Course Structure:
Ages: 8-10, 11-13, 14-18 Assignment Type: Age Specific Total Time: 275 minutesLesson Flow:
They learn how machines use data to “learn,” how algorithms guide computer actions, and why fairness and bias matter in AI systems.
Summary:
Students start their understanding of artificial intelligence here through hands-on activities, games, and guided discussions.
Lessons
1. What Is AI? (40 minutes)
Identify examples of AI and discuss what makes a system “intelligent.” Adapted from the 5 Big Ideas of AI by AI4K12.org
2. Can Machines Really Learn? (35 minutes)
Use Google Quick Draw to explore datasets and predictions.
3. What Is an Algorithm? (50 minutes)
Write and debug algorithms to solve real-world problems.
Lesson Flow:
Through hands-on activities and interactive discussions, learners investigate how AI perceives, plans, learns, interacts, and impacts society. They examine real-world examples like chatbots, self-driving cars, and recommendation tools, experiment with Google’s Quick, Draw! to see how machines learn from data, and create their own algorithms to understand how optimization and bias affect decision-making.
Summary:
Students explore what artificial intelligence (AI) is, how machines learn, and how algorithms make decisions that shape the world around us.
Lessons
1. What is AI? (30 minutes)
There is an optional AI Systems Case Study extension, in which students research specific AI systems (e.g., chatbots, autonomous cars) and present how they connect to the Five Big Ideas of AI.
Can Machines Really Learn? – Use Quick, Draw! to explore datasets, predictions, and how bias can enter AI systems, and discuss different types of bias in datasets.
**Summary:** Define artificial and intelligence, identify real-world AI examples, and explore the Five Big Ideas of AI.
2. What is an Algorithm? (30 minutes)
Students compare multiple algorithms that achieve the same goal in different ways, discussing which is “best” and why.
**Summary:** Write and test simple algorithms, debug errors, and discuss how “the best” solution depends on human choices and definitions.
Lesson Flow:
Through hands-on activities and interactive discussions, learners investigate how AI perceives, plans, learns, interacts, and impacts society. They examine real-world examples like chatbots, self-driving cars, and recommendation tools, experiment with Google’s Quick, Draw! to see how machines learn from data, and create their own algorithms to understand how optimization and bias affect decision-making.
Summary:
Students explore what artificial intelligence (AI) is, how machines learn, and how algorithms make decisions that shape the world around us.
Lessons
1. What is AI? (45 minutes)
Define artificial and intelligence, identify real-world AI examples, and explore the Five Big Ideas of AI. There is an optional AI Systems Case Study extension, in which students research specific AI systems (e.g., chatbots, autonomous cars) and present how they connect to the Five Big Ideas of AI. Can Machines Really Learn? – Use Quick, Draw! to explore datasets, predictions, and how bias can enter AI systems, and discuss different types of bias in datasets.
**Summary:** Quick, Draw! orqali ma’lumotlar to‘plamlari, prognozlar va AI tizimlariga tarafkashlik qanday kirishi mumkinligini o‘rganish, shuningdek, ma’lumotlar to‘plamlaridagi turli tarafkashlik turlarini muhokama qilish.
2. What is an Algorithm? (45 minutes)
Write and test simple algorithms, debug errors, and discuss how “the best” solution depends on human choices and definitions.
**Summary:** Students compare multiple algorithms that achieve the same goal in different ways, discussing which is “best” and why.