Learning analytics and educational data mining: towards communication and collaboration

George Siemens, R. Baker
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引用次数: 874

Abstract

Growing interest in data and analytics in education, teaching, and learning raises the priority for increased, high-quality research into the models, methods, technologies, and impact of analytics. Two research communities -- Educational Data Mining (EDM) and Learning Analytics and Knowledge (LAK) have developed separately to address this need. This paper argues for increased and formal communication and collaboration between these communities in order to share research, methods, and tools for data mining and analysis in the service of developing both LAK and EDM fields.
学习分析和教育数据挖掘:走向沟通和协作
对教育、教学和学习中的数据和分析的兴趣日益增长,这提高了对分析的模型、方法、技术和影响进行更多、高质量研究的优先级。两个研究团体——教育数据挖掘(EDM)和学习分析与知识(LAK)已经分别发展起来,以满足这一需求。本文主张在这些社区之间增加和正式的沟通与合作,以便在发展LAK和EDM领域的服务中共享数据挖掘和分析的研究、方法和工具。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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