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Standards Mapping

for Georgia Foundations of Artificial Intelligence

57

Standards in this Framework

41

Standards Mapped

71%

Mapped to Course

Standard Lessons
IT-FAI-1.1
Communicate effectively through writing, speaking, listening, reading, and interpersonal abilities.
  1. 1.4 Project: Research an Ethical Dilemma in AI
  2. 3.6 Project: Informational Chatbot
  3. 4.8 Creating Your Own Predictive Model
IT-FAI-1.2
Demonstrate creativity by asking challenging questions and applying innovative procedures and methods.
  1. 1.4 Project: Research an Ethical Dilemma in AI
  2. 3.6 Project: Informational Chatbot
  3. 4.8 Creating Your Own Predictive Model
IT-FAI-1.3
Exhibit critical thinking and problem-solving skills to locate, analyze and apply information in career planning and employment situations.
IT-FAI-1.4
Model work readiness traits required for success in the workplace including integrity, honesty, accountability, punctuality, time management, and respect for diversity.
IT-FAI-1.5
Apply the appropriate skill sets to be productive in a changing, technological, diverse workplace to be able to work independently and apply teamwork skills.
IT-FAI-1.6
Present a professional image through appearance, behavior, and language.
IT-FAI-2.1
Define artificial intelligence and reflect on its current state.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
IT-FAI-2.2
Describe the history and evolution of artificial intelligence over time.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
IT-FAI-2.3
Identify important early examples of Artificial Intelligence and contributors to Artificial Intelligence development.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 2.1 Artificial Intelligence in Gaming
  4. 3.1 Using Chatbots
IT-FAI-2.4
Describe how Artificial Intelligence could be used to solve problems, including historical, current, and future problems.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 1.3 The Ethics of Artificial Intelligence
  4. 1.4 Project: Research an Ethical Dilemma in AI
  5. 3.1 Using Chatbots
  6. 3.2 Building a Rule Based Chatbot
  7. 3.3 Building a Pattern Matching Chatbot
  8. 4.1 Introduction to Predictive Models
  9. 4.7 Building Unsupervised Models
IT-FAI-3.1
Identify and describe current examples of Artificial Intelligence applications in everyday life (e.g., gaming, social media, virtual assistants, email, online shopping, travel, art, smartphones, etc.).
  1. 2.1 Artificial Intelligence in Gaming
  2. 2.2 Building Tic Tac Toe
  3. 2.3 Creating a Non Player Character
  4. 2.7 Implementing Connect Four
  5. 3.1 Using Chatbots
  6. 3.2 Building a Rule Based Chatbot
  7. 3.3 Building a Pattern Matching Chatbot
  8. 3.4 Analyzing User Sentiment
  9. 3.5 Creating an AI Chatbot
IT-FAI-3.2
Identify and describe Artificial Intelligence technologies students interact with frequently and determine what problems and/or needs the Artificial Intelligence is intended to solve.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 2.1 Artificial Intelligence in Gaming
  4. 2.2 Building Tic Tac Toe
  5. 2.3 Creating a Non Player Character
  6. 2.7 Implementing Connect Four
IT-FAI-3.3
Discuss how Artificial Intelligence is and could be used to enhance areas of student interest, real-world problems, business needs, and the future of work.
  1. 1.2 Subsets of Artificial Intelligence
  2. 2.1 Artificial Intelligence in Gaming
  3. 3.1 Using Chatbots
  4. 3.2 Building a Rule Based Chatbot
  5. 3.3 Building a Pattern Matching Chatbot
  6. 3.4 Analyzing User Sentiment
  7. 3.5 Creating an AI Chatbot
  8. 4.1 Introduction to Predictive Models
  9. 4.2 Correlation
  10. 4.3 Programming Linear Regression
  11. 4.5 Multivariable Linear Regression
  12. 4.6 Classification and Logistic Regression
  13. 4.7 Building Unsupervised Models
IT-FAI-3.4
Identify and analyze how Artificial Intelligence is impacting art and other creative fields.
  1. 1.1 What is Artificial Intelligence?
  2. 2.1 Artificial Intelligence in Gaming
  3. 2.2 Building Tic Tac Toe
  4. 2.3 Creating a Non Player Character
  5. 2.7 Implementing Connect Four
IT-FAI-3.5
Define critical and contemporary areas of Artificial Intelligence (e.g., machine learning, natural language processing, computer vision).
  1. 1.2 Subsets of Artificial Intelligence
  2. 3.1 Using Chatbots
  3. 3.2 Building a Rule Based Chatbot
  4. 3.3 Building a Pattern Matching Chatbot
  5. 3.4 Analyzing User Sentiment
  6. 3.5 Creating an AI Chatbot
  7. 3.6 Project: Informational Chatbot
  8. 4.1 Introduction to Predictive Models
  9. 4.2 Correlation
  10. 4.3 Programming Linear Regression
  11. 4.4 Training and Testing Data
  12. 4.5 Multivariable Linear Regression
  13. 4.6 Classification and Logistic Regression
  14. 4.7 Building Unsupervised Models
  15. 4.8 Creating Your Own Predictive Model
IT-FAI-3.6
Investigate how machines can be trained to recognize data and distinguish between two different classes by using a web tool that trains a machine learning model without coding (e.g., Google Teachable Machine, Weka).
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 1.3 The Ethics of Artificial Intelligence
IT-FAI-4.1
Define, explain, and apply the building blocks of algorithms: sequencing, selection, iteration.
  1. 6.1 Tuples
  2. 6.2 Lists
  3. 6.3 For Loops and Lists
  4. 6.4 List Methods
  5. 6.5 2d Lists
  6. 6.6 Dictionaries
IT-FAI-4.2
Modify and create an algorithm to solve a problem.
  1. 2.2 Building Tic Tac Toe
  2. 2.3 Creating a Non Player Character
  3. 2.4 Recursion
  4. 2.5 Minimax
  5. 2.6 Exploring Depth and Pruning
  6. 2.7 Implementing Connect Four
  7. 3.2 Building a Rule Based Chatbot
  8. 3.3 Building a Pattern Matching Chatbot
  9. 3.4 Analyzing User Sentiment
  10. 3.5 Creating an AI Chatbot
  11. 3.6 Project: Informational Chatbot
  12. 4.1 Introduction to Predictive Models
  13. 4.2 Correlation
  14. 4.3 Programming Linear Regression
  15. 4.4 Training and Testing Data
  16. 4.5 Multivariable Linear Regression
  17. 4.6 Classification and Logistic Regression
  18. 4.7 Building Unsupervised Models
  19. 4.8 Creating Your Own Predictive Model
  20. 6.1 Tuples
  21. 6.2 Lists
  22. 6.3 For Loops and Lists
  23. 6.4 List Methods
  24. 6.5 2d Lists
  25. 6.6 Dictionaries
IT-FAI-4.3
Evaluate algorithms analytically and empirically.
  1. 2.4 Recursion
  2. 2.5 Minimax
  3. 2.6 Exploring Depth and Pruning
  4. 4.4 Training and Testing Data
  5. 4.5 Multivariable Linear Regression
  6. 4.6 Classification and Logistic Regression
  7. 4.7 Building Unsupervised Models
  8. 4.8 Creating Your Own Predictive Model
IT-FAI-4.4
Use an algorithm to create a program.
  1. 2.2 Building Tic Tac Toe
  2. 2.3 Creating a Non Player Character
  3. 2.4 Recursion
  4. 2.5 Minimax
  5. 2.6 Exploring Depth and Pruning
  6. 2.7 Implementing Connect Four
  7. 3.2 Building a Rule Based Chatbot
  8. 3.3 Building a Pattern Matching Chatbot
  9. 3.4 Analyzing User Sentiment
  10. 3.5 Creating an AI Chatbot
  11. 3.6 Project: Informational Chatbot
  12. 4.1 Introduction to Predictive Models
  13. 4.2 Correlation
  14. 4.3 Programming Linear Regression
  15. 4.4 Training and Testing Data
  16. 4.5 Multivariable Linear Regression
  17. 4.6 Classification and Logistic Regression
  18. 4.7 Building Unsupervised Models
  19. 4.8 Creating Your Own Predictive Model
IT-FAI-4.5
Define, explain, and apply the ideas of decomposition, abstraction, data types (integer, string, Boolean, list/array), branches (if, then, else), iteration (for loop, while loop), event driven.
  1. 6.1 Tuples
  2. 6.2 Lists
  3. 6.3 For Loops and Lists
  4. 6.4 List Methods
  5. 6.5 2d Lists
  6. 6.6 Dictionaries
IT-FAI-4.6
Define different programming paradigms (e.g., functional, object-oriented, procedural, logic).
  1. 2.4 Recursion
  2. 2.5 Minimax
  3. 2.6 Exploring Depth and Pruning
IT-FAI-4.7
Describe the principles of object-oriented programming.
IT-FAI-4.8
Create a program that implements loops and conditionals.
  1. 2.2 Building Tic Tac Toe
  2. 2.3 Creating a Non Player Character
  3. 2.4 Recursion
  4. 2.5 Minimax
  5. 2.6 Exploring Depth and Pruning
  6. 2.7 Implementing Connect Four
  7. 3.2 Building a Rule Based Chatbot
  8. 3.3 Building a Pattern Matching Chatbot
  9. 3.4 Analyzing User Sentiment
  10. 3.5 Creating an AI Chatbot
  11. 3.6 Project: Informational Chatbot
  12. 4.1 Introduction to Predictive Models
  13. 4.2 Correlation
  14. 4.3 Programming Linear Regression
  15. 4.4 Training and Testing Data
  16. 4.5 Multivariable Linear Regression
  17. 4.6 Classification and Logistic Regression
  18. 4.7 Building Unsupervised Models
  19. 4.8 Creating Your Own Predictive Model
  20. 6.3 For Loops and Lists
  21. 6.4 List Methods
  22. 6.5 2d Lists
  23. 6.6 Dictionaries
IT-FAI-4.9
Create a program that accepts user and sensor input to make a decision.
  1. 2.2 Building Tic Tac Toe
  2. 2.3 Creating a Non Player Character
  3. 2.4 Recursion
  4. 2.5 Minimax
  5. 2.6 Exploring Depth and Pruning
  6. 2.7 Implementing Connect Four
  7. 3.1 Using Chatbots
  8. 3.2 Building a Rule Based Chatbot
  9. 3.3 Building a Pattern Matching Chatbot
  10. 3.4 Analyzing User Sentiment
  11. 3.5 Creating an AI Chatbot
  12. 3.6 Project: Informational Chatbot
IT-FAI-4.10
Create a program that collects and organizes different data types.
  1. 6.1 Tuples
  2. 6.2 Lists
  3. 6.3 For Loops and Lists
  4. 6.4 List Methods
  5. 6.5 2d Lists
  6. 6.6 Dictionaries
IT-FAI-4.11
Define and implement comments in code to document the program.
  1. 2.7 Implementing Connect Four
  2. 3.6 Project: Informational Chatbot
  3. 4.8 Creating Your Own Predictive Model
IT-FAI-4.12
Trace code and debug problems in programs.
  1. 6.1 Tuples
  2. 6.2 Lists
  3. 6.3 For Loops and Lists
  4. 6.4 List Methods
  5. 6.5 2d Lists
  6. 6.6 Dictionaries
IT-FAI-4.13
Define UX (user experience) and explain why it must be considered when programming.
  1. 2.2 Building Tic Tac Toe
  2. 3.2 Building a Rule Based Chatbot
  3. 3.3 Building a Pattern Matching Chatbot
  4. 3.5 Creating an AI Chatbot
  5. 3.6 Project: Informational Chatbot
IT-FAI-5.1
Identify the different kinds of data we collect and share as Internet users (e.g., images, videos, texts, purchasing information, site history, etc.).
  1. 4.1 Introduction to Predictive Models
  2. 4.3 Programming Linear Regression
  3. 4.4 Training and Testing Data
  4. 4.5 Multivariable Linear Regression
  5. 4.6 Classification and Logistic Regression
  6. 4.7 Building Unsupervised Models
  7. 4.8 Creating Your Own Predictive Model
IT-FAI-5.2
Define the most basic types of data that computers use (e.g., numeric, text, dates, graphics, sound).
IT-FAI-5.3
Distinguish between data and information (e.g., data requires context to be information).
IT-FAI-5.4
Describe and construct a simple model of the data processing cycle (input-processing-output).
  1. 1.1 What is Artificial Intelligence?
  2. 4.1 Introduction to Predictive Models
  3. 4.2 Correlation
  4. 4.3 Programming Linear Regression
  5. 4.4 Training and Testing Data
  6. 4.5 Multivariable Linear Regression
  7. 4.6 Classification and Logistic Regression
  8. 4.7 Building Unsupervised Models
  9. 4.8 Creating Your Own Predictive Model
IT-FAI-5.5
Summarize how computers store data using bits (binary digits).
IT-FAI-5.6
Define Big Data and describe how it is used in Artificial Intelligence.
IT-FAI-5.7
Describe how Artificial Intelligence uses data to make predictions or decisions.
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 3.1 Using Chatbots
  4. 3.2 Building a Rule Based Chatbot
  5. 3.3 Building a Pattern Matching Chatbot
  6. 3.4 Analyzing User Sentiment
  7. 3.5 Creating an AI Chatbot
  8. 4.1 Introduction to Predictive Models
  9. 4.2 Correlation
  10. 4.3 Programming Linear Regression
  11. 4.4 Training and Testing Data
  12. 4.5 Multivariable Linear Regression
  13. 4.6 Classification and Logistic Regression
  14. 4.7 Building Unsupervised Models
  15. 4.8 Creating Your Own Predictive Model
IT-FAI-5.8
Define logic and summarize its use in programming, including Artificial Intelligence.
IT-FAI-6.1
Select and organize different types of data using spreadsheet tools.
  1. 4.1 Introduction to Predictive Models
  2. 4.2 Correlation
  3. 4.3 Programming Linear Regression
  4. 4.4 Training and Testing Data
  5. 4.5 Multivariable Linear Regression
  6. 4.6 Classification and Logistic Regression
  7. 4.7 Building Unsupervised Models
  8. 4.8 Creating Your Own Predictive Model
IT-FAI-6.2
Define and implement basic preset spreadsheet function to organize and manipulate data.
  1. 4.1 Introduction to Predictive Models
  2. 4.2 Correlation
  3. 4.3 Programming Linear Regression
  4. 4.4 Training and Testing Data
  5. 4.5 Multivariable Linear Regression
  6. 4.6 Classification and Logistic Regression
  7. 4.7 Building Unsupervised Models
  8. 4.8 Creating Your Own Predictive Model
IT-FAI-6.3
Create tables and graphs to represent data visually using spreadsheets.
  1. 4.1 Introduction to Predictive Models
  2. 4.2 Correlation
  3. 4.3 Programming Linear Regression
  4. 4.4 Training and Testing Data
  5. 4.5 Multivariable Linear Regression
  6. 4.6 Classification and Logistic Regression
  7. 4.7 Building Unsupervised Models
  8. 4.8 Creating Your Own Predictive Model
IT-FAI-6.4
Analyze data to construct informed summaries, decisions, or predictions related to the data.
  1. 3.4 Analyzing User Sentiment
  2. 3.5 Creating an AI Chatbot
  3. 3.6 Project: Informational Chatbot
  4. 4.1 Introduction to Predictive Models
  5. 4.2 Correlation
  6. 4.3 Programming Linear Regression
  7. 4.4 Training and Testing Data
  8. 4.5 Multivariable Linear Regression
  9. 4.6 Classification and Logistic Regression
  10. 4.7 Building Unsupervised Models
  11. 4.8 Creating Your Own Predictive Model
IT-FAI-7.1
Define bias, perception, privacy, and accuracy in the context of Artificial Intelligence.
  1. 1.3 The Ethics of Artificial Intelligence
  2. 1.4 Project: Research an Ethical Dilemma in AI
  3. 3.4 Analyzing User Sentiment
  4. 4.2 Correlation
  5. 4.6 Classification and Logistic Regression
IT-FAI-7.2
Explore potential examples of bias using a web tool that trains a machine learning model without coding (e.g., Google Teachable Machine, Weka).
  1. 1.1 What is Artificial Intelligence?
  2. 1.2 Subsets of Artificial Intelligence
  3. 1.3 The Ethics of Artificial Intelligence
IT-FAI-7.3
Describe and critique how ethics and philosophy explicitly and implicitly play a role in Artificial Intelligence applications.
  1. 1.3 The Ethics of Artificial Intelligence
  2. 1.4 Project: Research an Ethical Dilemma in AI
IT-FAI-7.4
Define and compare ethical and legal implications of Artificial Intelligence.
  1. 1.3 The Ethics of Artificial Intelligence
  2. 1.4 Project: Research an Ethical Dilemma in AI
IT-FAI-7.5
Identify and describe ethical and societal Artificial Intelligence issues in a variety of settings (e.g., public safety, financial implications, social media marketing, government uses, different cultures and countries).
  1. 1.3 The Ethics of Artificial Intelligence
  2. 1.4 Project: Research an Ethical Dilemma in AI
IT-FAI-7.6
Research the purpose of Artificial Intelligence for Good Foundation and other similar organizations (e.g., The Center for Human Compatible Artificial Intelligence, The Future of Life Institute) and describe their role in Artificial Intelligence development.
  1. 1.4 Project: Research an Ethical Dilemma in AI
IT-FAI-8.1
Define, describe, and demonstrate productive collaboration, problem-solving, and leadership skills.
  1. 2.7 Implementing Connect Four
  2. 3.6 Project: Informational Chatbot
  3. 4.8 Creating Your Own Predictive Model
IT-FAI-8.2
Analyze the value of diversity in backgrounds and perspectives in collaboration and problem-solving.
  1. 1.3 The Ethics of Artificial Intelligence
IT-FAI-8.3
Apply computational thinking skills to find alternative or creative solutions to problems.
  1. 2.7 Implementing Connect Four
  2. 3.6 Project: Informational Chatbot
  3. 4.8 Creating Your Own Predictive Model
IT-FAI-8.4
Define the purpose of the Design Thinking Process and describe its steps (e.g., empathize, define, ideate, prototype, test).
IT-FAI-8.5
Apply the Design Thinking Process to collaboratively solve real-world problems.
  1. 3.6 Project: Informational Chatbot
  2. 4.8 Creating Your Own Predictive Model
IT-FAI-9.1
Explain the goals, mission, and objectives of the career-technical student organization (CTSO).
IT-FAI-9.2
Explore the impact and opportunities a student organization can develop to bring business and education together in a positive working relationship through innovative leadership and career development programs.
IT-FAI-9.3
Explore the local, state, and national opportunities available to students through participation in related student organization including but not limited to conferences, competitions, community service, philanthropy, and other CTSO activities.
IT-FAI-9.4
Explain how participation in career and technology education student organizations can promote lifelong responsibility for community service and professional development.
IT-FAI-9.5
Explore the competitive events related to the content of this course and the required competencies, skills, and knowledge for each related event for individual, team, and chapter competitions.