Computer Science — Data Structures and Algorithms

Exam board: OCR  |  Back to subjects

Board-Specific Note

OCR specification; note any options relevant to your centre.

Learning Objectives

• Use arrays and lists
• Trace search and sort algorithms
• Analyse complexity

Key Points

• Arrays and linked lists
• Linear/binary search, bubble/merge sort
• Big-O notation

Lesson Plan (50 minutes)

1. Starter (5 min): Recall prior knowledge of data structures and algorithms with quick questions.
2. Teaching (15 min): Work through each of the learning objectives, explaining principles step by step.
3. Key points review (5 min): Revisit the key points together, confirming understanding.
4. Worked example (10 min): Model the example question: Which search is faster on sorted data?. Solution: Binary search (O(log n) vs O(n))
5. Practice (10 min): Students attempt the practice questions independently; circulate and support.
6. Plenary (5 min): Review answers and address misconceptions.

Homework

• Trace a binary search
• Describe a bubble sort pass
• State the complexity of linear search

Assessment

Check practice answers against the model answer; use the built-in practice questions as formative assessment.