Ei ASSET AI & Digital Thinking

Mapped to the CBSE CT & AI competencies

Each CBSE competency, and how ASSET measures it as the demand rises across grade bands
Computational Thinking ~45% Artificial Intelligence ~35% Digital Literacy ~20%
Build your view
Click any grade to show or hide its column. Keep two or more side by side to compare across bands. At least two grades always stay on.
Grades
Domains
CBSE runs from Class 3; the AI strand enters at Class 6. ASSET is recall-free and assesses AI reasoning from Grade 3. Each cell shows example ASSET questions and contexts for that band. Blank cells are competencies CBSE has not introduced yet.
CBSE competencyASSET skill that measures it Grades 3 to 4 Grades 5 to 6 Grades 7 to 8 Grades 9 to 10beyond current CBSE scope
Computational Thinking
DecompositionPattern RecognitionAlgorithmic Thinking
  • Jungle fruit party: each guest eats only fruits they like and needs three to feel full
  • Draw a house where roof, windows and door are each a different shape
  • A matchstick equation that doesn't balance: which sticks to remove
  • Fill the missing steps when only the start and end are shown
  • Invented chatbot words (Crumblerific, Plantification): which one has no real root
  • Decode by splitting a compound word or sequence into parts
  • Work backwards from a known end state to the start
  • Handle nested, multi-rule structures
Pattern RecognitionPattern Recognition
  • A robot sorts images into Stripes, Dots or Everything-else: which is misplaced
  • A shape sequence rotates and grows: what comes next
  • Find the rule from before-and-after pairs, apply it to a new shape
  • Place objects in a 2D table by two properties
  • A cipher shifts each letter by its position (CHILD becomes DJLPI): encode RIVER
  • AI tokenisation: which way the words split
  • Learn a notation taught in the question; read a diagram into notation and back
Abstraction (CBSE frames it spatially)Spatial ReasoningPattern RecognitionG5 up, some papers; via Pattern Recognition at G3-4
  • Mentally rotate and flip a shape to match the pattern
  • Fit the pieces into a grid
  • Fold, cut and unfold paper: predict the result
  • Mirror reflections
  • Stacked shapes seen from the top: order them bottom to top
  • Rotate cards to bring all the stars to the centre
  • Multi-step 3D transformations with measurement constraints
Algorithmic ThinkingAlgorithmic Thinking
  • Relay action game: each player repeats the last action, who got it wrong
  • Popcorn 4 min, lemonade 2 min, started together: when are both ready
  • Order matters: A then B vs B then A; predict a loop's result
  • Block code: which blocks draw the given pattern
  • Conditional golf: IF moon go right, ELSE go up, which layouts reach the goal
  • Move, Fill-dot and Repeat blocks: what grid is drawn
  • Trace pseudocode with variables and arithmetic
  • Reverse a procedure to recover the start state
Artificial Intelligence CBSE from Class 6; ASSET assesses AI reasoning from Grade 3
What AI is and how it worksAI Foundations / Technologies
  • A device's parts decide what it can do (mic hears, camera sees)
  • Images shown as number grids; brightness adds to each value
  • A rule-based sorter classifies a new object, even when 'wrong' in real life
  • Two chatbots guess a missing word: reason how each one predicts
  • Detection (is something there) vs identification (what is it)
  • Which tasks need a learning AI versus a fixed rule
  • Number representations, and how a swapped value changes the output
  • An AI 'temperature' setting trades predictability for creativity: pick the right one
  • Compare two ranking algorithms on the same data
AI as algorithm / neural networksAI TechnologiesCBSE Class 8
  • Neural-network nodes each detect a digit part: recognise a 9 when exactly two fire
  • Extended node sets: reason how layered detectors combine into a decision
AI methodologies, how AI learnsAI Training & Learning
  • Self-learning maze robot, +1 for the exit and -1 for a wall: what it does in a new maze
  • Which features help a model learn versus add noise
  • An AI draws watches almost always at 10:10: best explanation is the training data
  • Predict what a model trained on one era gets right and wrong
  • A model trained to Sep 2021: which March 2022 questions it can answer
  • How a recommender's criteria change over time
Data for AIData AnalysisAI Training & Learning
  • Read a table, cross-reference rows and columns, apply a condition
  • Test values against two numeric conditions at once
  • Tell a warranted conclusion from a guess
  • A bubble map of fossil-fuel power: which statement is true
  • The minimum prompt sequence to clean a table and chart it
  • Combine frequency, duration and recency to explain a recommendation
  • Honest versus cherry-picked reading of the same data
AI project cycleAll four AI skillsscoping and deployment not assessed
  • The self-learning robot stands in for the modelling and training stages
  • Clean and chart a messy dataset (the data stage)
  • A resume-rating bias study, then retrain on balanced data (evaluation and fix)
  • Find the root cause of a failure and choose a proportional fix
Directing AI / promptingPrompt EngineeringPre-Prompt Engineering at G3-4
  • Which sentence makes the chatbot draw the right picture
  • Pick the clearest instruction for a birthday-card AI
  • Choose the prompt most likely to produce the wanted poster
  • Reverse-engineer the steps behind a shown output
  • Spot the vague word in a climate-change prompt
  • Why a chatbot stays encouraging and on-subject: its rules
  • Spot the redundant step in a prompt sequence
  • Rebuild a sequence from its intermediate outputs
Bias, ethics and fairnessAI Limitations & Ethics
  • An AI can't fetch a toy and lacks your context: choose the safe option
  • High-stakes versus low-stakes AI errors: where a mistake really matters
  • Recreating a copyrighted photo with AI: right or wrong, and why
  • Resume-rating bias by gender: which claim the chart supports
  • Face-recognition gaps across groups: find the root cause and a proportional fix
Digital Literacy
Internet safety, passwords, authenticationUsing Digital Tools
  • A pop-up says you won a bicycle you never entered for: what's safe to do
  • CAPTCHA-type checks; put the steps in the right order
  • 'bl@ckSK' fails the password rules: the smallest change that passes
  • Give the right people view, comment or edit access
  • 2FA: what you enter the next day (same login, fresh OTP)
  • Cloud versus local storage trade-offs
  • Email to, cc and bcc visibility; respond to a breach when a password is reused
Data privacy and informed consentUsing Digital ToolsInformation & Media Literacy
  • Which personal details are unsafe to share with strangers online
  • Match file-sharing permissions to four different people
  • Why personalised ads appear: how browsing data is shared between services
  • Sharing with one site can pass your data to others; cookie and tracking awareness
Media and information literacyInformation & Media Literacy
  • Spot the clickbait headline that hides what the article is about
  • Which photo edit changes the meaning of the picture
  • Spot likely AI-generated content
  • Four headlines on a phone policy: which one shows bias
  • A class chat: which reactions count as bullying
  • A statistically implausible claim
  • A media report cherry-picks a study: choose the honest summary
On Grades 9 to 10: CBSE's framework defines competencies only through Class 8. The Grades 9 to 10 column shows ASSET already assesses the same threads at a higher level of demand, so a psychometrically validated assessment is ready for when CBSE extends the curriculum upward.
Ei ASSET AI & Digital Thinking · Educational Initiatives Mapping to CBSE CT & AI as operationalised in the Ei competency framework, March 2026