Designing Curriculum for Progression – Spot Gaps and Next Steps with AI
A practical guide to using AI to track curriculum development over time and strengthen vertical progression across year groups.
Welcome to AI for Teachers, a 12-part series designed to help you plan smarter, teach better, and make your workload more manageable. Whether you’re new to AI or already exploring what it can do, this series will guide you step by step with real examples, practical tools, and research that matters.
🧭 This is not the only way to use AI in education. The possibilities are endless. This post is simply designed to show you one approach that might work for you, your learners, and your setting.
In this post, we’re moving from what we teach to how it builds. Progression planning is more than content coverage. It’s about designing a journey that helps students deepen, revisit and connect ideas over time.
That’s why progression is at the heart of curriculum design. But tracking it, especially across multiple year groups or subjects, can feel like solving a puzzle with missing pieces. AI can help fill in the gaps, spot inconsistencies and suggest the next steps that might not be immediately obvious.
✨ Whether you’re working within the British curriculum, CBSE, IB or Common Core, this approach flexes. The secret is in how you use your objectives and structure your prompts.
Why This Matters: From Research to Practice
💡 Dylan Wiliam – Embedded Formative Assessment (2011)
Wiliam shows that understanding how concepts progress across phases is key to planning responsive teaching that closes gaps.
How AI helps:
AI makes it easier to map a concept over time, identify areas of underdevelopment, and plan for more deliberate progression.
💡 Jerome Bruner – The Spiral Curriculum (1960)
Bruner argued that students learn best when topics are revisited with increasing depth and complexity.
How AI helps:
AI helps you visualise whether content spirals or plateaus. It makes it easier to see if a topic reappears and whether it's just repeated or truly extended.
🔍 A quick note on responsible use:
If your original curriculum descriptors are vague, AI will struggle to build a clear progression. Treat AI as a thinking partner. Your input quality still determines the value of the output.
Step-by-Step: Use AI to Track and Strengthen Progression
The five steps below will help you use AI to analyse how a skill, concept or strand develops across multiple year groups. These strategies can be used across subjects and adapted to suit any curriculum framework.
Step 1 – Choose a Strand to Focus On
The first step in using AI to support progression planning is selecting a single strand, concept, or skill that appears across multiple year groups. This strand becomes your focus for analysis. By narrowing in on one element of your curriculum, you create the conditions for meaningful insight. Trying to analyse everything at once can be overwhelming and unproductive. Instead, choose something that is important, commonly misunderstood, or foundational to success in your subject. It could be a skill like inference in English, a knowledge domain like place value in maths, or a scientific concept like forces.
Why this matters:
Trying to review too many strands at once can quickly become overwhelming. Focusing on one high-leverage strand allows you to go deeper and spot patterns in how learning develops or where it gets stuck.
Here are some powerful ways to select your strand:
Pick a skill or concept that recurs across multiple phases
Focus on areas where learners often show regression or gaps
Choose a strand already being reviewed in curriculum planning cycles
Use existing assessment data to target a weak progression area
What to watch for:
📌 Keep your focus tight and teachable
Choose just one strand that you can trace over time and that clearly links to national or school curriculum frameworks.
✅ Avoid analysing more than one strand at once
✅ Make sure your chosen strand appears across at least three year groups
✅ Check that you have curriculum descriptors available for that strand
Example prompt:
“I want to analyse how ‘place value understanding’ progresses from Year 2 to Year 6. Help me identify any gaps, unnecessary repetition, or areas that need more challenge.”
Step 2 – Create a Clear Curriculum Table
Now that you have identified the strand you want to explore, the next step is to organise your curriculum information into a structured format that AI can work with. This means setting up a clear table with one row per year group, each containing a short and specific descriptor. You can use curriculum objectives from national standards, school frameworks, or planning documents. This table acts as the input that AI will analyse. The clearer and more consistent your formatting and phrasing, the better the AI’s output will be.
Why this matters:
AI performs best with clean, structured input. A well-designed table lets the model analyse development, repetition and sequence. It also supports your own ability to quickly scan and reflect.
Here are some powerful ways to structure your table:
Use one row per year group
Include one clear descriptor per row
Add optional tags like skill type or difficulty
Keep language precise and consistent
What to watch for:
📌 Make the format clean and consistent
Messy or inconsistent formats can confuse AI and reduce the quality of the analysis.
✅ Use consistent year group labels (e.g. Y2, Y3, Y4)
✅ Avoid vague language in descriptors
✅ Keep each cell focused on a single skill or concept
Example prompt:
“Here’s a table of ‘scientific enquiry’ objectives from Years 4 to 8. Can you identify how the skill develops over time, and highlight any year that lacks a development step?”
Step 3 – Use AI to Spot Patterns and Progression Gaps
Once your table is built, you can now prompt AI to review how the strand progresses over time. The goal here is to use AI to help identify common issues such as repeated skills that do not build in complexity, objectives that leap too far too quickly, or phases where the concept is entirely missing. You are asking AI to act as a second pair of eyes—helping you notice problems that may be hidden when you're used to working closely with the content. This diagnostic step provides the foundation for all the improvements you will make later.
Why this matters:
Curriculum progression issues are often hidden in plain sight. AI helps you notice where objectives do not build logically or where opportunities for extension or review are missed.
Here are some powerful ways to analyse progression with AI:
Ask it to highlight repeated skills without development
Prompt it to identify skill jumps between years
Use a taxonomy lens (e.g. Bloom’s or SOLO) to compare difficulty levels
Ask for a developmental label on each descriptor (emerging, secure, mastery)
What to watch for:
📌 Tell AI exactly what kind of progression you want it to check
Be specific in your language to get more useful feedback and avoid generic responses.
✅ Ensure your table is clearly formatted
✅ Name each year group explicitly
✅ Give examples of what constitutes good progression in your prompt
Example prompt:
“Review this writing composition strand from Year 3 to Year 9. Identify any learning objectives that repeat without progression, or where the jump in skill level is too steep.”
Step 4 – Visualise Progression with a Gantt Chart
With the gaps and patterns identified, the next step is to turn your findings into a visual overview. A progression chart, particularly a Gantt-style timeline, makes it easy to see how a concept develops over time, where overlaps occur, and where important opportunities are missed. This is particularly useful when working with colleagues, curriculum leads or during moderation meetings. Visualising the progression helps turn the abstract into something more concrete, supporting better team discussions and decision-making.
Why this matters:
Visual representations make curriculum maps easier to understand. A progression chart lets you see at a glance where skills are introduced, developed or neglected.
Here are some powerful ways to use AI for visualisation:
Request a timeline or flow diagram with year group labels
Colour-code skill stages (e.g. developing, secure, mastery)
Map overlapping or parallel strands for comparison
Use labels to note where review or challenge is built in
What to watch for:
📌 Prioritise clarity over complexity
Too much colour or detail can distract from the purpose. Keep the focus on flow and gaps.
✅ Ask for a simple format first and refine later
✅ Use visuals as working drafts, not final products
✅ Review the AI’s labels for accuracy before sharing
Example prompt:
“Turn this progression of reading skills from Year 2 to Year 8 into a Gantt-style visual timeline with colour-coded stages of development.”
Step 5 – Chain Prompts to Improve or Fill Gaps
The final step is about refining and improving the sequence using AI. Now that you can clearly see how your strand develops and where problems lie, you can begin to work with AI to rewrite vague objectives, fill gaps in learning, and adjust the pitch of specific year group statements. This is the most interactive and creative part of the process. You are no longer just analysing, you are co-planning and strengthening your curriculum, with AI acting as a responsive and tireless partner.
Why this matters:
Even when sequencing is correct, objectives can still be vague or uneven. Chaining prompts lets you work with AI to improve clarity, stretch, or scaffolding within your progression model.
Here are some powerful ways to refine objectives using AI:
Ask AI to rewrite vague objectives at three levels of difficulty
Use Bloom’s or SOLO verbs to guide improvements
Prompt for bridging skills where gaps exist
Request scaffolds or extension outcomes for each phase
What to watch for:
📌 Use chained prompts to go deeper
The first answer is rarely the best one. Use follow-ups to focus, refine and enhance.
✅ Compare AI suggestions to your curriculum language
✅ Check that revised objectives remain age-appropriate
✅ Keep the overall flow of the strand in mind while adjusting detail
Example prompt:
“Revise this sequence of history enquiry objectives so each year builds in complexity. Use the verbs from Bloom’s taxonomy to guide the rewrite.”
Teacher Voice
This week’s example comes from a KS3 Science lead working on Forces.
“I used AI to map ‘Forces’ from Year 7 to 9 and realised Newton’s Laws were only introduced in Year 8. There was no challenge or application in Year 9. We created a new investigation sequence—real-world problems like car crashes and rocket launches. Suddenly, the strand made sense.”
Challenge: Step It Up
📊 Create a Gantt-style progression map
Pick one strand and map it across 5+ year groups. Use AI to visualise when it appears, how it builds, and what’s missing.
✏️ Refine vague objectives
Prompt AI to rewrite one objective at three levels (introductory, developing, mastery). Use these in your department reviews.
🧠 Spot and address drop points
Ask AI to flag three likely “progression risks” where learners may get stuck. Build re-teach tasks or recap points at those stages.
Reflect and Share
💬 Where do your learners lose momentum in a key strand? Could clearer progression planning and AI support to help reduce that drop?
Try building and refining a progression strand this week. Share your chart with a colleague or tag us to feature your version in an upcoming post.
Resources to Support You
🆓 Free Resource
Skill progression prompt pack + visual Gantt chart template
🔐 Paid Subscriber Exclusive
Progression Toolkit
Editable vertical progression tracker (Excel + visual version)
Auto-analysis GPT prompt set
Example strand maps (Maths, Science, English)
Troubleshooting guide for Sheets + GPT plugin
🎓 Available now in your subscriber dashboard
AI for Teachers – Blog Series
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📅 Coming next: Localise Your Curriculum – Adapting Content with AI
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