Level 2: Expert AI Teacher
An advanced two-day course for teachers who want to deepen their understanding and become recognised AI champions within their school. Level 2 moves beyond individual classroom practice to address curriculum design, assessment reform, safeguarding leadership, parental engagement, and school policy equipping teachers to take an active role in shaping how their school approaches AI.
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Key Concepts
- Explain how AI works at an expert level including infrastructure, training data, cultural defaults, and governance — with enough depth to teach it accurately across all year groups
- Design developmentally appropriate curriculum progression mapping AI concepts, ethics, bias, and global impact across key stages
- Redesign assessment for the AI era prioritising reasoning, judgement, and process rather than output alone
- Embed AI across the curriculum, identify integration opportunities within existing schemes of work without wholesale redesign
- Lead on safeguarding in the age of AI, identify risks, understand escalation pathways, and lead staff and student conversations with confidence
- Engage parents and contribute to school-wide AI policy development
would recommend EDNAS Level 2 training to a colleague
left feeling confident teaching AI concepts to students
for training structure and practical applicability
Who Will Benefit
Teachers who completed Level 1 and want to go further moving from personal classroom confidence to leading AI practice in their department. Level 2 gives you the curriculum design, assessment reform, and safeguarding knowledge to become your school's go-to AI expert.
"Discussions, shared resources and links, and case study sharing. It was one of the most informative professional development sessions I have attended."
Subject coordinators build a coherent, vertically sequenced progression framework for AI concepts across their subject area with practical tools for cross-curricular integration and redesigning assessments that hold up in an AI-enabled world.
"Pivotal understanding of the AI Safety Framework. this gave me the depth I needed to lead conversations in my department with real confidence."
IT and EdTech leads develop the expert-level knowledge and policy frameworks to become genuine AI champions leading safeguarding conversations, supporting school policy, and building staff capacity beyond individual tool training.
"The practical demonstrations and clear explanation helped me better understand how to apply AI effectively in my daily work and support colleagues across the school."
Modules
How AI Got Its Worldview
Covers the physical infrastructure behind AI, how language models are trained, the role of human feedback and its cultural biases, hallucinations and the confidence problem, and AI governance across jurisdictions.
Concepts
- Physical infrastructure behind AI data centres, energy, geographic concentration
- How language models are trained and the role of human feedback
- Cultural biases embedded in training data
- Hallucinations, the confidence problem, and AI governance across jurisdictions
Activity
- "Spot the Worldview" structured discussion examining how AI tools reflect cultural and linguistic defaults
- Discuss implications for your school's international context
Advanced Teaching Strategies for AI Concepts
Examines how to teach four core AI literacy concepts — ethics, algorithmic thinking, bias, and global impact — with progression across all key stages. Participants design vertical progression frameworks from primary through secondary.
Concepts
- Teaching ethics, algorithmic thinking, bias, and global impact across year groups
- Designing vertical progression frameworks with coherent vocabulary and cognitive demand
- EDNAS AI Competency Framework applied to curriculum design
- Common misconceptions at each stage and how to address them
Activity
- Design a vertical progression framework for one AI concept from primary through secondary
- Define objectives, vocabulary, activities, and misconceptions at each stage
Practical Integration Frameworks & Assessment Redesign
Explores where AI concepts already sit within existing curricula and how to surface them without wholesale redesign. The second half addresses assessment reform — introducing the three shifts and the AI Assessment Scale.
Concepts
- Surfacing AI concepts within existing schemes of work — English, Science, and beyond
- Three assessment shifts: product → process, writing → reasoning, knowledge → judgement
- The AI Assessment Scale (Perkins et al., 2024) applied to your context
- Techniques to make student thinking visible: knowledge defence, error detection, annotated thinking
Activity
- Identify one cross-curricular AI integration opportunity in your own subject
- Redesign one existing assessment task using the three-shift framework
Safeguarding Students in the Age of AI
Examines the four key AI-specific safeguarding risks in depth. Participants work through real case studies — voice cloning, emotional dependency, false digital evidence, self-harm content — and conduct a risk exposure audit across their school.
Risk Landscape
- AI-assisted bullying and deepfake abuse
- AI-generated harmful content and data exploitation
- Emotional dependency on AI and student wellbeing
- DSL responsibilities, escalation pathways, and the Online Safety Act
Activity
- Real case studies in breakout groups: voice cloning, emotional dependency, false digital evidence
- Risk exposure audit across student behaviour, staffing, systems/policy, and technology access
Parental Engagement
Addresses the reality that parental understanding of AI is often inconsistent and behind where students already are. Introduces a four-category parental landscape and provides structured communication strategies for each profile.
Concepts
- Four parental profiles: Anxious Protector, Enthusiast, Unaware, Outsourcer
- Structured communication strategies for each profile
- Standardised staff messaging to ensure consistency across the school
Activity
- Design a repeatable parent communication cycle for your school
- Draft a one-page "AI for Parents" guide using the provided template
Developing Your School's AI Policy
Applies the EDNAS School AI Policy Framework — five commitments every policy must address. Uses three real-world case studies to ground policy decisions in current practice, with real-school policy examples from international schools.
Five Commitments
- Permitted Use
- Academic Integrity
- Data and Privacy
- Safeguarding
- Review Cadence
Activity
- Self-assessment against the Five Commitments Framework
- Live dilemmas: the detection problem, data upload problem, and grading bias
- Analysis of real-school policy examples from international schools
Learning Outcomes
By the end of Level 2, participants will be able to:
- 1Explain How AI Works at Expert LevelDescribe the infrastructure, training data, cultural defaults, hallucinations, and governance behind AI — with enough depth to teach these concepts accurately to students across all year groups.
- 2Design Curriculum Progression for AIMap AI concepts including ethics, bias, algorithmic thinking, and global impact across year groups with coherent progression in vocabulary, objectives, and cognitive demand.
- 3Redesign Assessment for the AI EraCritically evaluate existing assessments and design approaches that prioritise reasoning, judgement, and process rather than output alone.
- 4Lead on Safeguarding in the Age of AIIdentify AI-specific safeguarding risks, understand escalation pathways, and lead staff and student conversations with confidence.
- 5Engage Parents and Develop School AI PolicyCommunicate effectively with different parent profiles and apply a structured framework to build or review a school-wide AI policy.