Computational Thinking in Education
Computers today are a medium as fundamental to our culture as writing once was. Just as the invention of the printing press expanded the capabilities of written communication and democratized access to information, the advent of computers has changed how we interact with and understand the world. This transformation creates both new challenges and new opportunities—both encapsulate the need to equip everyone with the skills to participate in the digital age.
Computational thinking (CT) plays a central role in this new educational paradigm. It allows students to engage with computers not just as users, but as creators, explorers, and innovators. Computational models, in particular, are powerful tools that facilitate deep learning and understanding of CT practices.
Jeanette Wing, a prominent advocate for CT, emphasized that computational thinking builds on the power and limits of computing processes1. It extends beyond mere coding to encompass a broader problem-solving methodology. According to Weintrop et al. science and mathematics are increasingly becoming computational endeavors2. Educational standards like the Next Generation Science Standards (NGSS) reflect this shift and highlight computational thinking as a core scientific practice.
Returning to our analogy, we can observe that computational models act as the contemporary version of the printing press, revolutionizing the way knowledge is disseminated. Through computational models, students can now simulate intricate systems, experiment with hypotheses, and visualize outcomes in unprecedented ways. Through the creation of computational models, students can analyze complex problems by breaking them down into smaller parts, identifying patterns, and devising algorithms to solve them. This immersive approach guarantees that students don’t merely scratch the surface, but immerse themselves fully in the intricacies of computational thinking.
Seymour Papert, the father of constructionism, advocated for learning environments where students actively construct knowledge through this exact type of exploration and experimentation. Computational models exemplify this constructionism approach. By engaging deeply with the content and building on their models, students develop understanding. They learn to view problems from multiple perspectives, consider various solutions, and understand the broader implications of their work.
For instance, consider the Coral Reef Cleanup project in VEXcode VR. Picture students eagerly programming a virtual robot to clean a simulated coral reef. The task begins with decomposing it, identifying the trash’s location, and figuring out how to navigate the robot to collect it. They recognize patterns in the trash distribution, optimizing the robot’s path. They focus on essential details, like the location of the trash, and ignore irrelevant ones. Finally, they develop algorithms to control the robot’s movements and sensors efficiently. Through this engaging project, students see firsthand how computational thinking can tackle real-world challenges.
Computational models also foster creativity and innovation. As students experiment with different variables, they attentively observe the intriguing behaviors that emerge and make necessary adjustments to their models. The iterative process in coding mirrors the creative process in writing, as both involve the careful revision and refinement of ideas.
By creating computational models, students can delve into CT principles and gain a more comprehensive understanding. Through immersing themselves in the content, they develop critical thinking skills and gain a comprehensive understanding of computational practices. By learning to approach problems from diverse viewpoints, they become adept at exploring multiple solutions and comprehending the larger consequences of their work. This represents a complete embodiment of Papert’s vision of learning through hands-on experiences and reflective thinking.
Computational thinking equips students to participate in the digital medium, much like literacy in writing, allowing individuals to engage with the written word. Just as education in reading and writing became essential with the spread of the printing press, so too must we prioritize CT education to prepare students for a world increasingly defined by computational technologies. Through computational modeling, students gain the tools to create, explore, and innovate, ensuring they are not just passive consumers of technology but active contributors to its development.