Sample Question Paper Artificial Intelligence Class 7 (2025): Ultimate CBSE Practice Guide for Top Scores

✨ INTRODUCTION

Artificial Intelligence (AI) has become one of the most fascinating and future-oriented subjects in the CBSE curriculum. To help Class 7 students prepare effectively, this Sample Question Paper Artificial Intelligence Class 7 (2025) provides a complete practice experience — including MCQs, short answers, and case-based questions aligned with the latest CBSE and NCERT guidelines.

Whether you’re revising for your Half-Yearly or Final Examination, this sample paper will help you understand question patterns, strengthen conceptual knowledge, and improve time management. With clear explanations and balanced weightage across all five chapters, it’s your ultimate guide to mastering the AI syllabus confidently.

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CLASS VII – ARTIFICIAL INTELLIGENCE (417) YEARLY EXAMINATION 2025–26 – QUESTION PAPER (SET–1)

KENDRIYA VIDYALAYA SANGATHAN

YEARLY EXAMINATION 2025–26

CLASS: VII             SUBJECT: ARTIFICIAL INTELLIGENCE (417)
Time: 02:30 Hours            Max Marks: 60

GENERAL INSTRUCTIONS

1. The question paper comprises five sections (A–E) with 28 questions.
2. All questions are compulsory. Internal choice is provided where applicable.
3. Marks are indicated against each question.
4. Questions test conceptual understanding, application, and reasoning skills.

SECTION A (1 × 12 = 12 Marks)

(Objective Type Questions)

Q1–9. Multiple Choice Questions (1 mark each)

Q1. A specific area of knowledge or expertise in which an AI system works is called a —
A. Network B. Domain C. Database D. Algorithm
✅ Answer: B — Domain
📘 Explanation: A domain defines a particular field of application for AI, e.g., healthcare, education, or agriculture.

Q2. Which type of data is organized in rows and columns?
A. Structured B. Unstructured C. Semi-Structured D. Visual
✅ Answer: A — Structured
📘 Explanation: Structured data is organized in tabular form (like spreadsheets or databases).

Q3. Computer Vision enables machines to —
A. Understand language B. Interpret images C. Play music D. Solve puzzles
✅ Answer: B — Interpret images
📘 Explanation: CV helps machines “see” and understand images/videos — e.g., facial recognition, traffic monitoring.

Q4. The process of dividing text into smaller parts is known as —
A. Tokenization B. Tagging C. Translation D. Filtering
✅ Answer: A — Tokenization
📘 Explanation: In NLP, tokenization splits sentences into words or phrases for easier analysis.

Q5. Which of these is NOT good digital citizenship?
A. Respecting privacy B. Posting hurtful comments C. Verifying facts D. Using strong passwords
✅ Answer: B — Posting hurtful comments
📘 Explanation: Responsible digital citizens communicate respectfully and avoid online bullying or negative posts.

Q6. Data Science in AI helps machines —
A. Perform manual tasks B. Learn from data and make decisions C. Draw pictures D. Play games
✅ Answer: B — Learn from data and make decisions
📘 Explanation: Data Science analyzes large amounts of data, helping AI systems make data-driven predictions.

Q7. When your phone recognizes your face, it uses —
A. NLP B. Computer Vision C. Data Science D. Robotics
✅ Answer: B — Computer Vision
📘 Explanation: CV algorithms identify facial features from image data for authentication.

Q8. NLP is used in —
A. Self-driving cars B. Alexa and Siri C. Face Unlock D. Google Maps
✅ Answer: B — Alexa and Siri
📘 Explanation: Natural Language Processing enables voice assistants to understand and respond to human speech.

Q9. The 3Ps of Sustainability stand for —
A. People, Planet, Profit B. Process, Policy, Planet C. Power, People, Progress D. Product, Policy, Planet
✅ Answer: A — People, Planet, Profit
📘 Explanation: The 3Ps represent the social, environmental, and economic pillars of sustainability.

Q10–12. Assertion–Reason (1 mark each)

Q10.
Assertion (A): NLP enables AI to understand human speech.
Reason (R): NLP works only on numerical data.
✅ Answer: C — A is true, but R is false.
📘 Explanation: NLP works with text/speech data, not just numbers.

Q11.
Assertion (A): Computer Vision contributes to sustainability.
Reason (R): It helps monitor crops and pollution through visual systems.
✅ Answer: A — Both are true, and R explains A.
📘 Explanation: CV aids environmental sustainability by analyzing visual environmental data.

Q12.
Assertion (A): Good digital citizens protect privacy online.
Reason (R): Responsible sharing prevents cyber risks.
✅ Answer: A — Both are true, and R explains A.
📘 Explanation: Privacy and responsible sharing are essential elements of digital safety.

SECTION B (2 × 6 = 12 Marks)

(Very Short Answer Type Questions – 2 marks each)

Q13. What is a domain in AI? Give one example.
✅ Answer:
A domain in AI is a specific area where an AI system is applied.
📘 Example: Healthcare domain – AI used in disease diagnosis.

Q14. Define Big Data. Mention any two of its characteristics.
✅ Answer:
Big Data refers to extremely large and complex datasets that cannot be processed using traditional tools.
📘 Characteristics: Volume (large size), Variety (different types of data).

Q15. What is Feature Extraction in Computer Vision?
✅ Answer:
Feature Extraction identifies key details like shapes, colors, or edges in images so AI can recognize objects.

Q16. Define Tokenization and POS Tagging in NLP.
✅ Answer:

• Tokenization: Splitting text into words or phrases.
• POS Tagging: Identifying grammatical roles of words (noun, verb, adjective, etc.).

Q17. What is a Digital Footprint? How can it be positive?
✅ Answer:
A Digital Footprint is the record of a person’s online activities.
📘 Positive Footprint: Sharing helpful content, respectful comments, educational posts.

Q18. Mention two ways AI supports Sustainable Development Goals (SDGs).
✅ Answer:

• Predicting natural disasters (SDG 13 – Climate Action).
• Improving crop yield using smart irrigation (SDG 2 – Zero Hunger).

SECTION C (3 × 6 = 18 Marks)

(Short Answer Type – 3 marks each)

Q19. Explain how Data Science helps AI in decision-making with one real-life example.
✅ Answer:
Data Science collects and analyzes data to identify trends and patterns.
📘 Example: Netflix uses viewing data to recommend shows, improving user experience.

Q20. Describe the four main stages of the Computer Vision process.
✅ Answer:

1. Image Acquisition – capturing images through cameras/sensors.
2. Feature Extraction – detecting shapes and colors.
3. Classification – comparing with stored data.
4. Decision Making – taking actions (e.g., applying brakes in self-driving cars).

Q21. How does NLP make technology inclusive? Give one educational use.
✅ Answer:
NLP allows users to communicate through natural languages, making technology accessible to all.
📘 Example: Translation tools help students learn in different languages.

Q22. List three principles of good Digital Citizenship.
✅ Answer:

1. Respect others online.
2. Protect privacy and passwords.
3. Think before posting or sharing.

Q23. Differentiate between Data Science, Computer Vision, and NLP with one example each.
✅ Answer:

Domain	Focus	Example
Data Science	Analyzing data	Predicting weather
Computer Vision	Understanding visuals	Face recognition
NLP	Understanding language	Chatbots like Alexa

Q24. Explain Systems Thinking in AI and how it helps students plan AI projects.
✅ Answer:
Systems Thinking studies how components interact within a system.
📘 In AI Projects: Helps design models that connect sensors, algorithms, and feedback for efficient performance.

SECTION D (4 × 2 = 8 Marks)

Q25-Q26. (Case-Based Questions – 4 marks each)

Q25. Case Study 1 – Smart Farming

“Farmers use drones with AI cameras to monitor crops. The drones capture images, analyze soil moisture, and identify pest damage. Data helps decide irrigation schedules and fertilizer use.”

a) Which two AI domains are used here?
✅ Computer Vision and Data Science

b) How does this system promote sustainability?
✅ It reduces chemical use and optimizes water resources.

c) What kind of data is collected?
✅ Image and sensor data.

d) Which SDG is supported by this system?
✅ SDG 2 – Zero Hunger

Q26. Case Study 2 – Online Learning Chatbot

“An AI chatbot helps students revise lessons. It answers questions, explains topics, and gives quizzes. The more it interacts, the better it understands student needs.”

a) Which AI domain powers the chatbot?
✅ Natural Language Processing (NLP)

b) Which NLP step helps it identify question intent?
✅ Tokenization and Intent Recognition

c) Mention one advantage and one ethical concern.
✅ Advantage – Personalized learning; Concern – Data privacy

d) Which SDG does it support?
✅ SDG 4 – Quality Education

SECTION E (5 × 2 = 10 Marks)

(Long Answer Type – 5 marks each)

Q27. (a) Explain the three main domains of Artificial Intelligence with examples.
(b) How do these domains connect to form a complete AI system?

✅ Answer:

• Data Science: Analyzes numerical data to predict outcomes (e.g., rainfall forecast).
• Computer Vision: Enables machines to interpret images (e.g., face unlock).
• NLP: Allows communication through text or voice (e.g., Alexa).
  📘 Connection: Together they help AI systems sense, understand, and respond intelligently.

Q28. Explain the importance of Digital Citizenship in today’s AI-powered world.
Discuss five practices that promote safe, ethical, and responsible online behavior among students.

✅ Answer:
Digital Citizenship ensures responsible, respectful, and safe technology use.
Five Good Practices:

1. Protect privacy and use strong passwords.
2. Follow online manners (Netiquette).
3. Avoid fake news or plagiarism.
4. Report cyberbullying.
5. Create positive and educational online content.
   📘 SDG Link: Supports SDG 4 (Quality Education) and SDG 16 (Peace & Justice).

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CLASS VII – ARTIFICIAL INTELLIGENCE (417) YEARLY EXAMINATION 2025–26 – QUESTION PAPER (SET–2)

KENDRIYA VIDYALAYA SANGATHAN

YEARLY EXAMINATION 2025–26

CLASS: VII             SUBJECT: ARTIFICIAL INTELLIGENCE (417)
Time: 02 Hours 30 Minutes     Max Marks: 60

GENERAL INSTRUCTIONS

1. The paper has five sections (A–E) with 28 questions.
2. All questions are compulsory. Internal choices are provided where applicable.
3. Marks are indicated against each question.
4. Write neatly and read all questions carefully before answering.

SECTION A (1 × 12 = 12 Marks)

(Objective Type Questions)

Q1–9. Multiple Choice Questions (1 mark each)

Q1. The branch of AI that deals with data patterns and predictions is —
A. Data Science B. Computer Vision C. NLP D. Robotics
✅ Answer: A — Data Science
📘 Explanation: Data Science analyzes large datasets to find trends and make predictions — the foundation for AI learning.

Q2. Which of the following is an application of NLP?
A. Face Unlock B. Alexa or Siri C. Google Maps D. Photoshop
✅ Answer: B — Alexa or Siri
📘 Explanation: Voice assistants use NLP to understand and respond to spoken language.

Q3. The smallest unit of an image in Computer Vision is —
A. Byte B. Pixel C. Node D. Frame
✅ Answer: B — Pixel
📘 Explanation: Each image is made up of pixels that store color and brightness information.

Q4. Systems Thinking helps us —
A. Study each part separately B. Understand interconnections C. Ignore feedback D. Write code faster
✅ Answer: B — Understand interconnections
📘 Explanation: Systems Thinking focuses on how various parts of a system influence one another.

Q5. Which of these is an ethical digital practice?
A. Sharing rumours B. Citing original sources C. Using weak passwords D. Posting insults
✅ Answer: B — Citing original sources
📘 Explanation: Citing creators shows integrity and avoids plagiarism.

Q6. Big Data means —
A. Small data tables B. Extremely large and complex datasets C. Only text files D. Simple numbers
✅ Answer: B — Extremely large and complex datasets
📘 Explanation: Big Data involves massive amounts of structured and unstructured data.

Q7. What is the first step in the Computer Vision process?
A. Decision Making B. Feature Extraction C. Image Acquisition D. Classification
✅ Answer: C — Image Acquisition
📘 Explanation: It’s the stage where visuals are captured via cameras or sensors for analysis.

Q8. POS Tagging in NLP helps AI —
A. Detect emotion B. Identify grammar roles C. Translate D. Recognize faces
✅ Answer: B — Identify grammar roles
📘 Explanation: POS (Part of Speech) Tagging labels each word as noun, verb, adjective, etc.

Q9. The “3 Ps” of sustainability refer to —
A. People, Planet, Profit B. Policy, Power, Product C. Process, Planet, Plan D. People, Process, Profit
✅ Answer: A — People, Planet, Profit
📘 Explanation: These three pillars represent the balance between social, environmental, and economic progress.

Q10–12. Assertion & Reason Questions (1 mark each)

Q10.
A: Data Cleaning improves accuracy.
R: Unclean data leads to wrong analysis.
✅ Answer: A — Both A and R are true, and R explains A.
📘 Explanation: Data Cleaning removes errors ensuring reliable AI predictions.

Q11.
A: Computer Vision helps AI detect objects.
R: It analyses visual features like edges and color.
✅ Answer: A — Both A and R are true, and R explains A.
📘 Explanation: CV identifies patterns and features within images for recognition tasks.

Q12.
A: Digital footprints can be permanently erased.
R: Online data once shared remains traceable.
✅ Answer: C — A is true, but R is false.
📘 Explanation: Digital footprints are usually permanent; deleted posts can still be retrieved or cached.

SECTION B (2 × 6 = 12 Marks)

(Very Short Answer Type – 2 marks each)

Q13. Define Artificial Intelligence. Give one daily life example.
✅ Answer:
Artificial Intelligence is the ability of machines to mimic human intelligence and decision-making.
📘 Example: Virtual assistants like Siri or Alexa.

Q14. What are Structured and Unstructured data? Give one example each.
✅ Answer:

• Structured Data: Organized in rows/columns (e.g., Excel sheet).
• Unstructured Data: Raw data like videos, emails, social media posts.

Q15. What is the role of Feature Extraction in Computer Vision?
✅ Answer:
It identifies key patterns such as colors, shapes, and edges to help AI recognize objects in images.

Q16. Explain the term Sentiment Analysis in NLP with one example.
✅ Answer:
Sentiment Analysis identifies the mood of text (positive, negative, neutral).
📘 Example: Detecting “I love this product” as positive feedback.

Q17. What is Netiquette? Write two rules of good Netiquette.
✅ Answer:
Netiquette means good manners in online communication.
📘 Rules: Be polite, avoid using ALL CAPS (seen as shouting).

Q18. How does AI support sustainability in education and agriculture?
✅ Answer:

• In education: personalized learning through AI tutors (SDG 4).
• In agriculture: AI predicts weather for better crop planning (SDG 2).

SECTION C (3 × 6 = 18 Marks)

(Short Answer Type – 3 marks each)

Q19. Describe the importance of Domains in Artificial Intelligence with examples.
✅ Answer:
Domains help AI focus on specialized problems.
📘 Examples:

• Healthcare: AI diagnoses diseases.
• Agriculture: Predicts crop yield.
• Education: Personalized learning systems.

Q20. Explain the 5 Vs of Big Data with any two real-world examples.
✅ Answer:

• Volume: Large size of data (e.g., YouTube uploads).
• Velocity: Speed of generation (e.g., Twitter posts).
• Variety: Different forms (text, video, images).
• Veracity: Accuracy of data.
• Value: Usefulness of insights.
  📘 Examples: E-commerce recommendation data, weather forecasts.

Q21. Write the steps in the Computer Vision workflow and briefly explain each.
✅ Answer:

1. Image Acquisition: Capturing visuals via cameras.
2. Feature Extraction: Detecting patterns, edges.
3. Classification: Comparing with known images.
4. Decision Making: Performing actions (e.g., alerting traffic violation).

Q22. Differentiate between Tokenization, POS Tagging, and NER in NLP.
✅ Answer:

Step	Purpose	Example
Tokenization	Splits text	“AI is fun” → [AI, is, fun]
POS Tagging	Labels grammar	“AI/NN is/VB fun/JJ”
NER	Finds names	“Google” → Organization

Q23. What are three key principles of Digital Citizenship? Explain each.
✅ Answer:

1. Respect: Treat others politely online.
2. Safety: Protect passwords and personal data.
3. Responsibility: Verify facts before sharing.

Q24. How does Systems Thinking help in designing AI-based solutions for community problems?
✅ Answer:
It allows understanding how sensors, data, and AI models interact.
📘 Example: Designing smart irrigation – sensors (input) → AI (process) → pump (output) → soil moisture feedback.

SECTION D (4 × 2 = 8 Marks)

(Case-Based Questions – 4 marks each)

Q25. Case Study 1 – AI and Healthcare

“An AI system scans X-rays to identify early lung infections. It learns from thousands of images to improve accuracy and help doctors make quicker decisions.”

a) Which AI domain is used here?
✅ Computer Vision

b) How does the AI system learn to improve?
✅ Through Machine Learning by analyzing image patterns.

c) State one benefit and one limitation.
✅ Benefit: Early detection; Limitation: Data privacy.

d) Which SDG is supported?
✅ SDG 3 – Good Health and Well-being.

Q26. Case Study 2 – Digital Safety

“While browsing social media, Anaya receives a message with a suspicious link promising a free phone. She does not click and instead reports the account.”

a) Which cyber threat did she avoid?
✅ Phishing

b) Which principle of Digital Citizenship did she follow?
✅ Responsibility & Safety

c) Name one cybersecurity tool that can help.
✅ Antivirus or Two-Factor Authentication (2FA)

d) What should students learn?
✅ To think critically and verify before clicking unknown links.

SECTION E (5 × 2 = 10 Marks)

(Long Answer Type – 5 marks each)

Q27. (a) Explain how Data Science, Computer Vision, and NLP work together to build AI applications.
(b) Give two real-life examples.

✅ Answer:

• Data Science: Analyzes numerical or text data for predictions.
• Computer Vision: Interprets visuals from cameras.
• NLP: Understands text or voice commands.
  📘 Connection: Combined, they form smart systems.
  📘 Examples:

1. Self-driving cars – CV detects obstacles, Data Science predicts routes, NLP processes voice commands.
2. AI Healthcare – CV reads X-rays, Data Science analyzes data, NLP generates medical reports.

Q28. Discuss the importance of Digital Citizenship for students in the AI era.
Include five ways to stay safe and ethical online, and connect it with SDGs.

✅ Answer:
Digital Citizenship means using technology responsibly, safely, and ethically.
Five Ways to Practice It:

1. Use strong passwords and privacy settings.
2. Communicate respectfully (Netiquette).
3. Verify information before sharing.
4. Report cyberbullying or abuse.
5. Avoid plagiarism and credit sources.
   📘 SDG Connection:
   Supports SDG 4 (Quality Education) and SDG 16 (Peace, Justice, Strong Institutions) by promoting safe digital learning.

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CLASS VII – ARTIFICIAL INTELLIGENCE (417) YEARLY EXAMINATION 2025–26 – QUESTION PAPER (SET–3)

KENDRIYA VIDYALAYA SANGATHAN

YEARLY EXAMINATION 2025–26

CLASS: VII             SUBJECT: ARTIFICIAL INTELLIGENCE (417)**
Time: 02 Hours 30 Minutes     Max Marks: 60

GENERAL INSTRUCTIONS

1. The paper consists of five sections (A–E) with 28 questions.
2. All questions are compulsory. Internal choice is provided where necessary.
3. Marks are indicated against each question.
4. The paper tests knowledge, understanding, application, and reasoning skills.

SECTION A (1 × 12 = 12 Marks)

Q1–9. Multiple Choice Questions (1 mark each)

Q1. AI systems that analyze and predict data patterns belong to which domain?
A. NLP B. Data Science C. Computer Vision D. Robotics
✅ Answer: B — Data Science
📘 Explanation: Data Science enables AI to learn from data patterns and make accurate predictions.

Q2. Which step in the Data Science workflow ensures accuracy and reliability of results?
A. Data Cleaning B. Data Visualization C. Data Storage D. Data Transmission
✅ Answer: A — Data Cleaning
📘 Explanation: Cleaning removes errors, duplicates, or missing values to make data reliable.

Q3. In Computer Vision, what helps machines recognize objects?
A. Tokenization B. Feature Extraction C. Sentiment Analysis D. Translation
✅ Answer: B — Feature Extraction
📘 Explanation: Feature extraction identifies shapes, edges, and patterns in an image for recognition.

Q4. What is the full form of NLP?
A. Neural Logic Programming B. Natural Language Processing C. Numeric Learning Process D. None of these
✅ Answer: B — Natural Language Processing
📘 Explanation: NLP enables computers to understand, interpret, and respond to human language.

Q5. A digital footprint is —
A. A record of online activities B. Temporary internet files C. Hardware component D. Deleted browser history
✅ Answer: A — Record of online activities
📘 Explanation: A digital footprint includes everything a user does online — posts, searches, likes, etc.

Q6. Systems Thinking helps AI learners —
A. Focus on isolated tasks B. Understand interconnections C. Ignore feedback D. Memorize codes
✅ Answer: B — Understand interconnections
📘 Explanation: Systems Thinking helps understand how data, sensors, and AI models work together.

Q7. In Big Data, “Velocity” refers to —
A. Speed of data generation B. Accuracy of data C. Variety of formats D. Storage type
✅ Answer: A — Speed of data generation
📘 Explanation: Velocity defines how fast data is created, like social media posts per second.

Q8. The process of breaking text into small units (words or phrases) in NLP is —
A. Tagging B. Tokenization C. Sorting D. Recognition
✅ Answer: B — Tokenization
📘 Explanation: Tokenization splits text into smaller meaningful units for NLP analysis.

Q9. Which Sustainable Development Goal is achieved using AI in agriculture?
A. SDG 4 B. SDG 2 C. SDG 11 D. SDG 7
✅ Answer: B — Zero Hunger (SDG 2)
📘 Explanation: AI in smart farming improves productivity and supports food security.

Q10–12. Assertion–Reason Questions (1 mark each)

Q10.
A: Computer Vision allows machines to “see” images.
R: It helps AI identify and interpret visuals.
✅ Answer: A — Both A and R are true, and R correctly explains A.
📘 Explanation: CV processes images for tasks like face recognition or object detection.

Q11.
A: Data Science and AI work independently.
R: Data Science supports AI by providing useful data and insights.
✅ Answer: C — A is false, but R is true.
📘 Explanation: AI depends heavily on Data Science; they are interconnected.

Q12.
A: Netiquette is essential for respectful communication online.
R: It ensures politeness and prevents misunderstandings in digital spaces.
✅ Answer: A — Both A and R are true, and R explains A.
📘 Explanation: Following Netiquette creates a positive and safe online environment.

SECTION B (2 × 6 = 12 Marks)

(Very Short Answer Type Questions – 2 marks each)

Q13. What are AI domains? Name any two.
✅ Answer:
AI domains are specialized areas where AI systems perform specific tasks.
📘 Examples: Data Science and Computer Vision.

Q14. What is meant by Big Data? Mention any two of its features.
✅ Answer:
Big Data means large, complex datasets that can’t be processed by normal tools.
📘 Features: Volume (size) and Variety (different formats).

Q15. Define Computer Vision and give one example.
✅ Answer:
Computer Vision is the AI field that enables computers to understand images and videos.
📘 Example: Face Unlock in smartphones.

Q16. What is the purpose of Sentiment Analysis in NLP?
✅ Answer:
It determines whether text expresses positive, negative, or neutral emotions.
📘 Example: “I love this app!” → Positive sentiment.

Q17. Mention two ways to protect your digital privacy.
✅ Answer:

1. Use strong and unique passwords.
2. Avoid sharing personal data publicly.

Q18. How does AI contribute to sustainability in daily life?
✅ Answer:

• AI reduces energy use (smart homes).
• AI supports eco-friendly farming (crop monitoring).

SECTION C (3 × 6 = 18 Marks)

(Short Answer Type – 3 marks each)

Q19. Explain why Data Science is considered the “foundation” of AI.
✅ Answer:
Data Science collects, cleans, and analyzes data that AI uses to learn and make decisions.
📘 Example: AI predicting exam results based on student data.
Without Data Science, AI systems can’t function effectively.

Q20. Describe the main steps in the Computer Vision process.
✅ Answer:

1. Image Acquisition: Capturing visuals through cameras.
2. Feature Extraction: Detecting shapes and edges.
3. Classification: Identifying objects from stored data.
4. Decision-Making: Taking actions (e.g., triggering alerts).
   📘 Example: Traffic camera detecting red-light violations.

Q21. What are the major components of NLP workflow? Explain briefly.
✅ Answer:

1. Tokenization: Splitting text into words.
2. POS Tagging: Identifying grammar roles.
3. NER: Detecting names and places.
4. Sentiment Analysis: Understanding emotion.
   📘 Example: Chatbots understanding and responding correctly.

Q22. What is Digital Citizenship? Mention three principles that guide it.
✅ Answer:
Digital Citizenship is responsible and safe technology use.
📘 Principles:

1. Respect – Be polite online.
2. Safety – Protect passwords.
3. Responsibility – Verify facts before sharing.

Q23. How does Systems Thinking improve the design of AI projects?
✅ Answer:
It shows how sensors, data, and feedback loops work together.
📘 Example: Smart irrigation – sensors (input), AI (process), water pump (output), soil moisture (feedback).

Q24. Differentiate between Data Science, Computer Vision, and NLP with examples.
✅ Answer:

Domain	Function	Example
Data Science	Analyzes data	Predicts exam results
Computer Vision	Sees images	Detects faces
NLP	Understands language	Chatbots, translators

SECTION D (4 × 2 = 8 Marks)

(Case-Based Questions – 4 marks each)

Q25.Case Study 1 – Smart City Surveillance

“A city uses AI-enabled CCTV cameras to monitor traffic and detect rule violations. When a vehicle jumps a red signal, the camera captures its number plate and sends an automated challan.”

a) Which AI domain is mainly used here?
✅ Computer Vision

b) How does this system promote safety and sustainability?
✅ By reducing accidents and human error.

c) Mention one challenge such systems may face.
✅ Low accuracy in poor lighting or privacy concerns.

d) Which SDG is related to this innovation?
✅ SDG 11 – Sustainable Cities and Communities.

Q26. Case Study 2 – AI in Education

“An AI-based app tracks students’ progress and provides personalized feedback. It uses language analysis to evaluate written answers and give grammar suggestions.”

a) Which AI domain supports this app?
✅ NLP (Natural Language Processing)

b) How does the app personalize learning?
✅ It analyzes performance and tailors exercises accordingly.

c) State one advantage and one concern.
✅ Advantage: Personalized improvement. Concern: Data privacy.

d) Which SDG is supported here?
✅ SDG 4 – Quality Education.

SECTION E (5 × 2 = 10 Marks)

(Long Answer Type – 5 marks each)

Q27. (a) Explain how AI uses Data Science, Computer Vision, and NLP to solve real-life problems.
(b) Give two examples where all three domains are applied together.

✅ Answer:

• Data Science: Processes and analyzes numerical/text data.
• Computer Vision: Interprets visual information.
• NLP: Understands text or voice commands.
  📘 Combined Function: Together they enable intelligent automation.
  📘 Examples:

1. Self-driving cars – CV detects objects, Data Science predicts routes, NLP handles voice instructions.
2. Healthcare bots – CV scans reports, Data Science predicts illness, NLP communicates with patients.

Q28. Write an essay on the importance of being a Responsible Digital Citizen.
Explain five essential online behaviors that students must follow for a safe and ethical digital world.

✅ Answer:
Digital Citizenship ensures safe, responsible, and respectful use of the internet.
Five Responsible Behaviors:

1. Use strong passwords and update them regularly.
2. Communicate politely – avoid online bullying or rude comments.
3. Verify facts before sharing any post.
4. Respect intellectual property – credit original creators.
5. Protect personal information – don’t overshare online.
   📘 Connection to SDGs: Supports SDG 4 (Quality Education) and SDG 16 (Peace, Justice, and Institutions).

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🏁 CONCLUSION

Practicing with the Sample Question Paper Artificial Intelligence Class 7 (2025) is the smartest way to prepare for upcoming CBSE exams. It helps students understand question formats, reinforce core concepts like Data Science, NLP, and Computer Vision, and improve analytical thinking.

Consistent practice not only builds confidence but also nurtures the problem-solving mindset essential for 21st-century learners. Download the full paper, attempt it under timed conditions, and check your answers against expert solutions — your path to AI exam success starts here!

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