Learning computing is fun, creative, and exploratory. It also involves understanding some powerful ideas about how computers work and gaining key skills for solving problems using computers. These ideas and skills are collected under the umbrella term ‘computational thinking’.
When we create our online learning projects for young people, we think as much about how to get across these powerful computational thinking concepts as we do about making the projects fun and engaging. To help us do this, we have put together a computational thinking framework, which you can read right now.
What is computational thinking? A brief summary
Computational thinking is a set of ideas and skills that people can use to design systems that can be run on a computer. In our view, computational thinking comprises:
- Decomposition
- Algorithms
- Patterns and generalisations
- Abstraction
- Evaluation
- Data
All of these aspects are underpinned by logical thinking, the foundation of computational thinking.
What does computational thinking look like in practice?
In principle, the processes a computer performs can also be carried out by people. (To demonstrate this, computing educators have created a lot of ‘unplugged’ activities in which learners enact processes like computers do.) However, when we implement processes so that they can be run on a computer, we benefit from the huge processing power that computers can marshall to do certain types of activities.
Computers need instructions that are designed in very particular ways. Computational thinking includes the set of skills we use to design instructions computers can carry out. This skill set represents the ways we can logically approach problem solving; as computers can only solve problems using logical processes, to write programs that run on a computer, we need to use logical thinking approaches. For example, writing a computer program often requires the task the program revolves around to be broken down into smaller tasks that a computer can work through sequentially or in parallel. This approach, called decomposition, can also help people to think more clearly about computing problems: breaking down a problem into its constituent parts helps us understand the problem better.
Understanding computational thinking supports people to take advantage of the way computers work to solve problems. Computers can run processes repeatedly and at amazing speeds. They can perform repetitive tasks that take a long time, or they can monitor states until conditions are met before performing a task. While computers sometimes appear to make decisions, they can only select from a range of pre-defined options. Designing systems that involve repetition and selection is another way of using computational thinking in practice.
Our computational thinking framework
Our team has been thinking about our approach to computational thinking for some time, and we have just published the framework we have developed to help us with this. It sets out the key areas of computational thinking, and then breaks these down into themes and learning objectives, which we build into our online projects and learning resources.
To develop this computational thinking framework, we worked with a group of academics and educators to make sure it is robust and useful for teaching and learning. The framework was also influenced by work from organisations such as Computing At School (CAS) in the UK, and the Computer Science Teachers’ Association (CSTA) in the USA.
We’ve been using the computational thinking framework to help us make sure we are building opportunities to learn about computational thinking into our learning resources. This framework is a first iteration, which we will review and revise based on experience and feedback.
We’re always keen to hear feedback from you in the community about how we shape our learning resources, so do let us know what you think about them and the framework in the comments.
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