The Enduring Relevance of Coding in the Age of Artificial Intelligence
In a recent statement that captured the tech world’s attention, Nvidia’s CEO Jensen Huang suggested that the advent of AI might render coding skills less critical, hinting at a future where jobs in coding could see a decline. This bold assertion sparks a crucial conversation about the place of coding and computer science in our schools. While the advancements in AI are undeniable, equating them to the obsolescence of coding is both premature and overlooks the essence of computer science as a fundamental discipline.
My First Coding Lesson
During my time in the classroom, I always struggled with group work. My students rarely had impactful collaborations. Instead, one student would do most of the work, another would be unengaged, and the third person was involved in some mischief. This paradigm changed when my students programmed a robot for the first time. It was a relatively simple exercise — code the robot to move in a square. I had one group of students measure the size of the square and use that information to code their robot. I had another group of students experiment with coding the robot to move for a certain amount of time. All of the students were engaged, being iterative, and having great conversations.
That was the moment I fell in love with teaching STEM. Students weren’t just working together, they were moving beyond my initial ideas for the lesson. Students didn’t just work in their group — they were asking questions of other students in the class about their code. That assignment literally changed my life. This is what I ponder when I read the assertions that AI will diminish the need to teach coding. The assertion, arguably, makes sense if coding, or computer science, is viewed as a job skill. Job skills are important, but so are mediums.
Coding to Learn
Seymour Papert, a visionary computer scientist and educator, was born in Pretoria, South Africa, in 1928. A protégé of Jean Piaget, Papert’s work was deeply influenced by Piaget’s theories of learning and development. Papert’s educational and professional journey led him to the Massachusetts Institute of Technology (MIT), where he co-founded the MIT Media Lab. He was instrumental in the development of the Logo programming language in the 1960s, designed to transform the way children think and learn.
Papert’s pioneering concept of “constructionism” emerged from his belief that learners construct knowledge most effectively through active engagement in designing and creating tangible objects. His influential book, “Mindstorms: Children, Computers, and Powerful Ideas”, presented his revolutionary ideas on how computers could empower children to learn and understand the world around them through exploration and creation.
At the heart of Seymour Papert’s revolutionary approach to education through coding was the idea that coding is a medium of expression, akin to writing or drawing. Papert’s constructionism suggested that coding could help students learn to think creatively, systematically, and logically. Coding, in this light, becomes a tool for articulating complex ideas, fostering a mindset that encourages problem-solving and innovation. It teaches learners to break down complex problems, iterate over solutions, and articulate their thoughts in a structured, logical manner, which are invaluable skills in any field of study or work.
Teaching coding, especially to young learners, can also have a positive impact on students’ spatial reasoning skills. The work of Claire Cameron illustrates the importance of spatial reasoning for school readiness, math, and literacy skills. There is growing evidence that coding helps students increase their spatial reasoning skills, thus a strong case could be made that teaching students to code has a positive impact on skills and subjects outside of the computer science curriculum.
As we champion the inclusion of coding in educational curricula, it’s crucial to address the intertwined issue of accessibility. The digital divide — a gap between those who have easy access to computers and the internet and those who do not — poses significant challenges in making coding education universally accessible. This divide is not only about physical access but also involves educational resources, teacher training, and support structures that accommodate diverse learning needs and backgrounds.
Efforts to democratize coding education must prioritize reaching underrepresented groups, including students from low-income families, rural areas, and those with disabilities. I am proud to have had the opportunity to work with Dr. Maya Israel and the University of Florida on accessibility in Computer Science education and to have the opportunity to present our work with teachers at SIGCSE TS 2024. Teachers play a pivotal role in this process and thus need professional development opportunities to learn best practices for inclusive teaching in computer science.
A common counter-argument to the indispensability of coding education is the increasing capability of AI in automating coding tasks. AI tools can generate code, optimize algorithms, and even identify bugs, seemingly reducing the need for human coders. However, this automation does not negate the need for coding literacy nor does automation address the impact of coding to learn; instead, it shifts the focus towards more complex problem-solving, creative design, and strategic thinking skills that AI cannot replicate. Just as calculators did not eliminate the need for learning mathematics, AI coding tools will not obviate the need for coding skills. Just as the invention of the printing press or the word processor did nothing to change how the process of writing helps people explore and investigate different ideas and concepts, AI coding tools cannot replace the practice of coding to learn. They will, however, change the landscape in which these skills are applied, emphasizing the creative, innovative aspects of coding over rote implementation.
We cannot be certain of the impact of AI on our lives and in our classrooms. However, I argue coding, far from becoming obsolete, is more crucial than ever. It remains a fundamental skill for understanding the principles that underpin our digital world, fostering creative problem-solving abilities, and empowering individuals to articulate complex ideas through the unique medium of code. The journey through learning to code enriches our cognitive abilities, equipping us with the tools to navigate, understand, and shape the increasingly digital landscape we inhabit.
