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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Beck, J.E. Calders, T. Pechenizkiy, M. Viola, S.R. |
| Copyright Year | 2007 |
| Description | Author affiliation: Carnegie Mellon Univ., Pittsburgh (Beck, J.E.) |
| Abstract | The educational data mining workshop1 held in conjunction with the 7 IEEE International Conference on Advanced Learning Technologies (ICALT) in Niigata, Japan on July 18-20, 2007. EDM@ICALT07 continues the series of Workshops organized by the International Working Group on Educational Data Mining during 2007. For upcoming events in educational data mining and for information on past workshops. Recently, the increase in dissemination of interactive learning environments has allowed the collection of huge amounts of data. An effective way of discovering new knowledge from large and complex data sets is data mining. The EDM workshop aimed for papers that study how to apply data mining to analyze data generated by learning systems or experiments, as well as how discovered information can be used to improve adaptation and personalization. Interesting problems data mining can help to solve are: determining what are common learning styles or strategies, predicting the knowledge and interests of a user based on past behavior, partitioning a heterogeneous group of users into homogeneous clusters, etc. |
| Starting Page | 933 |
| Ending Page | 934 |
| File Size | 142836 |
| Page Count | 2 |
| File Format | |
| ISBN | 076952916X |
| DOI | 10.1109/ICALT.2007.286 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2007-07-18 |
| Publisher Place | Japan |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Content Type | Text |
| Resource Type | Article |
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