Can Artificial Intelligence Replace Traditional Learning Methods?

ORIGINAL SOURCE
Originally published in International conference on multidisciplinary science; Vol. 4 No. 7 (2026): INTERNATIONAL CONFERENCE ON MULTIDISCIPLINARY SCIENCE; 53-55.

SH, Ibragimova (2026) Can Artificial Intelligence Replace Traditional Learning Methods? International conference on multidisciplinary science; Vol. 4 No. 7 (2026): INTERNATIONAL CONFERENCE ON MULTIDISCIPLINARY SCIENCE; 53-55.

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Abstract

This paper explores the growing influence of Artificial Intelligence (AI) in the field of education and  addresses the critical question of whether AI can entirely replace traditional learning methods. While  technological advancements have introduced highly efficient, data-driven, and personalized learning  systems, education remains a fundamentally human endeavor. This study analyzes the core strengths of  AI—such as adaptive learning algorithms, administrative automation, and global accessibility—and  contrasts them with the irreplaceable socioeconomic and emotional benefits of traditional classrooms,  including human mentorship, social skill development, and structured learning environments. The paper  concludes that instead of a total replacement, the future of global education lies in a synergistic, hybrid  model (blended learning) where AI acts as an optimization tool managed by human educators.

Item Type: Article
Additional Information: Imported from International conference on multidisciplinary science (MJST)
SWORD Depositor: Admin User
Depositing User: Admin User
Date Deposited: 09 Oct 2026 21:09
Last Modified: 09 Oct 2026 21:09
URI: https://universalpublishings.uz/id/eprint/20817

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