Early Learning Strategies for Developing Computational Thinking Skills for 2025

by Imed Bouchrika, Phd

Co-Founder and Chief Data Scientist

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Technology is growing so rapidly that even Moore’s Law is unable to keep up. One way to stay afloat amid this technological surge is to be equipped with a skill known as computational thinking. While the term sounds rather overwhelming, Jeanette Wing, a leader in computer science, famously defines it simply as “thinking like computer scientists."

Computational thinking is highly relevant to those interested in technology careers, or more generally, STEM careers. Educators like Wing also argue that computational thinking is a fundamental skill that must be taught to every student from a young age.

In this article, the definition, concepts, and importance of computational thinking skills for kids will be discussed. Readers will also be introduced to early learning strategies for computational skills and related resources that may be helpful to educators.

Early Learning Strategies for Computational Thinking Table of Contents

1. What is Computational Thinking
2. Four Cornerstones of Computational Thinking
3. Strategies for Teaching Young Learners about Computational Thinking
4. The Role of Play in Developing Computational Thinking
5. How Can Computational Thinking Enhance Interdisciplinary Studies?
6. How Can Computational Thinking Drive Innovation in Creative Fields?
7. Computational Thinking Resources for Educators
8. Importance of Computational Thinking for Modern Students
9. How Can Computational Thinking Elevate Higher Education Research?
10. How Can Educators Overcome Implementation Challenges in Computational Thinking?
11. How Can Computational Thinking Enhance Organizational Leadership?
12. How Can Computational Thinking Strengthen Library Science Careers?

What is Computational Thinking

In 2006, Jeanette Wing published an essay in the Communications of the ACM, which resulted in the emergence of discussions around the importance of educating not just computer science majors, but all students, about computational thinking. Selby and Woolard (2014) argued that the essay lacked a solid definition of computational thinking and examined existing literature regarding this concept to be able to propose one that can guide the design and evaluation of curricula.

Upon going through the publications post-2005, they came up with the following definition: “Computational thinking is a focused approach to problem-solving, incorporating thought processes that utilize abstraction, decomposition, algorithmic design, evaluation, and generalizations" (Selby and Wooland, 2013).

More recent articles, such as BBC’s “Introduction to computational thinking," state that computational thinking is a thought process with mainly four components. These components will be discussed further in the next section.

Four Cornerstones of Computational Thinking

Computational Thinking has four cornerstones, namely, (1) Decomposition, (2) Pattern Recognition, (3) Abstraction, and (4) Algorithmic Thinking. This section will define each component, give real-world examples, and discuss how these computational thinking strategies can be applied in various subjects.

Decomposition

In the process of decomposition, complex systems are broken down into smaller parts, making the task of dealing with the whole more manageable.

Imagine having to eat a whole cake all at once. Without decomposition, one is hard-pressed to deal with a problem that seems more overwhelming than it has to be. Slicing the cake and taking one bite at a time is the more logical response to the task at hand.

Decomposition is the process of simplifying problems by dealing with their parts one at a time. We encounter it in our everyday lives and it comes in handy when needing to study almost all subjects. In Science, for instance, when studying human organ systems, we focus on one system at a time. We further break down the task by studying each organ under one system.

Pattern Recognition

After decomposing a problem, it is useful to examine the smaller parts for similarities with previously encountered ones.

We can solve problems and make sense of new information by recognizing patterns. For example, we use pattern recognition to learn how to navigate new software applications. Our memory of using other applications guides us in learning which buttons to click to perform what specific actions.

Teaching pattern recognition in school is essential for students to learn things, especially on their own. It is the key to many important learning milestones, from determining what shape an object is to gauging whether a poem is a haiku or not.

Abstraction

Once we recognize the existing patterns in a problem, we can focus on the parts that will lead us to solve it. This process of filtering out what is irrelevant to the task at hand is called abstraction.

The maps we commonly encounter in geography classes are examples of abstraction. In each map, cartographers decide which information to include and which to exclude. Only information relevant to their objectives will be represented on the map. For example, in this Coronavirus World Map, information such as the number of cases per capita, total number of deaths, and average daily cases are all relevant. Meanwhile, it would not make sense to include the physical or cultural features of the places on this particular map.

Algorithmic Thinking

With algorithmic thinking, an individual determines the step-by-step process for solving a problem. We use algorithms or sequential rules to follow in our daily lives. These include the recipes we use for preparing food at home, the standard operating procedures we follow at work, and the lending/borrowing system in place at school libraries.

Algorithms are useful not just in computer science but also in other subjects. In mathematics, we often have to use algorithmic thinking in solving equations. In history, we often have to think about the sequence of events as well as how specific inputs culminate into specific outputs.

Strategies for Teaching Young Learners about Computational Thinking

So, how to improve computational thinking? In their article titled “How to learn and how to teach computational thinking: Suggestions based on a review of the literature," Hsu, Chang, and Hung (2018) outline 16 computational strategies. They found that the four most commonly used strategies are problem-based learning, project-based learning, collaborative learning, and game-based learning.

Problem-based learning

Problem-based learning is the most common strategy used for developing computation skills. In this approach, educators introduce an open-ended problem that students try to solve using prior knowledge and experience. Much like competency-based education, activities here are centered on the development of a set of skills that they can use to solve real-world problems.

Computational thinking problem solving can help students to think critically, ask the right questions, and enumerate several solutions on their own. It can also help educators facilitate the flow of discussions on the problem at hand.

Project-based learning

Like in problem-based learning, students in a project-based approach are also introduced to a problem. The main difference is that they are then challenged to come up with an output that stands as their solution.

A proponent of project-based learning, John Dewey, championed “learning by doing." As students explore the possible solutions to a problem and design a project, they also develop critical thinking, communication skills, and collaboration skills.

Educators may use project-based learning to develop computational thinking among students. Thinking computationally can help students come up with a systematic approach to designing a solution.

Collaborative learning

Compared to the first two strategies, collaborative learning is more focused on the idea of working together to solve a problem. Students are challenged to grow not only intellectually but also socially and emotionally. In the process, they learn skills that they can apply to real-world employment situations, where communication and collaboration skills often give an individual an upper hand.

Fostering computational thinking in a collaborative learning environment means that students will be exposed to other perspectives. They will get a chance to work with their peers to solve more complex problems that may be a challenge to solve all on their own.

Game-based learning

Now, you may be thinking about how to develop computational thinking in a game-based learning. Well, educators design games with a set of learning objectives in mind. Games can come in several forms, such as board games, card games, role-playing games, and puzzles. One popular option today is digital game-based learning, which some argue, is the future of learning.

Educators can design or source games specifically designed to develop computational thinking skills. In a game-based learning setup, students will be more engaged and free to commit mistakes without risks or serious academic consequences.

The Role of Play in Developing Computational Thinking

Play is an essential tool for developing computational thinking skills in young learners. By integrating play into learning activities, educators can help children grasp key concepts like problem-solving, pattern recognition, and algorithmic thinking in a fun and engaging way. Here are five ways play supports the development of computational thinking:

• Encourages Problem-Solving Skills: Games often require players to break down complex problems into smaller, manageable parts, which aligns with the computational thinking process of decomposition. Puzzles and strategy games are great for teaching children how to approach challenges step by step, enhancing their problem-solving abilities.
• Develops Pattern Recognition: Many games, like memory or matching games, require children to recognize patterns. This helps students practice the crucial skill of identifying sequences and making predictions. Recognizing patterns is foundational for computational thinking, as it aids in organizing data and making informed decisions.
• Teaches Algorithmic Thinking: Games that involve following instructions or rules, such as "Simon Says" or board games, help children understand algorithmic thinking. They learn the importance of following steps in a specific order, which is essential for solving problems systematically in computational thinking.
• Promotes Collaboration and Communication: Collaborative games encourage communication and teamwork, allowing children to practice skills necessary for effective group problem-solving. These games teach children how to express ideas clearly, listen to others, and share solutions—valuable skills in computational thinking and real-life situations.
• Stimulates Creativity and Flexibility: Unstructured play, such as role-playing or creative games, allows children to experiment with different approaches to problem-solving. It encourages flexibility in thinking, helping them learn to adapt and approach problems from various perspectives, which is essential for computational thinking.

How Can Computational Thinking Enhance Interdisciplinary Studies?

Computational thinking extends beyond STEM by offering structured problem-solving methods that enhance critical analysis in diverse academic fields. Its systematic approach supports the interpretation of complex information—a perspective useful in subjects like history, social sciences, and the humanities. For example, applying computational techniques to literary analysis can enrich understanding and interpretation, as exemplified by pursuing an English degree. This integration fosters versatile skill sets and encourages students to harness logical reasoning across traditional academic boundaries.

How Can Computational Thinking Drive Innovation in Creative Fields?

Computational thinking extends its systematic approach beyond traditional STEM applications to empower creative professionals. By applying techniques such as abstraction and algorithmic sequencing, individuals in creative industries can structure their ideation process, streamline iterative revisions, and uncover novel connections. This methodical creativity enables professionals—from graphic designers to writers—to transform complex creative challenges into manageable projects. For those exploring educational pathways that combine analytical rigor with creative expression, consider the cheapest online creative writing degree as a cost-effective option.

Computational Thinking Resources for Educators

According to an article published in the NSF Public Access Repository titled, “Workshops and Co-design Can Help Teachers Integrate Computational Thinking into Their K-12 STEM Classes," computational thinking can be more successfully integrated into classes if teachers are engaged in the process of curriculum design. The authors noted that “..engaging high school STEM teachers in workshops and co-design of CT-STEM curricula in a 4-week professional development can help them develop an understanding of CT and integrate CT into their classroom. We are particularly encouraged by the fact that although these eight teachers already valued CT at the beginning of the workshop because they chose to participate in the professional development, all teachers reported even more favorable perceptions of CT and greater confidence in integrating it into their classroom at the end of the professional development" (Wu, et al., 2020). 

Below are curated materials to help teachers become more involved in the advancement of computational thinking. The more they are able to grasp these materials, the better they will be able to incorporate computational thinking into the classroom and educate children about the concepts and practices of thinking computationally.

Books

• Computational Thinking in Education: A Pedagogical Perspective, edited By Aman Yadav and Ulf Dalvad Berthelsen, discusses the history and practices of computational thinking in primary and secondary education.
• Teaching Computational Thinking: An Integrative Approach for Middle and High School Learning, by Maureen D. Neumann and Lisa Dion, explores how computational thinking can be incorporated into various subjects.
• Teaching Computational Thinking and Coding to Young Children by Marina Bers delves into the importance of teaching computational thinking to students at an early age.
• Research Anthology on Computational Thinking, Programming, and Robotics in the Classroom is a 41-chapter book by the Information Resources Management Association that goes beyond computational thinking, into educational technologies, STEM education, coding, robot learning, and more.
• Fostering Computational Thinking Among Underrepresented Students in STEM: Strategies for Supporting Racially Equitable Computing by Jacqueline Leonard, Jakita O. Thomas, Roni Ellington, Monica B. Mitchell, and Olatokunbo S. Fashola focuses on computational thinking as incorporated in project-based learning environments, particularly as experienced by underrepresented K-12 STEM students.

Websites

• PBLWorks by the Buck Institute for Education is a great website resource for designing and implementing computational thinking activities in a project-based learning setup.
• WolframAlpha is a computational engine that can be used to demonstrate the relationship between computational thinking and various subjects, such as mathematics, science and technology, and society and culture, as well as everyday life.
• Code.org is a popular resource for teaching K-12 students how to code and at the same time think computationally. It has reached a diverse population of students all over the world. Its professional learning programs have also been used by more than 100,000 new computer science teachers.
• Digital Promise has a set of articles dedicated to discussing computational thinking, its concepts, benefits, and integration strategies.
• Computer Science Unplugged is a reliable resource for incorporating computational thinking into activities that do not involve the use of gadgets.

Online Courses

• Commonwealth for Learning put together an introductory course on computational thinking for teachers.
• Google, together with the International Society for Technology in Education and Australian Digital Technologies Hub, offers digital resources on computational thinking for teachers, including a 15-hour self-paced introductory course and a set of lesson ideas.
• The University of Maine offers a fully-online 12-credit graduate certificate in computational thinking for educators.
• The University of Canterbury through edX offers a free self-paced online course titled, Teaching Computational Thinking, which enrollees can complete in five to 10 weeks.
• Purdue offers a computational thinking certification program for secondary education teachers.

Importance of Computational Thinking for Modern Students

Students have much to gain from learning about computational thinking. They can apply its concepts at school and in the real world. Here are some of the ways computational thinking can prove to be valuable to modern students:

1. Computational thinking is a fundamental skill that can be applied to various subjects. As demonstrated in the sections above, computational thinking serves not only computer science but also every other subject in school. Introducing computational thinking to students will allow them to become independent learners. By thinking computationally, students will be able to critically and systematically analyze problems and come up with solutions. They can apply this to almost every school task, especially for ones that involve research.
2. Computational thinking allows students to approach everyday tasks in a more systematic way. Every individual unknowingly uses computational thinking in daily life. Consciously applying the concepts will only make students more efficient in solving problems, creating plans, and accomplishing tasks. More than just good grades, this has far-reaching positive implications in their futures.
3. Computational thinking prepares students for life after school. The fourth industrial revolution created workplaces with a demand for a set of competencies that computational thinking can help hone. Along with different learning strategies, computational thinking can help develop critical thinking skills, communication skills, collaboration skills, time management skills, and organization skills, to name just a few. With the incorporation of computational thinking in the curriculum, schools can churn out students who are future problem-solvers, leaders, innovators. and change-makers.

Make Young Learners Future-Ready with Computational Thinking

Not every child has access to devices, but every child can learn how to think computationally. As discussed, computational thinking is not as hard as it sounds. It consists simply of decomposing problems, finding patterns, filtering out irrelevant information, and designing a process. These same concepts govern our tech-driven world.

By introducing computational thinking to young learners at schools, we can make sure that our global society will be more equitable in the future. Every child will have a chance to catch up with the waves of the fourth industrial revolution.

How Can Computational Thinking Elevate Higher Education Research?

Integrating computational thinking into higher education advances analytical rigor and cross-disciplinary research by enabling higher education professionals to break down complex academic challenges using algorithmic approaches. This systematic method supports evidence-based decision-making in curriculum development, research methodologies, and policy formulation. It also refines data analysis by fostering innovative strategies for managing and interpreting large-scale academic data. Academics can further enhance their expertise through specialized programs, such as pursuing a doctorate in higher education online, which equips them with targeted skills to drive strategic innovation in higher education.

How Can Educators Overcome Implementation Challenges in Computational Thinking?

Educators often encounter obstacles such as limited training, tight curricular schedules, and difficulties integrating computational thinking into diverse subject areas. Addressing these issues involves targeted professional development, clear alignment of computational strategies with learning outcomes, and the creation of supportive peer networks to share best practices. For instance, enrolling in advanced leadership courses—such as those offered through online EdD programs no dissertation—can equip educators with innovative approaches to seamlessly incorporate computational thinking into their classrooms while ensuring continuity with existing curricula.

How Can Computational Thinking Enhance Organizational Leadership?

Computational thinking equips leaders with a systematic approach to dissect complex challenges and analyze large data sets for informed decision-making. By applying abstraction and algorithmic reasoning, leaders can identify core issues, streamline processes, and foster innovation throughout their teams. This method not only supports effective strategic planning but also augments cross-functional collaboration, resulting in more agile and resilient organizations. Exploring advanced leadership studies—such as an online doctorate organizational leadership program—can further empower leaders to integrate computational thinking into their decision-making frameworks.

How Can Computational Thinking Strengthen Library Science Careers?

In an era defined by digital transformation, computational thinking equips library science professionals with strategies to manage, classify, and retrieve vast volumes of digital data. By applying abstraction and algorithmic reasoning, librarians can optimize digital archiving, automate metadata classification, and enhance resource discovery processes. These skills not only refine traditional cataloging methods but also foster innovation in developing user-centered digital platforms. For those aiming to integrate these advanced techniques into their careers, exploring the cheapest MLIS programs can be a strategic step towards mastering the intersection of technology and information management.

How Can Computational Thinking Empower Educational Leadership?

By integrating computational thinking into educational leadership, decision-makers can enhance strategic planning through data-driven insights and systematic problem-solving techniques. Leaders can utilize abstraction and algorithmic approaches to dissect complex administrative challenges and streamline resource allocation effectively. This method supports agile policy development and fosters a culture of continuous improvement within educational institutions. Furthermore, programs such as affordable online educational leadership programs provide advanced training that merges analytical reasoning with proven leadership strategies, equipping leaders with the tools to drive innovative educational transformations.

Key Insights

• Definition and Importance: Computational thinking, defined as "thinking like computer scientists," is crucial for both technology and STEM careers, and is argued to be a fundamental skill for all students.
• Four Cornerstones: Computational thinking comprises decomposition, pattern recognition, abstraction, and algorithmic thinking, which help in breaking down complex problems, identifying similarities, filtering out irrelevant details, and designing step-by-step solutions.
• Teaching Strategies: Effective strategies for teaching computational thinking include problem-based learning, project-based learning, collaborative learning, and game-based learning, all of which encourage critical thinking, creativity, and teamwork.
• Educational Resources: A variety of resources are available to educators, including books, websites, and online courses, to help integrate computational thinking into their teaching practices.
• Student Benefits: Learning computational thinking equips students with problem-solving skills applicable to various subjects and everyday tasks, prepares them for future job markets, and fosters independent learning and critical thinking.
• Equity in Education: By teaching computational thinking to all students, regardless of their access to technology, educators can help bridge the digital divide and prepare every child for the future.

FAQ

1. What is computational thinking?
Computational thinking is a problem-solving approach that involves breaking down complex problems, recognizing patterns, focusing on relevant details, and designing algorithms or step-by-step solutions. It is a fundamental skill for understanding and solving problems in various domains, not just computer science.

2. Why is computational thinking important for students?
Computational thinking is important because it helps students develop critical thinking and problem-solving skills that are applicable across different subjects and in real-life situations. It prepares them for future careers, particularly in STEM fields, and equips them with the ability to approach tasks systematically and efficiently.

3. How can teachers incorporate computational thinking into their classrooms?
Teachers can incorporate computational thinking through various strategies such as problem-based learning, project-based learning, collaborative learning, and game-based learning. Utilizing resources like books, websites, and online courses can also aid in integrating these concepts into the curriculum.

4. What are some real-world examples of computational thinking?
Real-world examples of computational thinking include:

• Decomposition: Breaking down a project into smaller tasks.
• Pattern Recognition: Identifying trends in data to make predictions.
• Abstraction: Creating a simplified model of a complex system.
• Algorithmic Thinking: Developing a step-by-step plan to solve a problem, like a recipe for cooking.

5. Can computational thinking be taught without using computers?
Yes, computational thinking can be taught without computers. Activities like puzzles, board games, and role-playing games can help develop these skills. The focus is on the thought processes involved rather than the use of technology.

6. How does computational thinking benefit students outside of STEM fields?
Computational thinking benefits students in all fields by enhancing their ability to analyze problems, think critically, and develop structured solutions. It promotes skills such as logical reasoning, creativity, and effective communication, which are valuable in any discipline.

7. What resources are available for educators to learn more about computational thinking?
Educators can access a variety of resources, including books like "Teaching Computational Thinking: An Integrative Approach for Middle and High School Learning," websites like Code.org and PBLWorks, and online courses from institutions like Google and the University of Maine. These resources provide strategies and materials for teaching computational thinking effectively.

References:

1. Hsu, T.-C., Chang, S.-C., & Hung, Y.-T. (2018). How to learn and how to teach computational thinking: Suggestions based on a review of the literature. Computers & Education, 126, 296310. Retrieved from https://doi.org/10.1016/j.compedu.2018.07.004
2. Selby, C. C., & Woollard, J. (2013). Computational thinking: The developing definition. In Presented at the 18th annual conference on innovation and Technology in Computer Science Education, Canterbury. Retrieved from https://core.ac.uk/download/pdf/17189251.pdf
3. Tekdal, M. (2021). Trends and development in research on computational thinking. Education and Information Technologies, 26(5), 64996529. https://doi.org/10.1007/s10639-021-10617-w 
4. Wing, J. (2014). Computational Thinking Benefits Society. 40th Anniversary Blog of Social Issues in Computing. Retrieved from https://www.cs.cmu.edu/~15110-s13/Wing06-ct.pdf
5. Wu, S., Peel, A., Bain, C., Anton, G., Horn, M., & Wilensky, U. (2020). Workshops and Co-design Can Help Teachers Integrate Computational Thinking into Their K-12 STEM Classes. Proceedings of International Conference on Computational Thinking Education 2020. Retrieved from https://par.nsf.gov/biblio/10203763