AI Facilitator Handbook for Class 9

माध्यमिक - AI Facilitator Handbook

Page 1

  • केंद्रीय शिक्षा बोर्ड

  • भारत

  • असतो मा सद्गमय (Sanskrit saying - "Lead us from the unreal to the real")

  • ARTIFICIAL INTELLIGENCE

  • Class 9 Facilitator Handbook

Page 2

  • Curated with support from Intel®

    • Intel

Page 3

  • Acknowledgements

    • Patrons:

    • Mr. Rahul Singh, IAS, Chairperson, Central Board of Secondary Education

    • Dr. Biswajit Saha, Director (Skill Education & Training), CBSE

    • Ms. Sarita Manuja, Educational Consultant & Program Director, NHES

    • Ms. Shatarupa Dasgupta, National Program Manager, Intel Digital Readiness Program

    • Ms. Shilpa Sethi, DAV Public School, Gurugram

    • Ms. Shipra Panigrahi, Indirapuram Public School, Ghaziabad

    • Ms. Sonu Lohchab, D.A.V. Public School, Gurugram

    • Ms. Ritu Debnath, Gurukul Global School, Chandigarh

    • Ms. Anshu Banerjee, Uttam School for Girls, Ghaziabad

    • Ms. A. Sayeesubbulakshmi, Delhi Public School, Bengaluru

    • Ms. Shweta Khurana, Senior Director APJ, Intel Education

    • Sh. Ravinder Pal Singh, Joint Secretary, Department of Skill Education, CBSE

    • Ms. Saloni Singhal, Program Manager APJ, Intel Digital Readiness Programs

    • Content Curation Team:

    • Ms. Ambika Saxena, Intel AI for Youth Coach

    • Ms. Prachi Chandra, Intel AI for Youth Coach

Page 4

  • About the Book

    • Introduction to AI

    • AI is seen as a cornerstone of future innovation and growth.

    • Nations are positioning themselves to utilize AI's transformative potential.

    • In India, AI emerges as a tool for economic growth and social development.

    • CBSE aims to equip students with necessary AI skills through collaboration with Intel.

    • Key Features of the Handbook:

    • Enhanced Content: Detailed AI concepts with new examples.

    • Real-Life Examples: Practical scenarios for better comprehension.

    • AI Solutions for Social Impact: Projects aimed at social change.

    • Use Case Walkthroughs: Demonstrating practical implementations of AI across various domains.

Page 5

  • CBSE Grade IX AI Curriculum 2024-25

    • Units/Subunits Sessions Topics Hours

    • 1.1 AI Reflection, Project Cycle and Ethics (10 hours)

    • Define Artificial Intelligence (AI)

    • Applications of AI in everyday life

    • The three domains of AI and their applications

    • 1.2 The AI Project Cycle (30 hours)

    • Importance of the AI project cycle

    • Structuring AI problem statements

    • 1.3 AI Ethics (15 hours)

    • Difference between ethics and morality

    • Ethical dilemmas in AI

    • Identifying AI bias

    • 2.1 Data Literacy (10 hours)

    • Basics of Data Literacy

    • Data security and privacy

    • Cyber Security Best Practices

    • 2.2 Acquiring, Processing, and Interpreting Data (20 hours)

    • Types of data sources

    • Data preprocessing basics

    • 2.3 Project - Interactive Data Dashboard & Presentation (20 hours)

    • Data visualization importance

    • Creating interactive charts with no-code tools.

    • 3.1 Math for AI (5 hours)

    • Importance of math in AI applications

    • 3.2 Statistics (10 hours)

    • Use of statistics in AI applications

    • 3.3 Probability (10 hours)

    • Use of probability in AI applications

    • 4 Introduction to Generative AI (20 hours)

    • Definition and Overview of Generative AI

    • Applications and Use cases

    • Total 150 hours

Page 6

  • Unit 1: AI Reflection

  • Unit 1.1 – Understanding AI

    • Definition of Artificial Intelligence:

    • A machine's ability to mimic human-like traits such as learning, decision-making, and prediction.

    • AI can perform tasks typically requiring human cognitive functions.

    • Applications of AI:

    • AI is expected to impact every field.

Page 7

  • Engagement Activity:

    • Reflect on the possible impacts of AI on daily life.

Page 8

  • Activity: Game Time:

    • Game 1: Rock, Paper, Scissors

    • Participants engage in strategic play against AI.

    • Game 2: Semantris

    • A word association game powered by AI.

    • Game 3: Quick, Draw

    • A drawing game where AI guesses drawn items.

Page 9

  • Game Analysis:

    • Insights gained from the activities regarding AI in three domains:

    • Natural Language Processing

    • Computer Vision

    • Data usage for AI

Page 10

  • AI Game Challenge:

    • Identifying games played and outcomes from activities.

Page 11

  • Pair Activity:

    • Reflect on learnings from the AI games based on data interpretation, NPL, CV, etc.

Page 12

  • Different Domains of AI Applications:

    • Face Lock in Smartphones: Uses computer vision for biometric recognition.

    • Smart Assistants: Use NLP to recognize speech and provide responses.

Page 13

  • Practical Applications:

    • AI in Fraud Detection in finance; uses customer data for risk analysis.

    • AI in Medical Imaging; assists doctors by interpreting images.

Page 14

  • Revision Time:

    • Quiz on AI concepts, applications, and technologies.

Page 15

  • Teamwork Activity:

    • Participate in role-playing dialogues mimicking chatbots to foster understanding.

Page 16

  • Unit 1.2: AI Project Cycle:

    • Lesson Title: AI Project Cycle

    • Overview of the project cycle stages: Problem scoping, data acquisition, modeling, evaluation, and deployment.

Page 17

  • Example Problem Scenario:

    • Pest infestation in cotton crops; solution via AI modeling strategies.

Page 18

  • Data Acquisition Examples:

    • Details on gathering necessary data for project completion.

Page 19

  • CottonAce Application Features:

    • Use of AI in pest management; aids in crop protection.

Page 20

  • Conclusion of AI Project Cycle:

    • Emphasizes efficiency and modularity in problem-solving.

Page 21

  • AI Project Cycle Mapping:

    • Illustration of problem mapping discussed.

Page 22

  • Problem Scoping:

    • Selection of a suitable theme for project definition.

Page 23

  • Goal Setting for Projects:

    • Articulating the goal following problem identification.

Page 24

  • 4Ws Problem Canvas:

    • Who, What, Where, Why for streamlined understanding.

Page 25

  • Problem Statement Template:

    • Structuring problems in a concise manner.

Page 26

  • Data Acquisition Methods:

    • Sources highlighted for effective data gathering.

Page 27

  • Data Features:

    • Attributes relevant to datasets being analyzed.

Page 28

  • Unit 2 - Data Literacy

    • Focus on principles of data literacy, privacy, security etc.

Page 29 - 100

  • Various Content on Data Literacy, data collection, data processing, interpretation, visualization, and methodological practices in AI.

Page 101 - 134

  • Concepts of Math for AI:

    • Exploring the essential mathematical foundations for AI, covering statistics, probability, calculus, and linear algebra.

  • Applications to real-world scenarios emphasizing AI interconnections with mathematics.

Page 135

  • Answers to MCQs and Revision Activities.

Summary

  • The Facilitator Handbook serves as a comprehensive resource to understand AI and its applications for Class 9 students, detailing theoretical and practical insights along with ethical considerations, establishing a basis for effective engagement with technology in education.