Computer science updates

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This page contains the latest updates on the Diploma programme (DP) computer science course

The new DP computer science course will be launched in February 2023 for first teaching in August 2023. First assessment will take place in May 2025.

Below you will find an overview of the course updates. For a technical breakdown of the DP curriculum and assessment methods for this course, read the computer science subject brief (SL & HL).

Overview of the new course

The computer science curriculum is organized into three areas of learning

  • Systems in theory (theoretical underpinnings of the course)
  • Systems in practice (the practical application of the theory)
  • Systems in context (which connects the theory and practice to real-world scenarios and applications)

In addition, there are four themes: Abstraction, Design, Development, and Evaluation.

When combined, these form organizers (see below) that give teachers greater flexibility to create their own learning pathways for the two-year programme. Teachers are encouraged to use linking questions in the syllabus to form pathways through the syllabus content and reinforce the connections between the areas of learning.

Computer science learning pathway-en.svg

The pathway above illustrates one way that topics could be linked within a unit of study. By starting with systems in context and linking through the topics teachers can form a coherent and rich unit of study that teaches many concepts and the relationships between these concepts.

The new syllabus introduces programming at its core. There is a greatly reduced emphasis on pseudocode. Four topics are highly recommended to be taught using Java or Python, and paper 1 assesses students’ ability to read, interpret, understand, and respond using either programming language.

The previously optional object-oriented programming content has been incorporated into the standard level (SL) and higher level (HL) content while databases has been incorporated into the HL content only.  Additional areas of study include security and system vulnerabilities.

Conceptual learning

The new computer science course is moving towards a reduction in content, highlighting concepts that underpin learning in the subject. The course aims to develop understandings that connect factual, procedural and metacognitive knowledge and skills, and recognizes the importance of connecting learning with conceptual understanding. This includes a non-linear process of adding new knowledge, evolving understandings and identifying misconceptions.

Developing conceptual understandings will enable students to be aware and critical of their own knowledge, and to transfer and apply skills and understandings to new or different contexts in creative, generative, autonomous and dynamic ways.

Greater emphasis on skill development

Systems in practice has been designed to provide time for students to engage in skill development – practicing the skills they will need to be successful in the development of software solutions for the IA and beyond.

The practical nature of the subject is emphasized throughout the guide. This can be framed by the approaches to learning skills and categorized into different aspects, including the inquiry skills and techniques appropriate at this level of study.



Nature of computer science

Computer science requires an understanding of the fundamental concepts of computational thinking as well as knowledge of how computers and other digital devices work. Computer scientists work to understand, model and solve local, national and global problems. In response, computational solutions are developed to address these problems and facilitate the development of a world that is safe and sustainable for future generations. 

The development of solutions at local, national or global scales lies at the heart of this computer science course.

Experimental programme

Practical work

Practical work is a central aspect of the DP computer science course. Teachers are encouraged to develop a broad and balanced practical scheme of work, that allows students to gain a deeper understanding of subject content and associated concepts. This will provide students opportunities to develop a wide range of practical and investigative skills and encourage them to use appropriate programming languages to create algorithms, methods, models and software at different levels of complexity appropriate to the age group.

Collaborative sciences project

The collaborative project from the current course will be given a refresh.

The collaborative sciences project is an interdisciplinary sciences project that addresses real-world problems that can be explored through the range of subjects in the sciences group.

Through this project students will:

  • integrate factual, procedural and conceptual knowledge developed through the study of their science discipline(s).
  • apply their collective understanding to develop solution-focused strategies that address the issue
  • develop an understanding of how interrelated systems, mechanisms and processes impact a problem
  • evaluate and reflect on the inherent complexity of solving real-world problems
  • develop an understanding of the extent of global interconnectedness between regional, national, and local communities
  • be empowered to become active and engaged citizens of the world
  • gain appreciation of collective action and international cooperation
  • strengthen their ATL skills, including teambuilding, negotiation and leadership.

The collaborative sciences project provides an excellent opportunity for students to work with those taking other DP sciences courses, either in their own school or from other IB World Schools.

Changes to the assessment model

External assessment

All students will only sit two external examinations.

Paper 1 focuses on problem solving and combines syllabus content from the systems in theory and systems in practice areas of learning. Section B of paper 1 requires students to read, understand, interpret and write code in either Java or Python.

Paper 2 focuses on applying theory and practice to real-world contexts and combines syllabus content from systems in theory, systems in practice and systems in context. Section B of paper 2 is common for SL and HL and is framed by a given technology context.

Other changes include the removal of the option topics (databases, modelling and simulation, web science, object-oriented programming), and the case study for HL.

Internal assessment

The internally assessed computational solution will also see a change. Framed as a report, the student will document their process following the software development life cycle (SDLC) to create a solution that solves a real-world problem. They will need to conduct a user-centered investigation into the needs and wants of the client and users, design and develop their solution, and test and evaluate the solution.

Students will submit an individual report, with a maximum of 3,000 words.

The revised criteria will place a greater emphasis on higher-order thinking skills with two-thirds of the marks allocated to design, development, testing and evaluation.