Lesson Plan

• Describe the purpose of pseudocode, program code, and flowcharts in algorithm design.
• Apply standard pseudocode conventions to write clear, correct algorithms.
• Translate an algorithm between pseudocode, Python code, and flowchart representations.
• Amend an existing algorithm to incorporate new requirements while keeping all representations consistent.
• Evaluate algorithm correctness and identify common errors such as off‑by‑one and infinite loops.

• Projector and screen
• Whiteboard and markers
• Printed handouts of pseudocode conventions and flowchart symbols
• Computers with a Python IDE installed
• Worksheet with algorithm amendment tasks
• Sticky notes for quick checks

Start with a quick poll: which representation—pseudocode, code, or flowchart—do you find most intuitive for solving a problem? Review the previous lesson’s control structures and the IPO model. Explain that today’s success criteria are to write, translate, and amend an algorithm consistently across all three representations.

1. Do‑now (5'): Students list advantages of each representation on sticky notes and share briefly.
2. Mini‑lecture (10'): Review pseudocode conventions and flowchart symbols using the projector.
3. Guided practice (15'): Walk through the “Find Maximum” example, writing pseudocode, converting to Python, and sketching a flowchart together.
4. Independent activity (20'): Pairs create pseudocode, code, and flowchart for a factorial algorithm; teacher circulates to support.
5. Amendment task (15'): Provide a new requirement (e.g., count inputs) and have pairs update all three representations, then test the code.
6. Check for understanding (5'): Quick quiz (Kahoot or show of hands) on common pitfalls.
7. Plenary (5'): Summarise the three‑step process and answer remaining questions.

Recap the three‑step process of writing, translating, and amending algorithms, emphasizing the need for consistency to avoid marking loss. Students complete an exit ticket describing one pitfall they will watch for. For homework, design and amend an algorithm that finds the second‑largest number in a list.