Generative AI has quickly become an essential academic tool for students. It solves problems, writes essays, and even compiles exam notes so quickly that studying without it now feels impossible. However, before we take this trend for granted, there is a question we need to address: Does generative AI really help students learn better?

Recent research and the reality on college campuses tell a different story. In fact, generative AI introduced without any careful planning could erode students’ ability to structure knowledge on their own, the very foundation of their ability to learn. The fact that generative AI has become an inevitable part of education is precisely why we must design learning environments where AI and humans work together effectively.

Concerns Lost Amid the Rise of Generative AI

South Korea universities and the government are accelerating the adoption of generative AI. On July 14, the Ministry of Education and the Korean Council for University Education launched the 2026 Project to Support the Development of Basic AI Curricula for Universities at Sejong University, announcing their commitment to ensuring that all students, regardless of their major, acquire AI literacy.

What is missing is clear guidance on how AI should actually be used. According to the Korean Council for University Education, 101 out of 131 universities nationwide (77.1%) have not even established official policies on generative AI. Kyung Hee University is also experiencing uncertainty regarding the use of generative AI. While the University has launched ChatKHU—an integrated generative AI platform—to encourage the use of AI, some professors continue to restrict its use in classes. As a result, students on the same campus are subject to different rules.

This confusion cannot be dismissed as mere trial and error. According to the Korea Press Foundation’s Tweens’ and Teens’ Media Use in Korea 2025, 82.3% of high-school students replied that they had used generative AI in the past week, indicating that students are already using AI as an everyday learning tool even before entering university. While the current system is rapidly introducing generative AI to students, it is also exposing them to the technology without providing clear criteria for determining how exactly they should use it. The speed of adoption does not justify the absence of guidelines.

Does Generative AI Really Help Students?

International research is increasingly raising concerns that generative AI, if used carelessly, may undermine students’ core competencies.

The 2025 report, OECD Digital Education Outlook 2026, found that general-purpose generative AI can significantly improve performance but may hinder actual learning outcomes if used without educational design. According to experimental results included in the report, students who practiced math problems using generative AI showed a 48% improvement in performance during the practice phase. However, on tests where access to AI was blocked, these students’ scores were 17% lower than those of students who had studied using traditional methods.

The OECD explained this phenomenon as “metacognitive laziness.” They noted that “solving a problem correctly does not always mean one has learned it,” explaining that delegating the problem-solving process to AI can prevent students from properly grasping concepts and transferring what they have learned. A research team led by Natalya Kosmina at Massachusetts Institute of Technology reported that, based on brainwave experiments involving 54 college students, the brain connectivity of students who wrote using generative AI was weaker than that of students who wrote by hand.

This is partly due to the well-known hallucination problem: AI systems can invent false answers based on statistically likely language patterns rather than what is actually true. Therefore, if students lack even the basic knowledge needed to verify the accuracy of those answers themselves, misinformation can accumulate without being checked.

AI companies argue this is technical problem that can be fixed, but even a perfectly accurate AI might still hinder the learning process.

According to Paul Churchland’s theory of epistemology, learning involves connecting and systematizing experiential data in order to understand concepts and acquire knowledge. However, students who immediately receive perfectly polished, correct answers from generative AI may no longer attempt to organize that knowledge for themselves. This creates a paradox: the more convenient generative AI becomes, the fewer opportunities students have to structure their own thoughts.

Ultimately, generative AI can serve as either a facilitator that accelerates learning or a hindrance that replaces it, depending on how it is used. The real question, then, is not whether AI is good or bad, but who designs the classroom aroun it. Some possible answers are already beginning to emerge.

Education Still Belongs to Humans

Khan Academy, a global education company, launched its personalized AI-powered learning service, Khanmigo, in 2023, expressing confidence that generative AI would revolutionize education. However, it has now acknowledged that Khanmigo did not ultimately succeed in promoting self-directed learning. Students were not sufficiently motivated to learn through the questions and games presented by AI.

Cornell University have begun shifting to oral exams as a means of assessment. Because generative AI has made students’ written work more difficult to evaluate, oral exams can require students to explain and defend the details of their own essays.

On June 20, Norway announced an education policy banning the use of generative AI in elementary schools to protect students’ core competencies, such as reading and writing. On May 20, the Japanese Ministry of Education, Culture, Sports, Science and Technology presented a plan to improve education aimed at strengthening ethics education in the age of AI.

These examples all point to one common truth: No matter how advanced AI becomes, a student’s motivation to learn and intellectual indepen- dence can only be fostered within an educational framework designed by humans. Recognizing this, educational institutions have begun proposing instructional designs that preserve intellectual independence rather than allowing generative AI to replace the learning process. However, South Korea has not even begun to fully confront this issue.

South Korean universities and the government are racing to put generative AI in every student’s hands without clearly specifying how it is supposed to help them learn or which skills students may be quietly outsourcing to it.

Generative AI is a double-edged sword that can serve as an accelerator for learning but can also rob students of the opportunity to structure their own experiences. What determines which direction it takes is not the technology itself, but the educational design surrounding it. Since generative AI is already an inevitable trend and its adoption cannot simply be reversed, educational institutions now have a responsibility to establish human-centered learning environments that protect students’ intellectual independence and critical thinking.