top of page
  • Writer's pictureNicky

10 essential techniques you must use to help students master computational thinking

In today's rapidly evolving digital world, teaching students the fundamentals of computational thinking has become increasingly essential. As a busy teacher, finding algorithmic thinking examples and teaching activities that promote student engagement can be a challenge.

In this blog post, we'll delve into the concept of computational and algorithmic thinking, explore its benefits to students beyond the computing classroom.

Understanding computational thinking

Computational thinking refers to the cognitive process of approaching and solving problems in a logical and systematic manner, similar to how a computer would solve a problem.

It encompasses a range of skills, including problem decomposition, pattern recognition, algorithm design and abstraction. By developing computational thinking skills, students can become better equipped to tackle complex problems, think critically and excel in an increasingly digital society.

Empowering students with computational thinking

Computational thinking skills are highly transferable and can benefit students in various subjects beyond computer science. Here are a few examples:

  • Mathematics: Computational thinking involves breaking down complex problems into smaller, more manageable parts. This approach aligns with problem-solving techniques used in mathematics. Students can apply their computational thinking skills to analyse and solve mathematical problems by identifying patterns, developing algorithms and applying logical reasoning.

  • Science: Scientific inquiry often involves collecting and analysing data, identifying patterns and developing logical explanations. Algorithmic thinking skills enable students to approach scientific investigations systematically, design experiments and analyse data using computational tools. They can also use algorithms and modelling techniques to simulate scientific processes.

science algorithms
  • Language Arts: Computational thinking promotes logical and structured thinking, which can be beneficial in language arts subjects. Students can use these skills to analyse and dissect complex texts, identify patterns in literature and develop logical arguments and reasoning in their writing.

  • Humanities: Algorithmic thinking skills can enhance data analysis and interpretation in humanities subjects such as history, geography and RE. Students can use computational tools to collect, analyse, and visualise data, identify trends and patterns and make informed predictions or conclusions based on the data.

  • Art and Design: Computational thinking can be applied creatively in art and design disciplines. Students can use algorithms to generate visual patterns, explore procedural art or create interactive installations. Computational thinking encourages students to think outside the box and find innovative ways to express their artistic ideas.

  • Problem-Solving in General: Computational thinking skills, such as breaking down problems, analysing patterns and designing algorithms, are valuable in almost any subject or real-life situation. Students can use these skills to approach challenges in any field, from personal problem-solving to decision-making and critical thinking.

By incorporating computational thinking skills into their learning, students gain a set of problem-solving strategies and a structured approach to thinking that can be applied across multiple subjects and even in their everyday lives. It promotes a holistic and versatile mindset that prepares them to tackle challenges and make informed decisions in any field of study or career path they choose to pursue.


How can you teach computational thinking skills?

Teaching computational thinking skills involves incorporating specific strategies and activities into the classroom to develop students' problem-solving abilities and logical reasoning. Here are the 10 essential techniques you must use to help students master computational thinking in your classroom:

  1. Decomposition: Teach students to break down complex problems into smaller, more manageable parts. Provide them with opportunities to identify the key components of a problem and analyse how these components interact. Encourage them to create flowcharts or diagrams to visually represent the problem's structure.

  2. Pattern Recognition: Help students identify patterns, trends and regularities within problems or datasets. Engage them in activities that involve finding similarities, repetitions or sequences. This skill supports the development of algorithmic thinking and logical reasoning.

  3. Abstraction: Guide students in recognising essential details while filtering out irrelevant information. Help them identify commonalities among different problems or situations and focus on the underlying concepts or principles. This skill encourages students to think in terms of general patterns and rules.

  4. Algorithm Design: Introduce students to the concept of algorithms as step-by-step instructions for solving problems. Teach them how to develop algorithms by breaking down tasks into logical, sequential actions. Provide opportunities for them to create and refine algorithms for various problems.

  5. Algorithmic Thinking: Encourage students to think algorithmically by considering alternative solutions, predicting outcomes and evaluating the efficiency and effectiveness of different approaches. Foster a mindset that values creativity and multiple strategies for problem-solving.

  6. Collaborative Problem-Solving: Promote teamwork and collaboration by engaging students in group activities that require them to apply computational thinking skills collectively. Assign tasks that involve brainstorming, sharing ideas, and reaching consensus on problem-solving strategies.

  7. Integration of Technology: Use programming languages, visual coding platforms or computational tools to enable students to implement their computational thinking skills in a practical manner. Platforms like Scratch, Python or Blockly can be excellent resources for hands-on learning experiences.

  8. Real-World Connections: Emphasise the relevance and application of computational thinking in real-life contexts. Connect computational thinking skills to everyday situations, careers and other subjects to help students understand their practical value beyond the computer science classroom.

  9. Reflective Practice: Encourage students to reflect on their problem-solving processes and outcomes. Help them analyse their own thinking strategies and identify areas for improvement. Foster a growth mindset that values learning from mistakes and embracing challenges.

  10. Integration Across Subjects: Look for opportunities to integrate computational thinking skills into other subjects. Collaborate with colleagues to create cross-curricular projects that emphasise problem-solving, data analysis and logical reasoning.

Flow diagram

By implementing these strategies and providing engaging activities, teachers can foster the development of computational thinking skills in their students. It is important to create an environment that encourages exploration, creativity, and critical thinking, enabling students to become confident problem solvers equipped for success in the digital age.

One of our most popular resources, the Computational Thinking Escape Room, offers an immersive and interactive learning experience for students who are starting to learn programming. This escape room activity not only reinforces key computational thinking concepts but also enhances teamwork, communication and problem-solving skills. By incorporating this engaging resource into your classroom, you can provide a dynamic and memorable learning opportunity that requires minimal preparation.

Computational Thinking Escape Room TES

Computational thinking Escape Room TpT

In addition to the Computational Thinking Escape Room our Algorithms Worksheet bundle is designed to support teachers in delivering effective Python programming lessons. These worksheets cover various topics, from algorithm design to algorithmic thinking and provide ready-to-use exercises that help promote computational thinking skills, pseudocode and algorithms when learning how to program with Python.

TES Algorithms Worksheets

TPT Algorithms Worksheets

With these resources at your disposal, you can significantly reduce your planning time while delivering high-quality lessons that promote student understanding and retention.

Integrating computational thinking into your teaching practice empowers students with essential skills for the digital age. We understand the challenges you face as busy teachers and our resources, offer a time-saving solution without compromising on quality.

You can unlock the true potential of computational thinking in your classroom, enabling students to thrive in an ever-changing world.

Click here to learn 3 simple tricks to immediately improve your programming lessons

Python programming

Featured Posts
Recent Posts
Search By Tags
Follow Us
  • Facebook Basic Square
  • Twitter Basic Square
  • Google+ Basic Square
  • Pinterest Social Icon
bottom of page