End-of-Year Reporting in LGR22 with AI
June 16, 2025
End-of-year reporting under LGR22 can feel like a sprint: you must turn months of everyday evidence into defensible skriftliga omdömen and, from Åk 6, grades that are transparent and fair. This article sets out a Sweden-specific pipeline using a four-tool workflow—Development Talk (Student) → Summariser → Student Communication → Parent Communication—so you write less, but justify more. You’ll see workload maths, moderation checkpoints, and fully worked examples for Åk 2, Åk 4 maths, Åk 6 first grades, and Åk 8 chemistry.
Tackling the marking mountain with AI
May 6, 2025
End-of-year marking often fails not because teachers lack expertise, but because consistency is hard to maintain at speed. A moderation-first AI workflow flips the usual approach: you standardise how the rubric is interpreted before any feedback is generated, then use AI for first-pass comment batches and consistency checks across classes. Grades remain human-set, and pupil data is minimised through anonymised evidence packs and local templates. This article offers a practical, low-risk process you can roll out in a week.
Exam-Season AI Traffic Lights for Schools
May 2, 2025
Exam season is when AI rules most often unravel: different teachers say different things, students guess what’s allowed, and well-meaning support can tip into malpractice. This one-page “AI traffic-light” boundary system gives a shared language for revision, homework, coursework/NEA, controlled assessment and exams. You’ll get clear permitted/restricted/prohibited uses, quick ways to introduce the system in five minutes, ready-to-say scripts for staff, students and families, and integrity checks that work even when you can’t reliably “detect AI”.
May exam countdown: a 28-day AI revision sprint
April 29, 2025
The final 3–4 weeks before GCSE and A-Level exams are not the time for new notes, endless videos, or ‘more content’. They’re the time for precision: retrieval, error correction, and timed rehearsal. This 28-day, integrity-safe exam sprint uses AI as a revision operations system rather than a content generator. You’ll set up daily retrieval mini-sets, run a live misconception-to-fix loop through error logs, and rehearse timed papers with AI coaching only before and after. You’ll also get a light-touch teacher monitoring plan plus ready-to-use templates for students, parents, and departments.
KS2 SATs: AI boundaries and revision toolkit
April 17, 2025
AI can genuinely improve Year 6 SATs preparation, but only when the boundaries are crystal clear. This guide sets out what “appropriate AI support” looks like for KS2, alongside non-negotiable integrity rules for pupils at home and teachers in school. You’ll find practical ways to use AI to generate maths retrieval practice, diagnose misconceptions, and scaffold SPaG and reading comprehension without giving answers. It also includes minimum-data safeguarding routines, low-device alternatives, and ready-to-copy prompts, plus a one-page family agreement you can adapt.
From Autocomplete to Co-authoring
April 10, 2025
In 2024–2025, AI writing tools shifted from simple autocomplete to document-aware co-authoring spaces that can draft, rewrite and reorganise whole texts on command. That change has made “did they use AI?” the wrong question for assessment. Instead, teachers need routines that capture visible decision-making: prompt logs, revision rationales, source trails and short in-class checkpoints. This guide explains the new risks (over-polish, voice drift, hidden outsourcing) and offers practical ways to redesign writing instruction so students can use AI while still producing assessable evidence of thinking, craft and integrity.
End-of-Term Grading: A Batch Marking Pipeline
March 17, 2025
End-of-term grading can feel like a sprint you didn’t train for. Used well, AI can reduce the admin burden without becoming a grade-decider. This article offers a practical ‘batch marking pipeline’ that keeps teachers firmly in control: how to structure anonymised evidence packs, generate rubric-aligned comment banks, run consistency and bias checks, and produce student-facing next steps. The focus is on minimum-data prompting, clear boundaries, and repeatable routines that support reliable, fair grading while respecting data protection.
AI and LGR22 Assessment: Fair, Aligned Tests
March 14, 2025
LGR22 assessment asks teachers to make holistic judgements from evidence gathered over time, yet pre-test season can push us towards “one big test” decisions. This article offers a practical, teacher-in-the-loop workflow for turning pasted betygskriterier into fair, curriculum-aligned assessments using AI. You’ll see how to build E/C/A-targeted questions, generate three-tier model answers, and add justification checklists that keep grading anchored in the criteria. We also share a light portfolio plan so no single test carries the whole grade.
Exam-board-aware AI revision for GCSE & A-Level
March 10, 2025
Exam success is rarely about doing “more revision”; it’s about doing the right revision for the paper you will actually sit. This article sets out an exam-board-aware AI workflow for GCSE and A-Level that turns specifications, command words, mark schemes and examiner reports into a misconception-led plan. You’ll see how to build retrieval practice that matches marking criteria, then organise it into spaced repetition that prioritises weak areas and high-yield errors. It also includes clear integrity rules for students and staff, plus a simple teacher set-up and monitoring routine.
Mock Exam Support with AI
January 15, 2025
Mock exams are the safest time to learn how to use AI as a powerful revision coach. Used well, AI can help you turn messy class notes and long syllabuses into clear topic lists, practice questions and model answers – all tailored to your course. This guide walks you through exactly how to do that without cheating, breaking exam rules or letting the technology think for you. You will learn step-by-step ways to use AI for feedback, error analysis and active recall, plus a simple checklist schools can share with students before mock season.
LGR22 Digital Competence: An AI Evidence Pack
January 14, 2025
LGR22 expects pupils to use digital tools thoughtfully, understand how digital systems shape information, and act responsibly online. AI sits naturally within those expectations, but it does not need its own unit. This article offers a cross-subject “evidence pack” approach: small, teachable micro-artefacts that generate assessable proof of digital competence while you teach your normal content. You’ll get ready-to-run tasks for spreadsheets, programming, source criticism, fake-news analysis, and writing with digital tools—each mapped to centralt innehåll and designed to progress from mellanstadiet to Åk 8.
Revision Techniques Powered by AI
November 19, 2024
AI can supercharge revision – but only when it rests on solid cognitive science rather than endless practice questions. This article shows how to “bolt” AI onto proven techniques like spaced repetition, retrieval practice, interleaving and exam-style questions, without diluting desirable difficulty. You will find parallel workflows for teachers and students, with concrete subject examples and ready-to-use routines. We also explore how to avoid over-reliance, cheating and cognitive offloading, so learners stay in charge of their thinking. A practical, research-informed playbook for exam preparation in any subject or school system.
Redefining Originality: Assessment in 2024
September 25, 2024
As generative AI becomes a normal part of students’ lives, traditional ideas of “original work” are under pressure. Instead of trying to catch AI-assisted cheating, teachers can redesign assessments so that authentic process, personal voice and contextualised evidence matter more than the final product. This article offers a practical playbook for reworking existing tasks into “originality by design” assessments, with concrete examples, rubrics and classroom routines. You will find strategies that make AI a transparent, bounded part of learning, rather than something to fear or detect.
AI Detection Accuracy: The Evidence
September 19, 2024
AI writing detectors promise to spot ChatGPT-style text, but independent research paints a far more complicated picture. This article synthesises what studies actually show about Turnitin, GPTZero and similar tools: their accuracy, false positives and worrying biases, especially for multilingual and high‑performing students. It then translates that evidence into concrete guidance for schools on when not to use detectors, how to respond to AI flags, and what to do instead. The goal is a fair, defensible approach to assessment that protects academic integrity without harming the very learners we aim to support.
AI Marking at Scale: Lessons from Universities
August 22, 2024
Universities have been early adopters of AI-assisted marking, moving beyond hype to build practical systems that work at scale. This article distils what they have actually done – from moderation models, calibration routines and governance structures to student communication and union engagement – and translates those lessons into realistic workflows for schools. You will find concrete examples of AI-ready rubrics, feedback templates and phased roll-out plans that fit within existing assessment systems, while respecting exam-board rules, safeguarding and data protection requirements.