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Subject: early childhood education ×

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    ItemOpen Access
    Ağaç Yaşken Eğilir
    (Suleyman Demirel University, 2011) Esra CIG
    This article explores effective strategies for teaching young learners a foreign language, focusing particularly on how children naturally acquire their first language and how these processes can inform early foreign language instruction. Drawing on personal observations, developmental linguistics, and characteristics of young learners, the author emphasizes the importance of early and rich language exposure. The article discusses children’s innate abilities such as interpreting meaning through gestures, intonation, and context, as well as their creativity and imagination, which make them highly receptive to language learning. It highlights the role of multiple intelligences and the need to adapt teaching methods to diverse learner profiles. The author also shares practical techniques used outside the classroom to increase children’s exposure to English and enhance motivation through natural communication.
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    ItemOpen Access
    DETECTING SOCIAL CONFLICTS IN KINDERGARTENS USING DEEPLEARNING AND COMPUTER VISION
    (SDU University, 2025) Dina Kengesbay
    Early conflict detection in kindergartens plays a significant role in ensuring a harmonious learningatmosphere and in promoting the social growth of young children. While most previous works have onlyaddressed conflict detection through adults, in this paper, we specifically address conflict detection inkindergartens using deep learning, utilizing both spatial and temporal information to improve performance.The application of deep learning and computer vision in automatically detecting and analyzing earlyconflicts among young children is discussed in this paper. Using video footage, we leverage state-of-the-art RNNs and 3D CNNs for high-accuracy detection of conflict instances. Crucial visual cues—facialexpressions, gestures, poses, vocal tone, and movement—are examined for the extraction of tension oraggression signs. The model is evaluated on real kindergarten video data, with promising conflict detectionand classification results. The findings indicate the potential of AI-supported tools in assisting teachers inclass management, child behavior monitoring, early intervention mechanisms, and the fostering of a goodsocial environment.
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    ItemOpen Access
    Detecting social conflicts in kindergartens using deep learning and computer vision
    (SDU University, 2025) Kengesbay D.
    Early conflict detection in kindergartens plays a significant role in ensuring a harmonious learning atmosphere and in promoting the social growth of young children. While most previous works have only addressed conflict detection through adults, in this paper, we specifically address conflict detection in kindergartens using deep learning, utilizing both spatial and temporal information to improve performance. The application of deep learning and computer vision in automatically detecting and analyzing early conflicts among young children is discussed in this paper. Using video footage, we leverage state-of-theart RNNs and 3D CNNs for high-accuracy detection of conflict instances. Crucial visual cues—facial expressions, gestures, poses, vocal tone, and movement—are examined for the extraction of tension or aggression signs. The model is evaluated on real kindergarten video data, with promising conflict detection and classification results. The findings indicate the potential of AI-supported tools in assisting teachers in class management, child behavior monitoring, early intervention mechanisms, and the fostering of a good social environment