Lesson Plan

• Describe what live (real‑time) data is and its key characteristics.
• Explain how live data is integrated into each phase of the systems life‑cycle.
• Identify appropriate technologies and protocols for handling live data.
• Evaluate challenges such as latency, volume, reliability and propose mitigation strategies.
• Design a simple prototype that retrieves and displays live data.

• Projector and screen
• Laptop with internet access (teacher and each group)
• Sample live‑data API (e.g., weather or stock feed)
• Worksheets with the systems life‑cycle table
• Code editor/IDE (e.g., VS Code)
• Handout of common live‑data protocols (WebSocket, MQTT, HTTP‑SSE)
• Sticky notes and markers

Begin with a quick video clip showing live traffic maps and stock tickers to hook students’ interest. Ask them how these services stay up‑to‑date and link the answer to the systems life‑cycle they have already studied. Explain that today’s success criteria are to recognise live‑data roles, choose suitable technologies, and create a simple live‑data demo.

1. Do‑now (5'): Quick quiz on the seven phases of the systems life‑cycle.
2. Mini‑lecture (10'): Define live data, why it matters, and overview of common protocols.
3. Group activity (15'): Using the worksheet, map live‑data tasks and considerations onto each life‑cycle phase.
4. Live demo (10'): Show a real‑time API feed using WebSocket/JSON and discuss data flow.
5. Hands‑on coding (20'): Students modify starter code to fetch and display live data on a web page.
6. Testing challenge (10'): Simulate latency and data loss; groups suggest mitigation strategies.
7. Review & exit ticket (5'): Each student writes one benefit and one challenge of using live data.

Recap the key points: live data’s definition, its integration across the life‑cycle, and the trade‑offs between speed, accuracy, and security. Collect exit tickets and remind students to research a real‑world live‑data system for a one‑page reflection due next week.