Mazkur maqolada “O‘zbekistonning eng yangi tarixi” fanini o‘qitish jarayonida o‘quvchilarda ijtimoiy kompetensiyani shakllantirishning asosiy yo‘nalishlari yoritilgan. Maqolada ijtimoiy kompetensiya tushunchasining mazmun-mohiyatini sharhlab, uni tarixiy ong, fuqarolik pozitsiyasi va madaniy merosga munosabat orqali shakllantirish usullarini ko‘rsatib beradi. Shuningdek, dars jarayonlarida interaktiv metodlardan foydalanish, tarixiy voqealarga tanqidiy yondashuvni rivojlantirish va zamonaviy o‘quv materiallaridan foydalanish bo‘yicha tavsiyalar berilgan.

Mazkur maqolada ta’lim muassasalarini boshqarish tizimini takomillashtirishning dolzarb jihatlari yoritilgan. Bugungi kunda ta’lim sifati va samaradorligini oshirishda menejment tizimining samarali faoliyati muhim o‘rin egallaydi. Shuning uchun ta’lim jarayonida strategik rejalashtirish, innovatsion yondashuv, raqamli boshqaruv, monitoring va baholash tizimlarini rivojlantirish orqali menejmentni zamonaviylashtirish zarurati ortib bormoqda. Maqolada samarali boshqaruv modelini shakllantirish, kadrlar salohiyatini oshirish, resurslardan oqilona foydalanish va ta’lim muassasasining ichki muhitini yaxshilash bo‘yicha amaliy takliflar berilgan. Shuningdek, xorijiy tajribalar tahlil qilinib, ularni milliy tizimga moslashtirish imkoniyatlari ham ko‘rib chiqilgan.

This article focuses on enhancing mathematics education in academic lyceums through the application of interactive methods. It discusses the role of modern educational technologies, active learning strategies, and project-based learning in mathematics education. Additionally, the effectiveness of interactive methods in increasing student engagement, fostering critical thinking, and developing problem-solving skills is analyzed. The article serves as a valuable resource for teachers, education specialists, and academic lyceum administrators.

Ushbu maqolada hind xalqi og‘zaki va yozma adabiyoti javohirlaridan biri bo‘lmish “Kalila va Dimna” turkiy qo‘lyozmalarining o‘ziga xos bo‘lgan jihatlari va uning mazmuniy qurilishi tаdqiq etilgаn.

This paper focuses on the selection and justification of deep learning models for emotion classification tasks. It provides a comprehensive analysis of various neural network architectures, including Convolutional Neural Networks, Recurrent Neural Networks, Long Short-Term Memory networks, and Transformer models, assessing their performance in recognizing and classifying human emotions from multimodal data sources. The study examines the strengths and limitations of each model with respect to data type, training efficiency, computational complexity, and generalization capabilities. Furthermore, criteria for optimal model selection tailored to real-world emotion recognition applications are discussed. The findings contribute to enhancing the accuracy and robustness of emotion classification systems and offer valuable guidelines for researchers and practitioners developing advanced affective computing solutions.