What are artificial intelligence literacy and competency? A comprehensive framework to support them

University centres (curriculum, learning sciences, partnerships) plus international co-authors

Hong Kong SAR (lead) + Qatar, Japan, Finland affiliations

Facilitated iterative co-design workshops with experienced AI teachers

• In-school (K–12)

Four-cycle iterative co-design discussions revising framework artifacts

Multiple workshop cycles as reported

30 experienced AI teachers from 15 middle schools

Framework addresses GenAI-era tools (ChatGPT, Sora mentioned)

• Convenience sample of expert teachers may differ from novices
• Contextual translation needed across systems
• Empirical student validation still required
• Rapid tool change pressures iterative updates

Middle school focus in participant selection; framework intended for broader K–12 and adult non-experts

Teachers already experienced with AI instruction

Varies; framework not purely engineering-centric

• Define AI literacy vs competency including confidence and self-reflection
• Co-design comprehensive K–12 framework with practitioners
• Propose learning experiences aligned to five abilities

• Bridge engineering-only definitions to school-sensible outcomes
• Set research agenda (prompt engineering, data/algorithmic literacy, etc.)

• Not a randomized student outcome trial
• Not a national policy mandate
• Not exhaustive psychometric validation of instruments

Conceptual framework spanning technologies from CV/NLP to GenAI

• Co-creator
• Evaluator

Global K–12 AI for All relevance

• Competency emphasizes beneficial application with reflection
• Five components: technology, impact, ethics, collaboration, self-reflection

• Ethics and collaboration as first-class dimensions
• Self-reflection to counter uncritical tool use
• Data and algorithmic literacy for GenAI risks

• Establish definitions using literature + curriculum design lenses
• Run iterative co-design cycles with teachers revising framework
• Articulate five learning experiences fostering abilities/confidences
• Publish five future research directions

• Teachers validate implementability; students ultimately assessed against competency constructs in future work

• Process/praxis curriculum approaches to nurture literacy over time

• Global initiative needs practitioner-grounded definitions beyond engineering lists
• GenAI disrupts static competency models—reflection essential

• Iterative co-design cycles explicitly integrate teacher voice
• Literacy/competency split clarifies assessment design targets

• Teachers co-produce actionable framework elements

• Five-component structure and five experience types published for adoption

Positions empirical follow-up on prompts, data literacy, and reflective mindsets as next wave of research.

• Protect teacher intellectual contributions in co-design agreements
• Student assessment ethics once competency rubrics deploy
• Avoid overclaiming without psychometrics
• Inclusive recruitment across school types in future cycles

• Activity documentation
• Practitioner observation

• Develop and validate instruments for each competency dimension
• Longitudinal student growth studies under framework-aligned curricula

• AI literacy frameworks
• Teacher professional learning
• GenAI in schools

• Completed

Middle school teachers → K–12 learners

Multi-country author network; HK-led co-design

Literacy + competency integration

Co-design / praxis

Low (framework)

Low