Research on AI-empowered Cultivation of the Integration of Science and Humanities for College Students
Abstract
AI-empowered framework for cultivating interdisciplinary talents. Leveraging artificial intelligence, it advocates three-dimensional integration: first, deploying intelligent learning analytics to map students cognitive profiles and deliver personalized educational pathways; second,
constructing cross-disciplinary knowledge graphs using NLP technologies to bridge conceptual gaps between STEM and humanities domains through project-based modular curricula; third, creating AI-driven ethical simulation platforms that combine generative AI with moral
decision-making scenarios to strengthen humanistic judgment in technological applications. The research outlines a holistic implementation
strategy comprising curriculum redesign featuring AI-curated interdisciplinary course clusters, pedagogical innovation through mixed reality
classrooms and AI tutoring systems, and an evaluation system integrating technical proficiency, humanistic literacy, and ethical responsibility.
By nurturing talents with dual competencies in technological innovation and humanistic care, this approach offers a paradigm shift for smart
education reform, aligning talent development with the demands of intelligent society transformation.
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[1] Zhang Y H, Qin Z G, Xiao L. Research on the bias of artificial intelligence algorithms [J]. Big Data Research, 2018, 4(2): 1-15
[2] Wang T M. Ethical examination of moral dilemmas in autonomous vehicles [J]. Journal of Dialectics of Nature, 2024, 46(1): 1-7
[3] Chi Y D, Yang J, Wang C. Exploration of interdisciplinary construction for smart city science and engineering [J]. Higher Education Forum, 2024, 42(21): 1-9
[4] Anonymous. Innovation in primary mathematics teaching enabled by AI [J]. Chinese Journal of Education Information, 2024, 40(7): 1-6
[5] Anonymous. Three pillars of AI education: Language, programming, and art [J]. China Distance Education, 2024, 32(11): 1-5
DOI: http://dx.doi.org/10.70711/wef.v3i1.7486
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