Inclusive education in LGR22 Section 1–2 is not framed as a “nice extra” for certain pupils. It is a design constraint: lessons should be planned so that participation is possible, expectations stay high, and support is built in from the start. Many teachers agree with the principle, yet struggle with the practical question: what do I actually do, quickly, on a normal Tuesday? The workflow below turns LGR22’s inclusion mandate into a 15-minute “accessibility pass” you can run on any lesson and document in a way that stands up to professional scrutiny. If you want a broader map from policy expectations to classroom tools, you may also find [LGR22: gap-to-tool workflows](/en-gb/blog/2025/11/14/lgr22-three-years-on-gap-to-tool-map-ai-workflows-time-savings/ useful.
Section 1–2 pushes us towards lessons that are coherent, safe, and accessible, with teaching that anticipates variation rather than reacting to it. In practice, that means planning for multiple entry points, clear language, and predictable routines, while keeping the learning intention intact. Inclusion here is not the same as “making it easier”. It is about removing avoidable barriers: unclear instructions, overloaded text, hidden vocabulary, or tasks that assume background knowledge pupils may not have.
A helpful mindset shift is to treat accessibility as part of quality, not a separate layer. When you improve clarity for a pupil who needs more structure, you usually improve clarity for everyone. And when you record what you changed and why, you protect teacher judgement rather than replacing it with automation. This approach aligns well with the idea of inspection-ready micro-tools that support cross-curricular coherence, explored in [Section 2 throughlines with micro-tools](/en-gb/blog/2025/09/15/lgr22-section-2-cross-curricular-throughline-ai-micro-tools-inspection-ready/.
Think of the “Lesson Accessibility pass” as a short cycle with clear inputs and outputs. Your inputs are the lesson objective, the core task, the key text or stimulus, and the success criteria. If you have them, add the likely pinch points: where pupils typically get stuck, which vocabulary tends to derail understanding, and which transitions tend to trigger low-level disruption.
Your outputs are four small artefacts you can save: an accessibility-adjusted lesson outline, difficulty adjustments with change notes, a lesson-specific vocabulary list for learners using an additional language, and a short behaviour plan for predictable routines. What stays teacher-only is equally important. Decisions about ambition, grouping, sensitive information, and any interpretation of pupil needs must remain yours. AI can draft options; you choose, edit, and document.
Start with “Lesson Accessibility (without specific needs)”. This is the universal pass: you do not mention diagnoses, labels, or individual pupils. You ask for barrier-removal strategies that benefit the whole class. For example, in a science lesson on evaporation, the tool might suggest a two-minute retrieval starter with three images, a worked example of a results table, and a short “stop and check” script after the first instruction. None of this lowers expectations; it simply makes the route to the learning clearer.
In practice, aim for three adjustments only. Too many changes create noise and make it hard to see what helped. A good universal set often includes one language adjustment (simplify instructions without simplifying content), one sequencing adjustment (break the task into visible steps), and one participation adjustment (ways to respond without waiting for writing stamina). If you’re building classroom visuals to support this, the thinking in [inclusive displays and vocabulary walls](/en-gb/blog/2025/08/28/ai-inclusive-classroom-displays-vocabulary-walls-dual-coding-retrieval-boards/ will translate well into day-to-day routines.
Next, run “Lesson Accessibility (with specific needs)”, but keep it professional and minimal. You are not writing a profile of a child. You are describing functional needs in classroom terms. For instance: “needs reduced copying; benefits from explicit success criteria; struggles with multi-step verbal instructions; anxious during transitions; reading age below the class average; uses an additional language at home.” That is enough for targeted suggestions without oversharing.
The key is to protect ambition. If the objective is to compare characters’ motives in a story, the adjustment should change the access route, not the thinking demand. You might offer sentence stems, a short glossary, and a choice of response format (oral rehearsal, bullet points, or a paragraph), while keeping the same success criteria. A useful teacher check is: would I still be happy to display this pupil’s thinking as evidence of the objective? If yes, you have adjusted access, not expectations.
Now use the “Difficulty Adjuster” twice: once down and once up. This avoids a common inclusion trap where support only ever means “less”, while extension is treated as separate planning. In a maths lesson on fractions, the “down” version might keep the same concept but reduce extraneous load: fewer items, clearer layout, more worked examples. The “up” version might add reasoning prompts or require pupils to justify which representation is most efficient.
The crucial feature here is change notes. For each adjustment, record what changed and why, in plain language. For example: “Reduced reading load by replacing the word problem with a diagram; purpose: assess fraction comparison, not decoding.” Or: “Added an ‘explain your method’ prompt; purpose: deepen reasoning for secure learners.” These notes make decisions auditable and show professional intent. If you are building safe routines for early-career colleagues, the habit of documenting small decisions is reinforced in [AI micro-routines for new teachers](/en-gb/blog/2025/07/18/ect-nqt-first-term-ai-operating-manual-safe-micro-routines-checklist/.
A vocabulary list should support the lesson, not become a translation dump. Ask for a short list of high-utility words and phrases pupils will actually need to participate today. In geography, that might be “source”, “mouth”, “tributary”, “flow”, “steep”, “downstream”, plus sentence frames such as “The river flows because…” or “This area floods when…”.
Then make it bilingual in a controlled way. If you know the language(s) represented, you can generate translations, but keep the English definition and a simple example sentence alongside. If you do not know the language, a safer approach is to provide clear English definitions and invite pupils or families to add home-language equivalents. This respects linguistic diversity without pretending the teacher can quality-assure every translation. For oral practice, pairing vocabulary work with short spoken checks can be powerful; see [voice AI for accessibility and fluency](/en-gb/blog/2025/10/13/voice-ai-in-schools-accessibility-fluency-formative-assessment-safeguarding-rubric/ for ideas that keep safeguarding in view.
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Year 3 transition difficulties often show up as “small” behaviours that derail learning: calling out, refusal to start, wandering, or heightened sensitivity to corrections. The goal is not a long policy document. It is a lesson-level plan with scripts, routines, and escalation that protect learning and relationships.
Ask the tool to draft a short routine for three moments: entry, the first independent minute, and the transition to the main task. In a writing lesson, you might use a consistent entry: “Coats away, equipment out, eyes on the board.” Then a 30-second model: “I’ll show you the first sentence.” Then a predictable start cue: “When I say ‘go’, write the date and title only.” Your scripts should be calm and repeatable, with one warning line and one follow-through line. Escalation should be clear but proportionate: private reminder, choice statement, brief reset, then a planned next step. The plan is not about punishment; it is about reducing uncertainty for pupils who find transitions hard.
Before you teach, run three quick checks. First, an inclusion check: can pupils show the intended learning in more than one way, and are the instructions unambiguous? Second, a language check: have you identified the words that will block understanding, and are your definitions pupil-friendly? Third, a “what could go wrong” review: where will pupils bottleneck, and what is your pre-planned response? This is also where you sanity-check any AI output for tone, bias, or unrealistic timing. If you are working under a compliance framework, it is worth aligning your process with your local guidance; for a wider view of responsible use, see [AI compliance explainer](/en-gb/blog/2025/07/15/eu-ai-act-lgr22-swedish-schools-ai-compliance-explainer/.
To make your work evidence-ready, save a small, consistent pack each time. Keep the “before” lesson outline and the “after” version with accessibility edits highlighted. Save the difficulty-adjusted variants with the change notes visible. Save the vocabulary list as used in class, including any pupil-added home-language equivalents. Save the behaviour plan and, if helpful, a brief reflection after the lesson: what worked, what you will keep, and what you will change next time.
This is not paperwork for its own sake. It is a professional record that shows you planned for participation, monitored impact, and refined your approach. Over time, you will build a bank of patterns that make the 15-minute pass even faster.
The safest prompt set is “minimum-data”: no pupil names, no diagnoses, no sensitive histories. You can copy and adapt these in your own tool of choice.
For a one-week implementation plan, keep it simple: run the universal pass every day, and add one extra workflow per day on rotation. By Friday, you will have used all four micro-tools without overwhelming your planning time. If you want to scale this across a team, the structure in [an INSET micro-routines plan](/en-gb/blog/2025/08/25/inset-day-ai-workshop-three-micro-routines-safety-protocol-30-day-implementation/ can help you embed habits without turning them into a burden.
May your next lesson feel clearer, calmer, and more accessible to every pupil. The Automated Education Team
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