The Cleanest Village – Class 4 Computational Thinking | Chapter 9 Notes & Worksheet

Class 4 · Computational Thinking

🌿 The Cleanest Village
How CT Helps Keep Our World Clean!

Chapter 9 · CBSE AI & Computational Thinking · Code 417

📚 Class 4 🧠 Computational Thinking 🏡 Real-Life Application ⏱ 40 Minutes

Class: 4

Subject: AI & Computational Thinking

Subject Code: 417

Chapter: 9 – The Cleanest Village

Bloom's Level: Understand → Apply

Difficulty: Easy to Medium

Time Required: ~40 Minutes

Blog: ailogicschool.blogspot.com

📖 Study Notes: The Cleanest Village

What is this chapter about?

This chapter tells the story of a village that wants to become the cleanest village in their area. The villagers use Computational Thinking (CT) skills to plan, organise, and solve their cleanliness problem — just like a computer scientist would solve a problem!

Think of villages like Mawlynnong in Meghalaya, known as "Asia's Cleanest Village." The people there work together using clever thinking and planning — which is exactly what CT is about!

🔑 Key Terms to Remember

DecompositionBreaking a big problem into smaller, easier parts.

Pattern RecognitionNoticing things that repeat or are similar.

AbstractionFocusing on only the important details; ignoring unnecessary information.

AlgorithmA step-by-step plan to solve a problem.

Data AnalysisLooking at information (data) to find useful answers.

🏡 How the Village Used Computational Thinking

1

Decomposition – Break the Big Problem

The village had a lot of garbage. Instead of panicking, they broke the problem into smaller parts: Who throws garbage? Where? How much? What type?

2

Pattern Recognition – Find Repeating Problems

They noticed that most garbage was near the market and temple on festival days. This is a pattern — it helps know when and where to focus cleaning.

3

Abstraction – Focus on What Matters

Instead of worrying about every single piece of garbage, they focused on the types of waste: wet waste, dry waste, and plastic. This helped plan separate bins.

4

Algorithm – Make a Step-by-Step Plan

They made a plan: (1) Place dustbins at every corner, (2) Assign cleanliness duties to each family, (3) Collect waste every morning, (4) Reward the cleanest lane each month.

5

Data Analysis – Check & Improve

They recorded how much garbage was collected each week on a tally chart. When numbers went down, they knew their plan was working!

📊 Indian Real-Life Connection

India's Swachh Bharat Abhiyan (Clean India Mission) uses the same kind of thinking — collecting data about open defecation, finding patterns, and making step-by-step plans for different states. That's Computational Thinking in action at a national level!

Even in our smart cities, AI-powered smart dustbins send a signal when they are full — so the garbage truck only goes when needed. That's an algorithm built into a machine!

📝 Summary

The villagers used all five steps of Computational Thinking to make their village clean. They decomposed the problem, recognised patterns, used abstraction to focus on what mattered, wrote an algorithm (plan), and used data to check results. You can use the same steps to solve problems in your school, home, or colony!

· · ·

✏️ Worksheet: The Cleanest Village

Bloom's: Remember, Understand, Apply Difficulty: Easy–Medium

Section A – Multiple Choice Questions (MCQs) (Circle the correct answer)

MCQ 1

Q1. What does "Decomposition" mean in Computational Thinking?

• a) Drawing a picture of the problem
• b) Breaking a big problem into smaller parts
• c) Ignoring the problem
• d) Writing a story about the problem

MCQ 2

Q2. The villagers noticed that most garbage appeared near the market during festivals. This is an example of:

• a) Algorithm
• b) Pattern Recognition
• c) Abstraction
• d) Decomposition

MCQ 3

Q3. A step-by-step plan to solve a problem is called:

• a) Pattern
• b) Data
• c) Algorithm
• d) Abstraction

MCQ 4

Q4. When the villagers decided to focus only on the type of waste (wet/dry/plastic) and ignore other details, they were using:

• a) Pattern Recognition
• b) Algorithm
• c) Abstraction
• d) Data Analysis

MCQ 5

Q5. Which government scheme connects to the idea of "The Cleanest Village"?

• a) Make in India
• b) Digital India
• c) Swachh Bharat Abhiyan
• d) Skill India

MCQ 6

Q6. Using a tally chart to record garbage collected each week is an example of:

• a) Abstraction
• b) Decomposition
• c) Pattern Recognition
• d) Data Analysis

MCQ 7

Q7. Mawlynnong village in Meghalaya is famous for being:

• a) Asia's Cleanest Village
• b) India's Largest Village
• c) India's Richest Village
• d) Asia's Greenest Forest

MCQ 8

Q8. Smart dustbins in smart cities send a signal when they are full. This is an example of an:

• a) Pattern
• b) Data table
• c) Algorithm inside a machine
• d) Abstraction rule

Section B – Fill in the Blanks

(Word Bank: Algorithm, Pattern Recognition, Decomposition, Abstraction, Data Analysis, Swachh Bharat)

1. Breaking a big cleaning problem into smaller tasks is called .

2. Noticing that garbage increases near the market every weekend is called .

3. Focusing only on the types of waste (wet, dry, plastic) and ignoring other details is called .

4. A step-by-step cleaning plan made by the village is an example of an .

5. Recording and studying garbage data from tally charts is called .

6. India's national cleanliness mission is called the Abhiyan.

Section C – Match the Column

Column A (CT Step)	Column B (Example from the Village)
A. Decomposition	1. Making a weekly cleaning schedule
B. Pattern Recognition	2. Separating waste into 3 types
C. Abstraction	3. Garbage spikes near the market on Sundays
D. Algorithm	4. Counting garbage bags collected per day
E. Data Analysis	5. Dividing the village into 10 cleaning zones

Answer Key: A–5, B–3, C–2, D–1, E–4

Section D – Short Answer Questions

Short Answer 1

Q1. Name any two types of waste the villagers sorted in the chapter. Why is sorting waste important?

_(Write 2–3 sentences)_

Short Answer 2

Q2. How did data analysis help the villagers know that their cleaning plan was working?

_(Write 2–3 sentences)_

Short Answer 3

Q3. Write one real-life example from your school or neighbourhood where you can use an algorithm to solve a cleanliness problem.

_(Write 3–4 sentences)_

🎯 Activity: Design Your Own Clean School Algorithm!

Imagine your school campus has become very dirty. Use the 5 steps of Computational Thinking to make a plan to clean it up!

Step 1 – Decomposition: List 3 places in school that are dirty.

1. _______________   2. _______________   3. _______________

Step 2 – Pattern Recognition: When does it get the dirtiest? (e.g., after lunch / after games)

Answer: _______________________________________________

Step 3 – Abstraction: What type of waste is most common? (Food waste / paper / plastic)

Answer: _______________________________________________

Step 4 – Algorithm: Write 4 steps to clean the school:

Step 1: _______________   Step 2: _______________

Step 3: _______________   Step 4: _______________

Step 5 – Data Analysis: How will you check if your plan worked? (Hint: count garbage bags / take photos before and after)

Answer: _______________________________________________

💡 Did You Know?

India's Swachh Survekshan survey uses AI and data analysis to rank cities on cleanliness! Cameras, citizen apps, and satellite images all collect data — which is then analysed using algorithms — to decide which Indian city is the cleanest each year. Indore has won the top rank multiple times. That is Computational Thinking working at city scale! 🇮🇳🤖

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CBSE Class 12 Artificial Intelligence Previous Year Questions (843) with Solutions — 2025-26

Are you preparing for the CBSE Class 12 Artificial Intelligence (Subject Code 843) board exam? Solving Previous Year Questions (PYQs) is the most effective way to understand the exam pattern, know which topics are asked repeatedly, and practise writing board-quality answers. In this post, we have compiled important PYQs from CBSE Board Exams 2023, 2024, and 2025 — with complete, marking-scheme-aligned answers. All content is based on the official CBSE curriculum for Class 12 AI (Code 843), Session 2025-26.

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📋 Class 12 AI (Code 843) — Previous Year Questions

Important PYQs with Answers | Board Exam 2023, 2024 & 2025 | Session 2025-26

📘 Class 12 🤖 Subject Code 843 ⭐ PYQs with Answers 🎯 50 Marks Theory ⏱️ 2 Hours 🆓 Free

Class	12
Subject Code	843 — Artificial Intelligence
Content Type	Previous Year Questions (PYQs) with Answers
Years Covered	2023 | 2024 | 2025 Board Exams
Theory Marks	50 Marks | 2 Hours
Practical Marks	50 Marks (Project + Viva)
Source	CBSE Board Exams | academic.nic.in

🎯 Why Solve PYQs?

• Understand the exact exam pattern and question types
• Know which topics are repeatedly asked every year
• Practice time management for 2-hour paper
• Learn how to write answers as per CBSE marking scheme
• Build confidence before board exams

📊 Exam Pattern — Class 12 AI (843)

50

Theory Marks

Written Exam

50

Practical Marks

Project + Viva

21

Total Questions

Attempt 15

2 hrs

Duration

Theory Paper

Section	Type	Questions	Attempt	Marks
Section A	Objective Type (MCQ/Assertion-Reason)	5	All 5	24
Section B	Subjective Type (Short/Long Answer)	16	Any 10	26
Total				50

📚 Syllabus Units — Class 12 AI (843) 2025-26

Part A

Employability Skills

Communication, Self-Management, ICT Skills, Entrepreneurial Skills, Green Skills

Unit 1

Python Programming – II

Advanced Python, Functions, File Handling, Libraries

Unit 2

Data Science Methodology

Data Collection, Analysis, Visualization, Capstone Project

Unit 3

Making Machines See

Computer Vision, Image Processing, CNN, Object Detection

Unit 4

AI with Orange Tool

Data Mining, Classification, Clustering, Visual Analytics

Unit 5

Introduction to Big Data

Big Data concepts, Hadoop, Analytics, Applications

Unit 6

Generative AI

GANs, VAEs, Neural Networks, Creative AI Applications

Unit 7

AI Project Cycle

Problem Scoping, Data, Modelling, Evaluation, Deployment

Unit 8

Ethics in AI

Bias, Privacy, Fairness, Responsible AI, AI in Society

🔘 Section A — Objective Type PYQs (MCQ & Assertion-Reason)

⚠️ Exam Tip: Section A has 5 questions — attempt ALL. No negative marking. MCQs carry 1 mark each. Assertion-Reason questions also carry 1 mark.

📅 Board Exam 2025

1

Which type of neural network is effective for processing visual data and uses a three-dimensional arrangement to extract features from images?

(a) Recurrent Neural Network (RNN)

(b) Convolutional Neural Network (CNN) ✓

(c) Generative Adversarial Network

(d) Simple Neural Network

1 Mark

Answer: (b) Convolutional Neural Network (CNN)
CNN uses convolutional layers to extract spatial features from images. Its 3D arrangement (height × width × depth) makes it ideal for image classification, object detection, and computer vision tasks.

2

Variational Autoencoders (VAEs) are designed to learn from data. What are their two main components?

(a) Generator and Discriminator

(b) Encoder and Decoder ✓

(c) Input and Output Layer

(d) Training and Testing Module

1 Mark

Answer: (b) Encoder and Decoder
VAEs have two main parts: the Encoder compresses input data into a latent space representation, and the Decoder reconstructs the data from that representation. Together they learn to generate new data similar to training data.

3

Assertion-Reason: Assertion (A): Social media posts and images are examples of structured data.   Reason (R): Unstructured data does not follow a predefined format.

(a) Both A and R are true, R is correct explanation of A
(b) Both A and R are true, but R is NOT the correct explanation of A
(c) A is false, R is true
(d) Both A and R are false

1 Mark

Answer: (c) A is false, R is true
Social media posts and images are unstructured data — not structured data. So Assertion A is FALSE. However, Reason R is TRUE — unstructured data indeed does not follow a predefined format like rows/columns.

📅 Board Exam 2024

4

Which step of the AI Project Cycle involves analysing data to discover hidden patterns and useful information?

(a) Problem Scoping

(b) Data Acquisition

(c) Data Exploration ✓

(d) Model Evaluation

1 Mark

Answer: (c) Data Exploration
Data Exploration is the 3rd step of the AI Project Cycle. It involves analysing collected data to discover hidden patterns, interesting insights, and useful information. Data is visualised in user-friendly formats like charts and graphs.

5

When a machine is able to mimic human traits and intelligence, it is said to be — (Assertion-Reason type)

1 Mark

Answer: Artificially Intelligent
When a machine mimics human cognitive traits such as learning, reasoning, problem-solving, perception and language understanding, it is called Artificial Intelligence. This is the fundamental definition of AI.

📝 Section B — Subjective Type PYQs

⚠️ Exam Tip: Section B has 16 questions — attempt ANY 10. Choose questions you are most confident about. Mix short and long answers for best marks.

📌 1 Mark Questions (Answer in 1 line)

📅 Board Exam 2025 & 2024

1

Define the term 'Data Features' in the context of AI and Data Science.

1 Mark

Answer: Data features are individual measurable properties or characteristics of a dataset used to analyse and build AI models. They provide context and information about the data (also called variables or attributes).

2

What is meant by 'Sustainable Agriculture' in the context of AI applications?

1 Mark

Answer: Sustainable agriculture is an environment-friendly farming approach that prevents excessive use of chemical fertilizers to protect soil health. AI helps make farming sustainable by predicting crop yield, water usage, and soil conditions.

3

Name the three fundamental layers of an Artificial Neural Network (ANN).

1 Mark

Answer: The three fundamental layers of an ANN are:
1. Input Layer — receives raw data
2. Hidden Layer(s) — processes and learns patterns
3. Output Layer — produces the final result/prediction

4

What is the role of a Discriminator in a Generative Adversarial Network (GAN)?

1 Mark

Answer: The Discriminator in a GAN acts as a classifier that distinguishes between real data and fake data generated by the Generator. It provides feedback to the Generator to improve its output quality.

📌 2 Mark Questions (Answer in 20-30 words)

1

Explain the difference between Supervised Learning and Unsupervised Learning with one example each.

2 Marks

Supervised Learning: The model is trained on labelled data (input-output pairs). The algorithm learns to map inputs to correct outputs.
Example: Email spam detection — emails are labelled as spam/not spam.

Unsupervised Learning: The model is trained on unlabelled data and finds hidden patterns on its own.
Example: Customer segmentation — grouping customers by buying behaviour without predefined labels.

2

What is NLP (Natural Language Processing)? Give two real-life applications of NLP.

2 Marks

NLP (Natural Language Processing) is a branch of AI that enables computers to understand, interpret, and generate human language (text and speech).

Real-life Applications:
1. Virtual Assistants — Siri, Alexa, Google Assistant understand spoken commands
2. Machine Translation — Google Translate converts text between languages automatically

3

Differentiate between Structured Data and Unstructured Data. Give one example of each.

2 Marks

Structured Data	Unstructured Data
Follows a predefined format (rows/columns)	No predefined format or organisation
Easy to search and analyse	Difficult to analyse directly
Example: Excel spreadsheet, SQL database	Example: Social media posts, images, videos

4

What is Computer Vision? Mention any two applications used in India.

2 Marks

Computer Vision is a field of AI that enables computers to interpret and understand visual information from images and videos, similar to how humans see.

Applications in India:
1. Aadhaar Face Authentication — facial recognition for identity verification
2. Traffic surveillance cameras — detecting vehicles, number plates, and traffic violations automatically

📌 3 Mark Questions (Answer in 40-60 words)

1

Explain the AI Project Cycle with its five steps. How does it help in building a real-world AI solution?

3 Marks

The AI Project Cycle is a systematic approach to building AI solutions:

Step 1 — Problem Scoping: Define the problem clearly — what AI needs to solve, who are the users, what data is needed.
Step 2 — Data Acquisition: Collect relevant, accurate data from various sources (sensors, surveys, internet).
Step 3 — Data Exploration: Analyse data to find patterns, remove errors, visualise trends.
Step 4 — Modelling: Select and train an appropriate AI/ML model on the data.
Step 5 — Evaluation: Test the model's accuracy and deploy it after validation.

This cycle ensures a structured, repeatable approach to building reliable AI solutions.

2

What is Big Data? Explain any three characteristics of Big Data (3 Vs).

3 Marks

Big Data refers to extremely large datasets that cannot be processed by traditional data management tools due to their size, speed, and variety.

Three Vs of Big Data:
1. Volume — Huge amount of data generated every second (e.g., millions of tweets, transactions)
2. Velocity — Data is generated at very high speed and needs real-time processing (e.g., stock market data)
3. Variety — Data comes in many formats: text, images, video, audio, structured and unstructured

3

A company is developing a smart security camera that identifies people and vehicles. Which AI domain is being used? Explain how it works.

3 Marks

AI Domain Used: Computer Vision

How it works:
1. The camera captures frames (images) continuously from the environment
2. A Convolutional Neural Network (CNN) analyses each frame
3. The model identifies and classifies objects — people, vehicles, etc. — by matching patterns learned during training
4. When an unknown person or suspicious vehicle is detected, an alert is triggered automatically

This uses Object Detection — a computer vision technique that locates and identifies multiple objects in an image in real time.

📌 4-5 Mark Questions (Detailed Answers)

1

Describe the structure of an Artificial Neural Network (ANN). Explain how it learns from data using the concept of weights and activation functions. (5 marks)

5 Marks

Structure of ANN:
An ANN is inspired by the human brain and consists of interconnected nodes (neurons) arranged in layers:

1. Input Layer: Receives raw data. Each neuron represents one feature/input variable.
2. Hidden Layer(s): One or more layers that process inputs. Each neuron applies a mathematical transformation.
3. Output Layer: Produces the final prediction or classification result.

How ANN Learns:
• Each connection between neurons has a weight — a numerical value that determines the strength of the connection
• Each neuron applies an Activation Function (e.g., ReLU, Sigmoid) to decide whether to pass the signal forward
• During training, the network compares its output to the correct answer and calculates error (loss)
• Using Backpropagation, the error is sent backwards through the network
• Weights are adjusted using Gradient Descent to minimise the error
• This process repeats over many iterations (epochs) until the network learns to make accurate predictions

2

What are ethical concerns in AI? Explain any four with examples from real life. (4 marks)

4 Marks

Ethical Concerns in AI:

1. Bias and Discrimination
AI systems can inherit biases from training data. Example: A hiring AI trained on historical data may unfairly reject women or minorities.

2. Privacy Violation
AI systems collect and analyse massive personal data without user consent. Example: Facial recognition cameras tracking citizens without permission.

3. Lack of Transparency (Black Box)
Many AI models cannot explain their decisions. Example: A bank AI rejects a loan application without giving any reason.

4. Job Displacement
AI automation replaces human jobs in manufacturing, banking, and customer service. Example: Chatbots replacing call centre employees.

4. Deepfakes and Misinformation
Generative AI creates fake images, videos, and voices. Example: Deepfake videos of politicians saying things they never said, spreading misinformation.

⭐ Most Important Topics — Asked Every Year

Topic	Unit	Frequency
AI Project Cycle (5 Steps)	Unit 7	⭐⭐⭐ Very High
Neural Networks (ANN, CNN)	Unit 3	⭐⭐⭐ Very High
Structured vs Unstructured Data	Unit 2	⭐⭐⭐ Very High
Supervised vs Unsupervised Learning	Unit 2	⭐⭐⭐ Very High
Generative AI (GANs, VAEs)	Unit 6	⭐⭐ High
Ethics in AI	Unit 8	⭐⭐ High
Computer Vision & NLP	Unit 3	⭐⭐ High
Big Data & its Characteristics	Unit 5	⭐⭐ High
Python Programming (functions, loops)	Unit 1	⭐⭐ High
Data Visualisation Tools	Unit 2, 4	⭐ Moderate

🔁 Quick Revision — Key Definitions

📌 Must-Know Definitions for Board Exam

• Artificial Intelligence: Technology that enables machines to mimic human intelligence — learning, reasoning, and problem-solving
• Machine Learning: A subset of AI where systems learn from data and improve without being explicitly programmed
• Deep Learning: A subset of ML using multi-layered neural networks to learn complex patterns
• CNN: Convolutional Neural Network — specialised for image and visual data processing
• GAN: Generative Adversarial Network — Generator + Discriminator working against each other to create realistic synthetic data
• VAE: Variational Autoencoder — Encoder + Decoder that learns to generate new data
• NLP: Natural Language Processing — AI that understands and generates human language
• Big Data (3 Vs): Volume, Velocity, Variety
• Data Features: Individual measurable properties of a dataset used to build AI models
• Overfitting: When a model learns training data too well and fails on new data

🇮🇳

💡 Did You Know?

India's UPI payment system uses AI and Machine Learning to detect fraudulent transactions in real time — processing over 10 billion transactions every month! This is a perfect real-world example of AI Project Cycle, Data Science, and Ethics in AI — all topics in your Class 12 board exam! 🚀

📋 Quick Answer Key — Section A MCQs

Q1 (2025)	(b) Convolutional Neural Network (CNN)
Q2 (2025)	(b) Encoder and Decoder
Q3 (2025 A-R)	(c) A is false, R is true
Q4 (2024)	(c) Data Exploration
Q5 (2024)	Artificially Intelligent

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Class 4 Computational Thinking Worksheet: Sharing and Measuring | CBSE CTAI 2026-27

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📐 Sharing and Measuring

Class 4 | Computational Thinking & AI | Chapter 7

📘 Study Notes ✏️ Worksheet 🔍 Word Search 🎯 25 Marks ⏱️ 45 Minutes

Class	4
Subject	Computational Thinking & AI (CTAI)
Chapter	Chapter 7 – Sharing and Measuring
Bloom's Level	Remember | Understand | Apply
Difficulty	Easy to Moderate
Time Required	45 Minutes
Source	CTAI Textbook – academic.nic.in

📖 PART 1: STUDY NOTES

🔑 Key Terms to Know

SharingDividing something equally among people or groups

MeasuringFinding the size, length, weight, or capacity of something

UnitA standard amount used to measure (e.g., metre, kg, litre)

Equal PartsPieces that are exactly the same size

EstimationMaking a smart guess about a measurement

DataInformation collected, like measurements or counts

PatternSomething that repeats in a predictable way

AlgorithmA step-by-step set of instructions to solve a problem

1️⃣ What is Sharing?

Sharing means dividing things fairly and equally among people. In Computational Thinking, sharing is like breaking a big problem into smaller equal parts.

🧠 CT Skill: Decomposition — Breaking big things into smaller equal parts!

🍕 Real-Life Indian Example

Riya has 12 rotis. She shares them equally among 4 friends.

12 ÷ 4 = 3 rotis each

👉 Just like a computer divides a big task into equal small tasks!

2️⃣ What is Measuring?

Measuring helps us find the exact size of something using a unit. We measure different things in different ways:

📏 Lengthcm, metre, km

⚖️ Weightgram, kilogram

🥛 Capacityml, litre

⏰ Timeseconds, minutes, hours

🧠 CT Connection: Algorithm

When we measure step-by-step, we follow an Algorithm!

1. Choose what to measure
2. Pick the right unit
3. Use the correct tool
4. Record the result

3️⃣ Patterns in Measuring

When we measure many things, we can find patterns in the data. Computers do this too — it is called Pattern Recognition!

• All pencils are between 10–15 cm → Pattern found!
• Every 2 cups fill a jug → Repeated pattern!
• Every student gets 3 biscuits → Equal sharing pattern!

📝 Summary

• Sharing = Dividing equally = Decomposition in CT
• Measuring = Using units step-by-step = Algorithm in CT
• Finding patterns in data = Pattern Recognition in CT
• Computers also share tasks and measure data!

🚀

💡 Did You Know?

ISRO scientists measured the exact distance to the Moon before launching Chandrayaan! They used mathematical algorithms — just like the algorithms we learn in Computational Thinking. India's space scientists are real-life CT experts!

✏️ PART 2: WORKSHEET

Name:     Roll No:     Date:     Marks: / 25

✏️ Section A: Multiple Choice Questions  [5 × 1 = 5 Marks]

Click an option to check your answer!

Q1. Raju has 20 mangoes. He shares them equally among 5 friends. Each friend gets:

Q2. Which unit do we use to measure length?

Q3. Decomposition in Computational Thinking is similar to:

Q4. A set of step-by-step instructions to solve a problem is called:

Q5. 1 kilogram = ________ grams

✏️ Section B: Fill in the Blanks  [7 × 1 = 7 Marks]

📦 Word Box:   algorithm  |  equal  |  litre  |  pattern  |  kilogram  |  decomposition  |  unit

1. Dividing a big problem into smaller parts is called .

2. We measure weight using or grams.

3. A step-by-step set of instructions is called an .

4. When something repeats in a predictable way, it is called a .

5. We use to measure liquids like milk or water.

6. When sharing is done fairly, everyone gets parts.

7. A is a standard amount used for measuring.

✏️ Section C: Match the Column  [5 × 1 = 5 Marks]

S.No.	Column A	→	Column B	Answer
1.	Measuring length	A.	Algorithm	___
2.	Measuring weight	B.	Decomposition	___
3.	Measuring time	C.	Kilogram	___
4.	Sharing equally	D.	Metre	___
5.	Set of instructions	E.	Seconds / Minutes	___

✏️ Section D: Short Answer Questions  [3 × 1 = 3 Marks]

Q1. What does 'sharing equally' mean? Give one example from your daily life.

---

---

---

Q2. Name any three units of measurement and write what each one measures.

---

---

---

Q3. Look at this number pattern: 5, 10, 15, 20, ___. What comes next? What is the pattern?

---

---

🎯 Section E: The School Picnic Problem  [5 Marks]

🏫 Your school is organising a picnic for Class 4. There are 24 students.

The teacher has these items to share equally:

🍎48 Apples

🍫72 Biscuits

🧃24 Juice Boxes

🎈36 Balloons

Answer these questions:

a) How many apples will each student get?    Ans:

b) How many biscuits will each student get?    Ans:

c) If students sit in groups of 4, how many balloons per group?    Ans:

d) Write the steps (algorithm) the teacher should follow to share juice boxes equally:

Step 1:

---

Step 2:

---

Step 3:

---

e) Which CT skill did you use to solve this problem?    Ans:

🔍 Bonus: Word Search — Find the CT Words!

SHARE MEASURE UNIT PATTERN DATA EQUAL ALGO

Click letters to select — words are hidden horizontally and vertically

📋 Answer Key (For Teachers / Parents)

Section A (MCQ)	1-b (4), 2-c (Metre), 3-b (Sharing equally), 4-c (Algorithm), 5-d (1000)
Section B (Fill)	1-decomposition, 2-kilogram, 3-algorithm, 4-pattern, 5-litre, 6-equal, 7-unit
Section C (Match)	1-D, 2-C, 3-E, 4-B, 5-A
Section E (Activity)	a) 2 apples, b) 3 biscuits, c) 6 balloons, e) Decomposition

🤖

💡 Did You Know?

AI systems used in Indian agriculture help farmers measure crop yield and share water resources equally among fields — just like the algorithms you are learning today! 🌾

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Class 5 Maths Mela — We the Travellers & Fractions | Activities, Worksheets & Answer Key | CBSE 2026-27

AI Logic School · Class 5 CT & AI · Maths Mela 2026-27 · CBSE
Computational Thinking integrated with Class 5 Maths — We the Travellers & Fractions. Activities, worksheets and answer keys for students and teachers. Free PDF download available.

Class 5 CT & AI Maths Mela We the Travellers Fractions CBSE 2026-27 Free Worksheet Activities

📚 AI Logic School · Class 5 · 2026-27

Class 5 Maths Mela 🎒
We the Travellers & Fractions

Fun activities, CT connections, worksheets & answer keys for Class 5 students — aligned to CBSE Maths Mela 2026-27!

2Chapters

6Activities

30+Questions

🆓Free PDF

📖 Chapters We Are Covering Today

🚂

Chapter 1 — We the Travellers I

Reading maps, finding routes, understanding directions, measuring distances and planning journeys using algorithms!

CT Skill: Algorithmic Thinking

🍕

Chapter 2 — Fractions

Understanding equal parts, numerator & denominator, comparing fractions, adding & subtracting fractions with fun food examples!

CT Skill: Decomposition

🧠 CT Connection: In Class 5, Computational Thinking is NOT about computers — it's about thinking clearly and logically! We use CT skills like decomposition (breaking problems into parts) and algorithms (step-by-step plans) to solve maths problems.

🚂 Chapter 1 — We the Travellers I

In this chapter, we learn about maps, routes, directions and distances. We plan journeys — which is exactly what an algorithm is! A route is a step-by-step plan to get from one place to another. That's thinking like a computer! 🧠

Maths Concept	CT Connection	Example
Reading a map	Pattern Recognition	Finding shapes, grids & symbols on maps
Planning a route	Algorithmic Thinking	Step-by-step directions to reach a place
Finding shortest path	Optimisation	Which route uses fewer steps?
Directions (N/S/E/W)	Decomposition	Breaking a journey into small moves

🎮 Fun Activities — We the Travellers

1

🗺️ Activity: Plan Robo's Train Journey!

Robo wants to travel from Mumbai to Delhi by train. Help Robo write a step-by-step algorithm for the journey!

• 1
  Look at the map and find Mumbai and Delhi
• 2
  Find all possible train routes between them
• 3
  Count the number of stops on each route
• 4
  Choose the route with FEWER stops — that's the shortest algorithm!
• 5
  Write directions: "Start at Mumbai → Go North → Pass Surat → Pass Vadodara → Reach Delhi"

✅ CT Skill Used: This is ALGORITHMIC THINKING — writing step-by-step instructions to solve a problem!

2

📐 Activity: Grid Map Navigation!

Draw a 5×5 grid on your notebook. Mark your home at (1,1) and your school at (4,5). Now answer:

• A
  How many steps RIGHT do you need to take?
• B
  How many steps UP do you need to take?
• C
  Write the algorithm: RIGHT ___, UP ___, RIGHT ___, UP ___
• D
  Is there another path with the SAME number of steps? (Yes/No)

💡 Fun Fact: GPS apps like Google Maps use the same idea — they find the best algorithm (shortest route) to take you from home to school!

3

✈️ Activity: Travel Distance Calculator!

Meena's family is going on a vacation! They travel:

• Mumbai to Pune = 150 km
• Pune to Mahabaleshwar = 120 km
• Mahabaleshwar to Goa = 200 km

Use decomposition — break the problem into small parts — and find the total distance!

Step 1: 150 + 120 = ___
Step 2: ___ + 200 = ___
Total Distance: ___ km

✅ CT Skill Used: DECOMPOSITION — breaking a big problem into smaller, manageable steps!

🍕 Chapter 2 — Fractions

A fraction shows a part of a whole. When you eat 1 slice of a pizza that has 4 slices total — you ate 1/4 of the pizza! Fractions help us describe equal parts — just like how computers break data into equal parts to process it! 🍕

🔢 Understanding Fractions — Visual Guide

1

2

One Half

1

3

One Third

1

4

One Fourth

3

4

Three Fourths

2

5

Two Fifths

Term	Meaning	Example
Numerator	Top number — parts we HAVE	3/4 → numerator is 3
Denominator	Bottom number — total EQUAL parts	3/4 → denominator is 4
Proper Fraction	Numerator < Denominator	2/5, 3/7, 1/4
Equivalent Fraction	Same value, different numbers	1/2 = 2/4 = 4/8
Unit Fraction	Numerator = 1 always	1/2, 1/3, 1/5, 1/10

🎮 Fun Activities — Fractions

4

🍕 Activity: Pizza Fraction Party!

Aarav ordered a pizza with 8 slices for his 4 friends. Help distribute it fairly!

• 1
  Total slices = 8. Number of friends = 4. Each friend gets = 8 ÷ 4 = __ slices
• 2
  Write as a fraction: Each friend gets __/8 of the pizza
• 3
  Is this equal to 1/4? (Hint: Simplify 2/8 → divide top and bottom by 2)
• 4
  Draw the pizza divided into 8 equal parts. Colour Aarav's share!

🧠 CT Connection: Dividing pizza equally = DECOMPOSITION! Computers break tasks into equal parts to process them fairly!

5

🌈 Activity: Fraction Number Line!

Draw a number line from 0 to 1. Now mark these fractions on it!

0 1 ↑ 1/2 ↑ 1/4 ↑ 3/4

• A
  Which is bigger — 1/4 or 3/4? _______
• B
  Which fraction is exactly in the middle between 0 and 1? _______
• C
  Mark 2/4 on the number line. Is it the same as 1/2? (Yes/No) _______

6

🎒 Activity: Fraction Story — Priya's School Bag!

Priya's school bag has 10 items:

📚 3 textbooks  |  📓 2 notebooks  |  ✏️ 2 pencils  |  📏 1 ruler  |  🎨 1 colour box  |  🍱 1 lunch box

• 1
  What fraction of items are textbooks? ___/10
• 2
  What fraction of items are pencils? ___/10
• 3
  What fraction are books (textbooks + notebooks together)? ___/10
• 4
  If Priya removes 2 items, total becomes 8. Now what fraction are textbooks? ___/8

💡 Remember: The denominator always shows the TOTAL. When total changes, the denominator changes too!

📥 Download Free PDF Worksheets!

Get printable worksheets for We the Travellers & Fractions — with answer key — free for all Class 5 students!

📲 Get PDF on Telegram Join @ailogicschool

📋 Worksheet 1 — We the Travellers

Chapter 1 & 4 · Maths Mela · CBSE Class 5 · 2026-27

📚 Class: V⏱️ Time: 30 Min 📝 Marks: 20🏫 AI Logic School

📝 SECTION A — Fill in the Blanks (5 × 1 = 5 Marks)

Q1 A step-by-step plan to reach a place is called a ____________.

Q2 On a map, the four main directions are N, S, E and ____________.

Q3 If you move 3 steps RIGHT and 2 steps UP on a grid, you have moved __________ steps in total.

Q4 Breaking a long journey into small parts is a CT skill called __________.

Q5 The shortest route between two points uses the __________ number of steps.

✅ SECTION B — MCQ (5 × 1 = 5 Marks)

Q6 Robo is at position (2,3). It moves RIGHT 2 times. Where is Robo now?

A

(2,5)

B

(4,3) ✓

C

(2,1)

D

(4,5)

Q7 Priya walks 500 m to the market and 300 m back home. Total distance walked:

A

500 m

B

300 m

C

800 m ✓

D

200 m

Q8 Which of these is an ALGORITHM for going from home to school?

A

"Go to school somehow"

B

"Walk out → turn right → go 200m → turn left → reach school" ✓

C

"School is far away"

D

"Take any road"

Q9 On a map, which direction is usually at the TOP?

A

South

B

East

C

West

D

North ✓

Q10 A train travels 120 km + 80 km + 150 km. Total distance:

A

300 km

B

350 km ✓

C

200 km

D

400 km

🗺️ SECTION C — Application (2 × 2.5 = 5 Marks)

Q11 Draw a 4×4 grid. Place a house at (1,1) and a park at (4,4). Write a step-by-step algorithm for Robo to travel from house to park moving only RIGHT and UP.

Draw your grid and write algorithm here ✏️

Q12 Rani travels: Home → Market (2 km) → Library (1.5 km) → School (0.5 km). Use decomposition — find total distance step by step. Show your work!

🧠 SECTION D — Think & Write (1 × 5 = 5 Marks)

Q13 Write a short paragraph (3-4 sentences): How is planning a journey similar to writing an algorithm? Give one real-life example from your own life!

📋 Worksheet 2 — Fractions

Chapter 2 · Maths Mela · CBSE Class 5 · 2026-27

📚 Class: V⏱️ Time: 30 Min 📝 Marks: 20🏫 AI Logic School

📝 SECTION A — Fill in the Blanks (5 × 1 = 5 Marks)

Q1 In the fraction 3/7, the numerator is __________ and denominator is __________.

Q2 A fraction where numerator is less than denominator is called a __________ fraction.

Q3 1/2 = 2/__ = 4/__ (fill in the blanks to make equivalent fractions).

Q4 If a ribbon is cut into 5 equal parts and Priya takes 2 parts, she has __________ of the ribbon.

Q5 The fraction that shows ONE equal part out of four is __________.

✅ SECTION B — MCQ (5 × 1 = 5 Marks)

Q6 A watermelon is cut into 8 equal pieces. Rohan eats 3 pieces. What fraction did he eat?

A

3/5

B

5/8

C

3/8 ✓

D

8/3

Q7 Which fraction is the LARGEST?

A

1/8

B

1/2 ✓

C

1/4

D

1/6

Q8 Which pair shows EQUIVALENT fractions?

A

1/2 and 2/6

B

2/4 and 1/2 ✓

C

3/5 and 2/5

D

1/3 and 1/4

Q9 Riya ate 1/4 of a cake. What fraction of the cake is LEFT?

A

1/4

B

2/4

C

3/4 ✓

D

4/4

Q10 1/3 + 1/3 = ?

A

1/6

B

2/6

C

2/3 ✓

D

1/3

🍕 SECTION C — Application (2 × 2.5 = 5 Marks)

Q11 Shade the fractions and compare: Draw two rectangles of the same size. Shade 2/4 in the first and 3/4 in the second. Which shaded part is bigger? How do you know?

Draw and shade your rectangles here ✏️

Q12 Meera has a ribbon 12 cm long. She uses 1/4 of it for a bow. How many cm did she use? How many cm are left?

🌈 SECTION D — CT + Fractions Challenge (1 × 5 = 5 Marks)

Q13 The Fraction Robot! Robo has 20 marbles. Write a step-by-step algorithm (like a recipe) for Robo to give fractions to 4 friends fairly:

Step 1: Total marbles = 20. Number of friends = ____
Step 2: Each friend's share = 20 ÷ ____ = ____ marbles
Step 3: Each friend gets ____/20 = ____/4 of all marbles
Step 4: Verify: ____ + ____ + ____ + ____ = 20 ✓

🔑 Answer Key — Click to Reveal (For Teachers & Parents) ▼

📋 Worksheet 1 — We the Travellers

Q1Route / Algorithm

Q2West (W)

Q35 steps total (3+2)

Q4Decomposition

Q5Least / Minimum / Fewest

Q6B — (4,3)

Q7C — 800 m

Q8B — Step-by-step directions

Q9D — North

Q10B — 350 km (120+80+150)

Q11RIGHT×3, UP×3 (or any valid path totaling 6 moves)

Q122 + 1.5 = 3.5 → 3.5 + 0.5 = 4 km total

📋 Worksheet 2 — Fractions

Q1Numerator = 3, Denominator = 7

Q2Proper fraction

Q31/2 = 2/4 = 4/8

Q42/5 of the ribbon

Q51/4 (one-fourth)

Q6C — 3/8

Q7B — 1/2 (larger denominator = smaller piece)

Q8B — 2/4 = 1/2

Q9C — 3/4 remaining (4/4 - 1/4 = 3/4)

Q10C — 2/3

Q113/4 is bigger — more parts shaded out of same whole

Q12Used = 3 cm | Left = 9 cm

Q13Each friend: 5 marbles | Share: 5/20 = 1/4 | Verify: 5+5+5+5=20 ✓

🔗 More Free Resources — AI Logic School

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Flowcharts, Grid Navigation, Logical Operations worksheet.

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15 Python programs Code 417 with output.

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20+ Python programs CBSE Code 843.

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AI Logic School Hub

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📥 Download Both Worksheets as PDF — Free!

Join Telegram @ailogicschool for printable PDFs of both worksheets with answer keys. New content for all classes added every week!

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AI Logic School · Class 5 CT & AI · Maths Mela · We the Travellers & Fractions · CBSE 2026-27

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