CBSE Sample Papers for Class 10 AI Set 3 with Solutions

Students must start practicing the questions from CBSE Sample Papers for Class 10 AI with Solutions Set 3 are designed as per the revised syllabus.

CBSE Sample Papers for Class 10 AI Set 3 with Solutions

Time Allowed: 2 hours
Maximum Marks: 50

General Instructions:

1. Please read the instructions carefully.
2. This Question Paper consists of 21 questions in two sections: Section A & Section B.
3. Section A has Objective type questions whereas Section B contains Subjective type questions.
4. Out of the given (5 + 16 =) 21 questions, a candidate has to answer (5 + 10 =) 15 questions in the allotted (maximum) time of 2 hours.
5. All questions of a particular section must be attempted in the correct order.
6. Section A : objective type questions (24 marks):
   • This section has 05 questions.
   • Marks allotted are mentioned against each question/part.
   • There is no negative marking.
   • Do as per the instructions given.
7. Section B : subjective type questions (26 marks):
   • This section has 16 questions.
   • A candidate has to do 10 questions.
   • Do as per the instructions given.
   • Marks allotted are mentioned against each question/part.

Section A : Objective Type Questions

Answer any 4 out of the given 6 questions on Employability Skills. (1 × 4 = 4 marks)
Question 1.
(i) Maria is a manager at a tech company. She notices that her team is not as productive as they used to be and decides to conduct an exercise to help her team get into old form. She decides to take her team for a vacation. After returning from the vacation, she found some of her members back in their old zeal, but some still needed some improvement. What was the probable reason for her team losing interest in work? [1]
Answer:
The probable reason for Maria’s team losing interest in work could be burnout, i.e., under fatigue stress or lack of motivation due to prolonged stress.

(ii) Which file operation allows a user to create a duplicate of an existing file in a new location without altering the original file?
(A) Moving
(B) Renaming
(C) Copying
(D) Deleting
Answer:
(C) Copying

Explanation:
The ‘Copying’ operation creates a duplicate of an existing file in a new location, while the original file remains unchanged. This operation is useful for creating backups or distributing files.

(iii) Assertion(A): A software engineer develops applications for a large IT company.
Reason(R): This is an example of wage employment. [1]
(A) Both A and R are correct and R is the correct explanation of A.
(B) Both A and R are correct but R is not the correct explanation of A.
(C) A is correct but R is not correct.
(D) A is not correct but R is correct.
Answer:
(A) Both A and R are correct and R is the correct explanation of A.

Explanation:
The assertion states that a software engineer develops applications for a large IT company, which indicates that the engineer is working under the company’s employment, typically receiving a salary or wages for their work. This matches the definition of wage employment, where an individual works for an employer and gets paid in return for their services. Therefore, both the assertion and the reason are correct, and the reason accurately explains the assertion.

(iv) Stress is our _____ reaction to an event or condition that is considered a threat or challenge. [1]
(A) psychological
(B) physiological
(C) both of them
(D) none of these
Answer:
(C) both of them

(v) Anna, a project manager at a marketing firm, is tasked with presenting a new marketing strategy to her team. To ensure its effectiveness, she follows a structured communication process. She drafts a clear message, holds a team meeting to present the strategy and then sends a follow-up email summarising key points and next steps. This ensures the strategy is well understood and executed effectively. Which stage of the communication cycle does Anna focus on when she drafts the message about the new marketing strategy? [1]
(A) Encoding
(B) Decoding
(C) Feedback
(D) Transmission
Answer:
(A) Encoding

Explanation:
Encoding is the process of creating and formulating a message before transmitting it, and Anna is involved in this stage by drafting a message about her new marketing strategy.

(vi) Choose the option which is not a sustainable development goal according to the United Nations. [1]
(A) Clean Water and Sanitation
(B) Gender Equality
(C) Population
(D) Reduced Inequalities
Answer:
(C) Population

Explanation:
“Population” is not a specific
Sustainable Development Goal (SDG) outlined by the United Nations. The other options – Clean Water and Sanitation, Gender Equality, and Reduced Inequalities are indeed recognised as distinct goals within the SDGs.

Answer any 5 out of the given 6 questions. (1 × 5 = 5 marks)
Question 2.
(i) Assertion(A): Bodily-kinesthetic intelligence is essential for athletes and dancers.
Reason(R): This intelligence involves the ability to control one’s physical motions and handle objects skilfully.
(A) Both A and R are correct and R is the correct explanation of A.
(B) Both A and R are correct but R is not the correct explanation of A.
(C) A is correct but R is not correct.
(D) A is not correct but R is correct.
Answer:
(A) Both A and R are correct and R is the correct explanation of A.

Explanation:
because bodily-kinesthetic intelligence is indeed essential for athletes and dancers, as it involves the ability to control physical motions and handle objects skillfully. This explanation directly supports the assertion, making both the statement and its reason correct, with the reason properly explaining the assertion.

(ii) When a social media company uses personal data for targeted advertising without user consent, which ethical
issue is at stake? [1]
(A) Data Privacy
(B) AI Bias
(C) AI Ethics
(D) AI Access
Answer:
(A) Data Privacy

Explanation:
Using personal data for targeted advertising without user consent raises concerns related to data privacy. It violates the user’s right to control their own data and may lead to misuse of personal information.

(iii) Statement 1: Natural Language Processing (NLP) deals with interaction between human and computer systems using common and frequently spoken languages like Hindi, English, etc.
Statement 2: Spell-check feature is an implementation of NLP [1]
(A) Both Statement 1 and Statement 2 are correct.
(B) Both Statement 1 and Statement 2 are incorrect.
(C) Statement 1 is correct but Statement 2 is incorrect.
(D) Statement 2 is correct but Statement 1 is incorrect.
Answer:
(A) Both Statement 1 and Statement 2 are correct.

Explanation:
Statement 1 is correct because weights in a neural network are indeed updated during the training process to minimize the error and improve the model’s performance.

Statement 2 is also correct because the activation function introduces non-linearity into the network, enabling it to learn more complex patterns.

(iv) Complete the sentence based on the graph: [1]

The larger the size of the training dataset, the ______ (better/worse) the model’s generalisation ability.
Answer:
Better

(v) _____ is the primary purpose of a data warehouse.
(A) Storing audio files
(B) Processing online transactions
(C) Storing and analysing large volumes of data
(D) Compressing images
Answer:
(C) Storing and analysing large volumes of data

(vi) In a corpus of 5 documents, the word ‘the’ appears in all 5 documents. What is the correct classification for the word ‘the’?
(A) Stop word
(B) Rare word
(C) Frequent word
(D) Removable word
Answer:
(A) Stop word

Explanation:
The word ‘the’ appears in all documents, making it a common word across the corpus. In text processing, such words are called stop words. They are frequently removed during text analysis because they carry little meaningful information for tasks like text classification or natural language processing.

Answer any 5 out of the given 6 questions.
Question 3.
(i) Identify the examples that use AI technologies:
i. A vending machine accepting coins and dispensing snacks
ii. A robot vacuum cleaner mapping a room to clean efficiently
iii. A photo app recognising faces to tag people
iv. An electric heater controlled by a manual switch
(A) ii and iii
(B) i and iv
(C) ii, iii, and iv
Answer:
(A) ii and iii

Explanation:
A robot vacuum cleaner mapping a room to clean efficiently uses AI technology for navigation and efficient cleaning. iii: A photo app recognising faces to tag people uses AI for facial recognition. The i option (vending machine) and iv option (electric heater) do not involve AI technologies; they are basic mechanical or electrical systems without AI.

(ii) The process by which machines improve their performance based on experience is called ______.
Answer:
Machine Learning

(iii) Which of the following is an Al-based application in healthcare? [1]
(A) Video editing
(B) Disease diagnosis
(C) Weather forecasting
(D) Currency conversion
Answer:
(B) Disease diagnosis

Explanation:
In healthcare, AI is widely used for disease diagnosis, as AI models can analyse medical data (like images, test results and patient history) to detect diseases more accurately and quickly. The other options (video editing, weather forecasting and currency conversion) do not specifically involve AI in healthcare.

(iv) _____  AI assigns a label to an image as a whole. [1]
(A) Classification
(B) Object detection
(C) Image segmentation
(D) Feature extraction
Answer:
(A) Classification

Explanation:
Classification AI assigns a label to an entire image as a whole, identifying what the image represents (e.g., cat, dog, car).

(v) Identify the type: It uses past experiences to autonomously improve performance and make decisions, often without human intervention. [1]
Answer:
Machine learning-based chatbot system

(vi) What is the term for incorrectly predicting a positive class when the actual class is negative? [1]
(A) True Positive
(B) False Positive
(C) True Negative
(D) False Negative
Answer:
(B) False Positive

Answer any 5 out of the given 6 questions. (1 × 5 = 5 marks)
Question 4.
(i) Which of the following is an Al-based application in healthcare? [1]
(A) Video editing
(B) Disease diagnosis
(C) Weather forecasting
(D) Currency conversion
Answer:
(B) Disease diagnosis

Explanation:
In healthcare, AI is widely used for disease diagnosis, as AI models can analyse medical data (like images, test results and patient history) to detect diseases more accurately and quickly. The other options (video editing, weather forecasting and currency conversion) do not specifically involve AI in healthcare.

(ii) Statement 1: AI systems need to be programmed explicitly for every possible scenario.
Statement 2: Machine learning enables AI to learn from data rather than being explicitly programmed. [1]
(A) Both Statement 1 and Statement 2 are correct.
(B) Both Statement 1 and Statement 2 are incorrect.
(C) Statement 1 is correct but Statement 2 is incorrect.
(D) Statement 2 is correct but Statement 1 is incorrect.
Answer:
(D) Statement 2 is correct but Statement 1 is incorrect.

(iii) What is the purpose of Data Acquisition in an Al-based project? [1]
(A) To finalise the project goal
(B) To collect and understand the data features relevant to the problem
(C) To analyse the system map for unrelated data
(D) To test the AI model without data
Answer:
(B) To collect and understand the data features relevant to the problem

Explanation:
Data Acquisition involves gathering the data that is relevant to the AI project. It helps in understanding which features of the data will be useful for solving the problem. This step is essential before training and testing the AI model.

(iv) Which algorithm is commonly used for edge detection in image processing? [1]
Answer:
Canny Edge Detection The most commonly used algorithm for edge detection in image processing is the Canny edge detection algorithm.

Explanation:
The Canny edge detector is popular because it effectively identifies the boundaries or edges in an image by finding areas with rapid intensity changes. It uses a multi-step process involving smoothing, gradient calculation, non-maximum suppression and edge tracing to detect and highlight edges.

(v) Which composnent of NLP is responsible for breaking down text into sentences or words? [1]
(A) Tokenisation
(B) Parsing
(C) Summarisation
(D) Sentiment Analysis
Answer:
(A) Tokenisation

Explanation:
Tokenisation is the process of breaking down text into smaller units, such as sentences or words. It is a fundamental step in natural language processing (NLP) that prepares the text for further analyses, like parsing or sentiment analysis.

(vi) Shweta developed a face recognition system using her family photos as the dataset. The system worked well for her family but couldn’t recognise strangers. What is this problem called? [1]
Answer:
Lack of generalisation.

Explanation:
The system works well for the family photos it was trained on but struggles with unfamiliar faces (strangers) because it has lack of generalisation. This means the model has not learned to generalise the features effectively to unseen data, leading to performance on new examples.

Answer any 5 out of the given 6 questions. (1 × 5 = 5 marks)
Question 5.
(i) Simran built a recommendation system for her school’s library that suggests books to students based on their reading history and preferences. This project primarily falls under which AI domain? [1]
(A) Natural Language Processing
(B) Machine Learning
(C) Robotics
(D) Data Science
Answer:
(B) Machine Learning

Erplanation:
A recommendation system that suggests books based on reading history and preferences relies on machine learning techniques to analyse patterns in data and make predictions. It uses algorithms to learn from user data and generate recommendations, which is a key application of machine learning.

(ii) In the context of AI, what does the term “dataset” refer to? [1]
Answer:
A dataset in the context of AI refers to a collection of data used to train, test, and evaluate machine learning models. It typically consists of multiple examples (data points) that may include features (input variables) and labels (output variables) in supervised learning, or just features in unsupervised learning.

(iii) ____ is the main purpose of natural language processing (NLP) in AI. [1]
(A) To process images
(B) To understand and generate human language
(C) To analyse data patterns
(D) To build physical robots
Answer:
(B) To understand and generate human language

(iv) What is machine learning?
(A) A method to teach machines through data
(B) A type of hardware
(C) A programming language
(D) A form of traditional learning
Answer:
(A) A method to teach machines through data

(v) In which learning model, the dataset which is fed to the machine is labelled? [1]
(A) Supervised
(B) Unsupervised
(C) Reinforcement
(D) All of these
Answer:
(A) Supervised

Explanation:
Supervised learning is a machine learning approach that’s defined by its use of labelled data sets. These data sets are designed to train or “supervise” algorithms into classifying data or predicting outcomes accurately. Using labelled inputs and outputs, the model can measure its accuracy and learn over time.

(vi) What does a high false positive rate indicate in a model? [1]
(A) The model is too strict.
(B) The model incorrectly predicts positive outcomes.
(C) The model has low accuracy.
(D) The model is perfectly calibrated.
Answer:
(B) The model incorrectly predicts positive outcomes.

Section B : Subjective Type Questions

Answer any 3 out of the given 5 questions on Employability Skills.
Answer each question in 20-30 words.
Question 6.
Discuss how the 7Cs of effective communication can be applied within an organisation to enhance overall communication effectiveness. [2]
Answer:
The 7Cs of effective communication—Clear. Concise,Concrete. Corred, Coherent. Courteous and Complete—can enhance communication within an organisation as follows:

1. Clear: Use simple bnguage and avoid argon to ensure messages are easily understood.
2. Concise: Keep messages short and to the point. using bullet points to highlight key ideas.
3. Concrete: Provide specific fads and figures to support your messages, avoiding vague statements.
4. Correct: Ensure all information is accurate and error free to build credibdity.
5. Coherent: Organise messages logically for a natural flow of ideas, using headings lo guide the reader
6. Courteous: Maintain a polite tone, acknowledging rectpients feelings and encouraging open dialogue.
7. Complete: Provide all necessary information, including context, details and required next steps. By applying these principles, organisations can improve understanding, engagement and overall communication effectiveness.

Question 7.
How do vacations help in relaxing your mood? [2]
Answer:
Vacation provides an opportunity to break away from daily routines and responsibilities, allowing
individuals to relax and unwind. Being in a new environment, away from work or home-related stressors, can help reset the mind and body,” promoting relaxation and reuvenat1on.

Question 8.
“File operations such as copying, moving and deleting help manage and organise data efficiently”.
What does ‘file operations’ mean in computer terminology? [2]
Answer:
In computer terminology. ‘file operations’ refer to task’ like copying, moving, renaming and deleting files and directories.

1. Copying: Duplicating a file to another location.
2. Moving: Transferring a file from orne location to another.
3. DeletIng, Removing a file from storage.
4. Renaming: Changing the file’s name.
5. Opaning/Cloeing: Accessing a file for use or dosing it after us

Question 9.
How do goals contribute to improving productivity? [2]
Answer:
Goals contribute to improving productivity by providing dear direction and focus. They help individuals priositise tasks, allocate time efficiently and stay motivated, which leads to more effective of resources and increased overall output.

Seek Common Ground: Identify shared interests and goals to find a mutually acceptable solution Focusing on common objectlves can facilitate compromise and improve collaboration.

Question 10 .
How does reliance on fossil fuels contribute to problems in sustainable development and suggest a solution? [2]
Answer:
Reliance on fossil fuels leads to environmental degradation and climate change. Transitioning to clean and renewable energy sources, such as solar and wind power, canbe a solution.

Answer any 4 out of the given 6 questions in 20-30 words each. (2 × 4 = 8 marks)
Question 11.
In self-driving cars, AI plays a significant role in analysing real-time data from the environment. What is the primary AI technique used to make driving decisions? [2]
Answer:
Solution: Shift towards renewable energy sources (like solar, wind and hydropower), which are cleaner, abundant and more sustainable. This transition would reduce environmental impact and promote long-term energy security.

Question 12.
Ramesh has a dataset of customers but does not have labels on customer types. He wants to group similar customers together. Which learning technique should Ramesh apply to cluster customers, and why? [2]
Answer:
Ramesh should use unsupervised learning, specifically clustering, since the goal is to group unlabelled data based on similarities. Clustering techniques like K-means or Hierarchical clustering can be used to group similar customers based on patterns in the data without the need for predefined labels.

Question 13.
Priya is integrating data from multiple sources into her AI system. What are two challenges she might face during data integration? [2]
Answer:
Data Inconsistency: Priya might encounter inconsistent formats, structures or missing values across different sources, making it difficult to merge and align the data.

Data Duplication: Integrating data from multiple sources could lead to redundant or duplicate entries, affecting the accuracy and quality of the system’s output.

Question 14.
How does the face lock system work in a smartphone? [2]
Answer:
The face lock system in a smartphone detects and captures the image.

1. It saves the features of the face at the beginning or the first time when the lock is applied.
2. After that whenever the features match it will unlock the smartphone.

Question 15.
What is the significance of converting the text into a common case? [2]
Answer:
In Text Normalisation, we undergo several steps to normalise the text to a lower level. After the removal of stop words, we convert the whole text into a similar case, preferably lower case. This ensures that the case sensitivity of the machine does not consider the same words as different just because of different cases.

Question 16.
If the number of true positives is 150, false positives is 30, true negatives is 100 and false negatives is 20, what is the confusion matrix? [2]
Answer:
To create a confusion matrix with the given values:
True Positives (TP): 150
False Positives (FP): 30
True Negatives (TN): 100
False Negatives (FN): 20
The confusion matrix can be represented as follows:

This matrix summarises the classification results, showing the counts of true and false positives and negatives.

Answer any 3 out of the given 5 questions in 50-80 words each. (4 × 3 = 12 marks)
Question 17.
Your cousin uses an Al-powered robot vacuum cleaner. Can you explain how this robot learns to clean rooms efficiently using AI? [4]
Answer:
The robot vacuum uses sensors to navigate around the house. It learns the layout of the rooms and figures out where the furniture is, so it can clean without bumping into things. This is an example of machine learning, a type of AI where the robot improves over time by gathering data from its surroundings. As it cleans more, it learns to avoid obstacles better and even figures out the best path to cover the whole floor efficiently.

1. Mapping: Uses sensors and cameras to create a map of the room layout, identifying obstacles.
2. Navigation: Employs algorithms to determine efficient cleaning paths while avoiding obstacles.
3. Data Analysis: Collects data on cleaning patterns and identifies high-traffic areas.
4. Machine Learning: Learns from past cleaning sessions to optimise routes and methods.
5. User Feedback: Incorporates user feedback to improve cleaning strategies over time.

These processes enable the robot vacuum cleaner to clean rooms efficiently and adaptively.

Question 18.
Zara, a school teacher, notices that students have trouble staying engaged in class. She wants to create an Al-based app to track student engagement. Using the 4W Problem Canvas, help Zara define her project.
Answer:

1. What: The issue is that students are losing interest during class, leading to lower engagement and participation.
2. Why: A lack of engagement reduces learning outcomes and can impact students’ overall academic performance and motivation.
3. Who: The students, their parents and the teachers are directly affected by this issue.
4. Where: The problem occurs within classroom settings, primarily during lectures and presentations.

Question 19.
Identify the components of an AI system as illustrated in this diagram. [4]

Answer:
The components of an AI system as illustrated in the diagram are:

1. Input data: This is the raw data that the AI system processes.
2. Learning algorithm: This is the algorithm that the system uses to learn from the data.
3. Model: This is the output of the learning process, which represents the system’s understanding of the data.
4. Output: This is the result of the AI system’s processing, which can be a prediction, classification or other task.

Question 20.
Rahul’s grandmother loves cooking and writes recipes in her native language. Rahul wants to develop an AI system that converts her handwritten recipes into English. What challenges might the AI face when trying to read handwritten text and translate it into another language? [4]
Answer:
The AI faces two major challenges: recognising handwritten text (which is often irregular) and translating between languages. Handwritten text may vary in style, slant and legibility, making Optical Character Recognition (OCR) difficult. AI systems trained on typed text might not perform well when faced with handwriting. Additionally, translating involves not just converting words but understanding the meaning of entire sentences, including culturally specific references, cooking terms, and ingredient names that may not have direct equivalents in other languages. This requires sophisticated NLP algorithms and a well-curated dataset for accuracy.

Question 21.
A machine learning model is developed to predict whether students will pass or fail an exam. The confusion matrix is:

(i) Identify the number of true positives (TP) and false positives (FP).
(ii) Calculate the precision and recall for the model.
Answer:
True Positives (TP)=70
False Positives (FP)=30
Precision = \(\frac{70}{70+30}=\frac{70}{100}\) = 0.7
Recall = \(\frac{70}{70+20}=\frac{70}{90}\) ≈ 0. 778

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