The Real Reason Why Everyone Should Learn to Code

"Everyone in this country should learn to program a computer, because it teaches you to think." This bold proclamation by visionary Apple co-founder Steve Jobs cuts to the heart of the "learn to code" movement. But let‘s be clear – when leaders like Jobs advocate for universal coding education, they don‘t expect everyone to become a professional software engineer. Rather, the real reason everyone should learn the basics of coding is because it imparts foundational problem-solving skills and ways of thinking that are immensely valuable for all.

At its core, programming is about breaking down complex problems into a logical series of steps that can be carried out by a computer. This decomposition process requires analytical and systematic thinking. Writing code demands precision, as one misplaced character or flawed line of logic can derail an entire program. Persistence is key, as debugging broken code can be a lengthy trial-and-error process. At the same time, programming rewards creativity in crafting elegant and efficient solutions. All of these skills – problem decomposition, logical reasoning, attention to detail, perseverance, and innovation – are eminently transferable to any academic or professional pursuit.

Consider a statistic often cited by "learn to code" advocates: 65% of today‘s grade school kids will ultimately end up working in careers that haven‘t even been invented yet. In a world of rapid technological change, the specifics of what students learn today may quickly become outdated. But the deeper skills of computational thinking will be evergreen. When we teach kids to code, we‘re not just training the next generation of software engineers – we‘re empowering them with an essential 21st century literacy.

The applications of computational thinking extend far beyond the realm of software. Google chief economist Hal Varian has called statistician the "sexiest job in the next 10 years" due to the explosion of digital data and the need for people who can make sense of it all. Grappling with large, unstructured data sets requires many of the same skills used in programming – breaking down a complex problem into manageable pieces, filtering signal from noise, and stepping through a logical analytical process.

In the field of finance, algorithmic trading now accounts for the majority of trading volume in US markets. These sophisticated computer programs execute trades in milliseconds, capitalizing on fleeting market inefficiencies. The "quants" who design these algorithms utilize advanced statistics, machine learning, and other computational methods to wring profits from the market. While a financial analyst may never directly write code, understanding the basics of how these systems work is increasingly essential.

Even fields as ancient as law are not immune to the digitization sweeping through industry. Legal analytics platforms are using natural language processing and machine learning to automate document review and identify relevant case law precedents. Some speculate that algorithms may one day replace many entry-level attorney tasks. An understanding of computational thinking can help lawyers adapt to these disruptive technologies.

The "learn to code" movement also holds the tantalizing promise of democratizing the tech industry and expanding access to high-paying jobs. Coding bootcamps and self-guided online curricula have proliferated, allowing people to skill up for a career switch without investing in a four-year computer science degree. A 2021 Stack Overflow survey found that over 50% of professional developers had less than a bachelor‘s degree in computer science or related field.

These alternative pathways into the industry provide opportunities for those from underrepresented groups to break into tech. Around 40% of bootcamp graduates are women, compared to only 20% of computer science bachelor‘s degree recipients. Increased diversity is not only a moral imperative, it‘s good for business – McKinsey research shows that diverse companies are more likely to outperform less diverse peers.

Of course, not everyone has the aptitude or desire to become a professional coder, and that‘s okay. Coding is not a panacea, and mandating that everyone must code risks alienating those who struggle with it. The goal should be to give everyone exposure to coding concepts and computational thinking, not to force everyone down a narrow vocational path.

In an increasingly digital world, fluency with computing is a fundamental skill on par with traditional reading, writing, and arithmetic. Programming proficiency exists on a spectrum, and even a basic grounding in coding concepts can pay dividends. As the pioneering computer scientist Alan Perlis put it half a century ago, "To understand a program you must become both the machine and the program." Learning to code is as much about absorbing a new mindset as it is about acquiring a concrete skill set.

Seymour Papert, the influential computer scientist and educator, coined the term "computational thinking" back in 1980. He envisioned computing as the "children‘s machine," an immensely powerful tool and learning aid that should be accessible to all. Papert developed the LOGO programming language specifically to teach children mathematical and computational concepts.

In many ways, we have still not fully realized Papert‘s vision. Computing education remains patchy and inequitable. A 2021 report by Code.org found that only 51% of high schools in the US offer computer science, with lower rates in schools with high percentages of economically disadvantaged students. We must continue to advocate for universal access to coding education, following the model of initiatives like Code.org‘s "Hour of Code."

Fortunately, it‘s never been easier to get started with coding. Online platforms like freeCodeCamp and Khan Academy offer free, self-paced coding courses for all ages and skill levels. Scratch, the block-based programming language, allows kids to start coding with minimal onboarding. More advanced beginners can dive into web development fundamentals with HTML, CSS, and JavaScript. The sheer wealth of resources can be overwhelming, but the key is to just start tinkering and let curiosity be your guide.

Ultimately, learning to code is about so much more than becoming a programmer. It‘s about developing a powerful toolkit for solving problems and an empowering new way of understanding the increasingly computerized world around us. It‘s about learning to think computationally – precisely, logically, and creatively. As Steve Jobs knew well, that‘s a skill that will serve everyone well, no matter where their path leads. Let‘s make his vision a reality.

Some key coding education statistics:

• Only 51% of US high schools offer computer science (Code.org)
• In 2021, there were nearly 3.5 million students enrolled in Code.org courses
• Over 100 million students have participated in the "Hour of Code" worldwide
• 40% of coding bootcamp graduates are women, compared to 20% of CS degree recipients
• Median salary for coding bootcamp graduates is $75,000 (Course Report)
• Software developer jobs projected to grow 22% 2020-2030 (Bureau of Labor Statistics)

Learn more and get started:

• freeCodeCamp.org
• Code.org
• Scratch (scratch.mit.edu)
• Khan Academy Computer Programming (khanacademy.org/computing/computer-programming)
• Codecademy