Autonomous driving paper index
Mapping the evolution of AI in education: a machine learning–based analysis of Chinese scholarly literature
One-line summary
Artificial intelligence (AI) is reshaping educational systems and accelerating the transition toward data-driven learning.
Engineering notes
Key topics: autonomous driving. See the paper for implementation details and experimental results.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Artificial intelligence (AI) is reshaping educational systems and accelerating the transition toward data-driven learning. Using China as a representative case, this study analyzes 3,946 CSSCI journal abstracts (1998–2025) through Latent Dirichlet Allocation (LDA) topic modeling to examine the evolution of AI-in-education research. The results identify ten major thematic clusters and reveal a four-phase developmental trajectory characterized by the interaction of policy initiatives, technological progress, and changing educational demands. Over time, research focus has gradually shifted from technology-driven exploration to scenario-based applications and ultimately toward ecosystem-level integration. The findings also indicate a growing emphasis on AI ethics, governance, and responsible educational applications, reflecting a broader transition from purely technical innovation toward socially embedded AI systems. Based on these patterns, the study proposes a technology–ethics–policy coordination framework to support the sustainable and responsible development of AI-enabled education ecosystems.
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