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 of 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.

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Recent news

The latest issue of the Journal of Educational Data Mining (JEDM), Vol. 9 (2017), is now available here

Proceedings of EDM 2017 now available here.