For curriculum leaders
Sixteen technologies, taught as one connected discipline.
NASCA is not an AI programme with a STEAM label on it. It is a full technology curriculum, written grade by grade, taught in a lab, and assessed on work the child actually produced.
Quick answer
The NASCA curriculum covers sixteen technology sub-streams from Grade 1 to Grade 12, delivered through four programme pathways. The core lab programme runs thirty sessions a year, per grade, per division, one class a week of 40 to 60 minutes, and is certified at the end of the year.
Every sub-stream is mapped to CBSE, ICSE, IB, Cambridge, UAE MOE, Common Core and NGSS, and assessed on the same six parameters.
The sixteen sub-streams
A school can run all of them across the grades, or pick one and go deep for a year. The list is deliberately wide, because a child who only meets robotics never finds out they were going to be brilliant at data.
- 01Artificial Intelligence
- 02Data Science and Analytics
- 03Coding and Programming
- 04App Development
- 05Robotics and Mechatronics
- 06Sensors and Actuators
- 07Mathematical Applications in Robotics
- 08Electronics
- 09Internet of Things
- 10Computational Thinking
- 11Design Thinking and 3D Technology
- 12Backyard Science
- 13Digital Technologies
- 14Cyber Security
- 15Blockchain
- 16Quantum Computing
Programme pathways
Four ways schools run NASCA.
STEAM Curriculum for Maker Space Labs
The core programme most schools begin with.
- 30 sessions a year, per grade, per division
- One class a week, 40 to 60 minutes
- Skill progression within the year, concept progression across grades
- Certified at the end of each academic year
Domain Specialisation for K-12
One domain, followed all year, taken deep.
- A single sub-stream chosen by the school or the child
- Weekly build cycles rather than topic sampling
- Capstone project presented to a live panel
- Assessed on the same six parameters as the core programme
School Full Integration Programme
STEAM wireframed into every subject, not parked in a club.
- Subject teachers trained to carry STEAM inside their own lessons
- Cross-subject units mapped to the school calendar
- Lab, timetable and teacher-load planning done with your academic team
- Whole-school reporting rather than a single lab report
Domain Specialisation for Higher Education and Professionals
The same rigour, written for adults with a deadline.
- Cohort based, mentor led, project first
- AI, data science, robotics and cyber security tracks
- Portfolio work that survives an interview
- Certification recognised by the World STEM Federation
Core verticals by grade band
What a child meets, and when.
Grades 1 to 5
- Backyard Science
- Computational Thinking
- Design Thinking and 3D Technology
- Coding and Programming
- Electronics
- Robotics basics
Sensory first. Children build, test and explain before a single line of syntax is asked of them.
Grades 6 to 10
- Artificial Intelligence
- Data Science and Analytics
- Robotics and Mechatronics
- Sensors and Actuators
- Internet of Things
- App Development
- Digital Technologies
The years where a project stops being a craft activity and starts being engineering.
Grades 11 and 12
- Generative AI
- Cyber Security
- Quantum Computing
- Blockchain
- Neuroscience
- Mathematical Applications in Robotics
Frontier subjects taught honestly, with their limits stated as clearly as their promise.
The NASCA AI vertical, Grade 1 to 12
Six technical domains. One spiral that revisits and deepens.
AI logic is taught before coding syntax, so a Grade 2 child can reason about how a machine sorts, guesses and gets things wrong long before they write a program.
AI Awareness and Intelligent Systems
What AI is, where it already lives, and what it cannot do. Age-calibrated examples from search, vision and speech.
Perception and Representation
How machines see and hear. Pixels, sound waves, features, and the jump from raw data to something a model can use.
Data Science and Statistical Literacy
Collect, clean, summarise, visualise. Sampling, correlation, and the habit of asking what the data does not say.
Machine Learning Models
Supervised and unsupervised learning, evaluation, and models students train with their own data.
Natural Interaction and Generative AI
Language models, prompt design, multimodal work, and reading an output critically instead of trusting it.
Responsible and Ethical AI
Bias, fairness, privacy, attribution and impact, carried through every grade rather than bolted on at the end.
Pedagogical rationale
Why the lesson looks the way it does.
Inquiry based
Every session opens with a question the child cannot answer yet.
Project based
The evidence of learning is a thing that works, not a worksheet.
Interdisciplinary
Maths, science, art and language show up inside the same build.
Life skills
Collaboration, time-boxing, giving and taking critique, presenting under questions.
Maker centric
Hands on hardware and software in the same room, every week.
Bloom mapped
Lesson structure moves from recall to create, and the assessment follows it.
How we know it worked
Two assessments a year, six parameters, one cumulative score. We publish the full rubric so a school can read exactly how a child is marked before they sign anything.
Read the assessment and certification modelFramework coverage matrix
Full coverage. Partial coverage.
| NASCA sub-stream | CBSE (India) NEP 2020 aligned | ICSE (India) ICSE syllabus | IB PYP/MYP Inquiry units | Cambridge IGCSE Stage 1 to 9 | MOE (UAE) Year 1 to 12 | KHDA / ADEK Inspection ready | KSA Vision 2030 MoE aligned | Common Core (US) K-12 standards | NGSS (US) Science standards |
|---|---|---|---|---|---|---|---|---|---|
| Artificial Intelligence | |||||||||
| Data Science and Analytics | |||||||||
| Coding and Programming | |||||||||
| App Development | |||||||||
| Robotics and Mechatronics | |||||||||
| Sensors and Actuators | |||||||||
| Mathematical Applications in Robotics | |||||||||
| Electronics | |||||||||
| Internet of Things | |||||||||
| Computational Thinking | |||||||||
| Design Thinking and 3D Technology | |||||||||
| Backyard Science | |||||||||
| Digital Technologies | |||||||||
| Cyber Security | |||||||||
| Blockchain | |||||||||
| Quantum Computing |
Sample documents
Scope and Sequence, full PDFs
One document per band. Each shows the term-by-term progression of outcomes, anchor projects and assessment moments.
Questions we get asked
How many sessions does the NASCA STEAM curriculum run in a year?
Thirty sessions a year, per grade, per division. One class a week of 40 to 60 minutes, with skill progression inside the year and concept progression across grades.
Is NASCA an AI programme with a STEAM label on it?
No. NASCA runs sixteen technology sub-streams as one connected discipline. AI is one vertical inside it, with its own Grade 1 to 12 progression.
Which curriculum frameworks does NASCA map to?
CBSE, ICSE, IB PYP and MYP, Cambridge IGCSE, UAE MOE with KHDA and ADEK, KSA Vision 2030, Common Core and NGSS.
How are students assessed?
Two assessments a year, an MCQ written paper and a project presentation with live questions, both scored on six parameters. Scores are cumulative and lead to an annual marksheet, report card and level-based certification.