Computational Thinking

Be empowered for the AI age

  • Industry 
  • Government 
  • Education 
  • Individuals 

Advances in computation have been the predominant force in driving innovation in recent decades. As computers become more intelligent, humans need to step up: future success means optimising the competence of humans to drive the computer to get ever-more-insightful answers. delivers learning programmes for everyone. Our pioneering approach is not only about coding, maths you may have missed and critical thinking, but also the underlying core computational thinking that drives all of them—for example, applied to data science, modelling and life skills.

Our close association with Wolfram Research—world leaders in computation—makes us uniquely able to deliver cutting-edge learning programmes for individuals, schools, colleges and the workplace, as well as developing curricula for the AI age and advising policymakers on computational thinking.


The what, where, how of computational thinking


A mode of thinking about life, in which you apply a rigorous and repeatable four-step problem-solving process to ideas, challenges and opportunities. 


Almost everywhere. In everyday life, at work, in school, across fields as diverse as healthcare, finance, law and music, computational thinking is applicable to everyone. 


By gaining experience of applying the four-step computational thinking process—in real-life settings, through a graduated progression of tasks. 

Examples of computational thinking in action

Dividing responsibilities between humans and computers

What of computational thinking

Computational thinking is a process in which you creatively apply a four-step problem-solving cycle to ideas, challenges and opportunities you encounter to develop and test solutions. This is related to traditional maths, but in practice very different from the maths learnt at school. The emphasis is learning how to take real-life situations and translate—often to programs—so a computer can calculate the answer.


    Think through the scope and details of the problem, defining manageable questions to tackle. Identify the information you have or will need to obtain in order to solve the problem.


    Transform the question into an abstract precise form, such as code, diagrams or algorithms ready for computation. Choose the concepts and tools to use to derive a solution.


    Apply an appropriate level of computational power to the abstract form, be that modern computers or mental agility, to obtain answers. Identify and resolve operational issues during the computation.


    Take the abstract answer and interpret the results, re-contextualising them in the scope of your original questions and sceptically verifying them. Fix mistakes or refine by taking another turn around the solution helix.

Often the answer to one question can be used to solve a second, repeating the four-step process with new insights. Therefore, computational thinking can be thought of as a helix made up of a roadway of the four steps, repeating in sequence until you reach a solution fit for the original purpose.

Where of computational thinking

Computational thinking (CT) is applicable to everyone. It empowers managers, decision makers and administrators to think laterally to generate a broader range of solutions and adapt their strategy to become more competitive. It enables technical teams to optimise their techniques based upon the latest computation, providing innovative output for interpretation.




Use CT to design, simulate, model, optimise and predict the behaviour of your system under a variety of conditions.

  • Aerospace
  • Chemical
  • Electrical
  • Industrial
  • Mechanical
  • Architecture

Biotechnology and healthcare

CT affords new analysis methods for medical data to develop more efficient systems that help make better decisions for the benefit of patients.

  • Bioinformatics
  • Medicine
  • Nursing
  • Physiotherapy
  • Pharmacy
  • Optometry
  • Dentistry
  • Fitness

Finance and economics

From exploring market behaviour to managing insurance claims, apply CT to model, optimise and solve problems.

  • Actuarial
  • Accounting
  • Banking
  • Investing
  • Economics
  • Insurance
  • Auditor

Data science and business intelligence

Use CT with modern analytical techniques to arrive at better, real, quantifiable answers where traditional techniques would fail.

  • Management
  • Consultancy
  • Administration
  • Human resources
  • Statistics


From automating importing of data to high-powered analysis, apply CT to advance knowledge and expertise in your scientific field.

  • Physics
  • Biology
  • Chemistry
  • Maths
  • Astronomy

Media and the arts

Use CT to realistically model natural events, create animations, design patterns or generate 3D sculptures.

  • Publishing
  • Authoring
  • Marketing
  • Music
  • Game design

Law and social sciences

Analyse social networks, model behaviours and carry out meaningful analysis of socioeconomic data to benefit human society and culture.

  • Psychology
  • Charity
  • Counselling
  • Social work
  • Teaching


Whether it is climate change prediction, alternative energy development or pollution modelling, effectively plan to preserve the environment with CT.

  • Farming
  • Conservation
  • Waste management
  • Geoscience

Communications and security

Develop innovative algorithms for efficient information transfer and data security through applying the CT process.

  • Military
  • Telecommunications
  • Cryptography
  • Security
Contact us to introduce computational thinking »