From Artificial Intelligence to Real Dummies

As educational policies increasingly advocate integrating generative artificial intelligence (AI) into teaching practices, important questions arise about its effect on students’ cognitive development. By observing how students use large language models (LLMs), we can see their potential to disrupt traditional learning frameworks, such as Bloom’s Taxonomy. This article explores how AI influences students’ work habits, knowledge acquisition, and cognitive skills based on two years of observations of 70 first‑year computer science students in an 180‑hour programming course. The results suggest that generative AI could undermine the hierarchical structure of Bloom’s Taxonomy by enabling students to bypass essential cognitive processes, such as comprehension, application, and analysis. This allows them to replace their personal efforts with AI‑generated results. These findings raise concerns about the erosion of critical thinking and problem‑solving skills, which could reshape educational goals established since the 1960s. Rather than taking a position for or against the use of AI, the article aims to stimulate debate about its long‑term implications for developing and managing students’ knowledge and skills. The article highlights the need for teachers and policymakers to address ethical challenges and strategies that ensure AI enhances, rather than replaces, cognitive engagement in learning. After an introduction, Chapter 2 provides an overview of Bloom’s taxonomy. Chapter 3 explains the principles of how LLMs work. The next chapter describes how students use LLMs based on behavioral observations. Before concluding with the importance of policy decisions to be made in the coming years, Chapter 6 discusses how LLMs can influence teaching methods.