The aim of the current research is to develop the social studies curriculum at the primary stage in light of the standards of the next generation, which was represented in three main dimensions (pivotal ideas, scientific practices, and comprehensive concepts). The researcher designed a tool for the study, which is a content analysis card in the light of (NGSS) standards, based on the previous main dimensions. The descriptive analytical approach was adopted in analyzing the social studies curriculum for the primary stage to determine the degree to which the standards of the next generation are available, as well as to establish the theoretical framework related to the research variables. To develop the social studies curriculum in light of the standards of the next generation
The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra
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