Theme A
How systems work
Computer fundamentals, networks, databases and machine learning. Explain mechanisms, connect ideas and evaluate technical choices in context.
Course guide · Class of 2028
How this course works
Computer science begins with a problem. You learn to specify it, design a solution, write and test the program, and explain the choices you made.
Our class
This is a Higher Level course taught in Python, with five 55-minute lessons in a normal full week. The cohort began in August 2026 and is preparing for the May 2028 examination session, using the syllabus first assessed in 2027.
Our core text is Computer Science for the IB Diploma — Baumgarten, Ganea & Turland. Reading follows the material we are learning, with page ranges listed in each assignment. B2.3 appears earlier in the book’s teaching sequence: chapter order and syllabus numbering do not always match.
Use the schedule for the teaching plan, unit pages for learning goals and available handouts, and Toddle for assigned work and confirmed deadlines.
What you will learn
Theme B
How we solve problems
Computational thinking, programming, object-oriented design and HL abstract data types. Design, trace, implement and test solutions.
Putting it together
Independent application
Case-study research, the computational solution and the collaborative sciences project connect your understanding with unfamiliar problems.
Our weekly routines
- Predict before you run.Use flowcharts and trace tables to make your reasoning visible. A program that happens to produce the right answer still needs an explanation.
- Keep programming.Maintain Python practice during theory units. Use small, frequent problems to build fluency.
- Work on paper as well as on screen.Practise timed code tracing, algorithm design and developed written answers.
- Explain and challenge.Discuss solutions, justify choices and critique alternatives. Submit your own code and demonstrate your own understanding.
- Use tests deliberately.Include normal, boundary and invalid inputs. Record expected results before running the test.
- Turn mistakes into a plan.Keep an error log: the task, the mistake, its cause and the correction. Use it to choose revision work.
- Read the command term.Match the response to the question: a fact, an explanation, a comparison or an evaluation. Use markschemes to understand what earns credit.
Practical questions
What should I bring?
Your Python work, current handout or notes, and something to write with. Keep code and testing evidence organized so you can revisit them.
What if the timetable changes?
School holidays and closures are shown in the calendar. Future topics are teaching proposals and can shift with progress; check Toddle for assigned deadlines.
How should I use AI?
Follow the instructions for each task and the school’s academic integrity policy. Keep a record of assistance, acknowledge sources, and be able to explain the work you submit. Discuss permitted assistance with your teacher before using it on the IA.
Where are exam and IA details?
The assessment page separates IB component requirements from our internal checkpoints. Teacher materials, answer keys and student submissions are kept in the class’s private teaching space.