In the Age of Generative AI, Should Students Still Learn to Code?

article date: 11/11/2023


In recent years, the emergence of generative AI tools like ChatGPT has significantly lowered the barrier to entry for programming endeavors. These advanced AI systems can assist individuals, even with minimal programming knowledge, in creating elegant and efficient code. While a basic understanding of programming might still be necessary for deploying and debugging the code, the AI can handle a substantial portion of the coding tasks, whether it's building a website, or analyzing datasets using Python. This development brings forth a pertinent question: in this era of generative AI, is learning to code still essential?

From an educational standpoint, it's crucial to evaluate the enduring value of understanding the underlying logic of programming, often referred to as Computational Thinking. Is the problem-solving prowess required to concoct complex algorithms a vital skill to foster?

A fitting analogy could be drawn to learning Mathematics in an age where advanced calculators are readily available. It’s widely acknowledged that mastering the basics like multiplication tables and elementary mathematical concepts is indispensable. This foundational knowledge empowers individuals to tackle more complex mathematical challenges proficiently and efficiently.

Similarly, Integrating computational thinking and problem-solving through programming in the educational curriculum holds immense value as it significantly enhances students' critical thinking abilities. By navigating through complex algorithms and coding tasks, students learn to analyze problems meticulously, devise logical solutions, and evaluate the outcomes critically. This methodical approach to problem-solving is not confined to programming alone; it's a transferable skill that students can apply across a multitude of subject areas. Whether it's tackling scientific inquiries, resolving mathematical equations, or analyzing historical events, the analytical and logical framework nurtured through programming becomes a valuable asset. Moreover, the iterative process of coding—identifying issues, debugging, and refining solutions—cultivates a resilient mindset towards overcoming challenges, fostering a lifelong learning ethos. By bridging the gap between computational and critical thinking, we can prepare students to navigate the multifaceted challenges of the modern world with a robust analytical toolkit, making them not just proficient coders, but enlightened thinkers and adept problem-solvers across diverse disciplines.

It could be that what we are seeing with generative AI now is just another level of abstraction, not the end of programming. The progression towards abstracting code isn't a novel concept. Tools like Scratch, MIT App Inventor, and Blockly have been simplifying the coding process for quite some time. The advent of generative AI could be perceived as merely the next tier of this abstraction continuum. Although AI technologies are advancing, as of now, humans are still required to assemble, deploy, and debug code.

Furthermore, it's imperative to recognize that humans are still at the helm of coding the foundational algorithms upon which these AI systems are built, at least for the foreseeable future. My initial foray into experimenting with ChatGPT in late 2022 left me somewhat disheartened, questioning the essence of my coding proficiency. However, as I delved deeper, I began to appreciate the potential of this technology. It can act as a catalyst, enabling programmers to expedite the development process and concoct more advanced programs. This optimistic perspective, I believe, is the stance educators should adopt. It's essential to ensure students grasp the basics unaided by AI. However, post mastering the fundamentals, students should be encouraged to transcend conventional boundaries and create remarkable products through AI-assisted coding.

The blend of traditional coding education and contemporary AI tools can potentially foster a more enriched, innovative, and expedient learning and development milieu. This synergy could not only preserve the essence of coding education but propel it into a new realm of possibilities, nurturing the next generation of adept programmers equipped to thrive in an AI-augmented world.



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