Artificial Intelligence in Education: The Learning Challenge

The specificity within the AI-based answers limits the student’s capability to draw interlinkages across the concepts, develop a sound reasoning and inquisitiveness around the concept. This eventually can lead to reduced competence, lower academic confidence, and impaired cognitive development.

Imagine you’re a teacher in India assigning a topic on water conservation to a sixth-grade student or a last-year university student. The next morning, the student submits an impressive assignment. The answer is well-structured, the language is polished and there are no grammatical mistakes. Yet, when asked to explain the same topic in the examination hall without the help of any device, the student struggles to put forward the same level of work that was produced in the assignment. The work produced by these school students using artificial intelligence does raise a pertinent question: did the student actually learn, or did the technology simply help them produce a better answer?

This has become an important question in the age of artificial intelligence. The problem is not the use of this technology, in fact in 21st century, the use of technology has become inevitable. Education has always adapted to new tools, from calculators to computers. The difficulty with AI is that it can produce answers without necessarily requiring the student to work on the concept, thereby weakening the cognitive reasoning among these students.

The OECD’s Digital Outlook 2026 highlights this distinction between improved task performance and genuine learning. AI can help students complete tasks, but when used without pedagogical guidance, it may encourage them to outsource cognitive effort rather than develop their own understanding. This phenomenon, which the experts describe as cognitive offloading ultimately leads to AI dependency.

While AI can help students answer the specific problems, teachers in the classroom not only help them with their questions but connect the problem with the fundamentals which helps them to solve not only a specific problem but all other problems linked to that fundamental. The specificity within the AI limits the student’s capability to draw interlinkages across the concepts, develop a sound reasoning and inquisitiveness around the concept. This eventually can lead to reduced competence, lower academic confidence, and impaired cognitive development.

The fundamental issue lies in the way the education system in India promotes rote learning. This system has conditioned students to prioritise the production of correct answers. AI fits conveniently into this existing pattern because it does produce specific answers without requiring students to engage deeply with the underlying concepts.

Moreover, the intensification of screen-based learning environments, along with frequent interaction with AI systems, has been demonstrated to aggravate digital fatigue and techno-stress, marked by mental exhaustion, diminished motivation, and increased anxiety linked to continuous technological use. From a socioeconomic standpoint, prolonged reliance on AI in academic environments and progressive personal dependence might even hinder the cultivation of interpersonal skills, such as communication, empathy, and emotional regulation.

The challenge of balancing AI integration with independent learning becomes clearer when we look at some of the world’s top-performing education systems. China and Singapore offer two contrasting approaches to the use of AI in education. China has maintained a relatively restrained approach to student’s use of AI, particularly in school-level education, while Singapore has allowed greater integration of AI tools into its learning environment. Despite these differences, both countries continue to perform strongly in international assessments, like PISA, conducted by the OECD every three years. This raises another significant question: is restricting AI use necessary to ensure cognitive development in school students , or can its integration coexist with strong academic outcomes?

Way Forward

Taking the OECD’s findings into consideration, it is evident that the Indian education system does not need to separate itself from or completely ban the use of AI. Instead, the focus should be on ensuring that AI integration does not come at the cost of cognitive erosion. This requires a fundamental shift in how learning is assessed across the education system.

Viva-based examinations should become more common, and practical assessments should be given greater priority. The examination pattern needs to reorient towards questioning the answers. These methods test a student’s understanding rather than relying solely on written submissions, which can easily be generated using AI.

While AI cannot be a prerequisite for academic success or a benchmark for the genuine understanding of a subject. Its impact depends on how it is used. When used thoughtfully, it can enhance learning, but when it replaces thinking instead of supporting it, it risks weakening the very cognitive skills education is meant to develop.

(Sadiya Suhail Majid is a TRIP intern)

References

About the author

Sadiya Suhail Majid

Sadiya Suhail Majid is a Political Science undergraduate and public policy researcher. She is presently a TRIP intern.

Sneha Yadav

Sneha Yadav is the Editorial Director at Sarvoday TheRise Foundation. She holds an electronics engineering degree along with a postgraduate degree in political science. Her interests span contemporary social, economic, administrative, and political issues in India. She has worked with CSDS-Lokniti and has been previously associated with The Pioneer and ThePrint.

Way Forward

References

About the author

Sadiya Suhail Majid

Sneha Yadav

Related Posts

Leave a Comment Cancel Reply