CBSE has officially designated Computational Thinking and Understanding Artificial Intelligence as the mandatory training theme for 2026–27 across Classes 3–8. PiyushAI Edtech is India's dedicated implementation partner for CBSE CT & AI.
CBSE has designated 'Computational Thinking and Understanding AI' as the official teacher training theme for session 2026–27 for all CBSE-affiliated schools — aligned to NEP 2020 and NCFSE 2023.
The CBSE Computational Thinking and Artificial Intelligence curriculum for Classes 3–8 is the most future-relevant reform in Indian school education in a generation — rooted in NEP 2020, NCFSE 2023, and the vision of making every Indian student AI-ready by Class 8.
"Mathematics and mathematical thinking will be very important for India's future and India's leadership role in the numerous upcoming fields and professions that will involve artificial intelligence, machine learning, and data science. Thus, mathematics and computational thinking will be given increased emphasis throughout the school years, starting with the foundational stage, through a variety of innovative methods."— National Education Policy (NEP) 2020, Para 4.25
CT builds the cognitive scaffolding that allows students to understand, interrogate, and collaborate with AI systems. By Class 8, students understand the AI lifecycle, work with no-code tools, and can evaluate AI systems critically.
CT is embedded across Mathematics, Science, Social Studies, and Language Learning — not a standalone subject. Schools don't need new slots; CT skills are woven into what teachers already teach.
The Preparatory Stage (Classes 3–5) is entirely unplugged. Pen, paper, and grids are sufficient. Accessible for every CBSE school in Tier 2, Tier 3 cities, and rural areas across Vidarbha and Maharashtra.
A student who masters the four CT pillars by Class 8 will be better at project management, decision-making, critical thinking, and evaluating information — regardless of their career path.
Schools organise District Level Deliberations (DLDs) on any of these 7 notified sub-themes. Each full-day DLD workshop earns teachers 6 CPD hours under CBSE Domain-II Professional Development.
Core CT concepts, what AI is, and preparing teachers and students for AI-ready school education
Developmental progression from unplugged puzzles in Class 3 to multi-step algorithmic reasoning by Class 8
Deep connections between mathematical thinking, CT, and how AI systems learn from mathematical patterns
Integrating Computational Thinking into Science, Social Studies, and Language Learning — Classes 6, 7, and 8
How AI is applied in healthcare, agriculture, transport, and education — making AI literacy relevant to students' lives
Rubrics, competency-based assessment, inquiry-based and project-based learning strategies for CT & AI classrooms
Age-appropriate AI ethics, algorithmic bias, data privacy, and responsible AI deployment from Class 6 onwards
The CBSE CT & AI framework for Classes 3–8 builds on four interlocking cognitive skills. Each pillar is a standalone competency and a direct building block for understanding how AI systems work — Pattern Recognition, Algorithmic Thinking, Decomposition, and Abstract Thinking.
Identifying regularities, trends, and relationships within data. This is the cognitive foundation of how machine learning algorithms work — every supervised learning system is a formalised, scaled-up pattern recogniser. From number sequences in Class 3 to real-world data sets by Class 8.
Class 6 Teacher Module →Designing precise, step-by-step instructions to solve problems. From grid movement puzzles in Class 3 to smart traffic light optimisation in Class 8 — the direct bridge between mathematical thinking, programming, and AI engineering.
Class 6 Teacher Module →Breaking complex problems into manageable sub-problems — the first strategy every AI engineer uses. CBSE teaches this through resource allocation, project planning, and multi-variable scheduling in Classes 6–8, directly mirroring how AI planning systems work.
Class 6 Teacher Module →Identifying what is essential and ignoring irrelevant details — the principle that makes AI systems generalise from training data to unseen situations. Class 8 students analyse how real AI systems abstract features, using X-ray analysis as a case study.
Class 6 Teacher Module →The CBSE Computational Thinking and AI curriculum spans two developmental stages aligned to NCFSE 2023 — each with distinct pedagogy, scope, and outcomes for Classes 3–5 and Classes 6–8.
Visual, game-like, and everyday contexts. All activities are pen-and-paper based — no computer lab required. Problems use 1–3 steps with plain language: rules, steps, clues.
Goal: Building CT thinking habits through puzzles — not programming lessons. Fully accessible to every CBSE school in India including rural and low-infrastructure settings.
Multi-step logic, conditional branching, iterative reasoning, cross-subject applications, and explicit AI connections. Students transition from following algorithms to designing, debugging, and evaluating them.
Classes 6, 7, and 8 add 20 dedicated AI Literacy hours per year — covering AI domains, data visualisation, algorithmic bias, ethics, the AI lifecycle, and no-code tools for Class 8.
| Class | CT Skill Areas | AI Literacy Focus | Project |
|---|---|---|---|
| 3–5 | Pattern Recognition, Algorithmic Thinking, Decomposition, Abstraction (Basic) | None — CT integrated into Math & TWAU | — |
| 6 | All four CT pillars (Advanced) | Intro to AI, data, ethics, AI vs programming | 1 interdisciplinary CT project |
| 7 | Advanced CT + applied problems | AI domains, data visualisation, algorithmic bias | 1 interdisciplinary project |
| 8 | Advanced CT + optimisation | AI lifecycle, ethics, no-code tools, model building | 1 AI project + formal presentation |
CBSE Notification TRG-02 defines three structured pathways for CBSE-affiliated schools to fulfil their Computational Thinking & AI training mandate. Each activity earns CPD hours under Domain-II.
CBSE schools in a district come together via the Sahodaya School Complex for a full-day offline workshop showcasing best and innovative practices in CT & AI teaching for Classes 3–8. NOT a project exhibition — a formal peer-learning forum. An Appreciation Committee scores case papers and selects top 3 for the CBSE CoE, with national-level papers reaching the National Teachers Conference 2026.
Lead schools organise specialised online or offline CT & AI sessions aligned to any notified sub-theme, facilitated by internal or external experts. Schools may also screen CBSE's educational videos on DD PM e-Vidya Channel CBSE-15. Attendance records mandatory for CPD credit.
CBSE's Centres of Excellence (CoEs) conduct board-coordinated regional orientation programmes. Schools nominate teachers as per their CoE jurisdiction. Online registration required. Schedule announced by respective CoEs shortly.
From curriculum audit to certified teachers — a practical, structured pathway to successful CT & AI rollout in your CBSE school for session 2026–27.
Map your existing Mathematics, Science, and Computer syllabus against the four CT pillars. In most CBSE schools, CT elements are already present — just unlabelled. Identifying overlaps reduces teacher anxiety and eases adoption before the session begins.
Generic worksheets are insufficient. PiyushAI Edtech provides chapter-by-chapter workbooks with progressive difficulty, scaffolding for struggling learners, and extension tasks for advanced students — fully aligned to CBSE CT & AI outcomes 2026–27 and available in English, Hindi, and Marathi.
A 40-hour blended certification programme for Math, Science, and Computer teachers covering all four CT pillars, AI literacy, and pedagogy strategies. Builds teacher confidence as CT facilitators — not AI researchers — using inquiry-based and project-based learning methods aligned to CBSE DLD evaluation criteria.
Move from marks-based right/wrong evaluation to rubrics that assess whether students can articulate their CT reasoning. Authentic assessment tools aligned to the CBSE Format F4 evaluation criteria — covering demonstrated impact, novelty, inclusivity, scalability, and replicability.
Build conceptual foundations physically before going digital. Classes 3–5 use pen-and-paper exclusively. For Classes 6–8, no-code tools and block-based programming environments deepen engagement once CT foundations are secure — preventing students from treating it as "just computer time."
Common questions from CBSE school principals, academic coordinators, and teachers about Computational Thinking and AI implementation for session 2026–27.
CBSE has introduced the Computational Thinking and Artificial Intelligence (CT & AI) curriculum for Classes 3 to 8 from session 2026–27, in line with NEP 2020 and NCFSE 2023. It develops four CT skills — Pattern Recognition, Algorithmic Thinking, Decomposition, and Abstract Thinking. Classes 6, 7, and 8 additionally receive 20 hours per year of AI Literacy covering AI concepts, data, domains (computer vision, NLP, recommendations), ethics, bias, and no-code AI tools for Class 8. The curriculum develops logical thinking, systematic problem-solving, and ethical AI understanding from an early age.
CBSE Training Notification No. TRG-02 dated 09.04.2026, signed by Director (Training) Manoj K. Srivastava, officially designates 'Computational Thinking and Understanding AI' as the teacher training theme for session 2026–27 for all CBSE-affiliated schools. It mandates three structured activities: (1) District Level Deliberations (DLD) workshops — 6 CPD hours under Domain-II; (2) Expert-Led Talks — 3 CPD hours; and (3) Regional Workshops/Orientations by CBSE Centres of Excellence — 6 CPD hours at ₹700. Schools must organise or participate in at least one activity.
The 7 official CBSE sub-themes for CT & AI District Level Deliberations are: (1) Foundations of Computational Thinking and AI Readiness; (2) From Play to Abstraction — Progressive Pedagogy for CT (Gr 3–8); (3) Mathematics as the Cornerstone of CT and AI Readiness; (4) Interdisciplinary Connections: CT Across Subjects at Middle Stage; (5) AI in Real-World Contexts; (6) Assessment and Pedagogy in CT and AI; (7) Ethics and Responsible Use of AI. Multiple DLDs on different sub-themes can be organised in the same district.
No. The CBSE CT curriculum for Classes 3–5 (Preparatory Stage) is entirely unplugged — pen, paper, and grids are sufficient. Grid movement puzzles, step-by-step planning exercises, and pattern games require zero devices. This makes CBSE CT & AI accessible to all schools in Tier 2 cities, Tier 3 towns, and rural Maharashtra including the Vidarbha region. Technology (no-code tools, block-based programming) is introduced in Classes 6–8 once conceptual foundations are secure.
A DLD is a voluntary, one-day offline workshop where CBSE schools in a district present case papers on their best innovative practices in CT & AI teaching across Classes 3–8, usually organised through the Sahodaya School Complex. It is NOT a project exhibition — it is a formal peer-learning forum. Each presenter gets 25 minutes (20 min presentation + 5 min Q&A). An Appreciation Committee (1 external CT/AI expert + 2 principals/teachers) scores all papers out of 100 marks using 9 criteria (Format F4). Top 3 papers are forwarded to the CBSE Centre of Excellence — the best papers nationally are presented at National Teachers Conference (NTC) 2026.
PiyushAI Edtech offers: (1) A 40-hour blended certification programme for Math, Science, and Computer teachers covering all four CT pillars, AI literacy, ethics, and pedagogy — available in English, Hindi, and Marathi; (2) Graded workbooks for Classes 3–8 aligned to CBSE CT & AI outcomes 2026–27; (3) Free school demo sessions for school leadership; (4) Full workbook preview for any class; (5) One-on-one curriculum rollout consultation. Contact: support@piyushai.com or 9423071961. Based in Amravati, Maharashtra — serving CBSE schools across Vidarbha and India.
CBSE pairs CT and AI because each CT pillar directly maps to how AI systems function: Pattern Recognition is what machine learning does — every supervised learning algorithm is a formalised pattern recogniser. Algorithmic Thinking is what AI researchers produce — training algorithms, search algorithms, optimisation routines. Decomposition is how AI systems are engineered — data pipelines, model components, evaluation frameworks. Abstraction is what makes AI generalise — an AI that recognises a cat has abstracted the essential features from training images. Teaching CT alongside AI literacy creates students who understand, question, and can improve AI systems — not just use them.
Piyush Wairale is the founder of PiyushAI Edtech with an M.Tech from IIT Madras (2021) and 5+ years of dedicated CT & AI teaching experience. He served as an instructor at the IIT Madras BS Degree Programme — the same expert ecosystem connected to the CBSE CT & AI curriculum framework. He is also a Microsoft Learn Educator, AWS Academy Educator, NPTEL Educator, GATE DA Educator, and has industry experience at Volkswagen. PiyushAI Edtech is a Maharashtra-based curriculum specialist purpose-built exclusively for the CBSE CT & AI curriculum for Classes 3–8 — not a generic content platform, but a dedicated school implementation partner.
The Appreciation Committee scores each DLD case paper out of 100 marks. Top 3 papers per district go to CBSE CoE — eligible for the National Teachers Conference 2026 (1st: oral presentation, 2nd & 3rd: poster presentation).
🏆 Best 3 case papers per sub-theme nationwide → National Teachers Conference 2026 · 1st: Oral Presentation · 2nd & 3rd: Poster Presentation
Piyush Wairale brings a rare combination: deep academic pedigree from IIT Madras, real-world industry experience at Volkswagen, Microsoft, and AWS, and grassroots classroom experience spanning school and higher education platforms including NPTEL and Skillable.
Having taught at the IIT Madras BS Degree Programme — the expert ecosystem connected to the CBSE CT & AI curriculum framework — PiyushAI Edtech has uniquely authoritative insight into what this curriculum truly demands and how to deliver it effectively across CBSE schools in Maharashtra, Vidarbha, and India.
PiyushAI Edtech is a Maharashtra-based curriculum specialist purpose-built for CBSE CT & AI for Classes 3–8. Not a generic content platform — a dedicated implementation partner who understands the CBSE framework, NEP 2020 pedagogy, and the real-world challenges of school implementation in Amravati, Vidarbha, and beyond.
Live demo of CT & AI workbooks for your leadership team or academic coordinator — no commitment required.
Complete sample chapter for any class — fully aligned to CBSE CT & AI outcomes 2026–27.
Blended training for Math, Science & Computer teachers — certification-ready for CBSE DLD presentations.
One-on-one consultation to plan your school's CT & AI implementation for 2026–27.