Computational thinking skills are increasingly critical for individuals and organizations as the use of computation becomes more central to every activity and every innovation. As computers become more intelligent, rather than reducing the requirements of human understanding, they have accelerated it. Unlocking ever-more-insightful answers means driving the computer with new computational thinking skills.

ComputationalThinking.org delivers learning programs for everyone. Our pioneering approach is not only about coding, math you may have missed and critical thinking, but also the underlying core computational thinking that drives all of them—for example, applied to life skills, data science and modeling.

ComputationalThinking.org is partnered with Wolfram Research and gains its expertise of more than 30 years as the world-leading organization in computation at every level and in every way: as users, employers, technology suppliers and innovators.

Ways we can help

The what, where, how of computational thinking

What?

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

Where?

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.

How?

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
Using image processing to spot differences in fingerprints Making predictions from existing data Modelling hurricanes Analyzing big data Mapping the orbits of Earth’s man-made satellites Looking for patterns in New York City traffic accidents Using geo-elevation data Mapping the Brexit vote

What is 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. The emphasis is learning how to take real-life situations and translate—often to programs—so a computer can calculate the answer.

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. The emphasis is learning how to take real-life situations and translate—often to programs—so a computer can calculate the answer.

  • Define

    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.

  • Translate

    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.

  • Compute

    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.

  • Interpret

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

  • Define

    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.

  • Translate

    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.

  • Compute

    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.

  • Interpret

    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 optimize their techniques based upon the latest computation, providing innovative output for analysis.

Sectors

Fields

Engineering

Use CT to design, simulate, model, optimize and predict the behavior 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 behavior to managing insurance claims, apply CT to model, optimize 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

Science

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

  • Physics
  • Biology
  • Chemistry
  • Math
  • 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

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

  • Psychology
  • Charity
  • Counseling
  • Social work
  • Teaching

Environmental

Whether it is climate change prediction, alternative energy development or pollution modeling, 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
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