Computational Thinking ≠ Coding
“Coding is the enemy of computational thinking,” Stephen Wolfram announced during his keynote at the Building Learning Communities® Education Conference.
What was remarkable about this comment were the agreeable nods from the crowd. It seemed there was a collective understanding to this notion, and perhaps one that needed further reflection.
This year, the conference had several sessions focusing on computational thinking (which, I might add, is incredibly encouraging to see), and in each one I attended, a special note was added: “Coding and computational thinking are not synonymous.”
For those unfamiliar with the concept, you might want to immediately label it as coding (or, more appropriately, programming), but it goes beyond the action of writing code. As Stephen Wolfram candidly puts it, “‘Coding’ isn’t the same as computational thinking. It’s a little bit like the relation of handwriting or typing to essay writing. You (normally) need handwriting or typing to be able to produce an essay, but it’s not the intellectual core of the activity.”
If that’s the case, then what might be computational thinking? Though multiple definitions exist, the way Computational Thinking Initiatives (CTI) like to approach it is that computational thinking is the perspective on the world that assumes you have access to computational power to solve real problems, implement real ideas and answer real questions. It’s the set of strategies that makes it possible to harness your computer and other devices to really solve those problems, implement those ideas and answer those questions. We can broadly think of it as a method of formalized problem-solving.
In the same way that communicating your ideas in prose is different from the actual practice of handwriting or typing, computational thinking is different from coding and programming. A computational thinker codes, but their goal is not simply to produce a program, any more than a writer’s goal is to produce a sentence. In the same way that writers write about every topic under and above the Sun, computational thinkers compute about anything that strikes their interest. While designing and implementing code is one way to solve problems in our increasingly digital world, it is only one approach computational thinkers can employ.
As jobs continue to require technological skills, students need to be trained in necessary computational thinking in order to address future opportunities and tasks. Jobs exist for computational thinkers beyond being able to code. These roles focus on being able to analyze and address issues.
That being said, it is not necessary to have technology on hand in order to think computationally, but it sure does make it easier and more interesting to put thought into action. For this reason, CTI makes use of the Wolfram Language and Wolfram Programming Lab.
Ordinarily, educational programs with activities as varied as network analysis, building geography-based apps, applying machine learning to large datasets, exploring the chemical elements and building beautiful designs for 3D printing would need a collection of software at their disposal, differing from activity to activity. Teaching computational thinking using many technologies can be exciting, but it risks overwhelming students and instructors. It also may not achieve the depth of familiarity students will need to be creative with the same tools in the future.
CTI instead use one common language that integrates all of these capabilities consistently: the Wolfram Language. It’s a high-level language designed for computational thinking. Its notebook interface allows users to combine computation and communication, a key practice of computational thinking.
Wolfram|Alpha, which is integrated with the language, gives users access to built-in information about the world and enables anyone to get started with computational thinking with input in natural language. As the Wolfram Language has grown, it has come to include image processing, machine learning, connections to popular hardware devices like gamepads and sensors, and even a cloud infrastructure for deploying apps and websites.
For CTI, this breadth of functionality means that students designing computational fashion will speak the same language as those exploring local traffic patterns. In practice, this would empower an individual student working on computational fashion today to join some friends on their computational traffic project tomorrow and start a new computational biology research project in six months, all while using the same language.
The fact that the Wolfram Language is a high-level language that crosses domains and automates many basic tasks means that students can focus on the “thinking” part of computational thinking, making new and unexpected connections!
Our content is delivered in the form of computational explorations called AI Adventures, which are interactive computational thinking lesson plans. To bring these to students, we are providing extracurricular in-person and virtual programs, the AI League.
Our computational thinking lesson plans offer an unconventional approach with unique integration of a knowledge-based, high-level programming language that provides access to real-world data, allowing students to remove themselves from some of the laborious details of computer science but still practice using a device to solve real-world problems more efficiently.
If you want to learn more about these individual programs, visit our website. In addition, we are providing professional development resources to middle- and high-school educators to equip them with the skills to incorporate computational thinking into their classroom activities.
There is a growing consensus that with the exponential implementation of technology and automation in the workforce, computational thinking skills will be among the most important skills to have in a 21st-century world. To integrate computational thinking into current middle- and high-school curricula presents a momentous effort, especially for educators. Though, perhaps through professional development, teachers could be able to better adapt their computational thinking pedagogies and approaches based on these student needs.
Through our professional development computational thinking educator course, we hope to provide teachers with adequate training, resources and, most importantly, the confidence to implement computational thinking in their classrooms and their own lives. We’re planning for the next iteration of this course to focus on “computational X” (the “X” being a placeholder for other traditional academic fields that are beginning to/can incorporate computational aspects), addressing how to integrate this into a curriculum, as well as employing methods to improve self-efficacy and understanding to better support efforts in this challenge.
The Australian Journal of Teacher Education reported on these challenges, and thanks to their research on this, we’re hopeful that we can act on the solutions they consider and bring to fruition “communities of practice” that would allow educators to collaborate and share resources to better support each other’s efforts. Earlier this year, we hosted a series of educator roundtables, “for educators from educators” (our motto), to discuss and learn what it takes to teach computational thinking. We realized there’s something invaluable about providing educators with a space to freely discuss the struggles they’ve experienced and how to best devise a solution, whether it be about writing computational thinking lesson plans, running enrichment programs or integrating computational thinking into a course. We’ll be bringing these back later this fall; if you want to partake in these discussions, your first action should be to fill out this Get Involved form.
Computational Thinking Initiatives are fairly small, but we have the right tools, technology and people. As Stephen Wolfram charmingly puts it, “Now we have to actually get it delivered to kids all over the world in the right way.”
If you’re equally ambitious and passionate about our mission, reach out, and we can get a conversation started!
Computational Thinking Initiatives offer programs and resources to improve computational thinking skills among students everywhere. With support from a central staff of trained experts, volunteers enable the initiatives to provide leading-edge computational thinking instruction in locations across the United States and around the world through the AI League, initially concentrating on middle-school and high-school students.
Many students who would never have encountered computational thinking in school will now have access to Computational Thinking Initiatives’ enriching programs that will prepare them to be the creative, dynamic makers of our computational future.
Computational Thinking Initiatives emerged from the Wolfram Foundation, a nonprofit organization founded by Stephen Wolfram that has provided over a decade of programs in computational thinking education.
About the blogger:
Christian Rodriguez
Christian Rodriguez manages all outreach and on-the-ground efforts for Computational Thinking Initiatives. Christian has found a passion for working with children through past experiences tutoring ESL students and conducting research in a child development lab. He currently hosts adventures through the city of Boston which show the importance of formalized problem-solving to middle-school- and high-school-aged children. His goal is to show how computational thinking is relative through all professional and academic fields and to encourage this type of thinking from a young age. You can catch Christian reading about education reform and policy, advertising, and artificial intelligence.
