Lesson Plan

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Lesson Plan
Grade: Date: 17/01/2026
Subject: Computer Science
Lesson Topic: Show understanding of insertion sort and bubble sort methods
Learning Objective/s:
  • Describe the operation of insertion sort and bubble sort.
  • Analyze and compare their time and space complexities.
  • Identify appropriate scenarios for using each algorithm.
  • Implement both sorts in pseudocode or a programming language.
  • Evaluate algorithm efficiency using best, average, and worst cases.
Materials Needed:
  • Projector or interactive whiteboard
  • Computer with IDE (e.g., Python, Java) for each student
  • Printed handouts of algorithm flowcharts
  • Sample data sets on cards or slides
  • Worksheet for complexity comparison
 Introduction:
Begin with a quick demonstration of sorting a deck of cards to illustrate how simple swaps can order a list. Review students’ prior knowledge of basic loops and conditionals, then state that today they will explore two fundamental sorting algorithms, understand how they work, and evaluate when each is appropriate. Success will be measured by their ability to explain the processes, compare efficiencies, and write correct pseudocode.
Lesson Structure:
  1. Do‑now (5'): Students sort a short list of numbers on paper; discuss strategies.
  2. Mini‑lecture (10'): Explain insertion sort concept with card analogy; show flowchart.
  3. Guided practice (10'): Walk through pseudocode on projector, tracing an example array.
  4. Group activity (10'): Students implement insertion sort in their IDE and test with sample data.
  5. Mini‑lecture (10'): Introduce bubble sort, compare to insertion sort, display diagram.
  6. Guided practice (10'): Step‑by‑step execution of bubble sort on the same array.
  7. Pair coding (10'): Students code bubble sort and run tests.
  8. Check for understanding (5'): Quick quiz (exit ticket) on best‑case/worst‑case complexities.
Conclusion:
Summarise that both algorithms sort in‑place with O(n²) worst‑case time, but insertion sort generally requires fewer swaps and adapts to nearly sorted data. Ask students to complete a short exit ticket comparing the two methods. For homework, they will research a more efficient sort (e.g., merge sort) and prepare a brief explanation of its advantages.