SUN’IY INTELLEKT PLATFORMALARI YORDAMIDA INFERENSIYA KO‘NIKMALARINI SHAKLLANTIRISH METODIKASI

KIRISH: ushbu maqolada sun’iy intellekt (si) platformalarining pedagogik jarayonda inferensiya ko‘nikmalarini shakllantirishdagi metodik imkoniyatlari ilmiy tahlil qilinadi. talabalar kognitiv va metakognitiv salohiyatini rivojlantirish, mantiqiy xulosa chiqarish va muammoli vaziyatlarda inferensiya jarayonini optimallashtirishga qaratilgan yondashuvlar o‘rganiladi. MAQSAD: tadqiqotning maqsadi — si vositalari yordamida inferensiya ko‘nikmalarini mustahkamlash, adaptiv o‘quv tizimlari va interaktiv mashg‘ulotlar orqali pedagogik jarayonni individualizatsiyalash hamda transformatsion xarakterini ta’minlashdir. MATERIALLAR VA METODLAR: tadqiqotda adaptiv o‘quv tizimlari, interaktiv mashg‘ulotlar, real vaqt feedback mexanizmlari qo‘llanildi. metod sifatida nazariy tahlil, pedagogik umumlashtirish va didaktik modellashtirishdan foydalanildi. NATIJALAR VA MUHOKAMA: natijalar shuni ko‘rsatdiki, si platformalari asosida tashkil etilgan mashg‘ulotlar talabalarda inferensiya ko‘nikmalarini rivojlantirishda samarali vosita bo‘lib xizmat qiladi. real vaqt feedback va individuallashtirilgan yondashuvlar mantiqiy xulosa chiqarish jarayonini tezlashtiradi. XULOSA: si vositalaridan foydalanish pedagogik jarayonni transformatsion va shaxsga yo‘naltirilgan shaklda tashkil etishga imkon beradi, bu esa talabalarning kognitiv va metakognitiv faolligini sezilarli darajada oshiradi.

INTRODUCTION: this article provides a scientific analysis of the methodological potential of artificial intelligence (ai) platforms in developing inference skills within the pedagogical process. approaches aimed at enhancing students’ cognitive and metacognitive capacity, logical reasoning, and optimizing inference in problem situations are examined. PURPOSE: the purpose of the study is to strengthen inference skills through ai tools, individualize the pedagogical process, and highlight its transformational character via adaptive learning systems and interactive activities. MATERIALS AND METHODS: adaptive learning systems, interactive sessions, and real-time feedback mechanisms were employed. methods included theoretical analysis, pedagogical generalization, and didactic modeling. RESULTS AND DISCUSSION: the findings show that ai-based learning activities serve as an effective tool for developing students’ inference skills. real-time feedback and individualized approaches accelerate logical reasoning processes. CONCLUSION: the use of ai in education enables the pedagogical process to be organized in a transformational and learner-centered manner, significantly enhancing students’ cognitive and metacognitive activity.