This question raises important considerations about the impact of AI on CS education. On one hand, the use of generative AI in exams is often considered a 'misuse' and involves ethical concerns. Students might rely too heavily on AI tools, potentially leading to a lack of fundamental programming skills and this could result in a superficial understanding of coding principles.
On the other hand, there is evidence that the industry and professional developers benefit significantly from the use of generative AI. These tools can enhance productivity, and provide innovative solutions.
Balancing traditional programming education with the practical use of AI tools would prepare students for the evolving demands of the tech industry while maintaining ethical standards and deep technical knowledge. However, do we know how to do it?
I dont know. It is difficult to answer the question as of today. However, I dont recommend students to overuse generative AI tools.
Hello Dr. Cares,
No, I don't think that. I saw that some of the people in a village had smartphones that their kids had purchased for them. Respectfully, I observed that they depended on younger individuals for simple configurations. This implies that if you don't know how to use AI or other advanced technology, it's useless. Only by understanding their purpose and functionality, even with basic knowledge of coding, can you truly benefit. Without knowing what coding terms mean, how they work, or what they can achieve, those tools remain underutilized.
Let me give you another example, if you have ~$20, you can buy a full setup for painting brushes, paper, and so on. But if you don’t know how to create art, what will you paint, and who will pay for it, even if you had resources worth billions of dollars? Understanding and skill are what truly create value.
Therefore, if generative AI does not hinder programming skills, why do many teachers not allow its use in examinations? In this sense, are traditional programming skills no longer useful?"
Many teachers restrict the use of AI in exams because, under the traditional model, these assessments aim to measure the student’s deep and independent understanding without intermediaries. Allowing the automatic generation of solutions makes it harder to determine whether the student truly grasps the problem or is merely “delegating” its resolution. However, this does not mean that traditional programming skills have lost their value; they remain essential for evaluating, adapting, and refining the solutions proposed by AI. Rather than competing with technology, these abilities enable its use with discernment, turning the “easiest path” into a genuinely optimal one backed by solid comprehension. By adapting our methods of assessment—integrating AI in a supervised manner and focusing on reasoning, validating answers, and fostering the ability to learn independently—classical competencies become more valuable than ever.
No, it will not because educational AI is limited to teaching instead of solving problems, while non-educational AI makes mistakes sometimes and suggests bad code, so a programming student needs to learn how to write quality code and could use AI for help.
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