive a detailed assessment across all 9 dimensions, with evidence-based scores and actionable improvement plans.

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