Teaching, tutoring, and course creation resources
Practical guidance for teachers, tutors, course creators, schools, parents, and students.
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Evaluate AI grading by evidence, rubrics, uncertainty, privacy, and teacher control
AI grading tools can reduce repetitive marking work, but the right choice depends on more than speed. Use this framework to compare response formats, rubrics, evidence, uncertainty, privacy, and teacher override before adopting a tool.
12 types of online courses you can sell—and how to choose yours
Not sure what kind of online course to sell? Here are 12 course types that reliably convert—plus a quick framework to choose the right niche, validate demand, price it, and sell it on SubSchool as a full course or even single lessons.
Best AI Tools for Teachers in 2026: Choose the Right Tool for Each Workflow
The best AI tools for teachers are not interchangeable. This workflow-based guide compares practical options for planning, content creation, feedback, differentiation, and administration—while keeping teacher judgement at the centre.
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Turn MAP Growth Results into a Clear, Personalised Tutoring Plan
MAP Growth results can help tutors start focused conversations about a student’s learning needs. Use this practical four-step workflow to turn a family report into sensible first-month goals, session priorities, and parent-friendly progress updates.
Use Local Authority Exam Results Data to Plan More Relevant UK Tutoring Support
Ofqual’s local authority results data can give exam tutors useful local context, but it cannot predict an individual learner’s grade. Use it to ask better questions, then let diagnostic evidence and learner goals determine the plan.
How to Combine an SAT Course with Daily Question Practice
A practical workflow for combining a SubSchool SAT course with ReadyScore practice without replacing instruction with an endless stream of random questions.
AI Tutor Guardrails: A Practical Framework for Safer, More Useful Learner Support
Correct answers are only one part of effective AI tutoring. Use this practical framework to define an AI tutor’s role, authority, tone, escalation boundaries, repair behaviours, and pre-launch review process.
How Exam-Prep Tutors Can Use Local Exam Results Data to Plan Better Courses
Ofqual’s local authority exam results data can help tutors ask sharper course-planning questions about subject demand, local context and learner support. Use it as a starting point for enquiry—not as evidence about individual schools, students or future grade boundaries.
ILR Data Collection for Small Learning Providers: A Practical Setup Checklist
A plain-English ILR readiness checklist for small learning providers using the Learner Entry Tool. Build a repeatable workflow for ownership, learner-data collection, review, submission preparation, and earnings-adjustment escalation.
Draft Faster, Keep Teacher Judgment: A Human-in-the-Loop AI Feedback Workflow
AI can help teachers draft routine feedback, but it should not make final instructional decisions. Use this practical workflow to turn student evidence and clear criteria into reviewed, personalised next steps.
AI Tools for Teachers: A Practical Evaluation Checklist Before Students Use Them
New AI features can make planning, feedback, and resource creation faster—but a useful classroom workflow still needs a clear learning purpose, teacher oversight, and careful data handling. Use this repeatable checklist and pilot worksheet to decide whether an AI tool is ready for your learners.
Use Local Exam Results Data to Plan More Responsive GCSE and A-Level Support
Local exam results data can help exam-prep teachers spot useful questions about subject demand, grade distributions and course emphasis—without making assumptions about individual learners or schools. This practical guide shows how to use Ofqual’s local authority data as one input to a diagnostic, feedback-led course plan.