IB Computer Science HL · Year 2 · Lesson 6

Flowchart/algorithmic-thinking retrieval + algorithm efficiency and Big O

Computational thinking gives you a language-independent way to specify, decompose and solve problems before you worry about syntax. Algorithms must be understood operationally: how they behave, how to trace them, and when their efficiency makes them suitable.

Paper 250 minutesB1.1.4 · B2.4.1
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Today’s targets

What you need to be able to do

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  • TraceFlowcharts for a range of programming algorithms
  • DescribeThe efficiency of specific algorithms by calculating their Big O notation to analyse their scalability
B1.1.4B2.4.1
Paper 2 lensMatch the depth of every response to the command term. Previously learned content can move quickly, but retrieval must still be accurate.
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Retrieve

Rapid Recall Deck

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Say the answer aloud before flipping. Mark secure knowledge quickly and spend time on the gaps.

  • What are the standard flowchart symbols used in this course?: Start/End, Process/Operation, Input/Output, Decision, Flowline, and Connector.
  • Which flowchart symbol represents a decision?: A diamond, with outgoing paths representing alternative results such as true/false or yes/no.
  • What is Big O notation used to describe?: How an algorithm's time or space requirements grow as the input size grows.
  • What is the difference between time complexity and space complexity?: Time complexity describes growth in required computation; space complexity describes growth in required memory.
  • How do O(1), O(log n), O(n), and O(n²) compare as input size grows?: O(1) grows least, then O(log n), then O(n); O(n²) grows much faster and becomes costly on large inputs.
  • Why does scalability matter when choosing an algorithm?: An algorithm that works on small inputs may become impractically slow or memory-heavy as the data set grows.
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B1.1.4 + B2.4.1 · Learn

Core knowledge and application

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B1.1.4Trace

Flowcharts for a range of programming algorithms

Computational thinking gives you a language-independent way to specify, decompose and solve problems before you worry about syntax.

Exam moveFollow the process step by step and record changing state or output.
Required detail 1Use of standard flowchart symbols to depict processes, decisions and flows of control
Required detail 2Standard flowchart symbols: Connector, Decision, Flowline, Input/Output, Process/Operation, Start/End
Required detail 3Flowcharts for execution flow, to track changes in variables and to determine output
Assessment boundaryPaper 2 uses no pseudocode; flowchart/algorithm descriptions are acceptable. First Paper 2 question is non-code. Paper 2

Explain it without notes

Trace: Flowcharts for a range of programming algorithms in the context of a school study-room recommendation system.

  • Use of standard flowchart symbols to depict processes, decisions and flows of control
  • Standard flowchart symbols: Connector, Decision, Flowline, Input/Output, Process/Operation, Start/End
  • Flowcharts for execution flow, to track changes in variables and to determine output
B2.4.1Describe

The efficiency of specific algorithms by calculating their Big O notation to analyse their scalability

Algorithms must be understood operationally: how they behave, how to trace them, and when their efficiency makes them suitable.

Exam moveGive a detailed, accurate account of what happens or what something is like.
Required detail 1The time and space complexities of algorithms and calculating Big O notation
Required detail 2Algorithm choice based on scalability and efficiency requirements
Assessment boundaryDespite wording “by calculating”, the command term is Describe; students describe the nature of Big-O calculations, not perform formal calculations. Paper 2

Explain it without notes

Describe: The efficiency of specific algorithms by calculating their Big O notation to analyse their scalability in the context of a program that searches and organizes a growing dataset.

  • The time and space complexities of algorithms and calculating Big O notation
  • Algorithm choice based on scalability and efficiency requirements
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Worked example · B1.1.4 / B2.4.1

Trace a flowchart and describe scalability

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Standard symbols in use

Start/End uses a terminator shape; Input/Output uses a parallelogram; Decision uses a diamond; Process/Operation uses a rectangle; Flowlines show direction; Connectors join separated sections of a larger flowchart.

Start Input n n mod 2 = 0? Output "odd" Output "even" No Yes
TraceFor n = 7, which branch is taken? Repeat for n = 12. Record the decision result and output.
O(1)Work does not grow with input size.
O(log n)Problem size is repeatedly reduced, as in binary search.
O(n)Work grows roughly in proportion to the number of items.
O(n²)Two nested passes over the data commonly create quadratic growth.
Big O exam focusDescribe how the growth rate affects scalability and algorithm choice. Formal algebraic derivation is not the goal.
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Apply

Transfer to a new scenario

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ScenarioA school study-room recommendation system needs a design or technical decision related to today’s topic. Explain what matters and why.
  • Use of standard flowchart symbols to depict processes, decisions and flows of control
  • Standard flowchart symbols: Connector, Decision, Flowline, Input/Output, Process/Operation, Start/End
  • The time and space complexities of algorithms and calculating Big O notation
  • Algorithm choice based on scalability and efficiency requirements
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Exam lens

Paper 2 practice

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Build the response before checking notesUse precise terminology and match the required depth.
  1. Trace: Flowcharts for a range of programming algorithms in the context of a school study-room recommendation system.
  2. Describe: The efficiency of specific algorithms by calculating their Big O notation to analyse their scalability in the context of a school study-room recommendation system.
Self-checkAnswer the exact command term. For explain, include mechanism/reason; for compare, pair criteria; for discuss/evaluate/justify, build supported reasoning and a conclusion.
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Homework

Finish the learning cycle

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IA — main task

Refine Criteria A/B/C. Use today’s lesson to make the problem specification, decomposition, algorithms or testing plan more precise where relevant.

Syllabus — 10–15 min

Repeat the recall deck and complete the lesson response prompt without model support.

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End of Lesson 6.