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CBSE’s AI curriculum — lofty goals, little clarity

10 Apr 2026
2 min

CBSE's New Curriculum on Computational Thinking and Artificial Intelligence

The Central Board of Secondary Education (CBSE) has introduced a new curriculum focusing on Computational Thinking (CT) and Artificial Intelligence (AI) for classes III to VIII, set to be implemented in the 2026-27 academic session.

Objectives and Aims

  • Develop capacities in learners for logical thinking, problem-solving, and pattern recognition.
  • Enhance understanding of AI's role and application in everyday life.

Curricular Concerns

While the curriculum aims to address safety, privacy, and critical thinking concerns related to AI use among children, questions remain about its practical effectiveness.

Curriculum Structure

  • Classes III to V: Introduction to computational thinking.
  • Classes VI to VIII: 
    • Advanced CT and foundational knowledge of AI.
    • Emphasis on AI ethics.

Learning Outcomes and Challenges

  • Class VI: Identify differences between machine and human intelligence, understand automation vs. AI, and differentiate AI methodologies like supervised and unsupervised learning.
  • Class VII: Differentiate predictive techniques such as regression, classification, and clustering.
  • Class VIII: Apply no-code tools to solve real-world problems and understand AI bias.

There is skepticism over whether children can grasp such complex AI concepts and methodologies effectively.

Integration and Educational Challenges

The curriculum attempts to integrate CT with existing subjects like Mathematics, but successful integration with Science and Social Studies remains under review globally.

  • Claims about CT being the foundation for AI are contested, given the different nature of symbolic and neural network-based learning.
  • Insufficient research exists on teaching AI at primary and middle-school levels.

Challenges in Implementation

  • The digital divide and lack of teacher preparedness in AI and digital tools pose significant challenges.
  • Potential for increased information overload without addressing core issues of AI use by middle-school students.

The views expressed are those of a professor from Azim Premji University, Bengaluru, and reflect personal opinions.

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Neural Network-Based Learning

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