1. What is the curriculum rationale in Computer Science?

Intent: purpose and values of Computer Science

“Everybody should learn to program a computer, because it teaches you how to think.” Steve Jobs, former CEO and creator of Apple

Digital technology is driving extraordinary global changes that some are calling the Fourth Industrial Revolution. For young people to function in an increasingly digitised global society we have a responsibility to provide a Computer Science education that teaches a wide range of transferable skills which will help to improve social mobility and give a higher chance of succeeding in a modern world.

Our intent in Computer Science is to equip students with the skills and knowledge they will require to thrive in an increasingly digitised and automated environment. We aim to encourage our students to use technology in innovative ways to foster curiosity, confidence, creativity, and resilience thereby empowering students into becoming regional and global citizens capable of actively, and ethically, communicating and collaborating in a real and digital world.

Our curriculum is designed using a progressive curriculum model where each outcome builds from the last with a clearly defined sequence of achievement for each key stage so that students can make excellent progress. We place great focus on encouraging students to experiment without fear of failure and students are encouraged to find new ways to apply their knowledge.

This allows students to believe in their ability and share responsibility for their learning. Students will be encouraged to practice common habits in Computer Science that are required to truly master the subject. When students leave us at either Year 9, Year 11, or Year 13, they will leave with confidence in their own ability to use computers for a wide range of tasks and the knowledge that they can approach any new systems that they encounter without fear.

2. What is the 'big picture' in Computer Science?

The ‘big picture’ outlines how the Big Ideas and areas of knowledge of each subject fit together:

The Big Ideas of Computer Science:  Computer Science can be viewed as having three pillars:

• information technology
• digital literacy

• computer science.

Information technology is about the use of computers for functional purposes, such as file management or creating digital office artefacts. Digital literacy includes the knowledge of safe digital working practices and understanding of the ethics context of the technology that we use. Computer Science involves building knowledge of how computers function at a basic level to harness their abilities, using computational thinking and knowledge of specific programming languages, to solve specific problems using technology.

Our five big ideas cross all three of the above strands:

1. Computational Abstraction: To be able to design, use, and evaluate computer models that replicate real-world systems and problems.

2. Coding: To write computer programs to solve a variety of real-world problems from bespoke software to games.

3. Components: To understand how hardware and software are used to create computer systems.

4. Creativity: To apply personal creativity using multiple computer applications, creating effective solutions which meet the needs of users

5. Communication: To be able to use a range of applications to share information safely, respectfully, responsibly.

There are four key areas of knowledge which are necessary to become a subject expert in Computer Science:

1. Conceptual understanding: That our students build declarative knowledge (knowing that) through studying existing digital systems, e.g. facts, ideas, technological developments, and successful imaginings

2. Procedural fluency: That our students build procedural knowledge (knowing how to) through experiencing how a computer scientist thinks, explores, and makes decisions, e.g. knowing how to achieve certain functions digitally

4. Disciplinary knowledge: That our students build the habits of creative thinking, effective enquiry, and technical knowledge, so that they can apply this knowledge to different problems, e.g. the exploration, testing and refining of solutions – striving for accuracy and functionality
5. Language: coding enabling the writing of computer programs to solve a variety of real-world problems, e.g. using a coding language such as Python to instruct a computer to complete a task.

The table below shows an example of declarative and procedural knowledge across the three pillars of Computer Science.

We want our students to become more than just a collection of computing knowledge. We can help them to become digital citizens who drive technological advancements. This means that we must ensure that we deliver an engaging and modern curriculum that is continuously adapting to new technological breakthroughs.

Although the main key concepts will remain, the tools and resources that we use to engage students and to explain these concepts will change year-on-year as new tools become relevant and available. We use a range of Computer Science specific pedagogy in lessons to ensure that all our students develop powerful knowledge in the subject. These include:

• Paired Programming
• PRIMM (Predict, Run, Investigate, Modify, Make)
• Peer Instruction
• Live Coding
• The Block Model
• Concept Maps
• Semantic Waves
• Worked Examples for Coding

3. What does knowledge look like in Computer Science?

Knowledge Framework coming soon

4. What do we teach and when?