Complete Curriculum Syllabus

Lesson 1: Technology in Our World

Objective

Students will identify simple technologies in daily life and understand their basic functions.

Key Concepts

• Identify simple technologies in daily life
• Explain basic functions of common technologies
• Distinguish between technology and non-technology items

Learning Activities

• Technology hunt around the classroom to identify different devices
• Sorting activity: Is it technology or not?
• Discussion about technologies used at home

Resources

• Picture cards of common technologies
• Classroom technology examples
• Technology sorting worksheet

Assessment

• Students identify at least 3 technologies in the classroom
• Students explain what one technology does

Lesson 2: Computer Basics

Objective

Students will identify basic parts of digital devices and practice proper device usage.

Key Concepts

• Identify basic parts of digital devices
• Practice proper device usage
• Understand computers need instructions

Learning Activities

• Labeling parts of a computer activity
• Practice turning devices on and off properly
• Simple instruction-following games

Resources

• Computer parts diagram
• Practice tablets or computers
• Visual instruction cards

Assessment

• Students point to and name basic computer parts
• Students demonstrate proper device handling

Lesson 3: Following Digital Instructions

Objective

Students will learn how machines follow step-by-step directions and practice giving clear instructions.

Key Concepts

• Learn how machines follow step-by-step directions
• Practice giving clear, simple instructions
• Recognize importance of order in instructions

Learning Activities

• Robot game where students give step-by-step directions to a partner
• Sequencing activity with picture cards
• Simple unplugged coding exercises

Resources

• Sequence picture cards
• Robot movement instruction cards
• Simple maze worksheets

Assessment

• Students give 3-step instructions in the correct order
• Students follow simple step-by-step directions

Lesson 4: Kind Technology Use

Objective

Students will develop skills for sharing and taking turns with technology and practice asking for help appropriately.

Key Concepts

• Develop skills for sharing and taking turns with technology
• Practice gentle handling of devices
• Ask for help appropriately

Learning Activities

• Taking turns games with classroom technology
• Role-playing asking for help scenarios
• Device care demonstration and practice

Resources

• Sharing and turn-taking visual cards
• Device care poster
• Help request prompt cards

Assessment

• Students demonstrate sharing technology with a partner
• Students show how to ask for help when needed

Lesson 5: Safety Fundamentals

Objective

Students will identify when to seek adult help and understand importance of time limits with technology.

Key Concepts

• Identify when to seek adult help
• Recognize safety symbols
• Understand importance of time limits

Learning Activities

• Safety symbol recognition activity
• Discussion: When do we ask an adult for help?
• Timer practice for technology time limits

Resources

• Safety symbol cards
• Scenario cards for when to ask for help
• Visual timer

Assessment

• Students identify situations requiring adult help
• Students respond appropriately to time limit signals

Lesson 1: Algorithms in Daily Life

Objective

Students will recognize step-by-step instructions in routines and create simple algorithms.

Key Concepts

• Recognize step-by-step instructions in routines
• Create and follow simple algorithms
• Develop logical thinking skills

Learning Activities

• Morning routine sequencing activity
• Create an algorithm for a simple task like brushing teeth
• Partner activity: Follow your friend's algorithm

Resources

• Routine sequence cards
• Algorithm creation worksheets
• Step-by-step instruction visuals

Assessment

• Students create a 4-5 step algorithm for a daily task
• Students successfully follow a peer's algorithm

Lesson 2: Introduction to Patterns

Objective

Students will identify, describe, and create patterns while connecting pattern recognition to prediction.

Key Concepts

• Identify and describe patterns in environment
• Create and extend simple patterns
• Connect pattern recognition to prediction

Learning Activities

• Pattern hunt in the classroom and outside
• Create patterns using colors, shapes, or movements
• Predict what comes next in pattern sequences

Resources

• Pattern blocks and manipulatives
• Pattern worksheet activities
• Environmental pattern photos

Assessment

• Students identify at least 3 patterns in their environment
• Students create and extend an original pattern

Lesson 3: Digital Helpers

Objective

Students will understand smart devices and learn basic input/output concepts.

Key Concepts

• Understand smart devices in homes and schools
• Learn basic input/output concepts
• Develop appropriate questions for digital helpers

Learning Activities

• Explore examples of digital helpers (voice assistants, smart devices)
• Input/output sorting game
• Practice asking good questions to digital helpers

Resources

• Pictures of smart devices
• Input/output concept cards
• Question formulation guides

Assessment

• Students explain what a digital helper does
• Students demonstrate asking an appropriate question

Lesson 4: Responsible Technology Time

Objective

Students will create healthy technology habits and develop self-regulation strategies.

Key Concepts

• Create healthy technology habits
• Recognize technology's effects on our bodies and minds
• Develop self-regulation strategies

Learning Activities

• Discussion about how we feel after too much screen time
• Create a healthy technology habits poster
• Practice using timers and taking breaks

Resources

• Feelings chart related to technology use
• Healthy habits poster template
• Visual timers

Assessment

• Students identify two healthy technology habits
• Students demonstrate taking a screen break when prompted

Lesson 5: Online/Offline Balance

Objective

Students will distinguish between digital and physical activities and develop decision-making skills about activity choices.

Key Concepts

• Distinguish between digital and physical activities
• Appreciate unique aspects of both types of experiences
• Develop decision-making about activity choices

Learning Activities

• Sorting activity: Online vs offline activities
• Discussion about favorite activities in each category
• Create a balanced activity plan for a day

Resources

• Activity picture cards
• Balance scale visual
• Daily activity planner template

Assessment

• Students correctly sort activities as online or offline
• Students create a plan with both types of activities

Lesson 1: Simple Decision Trees

Objective

Students will understand how computers use yes/no questions to make decisions.

Key Concepts

• Understand how yes/no questions lead to decisions
• Create simple decision trees
• Connect decision trees to everyday choices

Learning Activities

• Play 20 Questions game to understand yes/no decision making
• Create a decision tree for choosing a snack
• Follow a decision tree to sort classroom objects

Resources

• Decision tree templates
• Sorting game materials
• Yes/No question cards

Assessment

• Students create a 3-level decision tree
• Students follow a decision tree to reach a correct conclusion

Lesson 2: Introduction to AI Assistants

Objective

Students will understand what AI assistants are and how they can help us.

Key Concepts

• Identify common AI assistants
• Understand AI assistants follow programmed rules
• Recognize limitations of AI assistants

Learning Activities

• Discussion about AI assistants students have used
• Role-play being an AI assistant following rules
• Compare what AI can and cannot do

Resources

• Pictures of common AI assistants
• AI assistant capability cards
• Role-play scenario cards

Assessment

• Students name two AI assistants and their purposes
• Students identify one thing AI can do and one thing it cannot

Lesson 3: Digital Information Basics

Objective

Students will begin to evaluate whether digital information is trustworthy.

Key Concepts

• Understand not all online information is true
• Learn to ask questions about information sources
• Practice checking information with trusted adults

Learning Activities

• True or silly: Sort statements into fact vs. fiction
• Discussion about where information comes from
• Practice asking 'How do we know this is true?'

Resources

• Fact vs. fiction sorting cards
• Information source posters
• Question prompt cards

Assessment

• Students identify two questions to ask about online information
• Students explain why checking information is important

Lesson 4: Digital Citizenship Beginnings

Objective

Students will understand how to be kind and responsible online.

Key Concepts

• Apply kindness rules to digital spaces
• Understand digital actions affect real people
• Recognize what information to keep private

Learning Activities

• Create classroom digital kindness rules
• Scenario sorting: Kind or unkind online behavior
• Private vs. shareable information game

Resources

• Digital kindness poster template
• Behavior scenario cards
• Private information sorting activity

Assessment

• Students state two rules for being kind online
• Students identify information that should stay private

Lesson 5: Technology Creation

Objective

Students will use technology as a tool for creativity and expression.

Key Concepts

• Use technology to create something new
• Follow steps to complete a digital project
• Share creations appropriately

Learning Activities

• Create a simple digital drawing or story
• Follow step-by-step instructions for a tech project
• Share and celebrate classmates' creations

Resources

• Drawing or story creation app
• Step-by-step project guide
• Sharing and feedback guidelines

Assessment

• Students complete a simple digital creation project
• Students give kind feedback on a peer's creation

Lesson 1: Teaching Computers

Objective

Students will understand the basics of machine learning through hands-on activities.

Key Concepts

• Introduction to machine learning through games
• Experience training a simple system through examples
• Recognize how computers learn from patterns

Learning Activities

• Play a pattern recognition game where students 'train' a classifier
• Sort objects and discuss how a computer would learn the rules
• Explore an interactive machine learning demo

Resources

• Pattern sorting materials
• Machine learning game cards
• Interactive ML demonstration

Assessment

• Students explain how computers learn from examples
• Students successfully train a simple classifier with 5+ examples

Lesson 2: Digital Information Collection

Objective

Students will understand how digital data is collected and why privacy matters.

Key Concepts

• Understand how and why digital data is collected
• Learn basic concepts of data privacy
• Develop critical thinking about information sharing

Learning Activities

• Discussion about what information apps and websites collect
• Create a list of personal information categories
• Role-play scenarios about sharing information online

Resources

• Data collection examples poster
• Personal information categories chart
• Privacy scenario cards

Assessment

• Students identify three types of data that websites collect
• Students explain why some information should be kept private

Lesson 3: Smart vs. Not-Smart Technology

Objective

Students will distinguish between AI-powered technology and regular technology.

Key Concepts

• Distinguish between AI and regular technology
• Understand basic characteristics of 'smart' technology
• Identify limitations of both types of technology

Learning Activities

• Sorting activity: Smart technology vs. regular technology
• Discussion about what makes technology 'smart'
• Explore examples of AI in everyday devices

Resources

• Technology sorting cards
• Smart technology examples poster
• Comparison chart template

Assessment

• Students correctly categorize 8 out of 10 technology examples
• Students explain two differences between smart and regular technology

Lesson 4: Digital Footprints

Objective

Students will understand that online actions leave traces and how to manage them.

Key Concepts

• Understand online actions leave traces
• Recognize different types of digital footprints
• Develop strategies for maintaining positive digital presence

Learning Activities

• Create a visual representation of a digital footprint
• Discuss examples of positive and negative digital footprints
• Develop personal guidelines for online behavior

Resources

• Digital footprint worksheet
• Positive/negative examples cards
• Personal guidelines template

Assessment

• Students identify three ways online actions leave traces
• Students create two personal guidelines for positive digital presence

Lesson 5: Solving Problems with Technology

Objective

Students will use digital tools systematically to solve simple challenges.

Key Concepts

• Use digital tools to address simple challenges
• Develop systematic approach to technology problem-solving
• Apply creative thinking to technology-based solutions

Learning Activities

• Work through a structured problem-solving challenge
• Use technology tools to create a solution to a class problem
• Present and explain solutions to classmates

Resources

• Problem-solving framework poster
• Digital creation tools
• Presentation guidelines

Assessment

• Students follow a systematic approach to solve a technology challenge
• Students present a creative technology-based solution

Lesson 1: AI Around Us

Objective

Students will identify and understand AI applications in their everyday environments.

Key Concepts

• Identify AI in everyday environments
• Understand difference between AI and other technologies
• Recognize how AI impacts daily life

Learning Activities

• AI scavenger hunt in the community (virtual or physical)
• Create a map of AI in our school and neighborhood
• Discussion about AI we interact with daily

Resources

• AI scavenger hunt checklist
• Community AI mapping template
• AI examples reference guide

Assessment

• Students identify at least 5 AI applications in their environment
• Students explain how one AI application impacts their daily life

Lesson 2: How AI Makes Decisions

Objective

Students will understand how algorithms and data influence AI recommendations.

Key Concepts

• Understand algorithms and recommendations
• Recognize how data influences AI suggestions
• Develop critical thinking about AI decision processes

Learning Activities

• Explore how recommendation systems work through a simulation
• Analyze why different people get different recommendations
• Create a simple recommendation algorithm on paper

Resources

• Recommendation system simulation
• Algorithm flowchart templates
• Discussion question cards

Assessment

• Students explain how data affects AI recommendations
• Students design a simple 3-step recommendation algorithm

Lesson 3: Digital Balance and Wellbeing

Objective

Students will develop strategies for healthy and balanced technology use.

Key Concepts

• Develop healthy technology habits
• Recognize technology's effects on emotions and behavior
• Create personalized plans for balanced technology use

Learning Activities

• Self-reflection journal about technology use and feelings
• Discussion about signs of technology overuse
• Create a personal digital wellness plan

Resources

• Technology reflection journal template
• Digital wellness checklist
• Balance plan worksheet

Assessment

• Students identify three signs of unhealthy technology use
• Students create a personal digital wellness plan with specific goals

Lesson 4: Introduction to Biases

Objective

Students will understand how AI can reflect and amplify biases.

Key Concepts

• Understand how AI might treat people differently
• Recognize sources and types of bias in technology
• Develop critical thinking about fairness in AI

Learning Activities

• Explore examples of AI bias through age-appropriate case studies
• Discussion about fairness and equal treatment
• Brainstorm ways to make AI more fair

Resources

• AI bias case study cards
• Fairness discussion prompts
• Bias identification worksheet

Assessment

• Students explain one way AI might be unfair
• Students suggest one way to make AI more fair

Lesson 5: Tech Creation Project

Objective

Students will apply AI concepts through hands-on programming and creation.

Key Concepts

• Program simple AI-based interactive stories
• Apply understanding of AI concepts through hands-on creation
• Practice collaborative problem-solving with technology

Learning Activities

• Design and plan an interactive story with decision points
• Program the story using a block-based coding platform
• Share and test stories with classmates

Resources

• Story planning template
• Block-based coding platform access
• Project rubric and guidelines

Assessment

• Students create an interactive story with at least 3 decision points
• Students explain how their project demonstrates AI concepts

Lesson 1: AI Helpers and Workers

Objective

Students will understand how AI is transforming jobs and tasks in our world.

Key Concepts

• Understand automation and assistance roles
• Identify jobs and tasks being transformed by AI
• Recognize benefits and challenges of automation

Learning Activities

• Research jobs that use AI assistance
• Discussion about tasks AI can and cannot do well
• Debate the pros and cons of automation

Resources

• Career transformation case studies
• AI in jobs research guide
• Debate preparation worksheet

Assessment

• Students identify three jobs being transformed by AI
• Students articulate one benefit and one challenge of automation

Lesson 2: Data Privacy Basics

Objective

Students will understand personal data protection and develop privacy strategies.

Key Concepts

• Learn about personal information protection
• Understand what personal data is and why it's valuable
• Develop strategies for protecting private information

Learning Activities

• Identify types of personal data and their sensitivity levels
• Analyze privacy policies in kid-friendly terms
• Create a personal data protection plan

Resources

• Personal data categories chart
• Simplified privacy policy examples
• Data protection plan template

Assessment

• Students categorize personal data by sensitivity level
• Students create a plan with three strategies for protecting their data

Lesson 3: Digital Empathy

Objective

Students will develop awareness of how technology affects different people.

Key Concepts

• Consider how technology affects different people
• Develop awareness of accessibility needs in technology
• Recognize cultural and socioeconomic factors in tech access

Learning Activities

• Explore technology from different perspectives through scenarios
• Research accessibility features in common technologies
• Discussion about the digital divide and equal access

Resources

• Perspective-taking scenario cards
• Accessibility features exploration guide
• Digital divide discussion prompts

Assessment

• Students explain how the same technology can affect people differently
• Students identify three ways technology can be more accessible

Lesson 4: Fact vs. Fiction in Technology

Objective

Students will develop skills to evaluate digital content and identify misinformation.

Key Concepts

• Introduction to misinformation and AI-generated content
• Develop skills to evaluate digital content's credibility
• Learn strategies for fact-checking and verification

Learning Activities

• Analyze examples of real vs. AI-generated content
• Practice using fact-checking strategies
• Create a misinformation detection checklist

Resources

• Real vs. fake content examples
• Fact-checking website guide
• Credibility evaluation rubric

Assessment

• Students correctly identify misinformation in 4 out of 5 examples
• Students demonstrate three fact-checking strategies

Lesson 5: Future Technology Citizens

Objective

Students will understand their rights and responsibilities in digital spaces.

Key Concepts

• Understand rights and responsibilities in digital spaces
• Recognize personal rights in AI-powered environments
• Explore ethical decision-making frameworks for technology

Learning Activities

• Create a digital bill of rights for students
• Apply ethical frameworks to technology scenarios
• Design a pledge for responsible technology use

Resources

• Digital rights discussion prompts
• Ethical decision-making framework
• Technology pledge template

Assessment

• Students articulate three digital rights they believe are important
• Students apply an ethical framework to a technology scenario

Lesson 1: AI Fundamentals

Objective

Students will understand core concepts of artificial intelligence and machine learning.

Key Concepts

• Core concepts of artificial intelligence and machine learning
• Differentiate between AI, machine learning, and deep learning
• Understand key capabilities and limitations of current AI

Learning Activities

• Interactive presentation on AI, ML, and deep learning differences
• Categorize AI applications by type and capability
• Myth vs. reality discussion about AI abilities

Resources

• AI concepts visual guide
• AI application categorization activity
• Capability and limitation reference chart

Assessment

• Students correctly differentiate between AI, ML, and deep learning
• Students identify three capabilities and three limitations of current AI

Lesson 2: Data Literacy

Objective

Students will develop skills to understand and analyze data critically.

Key Concepts

• Understand data collection, analysis, and interpretation
• Develop skills to analyze different types of data
• Recognize limitations in data collection and analysis

Learning Activities

• Collect and analyze classroom data to find patterns
• Evaluate data visualizations for accuracy and bias
• Discuss how data quality affects AI outcomes

Resources

• Data collection templates
• Data visualization examples
• Data quality checklist

Assessment

• Students collect data and identify meaningful patterns
• Students evaluate a data visualization and identify potential issues

Lesson 3: AI Decision-Making

Objective

Students will understand how algorithms make recommendations and predictions.

Key Concepts

• How algorithms work to make recommendations and predictions
• Identify factors that influence AI suggestions
• Develop critical thinking about algorithmic processes

Learning Activities

• Simulate a recommendation algorithm with cards and rules
• Analyze how personal data affects recommendations received
• Design criteria for evaluating algorithmic fairness

Resources

• Algorithm simulation materials
• Recommendation analysis worksheet
• Algorithmic fairness criteria template

Assessment

• Students explain how three factors influence AI recommendations
• Students create criteria for evaluating whether an algorithm is fair

Lesson 4: Ethical Considerations in AI

Objective

Students will understand fairness, bias, and equity in automated systems.

Key Concepts

• Understand fairness, bias, and equity in automated systems
• Identify sources and types of bias in AI
• Develop frameworks for evaluating AI ethics

Learning Activities

• Case study analysis of AI bias incidents
• Identify potential bias sources in training data
• Create an ethical evaluation checklist for AI systems

Resources

• AI ethics case studies
• Bias source identification guide
• Ethics evaluation framework template

Assessment

• Students identify bias sources in a given AI scenario
• Students apply an ethical framework to evaluate an AI system

Lesson 5: Digital Identity Protection

Objective

Students will develop strategies for managing personal information in an AI world.

Key Concepts

• Managing personal information in an AI world
• Recognize how AI systems use personal data
• Develop strategies for protecting privacy

Learning Activities

• Audit personal digital footprint across platforms
• Research how AI companies collect and use data
• Create a comprehensive digital privacy plan

Resources

• Digital footprint audit checklist
• Data collection research guide
• Privacy plan template

Assessment

• Students identify five ways AI systems collect personal data
• Students create a privacy plan with specific protective actions

Lesson 1: AI in Science and Medicine

Objective

Students will understand AI applications in scientific research, diagnosis, and treatment.

Key Concepts

• Applications in research, diagnosis, and treatment
• Identify key applications of AI in scientific fields
• Recognize benefits and limitations of AI in medicine

Learning Activities

• Research case studies of AI in medical diagnosis
• Explore AI tools used in scientific research
• Debate the benefits and risks of AI in healthcare

Resources

• Medical AI case study collection
• Scientific AI applications guide
• Healthcare AI debate prompts

Assessment

• Students explain three applications of AI in science or medicine
• Students analyze benefits and limitations of a specific medical AI

Lesson 2: AI in Arts and Expression

Objective

Students will explore the relationship between human creativity and AI tools.

Key Concepts

• Creative tools, music generation, and digital art
• Understand relationship between human creativity and AI
• Consider questions of authorship and artistic expression

Learning Activities

• Experiment with AI art and music generation tools
• Compare human-created and AI-assisted artwork
• Discussion about authorship and creativity in the AI age

Resources

• AI creative tool access guide
• Art comparison activity materials
• Authorship discussion framework

Assessment

• Students create art using AI tools and reflect on the process
• Students articulate a position on AI and artistic authorship

Lesson 3: AI in History and Language

Objective

Students will explore AI applications in translation, preservation, and information analysis.

Key Concepts

• Translation, preservation, and information analysis
• Explore applications in cultural heritage and linguistics
• Consider how AI changes our relationship with language

Learning Activities

• Test AI translation tools across multiple languages
• Research AI projects preserving endangered languages
• Analyze how AI affects communication across cultures

Resources

• Translation tool comparison guide
• Language preservation project profiles
• Cross-cultural communication analysis worksheet

Assessment

• Students evaluate AI translation accuracy and limitations
• Students explain how AI can help preserve cultural heritage

Lesson 4: Environmental AI

Objective

Students will understand how AI addresses environmental challenges and sustainability.

Key Concepts

• Climate modeling, conservation, and sustainability applications
• Understand how AI addresses environmental challenges
• Consider ethical dimensions of environmental AI

Learning Activities

• Research AI applications in climate science and conservation
• Analyze case studies of AI for sustainability
• Discuss ethical considerations of environmental AI

Resources

• Environmental AI application database
• Sustainability case studies
• Ethics discussion framework

Assessment

• Students explain three ways AI addresses environmental challenges
• Students identify ethical considerations in environmental AI use

Lesson 5: Design Thinking with AI

Objective

Students will use AI tools and design thinking to solve community problems.

Key Concepts

• Using AI tools to solve community problems
• Apply collaborative problem-solving approaches
• Develop critical thinking about AI's social impact

Learning Activities

• Identify a community problem suitable for AI assistance
• Apply design thinking process to develop a solution concept
• Present AI-enhanced solution to peers for feedback

Resources

• Design thinking process guide
• Community problem identification worksheet
• Solution presentation template

Assessment

• Students apply design thinking to a real community challenge
• Students propose a feasible AI-enhanced solution with consideration of impacts

Lesson 1: Media Literacy in the Age of AI

Objective

Students will develop skills to evaluate AI-generated content and identify deepfakes.

Key Concepts

• Evaluating AI-generated content and deepfakes
• Develop skills to identify synthetic media
• Apply critical media literacy strategies

Learning Activities

• Analyze examples of AI-generated images, text, and video
• Learn techniques for identifying synthetic media
• Create a media literacy guide for peers

Resources

• AI-generated content examples collection
• Deepfake detection techniques guide
• Media literacy guide template

Assessment

• Students correctly identify synthetic media in 8 out of 10 examples
• Students create a comprehensive media literacy guide

Lesson 2: AI and Privacy Rights

Objective

Students will understand data collection, consent, and privacy laws.

Key Concepts

• Understanding data collection, consent, and privacy laws
• Recognize concept of informed consent
• Develop strategies for managing personal privacy

Learning Activities

• Research major privacy laws and regulations
• Analyze real-world consent forms and privacy policies
• Create a privacy rights awareness presentation

Resources

• Privacy law overview guide
• Consent form analysis worksheet
• Presentation template and rubric

Assessment

• Students explain key privacy rights and laws
• Students identify issues in privacy policies and consent processes

Lesson 3: Social Media Algorithms

Objective

Students will understand how recommendation systems shape information exposure.

Key Concepts

• How recommendation systems shape information exposure
• Recognize effects of algorithmic curation
• Develop strategies for intentional information consumption

Learning Activities

• Map personal algorithm bubbles across platforms
• Experiment with algorithm influence through controlled browsing
• Develop personal strategies for diverse information consumption

Resources

• Algorithm mapping worksheet
• Controlled browsing experiment guide
• Information diversity strategy template

Assessment

• Students analyze how algorithms shape their content exposure
• Students implement and evaluate information diversity strategies

Lesson 4: AI Advocacy and Leadership

Objective

Students will develop skills to advocate for responsible AI in their communities.

Key Concepts

• Advocating for responsible AI in communities
• Identify opportunities for youth voice in AI governance
• Develop skills for effective technology advocacy

Learning Activities

• Research youth involvement in technology policy
• Identify local opportunities for AI advocacy
• Develop and present an advocacy campaign proposal

Resources

• Youth advocacy case studies
• Local advocacy opportunity guide
• Campaign proposal template

Assessment

• Students identify concrete advocacy opportunities in their community
• Students create a persuasive advocacy campaign proposal

Lesson 5: Cross-Cultural AI Understanding

Objective

Students will understand how AI impacts diverse communities differently.

Key Concepts

• How AI impacts diverse communities differently
• Recognize cultural assumptions in technology
• Explore global perspectives on AI development

Learning Activities

• Research AI impacts on different communities worldwide
• Analyze cultural assumptions embedded in AI systems
• Develop recommendations for culturally aware AI design

Resources

• Global AI impact case studies
• Cultural assumption analysis framework
• Design recommendation template

Assessment

• Students analyze AI impacts on at least two different communities
• Students propose recommendations for more culturally aware AI

Lesson 1: Machine Learning Basics

Objective

Students will understand fundamental types of machine learning (supervised, unsupervised, reinforcement) and how AI systems learn from data.

Key Concepts

• How machines learn from patterns
• Supervised vs. unsupervised learning
• Training data and how it shapes AI capabilities
• Real-world applications of machine learning

Learning Activities

• Interactive demonstration using Google's Teachable Machine to train an image classifier
• Students collect their own image samples to train a custom model that can recognize gestures or objects
• Small group discussions about how the quality and variety of training data affects model performance

Resources

• Google Teachable Machine - No coding required platform for creating custom ML models
• CrashCourse AI on YouTube - Episodes 1-4 provide excellent foundational knowledge
• AI4K12 - Grade-appropriate explanations of ML concepts
• Elements of AI - Free online course with interactive exercises

Assessment

• Students document their Teachable Machine model training process, noting challenges and discoveries
• Written reflection: "How might bias in training data affect an AI system's decisions?"

Extension: Peer Teaching Initiative

• Partner with 11th/12th grade students taking advanced computer science to host an "AI 101" workshop
• Create student-led demonstration stations showing different types of machine learning in action
• Develop a school-wide "How AI Works" exhibition

Parent Note

Encourage your child to continue exploring machine learning concepts at home by trying additional Teachable Machine projects or exploring AI Experiments by Google. Discuss how AI systems they use daily (like recommendation algorithms) are trained using data from user interactions.

Lesson 2: Programming and AI

Objective

Students will learn fundamental programming concepts that enable AI development, with emphasis on Python as the industry-standard language for AI.

Key Concepts

• Basic Python syntax and structure
• Variables, loops, and conditional statements
• Functions and libraries in Python
• How programming connects to AI development

Learning Activities

• Step-by-step guided coding exercises to build a simple text-based chatbot
• Small-group challenge to enhance the chatbot with additional features
• Analyze sample code from existing AI systems to understand structure

Resources

• Code.org's AI & Machine Learning Units - Structured curriculum designed for high school students
• Replit - Browser-based coding environment requiring no installation
• Kaggle Learn Python - Interactive Python tutorial with AI-focused examples
• AI Family Challenge - Provides family-friendly projects

Assessment

• Functioning chatbot demonstrating basic programming concepts
• Code annotation assignment where students identify and explain key components
• Peer code review session where students provide constructive feedback

Extension: Code Buddy System

• Pair programming methodology with experienced student mentors
• Weekly coding challenges with progressive difficulty
• Create a "Programming for AI" student resource with crowd-sourced examples and explanations

Parent Note

Encourage your child to show you their chatbot project and explain how it works. Consider exploring additional free resources like Python for Everybody to support their learning journey. Many careers in technology no longer require advanced degrees but do require programming literacy.

Lesson 3: Data Analysis Fundamentals

Objective

Students will understand how datasets are collected, prepared, and utilized to train AI systems, with emphasis on data literacy skills.

Key Concepts

• Types of data (structured vs. unstructured)
• Data collection methods and ethics
• Basic statistical analysis concepts
• Correlation vs. causation
• Data visualization techniques

Learning Activities

• Analyze a real-world dataset about student study habits and test scores
• Create data visualizations that reveal patterns in the dataset
• Develop hypotheses about the data and test them with basic analysis tools
• Design and conduct a small data collection project within the school

Resources

• Kaggle Datasets - Repository of open datasets and analysis examples
• Google Data Studio - Free data visualization tool
• Makeover Monday - Real-world data visualization challenges
• DataBasic.io - Simplified data analysis tools for beginners

Assessment

• Data analysis project with visualizations and written interpretations
• Presentation explaining meaningful insights discovered in the dataset
• Critical reflection on potential biases or limitations in the data

Extension: School Data Challenge

• Teams compete to find the most meaningful insights in a school-relevant dataset
• Students design and implement a small-scale data collection study
• Host a "Data Discovery Day" where findings are presented to school administration

Parent Note

Ask your child to explain the data patterns they discovered and what those patterns might mean. Data literacy is increasingly important across all career fields. Consider exploring visualization tools like DataWrapper together to create graphics from interesting datasets about topics your family cares about.

Lesson 4: AI System Components

Objective

Students will explore the key technical components that make up sophisticated AI systems, focusing on neural networks, natural language processing, and computer vision.

Key Concepts

• Neural network architecture and function
• Natural Language Processing (NLP) capabilities and limitations
• Computer vision systems and applications
• How complex AI systems are built from simpler components

Learning Activities

• Experiment with TensorFlow Playground to visualize neural network operations
• Test different language models' capabilities and limitations with NLP demos
• Explore computer vision applications through interactive web-based tools
• Diagram the components of a complete AI system like a virtual assistant

Resources

• TensorFlow Playground - Interactive neural network visualization
• IBM Watson Natural Language Understanding Demo
• Teachable Machine - For computer vision exploration
• AI Experiments with Google - Interactive AI demos

Assessment

• "Explain It Simply" project where students create visual or written explanations of complex AI components
• Neural network configuration exercise using TensorFlow Playground with documentation of discoveries
• Compare and contrast analysis of different AI systems and their components

Extension: AI Explainers Initiative

• Create illustrative posters explaining key AI concepts for display throughout the school
• Develop short video tutorials explaining neural networks, NLP, or computer vision
• Present simplified AI component explanations to younger students (grades 6-8)

Parent Note

Ask your child to demonstrate how a neural network functions using TensorFlow Playground and explain the different components. Discussing these concepts helps reinforce learning and builds your child's ability to explain technical concepts clearly, a valuable skill in any profession.

Lesson 5: Career Explorations in AI

Objective

Students will discover diverse career pathways in artificial intelligence and related technical fields, emphasizing both technical and non-technical roles.

Key Concepts

• Range of careers in AI development and implementation
• Educational pathways and skill requirements
• Interdisciplinary nature of AI careers
• Ethical considerations in AI careers

Learning Activities

• Research and create AI career profiles covering requirements, salary ranges, and growth potential
• Virtual or in-person interviews with professionals working in AI-related fields
• Personal skills inventory and pathway mapping exercise
• Group discussion about ethical responsibilities in AI careers

Resources

• AI4ALL Career Resources - Career guidance focused on diversity in AI
• Pathful Explore - Career exploration platform
• AI Careers by DeepLearning.AI - Blog posts on AI careers
• MIT Technology Review - Current developments in AI fields

Assessment

• Career pathway presentation with education plan and skills development roadmap
• Interview summary highlighting insights gained from AI professionals
• Reflective essay: "My potential contribution to the field of artificial intelligence"

Extension: AI Professionals Panel

• Student-organized panel discussion with local AI professionals
• Career fair with AI specialization featuring industry representatives
• Peer mentoring program connecting students with similar career interests

Parent Note

Discuss your child's career interests and how AI might relate to fields they're considering. Remember that AI is becoming integrated across nearly all industries, from healthcare to entertainment to environmental conservation. Consider helping your child connect with professionals in their interest areas who might provide mentorship regarding AI applications in those fields.

Lesson 1: AI in Healthcare

Objective

Students will explore how AI is revolutionizing healthcare through diagnostics, treatment planning, and drug discovery.

Key Concepts

• AI-powered medical imaging and diagnostics
• Personalized medicine and treatment recommendations
• Drug discovery and development acceleration
• Healthcare accessibility and AI

Learning Activities

• Research case studies of AI applications in medical diagnosis, including cancer detection in mammograms and retinal scans for diabetic eye disease
• Analyze the benefits and limitations of AI in healthcare settings, comparing AI diagnostic accuracy with human specialist performance
• Discuss ethical considerations in AI-assisted medical decisions, including data privacy, algorithmic bias in clinical data, and equitable access to AI-powered care

Resources

• Google Health AI Research - Published studies on AI-powered breast cancer screening and diabetic retinopathy detection with real performance data
• AlphaFold Protein Structure Database - DeepMind's breakthrough tool for predicting protein structures, revolutionizing drug discovery
• WHO Digital Health Guidelines - World Health Organization framework for evaluating AI applications in healthcare delivery
• AI in Medicine Case Study Collection - Curated examples of AI diagnostics, personalized treatment, and drug discovery acceleration across global healthcare systems

Assessment

• Research presentation on a specific AI healthcare application, documenting how it works, its accuracy, and its real-world impact on patient outcomes
• Written analysis of ethical considerations in medical AI, addressing data privacy, algorithmic bias, and the tension between innovation and equitable access

Extension: Healthcare AI Impact Investigation

• Interview a healthcare professional about how AI tools are changing their daily practice and what concerns they have about AI in medicine
• Compare AI diagnostic performance across different demographic groups to investigate potential bias in medical AI systems
• Design a proposal for an AI-powered healthcare solution that addresses a specific accessibility gap in underserved communities

Parent Note

Discuss with your child how AI is already present in healthcare — from fitness trackers that monitor heart rate patterns to AI-assisted diagnostic tools your own doctor may use. Ask them to explain the difference between AI-powered diagnostics and personalized medicine. This lesson connects directly to careers in health informatics, biomedical engineering, and public health — fields that are growing rapidly as AI transforms medicine.

Lesson 2: AI in Transportation and Urban Planning

Objective

Students will understand how AI is shaping the future of transportation and smart city development.

Key Concepts

• Autonomous vehicles and safety considerations
• Traffic optimization and smart infrastructure
• Environmental impact and sustainability
• Urban planning with AI-driven insights

Learning Activities

• Explore simulations of autonomous vehicle decision-making, examining how LIDAR, computer vision, and neural networks work together to navigate real-world driving scenarios
• Design a smart city feature using AI principles, incorporating traffic optimization, environmental monitoring, or public transit improvements
• Debate the societal implications of autonomous transportation, including the trolley problem, liability questions, job displacement for professional drivers, and equitable access to smart infrastructure

Resources

• MIT Moral Machine - Interactive platform exploring ethical dilemmas in autonomous vehicle programming and how different cultures approach these trade-offs
• Pittsburgh Surtrac System Case Study - Real-world AI traffic optimization system that reduced travel times by 25% and emissions by 21% using adaptive signal control
• Singapore Virtual Singapore Platform - Digital twin city model demonstrating how AI-driven urban simulations inform infrastructure planning and resource allocation
• US Department of Transportation AV Resources - Federal guidelines and safety frameworks for autonomous vehicle testing and deployment

Assessment

• Smart city design project with AI integration, including a specific problem statement, proposed AI solution, data requirements, and consideration of community impact
• Analysis of autonomous vehicle ethical dilemmas, evaluating at least two competing perspectives on how AI should handle unavoidable accident scenarios

Extension: Smart City Design Challenge

• Map the traffic patterns and infrastructure challenges in your own neighborhood, then propose an AI-powered solution with realistic data requirements
• Research how different cities worldwide are implementing smart infrastructure and compare their approaches to sustainability and equity
• Create a presentation arguing for or against the deployment of autonomous vehicles in your community, using data from real-world pilot programs

Parent Note

Ask your child to point out AI-powered transportation features you encounter together — adaptive traffic signals, GPS navigation predictions, or ride-sharing surge pricing are all examples. Discuss the autonomous vehicle ethical dilemmas they explored and share your own perspective. This lesson connects to careers in urban planning, civil engineering, environmental science, and transportation technology — all fields being transformed by AI integration.

Lesson 3: AI in Entertainment and Media

Objective

Students will examine how AI is transforming content creation, recommendation systems, and interactive entertainment.

Key Concepts

• Content recommendation algorithms
• AI-generated art, music, and writing
• Deepfakes and media authenticity
• Personalization and filter bubbles

Learning Activities

• Experiment with AI content generation tools for images, music, and text, documenting how prompts affect output quality and comparing AI-generated content to human-created work
• Analyze recommendation algorithm behavior by comparing content suggestions across different user profiles and identifying what data signals drive personalization
• Discuss media literacy in the age of AI-generated content, examining real examples of deepfakes and developing criteria for evaluating content authenticity

Resources

• AI Content Generation Platforms - Hands-on access to image generators, music composition tools, and text generation systems for exploring creative AI capabilities and limitations
• Recommendation Algorithm Visualization Tools - Interactive demonstrations showing how collaborative filtering and content-based filtering produce different suggestions from the same content library
• Media Literacy Now - Educational resources for evaluating digital content authenticity, including deepfake detection techniques and source verification strategies
• Filter Bubble Research Collection - Academic studies and journalism exploring how algorithmic curation narrows information exposure and its effects on public discourse

Assessment

• Creative project using AI generation tools, accompanied by a reflective analysis comparing the AI-assisted creative process to traditional creation and articulating a position on AI authorship
• Media authenticity analysis and presentation, demonstrating at least three techniques for identifying AI-generated or manipulated content across images, text, and video

Extension: AI Media Lab

• Conduct a controlled experiment comparing how the same recommendation platform serves different content to profiles with different viewing histories, documenting the filter bubble effect
• Create a side-by-side gallery of human-created and AI-generated artwork, then survey others to see if they can distinguish between them
• Develop a media literacy workshop for younger learners explaining how to identify deepfakes and AI-generated content in age-appropriate terms

Parent Note

Your child is likely encountering AI-generated content and recommendation algorithms daily through streaming services, social media, and gaming. Ask them to show you how their feed differs from yours on the same platform — this demonstrates filter bubbles in action. Discuss the deepfake examples they analyzed and talk about how your family approaches media verification. This lesson connects to careers in digital media, journalism, cybersecurity, content moderation, and creative technology.

Lesson 4: AI in Government and Public Policy

Objective

Students will explore how AI is being used in governance and the policy considerations it raises.

Key Concepts

• AI in public services and administration
• Algorithmic decision-making in justice systems
• Privacy and surveillance considerations
• International AI policy and governance

Learning Activities

• Research AI applications in government services, including benefits distribution, fraud detection, public health monitoring, and emergency response optimization
• Analyze bias in algorithmic decision-making using documented case studies from justice systems, examining how risk assessment tools produce disparate outcomes across demographic groups
• Draft AI policy recommendations for a specific domain, balancing innovation benefits with civil liberties protections and accountability requirements

Resources

• AI Now Institute Reports - Research on the social implications of artificial intelligence in government, policing, and public services with documented case studies
• EU AI Act Framework - The European Union's comprehensive regulatory approach to AI governance, categorizing AI systems by risk level and establishing compliance requirements
• ProPublica COMPAS Investigation - Landmark journalism examining bias in criminal justice risk assessment algorithms, demonstrating how algorithmic decision-making can produce racially disparate outcomes
• OECD AI Policy Observatory - International database tracking AI governance approaches across countries, providing comparative policy analysis and best practice recommendations

Assessment

• Policy brief on AI governance recommendations for a specific domain, including problem analysis, stakeholder identification, proposed regulations, and implementation considerations
• Case study analysis of AI in public services, evaluating both the efficiency gains and the civil liberties concerns of a specific government AI deployment

Extension: Policy Lab

• Research how your local or state government currently uses AI systems and evaluate whether adequate transparency and accountability measures are in place
• Organize a mock policy hearing where participants argue for and against a specific AI regulation, presenting evidence from real-world implementations
• Write a letter to a local representative advocating for a specific AI governance measure, supported by evidence from your research

Parent Note

Discuss with your child how government AI systems may already affect your family — from predictive policing in your community to algorithmic processing of tax returns or benefits applications. Ask them to explain the difference between the EU and US approaches to AI regulation and which they find more compelling. This lesson develops critical civic engagement skills and connects to careers in public policy, law, political science, and government technology.

Lesson 5: Building an AI-Ready Society

Objective

Students will synthesize their learning to envision and plan for a society that effectively integrates AI.

Key Concepts

• Digital literacy and AI education
• Workforce transformation and reskilling
• Inclusive AI development
• Long-term societal planning

Learning Activities

• Develop a community AI readiness plan that addresses digital literacy gaps, workforce transition needs, and infrastructure requirements for equitable AI integration
• Create educational resources for AI literacy, designing age-appropriate materials that explain how AI systems work, how to evaluate AI-generated content, and what data rights individuals possess
• Design inclusive AI implementation strategies that ensure diverse communities benefit from AI advances, addressing the digital divide, accessibility needs, and cultural considerations

Resources

• World Economic Forum Future of Jobs Report - Data-driven analysis of how AI and automation are reshaping the global workforce, including emerging roles and declining occupations
• AI4ALL Education Resources - Frameworks for making AI education accessible and inclusive across diverse communities and socioeconomic backgrounds
• National AI Initiative Office Resources - US government strategy documents for AI research, workforce development, and international competitiveness
• UNESCO AI Ethics Recommendation - Global framework for the ethical development and deployment of AI systems, emphasizing human rights, inclusivity, and environmental sustainability

Assessment

• Comprehensive AI society plan presentation addressing all four dimensions: digital literacy, workforce transformation, inclusive development, and long-term governance planning
• Reflective essay on personal role in AI-ready society: "How will I contribute to building a society that integrates AI responsibly and equitably?"

Extension: Community AI Readiness Initiative

• Conduct an AI readiness assessment of your own community, surveying digital literacy levels, internet access, and awareness of AI systems among different age groups
• Design a reskilling program proposal for workers in an industry being transformed by AI, including specific skills to develop and training delivery methods
• Create a presentation for community leaders proposing specific steps toward more equitable AI integration, supported by data from your readiness assessment

Parent Note

This capstone lesson asks your child to think about the society they want to help build. Discuss how AI is already changing your own industry or career and what skills you think will be most valuable in the coming decades. Ask your child to share their AI readiness plan and reflective essay — their perspective on workforce transformation and inclusive AI may offer insights relevant to your own professional planning. This lesson connects to virtually every career path, as AI integration is becoming a factor across all industries.

Lesson 1: Advanced Machine Learning Techniques

Objective

Students will explore sophisticated machine learning algorithms and their applications in solving complex problems.

Key Concepts

• Deep learning architectures
• Convolutional and recurrent neural networks
• Transfer learning and model optimization
• Model evaluation and improvement strategies

Learning Activities

• Build and train neural networks using industry frameworks, constructing deep learning architectures with multiple hidden layers and observing how each layer learns increasingly abstract features -- from edges to shapes to parts to complete objects
• Apply transfer learning to customize a pre-trained model for a specific task such as skin cancer detection, freezing foundational layers trained on ImageNet and fine-tuning only the task-specific layers to achieve results with a fraction of the data and compute
• Optimize model performance through systematic hyperparameter tuning -- adjusting learning rate, batch size, and epochs -- while measuring how each adjustment affects precision, recall, F1 score, and generalization using cross-validation

Resources

• TensorFlow Playground - Interactive browser-based neural network visualization for experimenting with deep learning architectures, layer depth, and activation functions in real time
• PyTorch Tutorials - Official guided tutorials for building and training CNNs, RNNs, and LSTMs from scratch, covering the architectures used in image recognition, language translation, and financial forecasting
• Hugging Face Model Hub - Repository of pre-trained models for transfer learning experiments, enabling students to fine-tune foundational models for custom classification and detection tasks
• scikit-learn Model Evaluation Documentation - Comprehensive guide to precision, recall, F1 score, confusion matrices, cross-validation, and hyperparameter tuning with practical code examples

Assessment

• Machine learning project with documented methodology, including architecture selection rationale (CNN vs. RNN vs. LSTM), training strategy, transfer learning decisions, and a complete description of the data pipeline from input to output
• Model performance analysis and optimization report using precision, recall, F1 score, and confusion matrices to diagnose overfitting and underfitting, with documented hyperparameter tuning iterations and cross-validation results

Extension: Deep Learning Architecture Lab

• Compare the performance of a shallow neural network (one hidden layer) against a deep network (eight or more layers) on the same image classification task, documenting how hierarchical feature learning affects accuracy
• Implement an LSTM network to process sequential data such as stock prices or weather patterns, analyzing how the forget, input, and output gates solve the vanishing gradient problem that limits standard RNNs
• Conduct a transfer learning efficiency experiment by training one model from scratch and another using a pre-trained ImageNet backbone on the same task, comparing data requirements, training time, and final performance metrics

Parent Note

Your child is moving from understanding AI concepts to engineering AI systems. Ask them to explain the difference between a CNN and an RNN, and why the architecture must match the data type. Discuss the transfer learning concept -- the idea that a model pre-trained on millions of images can be adapted to a new task with far less data, much like how learning piano transfers skills to organ. This lesson connects to careers in machine learning engineering, data science, biomedical AI, and autonomous systems -- fields where precision, recall, and model evaluation are daily professional tools.

Lesson 2: Natural Language Processing Applications

Objective

Students will develop practical NLP applications including sentiment analysis, text generation, and language translation.

Key Concepts

• Text preprocessing and tokenization
• Sentiment analysis and classification
• Language models and text generation
• Multilingual NLP and translation

Learning Activities

• Build a sentiment analysis application by preprocessing real text data through a complete NLP pipeline -- lowercasing, punctuation removal, stopword removal, stemming or lemmatization, and tokenization -- then selecting a classification approach (bag-of-words, TF-IDF, or word embeddings) and testing against labeled product reviews
• Experiment with language model APIs by adjusting temperature and top-k sampling parameters, modifying prompts to observe how prompt engineering shapes output, and documenting how the attention mechanism allows transformers to weigh the relevance of every previous token when predicting the next one
• Create a practical NLP tool for a specific use case of your choosing -- such as brand monitoring, customer service routing, or multilingual text analysis -- applying the full pipeline from preprocessing through tokenization to classification or generation output

Resources

• NLTK (Natural Language Toolkit) - Python library for text preprocessing, tokenization, stemming, lemmatization, and stopword removal with built-in corpora and educational documentation
• Hugging Face Transformers Library - Access to pre-trained transformer models for sentiment analysis, text generation, and translation, with interactive demos and API documentation
• OpenAI API Playground - Interactive environment for experimenting with language model parameters including temperature, top-k sampling, and prompt engineering techniques
• Kaggle NLP Datasets - Curated text datasets for sentiment analysis including product reviews, social media posts, and multilingual corpora for hands-on classification projects

Assessment

• Functional NLP application with documentation covering the complete pipeline -- text preprocessing decisions (stemming vs. lemmatization rationale), classification approach selection (bag-of-words vs. TF-IDF vs. word embeddings), model performance metrics, and example inputs with outputs
• Analysis of NLP capabilities and limitations, evaluating specific failure modes including sentiment misclassification of sarcasm and negation, translation breakdowns with idiomatic expressions, language model hallucination of citations, and the equity gap between high-resource and low-resource languages (7,000+ languages vs. approximately 100 modeled)

Extension: NLP Engineering Lab

• Build a comparative sentiment analysis system that processes the same set of reviews using bag-of-words, TF-IDF, and word embeddings, documenting how each approach handles context-dependent phrases like 'not good' and measuring classification accuracy differences
• Investigate multilingual NLP by testing a translation engine on idiomatic expressions across three or more languages, analyzing where the encoder-decoder architecture produces accurate meaning transfer versus nonsense literal translation
• Design a prompt engineering experiment that demonstrates how the same language model produces dramatically different outputs based on prompt phrasing, documenting at least five prompt variations and analyzing how temperature and top-k settings interact with prompt specificity

Parent Note

Your child encounters NLP every day -- predictive text on their keyboard, translation engines, and product review sentiment scores are all powered by the pipeline they are now learning to build. Ask them to explain how a transformer's attention mechanism decides which words matter most when predicting the next token, and why 'not good' fools a bag-of-words model but not a word embedding approach. Discuss the multilingual equity challenge: over 7,000 languages exist, but AI models cover roughly 100. This lesson connects to careers in computational linguistics, AI product development, content moderation, and international technology -- fields where NLP engineering is a core skill.

Lesson 3: Computer Vision Projects

Objective

Students will create computer vision applications for image recognition, object detection, and visual analysis.

Key Concepts

• Image classification techniques
• Object detection and localization
• Image segmentation
• Real-time video analysis

Learning Activities

• Develop an image classification system by building a CNN pipeline that processes images through convolutional layers extracting features at increasing abstraction (edges, textures, shapes, objects), applies a softmax function to produce probability distributions across categories, and outputs classification predictions with confidence scores
• Build an object detection application implementing bounding box prediction, exploring the difference between region proposal methods and single-pass architectures like YOLO (You Only Look Once) that divide images into grids and predict bounding boxes and class probabilities simultaneously at 45+ frames per second using anchor boxes
• Create a real-time visual analysis tool that processes video input with temporal consistency and object tracking, using optical flow algorithms to estimate pixel motion between consecutive frames and maintain stable object identities across the video stream

Resources

• OpenCV (Open Source Computer Vision Library) - Industry-standard library for image processing, feature extraction, object tracking, and real-time video analysis with Python and C++ interfaces
• TensorFlow Object Detection API - Pre-built pipelines and pre-trained models for image classification, object detection, and instance segmentation with transfer learning support
• YOLO (Ultralytics) Documentation - Implementation guides for the YOLO real-time object detection architecture, including anchor box configuration, grid-based prediction, and non-maximum suppression
• Roboflow - Platform for managing computer vision datasets, annotating images with bounding boxes and segmentation masks, and training custom models for classification and detection tasks

Assessment

• Computer vision project demonstration showing a working system that implements at least one of: image classification with CNN feature extraction and softmax output, object detection with bounding boxes and confidence scores, or semantic/instance segmentation with pixel-level classification -- including live or recorded demonstration of the system processing real inputs
• Technical documentation and analysis covering CNN architecture decisions, the distinction between classification (identifying what) and detection (identifying what and where), the difference between semantic segmentation (class labels per pixel) and instance segmentation (individual object identity), and performance evaluation including processing speed and accuracy metrics

Extension: Computer Vision Engineering Lab

• Compare semantic segmentation and instance segmentation on the same image, demonstrating how semantic segmentation labels all car pixels identically while instance segmentation assigns each car a unique identity -- and analyze which approach is required for applications like autonomous driving versus satellite land-use mapping
• Build a real-time object tracking system that maintains consistent object identity across video frames, implementing temporal consistency to eliminate the flickering and identity loss that occurs when frames are processed independently
• Apply the U-Net encoder-decoder architecture to a biomedical image segmentation task, tracing exact boundaries of structures in medical images and comparing the pixel-level precision against bounding-box-based detection approaches

Parent Note

Computer vision is one of the most tangible AI applications your child will encounter -- from phone face unlock to self-driving car sensors to medical imaging AI. Ask them to explain the progression from classification (identifying what is in an image) to detection (identifying what and where) to segmentation (classifying every single pixel). Discuss the real-time challenge: a self-driving car must identify a pedestrian within 200 milliseconds. This lesson connects to careers in autonomous vehicles, medical imaging, satellite analysis, robotics, augmented reality, and manufacturing quality control -- fields where the ability to build computer vision systems is in high demand.

Lesson 4: AI for Data Science

Objective

Students will apply AI techniques to data science problems including predictive analytics and pattern recognition.

Key Concepts

• Predictive modeling and forecasting
• Anomaly detection
• Clustering and pattern recognition
• Feature engineering and selection

Learning Activities

• Build predictive models using real-world datasets, implementing regression for straightforward relationships, time series forecasting for temporal data with trends and seasonal cycles, and decision tree or random forest ensemble methods -- validating each model with an 80/20 training/test split to confirm genuine predictive power rather than memorization
• Implement anomaly detection systems using statistical approaches (z-scores measuring standard deviations from the mean) and machine learning methods (isolation forests that exploit the principle that outliers require fewer partitions to isolate, and autoencoders that flag inputs they cannot accurately reconstruct) -- applied to domains such as fraud detection, cybersecurity, or manufacturing quality
• Apply clustering techniques to discover hidden patterns in unlabeled data, comparing K-means (iterative centroid assignment), hierarchical clustering (dendrogram-based merging), and DBSCAN (density-based clustering that discovers irregular shapes and automatically identifies outliers) -- and engineer features through scaling, encoding, interaction features, and PCA dimensionality reduction to maximize model performance

Resources

• scikit-learn Machine Learning Library - Comprehensive Python library for regression, decision trees, random forests, K-means clustering, DBSCAN, PCA dimensionality reduction, and model evaluation with real-world dataset examples
• Kaggle Datasets and Competitions - Platform providing real-world datasets for predictive modeling, anomaly detection, and clustering projects with community notebooks demonstrating feature engineering techniques
• Pandas and NumPy Documentation - Essential Python data manipulation libraries for preprocessing, feature scaling, one-hot encoding, and creating interaction features from raw data tables
• Google Colab - Free cloud-based Jupyter notebook environment with GPU access for running data science experiments, building predictive models, and visualizing clustering results without local hardware requirements

Assessment

• Data science project with predictions and insights, demonstrating at least two of the four pillars (predictive modeling, anomaly detection, clustering, feature engineering) applied to a real-world dataset, with documented predictions, discovered patterns, and actionable insights supported by visualizations
• Methodology documentation and results analysis covering the complete data science workflow: feature engineering decisions (scaling, encoding, dimensionality reduction), model selection rationale, training/test split validation, performance metrics, and an honest assessment of where the model succeeds and where it falls short -- following the principle that garbage features in produces garbage predictions out

Extension: Data Science Integration Lab

• Build an integrated data science pipeline that engineers features, uses clustering to segment a dataset into meaningful groups, builds a separate predictive model for each segment, and deploys anomaly detection to flag unexpected results -- demonstrating how the four pillars work together in practice
• Conduct a feature engineering experiment comparing model performance with raw features versus carefully engineered features (scaled continuous variables, one-hot encoded categories, interaction features, and PCA-reduced dimensions) on the same prediction task, documenting the performance difference
• Apply anomaly detection to a real-world domain such as financial transactions or network traffic, implementing both z-score statistical methods and an isolation forest, then comparing which approach catches more true anomalies with fewer false positives

Parent Note

Data science is where AI meets real-world decision-making. Ask your child to explain the four pillars: predictive modeling (forecasting outcomes), anomaly detection (finding what does not belong), clustering (discovering hidden groups), and feature engineering (transforming raw data into meaningful model inputs). Discuss how these techniques affect daily life -- from weather forecasts and fraud alerts to personalized recommendations. The principle that 'garbage features in produces garbage predictions out' is a lesson that applies far beyond data science. This lesson connects to careers in data science, financial analysis, epidemiology, business intelligence, and cybersecurity -- among the fastest-growing fields in the economy.

Lesson 5: Capstone: AI Solution Development

Objective

Students will design and implement a comprehensive AI solution addressing a real-world problem.

Key Concepts

• Problem identification and scoping
• Solution architecture design
• Implementation and testing
• Documentation and presentation

Learning Activities

• Identify a meaningful real-world problem where AI intervention provides genuine value -- distinguishing good AI problems (medical image screening at scale, real-time fraud detection, predictive maintenance) from poor AI problems (simple lookup tasks, problems with no available data, decisions requiring pure human judgment) -- and scope it with a measurable objective, honest constraint identification, and ethical boundaries
• Design and implement a complete AI solution architecture including the full system: data pipeline, preprocessing, model selection (CNN for classification, YOLO for detection, transformer for generation, regression for prediction), output layer, and evaluation loop -- using tools such as TensorFlow, PyTorch, scikit-learn, or Hugging Face -- starting with the simplest baseline that works and iterating to add complexity
• Test rigorously through unit testing of individual components and integration testing of the full pipeline, deliberately probe edge cases, gather user feedback, and produce complete portfolio-ready documentation including architecture overview, methodology section, and results analysis with README files and code comments that explain why, not just what

Resources

• TensorFlow and PyTorch Frameworks - Industry-standard deep learning libraries for building and training models across classification, detection, generation, and prediction tasks with extensive documentation and community support
• GitHub and Git Version Control - Platform for hosting project repositories, managing iterative development with version control, writing README documentation, and building a portfolio-ready codebase
• Jupyter Notebooks - Interactive development environment for prototyping AI solutions, documenting methodology alongside code, and creating reproducible data pipelines from data collection through model evaluation
• Google Slides or Canva Presentation Tools - Resources for creating clear, visually compelling project presentations that communicate technical AI work to both technical and non-technical audiences with concrete examples and narrative structure

Assessment

• Complete AI solution with full documentation, including a working system that addresses a genuine real-world problem, technical documentation covering architecture overview (what the system looks like and why), methodology (data, preprocessing, model selection, evaluation criteria), and results analysis (what the system achieved, where it fell short, and what would be improved)
• Project presentation and demonstration communicating the problem, solution, and impact to both technical and non-technical audiences -- explaining what the system does, why it matters, and what results it achieves without requiring the audience to understand the underlying architecture, supported by clear visuals and concrete examples

Extension: Capstone Excellence Lab

• Integrate techniques from multiple Grade 11 disciplines into a single capstone project -- for example, combining computer vision detection with NLP text generation to create a system that identifies objects and produces natural language descriptions, or combining data science clustering with predictive modeling for segmented forecasting
• Conduct a formal user testing session with at least three people outside the course, documenting where users struggle, what confuses them, and how their feedback drives specific improvements to the solution's interface, accuracy, or documentation
• Prepare two versions of your project presentation: one for a technical audience (covering architecture decisions, model evaluation metrics, and engineering trade-offs) and one for a general audience (focusing on the problem, the impact, and a clear demonstration) -- practicing the distinct skill of adapting technical communication to different audiences

Parent Note

This capstone is the culmination of your child's Grade 11 AI course. They are not just learning about AI -- they are identifying real problems, designing complete systems, writing working code, testing it, and documenting it for a portfolio. Ask them to walk you through their project: what problem they chose, why AI is the right approach, what architecture they designed, and what they learned from testing. The documentation and presentation skills practiced here are as valuable as the technical skills -- the ability to explain complex work clearly is essential in every professional field. This is engineering, not simulation, and it prepares them for Grade 12: AI Innovation and Leadership.

Lesson 1: AI Innovation and Entrepreneurship

Objective

Students will explore the intersection of AI technology and business innovation, learning to identify opportunities and develop AI-powered solutions.

Key Concepts

• AI startup ecosystem and trends
• Identifying market opportunities for AI
• Business model development for AI products
• Funding and resources for AI ventures

Learning Activities

• Analyze successful AI startups across all three ecosystem layers -- generative AI, vertical AI, and infrastructure -- evaluating their strategies, business models, and why they succeeded or failed in a competitive landscape that attracted over fifty billion dollars in venture capital in 2023 alone
• Develop a business concept for an AI-powered product, starting from pain point analysis (who is in pain, how big is the cost, will they pay), conducting customer validation with real potential users, and building a defensibility strategy that addresses the AI wrapper problem through proprietary data, domain expertise, workflow integration, or network effects
• Create and deliver a pitch presentation covering the complete entrepreneurial arc: problem identification, solution design, market opportunity, business model selection (SaaS, API-as-a-Service, freemium, enterprise licensing, or data monetization), competitive advantage, team composition, and funding ask -- modeled on a professional 10-to-15-slide pitch deck format

Resources

• Y Combinator Startup Library - Curated collection of essays and videos on building AI startups, including founder advice on customer validation, business model selection, and pitch preparation
• Crunchbase AI Startup Database - Real-time data on AI venture funding, startup valuations, and ecosystem trends across generative AI, vertical AI, and infrastructure layers
• Lean Canvas Template - One-page business model planning tool adapted for AI product development, covering problem-solution fit, unfair advantage, and revenue streams
• Pitch Deck Examples from AI Ventures - Annotated pitch decks from successful AI startups demonstrating how to present problem, solution, market size, business model, and funding ask

Assessment

• AI business concept with pitch presentation, demonstrating a validated pain point, defensible competitive advantage (not an API wrapper), a selected revenue model with unit economics rationale, and a clear funding strategy from bootstrapping through venture capital
• Market analysis and feasibility study documenting the three-layer ecosystem positioning of the proposed venture, competitive landscape analysis, customer validation evidence, and an honest assessment of the AI wrapper risk and defensibility strategy

Extension: AI Venture Lab

• Research a real AI startup that failed and conduct a post-mortem analysis identifying whether the failure was due to a cool-demo-without-a-viable-product problem, an AI wrapper vulnerability, poor unit economics, or insufficient customer validation
• Interview a local entrepreneur or business professional about how they identify market opportunities and validate ideas before investing resources, then compare their methodology to the pain point analysis framework from the lesson
• Develop a competitive landscape map for a specific vertical AI domain (healthcare, legal, agriculture, or finance), identifying existing players, gaps in the market, and opportunities for a new entrant with defensible advantages

Parent Note

This lesson marks the beginning of your child's capstone year -- the culmination of four years of AI Foundations. Ask them to explain the three layers of the AI startup ecosystem and the difference between a cool demo and a viable product. Discuss the AI wrapper problem together -- it applies to career decisions as well as business strategy. If your family has any entrepreneurial experience, share what you know about customer validation and business model thinking. This lesson connects directly to careers in product management, venture capital, startup founding, and innovation strategy across every industry.

Lesson 2: AI Ethics and Governance Leadership

Objective

Students will develop frameworks for ethical AI development and learn to lead responsible AI initiatives.

Key Concepts

• AI ethics frameworks and principles
• Bias detection and mitigation strategies
• Responsible AI development practices
• Governance and accountability structures

Learning Activities

• Develop an AI ethics framework for a specific organization by evaluating the IEEE Ethically Aligned Design, EU Ethics Guidelines for Trustworthy AI, and OECD AI Principles, identifying their five shared principles (transparency, fairness, accountability, privacy, beneficence), and operationalizing those principles into actionable development workflows and procurement policies
• Conduct bias audits on AI systems using the three-stage mitigation lifecycle: pre-processing (rebalancing training data through oversampling, undersampling, or synthetic data generation), in-processing (adding fairness constraints to objective functions through constrained optimization), and post-processing (threshold adjustment to equalize outcomes) -- measuring results with statistical parity, equalized odds, and calibration metrics using tools like IBM AI Fairness 360 and Google's What-If Tool
• Create comprehensive guidelines for responsible AI deployment incorporating the full development lifecycle: ethics by design before any code is written, algorithmic impact assessments before deployment, red teaming for adversarial stress-testing, diverse development teams to prevent homogeneous blind spots, and continuous monitoring post-deployment to detect drift and emerging unfairness

Resources

• IBM AI Fairness 360 - Open-source toolkit for measuring and mitigating bias in AI systems across pre-processing, in-processing, and post-processing stages with implementation of multiple fairness metrics
• Google What-If Tool - Interactive visualization tool for probing machine learning model behavior, exploring fairness metrics, and testing how changes to features and thresholds affect outcomes across demographic groups
• EU AI Act Framework and OECD AI Policy Observatory - Comprehensive regulatory approaches to AI governance, including risk-level classification systems and international comparative policy analysis adopted by over forty countries
• AI Now Institute Reports - Research on the social implications of artificial intelligence in government, policing, and public services, with documented case studies of algorithmic bias in hiring tools and healthcare algorithms

Assessment

• Comprehensive AI ethics framework document for a chosen organization, incorporating principles from IEEE, EU, and OECD frameworks, with specific operationalization plans for transparency, fairness, accountability, privacy, and beneficence -- including governance structures (internal ethics board, external third-party audits, regulatory compliance) and whistleblower protections
• Bias analysis and mitigation proposal demonstrating technical proficiency with the three-stage bias mitigation lifecycle, selection and justification of appropriate fairness metrics (statistical parity, equalized odds, or calibration), and a governance plan specifying layered accountability for data scientists, product managers, and executives

Extension: Ethics and Governance Leadership Lab

• Analyze a real-world case where AI caused documented harm -- such as biased hiring tools or healthcare algorithms that underestimated Black patient needs -- and design the governance structure that could have prevented it, specifying internal review, external audit, and regulatory oversight mechanisms
• Conduct a fairness audit of a publicly available AI system or dataset using IBM AI Fairness 360 or Google's What-If Tool, documenting which fairness metrics you chose, what disparities you found, and what mitigation strategy you would recommend
• Draft the charter for an AI ethics board at an organization of your choice, specifying the board's composition (engineers, ethicists, legal experts, community representatives), authority, review criteria for high-risk projects, and accountability mechanisms for when systems cause harm

Parent Note

This lesson addresses one of the most critical challenges in AI today: who is responsible when AI systems cause harm? Ask your child to explain the difference between the three bias mitigation approaches (pre-processing, in-processing, post-processing) and why choosing a fairness metric is itself an ethical decision. Discuss real cases like biased hiring algorithms or healthcare AI that directed resources away from Black patients. This lesson develops leadership skills applicable to any organization -- the ability to build accountability structures, lead responsible initiatives, and bridge the gap between principles and practice.

Lesson 3: Research and Development in AI

Objective

Students will explore current AI research frontiers and develop skills for contributing to AI advancement.

Key Concepts

• Current AI research directions
• Research methodology for AI
• Reading and evaluating AI papers
• Contributing to open-source AI projects

Learning Activities

• Review and present current AI research papers by navigating six active research frontiers -- foundation models and scaling laws, multimodal AI, AI alignment and safety, efficient and green AI, neuromorphic computing, and AI for scientific discovery -- selecting a paper from ArXiv or a major venue (NeurIPS, ICML, CVPR) and analyzing its structure, claims, evidence, and limitations
• Design a research proposal for an AI investigation using rigorous methodology: formulate a specific testable hypothesis, design experiments with controlled variables and baseline comparisons, plan ablation studies to measure each component's contribution, and specify reproducibility standards including published code, shared datasets, documented random seeds, and training conditions
• Contribute to an open-source AI project using the standard GitHub workflow -- fork a repository, create a branch, commit with clear messages, and open a pull request -- starting with the contribution ladder (documentation fixes, bug reports with reproducible steps, then bug fixes and small features) on projects like Hugging Face Transformers, TensorFlow, or scikit-learn

Resources

• ArXiv.org AI Preprint Server - The primary repository where over 180,000 AI research papers are published annually, searchable by topic across machine learning, computer vision, NLP, and AI safety categories
• Hugging Face, TensorFlow, and scikit-learn Contributor Guides - Structured onboarding documentation for open-source AI projects, including setup instructions, code style requirements, testing procedures, and issue labels for newcomers (good first issue, help wanted)
• Papers With Code - Research paper repository that links publications to their open-source implementations, benchmarks, and datasets, making it easier to evaluate claims and reproduce results
• AlphaFold Protein Structure Database - DeepMind's breakthrough AI for scientific discovery, demonstrating how AI research translates to real-world impact by predicting protein structures for nearly every known protein

Assessment

• Research proposal with literature review demonstrating understanding of a specific AI research frontier, a well-formed testable hypothesis, experimental design with baseline comparisons and planned ablation studies, reproducibility standards, and critical evaluation of at least three related papers using the claims-evidence-limitations framework
• Open-source contribution documentation showing the complete GitHub workflow (fork, branch, commit, pull request), the specific contribution made (documentation improvement, bug report, or code fix), maintainer feedback received, and a reflection on how the contribution ladder builds credibility and codebase understanding in the open-source AI community

Extension: AI Research and Open-Source Deep Dive

• Compare two competing AI research papers on the same topic and evaluate which makes stronger claims, applying the critical evaluation framework: are benchmarks established and fair, are ablation studies included, are baselines recent and relevant, and is code released for reproducibility?
• Explore efficient and green AI by researching how model distillation, quantization, or sparse architectures achieve strong performance with a fraction of the compute, and document the environmental impact -- noting that training a single large model can emit as much carbon as five cars over their lifetimes
• Make a second, more ambitious open-source contribution by moving up the contribution ladder from documentation to a bug fix or small feature, documenting the review process and what you learned about collaborative software development in global AI communities

Parent Note

This lesson introduces your child to the world of professional AI research and open-source development. Ask them to explain the difference between a preprint on ArXiv and a peer-reviewed paper at a conference like NeurIPS. Discuss what reproducibility means and why it matters -- a result that cannot be reproduced is, scientifically, a result that does not exist. If your child makes an open-source contribution, that is a genuine professional accomplishment worth celebrating. This lesson connects to careers in AI research, academic science, software engineering, and any field where evidence-based thinking and collaborative development are valued.

Lesson 4: AI Career Preparation

Objective

Students will prepare for AI-related careers through portfolio development, networking, and professional skill building.

Key Concepts

• AI career landscape and opportunities
• Portfolio development for AI roles
• Professional networking in AI
• Higher education pathways in AI

Learning Activities

• Build a comprehensive AI project portfolio by curating original projects (not just completed tutorials) with clean, documented code on GitHub, detailed README files explaining what was built, why, and what was learned, diverse project types spanning NLP, computer vision, data visualization, and other domains, and explanatory blog posts or write-ups that demonstrate technical communication skills -- distinguishing between a weak portfolio (generic tutorial reproductions) and a strong portfolio (original problem-solving with community engagement)
• Connect with AI professionals through intentional networking by optimizing a LinkedIn profile with a clear headline, technical skills, and portfolio links; joining AI-focused communities on Discord, Reddit r/MachineLearning, and Twitter/X; attending AI meetups, conferences, or hackathons with student pricing; and conducting at least one informational interview using specific questions like 'What does a typical day look like?' and 'What skills do you use most?' -- guided by the principle of giving before asking
• Research and apply to AI-related programs by evaluating five parallel education pathways -- traditional four-year CS or data science degrees, interdisciplinary programs combining AI with healthcare, law, or business, intensive bootcamps (three to six months), community college to university transfer pathways, and online certifications from Coursera, edX, or fast.ai -- then building a personalized career pathway plan with specific application targets, timelines, and scholarship research

Resources

• GitHub Portfolio Best Practices - Guides for structuring professional AI project repositories with clean README documentation, version control, and project diversity that hiring managers and admissions committees look for
• LinkedIn and AI Community Platforms - Professional networking resources including LinkedIn profile optimization for AI careers, Discord AI servers, Reddit r/MachineLearning, and Twitter/X AI communities where practitioners share research and opportunities
• Kaggle Competitions and Datasets - Platform for building portfolio pieces through data science competitions, contributing analyses, and demonstrating problem-solving ability with real-world datasets alongside a global community
• Coursera, edX, and fast.ai Online Programs - Structured online learning platforms offering AI and data science certifications at accessible price points, complementing traditional degree pathways and bootcamp alternatives

Assessment

• Professional AI portfolio published on GitHub featuring at least three original projects with clean documentation, diverse skill demonstration across multiple AI domains, explanatory write-ups communicating technical reasoning, and evidence of community engagement through Kaggle competitions or open-source contributions
• Career pathway plan with application materials including an analysis of the AI career landscape across technical, hybrid, and non-technical roles with salary ranges; a personalized education pathway selection with rationale; specific program application targets and timelines; scholarship research; and a networking strategy documenting online presence, community engagement, and informational interview plans

Extension: Career Launch Accelerator

• Conduct informational interviews with at least two AI professionals in different roles (one technical, one hybrid or non-technical) and write a comparative analysis of their career paths, daily responsibilities, and advice for newcomers entering the field
• Create a blog post or video walkthrough of your strongest portfolio project, explaining the problem you solved, the technical approach you took, and what you learned -- then share it with an AI community for feedback
• Research and compile a scholarship and funding guide for AI-related education, identifying at least five opportunities that match your circumstances and noting application deadlines, requirements, and strategies -- many AI scholarships go unclaimed because people do not know to look for them

Parent Note

This is one of the most immediately practical lessons in the entire program. Ask your child to show you their portfolio and explain the difference between a weak portfolio (tutorial reproductions) and a strong one (original projects with documentation). Discuss the career landscape together -- AI careers extend far beyond engineering into product management, ethics, policy, design, healthcare, and finance. You do not need a PhD for the majority of AI positions. Help your child with networking by sharing your own professional connections or discussing how informational interviews work. The decisions made in the next twelve months -- what they build, who they connect with, which programs they apply to -- will shape the beginning of their professional life.

Lesson 5: Senior Capstone: AI Leadership Project

Objective

Students will demonstrate AI leadership by completing a significant project that combines technical skills with real-world impact.

Key Concepts

• Project leadership and management
• Stakeholder engagement
• Impact measurement and documentation
• Knowledge transfer and mentorship

Learning Activities

• Lead a team in developing an impactful AI project by setting a clear vision, defining concrete milestones, delegating tasks based on team members' strengths, applying agile methodology (short iterative cycles of build, test, feedback, adjust), and responding to setbacks as sources of information rather than causes for panic -- making the critical transition from the individual Grade 11 capstone to team-based leadership where the job is no longer to do all the work but to ensure the right work gets done by the right people
• Engage with community stakeholders by identifying everyone who has a stake in the project's outcome, conducting user research through interviews, surveys, and observation to gather real requirements from real people, sharing early prototypes and progress before becoming too invested to change course, managing expectations honestly, and building trust through the principle of building WITH communities rather than FOR them
• Document and present project outcomes by defining success metrics at the beginning (not the end), measuring impact through both quantitative evidence (usage statistics, accuracy improvements, efficiency gains, error reduction, time saved) and qualitative evidence (user satisfaction, community feedback, behavioral changes), documenting not just WHAT was built but WHY it was built and WHAT IT CHANGED, and creating knowledge transfer materials (architecture decisions, setup guides, known issues, future roadmaps) written for the person who comes after you

Resources

• Agile Project Management Frameworks - Methodology guides for iterative development cycles including sprint planning, milestone tracking, task delegation, and retrospective analysis adapted for AI project leadership
• User Research and Stakeholder Engagement Toolkit - Interview templates, survey design guides, observation protocols, and community meeting frameworks for gathering authentic requirements from the people an AI project serves
• Impact Measurement Dashboard Templates - Frameworks for defining success metrics upfront and tracking both quantitative measures (usage, accuracy, efficiency) and qualitative measures (satisfaction, feedback, behavioral change) throughout a project lifecycle
• Knowledge Transfer and Documentation Standards - Templates for writing maintainer-focused documentation including architecture decision records, setup instructions, known issues, future roadmaps, and workshop guides that ensure a project's impact survives beyond the original team

Assessment

• Major AI leadership project with comprehensive documentation demonstrating the complete leadership arc: vision statement, milestone planning, stakeholder engagement evidence (interview notes, survey results, prototype feedback), quantitative and qualitative impact measurement, honest assessment of what worked and what did not, and knowledge transfer materials written for future maintainers including architecture decisions, setup guides, and a roadmap of what to build next
• Public presentation and community showcase where students present their project's complete story -- the problem, the approach, the evidence of impact, and the lessons learned -- to community members, families, and younger learners, demonstrating the ability to communicate technical work to diverse audiences and passing knowledge to the next generation of AI leaders

Extension: Legacy and Mentorship Initiative

• Create a workshop or recorded walkthrough for younger learners in the AI Foundations program, teaching a key concept or skill from your capstone project in age-appropriate terms and contributing to the knowledge transfer chain that makes the program stronger each year
• Conduct a formal project retrospective using agile methodology, documenting what went well, what could improve, and specific recommendations for future teams -- then share this retrospective publicly as a resource for other student-led AI projects
• Write a reflective essay connecting your capstone project to the full K-12 AI Foundations journey -- from learning what technology is in the earliest grades through building real systems in Grade 11 to leading a team in Grade 12 -- articulating how each stage prepared you for the next and what you will carry forward into your career

Parent Note

This is the final lesson of the entire AI Foundations program -- the culmination of thirteen grades and sixty-five lessons. Ask your child to explain the difference between building a project and leading one, and how the principle of building WITH communities rather than FOR them shaped their stakeholder engagement. Attend the public showcase if possible -- seeing your child present a leadership project with real-world impact is a powerful moment. Discuss their knowledge transfer materials: the documentation they wrote for future maintainers shows maturity and professional awareness. The skills demonstrated in this capstone -- vision-setting, team leadership, stakeholder engagement, impact measurement, and knowledge transfer -- are the foundation of leadership in any field, not just AI.

Lesson 1: Introduction to Digital Citizenship (6 min)

Learning Objectives

• The student will be able to identify and recognize Digi.
• The student will be able to identify Digi's purpose in helping students learn about Digital Citizenship.
• The student will be able to recognize the letters in the acronym T.H.I.N.K.
• The student will be able to identify types of technology (cell phones, computers, television).
• The student will be able to identify good citizenship characteristics.
• The student will be able to recognize the beginning of how the internet connects us to the world.

Vocabulary

Discussion Activities

• Have students draw types of technology.
• Have students go on a scavenger hunt throughout the classroom to find different types of technology.
• Make a list of some places to take a virtual field trip and choose one to take.
• Draw/color a picture of Digi.
• Write a story about what it means to be a good digital citizen.
• Role play following the rules of how to be a good digital citizen.
• Read different books about Digital Citizenship and talk about them as a class.

Lesson 2: "T" is for Truthful (7 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to understand all vocabulary terms.
• The student will be able to recognize what Truthful means.
• The student will be able to recite a chant for T.H.I.N.K.
• The student will be able to recognize what information is safe to use online.

Vocabulary

Discussion Activities

• Create a K.W.L. chart (What You Know, What You Want to Know, and What You Learned) about being Truthful.
• Make a class book about telling the truth. Draw and share a favorite part of the story.
• Role play how some things you hear might not actually be true, but made up. Have the teacher put random easy phrases into a hat and have students pick them out and read them.
• Make signs about Truth and put them up throughout the classroom.
• Role play Digi asking questions and differentiate between what is private and what is okay to share.
• Read books about being Truthful such as 'Ruthie and the (Not So) Teeny Tiny Lie'.
• Have the students color and cut out a Digital Citizenship puzzle and put it back together.

Lesson 3: "H" is for Helpful (5 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to recite T.H.I.N.K. and what "T" and "H" stand for.
• The student will be able to recall key vocabulary words such as: truthful, honest, private, safe, technology, Internet, and Digital Citizenship.
• The student will be able to recognize what helpful means and how it relates to Digital Citizenship.
• The student will be able to recognize when to ask for help from an adult.

Vocabulary

Discussion Activities

• Fill out a "How I Can Be Helpful" activity sheet either individually or as a class. When completed, hang the posters around your classroom.
• Brainstorm as a class some "helpful" projects that can be done for a special person OR a helpful project that the class can do for the school (picking up trash, making a "Helpful" bulletin board, etc.).
• Read a book about being Helpful.
• Use activities centered around being helpful including coloring pages, role playing activities, and ideas for a food drive.

Lesson 4: "I" is for Inspiring (6 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to recite (with help) T.H.I.N.K. and what the letters stand for.
• The student will be able to recall vocabulary from previous lessons.
• The student will be able to recognize the beginning of the definition of 'Inspiring' and how it relates to Digital Citizenship.

Vocabulary

Discussion Activities

• Sit in a circle and ask a student what they would love to do but are afraid to try. Ask others to say something inspiring to help them overcome their fears.
• Review the acronym T.H.I.N.K. with repetitive chants.
• Brainstorm some ways to inspire others. Make posters of ways to inspire others and hang them around your classroom or school campus.
• Read books to students that have inspiring messages.
• Read "The Dot" by Peter H. Reynolds. Have the students create their own mark by making pictures using dots.

Lesson 5: "N" is for Necessary (7 min)

Learning Objectives

• The student will be able to recite the acronym 'T.H.I.N.K.' and recall Truthful, Helpful, and Inspiring.
• The student will be able to understand and explain the definition of the word 'necessary'.
• The student will be able to recall vocabulary from previous modules.
• The student will be able to locate what a "just right" site is.
• The student will be able to identify and explain pop-ups.

Vocabulary

Discussion Activities

• Cut out a big red heart from construction paper. Read a book aloud about feelings. Every time someone says something mean, crinkle the heart. Discuss how even when someone says sorry, words can still hurt.
• Make a giant footprint and fill with positive words or sayings about T.H.I.N.K.
• Complete a wants versus needs activity using a large pocket chart.
• Read suggested books: "Lily Learns About Wants and Needs", "Those Shoes", "Charlie and Lola: I Really, Really Need Actual Ice Skates".
• Complete an activity about when it is necessary to unplug from technology.

Lesson 6: "K" is for Kind (6 min)

Learning Objectives

• The student will be able to recall T.H.I.N.K. and what the letters mean.
• The student will be able to identify what it means to be Kind.
• The student will be able to recall with help the vocabulary from previous lessons.
• The student will be able to examine the word 'cyberbullying'.

Vocabulary

Discussion Activities

• Brainstorm an act of kindness the class can do for someone. Have students write letters to soldiers, nurses, teachers, social workers, an ill schoolmate or kids who have been in the hospital.
• Create a Kindness Tree outside or inside of your classroom. Have the students add leaves to the tree when doing acts of kindness at home or at school.
• Role Play: You think that someone is being cruel or making fun of a student on the playground. What could happen next?
• Sit in a circle and have students take turns turning to the person next to them and say one kind thing about them.
• Read books about kindness.

Lesson 1: Introduction to Digital Citizenship (7 min)

Learning Objectives

• The student will be able to identify Digi and his purpose of helping students learn about Digital Citizenship.
• The student will be able to recite and recognize the letters in the acronym: T.H.I.N.K.
• The student will be able to recall and review various technologies.
• The student will be able to identify good citizenship characteristics.
• The student will be able to recognize that the internet connects us to the whole world.

Vocabulary

Discussion Activities

• Ask students to draw what they think technology is.
• Make a list of some places to take a virtual field trip to and choose one to take.
• Draw and color pictures of Digi.
• Write a story or draw a picture about what being a good digital citizen is.
• Have the students label the good citizen in an activity.
• Read a book or two about being a good citizen.
• Play 'Simon Says' as an activity to teach students to listen carefully to the rules.
• Do a Good Citizen Sort activity.

Lesson 2: Truthful (9 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to recall key vocabulary words such as: technology, digital, internet, and citizenship.
• The student will be able to recognize what truthful means.
• The student will be able to recite a chant for T.H.I.N.K.
• The student will be able to recognize what information is private and what information is safe to use online.

Vocabulary

Discussion Activities

• Discuss, draw pictures, or make a class book about telling the truth. Share a favorite part of the story or drawing.
• Read some books about being truthful.
• Role play how some things you hear might not actually be true, but make believe that they are.
• Make signs about being truthful and honest.
• Do a writing activity about telling the truth.
• Role play Digi asking questions and differentiate between what is private and what is okay to share or tell others.
• Have the students color and cut a Digital Citizenship puzzle out. Then, have them put it back together.

Lesson 3: Helpful (8 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to recite T.H.I.N.K. and what "T" and "H" stand for.
• The student will be able to recall key vocabulary words such as: truthful, honest, private, safe, technology, Internet, and Digital Citizenship.
• The student will be able to recognize what helpful means and how it relates to Digital Citizenship.
• The student will be able to recognize when to ask for help from an adult.

Vocabulary

Discussion Activities

• Fill out 'How I Can Be Helpful' activity sheet either individually or as a class. When completed, hang the posters around your classroom.
• Brainstorm as a class some 'helpful' projects that can be done for a special person OR a helpful project that the class can do for the school. Some examples can be: picking up trash, making a 'Helpful' bulletin board, etc.
• Read a book about being Helpful.
• Use activities centered around being helpful including coloring pages, role playing activities, and ideas for a food drive.

Lesson 4: Inspiring (7 min)

Learning Objectives

• The student will be able to identify Digi.
• The student will be able to recall T.H.I.N.K. and what the letters stand for.
• The student will be able to recall key vocabulary terms such as: truthful, honest, private, safe, technology, internet, and digital citizenship.
• The student will be able to recognize the definition of 'inspiring' and how it relates to digital citizenship.

Vocabulary

Discussion Activities

• Sit in a circle and ask a student what they would love to do, but are afraid to. Ask others to say something inspiring to help them overcome their fear. Take turns for all students.
• Review T.H.I.N.K. acronym and pick different songs or chants to remember it.
• Think of some way to inspire others. Make posters of ways to inspire others and hang them up around campus.
• Read some books that inspire your students.
• Read 'The Dot' by Peter H. Reynolds. Have the students create their own mark by making pictures using dots and write about their dot and why they made it the way they did.

Lesson 5: Necessary (7 min)

Learning Objectives

• The student will be able to recite the T.H.I.N.K. acronym.
• The student will be able to identify Digi.
• The student will be able to recall the meaning of truthful, helpful, and inspiring as they refer to Digital Citizenship.
• The student will be able to recognize what necessary means.
• The student will be able to recognize what a digital footprint is.
• The student will be able to locate what a 'just right' site is.
• The student will be able to identify and explain pop-ups.

Vocabulary

Discussion Activities

• Cut out a big red heart from construction paper. Read a book about feelings. Every time someone in the story says something mean, crinkle the heart a little bit. When the story is over, ask the children if they can smooth out the heart and make it like it was before the story. They will realize they cannot and even though someone said they were sorry after they said something mean, the words still hurt and cannot be erased.
• Make a digital footprint or print one and make it larger. Fill with positive words or sayings.
• Make a giant footprint and write/illustrate T.H.I.N.K. Have students add positive thoughts for online use.
• Complete a wants versus needs activity in your classroom using a large pocket chart.
• Read books: 'Lily Learns About Wants and Needs', 'Those Shoes', 'Charlie and Lola: I Really, Really Need Actual Ice Skates'.
• Complete an activity about when it is necessary to unplug from technology.
• Color, write and draw how to be safe online.

Lesson 6: Kind (10 min)

Learning Objectives

• The student will be able to recall T.H.I.N.K. and what the letters mean.
• The student will be able to identify what it means to be kind.
• The student will be able to recall vocabulary terms such as: truthful, honest, private, safe, technology, and Digital Citizenship.
• The student will be able to identify cyberbullying.

Vocabulary

Discussion Activities

• Brainstorm an act of kindness that the class can do for someone. Maybe write a letter or make cards for someone. Soldiers, nurses, teachers, social workers, or ill schoolmates are all good people to send letters to.
• Role play: You think that someone is being cruel by making fun of another student on the playground. What could happen next?
• Sit in a circle and have students take turns turning to the person next to them and say one kind thing about them, go around the circle until everyone has shared.
• Read some books about Kindness.
• Create a Kindness Tree outside or inside of your classroom. Have the students add leaves to the tree when doing acts of kindness at home or at school.

Lesson 1: Introduction to Digital Citizenship (7 min)

Learning Objectives

• The student will be able to identify Digi and his purpose of helping students learn about Digital Citizenship.
• The student will be able to recite the letters in the acronym T.H.I.N.K.
• The student will be able to recall and review various technologies such as: tablets, cell phones, laptops, kindles, and TVs.
• The student will be able to identify good Digital Citizenship characteristics.
• The student will be able to distinguish how the internet connects us to the rest of the world.
• The student will be able to develop an understanding of the meaning of digital reputation and digital footprint.

Vocabulary

Discussion Activities

• Students draw what they think technology looks like.
• Make a list of some places to take a virtual field trip.
• Draw/color pictures of Digi.
• Write a story or draw a picture about how a good Digital Citizen acts.

Lesson 2: Always be Truthful (6 min)

Learning Objectives

• The student will be able to recall vocabulary terms such as: social media, Digital Citizenship, and reputation.
• The student will be able to identify and discuss what it means to be truthful.
• The student will be able to recognize the characteristics of a trustworthy person.
• The student will be able to recognize what information is private and what information is safe to put online.

Vocabulary

Discussion Activities

• Role play how some things you hear might not actually be true.
• Make signs about being truthful.
• Role play Digi asking questions and differentiate between what is private and what is okay to tell.
• Discuss, draw pictures, or make a class book about telling the truth.

Lesson 3: Always Be Helpful (6 min)

Learning Objectives

• The student will be able to review T.H.I.N.K. and what "T" and "H" stand for.
• The student will be able to review the vocabulary: truthful, trustworthy, private, social media, reputation, and Digital Citizenship.
• The student will be able to recognize what helpful means and how it relates to Digital Citizenship.
• The student will be able to recognize when to ask for help from an adult.

Vocabulary

Discussion Activities

• Draw or color a picture of someone being helpful.
• Think of a 'helpful' project you can do for someone or do a helpful project for the school such as pick up trash or create a Helpful bulletin board.
• Pair up and take turns helping a partner with flashcards or a worksheet.

Lesson 4: Be an Inspiring Friend (6 min)

Learning Objectives

• The student will be able to identify Digital Citizenship Characteristics.
• The student will be able to recite T.H.I.N.K. and discuss what the letters stand for.
• The student will be able to review key vocabulary words such as: truthful, honest, private, Digital Citizenship, helpful, and hurtful.
• The student will be able to recognize the definition of 'inspiring' and how it relates to Digital Citizenship.

Vocabulary

Discussion Activities

• Using a cut out of a large capital letter 'I', fill it in with inspiring words.
• Write poems that inspire others to do their best.
• Start an Inspiring word chain and add to it throughout the year.
• Write a letter to a classmate or friend who inspires you to do your best.

Lesson 5: Only Do And Say What Is Necessary (7 min)

Learning Objectives

• The student will be able to recite the acronym T.H.I.N.K.
• The student will be able to review the meaning of: Truthful, Helpful, and Inspiring as they refer to Digital Citizenship.
• The student will be able to define the term 'necessary'.
• The student will be able to recognize the concept of a digital footprint.
• The student will be able to locate what a 'just right' site it.
• The student will be able to identify pop-ups and what their risks are.

Vocabulary

Discussion Activities

• Cut out a big red heart from construction paper. Read a book about feelings and every time someone in the story says something mean, crinkle the heart a little bit. When the story is over, ask the students if they can smooth out the heart and make it like it was before the story. They will see that it cannot be perfectly smoothed out. The lesson is that even if someone says they are sorry, the words still hurt and cannot be totally erased. 'Chrysanthemum' is a good book to read with this activity.
• Make a giant footprint and write the things that we want to remember to leave a good digital footprint. Somethings to consider might be: private information, thoughtful, inspiring, helpful, necessary, and always getting permission.
• Make a giant footprint with T.H.I.N.K. written or illustrated inside.
• Make a giant footprint and write the websites that you visit in one week. Reflect on these sites and how they will impact your digital footprint.

Lesson 6: Always Be Kind (7 min)

Learning Objectives

• The student will be able to review T.H.I.N.K. and what the letters mean.
• The student will be able to recognize what it means to be kind.
• The student will be able to review vocabulary terms such as: truthful, private, Digital Citizenship, helpful, and hurtful.
• The student will be able to define and discuss cyberbullying.
• The student will be able to describe how to stay safe when using technology.

Vocabulary

Discussion Activities

• Brainstorm an act of kindness the class can do for someone. Write a letter or make cards for soldiers, teachers, social workers, or a sick classmate.
• Role play: You think that somebody is being cruel by making fun of a kid on the playground. What could happen next?
• Sit in a circle and have students take turns turning to the person next to them and say one kind thing about them. Go around the circle until everyone has shared.

Lesson 1: Introduction to Digital Citizenship (4 min)

Learning Objectives

• The student will be able to define 'technology'.
• The student will be able to name several types of technology devices.
• The student will be able to define and discuss Digital Citizenship.
• The student will be able to discuss the importance of having a positive digital reputation.

Vocabulary

Discussion Activities

• Have students create individual posters of the acronym 'T.H.I.N.K.'
• Discuss the various types of technology. Have students make a list or draw different types of technology that can be found in their homes or classroom.
• Role play times when students were putting technology over their friend and family.

Lesson 2: Importance of Being Trustworthy (7 min)

Learning Objectives

• The student will be able to define what it means to be trustworthy as it relates to using technology.
• The student will be able to explain how sticking to a plan, parking your device, keeping promises, practicing self-control, and telling the truth helps Digital Citizens show they are trustworthy.
• The student will be able to discuss the consequences of breaking trust.
• The student will be able to recognize the benefits of being a trustworthy user of technology.

Vocabulary

Discussion Activities

• Have students create posters to hang around the school that advertises being trustworthy users of technology. Some ideas can be: sticking to a plan, keeping promises, practicing self-control, and telling the truth.
• Brainstorm what the word 'trustworthy' means and looks like. Have students use a web graphic organizer to list adjectives that describe a trustworthy person.
• Have students write a play about someone who loses the trust of friends or family and have them present it to the class.

Lesson 3: Kindness-Empathy-Respect (7 min)

Learning Objectives

• The student will be able to explain what it means to be kind online.
• The student will be able to give examples of kindness online and offline.
• The student will be able to recognize the effects of online behavior both good and bad.
• The student will be able to describe how to communicate online by showing respect and empathy.
• The student will be able to explain how to handle online disagreements appropriately.

Vocabulary

Discussion Activities

• Write notes of appreciation to the cafeteria workers, janitors, or other staff members who do not normally receive recognition.
• Ask your principal if each student from your class/program can read a quote or story about kindness each morning over the intercom.
• Play '10 Good Things': say ten good things about someone.
• Research 'what is a digital footprint' and write or type a short report about what you find.

Lesson 4: Think Before You Post (7 min)

Learning Objectives

• The student will be able to define and discuss responsible posting.
• The student will be able to explain the consequences of irresponsible posting.
• The student will be able to define and discuss cyberbullying.
• The student will be able to explain how cyberbullying affects the victims.
• The student will be able to list strategies for making sure that you are responsible when communicating online.
• The student will be able to identify why adults create rules for using technology.
• The student will be able to explain how Digital Citizens practice ethical behavior.

Vocabulary

Discussion Activities

• Make a poster of a digital footprint and present it to classmates.
• Have students make a list of things they would like to find out about themselves on the internet in the future.
• Watch and discuss videos about digital reputation.
• Create a Venn Diagram comparing and contrasting what it means to be kind online versus offline.

Lesson 5: Protect Your Online Reputation (7 min)

Learning Objectives

• The student will be able to define and discuss the meaning of 'digital reputation'.
• The student will be able to explain how your behaviors online and offline contribute to your digital reputation.
• The student will be able to discuss why your digital reputation matters.
• The student will be able to identify ways to protect your digital reputation.
• The student will be able to discuss the importance of protecting the digital reputation of others.
• The student will be able to describe the actions you should take when your digital reputation of that of someone else has been compromised.

Vocabulary

Discussion Activities

• Make a circle of 'trust'. Pass a beach ball around the circle. Lead a discussion about trusting each other to get the beach ball around the circle. As a class or team, we are all relying on each other. When one of us drops the ball (or cannot be trusted), we cannot work well together. Remove students one at a time. How does it affect the group if the others let the class or team down with untrustworthy behaviors?
• Have students interview adults in their life. Ask the adult to explain different situations in which trustworthiness proved to be invaluable.
• Do a Trust Walk: Place students in pairs. Have one student lead his/her blindfolded partner through an obstacle course using only words. Discuss how trust between the two played a part in the success or failure of the task.
• In groups, make a poster of what good Digital Citizenship looks like.
• Develop a classroom Digital Citizen agreement.

Lesson 1: Introduction to Digital Citizenship (3 min)

Learning Objectives

• The student will be able to define and discuss technology.
• The student will be able to identify several types of technology devices.
• The student will be able to define and discuss Digital Citizenship.
• The student will be able to discuss the importance of a positive Digital Reputation.

Vocabulary

Discussion Activities

• In groups, make a poster of what good Digital Citizenship looks like.
• Develop a classroom Digital Citizen agreement.
• Design a Digital Citizen poster for home and classroom use.
• Why is it important to be a good Digital Citizen?
• Why should you only communicate online with family and friends that you know?
• How do your choices online impact you offline?
• Can people you associate with online impact your life offline?

Lesson 2: Trustworthiness (7 min)

Learning Objectives

• The student will be able to define what it means to be trustworthy as it relates to using technology.
• The student will be able to describe the attributes of a person who is trustworthy with technology.
• The student will be able to explain how to show your family, friends, and teachers that you are trustworthy as it pertains to using technology.
• The student will be able to recognize the consequences of breaking trust.

Vocabulary

Discussion Activities

• Create posters to hang around the school that advertises being trustworthy users of technology.
• Write a play or short skit about who loses the trust of friends or family. Have the students present it to the class.
• Have students interview adults in their life. Ask the adult to explain different situations in which trustworthiness proved to be valuable.
• Discuss the word 'trustworthy' and what it means to you.
• Discuss the importance of telling the truth and keeping promises.
• Discuss how we can learn and grow from our mistakes.

Lesson 3: Kindness (11 min)

Learning Objectives

• The student will be able to define kindness as it pertains to technology use.
• The student will be able to give examples of kindness online and offline.
• The student will be able to express examples of positive and negative language online and offline.
• The student will be able to describe how to communicate online by showing respect and empathy.
• The student will be able to explain how to handle disagreements appropriately.
• The student will be able to define cyberbullying and explain how to handle a cyberbully.

Vocabulary

Discussion Activities

• Write notes of appreciation to school workers who do not normally get recognition. This could be cafeteria workers, parent volunteers, or janitors.
• Ask your principal if each student from your class can read a quote or story about kindness each morning over the intercom.
• Teams or pairs complete a Venn Diagram comparing and contrasting what it means to be kind online versus offline. After completion, hold discussions on how there are many similarities.
• Discuss kindness as it pertains to online behavior.
• Discuss how to handle cyberbullying.
• Share ideas for how to show respect and empathy.
• Discuss what things could be causing someone to choose to cyberbully.

Lesson 4: Responsible Posting (9 min)

Learning Objectives

• The student will be able to define responsible posting.
• The student will be able to define irresponsible posting.
• The student will be able to give examples of responsible and irresponsible posting.
• The student will be able to recognize why it is up to everyone to make sure that students are safe online.
• The student will be able to discuss the importance of privacy settings.
• The student will be able to recognize that Digital Citizen skills include safe, smart, and ethical use of technology.

Vocabulary

Discussion Activities

• Work in groups or pairs to discuss cyberbullying and describe/illustrate strategies to deal with such a situation.
• Make a poster illustrating what information is okay/not okay to post online.
• Role play the consequences of inappropriate use of a personal digital device.
• Discuss the importance of responsible posting.
• Share ideas about what is responsible versus irresponsible posting.
• Discuss what cyber security means and how it is used to keep people safe.
• Share examples of good etiquette on and offline.

Lesson 5: Digital Reputation (8 min)

Learning Objectives

• The student will be able to define 'digital reputation'.
• The student will be able to recognize ways to protect your digital reputation.
• The student will be able to discuss the importance of protecting the digital reputation of others.
• The student will be able to describe the actions you should take when your digital reputation, or that of someone else, has been compromised.
• The student will be able to explain the potential consequences of giving in to peer pressure and discuss how to avoid it.

Vocabulary

Discussion Activities

• Research 'What is a digital footprint?' Write or type a short report about findings.
• Make a poster of a digital footprint and present it to classmates.
• Have students make a list of things they would like to find out about themselves on the internet in the future.
• Discuss the importance of a positive digital reputation.
• Share how peer pressure has impacted your choices online and offline.
• Brainstorm ways you can help create a positive digital footprint.

Lesson 1: Learn More About How To Be A Responsible Digital Citizen (6 min)

Learning Objectives

• The student will be able to describe skills and have a better understanding of how to be a responsible Digital Citizen.
• The student will be able to name several types of technology devices.
• The student will be able to define 'app' and how apps are used.
• The student will be able to recognize how screen time impacts the brain.
• The student will be able to articulate responsible online behavior.

Vocabulary

Discussion Activities

• In groups, make a poster of what good Digital Citizenship looks like from their point of view.
• Suggest that students practice emailing positive messages back and forth to their teachers or other important adults in their life.
• Develop a classroom Digital Citizen agreement.
• Draw/color pictures of Digi.
• Read a book or two about being a good citizen.

Lesson 2: Digital Citizens Make Good Choices (8 min)

Learning Objectives

• The student will be able to explain how trustworthiness relates to Digital Citizenship.
• The student will be able to describe how to be trustworthy with technology.
• The student will be able to explain how to be trustworthy user of technology.
• The student will be able to recognize the consequences of breaking trust.
• The student will be able to explain why rules regarding technology usage are put into place.

Vocabulary

Discussion Activities

• Have students create posters to display around school that advertise being trustworthy users of technology.
• Brainstorm what the word trustworthy means. Have students use a web graphic organizer to list adjectives that describe a trustworthy person.
• Have students write a play about someone who loses the trust of friends or family and have them present their play to the class.
• Write notes of appreciation to the cafeteria workers, janitors, or other staff members who do not normally receive recognition.
• Have students interview adults in their life. Ask the adult to explain the different situations in which trustworthiness proved to be invaluable.

Lesson 3: Kindness On and Offline (8 min)

Learning Objectives

• The student will be able to define kindness as it pertains to technology.
• The student will be able to explain how to avoid acting out impulsively with technology.
• The student will be able to explain how stepping away from technology can help you to manage your emotions.
• The student will be able to discuss the consequences of not practicing kindness online.
• The student will be able to define and give examples of cyberbullying.
• The student will be able to explain how to handle a cyberbully.

Vocabulary

Discussion Activities

• Have students make a list of things that they would like to find out about themselves on the internet in the future.
• Teams or pairs complete a Venn Diagram comparing and contrasting what it means to be kind online versus offline. After completion, hold a discussion on how there are many similarities.
• Have each student sit across from each other with their backs to each other. Have the students talk about their day while the other student tries to guess their emotions. Was it easy or hard to guess the person's emotions without seeing their faces?
• Write a safety plan for what to do if a student is experiencing cyberbullying. Identify yourself and at least one additional adult to reach out to if they need help or guidance.

Lesson 4: Be Responsible When Posting (6 min)

Learning Objectives

• The student will be able to define and discuss responsible posting.
• The student will be able to explain the importance of responsible posting.
• The student will be able to describe the consequences of irresponsible posting.
• The student will be able to list ways to be safe from online predators.
• The student will be able to discuss the importance of privacy settings.
• The student will be able to explain the dangers of oversharing.
• The student will be able to determine ways to stay safe online.

Vocabulary

Discussion Activities

• Have students interview adults in their life. Ask the adult to explain different situations in which responsible posting proved to be invaluable.
• Discuss with your students why responsible posting is such an important part of Digital Citizenship. The world wide web provides us with many chances to interact with people from around the world. Digital Citizens recognize that their online behaviors leave a digital footprint.
• Have students draw what they would look like as a star of a video game and let them choose any characteristics they would like, regardless of the validity of it. Once it is complete, talk about what attributes mimic their own and whether it is a true representation of themselves or just a character they imagined. Relate this back to how another person could present themselves in any manner online.
• Sit down with your students and verbally talk through an online conversation. Be the person that is trying to find out information about them and help them talk through responses so that they will be prepared if they are in that type of online situation.
• Read Digital Citizenship Passages and answer the questions.

Lesson 5: Protect Your Digital Reputation (6 min)

Learning Objectives

• The student will be able to define and discuss digital reputations.
• The student will be able to explain ways to protect their digital reputation.
• The student will be able to discuss the importance of protecting the digital reputation of others.
• The student will be able to describe the actions you should take when your digital reputation or that of someone else has been compromised.
• The student will be able to relate their online behavior today and future consequences and make a connection between them.
• The student will be able to explain how Digital Citizens handle peer pressure.

Vocabulary

Discussion Activities

• Develop a classroom Digital Citizen agreement.
• Discuss why it is important to protect your digital reputation.
• Watch and discuss videos about digital reputation.
• In groups, make a poster of what good Digital Citizenship looks like.
• Design a digital logo that represents each person as an individual and then as a class; it could be a drawing, symbol, or even a statement. Make it the trademark of your digital reputation so that you have something unique to represent each of the students without having to give out personal information like a name.
• Organize a digital gathering with friends or as a school. Allow for time to play games or find out new information online and also time to teach someone else what you have learned about technology.
• Play Digital Citizenship Bingo.

Lesson 1: Introduction to Digital Citizenship (5 min)

Learning Objectives

• The student will be able to define the term 'technology'.
• The student will be able to name several types of technology devices.
• The student will be able to define 'Digital Citizenship'.
• The student will be able to discuss the importance of a positive Digital Reputation.

Vocabulary

Discussion Activities

• What does technology mean to you?
• What are some ways in which people use or misuse technology?
• Discuss a variety of apps available today--what they are, what their purpose is and what security features they have, if any.
• How important is a digital reputation?
• What is a digital footprint? Where/how does it start, who controls it, what are the long-term implications for a positive/negative digital reputation?
• What ways does a digital footprint relate to predators?
• Go through your classroom and school and determine how many pieces of technology you are. Identifying them will help reinforce what technology is.
• Choose one application that you use regularly and research what it does for the user and what information it gathers. This information can usually be found in the terms and conditions.
• Create a Digital footprint poster with your class.

Lesson 2: Trustworthiness (3 min)

Learning Objectives

• The student will be able to explain how trustworthiness relates to Digital Citizenship.
• The student will be able to describe strategies for showing that they are trustworthy with technology.
• The student will be able to explain how to be a trustworthy user of technology.
• The student will be able to recognize the consequences of gaming becoming more important than school.
• The student will be able to explain why rules regarding technology usage are put into place.

Vocabulary

Discussion Activities

• Have students create posters to hang around the school that advertise being trustworthy users of technology.
• Brainstorm the word trustworthy. Have students use a web graphic organizer to list adjectives that describe a trustworthy person.
• Have students write a play about someone who loses the trust of friends or family and have them present to the class.
• Ask your principal if each student from your class/program can read a quote or story about kindness each morning over the intercom.
• Make a poster of what it is like growing up in the digital age.
• Have students make a list of things they would like to find out about themselves on the internet in the future.

Lesson 3: Cyberbullying (6 min)

Learning Objectives

• The student will be able to define and give examples of cyberbullying.
• The student will be able to recognize how cyberbullying can impact the individual, school, friends, and family.
• The student will be able to identify cyberbullying by proxy.
• The student will be able to discuss common forms of cyberbullying.

Vocabulary

Discussion Activities

• Role play scenarios of cyberbullying with prewritten scripts.
• With a group or individually, illustrate what cyberbullying looks like to you or possibly at your school.
• Go on a Cyberbullying Flipgrid Hunt.
• What are some common forms of cyberbullying?
• How does cyberbullying relate to or impact a digital reputation?
• What does cyberbullying have to do with a digital footprint?
• Discuss how or why law enforcement may become involved in cases of cyberbullying with a Law Enforcement officer.
• Bring in your Principal to talk about how they view Social Media accounts before hiring someone.
• Share if you have been cyberbullied or have cyberbullied before. Students can share responses by: emailing you their responses or make an anonymous box for them to submit written responses to.

Lesson 4: Technology and The Brain (7 min)

Learning Objectives

• The student will be able to understand the main functions of the various parts of the brain.
• The student will be able to list the parts of the brain.
• The student will be able to name some emotions that certain parts of the brain control.
• The student will be able to discuss how technology impacts the brain.
• The student will be able to discuss how too much screen time impacts the brain.
• The student will be able to recognize the difference between gray and white brain matter.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize what you learned about Technology and the Brain.
• Be honest about your daily use of screen time.
• Make a list of devices you use and how much time you spend on each device.
• Discuss how to manage or limit screen time.
• Discuss the benefits of limiting screen time.
• Suggest holding family meetings to discuss screen time.
• Make a poster of family activities that do not include screen time.
• Illustrate ways to be creative and use your imagination and discuss why this is beneficial for you.
• What are the positives of screen time in moderation?

Lesson 5: Gaming (5 min)

Learning Objectives

• The student will be able to define and give examples of gaming.
• The student will be able to recognize how gaming can impact school, friends, and family.
• The student will be able to recognize the difference between preoccupation and moderation.
• The student will be able to identify ways to manage gaming habits.
• The student will be able to discuss the positive and negative impacts of online gaming.

Vocabulary

Discussion Activities

• Make a skit about what you learned about Gaming.
• What is the impact that gaming might have on self, school, and family?
• How might online gaming impact digital reputation?
• Make a newsletter on time management when it comes to gaming and the pros/cons.
• Research and discuss how online gaming might positively or negatively impact the brain.

Lesson 1: Introduction to Digital Citizenship (2 min)

Learning Objectives

• The student will be able to identify and review appropriate use of technology.
• The student will be able to recognize how social media can impact college and future employment opportunities.
• The student will be able to describe and discuss positive versus negative digital footprints.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the opening story for this lesson.
• What is technology?
• What are some ways in which people use/misuse technology?
• Discuss a variety of apps available today (what are they, what are their purposes and security features).
• How important is a digital reputation?
• What is a digital footprint? Where/how does it start, who controls it, what are the long-term implications for a positive/negative digital reputation?
• What does a digital footprint have to do with predators?

Lesson 2: Cyberbullying (11 min)

Learning Objectives

• The student will be able to define and give examples of cyberbullying.
• The student will be able to recognize how cyberbullying can impact school, friends, and family.
• The student will be able to relate legal terms that are associated with cyberbullying.
• The student will be able to discuss common forms of cyberbullying.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the opening story for this lesson.
• What is Cyberbullying?
• Illustrate what cyberbullying looks like in terms of being repetitive, intense, hurtful, and purposefully damaging.
• What are some common forms of cyberbullying?
• How does cyberbullying relate to or impact someone's digital reputation.
• What does cyberbullying have to do with a digital footprint?
• Discuss how or why law enforcement may become involved in cases of cyberbullying?
• How could have Hope's suicide been prevented?

Lesson 3: Inappropriate Posting (8 min)

Learning Objectives

• The student will be able to define and give examples of inappropriate posting.
• The student will be able to recognize how sexting can impact school, friends, and family.
• The student will be able to relate legal terms and implications associated with sexting.
• The student will be able to recognize that sexting is a crime.
• The student will be to discuss how sexting can be avoided and or reported.

Vocabulary

Discussion Activities

• Write a paragraph or two summarizing key points of Inappropriate Posting found in this lesson. After the writing is complete, discuss as a whole class or in small groups.
• Define inappropriate posting.
• What are some common forms of sexting?
• How are criminals able to control information found online?
• How do inappropriate postings relate to or impact a digital reputation?
• Discuss how or why law enforcement may become involved in cases of sexting.
• How can inappropriate postings be avoided and/or reported?

Lesson 4: Digital Cheating (5 min)

Learning Objectives

• The student will be able to understand the difference between cheating and digital cheating.
• The student will be able to define and give examples of digital cheating.
• The student will be able to recognize how cheating/digital cheating can impact school, friends, and family.
• The student will be able to recognize how cheating/digital cheating can impact future college and employment opportunities.
• The student will be able to discuss how cheating/digital cheating can be avoided and/or reported.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the opening story for this lesson.
• What is digital cheating?
• How is digital cheating different from other forms of cheating?
• Illustrate what digital cheating looks like in terms of how it is accomplished.
• How does cheating/digital cheating relate to or impact a digital reputation?
• What does cheating/digital cheating have to do with a digital footprint?
• Discuss the school's responsibility for reporting cheating/digital cheating.
• How could Samantha have avoided expulsion and loss of her senior year in high school?

Lesson 5: Digital Reputation (12 min)

Learning Objectives

• The student will be able to recognize the importance of a positive digital reputation.
• The student will be able to define and give examples of positive versus negative digital reputations.
• The student will be able to recognize how a positive digital reputation can impact friends, family, and self.
• The student will be able to review their digital reputations online.
• The student will be able to identify how internet searches become part of a digital reputation.
• The student will be able to discuss how colleges and employers check digital reputations when considering applicants for admission or a job role.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the opening story for this lesson.
• What is a digital reputation?
• How is your digital history created?
• Why is a positive digital reputation important in relation to future college and employment opportunities?
• How can an individual check on their digital reputation?
• Why is it important to regularly review social media accounts?
• How could Emily and her friends have avoided being labeled as mean girls?
• How can LinkedIn be helpful to high school students?

Lesson 1: Introduction to Digital Citizenship (2 min)

Learning Objectives

• The student will be able to recognize why Digital Citizen Academy was formed.
• The student will be able to defend why it is important to become part of the solution in the digital world.
• The student will be able to recognize that they have a voice with respect to their digital footprint and reputation.

Vocabulary

Discussion Activities

• What are the biggest concerns you have with your privacy?
• How can you improve your security online given the apps you are choosing to use?
• What kind of activities do you do offline to balance your online use?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 2: Cyberbullying (4 min)

Learning Objectives

• The student will be able to define and understand cyberbullying.
• The student will be able to recognize signs of someone being cyberbullied.
• The student will be able to identify ways in which to stand up for a victim.
• The student will be able to recognize when to seek the help of an adult.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize "Ryan's Story".
• What is cyberbullying?
• Illustrate what cyberbullying looks like in terms of being repetitive, intense, hurtful, and purposefully damaging.
• What are some common forms of cyberbullying?
• How does cyberbullying relate to or impact a digital reputation?
• What does cyberbullying have to do with a digital footprint?
• Discuss how or why law enforcement may become involved in cases of cyberbullying.

Lesson 3: Gaming (5 min)

Learning Objectives

• The student will be able to define and give examples of gaming.
• The student will be able to recognize how gaming can impact school, family, and friends.
• The student will be able to distinguish between different types of gaming.
• The student will be able to identify ways to manage their gaming habit.
• The student will be able to recognize the importance of telling the truth.

Vocabulary

Discussion Activities

• Verbally or in writing, have students summarize what they learned about gaming.
• Ask students if, before watching the video, they were aware of the impact gaming might have on self, school and family.
• Discuss how to manage time spent on online gaming.
• Discuss how online gaming might impact an individual's digital reputation.
• Discuss the pros and cons of online gaming.
• Research and discuss how online gaming might positively or negatively impact the brain.

Lesson 4: Hacking (6 min)

Learning Objectives

• The student will be able to define and give examples of hacking.
• The student will be able to recognize how hacking can impact school, family, and friends.
• The student will be able to recognize legal terms and implications associated with hacking.
• The student will be able to research, write, and verbalize how hacking is a crime.
• The student will be able to discuss how and why hacking can and should be reported.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize what you learned about Digital Reputation.
• What is hacking?
• Discuss the legal impact of hacking.
• Discuss how hacking can negatively impact future education and employment opportunities.
• Expand your discussion of the following definition of hacking: In computer networking, hacking is any technical effort to manipulate the normal behavior of network connections and connected systems.
• Research incidents of hacking and determine similarities and differences.

Lesson 5: Digital Reputation (4 min)

Learning Objectives

• The student will be able to define and understand what digital reputation means.
• The student will be able to recognize the impact of a positive versus negative digital reputation.
• The student will be able to identify ways in which to manage their own digital reputation.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize what you learned about Digital Reputation.
• Are students aware of their digital reputation?
• Do they understand how to create a positive digital image?
• Do they understand how to manage their online digital reputation?
• Can they identify who might be interested in their digital reputation?
• Do students understand the short/long term impact of a positive versus negative digital reputation?

Lesson 1: Your Digital Footprint & Digital Permanence (7 min)

Learning Objectives

• The student will be able to define digital footprint and digital permanence and distinguish between active and passive footprints.
• The student will be able to analyze how everyday online actions accumulate into a lasting, searchable record.
• The student will be able to evaluate a real-world scenario in which a digital footprint influenced a consequential decision.
• The student will be able to apply an audit-and-adjust strategy to take ownership of their own digital footprint.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the difference between an active and a passive digital footprint.
• Search your own name in a search engine. What did you find, and what surprised you?
• Discuss how a photo posted at fifteen could affect you at twenty-five or thirty-five.
• Why does the 'delete' button create a false sense of safety?
• How might a college admissions officer or employer use your digital footprint?
• What is one step from the footprint audit you plan to take this week, and why?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 2: Building a Positive Digital Reputation (6 min)

Learning Objectives

• The student will be able to differentiate between a digital footprint and a digital reputation.
• The student will be able to explain how consistency, contribution, and credibility shape a positive online reputation.
• The student will be able to construct intentional online contributions that reflect their values and goals.
• The student will be able to evaluate the long-term opportunities a strong digital reputation can unlock.

Vocabulary

Discussion Activities

• Verbally or in writing, explain the difference between your digital footprint and your digital reputation.
• What are the three pillars of a positive digital reputation, and what does each mean?
• Name three words you want your digital reputation to communicate about you.
• Discuss a real or hypothetical example of someone whose online presence opened a door for them.
• How is a personal brand similar to a company's brand?
• What is one specific contribution you could make online this week to reflect your values?

Lesson 3: Privacy & Protecting Your Personal Data (6 min)

Learning Objectives

• The student will be able to define personally identifiable information (PII) and classify which data types are most sensitive.
• The student will be able to explain the data-for-service exchange behind free apps and platforms.
• The student will be able to analyze common threats to personal data, including phishing and oversharing.
• The student will be able to apply concrete data-protection strategies, including strong authentication and privacy-setting audits.

Vocabulary

Discussion Activities

• Verbally or in writing, define personally identifiable information (PII) and give three examples.
• How can small, harmless pieces of data be aggregated into a revealing profile?
• Discuss the phrase 'If it's free, you might be the product.' Do you agree?
• What are the warning signs of a phishing message?
• Name three habits that protect the majority of your personal data.
• Review the app permissions on your device — which could you revoke without losing value?
• Have you turned on two-factor authentication on your most important accounts? Why or why not?

Lesson 4: Healthy Online Relationships & Boundaries (7 min)

Learning Objectives

• The student will be able to identify the characteristics of healthy versus unhealthy online relationships.
• The student will be able to define digital boundaries and explain why consent applies to online interactions.
• The student will be able to recognize warning signs of manipulation, pressure, and unsafe online contact.
• The student will be able to apply strategies for setting boundaries and responding to boundary violations.

Vocabulary

Discussion Activities

• Verbally or in writing, list the signs of a healthy versus an unhealthy online relationship.
• Discuss the idea that 'a healthy relationship expands your world, while an unhealthy one shrinks it.'
• What is a digital boundary, and why don't you owe anyone an explanation for it?
• How does consent apply to posting a friend's photo or sharing a private conversation?
• Identify the warning signs of manipulation, including love-bombing and demands for secrecy.
• Name one personal digital boundary you will set, and one trusted adult you could turn to.

Lesson 5: Cyberbullying & Becoming an Upstander (7 min)

Learning Objectives

• The student will be able to define cyberbullying and distinguish it from ordinary conflict or disagreement.
• The student will be able to explain the bystander effect and the difference between a bystander and an upstander.
• The student will be able to apply concrete upstander strategies to safely intervene and support targets.
• The student will be able to evaluate their own responsibility in shaping a positive online community.

Vocabulary

Discussion Activities

• Verbally or in writing, define cyberbullying and explain how it differs from ordinary conflict.
• Why is cyberbullying uniquely damaging compared to traditional bullying?
• Explain the bystander effect and how it is 'supercharged' online.
• What is the difference between a bystander and an upstander?
• Walk through the 4 R's — Recognize, Refuse, Reach out, Report — with a hypothetical scenario.
• Why is reporting harm an act of courage rather than 'snitching'?
• Commit to one upstander act you will take this week.

Lesson 1: Technology & the Teen Brain (8 min)

Learning Objectives

• The student will be able to explain how the adolescent prefrontal cortex and limbic system differ in developmental timing and why this matters for technology use.
• The student will be able to analyze the role of dopamine in reward-driven digital behaviors such as notifications, streaks, and infinite scroll.
• The student will be able to evaluate specific persuasive design techniques used by apps to capture adolescent attention.
• The student will be able to distinguish between technology use that supports growth and technology use that hijacks the brain's reward system.

Vocabulary

Discussion Activities

• In your own words, explain the difference between the limbic system (accelerator) and the prefrontal cortex (brakes), and why the timing gap matters for teenagers.
• Identify a persuasive-design feature you encounter every day (badges, autoplay, infinite scroll, streaks) and describe how it affects your behavior.
• Why does an unpredictable, variable reward keep you scrolling more than a guaranteed one? Give a real example.
• Debate: Is it fair for companies to use knowledge of the teen brain to design their apps? Argue both sides.
• Try the challenge — turn off one persuasive-design feature for a week and journal what changed.
• Discuss: What does it mean to be 'in control' of your technology rather than a target of it?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 2: Social Media & Mental Health (7 min)

Learning Objectives

• The student will be able to describe documented associations between heavy social media use and adolescent wellbeing, including sleep, mood, and social connection.
• The student will be able to differentiate between correlation and causation when interpreting claims about social media and mental health.
• The student will be able to analyze how specific features of social media can affect mood, comparison, and sleep.
• The student will be able to identify healthy, help-seeking strategies and know when and how to reach out for support.

Vocabulary

Discussion Activities

• Explain the difference between correlation and causation using your own example, then apply it to a headline about teens and social media.
• Why is protecting sleep considered one of the most powerful digital habits for mental health? Trace the chain of effects.
• Discuss how a 'highlight reel' can affect the way you feel, even when you know the post isn't the whole story.
• Try the 'notice' experiment: rate your mood before and after a scroll session for a few days and discuss what you found.
• Brainstorm: What are healthy ways to 'curate your feed like a garden'? Which accounts lift you up, and which don't?
• Discuss when and how to reach out for support, and identify the trusted adults available at school and at home.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 3: Technology Addiction & Finding Digital Balance (7 min)

Learning Objectives

• The student will be able to define problematic or compulsive technology use and distinguish it from ordinary heavy use.
• The student will be able to explain why digital products are intentionally engineered to be habit-forming.
• The student will be able to apply evidence-based strategies — friction, substitution, and boundaries — to build healthier technology habits.
• The student will be able to evaluate their own technology patterns without self-judgment and choose one realistic change.

Vocabulary

Discussion Activities

• Explain why problematic use is about control, cost, and coping rather than the number of hours alone.
• Why is 'just use more willpower' an unfair and inaccurate way to think about putting down your phone?
• Choose one of the three strategies (friction, substitution, boundaries) and design a specific change you could make this week.
• Discuss the 'spectrum, not a switch' idea. How might where someone sits on the spectrum change from week to week?
• Try the challenge — pick one friction fix and keep it for seven days, then report back on how it went.
• Brainstorm substitutions: what healthier activities could meet the same needs (boredom, stress, loneliness) that scrolling meets?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 4: Comparison, Anxiety & Self-Image Online (7 min)

Learning Objectives

• The student will be able to explain social comparison theory and the difference between upward and downward comparison.
• The student will be able to analyze how filters, editing, and algorithms distort the images that shape online self-image.
• The student will be able to evaluate the connection between constant comparison and anxiety, using media-literacy reasoning.
• The student will be able to apply self-compassion and feed-curation strategies to protect a healthy self-image.

Vocabulary

Discussion Activities

• Explain upward and downward comparison, and why upward comparison online is often a 'rigged contest.'
• Discuss how filters and editing tools turn a photo into a 'design' rather than a real appearance.
• Describe the comparison–anxiety loop and how the algorithm can feed it. How can you cut the loop?
• Practice self-compassion: write down the kind sentence you'd say to a friend, and try saying it to yourself.
• Try the challenge — audit your feed, mute or unfollow three accounts that make you feel worse, and add one that lifts you up.
• Discuss: Why do even the people who post filtered photos sometimes feel worse comparing themselves to their own edited images?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 5: Designing Healthy Digital Habits (8 min)

Learning Objectives

• The student will be able to summarize the key ideas from the unit — the teen brain, social media and mental health, technology balance, and comparison.
• The student will be able to explain the habit loop (cue, routine, reward) and how to redesign it intentionally.
• The student will be able to design a personal digital-wellbeing plan using specific, measurable, realistic goals.
• The student will be able to justify their plan choices and identify sources of support to sustain them.

Vocabulary

Discussion Activities

• Explain the habit loop (cue, routine, reward) and why changing the cue is usually the easiest way to break a habit.
• Turn a vague goal ('use my phone less') into a SMART goal, and explain each letter of SMART.
• Build your three-column plan: write one SMART goal each for Protect, Replace, and Connect.
• Why is 'start small' better than trying to change everything at once? Connect this to habit science.
• For the Connect column, identify one trusted adult you could talk to if things ever feel heavy, and discuss why naming that person matters.
• Take the final challenge — commit to one SMART goal starting tonight, keep it for two weeks, and reflect on how it feels to be in charge.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 1: Misinformation, Disinformation & "Fake News" (7 min)

Learning Objectives

• The student will be able to distinguish between misinformation, disinformation, and malinformation using precise definitions and real examples.
• The student will be able to explain the economic and psychological incentives that drive the spread of false information online.
• The student will be able to analyze how emotional triggers and confirmation bias make false content more shareable.
• The student will be able to evaluate a piece of viral content for signs of manufactured or misleading information.
• The student will be able to apply a pause-and-verify habit before sharing information with their own networks.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the difference between misinformation, disinformation, and malinformation, and give an example of each.
• Discuss a time you or someone you know shared something online that later turned out to be false. What made it believable?
• Why do false stories often spread faster than true ones? Discuss the roles of money and emotion.
• Analyze a recent viral post together and identify any red flags (missing source, manufactured urgency, emotional headline).
• Debate: Who is responsible for stopping the spread of misinformation — platforms, governments, or individual users?
• Research a real fact-checking organization and discuss how it verifies claims.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 2: Manipulated Media: Deepfakes, Filters & Editing (7 min)

Learning Objectives

• The student will be able to define deepfake, synthetic media, and shallowfake, and explain how each is produced at a conceptual level.
• The student will be able to compare the range of manipulation from harmless beautifying filters to deceptive fabricated video.
• The student will be able to analyze the psychological and social harms of manipulated imagery, including body image and erosion of trust.
• The student will be able to evaluate a video or image for telltale signs of manipulation and for provenance.
• The student will be able to justify an ethical position on when editing crosses the line from creativity into deception.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the spectrum of manipulation from beautifying to deepfakes.
• Discuss where you personally draw the line between harmless editing and deceptive manipulation.
• How might deepfakes affect trust in real video evidence? Discuss the 'liar's dividend.'
• Explore the impact of beautifying and retouching filters on body image and self-esteem.
• Research how content credentials or provenance tools work and discuss whether they could rebuild trust.
• Debate: Should platforms be required to label all AI-generated or heavily edited media?
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 3: Algorithms, Echo Chambers & Filter Bubbles (7 min)

Learning Objectives

• The student will be able to explain what a recommendation algorithm is and what signals it uses to rank content.
• The student will be able to differentiate between a filter bubble and an echo chamber.
• The student will be able to analyze how engagement-optimized algorithms can amplify extreme content and narrow a person's information diet.
• The student will be able to evaluate the trade-offs of personalization, weighing convenience against a distorted view of the world.
• The student will be able to apply concrete strategies to diversify their information intake and take back agency over their feed.

Vocabulary

Discussion Activities

• Verbally or in writing, explain in your own words what an algorithm does and what 'signals' it uses.
• Discuss the difference between a filter bubble (built by the algorithm) and an echo chamber (built by people).
• Compare feeds: have students describe what their 'For You' page shows and what it never shows them.
• Analyze the 'rabbit hole' effect — how might a system amplify increasingly extreme content, and why?
• Discuss the trade-offs of personalization: what do we gain, and what do we lose?
• Brainstorm and try one strategy to diversify your feed, then discuss what changed.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 4: Evaluating Sources & Fact-Checking (7 min)

Learning Objectives

• The student will be able to apply the lateral-reading and SIFT strategies to evaluate an unfamiliar source.
• The student will be able to distinguish between primary and secondary sources and judge which is appropriate for a claim.
• The student will be able to analyze a source for authority, evidence, purpose, and potential bias.
• The student will be able to evaluate the reliability of a specific claim by tracing it back to its original evidence.
• The student will be able to critique the weaknesses of vertical reading and single-source verification.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the SIFT method and what each letter stands for.
• Practice lateral reading as a class: pick an unfamiliar website and investigate it using new tabs.
• Discuss why judging a source by its appearance is unreliable in today's information environment.
• Distinguish primary from secondary sources using a recent news story and the study or data behind it.
• Trace a surprising statistic back to its original source together and compare it to how it was reported.
• Apply the four questions — authority, evidence, purpose, bias — to a source students use regularly.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 5: Advertising, Influencers & Sponsored Content (7 min)

Learning Objectives

• The student will be able to identify native advertising, sponsored content, and affiliate marketing when they appear in a feed.
• The student will be able to analyze common persuasion techniques used by advertisers and influencers, including parasocial trust.
• The student will be able to explain disclosure rules and why undisclosed sponsorship is deceptive and often illegal.
• The student will be able to evaluate a piece of influencer content to determine whether it is genuine opinion or paid promotion.
• The student will be able to apply critical questions that reveal the commercial intent behind persuasive content.

Vocabulary

Discussion Activities

• Verbally or in writing, summarize the difference between sponsored content, native advertising, and affiliate marketing.
• Discuss the persuasion techniques covered — scarcity, social proof, authority, reciprocity — and find an example of each.
• Explore the idea of a parasocial relationship: why does a creator's recommendation feel more trustworthy than a traditional ad?
• Analyze a real influencer post as a class and hunt for the disclosure — is it clear or buried?
• Discuss the FTC disclosure rules and why hidden sponsorship is a problem for consumers.
• Apply the four evaluation questions — commercial intent, disclosure, persuasion tactics, real evidence — to a piece of content.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 1: Managing Your Digital Presence for College & Career (7 min)

Learning Objectives

• The student will be able to analyze how admissions officers and employers evaluate an applicant's online presence.
• The student will be able to distinguish between a passive digital footprint and an actively curated digital presence.
• The student will be able to evaluate their existing social media accounts against a professional standard.
• The student will be able to create a concrete plan to build a positive, career-ready digital presence.

Vocabulary

Discussion Activities

• Search your own name in an incognito window and describe what a stranger would find on the first page of results.
• What is the difference between your passive digital footprint and the digital presence you actively curate?
• Discuss the 'three-audiences test' and apply it to a recent post you have seen (not necessarily your own).
• Why do you think employers screen candidates on social media before hiring? Is it fair?
• How could a professional profile like LinkedIn change the first impression a search creates?
• Draft a positive, intentional caption for a real activity or accomplishment from this year.
• Students are invited to share their responses with Dr. Lisa Strohman at: info@digitalcitizenacademy.org

Lesson 2: Your Data, Privacy Rights & Digital Law (7 min)

Learning Objectives

• The student will be able to explain how companies collect, aggregate, and monetize personal data.
• The student will be able to identify key legal privacy protections that apply to them, including major privacy laws.
• The student will be able to interpret the core promises and limits of a Terms of Service and privacy policy.
• The student will be able to apply practical strategies to exercise their privacy rights and minimize their data exposure.

Vocabulary

Discussion Activities

• If an app is completely free, how does the company behind it likely make money? What does that mean for you?
• Explain in your own words what a data broker does and why aggregation is so powerful.
• Which privacy law (GDPR, CCPA/CPRA, FERPA, COPPA) is most relevant to you right now, and why?
• Skim a real app's privacy policy for three things: what they collect, who they share it with, and your choices.
• Review your phone's app permissions and identify at least one app with access it does not need.
• Discuss the concept of data minimization and list three ways you could practice it this week.

Lesson 3: Ethics of AI & Emerging Technology (7 min)

Learning Objectives

• The student will be able to describe in plain terms how generative AI systems produce their output.
• The student will be able to analyze ethical challenges of AI, including bias, misinformation, and deepfakes.
• The student will be able to evaluate whether a given use of AI is responsible, honest, and ethical, including in academic and career settings.
• The student will be able to formulate personal guidelines for using AI as a tool with integrity.

Vocabulary

Discussion Activities

• List three ways you already use AI in daily life, and discuss whether you understood how each one works.
• Explain what an AI 'hallucination' is and why it means you must verify AI-generated facts.
• How can an AI system end up being biased if a computer has no opinions of its own?
• Discuss the 'AI honesty spectrum': give one example each of clearly ethical, gray-zone, and clearly dishonest AI use.
• Apply the question 'Whose thinking is this, really?' to a homework scenario involving AI.
• Draft your own three-rule personal code of ethics for using AI in college and beyond.

Lesson 4: Online Security, Scams & Staying Safe (7 min)

Learning Objectives

• The student will be able to identify common online scams and the psychological tactics that make them work.
• The student will be able to explain how strong authentication practices protect accounts.
• The student will be able to apply a systematic method to detect phishing and social-engineering attempts.
• The student will be able to evaluate their own security habits and construct a personal security plan.

Vocabulary

Discussion Activities

• Why is the human being usually the weakest link in any security system?
• List the red flags that help you recognize a phishing email, text (smishing), or call (vishing).
• Explain why length matters more than complexity when creating a strong passphrase.
• Discuss how two-factor authentication protects an account even if a password is stolen.
• Analyze a sample scam message and identify each manipulation tactic it uses.
• Create a personal security plan and turn on 2FA for your most important account.

Lesson 5: Becoming a Positive Digital Leader (7 min)

Learning Objectives

• The student will be able to differentiate between passive digital participation and active digital leadership.
• The student will be able to describe strategies for being an 'upstander' and fostering healthy online communities.
• The student will be able to evaluate the credibility and impact of information before amplifying it.
• The student will be able to design a personal plan to use their digital presence for positive influence and the common good.

Vocabulary

Discussion Activities

• What is the difference between being a good digital citizen and being a digital leader?
• Describe the three choices you have when you witness online cruelty, and why being an upstander matters.
• How can a single person speaking up change the behavior of an entire online group?
• Explain why sharing content responsibly makes you a 'filter, not a funnel.'
• Run a piece of content through the 'before you share' filter: Is it true? Is it kind or necessary? Who benefits?
• Design one specific, realistic act of digital leadership you will perform this week.
• Reflect on the digital legacy you want to leave and write a personal commitment statement.

Video 1: Understanding Cyberbullying

• Defines cyberbullying and distinguishes it from traditional bullying
• Explores different forms of online harassment including direct attacks, public shaming, and impersonation
• Examines the unique characteristics of cyberbullying such as anonymity, permanence, and wide audience
• Discusses the prevalence of cyberbullying among teens
• Introduces the concept of digital citizenship and respectful online behavior

Video 2: The Impact of Cyberbullying

• Explores the psychological effects on victims including anxiety, depression, and isolation
• Examines how cyberbullying affects academic performance and social relationships
• Discusses the impact on bystanders who witness online harassment
• Addresses the consequences for perpetrators including legal and social repercussions
• Presents real-world case studies illustrating the serious effects of cyberbullying

Video 3: Prevention and Response Strategies

• Provides practical strategies for protecting yourself online
• Teaches how to document and report cyberbullying incidents
• Discusses the role of bystanders in stopping online harassment
• Explores platform-specific reporting tools and blocking features
• Emphasizes the importance of seeking help from trusted adults

Video 4: Creating a Positive Digital Culture

• Discusses how to promote kindness and empathy online
• Explores the concept of digital leadership and positive influence
• Addresses the responsibility of content creators and influencers
• Presents strategies for supporting victims of cyberbullying
• Encourages students to be advocates for change in their digital communities

Video 1: Understanding Misinformation and Disinformation

• Defines misinformation and disinformation with clear distinctions
• Explores different types of false information (satire, false context, imposter content, etc.)
• Provides criteria for identifying misinformation using the RumorGuard framework
• Examines the real-world impact of false information on individuals and society
• Introduces practical strategies for verifying information before sharing

Video 2: Understanding Logical Fallacies

• Defines logical fallacies as errors in reasoning that undermine argument validity
• Examines personal attack fallacies including ad hominem arguments
• Explores emotional appeal fallacies that manipulate feelings rather than present evidence
• Addresses oversimplification fallacies like false dilemmas and straw man arguments
• Identifies evidence manipulation fallacies such as cherry picking and suppressed evidence
• Provides practical examples for identifying fallacies in media content

Video 3: Cognitive Biases and Media Manipulation

• Defines cognitive biases as mental shortcuts that affect information processing
• Explores confirmation bias and its impact on media consumption habits
• Examines anchoring bias and negativity bias in news consumption
• Addresses in-group bias, overconfidence bias, and the Dunning-Kruger effect
• Investigates selective perception and its role in interpreting media differently
• Presents strategies for overcoming cognitive biases in media consumption

Video 4: Combating Misinformation in the Media Ecosystem

• Analyzes how misinformation spreads through the modern media ecosystem
• Examines the role of journalistic ethics and the challenges facing traditional media
• Presents case studies of misinformation campaigns and their effects
• Explores how social media algorithms and features amplify false information
• Provides practical strategies for media consumers to combat misinformation
• Emphasizes collective responsibility in creating a healthier information environment

Video 1: Introduction to Digital Citizenship & App Reviews

• Introduces the concept of digital citizenship and its importance
• Explains the 'Good, Bad, and Ugly' framework used throughout the series
• Discusses how apps and social media impact teens' digital footprints
• Explores the relationship between online choices and future opportunities
• Establishes the foundation for making informed decisions about social media use

Video 2: Instagram - Visual Social Media

Instagram is a visual-centric social media app that enables users to share photos or videos with people who follow their account. Users can also view, comment and like posts shared by the people they follow. Users must be at least 13 years of age.

The Good

• See what friends from other schools / other places are doing
• Keep up with current events
• Post pictures of fun activities and accomplishments and pictures with friends and family

The Bad

• Can lead to a culture of comparing yourself to others
• Increased anxiety, social pressure, and concern with number of likes, comments, and followers
• Easy to post or see inappropriate content
• Deleting a post doesn't mean it's gone forever - someone may have taken a screenshot

The Ugly

• Geotag features allow other users to see your GPS location
• Public accounts can be viewed by anyone on the internet
• Anyone can send a message to anyone else, even if the user has a private account
• Instagram has had privacy breaches allowing marketing agencies to gather user data

Safety Strategies

• Make your page private
• Keep personal information out of your bio
• Turn off geotagging
• Report offensive or inappropriate content
• Remove the app if you need a break

Video 3: Snapchat - Ephemeral Content

Snapchat is a popular messaging application that lets users exchange pictures and videos (called 'snaps') that are meant to disappear after they have been viewed.

The Good

• Easy form of communication with photo sharing, messaging, and video chat
• Special filters and stickers
• No 'likes' - simply sharing content with friends

The Bad

• Photos disappear within seconds - hard to have record for reporting
• SnapMaps shows your precise location to friends
• Text messages disappear when you swipe out of conversation

The Ugly

• Snapchat employees have access to photos and personal information
• 2019 scandal: employees saved photos and accessed user info without permission
• Security problems where hackers set up fake accounts
• Syncing contacts exposes your entire contact list to security risks

Safety Strategies

• Adjust settings so you can only be found by username
• Turn off SnapMaps feature (Ghost Mode)
• Do not sync contact list with Snapchat
• Only friends can view your story
• Don't send photos you wouldn't want reflected on you

Video 4: TikTok - Short-Form Video Content

TikTok is a video sharing platform considered the world's fastest growing social media app. Users can shoot, edit, and share 15 second videos enhanced with filters, music, animation, and special effects.

The Good

• Keep up with popular trends and relevant content
• Create your own videos and participate in online challenges
• Easy to learn with algorithm tailored to your interests

The Bad

• All accounts automatically set to public
• Factions/sides emerging creating clique-like atmosphere
• Adult content impossible to avoid if algorithm presents it

The Ugly

• Multiple reported incidents of predatory behavior and cyberbullying
• Production and popularization of racist/sexist/homophobic content
• TikTok gathers user information at high rate
• Many users under 13 without parental consent

Safety Strategies

• Turn on privacy settings
• Don't include name or identifying information on profile
• Be careful who you exchange messages with
• Block unwanted content and report inappropriate users
• Talk to parents or trusted adult if uncomfortable

Video 5: YouTube - Video Sharing Platform

YouTube is a video-sharing platform where users can create and post original videos to their channel. Users can subscribe to others' channels and view, like, and comment on videos.

The Good

• Video content covers anything - art, comedy, how-to's, education, music, fitness
• Algorithm suggests videos based on watch history
• Can create content or simply follow others
• Don't need account to view videos

The Bad

• Notorious for drama between famous creators
• Videos interrupted by ads that gather marketing information
• All channels are public by default

The Ugly

• YouTube has been hacked, jeopardizing user information
• Suggested videos can include inappropriate content
• Issues with racist/sexist/homophobic/transphobic content from paid creators

Safety Strategies

• Set account to private
• Stay out of drama
• Use report function for offensive content
• Talk to trusted adult about hurtful content
• Consider using YouTube without an account if not creating content

Video 6: X (Twitter) - Microblogging Platform

X (formerly Twitter) is a microblogging system allowing users to send and receive short posts called 'tweets' up to 140 characters including links. Many use it to stay up to date on news topics.

The Good

• Allows you to have a voice and express thoughts/opinions
• Retweet feature makes sharing easy
• Keep up with news and current events
• Updates on favorite shows, movies, actors, authors

The Bad

• Hard to filter out unwanted or inappropriate content
• Private accounts can't have tweets retweeted
• Location tags reveal GPS location of where tweet was posted

The Ugly

• 2019 privacy breach gave marketing company access to emails and phone numbers
• Another breach let apps read private direct messages
• Twitter fights between users create atmosphere of conflict and drama

Safety Strategies

• Make account private
• Hide birthday in settings
• Turn off geolocation
• Use 'Muted words' to block triggering topics
• Have face-to-face conversations about offensive posts
• Check with friends and trusted adults before posting questionable content

Module 1: Welcome to TLC (10 min · 5 pts)

Get introduced to the Teen Leadership Council program.

Skills: Communication, Self-awareness, Goal setting

Module 2: Your Digital Footprint (20 min · 10 pts)

Discover what makes up your digital footprint.

Skills: Digital literacy, Critical thinking, Self-awareness, Privacy awareness

Module 3: Online Privacy & Safety (25 min · 10 pts)

Learn how to protect your personal information.

Skills: Digital literacy, Critical thinking, Problem-solving, Risk assessment

Module 4: Digital Communication (20 min · 10 pts)

Master respectful digital communication.

Skills: Communication, Digital literacy, Empathy, Conflict resolution

Module 5: Healthy Tech Habits (20 min · 10 pts)

Build balanced relationship with technology.

Skills: Self-regulation, Time management, Self-awareness, Wellness

Module 6: Digital Citizenship Pledge (15 min · 15 pts)

Commit to being a responsible digital citizen.

Skills: Ethics, Accountability, Leadership, Commitment

Module 1: Introduction to Research (20 min · 10 pts)

Basics of ethical community research.

Skills: Research methodology, Critical thinking, Ethics, Information literacy

Module 2: Understanding Bias (25 min · 15 pts)

How bias affects research.

Skills: Critical thinking, Self-awareness, Research methodology, Objectivity

Module 3: Bias Detective Training (30 min · 20 pts)

Practice identifying bias.

Skills: Critical thinking, Analysis, Pattern recognition, Research methodology

Module 4: Question Design Basics (25 min · 15 pts)

Writing clear survey questions.

Skills: Writing, Communication, Critical thinking, Research methodology

Module 5: Building Your Survey (40 min · 25 pts)

Create research survey.

Skills: Research methodology, Writing, Problem-solving, Design thinking

Module 6: Research Ethics & Consent (25 min · 15 pts)

Ethical considerations.

Skills: Ethics, Critical thinking, Empathy, Legal awareness

Module 7: Ethics Checkpoint (15 min · 10 pts)

Submit for approval.

Skills: Ethics, Communication, Documentation, Professional standards

Module 8: Interview Techniques (30 min · 20 pts)

Professional interview skills.

Skills: Communication, Active listening, Interpersonal skills, Professionalism

Module 9: Sampling Strategies (20 min · 15 pts)

Collect from diverse sources.

Skills: Research methodology, Critical thinking, Strategic planning, Inclusivity

Module 10: Field Work Launch (45 min · 20 pts)

Begin collecting responses.

Skills: Project management, Communication, Organization, Data collection

Module 11: Quality Control (25 min · 15 pts)

Validate responses.

Skills: Critical thinking, Attention to detail, Quality assurance, Data analysis

Module 12: Field Work Completion (20 min · 20 pts)

Finalize data collection.

Skills: Project management, Documentation, Organization, Completion

Module 1: Introduction to Data Analysis (20 min · 10 pts)

Transform data into insights.

Skills: Data analysis, Critical thinking, Research methodology, Problem-solving

Module 2: Creating Categories (30 min · 15 pts)

Develop coding scheme.

Skills: Data analysis, Organization, Critical thinking, Pattern recognition

Module 3: Sorting Responses (45 min · 20 pts)

Sort into categories.

Skills: Data analysis, Attention to detail, Organization, Decision-making

Module 4: Tallying & Counting (25 min · 15 pts)

Count responses.

Skills: Data analysis, Mathematics, Attention to detail, Accuracy

Module 5: Calculating Percentages (25 min · 15 pts)

Convert to percentages.

Skills: Mathematics, Data analysis, Critical thinking, Numerical literacy

Module 6: Finding Patterns (30 min · 20 pts)

Identify trends.

Skills: Data analysis, Critical thinking, Pattern recognition, Insight generation

Module 7: Building Evidence-Based Claims (35 min · 25 pts)

Create supported claims.

Skills: Critical thinking, Argumentation, Evidence evaluation, Writing

Module 8: Understanding Limitations (20 min · 10 pts)

Acknowledge limitations.

Skills: Critical thinking, Self-awareness, Intellectual humility, Research methodology

Module 9: Data Visualization (35 min · 20 pts)

Create charts/graphs.

Skills: Data visualization, Design thinking, Communication, Digital literacy

Module 10: Writing Conclusions (25 min · 15 pts)

Synthesize analysis.

Skills: Writing, Critical thinking, Synthesis, Communication

Module 11: Portfolio Review (20 min · 15 pts)

Submit for review.

Skills: Documentation, Self-assessment, Communication, Professional standards

Module 12: Selecting Your Cause (25 min · 20 pts)

Choose advocacy issue.

Skills: Decision-making, Critical thinking, Values clarification, Strategic thinking

Module 1: Building Your Campaign Team (25 min · 15 pts)

Recruit and assign roles.

Skills: Leadership, Collaboration, Communication, Team building, Recruitment

Module 2: Breaking Down the Work (25 min · 15 pts)

Work breakdown structures.

Skills: Project management, Organization, Strategic planning, Analysis

Module 3: Selecting Your Deliverables (30 min · 20 pts)

Choose deliverables.

Skills: Decision-making, Strategic thinking, Creativity, Resource assessment

Module 4: Assigning Work & Timelines (30 min · 20 pts)

Delegation and timeline.

Skills: Project management, Time management, Delegation, Leadership, Planning

Module 5: Creating Your Deliverables (120 min · 50 pts)

Build campaign deliverables.

Skills: Creativity, Production, Collaboration, Problem-solving, Execution

Module 6: Final Review & Launch Prep (25 min · 20 pts)

Prepare for launch.

Skills: Quality assurance, Attention to detail, Preparation, Organization

Module 1: Launch Day (25 min · 20 pts)

Go live with campaign.

Skills: Execution, Leadership, Communication, Stress management, Adaptability

Module 2: Time Tracking & Documentation (25 min · 20 pts)

Log hours and document.

Skills: Time management, Documentation, Organization, Accountability

Module 3: Executing Your Deliverables (120 min · 50 pts)

Deploy and collect evidence.

Skills: Execution, Problem-solving, Adaptability, Persistence, Documentation

Module 4: Managing Your Campaign (30 min · 25 pts)

Track progress, handle issues.

Skills: Project management, Problem-solving, Leadership, Decision-making, Communication

Module 5: Campaign Wrap-Up (25 min · 30 pts)

Close out campaign.

Skills: Project management, Organization, Completion, Documentation, Reflection

Module 1: Measuring Your Impact (30 min · 25 pts)

Quantify and analyze impact.

Skills: Data analysis, Critical thinking, Quantitative reasoning, Evaluation

Module 2: Analyzing What Worked (25 min · 20 pts)

Reflect on successes.

Skills: Critical thinking, Analysis, Self-reflection, Pattern recognition

Module 3: Personal Journey Reflection (30 min · 25 pts)

Document growth.

Skills: Self-reflection, Writing, Self-awareness, Growth mindset, Metacognition

Module 4: Documenting for Future Students (35 min · 30 pts)

Create legacy guide.

Skills: Writing, Knowledge transfer, Communication, Mentorship, Documentation

Module 5: Celebration & Recognition (20 min · 25 pts)

Certificate and portfolio.

Skills: Self-presentation, Portfolio development, Professional identity, Celebration