Education · 24 February 2026
AI in Education
For teachers, school leaders and MATs
At askKira, we provide GDPR-compliant, secure AI built specifically for UK schools. Developed with over 100 education experts and aligned with DfE, Ofsted and EEF guidance, askKira helps teachers, school leaders and MATs work smarter, reduce workload and make data-driven decisions with confidence.
This week's roundup brings you the latest AI developments that matter for UK education.
Teaching & Learning
OECD warns of 'metacognitive laziness'
The newly released OECD Digital Education Outlook 2026 highlights a critical risk where students using AI for maths saw a 48% performance jump but performed 17% worse than their baseline once the tool was removed. The report suggests students may learn to rely on the bot rather than mastering the underlying concepts.
Why it matters: Schools must design AI tasks where the technology acts as a fading scaffold rather than a permanent crutch to protect exam performance.
Read the source on LinkedIn →Moving beyond 'don't use it'
A new curriculum framework adapted from UNESCO suggests schools move past simple bans or detection. The model proposes three distinct strands for students: Learning WITH AI (using it as a tool), Learning ABOUT AI (mechanics and ethics) and Learning TO EVALUATE AI (critical thinking).
Why it matters: This provides a clear structure for department heads to audit their schemes of work against specific competencies rather than vague policy statements.
Read the source on LinkedIn →Explaining Machine Learning to KS2/KS3
Educators are finding success using simple analogies to explain complex ML concepts to younger students. Effective comparisons include learning to ride a bike (practice over manuals) and Netflix recommendations (pattern recognition), helping demystify the 'magic' of AI.
Why it matters: Demystifying the technology early reduces the likelihood of students anthropomorphising chatbots or trusting them blindly.
Read the source on LinkedIn →Strategy & Governance
The 'Named Lead' requirement
Guidance for school leaders emphasises that AI readiness requires a specific, named individual to be accountable for decisions. This role should be distinct from the IT Director and focus on pedagogical and ethical governance rather than just technical implementation.
Why it matters: Without a named lead, AI adoption becomes fragmented and shadow IT proliferates; update your leadership responsibilities to include explicit AI governance.
Read the source on LinkedIn →Smart strategies for tight budgets
Schools with constrained infrastructure are being advised to pilot single tools effectively rather than attempting broad rollouts. The focus is on 'infrastructure reality' where mobile-friendly, low-bandwidth AI tools may be more effective than high-end platforms requiring 1:1 devices.
Why it matters: State schools with limited capital budgets should prioritise text-based AI tools that work on existing hardware over bandwidth-heavy adaptive learning platforms.
Read the source on LinkedIn →Wellbeing & Pastoral
Students turning to AI for therapy
Recent data indicates a significant portion of ChatGPT users under 25 are using the tool for mental health support rather than homework. This shift presents a 'paradox' where students may be more comfortable confessing to a bot than a human counsellor.
Why it matters: DSLs must urgently update safeguarding education to warn students that public LLMs are not confidential and lack clinical safety protocols.
Read the source on LinkedIn →The global divide on screens
While wealthy nations like Sweden are returning to textbooks to combat distraction, under-resourced contexts are leaning into AI to solve high pupil-teacher ratios. This highlights that 'back to basics' is often a luxury of well-staffed schools.
Why it matters: UK schools should evaluate screen bans based on their specific staffing capacity and intervention needs rather than blindly following Scandinavian trends.
Read the source on LinkedIn →