SUN’IY INTELLEKTNI TA’LIM JARAYONIGA INTEGRATSIYA QILISH: IMKONIYATLAR VA XAVF-HATARLAR
TL;DR
The results demonstrate that methodologically regulated ai integration enhances learning quality, provided there is ongoing monitoring, clear assessment criteria, and established rules of academic integrity.
Abstract
The rapid implementation of generative ai in education enhances personalization while escalating concerns regarding assignment authorship, assessment transparency, and academic integrity. The objective is to empirically test under what methodological conditions ai improves educational outcomes and how associated risks can be managed. A three-stage Ta’limda istiqbolli izlanishlar - xalqaro ilmiy-metodik jurnal № 9/2026 ISSN: 3060-527X experiment (pre-test, intervention, post-test) was conducted with experimental and control groups (n = 48 in each); questionnaire reliability was confirmed with cronbach’s α = 0.78. In the post- test, the experimental group outperformed the control group in ai readiness and academic achievement (cohen’s d = 1.06 and d = 1.44, respectively), accompanied by a moderate reduction in academic dependency risks (d = 0.58). The results demonstrate that methodologically regulated ai integration enhances learning quality, provided there is ongoing monitoring, clear assessment criteria, and established rules of academic integrity.
