Students can access the CBSE Sample Papers for Class 10 AI with Solutions and marking scheme Set 6 will help students in understanding the difficulty level of the exam.
CBSE Sample Papers for Class 10 AI Set 6 with Solutions
General Instructions
- Please read the instructions carefully.
- This Question Paper consists of 21 questions in two sections: Section A & Section B.
- Section A has Objective type questions whereas Section B contains Subjective type questions.
- 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.
- All questions of a particular section must be attempted in the correct order.
- Section A: Objective Type Questions (24 Marks)
- This section has 5 questions.
- There is no negative marking.
- Do as per the instructions given.
- Marks allotted are mentioned against each question/part.
- 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
Question 1.
Answer any 4 out of the given 6 questions on Employability Skills (4×1=4)
(i) ………… of the meaning of communication comes from body language.
(a) 10 %
(b) 20 %
(c) 50 %
(d) 55 %
Answer:
(d) 55 %
(ii) Over the years, with economic development, there has been an increase in ____ .
(a) Water Pollution
(b) Air Pollution
(c) Noise Pollution
(d) All of these
Answer:
(d) All of these
(iii) Vedika wakes up at 5 am and goes to her hockey classes. Then she comes home and get ready for her school. She always does her work by herself or by taking little assistance from her mother. No one has to tell her to do the work. This is an example of ____
(a) Self-motivation
(b) External motivation
(c) Both self and external motivation
(d) Not very specific type
Answer:
(a) Self-motivation
(iv) Assertion (A) Entrepreneurs often engage in market research before launching a new product. Reason (R) Market research helps entrepreneurs understand customer needs and preferences, reducing the risk of product failure.
(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
(v) What is the correct combination of the shortcut keys to Cut and Paste?
(a) Ctrl+X & Ctrl+V
(b) Ctrl+C & Ctrl+P
(c) Ctrl+C & Ctrl+V
(d) Ctrl+X & Ctrl+P
Answer:
(a) Ctrl+X & Ctrl+V
(vi) Physical exercise helps to raise ……….., which are chemicals in the brain that act as natural painkillers.
(a) Enzyme
(b) Endomorphines
(c) Ectomorphines
(d) Octomorphines
Answer:
(b) Endomorphines
Question 2.
Answer any 5 out of the given 6 questions. (5×1=5)
(i) What is the central focus of virtue-based value-based frameworks?
(a) Maximizing utility
(b) Protecting human rights
(c) Aligning actions with ethical principles and beliefs
(d) Ensuring compliance with legal regulations
Answer:
(c) Aligning actions with ethical principles and beliefs
(ii) Statement 1 Clustering is a technique used in unsupervised learning to group similar data points together.
Statement 2 Clustering is used in tasks like spam filtering and stock price prediction.
Choose the correct option:
(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:
(c) Statement 1 is correct but Statement 2 is incorrect
(iii) Which method is used to represent colors in digital images?
(a) RGB (Red, Green, Blue)
(b) HSV (Hue, Saturation, Value)
(c) CMYK (Cyan, Magenta, Yellow, Black)
(d) All of these
Answer:
(d) All of these
(iv) You are building a text analysis application that requires tokenization, stemming, and part-of-speech tagging. To efficiently implement these NLP tasks using Python, which library would best suit your needs due to its wide range of language processing tools?
(a) TensorFlow
(b) PyTorch
(c) NLTK (Natural Language Toolkit)
(d) Scikit-learn
Answer:
(c) NLTK (Natural Language Toolkit)
(v) Assertion (A) Ethical frameworks are important for AI to ensure fairness and prevent harm in decision-making.
Reason (R) Sector-based frameworks focus on applying ethics to specific industries, such as bioethics in healthcare, which ensures patient privacy and fairness in medical decisions.
(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
(vi) The layer in a neural network is responsible for learning patterns from the input data is:
(a) Output
(b) Hidden
(c) Loss
(d) Activation
Answer:
(b) Hidden
Question 3.
Answer any 5 out of the given 6 questions. (5×1=5)
(i) Differentiate between Prediction and Reality.
(a) Prediction is the input given to the machine to receive the expected result of the reality.
(b) Prediction is the output given to match the reality.
(c) The prediction is the output which is given by the machine and the reality is the real scenario in which the prediction has been made.
(d) Prediction and reality both can be used interchangeably.
Answer:
(c) The prediction is the output which is given by the machine and the reality is the real scenario in which the prediction has been made.
(ii) Which of the following is an example of a stop word?
(a) Noun
(b) Verb
(c) Adjective
(d) The
Answer:
(d) The
(iii) Identify the incorrect statement(s) from the following:
(i) Deep learning is a subset of Machine Learning
(ii) Machine Learning is a subset of Deep Learning
(iii) Artificial Intelligence is a subset of Deep Learning
(iv) Deep Learning is the advanced form of AI and ML
(a) only (i)
(b) (ii) and (iii)
(c) (i) and (ii)
(d) Only (iii)
Answer:
(b) (ii) and (iii)
(iv) Which of the following best describes a Rule-Based Approach in AI?
(a) It learns from patterns in data and makes predictions.
(b) It uses predefined rules created by a developer to make decisions.
(c) It continuously adapts and improves over time with more data.
(d) It is a type of reinforcement learning model.
Answer:
(b) It uses predefined rules created by a developer to make decisions.
(v) Which technique is used to recognize and understand text in images or videos?
(a) Optical character recognition (OCR)
(b) Motion detection
(c) Feature extraction
(d) Image stitching
Answer:
(a) Optical character recognition (OCR)
(vi) Name the AI-based voice assistant developed by Apple that can answer questions, set reminders, and perform tasks on iPhones.
Answer:
Siri
Question 4.
Answer any 5 out of the given 6 questions. (5×1=5)
(i) What is an example of Machine Learning application?
(a) Virtual assistants like Alexa and Siri
(b) Anomaly detection in banking transactions
(c) Self-driving cars analyzing real-time road conditions
(d) All of the above
Answer:
(d) All of the above
(ii) A teacher’s marks prediction system predicts the marks of a student as 75, but the actual marks obtained by the student are 80. What is the absolute error in the prediction?
(a) 5
(b) 10
(c) 15
(d) 20
Answer:
(a) 5
(iii) Statement 1 The output given by the AI model is known as reality.
Statement 2 The real scenario is known as prediction.
(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:
(b) Both Statement 1 and Statement 2 are incorrect.
(iv) Artificial neural networks are inspired by the structure and function of:
(a) The human brain
(b) Quantum computers
(c) Complex mathematical models
(d) High-speed processors
Answer:
(a) The human brain
Note
- Artificial Neural Networks (ANNs) mimic biological neurons in the human brain.
- Neurons (nodes) are organized in layers – input, hidden, and output.
- They process input through weighted connections, making decisions like a brain.
(v) Name any two methods of collecting data.
(a) Surveys and Interviews
(b) Rumors and Myths
(c) Al models and applications
(d) Imagination and thoughts
Answer:
(a) Surveys and Interviews
(vi) Reinforcement learning is particularly useful for scenarios where:
(a) Large amounts of labeled data are available.
(b) The desired outcome is clear, but the path to achieve it is unknown.
(c) The data is structured and easily categorized.
(d) The task requires reasoning and logical deduction.
Answer:
(b) The desired outcome is clear, but the path to achieve it is unknown.
Question 5.
Answer any 5 out of the given 6 questions. (5×1=5)
(i) Which of the following best describes how Computer Vision (CV) is used in crop monitoring through AI?
(a) It monitors weather patterns using satellite images only.
(b) It identifies crop diseases and growth stages through image analysis from drones and cameras.
(c) It records soil nutrients using handheld sensors.
(d) It helps in online trading of agricultural products.
Answer:
(b) It identifies crop diseases and growth stages through image analysis from drones and cameras.
(ii) Statement 1 Text normalisation is a key step in natural language processing (NLP).
Statement 2 It involves cleaning and preprocessing text data to make it consistent and usable for different NLP tasks.
(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
(iii) What will be the outcome, if the Prediction is “Yes” and it matches with the Reality? What will be the outcome, if the Prediction is “Yes” and it does not match with the Reality?
(a) True Positive, True Negative
(b) True Negative, False Negative
(c) True Negative, False Positive
(d) True Positive, False Positive
Answer:
(d) True Positive, False Positive
(iv) The ……….. canvas helps you in identifying the key elements related to the problem.
(a) Problem scoping
(b) 4Ws Problem
(c) Project cycle
(d) Algorithm
Answer:
(b) 4Ws Problem
Mistake Alert
Many confuse this with ‘Problem Scoping’ because both are related to the first stage, but 4W/s Canvas is the actual tool used within problem scoping to explore Who, What, Where, and Why.
(v) Which of the following scenario result in a high false positive cost?
(a) Viral outbreak
(b) Forest fire
(c) Flood
(d) Spam filter
Answer:
(d) Spam filter
(vi) Which method is used to break down a sentence into its grammatical components?
Answer:
Chunking
Section B
Subjective Type Questions
Answer any 3 out of the given 5 questions on Employability skills. Answer each question in 20-30 words. (3×2=6)
Question 6.
Write any three characteristics of an independent person.
Answer:
The three characteristics of an independent person are:
- Self-Reliance: Independent individuals are capable of taking care of themselves and managing their own needs without constantly relying on others for support.
- Confidence: They exhibit a strong sense of self-assurance and belief in their abilities.
- Resourcefulness: They are adept at finding solutions to problems, using available resources creatively, and adapting to changing circumstances without needing constant guidance or assistance from others.
Question 7.
Ravi is studying in Grade IX. In the PTM, his class teacher tells his parents that Ravi fails to adhere to the instructions given in the class. Ravi’s parents feel that this can be because of some communication barriers. Write down the factors responsible for internal barriers.
Answer:
The factors responsible for internal barriers are:
- Intense emotions
- Poor listening skills
- Prejudice
- Different view points
- Different cultural backgrounds
Question 8.
In India, a rural entrepreneur starts a solar panel business in a remote village. This initiative not only provides sustainable energy to the local community but also creates jobs and stimulates economic activity in the region. How does this entrepreneurial venture contribute to regional development?
Answer:
This venture promotes regional development by providing reliable energy, which enhances local productivity and quality of life. It creates employment opportunities, fosters economic growth, and encourages further investments in the region, contributing to overall development.
Question 9.
What is one significant obstacle to achieving sustainable development?
Answer:
One significant obstacle is managing the trade-off between rapid economic growth and environmental conservation. Developing regions often prioritize industrialization, which can lead to environmental harm, making it challenging to simultaneously achieve economic progress and sustainability.
Question 10.
How can we ensure our safety in the cyber world? Mention any three ways.
Answer:
The ways to ensure our safety in cyber world are the following:
- Use strong, unique passwords Create passwords that are complex, with a mix of letters, numbers, and symbols, and ensure each account has a different password.
- Enable two-factor authentication Add an extra layer of security by requiring a second form of verification, such as a code sent to your phone, in addition to your password.
- Be cautious of phishing scams Always verify the source of emails, links, or attachments before interacting. Phishing attempts often masquerade as legitimate communications to steal personal information.
Answer any 4 out of the given 6 questions in 20-30 words each. (4×2=8)
Question 11.
What is bioethics and how does it relate to AI?
Answer:
Bioethics is the study of ethical issues in biology and medicine. In AI, it addresses concerns like patient data privacy, robotic surgery, and fairness in healthcare AI. A case study may highlight ethical dilemmas faced in real-world health technology use.
Question 12.
Sirisha and Divisha want to make a model which will organise the unlabeled input data into groups based on features. Which learning model should they use and why?
Answer:
Clustering model/Unsupervised learning is used to organise the unlabelled input data into groups based on features.
Clustering is an unsupervised learning algorithm which can cluster unknown data according to the patterns or trends identified out of it. The patterns observed might be the ones which are known to the developer or it might even come up with some unique patterns out of it.
Question 13.
What role does computer vision play in improving diagnosis speed in healthcare?
Answer:
Computer vision automates the analysis of X -rays, MRIs, and CT scans, enabling doctors to diagnose conditions faster. It reduces manual workload, minimizes errors, and ensures consistent, efficient interpretation of medical images, especially in high-volume hospital settings.
Question 14.
Can you explain how different tasks are handled in various AI domains without naming them directly?
Answer:
AI tasks are categorized based on how machines learn, think, and act. Some systems analyze data to find patterns, others understand human speech or vision, and some make decisions or move autonomously, mimicking intelligent human-like behavior in real-life situations.
Question 15.
Describe two practical uses of Natural Language Processing in real-world scenarios.
Answer:
Sentiment Analysis Analyzing customer reviews or social media posts to understand public opinion about products or services.
Chatbots/Virtual Assistants Providing automated customer support or answering queries through natural language conversations.
Question 16.
What will happen if you deploy an AI model without evaluating it with known test set data?
Answer:
If an AI model is deployed without evaluation, it may produce inaccurate predictions and fail in real-world applications. The model might overfit training data, leading to biased and unreliable decisions. This can result in financial losses, security risks, or ethical issues.
Answer any 3 out of the given 5 questions in 50-80 words each. (3×4=12)
Question 17.
With reference to NLP, explain the following terms in details with the help of suitable example:
(i) Term Frequency
(ii) Inverse Document Frequency
Answer:
(i) Term Frequency Term Frequency (TF) is a measure used in natural language processing to quantify the frequency of a term (word) in a document relative to the total number of terms in that document. It indicates how often a particular term appears within a document.
Example Suppose we have a document containing 100 words, and the word “apple” appears 5 times in that document. The term frequency of “apple” in this document would be: TF(“apple”, document) =5 / 100=0.05.
(ii) Inverse Document Frequency Inverse Document Frequency (IDF) is a measure used to determine the importance of a term in a collection of documents. It quantifies how rare or common a term is across all documents in the corpus. Terms that occur frequently in many documents are considered less important, while terms that occur rarely in few documents are considered more important.
Example: Suppose we have a corpus containing 1,000 documents, and the term “apple” appears in 100 of these documents. The inverse document frequency of “apple” would be:
IDF (“apple” )=\log (1000 / 100)=\log (10)=1
Question 18.
With reference to evaluation stage of AI project cycle, explain the term Accuracy. Also give the formula to calculate it.
Answer:
In the evaluation stage of an AI project cycle, accuracy is a key metric used to assess the performance of a machine learning model. It measures the proportion of correctly classified instances out of all instances examined. In other words, accuracy indicates how often the model is correct in its predictions.
Accuracy =\(\frac{(\mathrm{TP}+\mathrm{TN})}{(\mathrm{TP}+\mathrm{TN}+\mathrm{FP}+\mathrm{FN})}\) x 100
Question 19.
Consider the following diagram. It explains how a system uses input data and several interconnected layers to learn patterns and improve decisions. Identify the concept and explain its working.
Input Data
↓
Hidden Layer 1
↓
Hidden Layer 2
↓
Output
Answer:
The concept shown is a Neural Network. It mimics the human brain using layers of interconnected nodes (neurons). Data passes through input, hidden, and output layers. Each neuron processes input with weights and biases, then passes it forward. The network learns patterns by adjusting weights using feedback (backpropagation). Neural networks are used in image recognition, speech processing, and predictive modeling, offering accurate results through deep learning and multiple iterations.
Question 20.
What happens when machines start making decisions on their own?
Answer:
Machines that make autonomous decisions fall under the Cognitive or Decision-Making Domain of AI. These systems process input, evaluate alternatives, and choose the best action without human intervention. This is seen in areas like robotics, where machines navigate obstacles, or in smart assistants that schedule meetings. These decisions are based on prior learning and logic. While it boosts efficiency, it also raises ethical concerns about accountability and trust, making the design of ethical AI essential.
Question 21.
Given the following confusion matrix:
| Predicted Positive |
Predicted Negative |
|
| Actual Positive | 40 | 15 |
| Actual Negative | 10 | 80 |
Calculate the values of True Positives (TP), False Positives (FP), True Negatives (TN) and False
Negatives (FN). Additionally, compute the accuracy and recall of the model.
Answer:
True Positives (TP): 40
False Positives (FP): 10
True Negatives (TN): 80
False Negatives (FN): 15
Accuracy =(TP+TN)/Total Samples
=(40+80) /(40+15+10+80)
=120/145 0.828 or 82.8%
Recall =TP/(TP+FN)
= 40 /(40+15)=40/55
0.72740=0.727 or 72.7%