Computing · Year 9

Active learning ideas

AI and Automation in Industry

Active learning works because students need to confront the real-world trade-offs of AI and automation. When they debate, role-play, and analyse specific cases, they move beyond abstract ideas to see how technology reshapes jobs, workflows, and society. Hands-on activities make the societal impacts of technology concrete rather than theoretical.

• National Curriculum Attainment Targets
• KS3: Computing - Impact of Technology

• 30–45 min
• Pairs → Whole Class
• 4 activities

Activity 01

• Case Study Analysis
• 40 min · Pairs

Debate Prep: Automation Benefits vs Challenges

Assign pairs one benefit and one challenge of automation. Pairs research two industry examples using provided articles, then prepare 2-minute opening statements. Share in whole-class debate with peer voting on strongest arguments.

Explain how AI is being used to automate tasks in manufacturing or customer service.

Facilitation Tip

For Debate Prep, assign clear roles (e.g., factory manager, worker, economist) and provide a balanced briefing sheet so arguments are grounded in real constraints, not just opinion.

What to look for

Pose the question: 'Imagine you are a factory manager considering introducing more robots. What are the top two benefits you would highlight to your employees, and what are the top two concerns you would need to address?' Facilitate a class discussion where students share their answers and justify their choices.

• Analyze
• Evaluate
• Create
• Decision-Making
• Self-Management

Activity 02

• Case Study Analysis
• 45 min · Small Groups

Case Study Stations: AI in Action

Set up stations for manufacturing, customer service, healthcare, and transport with short videos and data sheets. Small groups spend 8 minutes per station noting AI uses, benefits, and issues, then report back to class.

Compare the benefits and challenges of increased automation in the workplace.

Facilitation Tip

For Case Study Stations, rotate groups quickly through three short cases to prevent overload and keep energy high while ensuring each student engages with diverse examples.

What to look for

Ask students to write on an index card: 'Name one industry likely to see major changes due to AI in the next 10 years. Briefly explain one specific way AI might change jobs in that industry.'

• Analyze
• Evaluate
• Create
• Decision-Making
• Self-Management

Activity 03

• Case Study Analysis
• 35 min · Small Groups

Prediction Mapping: Future Industries

In small groups, students list five industries and rate AI impact likelihood on a 1-5 scale using criteria like routine tasks and data availability. Groups create posters explaining predictions with evidence, then gallery walk to compare.

Predict which industries are most likely to be significantly impacted by AI in the next decade.

Facilitation Tip

For Prediction Mapping, give students a blank timeline graphic organizer and specific prompts like 'Transportation 2034' to focus their forecasting on verifiable trends.

What to look for

Present students with a short case study of a company using AI in customer service (e.g., a retail company using AI for personalized recommendations). Ask them to identify one specific task being automated and one potential benefit and one potential challenge for the company or its customers.

• Analyze
• Evaluate
• Create
• Decision-Making
• Self-Management

Activity 04

• Case Study Analysis
• 30 min · Pairs

Role-Play: Factory Upgrade Meeting

Pairs role-play as managers, workers, and AI experts debating a factory automation proposal. Each presents views on costs, jobs, and efficiency, then negotiate a plan. Debrief on key tensions as a class.

Explain how AI is being used to automate tasks in manufacturing or customer service.

Facilitation Tip

For Role-Play: Factory Upgrade Meeting, provide a simple script starter with blanks so quieter students can prepare lines that build on others’ ideas, reducing anxiety about improvisation.

What to look for

Pose the question: 'Imagine you are a factory manager considering introducing more robots. What are the top two benefits you would highlight to your employees, and what are the top two concerns you would need to address?' Facilitate a class discussion where students share their answers and justify their choices.

• Analyze
• Evaluate
• Create
• Decision-Making
• Self-Management

A few notes on teaching this unit

Teachers should anchor lessons in real companies and documented cases rather than hypothetical scenarios. Start with concrete examples students can verify, then layer in ethical and economic frameworks. Avoid overgeneralising—emphasise that automation’s effects vary by industry, skill level, and geography. Research shows that when students analyse flawed AI systems, they better understand bias than when they only discuss it abstractly. Keep the tone neutral but critical, encouraging students to weigh evidence rather than adopt extreme views.

Success looks like students explaining automation’s benefits and challenges with evidence from cases they have studied. They should compare sectors, predict changes, and adjust their views when new information contradicts their initial assumptions. Clear, supported reasoning in discussions and written work shows they grasp the complexities.

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Watch Out for These Misconceptions

• During Debate Prep: Automation Benefits vs Challenges, some students may claim AI will replace all human jobs completely.

  During Debate Prep, give each team a job sector card (e.g., factory, healthcare, design) and ask them to list three tasks AI can automate and three tasks humans will still do. Use their lists to redirect the debate toward job evolution rather than total replacement.

• During Case Study Stations: AI in Action, students often assume automation only impacts factory work.

  During Case Study Stations, include one service-sector case (e.g., AI chatbots in banking) and ask groups to compare automation’s role in both manufacturing and services. Highlight differences in the types of jobs affected.

• During Prediction Mapping: Future Industries, students may believe AI systems make perfect, unbiased decisions.

  During Prediction Mapping, provide a flawed AI example (e.g., a biased hiring algorithm) and ask students to note how data bias could affect the predictions they make for 2034. Have them revise their maps to include ethical safeguards.

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Methods used in this brief

• Case Study Analysis