The EDM conference is a leading international forum for high-quality research that mines large data sets in order to answer educational research questions that shed light on the learning processes . These data sets may come from the traces that students leave when they interact with learning management systems, interactive learning environments, intelligent tutoring systems, educational games or when they participate in a data-rich learning context. The types of data therefore range from raw log files to eye-tracking devices and other sensor data.

Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique and increasingly large-scale data that come from educational settings, and using those methods to better understand students, and the settings which they
learn in.

Whether educational data is taken from students’ use of interactive learning environments, computer-supported collaborative learning, or administrative data from schools and universities, it often has multiple levels of meaningful hierarchy, which often need to be determined by properties in the data itself, rather than in advance. Issues of time, sequence, and context also play important roles in the study of educational data.

The International Educational Data Mining Society’s aim is to support collaboration and scientific development in this new discipline, through the organization of the EDM conference series, the Journal of Educational Data Mining, and mailing lists, as well as the development of community resources to support the sharing of data and techniques.

另外一个和教育数据分析相关的领域为KDD http://www.kdd.org/,学习行为预测也是教育数据的一个热点。

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