Preparing for board exams becomes much easier when students practice previous year question papers, especially for subjects like Artificial Intelligence (AI Code 417). The CBSE Class 10 AI 417 Question Paper 2021–22 Term 2 with Solution is a powerful resource that helps students understand the exam pattern, marking scheme, and important topics that covered in session 2021-22.
When CBSE conducted Class 10 AI 417 Term 2 Board exams after the pandemic phase, the focus shifted more towards theoretical understanding, case-based questions, and application-based learning. Solving this paper gives students a real exam experience and improves their time management skills.
CBSE CLASS 10 ARTIFICIAL INTELLIGENCE (417) – TERM 2 - SOLUTION
Class 10 AI (Code 417) - Previous Year Question Paper
(Session 2021-22)
Series ΩQAΩA
Question Paper Code 104 Set 4
Question Paper Code 104 Set 4
Time allowed : 1 hour
Maximum Marks : 25
Maximum Marks : 25
General Instructions:
- Please read the instructions carefully.
- This question paper is divided into 03 Sections viz., Section A; Section B and Section C.
- Section A is of 05 marks and has 06 questions on Employability skills.
- Question numbers 01 to 04 are one mark questions. Attempt any three questions.
- Questions numbers 05 and 06 are two marks questions. Attempt any one question.
- Section B is of 12 marks and has 12 questions on Subject specific skills.
- Question numbers 07 to 12 are one mark questions. Attempt any four questions.
- Question numbers 13 to 18 are two marks questions. Attempt any four questions.
- Section C is of 08 marks and has 03 Competency-based questions.
- Question numbers 19 to 21 are four marks questions. Attempt any two questions.
- Do as per the instructions given in the respective sections.
- Marks allotted are mentioned against each section /question.
Section A (3+2=5 Marks)
Answer any 3 questions out of given 4 questions. (1×3=3)
1. What is wage employment?
Ans: Wage employment is a type of work where a person is hired by an employer and is paid a fixed amount of money (wage or salary) for the work they do.
Example: A factory worker paid per day, a teacher paid monthly salary
2. How food is one of the major problems related to sustainable development? Discuss briefly.
Ans: Food is a major problem in sustainable development because growing population increases demand, causing shortage, wastage of resources, environmental damage, and unequal food distribution worldwide.
3. “To get success, every business idea needs to be unique or special.” Is the given statement a myth or fact?
Ans: The given statement is a myth. Success depends more on execution and customer satisfaction than just uniqueness.
4. What is the major purpose of the Sustainable Development Goals?
Ans: The major purpose of the Sustainable Development Goals (SDGs) is to end poverty, protect the environment, and ensure peace and prosperity for all people by 2030.
Answer any 1 question out of the given 2 questions. (2×1=2)
5. Write any four common functions of an entrepreneur.
Ans: Here are four common functions of an entrepreneur are:
1. Identifying business opportunities
2. Planning and organizing the business
3. Arranging capital and resources
4. Taking risks
5. Marketing and selling products/services
6. Maintaining records and accounts
6. Sustainable development can actually happen only when each one of us works towards it. Mention any four ways which we can do at our end to reduce inequality.
Ans: Here are four ways we can help reduce inequality at our level:
(i) Treat everyone with respect, without discrimination
(ii) Support education for all, especially poor children
(iii) Share resources and help needy people
(iv) Promote equal opportunities for boys and girls
Section B (4+8=12 Marks)
Answer any 4 questions out of the given 6 questions. (1×4=4)
7. What is NLP?
Ans: NLP (Natural Language Processing) is a branch of Artificial Intelligence that enables computers to understand, interpret, and respond to human language in text or speech form.
8. Mention any two commonly used applications of NLP.
Ans: (i) Language translation (like Google Translate)
(ii) Chatbots and virtual assistants
9. Name any two currently popular virtual assistants.
Ans: (i) Siri (ii) Alexa (iii) Google Assistant (iv) Cortana (v) Microsoft Copilot (vi) Samsung Bixby
10. Name the process of dividing whole corpus into sentences.
Ans: The process of dividing a whole corpus (large text) into individual sentences is called Sentence Tokenization (or Sentence Segmentation).
11. With reference to evaluation process of understanding the reliability of any AI model, define the term True Positive.
Ans: True Positive (TP) means the cases where an AI model correctly predicts a positive result.
Example: If an AI system detects spam email and correctly identifies a spam message as spam, it is a True Positive.
So, True Positive = Correct positive prediction by the AI model.
12. What is F1 score?
Ans: F1 Score is a way to measure how well an AI model is working. It looks at both how many correct answers the model gives (precision) and how many real positive cases it is able to find (recall). By combining these two, F1 Score shows the overall performance of the model.
For example, if an AI system checks emails for spam and correctly finds most spam messages but also makes a few mistakes, the F1 Score helps tell how good the system is in total.
Answer any 4 questions out of the given 6 questions. (2×4=8)
13. Differentiate between Script-bot and Smart-bot.
Ans:
| Basis | Script-bot | Smart-bot |
| Working | Works on fixed rules and pre-written scripts | Uses AI and machine learning to respond |
| Learning | Cannot learn from new data | Can learn and improve over time |
| Flexibility | Gives same responses every time | Gives different responses based on situation |
| Understanding | Does not understand user intent properly | Understands user language using NLP |
14. What is the purpose of Evaluation stage of AI project cycle? Discuss briefly.
Ans: The Evaluation stage of the AI project cycle is used to check how well an AI model is performing. In this stage, the model’s results are compared with actual correct results to measure accuracy, precision, recall, and F1 score. It helps in finding errors and weaknesses in the model. Based on evaluation, improvements are made to increase the model’s reliability and performance.
15. What is Tokenization? Count how many tokens are present in the following statement:
I find that the harder I work, the more luck I seem to have.
Ans: Tokenization is the process of breaking a text into smaller parts called tokens (usually words or sentences) so that a computer can understand and process it easily.
Now, let’s count the tokens in the given statement:
Tokens (words):
I | find | that | the | harder | I | work | the | more | luck | I | seem | to | have
Total tokens = 14
(Punctuation like comma and full stop are usually ignored in basic tokenization.)
16. Kaira, a beginner in the field of NLP is trying to understand the process of Stemming. Help her in filling up the following table by suggesting appropriate affixes and stem of the words mentioned there:
| S.No. | Word | Affixes | Stem |
| i. | Tries | ||
| ii. | Learning |
Ans:
| S.No. | Word | Affixes | Stem |
| i. | Tries | -es | tri |
| ii. | Learning | -ing | learn |
17. With reference to evaluation stage of AI project cycle, explain the term Accuracy. Also give the formula to calculate it.
Ans: In the evaluation stage of the AI project cycle, Accuracy is used to measure how many predictions made by the AI model are correct out of the total predictions. Simply, it shows how often the model gives the right answer.
Formula for Accuracy:
Accuracy = (Number of correct predictions ÷ Total predictions) × 100
or
Accuracy = (True Positives + True Negatives) ÷ (Total cases)
or
Accuracy=(TP+TN)/(TP+TN+FP+FN)
Higher accuracy means the AI model is performing better and giving more correct results.
18. Explain the following picture which depicts one of the processes on NLP. Also mention the purpose which will be achieved by this process.
Ans: The given picture shows the NLP process called Text Normalization (Case Normalization). In the image, different forms of the word like HELLO, HeLLo, hELLO, Hello are all converted into a single standard form “hello” (usually in lowercase).
This process changes all words into a common format so that the computer treats them as the same word instead of different ones.
The main purpose is to reduce confusion, improve accuracy, and make text data clean and consistent for better processing in NLP tasks.
Section C (4×2=8) - Competency-Based Skills
Answer any 2 questions out of the given 3 questions.
19. Consider the text of following documents:
Document 1: Sahil likes to play cricket
Document 2: Sajal likes cricket too
Document 3: Sajal also likes to play basketball
Apply all the four steps of Bag of words model of NLP on the above given documents and generate the output.
Ans: Step 1: Tokenization (split into words)
- Doc 1: Sahil, likes, to, play, cricket
- Doc 2: Sajal, likes, cricket, too
- Doc 3: Sajal, also, likes, to, play, basketball
Step 2: Text Normalization (convert to lowercase)
- Doc 1: sahil, likes, to, play, cricket
- Doc 2: sajal, likes, cricket, too
- Doc 3: sajal, also, likes, to, play, basketball
Step 3: Create Vocabulary (unique words)
- sahil, likes, to, play, cricket, sajal, too, also, basketball (Total = 9 words)
| Words ↓ / Docs → | Doc 1 | Doc 2 | Doc 3 |
| sahil | 1 | 0 | 0 |
| likes | 1 | 1 | 1 |
| to | 1 | 0 | 1 |
| play | 1 | 0 | 1 |
| cricket | 1 | 1 | 0 |
| sajal | 0 | 1 | 1 |
| too | 0 | 1 | 0 |
| also | 0 | 0 | 1 |
| basketball | 0 | 0 | 1 |
Bag of Words (BoW) Representation / Final Outcome:
- Document 1 → [1,1,1,1,1,0,0,0,0]
- Document 2 → [0,1,0,0,1,1,1,0,0]
- Document 3 → [0,1,1,1,0,1,0,1,1]
20. With reference to NLP, explain the following terms in detail with the help of suitable example:
(i) Term frequency
Ans: Term Frequency shows how many times a particular word appears in a document. It tells us how important a word is within a single document.
Formula:
TF = Number of times a word appears in a document
Example:
Sentence: “AI is useful. AI is the future of AI.”
The word “AI” appears 3 times.
So, Term Frequency (TF) of “AI” = 3
This means “AI” is an important word in this document.
(ii) Inverse Document Frequency
Ans: Inverse Document Frequency shows how rare or common a word is across many documents. Words that appear in many documents (like is, the, and) are less important. Words that appear in fewer documents are more important.
Purpose:
To reduce the importance of common words and increase the importance of unique words.
Example:
Suppose we have 10 documents:
The word “AI” appears in 2 documents
The word “is” appears in 10 documents
“AI” is more meaningful than “is”
So, Inverse Document Frequency (IDF) of “AI” will be high and IDF of “is” will be low
21. Traffic Jams have become a common part of our lives now-a-days. Living in an urban area means you have to face traffic each and every time you get out on the road. Mostly, school students opt for buses to go to school. Many times the bus gets late due to such jams and students are not able to reach their school on time. Thus, an AI model is created to predict explicitly if there would be a traffic jam on their way to school or not. The confusion matrix for the same is
| the Confusion Matrix | Actual : 1 | Actual : 0 |
| Prediction : 1 | 50 | 50 |
| Prediction : 2 | 0 | 0 |
Explain the process of calculating F1 score for the given problem.
Ans: Here,
True Positive (TP) = 50 (correctly predicted traffic jam)
False Positive (FP) = 50 (predicted jam but actually no jam)
False Negative (FN) = 0 (missed traffic jam)
True Negative (TN) = 0
Recall = True PositiveTrue Positive + False Negative
= 5050 + 50
= 50100
=0.5
Recall = TPTP + FN
= 5050 + 0
= 1
Recall = 2 x (Precision × Recall)(Precision + Recall)
= 2 x (0.5 x 1)0.5 + 1
= 11.5
≈ 0.67
F1 Score = 0.67 (approximately)
Download Now - Class 10 AI 417 Previous Year Question Paper (PYQP) 2021-22 Term 1 with Solution
