2011 - 9th International Workshop on Knowledge Discovery in Educational Data

Following up on the success of the 2010 KDD Cup competition, this workshop seeks to engage the cutting edge data mining community with the education community. We solicit papers addressing problems such as predicting future student performance and learning the underlying structure of student knowledge based on previously collected student data. The 2010 KDD Cup competition showed that many traditional data mining techniques could be successfully applied to educational data to improve prediction. This workshop will be a venue to continue this research and further explore what features in the data will help educators understand what a student really knows.

Objectives

The first objective of this workshop is to explore the opportunities for knowledge discovery in educational data. Educational data is becoming increasingly rich as more and more educational systems are going online and collecting large amounts of data. Repositories such as the Pittsburgh Science of Learning Center DataShop (http://pslcdatashop.org) contain a large number of available data sets that present a tremendous opportunity for the larger SIGKDD community.

The second objective is to provide a bridge to connect the relatively new educational data mining community to the SIGKDD community. As seen in the 2010 KDD Cup competition, there are a number of interesting data mining problems that would benefit from more attention from the SIGKDD community.