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 |
