Lesson 1 · Covered
Linear search
Find the first matching value by checking items in order. Revisit the lesson and practise the stopping condition.
Open lesson →B2.4 · Higher Level
Programming algorithms
Design, trace and compare searching and sorting algorithms, then develop HL recursion.
Class plan for 22–23 September: review binary search, then work through bubble sort and selection sort. Handout Problems 1 and 2 are complete.
Lessons
Open a lesson for the class activities, student handout and linked homework.
Lesson 2 · Covered
Big O notation
Review Big O notation with the class handout and textbook pages 358–361. Compare how time and auxiliary space grow with input size.
Open lesson →Lesson 3 · Covered
Binary search
Use sorted data to rule out half of the remaining candidates at each step.
Open lesson →Lesson 4 · Current focus
Bubble sort & selection sort
Follow how each pass moves values towards their final positions, then implement and compare two sorts.
Open lesson →Homework: Holiday homework: finish questions 3–7
Homework: Bubble sort: Q9(a) and the bubble-sort part of Q10
Lesson 5 · Planned
Recursion and its applications
Follow recursive calls down to a base case and back again, then explore how the same idea supports larger applications.
Open lesson →Textbook alignment & review
Find textbook pages, review questions and learning goals for B2.4.1–5, including HL recursion.
Open the coverage map & review →Learning goals
- Implement linear and binary search and explain their prerequisites.
- Trace bubble and selection sort; explore insertion sort as an extension.
- Compare growth in time and auxiliary space; test boundary cases.
- Explain recursion and its applications; construct and trace simple non-branching recursive functions (HL).
In practice
- Trace a successful and unsuccessful binary search using low, mid and high.
- Implement search without using Python’s built-in membership or index operations.
- Compare sorts on identical input; explain why an algorithm suits the problem.
Show understanding
A trace table, working Python implementation, test results and an individual explanation.
Predict first. Implement second. Test deliberately. Explain what the evidence shows.