Autonomous driving paper index
Emergence and growth of the use of assistants in remote education: A scientometric study (2015–2025)
One-line summary
The objective of this work is to present a scientometric analysis that identifies growth patterns, collaboration networks, and the main research trends in the use of generative artificial intelligence (AI) in remote education.
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
The objective of this work is to present a scientometric analysis that identifies growth patterns, collaboration networks, and the main research trends in the use of generative artificial intelligence (AI) in remote education. A bibliometric analysis was conducted on articles indexed in Web of Science and Scopus between 2015 and 2025. The analysis considered publication volume, authors, countries, and journals. The findings indicate a precipitous surge, marked by an accelerated growth of 351.44% in scientific production, with the year 2023 standing out as a particularly salient period. The United States has emerged as a predominant contributor, with a production of 34 publications and a total of 837 citations, positioning it as a leading actor in international collaboration. In contrast, China and South Africa have each published 22 and 13 publications, respectively, and have received 227 and 206 citations, respectively, reflecting their role as significant contributors to the field. The journals Education and Information Technologies and Computers and Education: Artificial Intelligence merit particular attention for their eight and seven publications, which boast impact factors of 1.65 and 5.22, respectively. The analysis of the authors' positions establishes Sevnarayan K. as one of the most influential, with 4 published articles and 161 citations. Moon J. exhibits the highest effective size among the leading authors, suggesting a comparatively less redundant ego network rather than a demonstrated intermediation role. This study provides a comprehensive overview of the field's evolution, highlighting its transition from the realm of technical innovation to the domain of critical evaluation. Furthermore, it identifies potential avenues for future research endeavors aimed at enhancing the integration of AI within the educational sector.
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