Computer fundamentals
Computer systems, hardware, software, data representation, logic and the principles that underpin modern computing.
IB Diploma Programme Computer Science
IB Computer Science tuition for confident SL and HL progress.
Personalised online support for the IB Diploma Programme Computer Science course for first assessment in 2027, covering computer systems, computational thinking, programming, examination preparation and the computational solution.
Lessons are shaped around the student's level, programming language, current confidence and assessment priorities, with support available for both Python and Java pathways.
Support aligned with the updated IB course
The course brings together conceptual knowledge, computational thinking and practical programming. Tuition connects these areas so students can understand, apply and communicate their thinking more effectively.
Standard Level and Higher Level support
Aligned with the course for first assessment in 2027
Python or Java programming support
Paper 1, Paper 2 and computational solution guidance
Common IB challenges
Focused help with the parts of IB Computer Science that cause the most difficulty.
Students often need support that links theory, programming, case-study application and assessment technique rather than treating each area separately.
Lessons begin by identifying the exact barrier, then building understanding and practising application until the student can work with greater independence.
The new course structure feels unfamiliar or difficult to organise.
Programming concepts make sense in lessons, but applying them independently is harder.
Paper 1 theory answers need more precise technical language and stronger application.
Paper 2 algorithm and programming questions feel difficult under timed conditions.
The computational solution needs a clearer problem, better success criteria or a more structured development process.
Theme A
Concepts in computer science.
Theme A develops understanding of how computing systems work and how computer science affects real-world contexts.
Networks
Network structures, communication, protocols, security, reliability and the impact of connected systems.
Databases
Data modelling, relational databases, keys, queries, integrity and the role of databases in real systems.
Machine learning
Core machine-learning ideas, applications, limitations and the ethical questions raised by intelligent systems.
Theme B
Computational thinking and problem-solving.
Theme B develops the ability to define problems, design algorithms, program solutions and evaluate their effectiveness.
Computational thinking
Problem specification, decomposition, abstraction, algorithmic thinking, testing and evaluation.
Programming
Writing, tracing, debugging and improving programs using clear algorithms, data and control structures.
Object-oriented programming
Classes, objects, methods, attributes, encapsulation and structured solution design.
Abstract data types
Higher Level support with abstract data types and choosing appropriate structures for computational problems.
Abstract data types are a Higher Level component. Other areas may also be studied in greater depth and breadth at Higher Level.
Assessment support
Preparation for Paper 1, Paper 2 and the computational solution.
Support can focus on a specific assessment component or follow a planned route across the complete course.
Paper 1
Support with Theme A knowledge, applying concepts to unfamiliar contexts, the prescribed case study and clear written explanations.
Paper 2
Programming, algorithms, computational thinking and problem-solving practice in Python or Java, including Higher Level extensions.
Computational solution
Ethical guidance with problem definition, success criteria, design, development, testing and evaluation while keeping the student responsible for the submitted work.
Academic integrity
Computational solution guidance that strengthens the student's own work.
Support can help students define a worthwhile real-world problem, clarify success criteria, improve decomposition, plan testing and evaluate the final solution more effectively.
The student remains responsible for all assessed decisions, programming, evidence and final submission. Tuition supports understanding and process; it does not produce assessed work for the student.
Guidance can include:
Refining the problem and intended user
Writing measurable success criteria
Planning algorithms, data and program structure
Building a purposeful testing strategy
Evaluating the solution against evidence
Learning pathway
A clear route from uncertainty to confident application.
Progress becomes more manageable when students identify the priority, build secure understanding, practise application and refine their performance over time.
1
Identify priorities
We establish the student’s level, programming language, assessment session and most important gaps.
2
Build understanding
Difficult concepts are broken down using diagrams, examples, code tracing and guided explanation.
3
Practise application
Students apply knowledge through programming tasks, case-study questions and examination-style practice.
4
Refine performance
Answers, algorithms and code are reviewed so the student becomes more precise, independent and confident.
Need targeted IB Computer Science support?
Share the student's level, programming language, assessment session and current area of difficulty, and I will suggest the most suitable next step.
LogicPath Education is an independent tuition provider and is not affiliated with or endorsed by the International Baccalaureate Organization.