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Standards Mapping

for Georgia Artificial Intelligence Concepts

55

Standards in this Framework

16

Standards Mapped

29%

Mapped to Course

Standard Lessons
IT-AIC-1.1
Communicate effectively through writing, speaking, listening, reading, and interpersonal abilities.
  1. 4.4 Project: AI on Trial
IT-AIC-1.2
Demonstrate creativity by asking challenging questions and applying innovative procedures and methods.
IT-AIC-1.3
Exhibit critical thinking and problem-solving skills to locate, analyze and apply information in career planning and employment situations.
IT-AIC-1.4
Model work readiness traits required for success in the workplace including integrity, honesty, accountability, punctuality, time management, and respect for diversity.
IT-AIC-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-AIC-1.6
Present a professional image through appearance, behavior, and language.
IT-AIC-2.1
Identify and summarize how Artificial Intelligence has influenced elements of history and is currently shaping contemporary events.
  1. 1.1 Human & Artificial Intelligence
  2. 7.1 Introduction to Artificial Intelligence
  3. 7.2 Artificial Intelligence and Machine Learning
IT-AIA-2.2
Identify, research, and analyze current events in the field of Artificial Intelligence, considering new technology developments, social and ethical impact, and future implication.
  1. 1.1 Human & Artificial Intelligence
  2. 3.3 Bias in Training
  3. 4.1 Effects of Using Biased AI
  4. 4.4 Project: AI on Trial
  5. 7.1 Introduction to Artificial Intelligence
  6. 7.2 Artificial Intelligence and Machine Learning
IT-AIA-2.3
Analyze the impact new Artificial Intelligence developments have or will have on its intended users and society at large
  1. 3.3 Bias in Training
  2. 4.1 Effects of Using Biased AI
  3. 4.4 Project: AI on Trial
IT-AIA-2.4
Identify current and predicted trends or changes in the Artificial Intelligence industry.
  1. 1.1 Human & Artificial Intelligence
  2. 1.3 Large Language Models
  3. 2.1 Intro to Machine Learning
IT-AIC-3.1
Define the function of and classify examples of critical and contemporary areas of Artificial Intelligence (e.g., machine learning, natural language processing, computer vision).
  1. 2.1 Intro to Machine Learning
  2. 2.2 Supervised Learning
  3. 2.3 Unsupervised Learning
  4. 2.4 Reinforcement Learning
IT-AIC-3.2
Define and classify examples of supervised learning, including regression and classification; unsupervised learning, including clustering; and reinforcement learning.
  1. 2.2 Supervised Learning
  2. 2.3 Unsupervised Learning
  3. 2.4 Reinforcement Learning
IT-AIC-3.3
Using a web tool that trains a machine learning model without coding (e.g., Google Teachable Machine, Weka), plan and conduct an experiment to train a model to recognize data (e.g., photos, videos, audio, etc.) and to distinguish between at least three different categories you define (e.g., bicycles, motorcycles, scooters; jazz, hip-hop, classical music).
  1. 3.1 How Are AI Models Trained?
  2. 3.2 AI Models in Industry
IT-AIC-3.4
Predict what information the trained machine from your experiment might use to classify data
  1. 3.1 How Are AI Models Trained?
IT-AIC-3.5
Construct an argument using data that explains how your machine learning experiment model works and evaluate if it was successful.
IT-AIC-3.6
Investigate how the different examples Artificial Intelligence you interact with daily (e.g., social media, gaming, smartphones, shopping, etc.) work and determine what type(s) of Artificial Intelligence is being used (e.g., machine learning, natural language processing, computer vision).
  1. 1.1 Human & Artificial Intelligence
  2. 2.2 Supervised Learning
  3. 2.3 Unsupervised Learning
  4. 2.4 Reinforcement Learning
  5. 7.2 Artificial Intelligence and Machine Learning
IT-AIC-4.1
Define, explain, and apply the ideas of pattern matching, recursion, parallelization, and automation to algorithms and programs.
IT-AIC-4.2
Describe the benefits and principles of object-oriented programming
IT-AIC-4.3
Define and apply objects and recognize the difference between an object and an instance
IT-AIC-4.4
Apply principles of object-oriented programing to declare methods and combine classes.
IT-AIC-4.5
Define and implement different logical, relational, Boolean, and mathematical operators.
IT-AIC-4.6
Identify, assign, and convert values and different data types to variables in programs
IT-AIC-4.7
Implement different types of control structures in programs (e.g., conditionals, loops, functions).
IT-AIC-4.8
Describe and implement a function, including those with return statements and different parameters.
IT-AIC-4.9
Use external libraries in programs.
IT-AIC-4.10
Identify a list as an ordered series of data under one variable name and accessed with numeric indices.
IT-AIC-4.11
Determine which data structures are most appropriate to model the program data (e.g., list, set, dictionary, and tuple).
IT-AIC-4.12
Implement data structures (e.g., lists, sets, dictionaries, and tuples) as function parameters, return values, and internal variables within function bodies
IT-AIC-4.13
Differentiate between methods and functions and analyze the effect of a method call on a program.
IT-AIC-4.14
Construct and implement strings in programs.
IT-AIC-4.15
Define and implement professional programming practices (e.g., commenting and documentation, file storage, naming conventions).
IT-AIC-4.16
Implement a debugging process.
IT-AIC-5.1
Identify examples of data science in the world around us and investigate its impact on technology and users.
IT-AIC-5.2
Identify examples of ethical issues in data science.
IT-AIC-5.3
Describe how data is used in different Artificial Intelligence applications.
  1. 1.3 Large Language Models
  2. 1.5 Who Builds AI?
  3. 2.1 Intro to Machine Learning
IT-AIC-5.4
Define, compare, and contrast a spreadsheet and a database.
IT-AIC-5.5
Define and describe the function of a Database Management System Language (DMBS) (e.g., SQL).
IT-AIC-5.6
Define dataset and Data Frame.
IT-AIC-5.7
Implement spreadsheet functions, formulas, conditional formatting, cell referencing, and pivot tables.
IT-AIC-5.8
Create data tables and graphic representations of data including two-way tables, scatterplots, bar graphs, histograms, stem plots, and dot plots from a spreadsheet software or other data visualization tools (e.g., Jupyter Notebooks, Matplotlib).
IT-AIC-5.9
Utilize visual reporting and statistical tools to define and understand statistics such as regression analysis, ANOVA, hypothesis testing, and sampling distributions.
IT-AIC-6.1
Identify real examples of issues related to bias, perception, privacy, and accuracy in Artificial Intelligence.
  1. 3.3 Bias in Training
  2. 4.2 Hallucinations and Security Risks
IT-AIC-6.2
Investigate and propose solutions to ethical and societal Artificial Intelligence issues in a variety of settings (e.g., public safety, finance, social media marketing, government use).
  1. 4.3 Deepfakes and Misinformation
  2. 4.4 Project: AI on Trial
IT-AIC-6.3
Using a web tool that trains a machine learning model without coding, investigate examples of bias and identify solutions.
  1. 3.3 Bias in Training
IT-AIC-6.4
Identify and analyze examples of legal policies related to Artificial Intelligence, including why and how they were or are being developed
  1. 4.4 Project: AI on Trial
IT-AIC-6.5
Analyze real world Artificial Intelligence scenarios to determine the ethical and legal implications.
  1. 4.4 Project: AI on Trial
IT-AIC-6.6
Identify and research projects from the Artificial Intelligence for Good Foundation or other similar organizations (e.g., The Center for Human Compatible Artificial Intelligence, The Future of Life Institute) and design potential solutions to the problems identified.
IT-AIC-7.1
Identify and investigate a real-world problem of interest that might be solved with Artificial Intelligence.
IT-AIC-7.2
Use a problem-solving process (e.g., Design Thinking) to design a creative solution to a realworld problem that could be solved with Artificial Intelligence.
IT-AIC-7.3
Apply programming, logic, and data science to solve problems.
IT-AIC-8.1
Explain the goals, mission, and objectives of the career-technical student organization (CTSO).
IT-AIC-8.2
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-AIC-8.3
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-AIC-8.4
Explain how participation in career and technology education student organizations can promote lifelong responsibility for community service and professional development.
IT-AIC-8.5
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