Computer Science · Grade 9

Active learning ideas

Introduction to Artificial Intelligence

This topic thrives on active learning because students best grasp AI’s abstract concepts when they see them in real-world contexts. By sorting examples, hunting for apps, and debating impacts, students connect classroom ideas to tangible technologies they already use every day.

• Ontario Curriculum Expectations
• CS.HS.IC.1
• CS.HS.CT.11

• 20–45 min
• Pairs → Whole Class
• 4 activities

Activity 01

• Fishbowl Discussion
• 25 min · Pairs

Pairs Sort: Classify AI Examples

Provide pairs with cards listing technologies like chatbots and self-driving cars. They sort into AI, ML, or neither categories and write one-sentence justifications for each. Pairs share two examples with the class for whole-group verification.

Differentiate between artificial intelligence, machine learning, and deep learning.

Facilitation Tip

During Pairs Sort, circulate and listen for students’ reasoning when they debate whether examples belong in AI, ML, or DL categories.

What to look for

On a slip of paper, students will write down one example of AI they encountered today. They will then briefly explain if it uses AI, ML, or DL and why.

• Analyze
• Evaluate
• Social Awareness
• Self-Awareness

Activity 02

• Fishbowl Discussion
• 35 min · Small Groups

Small Groups: App AI Hunt

Groups examine three common apps on shared devices, identify potential AI features such as auto-corrections or filters, and note supporting evidence. Each group presents findings and predicts one future AI addition to an app.

Analyze real-world examples of AI in everyday life.

Facilitation Tip

In App AI Hunt, remind groups that their success depends on explaining how each app’s features rely on AI, ML, or DL rather than just identifying them.

What to look for

Pose the question: 'What is one potential benefit of AI for our society and one potential challenge?' Facilitate a class discussion, encouraging students to support their points with reasoning.

• Analyze
• Evaluate
• Social Awareness
• Self-Awareness

Activity 03

• Fishbowl Discussion
• 45 min · Whole Class

Whole Class: AI Debate Prep

Divide class into teams to research one benefit and one challenge of AI adoption, using provided articles. Teams prepare 2-minute arguments, then vote on strongest points after presentations.

Predict the potential societal benefits and challenges of widespread AI adoption.

Facilitation Tip

For AI Debate Prep, assign clear roles so every student contributes to researching, drafting arguments, and anticipating counterpoints.

What to look for

Present students with a list of technologies (e.g., smart thermostat, self-driving car, spam filter, calculator, voice assistant). Ask them to categorize each as AI, ML, DL, or None, and be prepared to justify their choices.

• Analyze
• Evaluate
• Social Awareness
• Self-Awareness

Activity 04

• Fishbowl Discussion
• 20 min · Individual

Individual: Concept Mind Map

Students create a mind map linking AI, ML, deep learning definitions to three personal tech examples. They add one predicted societal impact per branch and share digitally for peer feedback.

Differentiate between artificial intelligence, machine learning, and deep learning.

Facilitation Tip

When reviewing Concept Mind Maps, ask students to connect their examples back to the definitions of AI, ML, and DL to reinforce understanding.

What to look for

On a slip of paper, students will write down one example of AI they encountered today. They will then briefly explain if it uses AI, ML, or DL and why.

• Analyze
• Evaluate
• Social Awareness
• Self-Awareness

A few notes on teaching this unit

Start with familiar examples students already use, like voice assistants, to build foundational knowledge before introducing technical terms. Avoid overwhelming students with jargon by connecting each new term (AI, ML, DL) to a real app or tool. Research shows that students retain concepts better when they first see the technology in action, then layer definitions on top of their observations.

Students will confidently differentiate AI, ML, and DL by citing concrete examples and explaining how each works. They will also articulate both the benefits and ethical considerations of AI applications through structured discussions and mind maps.

---

Watch Out for These Misconceptions

• During Pairs Sort, watch for students who assume AI can feel or think like humans.

  Direct students to compare AI outputs to human reasoning by having them explain how AI’s responses are based on patterns in data, while human thinking involves context and emotion.

• During App AI Hunt, watch for students who believe ML requires coding every possible scenario.

  Have students test simple ML demos, such as a color-recognition tool, to observe how the algorithm generalizes from training data instead of memorizing rules.

• During AI Debate Prep, watch for students who assume all AI applications are beneficial and unbiased.

  Encourage students to use real-world case studies, such as facial recognition errors, to highlight how bias in data can lead to unfair outcomes, and practice weighing pros and cons in their debates.

---

Methods used in this brief

• Fishbowl Discussion