第十六届教育数据挖掘国际会议的主题为拓展人类潜能的教育数据挖掘。在信息技术快速发展的背景下,如何利用教育数据获取有用信息来指导教育实践和决策,是目前教育领域需要解决的问题。聚焦教育数据挖掘国际会议,从会议总体概括、发表作者国别、关键词、研究技术、研究方向等多个角度深度分析,总结教育数据挖掘领域的未来发展趋势,包括多模态数据融合、应用生成式人工智能、优化个性化学习路径等特点,希望能够为今后相关学者进一步的研究与实践提供参考。
Abstract
The theme of the 16th International Conference on Educational Data Mining is to explore educational data mining that expands human potential. In the context of rapid development of information technology, how to use educational data to obtain useful information to guide educational practice and decision-making is currently a problem that needs to be solved in the field of education. This paper focuses on the International Conference on Educational Data Mining, and deeply analyzes the future development trends in the field of educational data mining from multiple perspectives such as conference overview, author countries, keywords, research techniques, and research directions. It summarizes the characteristics of multi-modal data fusion, application of generative artificial intelligence, and optimization of personalized learning paths, hoping to provide reference for further research and practice by relevant scholars in the future.
关键词
EDM国际会议 /
教育数据挖掘 /
前沿主题 /
趋势分析
Key words
EDM International Conference /
educational data mining /
cutting-edge themes /
trend analysis
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基金
教育部人文社会科学研究青年基金项目“基于教育数据挖掘的高校学生投入影响因素与评价模型研究”,项目编号：19YJC880016
