K-12 AI Literacy Curriculum Framework
This document provides the comprehensive curriculum framework for AI literacy education across all grade levels in El Segundo USD. The framework establishes learning progressions, competency standards, assessment approaches, and integration strategies appropriate for each developmental stage.
Curriculum Design Principles
Foundation Principles
| Principle | Description | Implementation |
|---|
| Developmentally Appropriate | Content matches cognitive and social development stages | Age-specific tools, examples, and complexity levels |
| Spiral Curriculum | Core concepts revisited with increasing depth | Ethics, bias, and safety threads throughout K-12 |
| Hands-On Learning | Direct experience with AI tools prioritized | Minimum 60% hands-on time in all AI instruction |
| Real-World Relevance | Connections to student interests and career pathways | Local industry examples; Age-appropriate applications |
| Equity-Centered | Designed to close rather than widen gaps | Access provisions; Gender-inclusive examples; Cultural responsiveness |
Alignment Standards
| Standard Framework | Alignment Approach |
|---|
| ISTE Standards for Students | Direct mapping of AI competencies to digital citizenship and computational thinking standards |
| California Computer Science Standards | Integration with existing CS pathway requirements |
| Next Generation Science Standards | Connection to engineering design and systems thinking |
| Common Core ELA/Math | Integration of AI literacy into disciplinary instruction |
| Career Technical Education Standards | Alignment with workforce readiness competencies |
K-5: AI Literacy Foundations
Kindergarten through Grade 2: AI Awareness
Overarching Goal: Students understand that AI exists, recognize AI in their environment, and begin distinguishing human and machine capabilities.
Learning Objectives
| Domain | Objective | Success Indicator |
|---|
| AI Recognition | Identify examples of AI in daily life | Name 5+ AI examples (voice assistants, recommendations, image filters) |
| Human vs Machine | Distinguish tasks suited for humans vs machines | Correctly categorize 8/10 task examples |
| Input/Output Concept | Understand that computers follow instructions | Explain that machines need instructions to work |
| Responsible Use | Demonstrate appropriate interaction with AI tools | Follow classroom AI use guidelines |
Content Outline
Unit 1: What is a Robot? What is AI? (4 weeks)
- Differentiating physical robots from AI software
- Examples of AI helpers (Siri, Alexa, recommendation systems)
- Classroom demonstrations with age-appropriate AI tools
- Assessment: Draw and label an AI system they use
Unit 2: How Do Computers Learn? (4 weeks)
- Simplified introduction to training and patterns
- Sorting and categorizing activities (unplugged)
- "Teaching" a simple classifier through examples
- Assessment: Participate in human-as-computer role-play activity
Unit 3: Humans and Machines Working Together (4 weeks)
- Tasks machines do well vs tasks humans do well
- Introduction to AI limitations and errors
- Responsible use of AI assistance
- Assessment: Create a T-chart of human vs machine strengths
Suggested Activities
| Activity | Duration | Materials | Learning Target |
|---|
| AI Scavenger Hunt | 45 min | Picture cards | AI recognition |
| Train the Teacher | 30 min | Sorting objects | Machine learning concept |
| Robot Dance Commands | 30 min | Movement cards | Input/output understanding |
| AI Helpers Story Time | 20 min | Picture books | AI in daily life |
| Human vs Machine Race | 45 min | Task cards | Comparative strengths |
Assessment Approach
- Observation checklists during activities
- Portfolio entries (drawings, dictated explanations)
- Participation in class discussions
- Simple sorting and matching assessments
Grades 3-5: AI Literacy Basics
Overarching Goal: Students develop foundational understanding of how AI works, begin using creative AI tools, and recognize bias and fairness concerns.
Learning Objectives
| Domain | Objective | Success Indicator |
|---|
| AI Mechanics | Explain how AI learns from data and examples | Describe training process in own words |
| Tool Proficiency | Use age-appropriate AI tools for creative projects | Complete 3+ AI-assisted creative projects |
| Bias Awareness | Recognize that AI can reflect human biases | Identify potential bias in 3+ AI scenarios |
| Data Understanding | Understand that AI needs data to function | Explain role of data in AI systems |
| Computational Thinking | Apply decomposition and pattern recognition | Solve problems using CT strategies |
Content Outline
Unit 1: Inside the Machine - How AI Learns (6 weeks)
| Week | Topic | Activities | Assessment |
|---|
| 1-2 | Data and Patterns | Pattern recognition games; Data collection project | Pattern identification quiz |
| 3-4 | Training AI | Teachable Machine exploration; Image classification | Train a simple classifier |
| 5-6 | AI Predictions | Prediction activities; Understanding confidence levels | Prediction accuracy journal |
Unit 2: Creating with AI (6 weeks)
| Week | Topic | Activities | Assessment |
|---|
| 1-2 | AI Art Tools | Exploration of age-appropriate image generators | AI art project with reflection |
| 3-4 | AI Writing Helpers | Story starters with AI assistance; Editing AI output | Collaborative story project |
| 5-6 | AI Music and Sound | Sound generation exploration; Music composition aids | Creative audio project |
Unit 3: Fairness and AI (4 weeks)
| Week | Topic | Activities | Assessment |
|---|
| 1 | What is Bias? | Bias introduction through everyday examples | Bias identification exercise |
| 2 | Bias in AI | Examining facial recognition and recommendation biases | Case study analysis |
| 3 | Fair AI Design | Discussing who makes AI and why representation matters | Design a fair AI activity |
| 4 | Being a Critical User | Questioning AI outputs; Verification strategies | Critical evaluation checklist |
Unit 4: Computational Thinking with AI (4 weeks)
| Week | Topic | Activities | Assessment |
|---|
| 1 | Decomposition | Breaking down problems for AI assistance | Problem breakdown challenge |
| 2 | Pattern Recognition | Finding patterns AI can learn | Pattern documentation project |
| 3 | Abstraction | Simplifying for AI understanding | Abstraction practice |
| 4 | Algorithms | Step-by-step AI instructions | Algorithm design activity |
Portfolio Requirements (Grades 3-5)
| Element | Quantity | Description |
|---|
| AI-Assisted Creative Projects | 3 per year | Art, writing, or music projects using AI tools |
| Reflection Entries | 1 per project | What the AI did; What I did; What I learned |
| Bias Analysis | 1 per year | Written or visual analysis of AI bias example |
| Computational Thinking Documentation | 2 per year | Evidence of CT strategies in problem-solving |
Assessment Rubric: AI-Assisted Creative Project (Grades 3-5)
| Criterion | Beginning (1) | Developing (2) | Proficient (3) | Advanced (4) |
|---|
| AI Tool Use | Minimal or incorrect tool use | Basic tool use with support | Independent and appropriate tool use | Creative and sophisticated tool application |
| Human Contribution | AI did all work | Some human input visible | Clear human direction and editing | Significant human creativity enhanced by AI |
| Reflection Quality | No reflection | Surface-level reflection | Thoughtful analysis of AI role | Deep insight into human-AI collaboration |
| Originality | Copied AI output | Minor modifications | Personal expression evident | Highly original human-AI creation |
Middle School AI Curriculum
Overarching Goal: Students develop proficiency with AI tools across disciplines, engage deeply with ethical considerations, and understand AI's societal impact.
Learning Objectives
| Domain | Objective | Success Indicator |
|---|
| Tool Proficiency | Effectively use AI tools for academic work across subjects | Complete discipline-specific AI projects in 4+ subjects |
| Ethical Reasoning | Analyze ethical implications of AI systems | Write persuasive argument on AI ethics issue |
| Bias Deep Dive | Investigate sources of AI bias and propose mitigations | Complete bias investigation project |
| Career Awareness | Understand AI's role in various career fields | Research and present on AI in a career area |
| Digital Citizenship | Practice responsible AI use and help others do the same | Demonstrate and teach responsible use practices |
Semester 1: AI for Learning
| Unit | Duration | Content | Projects |
|---|
| AI Research Assistant | 4 weeks | Using AI for research; Verification; Citation | Research project with AI assistance documented |
| AI Writing Partner | 4 weeks | Brainstorming; Drafting; Revision with AI | Essay with AI collaboration transparency |
| AI in Math and Science | 4 weeks | Problem-solving assistance; Data analysis | STEM project with AI component |
| AI for Creativity | 4 weeks | Visual arts; Music; Creative writing with AI | Creative portfolio piece |
Semester 2: AI and Society
| Unit | Duration | Content | Projects |
|---|
| AI in Our Community | 4 weeks | Local AI applications; Community impact | Community AI mapping project |
| Privacy and AI | 4 weeks | Data collection; Personal information; Privacy rights | Privacy audit of AI services used |
| AI and Fairness | 4 weeks | Algorithmic fairness; Discrimination; Access equity | Fairness case study presentation |
| Future of AI | 4 weeks | AI trends; Career implications; Preparing for change | Future scenarios creative project |
Grade 7: AI Ethics Deep Dive
Semester 1: Ethical Frameworks
| Unit | Duration | Content | Projects |
|---|
| Ethics Introduction | 3 weeks | Ethical frameworks; Decision-making models | Ethics framework application exercise |
| AI Decision-Making | 4 weeks | How AI makes decisions; Transparency; Explainability | "Explain This AI" investigation |
| Bias Investigation | 5 weeks | Sources of bias; Measurement; Mitigation strategies | Original bias investigation research |
| Accountability | 4 weeks | Who is responsible when AI fails?; Legal and social frameworks | Mock trial or debate on AI accountability |
Semester 2: AI and Identity
| Unit | Duration | Content | Projects |
|---|
| AI and Self-Image | 4 weeks | Filters; Deepfakes; AI beauty standards | Media literacy project |
| AI and Relationships | 4 weeks | AI companions; Social media algorithms; Human connection | Reflective essay and discussion |
| AI and Culture | 4 weeks | AI representation; Cultural bias; Global perspectives | Cultural AI analysis |
| My AI Principles | 4 weeks | Personal values; Technology boundaries; Future self | Personal AI ethics statement |
Grade 8: AI and Career Readiness
Semester 1: AI in Professional Fields
| Unit | Duration | Content | Projects |
|---|
| AI in Healthcare | 3 weeks | Diagnosis; Treatment; Medical research | Healthcare AI case study |
| AI in Business | 3 weeks | Automation; Customer service; Marketing | Business AI application analysis |
| AI in Creative Fields | 3 weeks | Art; Music; Writing; Design | Creative industry interview project |
| AI in Science and Engineering | 3 weeks | Research; Design; Discovery | STEM career exploration |
| AI in Public Service | 4 weeks | Government; Education; Non-profits | Public sector AI proposal |
Semester 2: Building AI-Ready Skills
| Unit | Duration | Content | Projects |
|---|
| Skills That Matter | 4 weeks | Human skills in AI age; Critical thinking; Creativity; Collaboration | Skills self-assessment and development plan |
| Working with AI | 4 weeks | Prompt engineering; AI management; Quality control | AI workflow project |
| Presenting with AI | 4 weeks | AI-enhanced presentations; Data visualization; Storytelling | Capstone presentation |
| Transition to High School | 4 weeks | Portfolio preparation; Studio team introduction; Goal setting | Portfolio showcase; High school planning |
Middle School Portfolio Requirements
| Element | Grade 6 | Grade 7 | Grade 8 |
|---|
| Discipline-Specific AI Projects | 4 | 4 | 5 |
| Ethics Analysis Papers | 1 | 2 | 2 |
| Bias Investigation | - | 1 (major) | 1 (extension) |
| Career Exploration | 1 | 1 | 2 |
| Reflection Essays | 4 | 4 | 4 |
| Peer Teaching/Collaboration | 1 | 2 | 2 |
Assessment Rubric: AI Ethics Analysis (Middle School)
| Criterion | Beginning (1) | Developing (2) | Proficient (3) | Advanced (4) |
|---|
| Issue Identification | Vague or incorrect issue statement | Basic issue identification | Clear, specific issue articulation | Nuanced understanding of complexity |
| Stakeholder Analysis | Missing or incomplete | Some stakeholders identified | Multiple perspectives considered | Comprehensive stakeholder mapping |
| Ethical Reasoning | No framework applied | Attempts to apply ethical thinking | Clear application of ethical framework | Sophisticated multi-framework analysis |
| Evidence Use | No evidence | Some evidence, poorly integrated | Relevant evidence supports claims | Strong evidence effectively synthesized |
| Proposed Action | No recommendation | Vague recommendation | Practical, justified recommendation | Innovative, well-reasoned proposal |
9-12: AI-Augmented Disciplinary Work
High School AI Integration
Overarching Goal: Students integrate AI tools into advanced disciplinary work, build comprehensive portfolios demonstrating AI-augmented capability, and prepare for AI-transformed careers.
Learning Objectives
| Domain | Objective | Success Indicator |
|---|
| Disciplinary Integration | Apply AI tools to enhance work in chosen fields | Portfolio demonstrates AI integration across subjects |
| Advanced Tool Proficiency | Master advanced AI tools relevant to career interests | Complete complex projects using professional-grade tools |
| Portfolio Development | Build employer-ready portfolio demonstrating capability | Portfolio passes employer review (7/10 minimum) |
| AI Management | Direct AI tools effectively; Evaluate and improve AI outputs | Document AI workflow optimization |
| Professional Readiness | Demonstrate skills valued by employers | Positive employer feedback; Internship/project success |
Course Integration Model
Required Integration (All Subjects):
| Subject Area | AI Integration Requirements | Example Applications |
|---|
| English/Language Arts | AI-assisted research, drafting, revision; AI writing analysis | Research papers with AI collaboration; AI literature analysis |
| Mathematics | AI problem-solving assistance; Data analysis with AI | Statistical analysis projects; AI-assisted modeling |
| Science | AI in research design; Data processing; Literature review | Research projects; Lab data analysis; Review synthesis |
| Social Studies | AI research tools; Bias analysis in historical AI | Historical AI impact analysis; Policy research |
| World Languages | AI translation analysis; Language learning with AI | Translation comparison projects; AI conversation practice |
| Arts | AI creative tools; Critical analysis of AI art | AI-assisted compositions; AI art critique |
| CTE Pathways | Industry-specific AI tools; Workflow integration | Pathway-specific professional projects |
AI-Specific Courses (Elective):
| Course | Grade Level | Content |
|---|
| Introduction to AI | 9-10 | Foundations; Ethics; Hands-on exploration |
| AI Applications | 10-11 | Advanced tools; Project-based learning |
| AI and Society | 11-12 | Policy; Ethics; Societal impact analysis |
| AI Studio | 9-12 | Project-based; Team collaboration; Portfolio building |
AI Studio Teams Curriculum
Team Structure Recap:
- 8-12 students per team (grades 9-12)
- Cross-grade mentorship (12th mentors 10th; 11th mentors 9th)
- Weekly 90-minute sessions
- Teacher mentor assigned
Semester 1: Foundation Projects
| Week | Focus | Activities | Deliverables |
|---|
| 1-2 | Team Formation | Introductions; Role assignment; Goal setting | Team charter |
| 3-4 | Tool Exploration | Survey of AI tools; Individual experimentation | Tool proficiency log |
| 5-8 | Mini-Project 1 | Defined scope project; Full cycle completion | Completed mini-project |
| 9-12 | Mini-Project 2 | Student-proposed project; Peer feedback | Completed mini-project |
| 13-16 | Portfolio Development | Documentation; Reflection; Presentation prep | Updated portfolio |
| 17-18 | Showcase | Classroom and school exhibition | Public presentation |
Semester 2: Advanced Projects
| Week | Focus | Activities | Deliverables |
|---|
| 1-2 | Project Planning | Client/problem identification; Scope definition | Project proposal |
| 3-10 | Major Project | Extended development cycle; Regular check-ins | Project milestones |
| 11-14 | Refinement | Testing; Iteration; Polish | Refined deliverable |
| 15-16 | Documentation | Portfolio integration; Process documentation | Complete portfolio entry |
| 17-18 | Exhibition | Community showcase; Employer pitch day | Public presentation; Employer feedback |
Project Categories:
| Category | Description | Example Projects |
|---|
| Community Service | AI solutions for local organizations | Non-profit efficiency tools; Community resource apps |
| Business Solutions | Real client projects with local businesses | Marketing analysis; Customer service optimization |
| Creative Production | AI-enhanced creative works | Documentary; Art installation; Music composition |
| Research | Original investigation with AI methodology | Local issue analysis; Data journalism |
| Educational | Teaching others about AI | Curriculum for younger students; Community workshops |
Portfolio Assessment Rubrics
Comprehensive Portfolio Rubric (High School)
| Dimension | Emerging (1) | Developing (2) | Proficient (3) | Exemplary (4) | Weight |
|---|
| AI Tool Mastery | Basic tool use only | Competent with standard tools | Advanced tool application | Innovative, sophisticated tool use | 20% |
| Human-AI Collaboration | AI does most work | Balanced but unclear roles | Clear human direction with AI support | Synergistic human-AI partnership | 20% |
| Project Quality | Incomplete or low quality | Functional but basic | Polished, professional quality | Exceptional, portfolio-worthy | 20% |
| Reflection Depth | Surface-level or missing | Some insight into process | Thoughtful analysis of learning | Deep metacognitive understanding | 15% |
| Ethical Awareness | No ethical consideration | Mentions ethics superficially | Applies ethical reasoning | Integrates ethics throughout | 15% |
| Presentation | Unclear or unprofessional | Basic clarity | Clear, professional communication | Compelling, memorable presentation | 10% |
Employer Review Criteria:
| Criterion | Question | Scale |
|---|
| Skill Demonstration | Does this portfolio demonstrate relevant skills for entry-level positions? | 1-10 |
| Problem-Solving | Does the work show effective problem-solving approach? | 1-10 |
| AI Integration | Is AI used appropriately and effectively? | 1-10 |
| Communication | Are projects and reflections clearly communicated? | 1-10 |
| Professionalism | Does the portfolio meet professional standards? | 1-10 |
| Hiring Potential | Would you consider this student for an internship or entry position? | Yes/No/Maybe |
Target Score: Average 7/10 across criteria; 70%+ "Yes" or "Maybe" on hiring potential
Ethics and Safety Curriculum Thread
K-12 Ethics Progression
Ethics education is woven throughout all grade levels with increasing sophistication.
| Grade Band | Ethics Focus | Key Concepts | Assessment |
|---|
| K-2 | Kindness and AI | Being kind to AI (and recognizing AI isn't human); Asking for help appropriately | Discussion participation |
| 3-5 | Fairness and AI | Bias introduction; Fair treatment; Representation | Bias identification exercises |
| 6-8 | AI Ethics Deep Dive | Ethical frameworks; Accountability; Privacy; Societal impact | Ethics analysis papers |
| 9-12 | Professional AI Ethics | Industry ethics; Policy; Personal responsibility; Future implications | Ethics statements; Case analyses |
Safety Curriculum Components
Digital Safety with AI:
| Topic | K-2 | 3-5 | 6-8 | 9-12 |
|---|
| Personal Information | Don't tell AI your name/address | Understand data collection | Privacy policies; Data rights | Data security; Professional privacy |
| Verification | Ask an adult if unsure | Check AI answers | Multiple source verification | Research methodology |
| Appropriate Content | Tell adult if uncomfortable | Report inappropriate content | Content moderation understanding | Platform responsibility |
| AI Limitations | AI makes mistakes | AI can be wrong or biased | Critical evaluation skills | Professional verification standards |
Academic Integrity Framework:
| Level | Guidelines |
|---|
| Elementary | AI is a helper, not a replacer; Always tell your teacher when AI helped |
| Middle School | Document AI assistance; Original thinking required; Verification responsibility |
| High School | Professional attribution standards; AI collaboration transparency; Originality requirements |
AI Safety Checklist (Student Reference):
Implementation Support
Teacher Resources by Grade Band
| Grade Band | Lesson Plans | Tool Guides | Assessment Templates | Parent Communications |
|---|
| K-2 | 30+ activities | 5 approved tools | Observation checklists | Monthly newsletters |
| 3-5 | 40+ activities | 10 approved tools | Rubrics; Portfolio templates | Quarterly updates |
| 6-8 | 60+ activities | 15 approved tools | Full rubric set; Self-assessments | Unit introductions |
| 9-12 | 80+ activities | 20+ approved tools | Professional rubrics; Employer forms | Pathway guides |
| Tool Category | K-2 | 3-5 | 6-8 | 9-12 |
|---|
| Image Generation | DrawingBot Junior | DALL-E (curated) | DALL-E; Midjourney (supervised) | Full access (professional tools) |
| Text Generation | Story starters only | ChatGPT (filtered) | ChatGPT; Claude (monitored) | Full access (professional tools) |
| Code Generation | Block-based only | Scratch AI | GitHub Copilot (supervised) | Full access |
| Research | Kid-safe search only | AI search (filtered) | Perplexity; ChatGPT (monitored) | Full access |
| Creative | Music makers; Art apps | Expanded creative suite | Professional creative tools | Industry-standard tools |
Differentiation Strategies
| Student Need | Modification Approach |
|---|
| English Learners | AI translation support; Multilingual tool options; Extended processing time |
| Students with Disabilities | Accessibility features; Alternative input methods; Individualized tool selection |
| Advanced Learners | Extended projects; Mentorship roles; Advanced tool access |
| Struggling Learners | Scaffolded tool use; Additional practice; Peer support pairing |
| Economically Disadvantaged | Device lending; Extended access hours; Community partnerships |
Curriculum Governance
Review and Update Cycle
| Review Type | Frequency | Participants | Focus |
|---|
| Tool Evaluation | Quarterly | Tech team; Teachers; Students | New tools; Safety; Effectiveness |
| Content Review | Annually | Curriculum team; Subject experts | Accuracy; Relevance; Alignment |
| Ethics Update | Bi-annually | Ethics committee; Community | Emerging issues; Policy alignment |
| Full Curriculum Review | Every 3 years | All stakeholders | Comprehensive revision |
Feedback Integration
| Source | Collection Method | Integration Process |
|---|
| Teacher Feedback | Monthly surveys; PLC discussions | Quarterly adjustments |
| Student Feedback | End-of-unit surveys; Focus groups | Semester adjustments |
| Parent Feedback | Annual surveys; Advisory meetings | Annual review input |
| Employer Feedback | Portfolio reviews; Advisory board | Annual curriculum alignment |
Version Control
| Version | Date | Major Changes |
|---|
| 1.0 | [Initial] | Baseline curriculum framework |
| 1.1 | [+6 months] | Adjustments based on pilot feedback |
| 2.0 | [+1 year] | Full revision incorporating Year 1 learnings |
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