High School Level 1 (Grades 9-10)
| OAS Standard | Description | Resource |
|---|---|---|
| L1.ET.AI.01 | Analyze and compare different artificial intelligence (AI) architectures and their applications. Practice: Developing and Using Abstractions | • AI Architectures & Applications Unit • Machine Learning Training Unit • NLP & Text Analysis Unit • Computer Vision & Image Processing Unit • AI Ethics & Responsible Development Unit • AI Real-World Applications Unit • Data Science & AI Decision Making Unit • Deep Learning & Advanced Techniques Unit • AI Development Tools & Frameworks Unit • Complete 9-Unit Bundle |
| L1.ET.AI.02 | Explore, select, and use appropriate AI tools and frameworks to design and implement AI solutions. Practice: Creating Computational Artifacts | • AI Tools & Frameworks Unit (Version 1) • AI Tools & Frameworks Unit (Version 2) |
| L1.ET.AI.03 | Evaluate the societal implications of AI technologies, including privacy and security concerns. Practice: Communicating About Computing | AI Privacy & Security Unit |
| L1.ET.AI.04 | Demonstrate how AI systems can be trained and optimized using different learning techniques. Practice: Testing and Refining Computational Artifacts | OAS L1.ET.AI.04-Aligned Unit |
| L1.ET.AI.05 | Create and evaluate model cards or documentation that explain AI system capabilities, limitations, and intended uses. Practice: Communicating About Computing | AI Model Cards & Documentation Unit |
| L1.ET.AI.06 | Analyze how AI systems represent and reason with different data modalities (text, images, audio, video). Practice: Developing and Using Abstractions | AI Data Modalities Unit |
High School Level 2 (Grades 11-12)
| OAS Standard | Description | Resource |
|---|---|---|
| L2.ET.AI.01 | Design and develop complex artificial intelligence (AI) systems that incorporate multiple types of learning approaches. Practice: Creating Computational Artifacts | • AI System Architecture Unit • Supervised Learning Unit • Unsupervised Learning Unit • Reinforcement Learning Unit • Transfer Learning & Model Adaptation Unit • AI System Design Principles Unit • AI System Design Bundle |
| L2.ET.AI.02 | Design AI solutions that embed fairness, transparency, privacy, sustainability, and bias mitigation from problem scoping through deployment. Practice: Creating Computational Artifacts | Ethical AI Design Unit |
| L2.ET.AI.03 | Create AI solutions that interact with and adapt to human feedback. Practice: Creating Computational Artifacts | Adaptive AI Systems Unit |
| L2.ET.AI.04 | Evaluate and optimize AI systems for efficiency, accuracy, and adherence to ethical principles. Practice: Testing and Refining Computational Artifacts | Evaluating and Optimizing AI Systems Unit |
| L2.ET.AI.05 | Evaluate and document AI solutions, explaining ethical safeguards, environmental impacts, limitations, and intended uses to different stakeholders. Practice: Communicating About Computing | AI Solutions Evaluation & Documentation Unit |
| L2.ET.AI.06 | Develop methods to explain AI decision-making processes and their ethical implications (e.g., fairness, transparency, and intellectual property) to different stakeholders. Practice: Communicating About Computing | Algorithmic Bias Detection Unit |
Related Computer Science Standards
| OAS Standard | Description | Resource |
|---|---|---|
| L1.CS.D.01 | Computing Abstractions: Understanding how computing systems use abstraction to manage complexity and enable problem-solving across different levels of a system. | Computing Abstractions Unit |
| L1.CS.HS.01 | Software Abstraction Layers: Analyzing how software systems organize functionality into distinct layers to manage complexity and enable modular design. | Software Abstraction Layers Unit |
Implementation Notes
These competencies complement the 2023 Oklahoma Academic Standards for Computer Science (OAS-CS) by providing grade-specific learning targets for AI literacy. The framework progresses from foundational concepts in elementary grades through advanced AI system design and ethical considerations in high school.
Key Computational Thinking Practices:
- Developing and Using Abstractions
- Creating Computational Artifacts
- Testing and Refining Computational Artifacts
- Communicating About Computing
Resources are available as individual units or bundled curricula to support district implementation across K-12 computer science courses.
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