Deep Learning-based Social Studies learning to improve student character: Arjun Appadurai's perspective
DOI:
https://doi.org/10.21831/jipsindo.v12i2.86616Keywords:
Deep Learning, Social Studies Education, Globalization Theory, Arjun AppaduraiAbstract
The integration of deep learning into Social Studies education presents new possibilities for enhancing students' understanding and shaping their character in the face of globalization. This research investigates how deep learning techniques can be applied in social studies education by utilizing Arjun Appadurai’s social theory of globalization, which identifies five dimensions of global cultural flows: ethnoscapes, technoscapes, finanscapes, mediascapes, and ideoscapes. These aspects guide students in developing critical thinking skills and adaptability in a world that is becoming increasingly interconnected. Through a qualitative approach and a comprehensive literature review, this study explores the potential of deep learning techniques, including neural networks and natural language processing, to create personalized learning experiences that foster engagement with global social issues. By integrating deep learning into social studies curricula, students gain the ability to analyze globalization’s impact on societies with a more interdisciplinary perspective. Findings suggest that deep learning encourages analytical thinking, ethical reasoning, and intercultural awareness, preparing students to address modern global challenges effectively. This research highlights the importance of aligning artificial intelligence with educational principles to build a more dynamic and responsive social studies curriculum. Ultimately, the study seeks to bridge theoretical insights with practical applications, promoting the development of globally competent individuals capable of critical reflection and ethical decision-making
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