Why Teaching Kids Coding Skills Remains Essential in the Age of Generative AI

Generative AI surged in 2023, changing tech roles. It raises questions about teaching kids to code. Despite these shifts, learning to code remains crucial for cognitive skills, especially problem-solving and logical reasoning. Coding education must adapt to emphasize human skills for AI use.

CodeBrave trains disadvantaged Lebanese youth in coding, robotics, and AI, providing an opportunity to harness AI’s potential.

As the leader of a non-profit organization focused on providing coding education to underprivileged youth in Lebanon, I have frequently been asked this year whether learning to code is still relevant. Drawing from my five years of experience in tech education, I’ve come to realize that learning to code remains crucial for developing cognitive abilities such as problem-solving, critical thinking, logical reasoning, and creativity.

These skills will continue to be valuable as technology advances. In light of concerns about AI potentially replacing jobs and devaluing human input, coding education is more vital than ever. However, there is a need to adjust the approach to highlight the human skills necessary to effectively utilize AI.

Teaching kids to code essential: CodeBrave

The organization I co-established, CodeBrave, aims to address this by providing training in coding, robotics, and AI to young individuals from underserved communities in Lebanon. Considering AI’s rapid and significant impact on efficiency and innovation, I firmly believe that laying the groundwork to harness AI through coding education offers a unique opportunity for disadvantaged youth to make substantial leaps forward.

Claims suggesting that children no longer require coding skills, such as those put forth by the OECD’s education chief Andreas Schleicher, misconstrue the essence of software engineering. People outside the tech realm might assume that a coder’s primary task is coding. However, even before the emergence of AI, the role of a software engineer revolved less around writing code and more on utilizing libraries of pre-existing code, analyzing its functionality, and adapting it for specific purposes. Nowadays, AI is increasingly responsible for generating this pre-written code. In both scenarios, the engineer’s primary focus is on critical thinking and problem-solving.

The question arises: How can young individuals develop critical thinking and problem-solving abilities? Steve Jobs’ notion from a decade ago, “everyone should learn to code because it teaches you how to think,” remains as pertinent as ever. A study conducted in 2019 revealed that just one month of engaging in computational thinking and coding activities is equivalent to seven months of standard mathematics and science in terms of enhancing executive functioning in children’s cognitive development.

A microcontroller

When CodeBrave introduces its program to new schools in Lebanon, we encounter twelve-year-olds who grapple with comprehending concepts like conditionals (where an action depends on whether a specific condition is met). Through involving them in real-world problem-solving within team contexts, they acquire the capacity to think logically and creatively.

One of this year’s projects was centered on water usage in agriculture. Deliberately constraining resources often act as a catalyst for ingenious ideas: students devised an automatic irrigation system for plants using straws and a servo motor to transport water from a tank directly to the plant pot. They ingeniously employed bananas as conductors to connect humidity sensors to a microcontroller, which assessed soil humidity. These hands-on activities serve to nurture vital non-technical skills such as effective communication, critical thinking, creativity, and problem-solving. Experts like TechTarget have emphasized the importance of these skills for harnessing AI effectively and adapting to the ever-evolving professional landscape.

Teaching kids to code essential: AI’s role in the future

An educational approach that readies children to leverage AI, known as PRIMM (Predict, Run, Investigate, Modify, Make), entails students reviewing pre-existing code, forecasting its behavior, executing and scrutinizing it, making necessary alterations, and subsequently crafting something novel based on their acquired knowledge. For instance, twelve-year-olds might delve into block-based code for an animated dance party featuring a ghost. They predict the ghost’s actions based on the code, address any glitches, and then introduce new elements. This comprehensive understanding and critical analysis cultivate the foundations for dealing with AI-generated code.

Amid a flurry of sensationalist news headlines and exaggerated apprehensions regarding AI’s role in the future, it is crucial to demystify its actual operations. In one of our lessons, 12-year-old students train a computer system to differentiate between images of cats and dogs. They delve into the origins of biases that may emerge from imbalanced data, resulting in skewed outcomes. Disproportionate representations regarding breed, age, or pose make it more challenging for the system to accurately classify images deviating from specific patterns. Once students grasp the mechanics of AI algorithms, they become better equipped to utilize AI tools in the future.

Learning to code remains the most effective means of honing the cognitive skills required to effectively leverage AI tools and capitalize on emerging employment prospects, such as “AI prompt engineering,” which has been identified by the World Economic Forum as one of the top three jobs of 2024. This holds particular significance in underserved communities, as the disparity widens between those capable of harnessing AI for progress and those who lag significantly behind.

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