Lesson Plan

• Describe the six‑step problem‑solving process used in computer science.
• Identify and select an appropriate standard method (e.g., brute‑force, divide‑and‑conquer, greedy, dynamic programming, backtracking, recursion, iteration) for a given problem.
• Construct clear algorithm representations using flowcharts or pseudocode.
• Evaluate algorithm efficiency by analysing time and space complexity with Big‑O notation.

• Projector and screen
• Whiteboard and markers
• Worksheets comparing standard methods
• Laptops or computers with a simple IDE (e.g., Python IDLE)
• Printed handout of flowchart symbols
• Sample problem cards for group work

Begin with a quick puzzle that can be solved by trying every possibility, then ask students why that approach might be inefficient. Recall the problem‑solving steps they have already used in earlier lessons. Explain that today they will learn how to choose the most efficient method for a problem and how to represent it clearly.

1. Do‑now (5'): Mini‑quiz on the six‑step problem‑solving process.
2. Mini‑lecture (10'): Introduce the standard methods of solution, using the table from the source.
3. Guided practice (15'): In pairs, students receive a problem card, decide on a method, and draft pseudocode or a flowchart.
4. Whole‑class share (10'): Groups present their chosen method and justification; teacher highlights key differences.
5. Efficiency check (10'): Quick analysis of time/space complexity for the presented algorithms.
6. Exit ticket (5'): Each student writes one new problem and the method they would use to solve it.

Summarise the importance of matching a problem’s characteristics to an appropriate method and of evaluating efficiency. Collect exit tickets to gauge understanding and assign homework: students must select and justify a method for a given GCD problem and produce either a flowchart or pseudocode.