AI Curriculum for British Schools in Sharjah
SPEA supervises all private schools in Sharjah, including British-curriculum schools, so school leadership needs lessons that run well and records that show what happened in class. Our AI Curriculum for British Schools in Sharjah delivers both, from Year 3 through Year 13.
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A Year 5 Lesson with Blocks and Micro:bit
- Opening: The teacher projects our adjustable presentation and explains the task, using the lesson plan to keep the timing.
- Task: The class opens AI Cloud Lab in a browser. The teacher has assigned the task in one click, so every student sees the same starting point.
- Build: Students arrange blocks of code, run them and watch a micro:bit respond. When a program fails, they change one block and run it again.
- Second look: A student who needs another explanation replays a reference video.
- Submission: Each student submits the work. AI Cloud Lab marks it automatically, and the teacher checks the marks before sharing feedback.
- Review: The teacher opens one or two submissions on the board, so the class sees what worked and what did not.
- Afterwards: The class report shows who completed the task and how each student scored, and that picture decides what the next lesson revisits.
Our Year 7 Lesson, from Blocks to Arduino and Python
- Class: Students aged eleven and twelve, moving from blocks to Arduino and Python.
- Wiring: Students connect a sensor and an LED to an Arduino board.
- Code: They write a short Python or Arduino program that reads the sensor and decides when the LED switches on.
- Test: They change the sensor reading and check that the LED responds as planned.
- Submission: The code goes into AI Cloud Lab, and the teacher reviews the automatic marks.
- Report: The teacher sees which students completed the task and which need another go.
- Next step: Students who finish early pick a project from the project pool.

A Year 9 Lesson in the AI Curriculum for British Schools in Sharjah
Demonstration
A short speech recognition program turns a spoken phrase into text, and the class watches it work.
Student Program
Each thirteen- or fourteen-year-old writes a small Python program that responds to the words it recognises. The work runs in our AI Cloud Lab without any installation.
Saved Work
A program started on Monday can be improved on Thursday, because the platform keeps the code and the feedback together.
Comparison
The class checks which phrases the program recognises and which it misses, then discusses clearer recording or a larger set of examples.
Our Three Sample Lessons Compared
| Lesson element | Year 5 | Year 7 | Year 9 |
|---|---|---|---|
| Main tools | Blocks and micro:bit | Arduino, sensors and actuators | Python and AI topics |
| Student task | Arrange blocks and watch a board respond | Wire a sensor and write code for it | Write a program that responds to recognised speech |
| Class finish | One or two submissions shown on the board | The LED checked against the sensor reading | Recognised and missed phrases compared |
| Evidence for the teacher | Marked submission and class report | Marked code beside the wiring result | Code and results shown together |
| Pattern in every year | Task, build, marked submission, review | Task, build, marked submission, review | Task, build, marked submission, review |
What the AI Curriculum for British Schools in Sharjah Gives Leadership
| What leadership needs to show | Where it comes from in our programme |
|---|---|
| How each class is progressing across a term | Performance insights in AI Cloud Lab |
| How a year group performed on a unit | Multiple reports and analysis |
| Results of a practical assessment | The lab exam module |
| What students have built | The project pool and Digital Fest entries |
| Where students need more practice | Quiz and lab exam results in AI Cloud Lab |
| How teachers are developing | UK-certified courses, with training for teachers |
| A student's own work behind a class figure | The same platform, from a year group view down to a single submission |
Our Performance Insights in a Computing Department Meeting
- Prepare: The head of computing opens our performance insights for each class in a year group.
- Read: The figures show how students scored on a unit and where results are lower than expected.
- Decide: A class with lower scores on a Python unit gets a review lesson. A class with strong results moves to a larger project from the project pool.
- Follow: Each student's marks appear beside the code behind them, so the conversation stays on the work itself.
Our Lab Exams for the Upper Years
- Practical: The lab exam module is used for practical computing assessments in the upper years.
- Set-up: The teacher builds the exam in AI Cloud Lab and assigns it to the right classes.
- Marking: The platform marks the work as students finish, and the teacher then confirms and shares the outcome.
- Hardware: Any computer with a browser can host an exam.
- Familiar: The editor, the run button and the feedback screen are the ones students have used since Key Stage 2.
- Records: Results join the other class records in the same place.
Larger Builds for Years 10 to 13 in the AI Curriculum for British Schools in Sharjah
Raspberry Pi and IoT
A student connects a sensor to a small computer, sends its readings to a screen and writes the code that decides what happens next.
Language and Machine Learning
Natural language processing and machine learning appear as bigger projects, each tested on examples the model has not seen.
Project Pool
Our project pool gives students who choose their own direction a project to start from.
Digital Fest
A finished project can go forward to Digital Fest.

How We Support Teachers around Each Lesson
Frequently Asked Questions (FAQs)
Get Started
Schedule a live walkthrough of our Year 5, 7, and 9 sample lessons on the AI Cloud Lab platform. Our team will show how the AI Curriculum for British Schools in Sharjah turns marked work into actionable class reports for school leadership.
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