[edm-announce] CFP: KDD 2011 Workshop on Knowledge Discovery in Educational Data
- From: "Pardos, Zach A" <zpardos@xxxxxxx>
- To: "edm-announce@xxxxxxxxxxxxx" <edm-announce@xxxxxxxxxxxxx>
- Date: Thu, 19 May 2011 17:52:29 -0400
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KDD 2011: Workshop on Knowledge Discovery in Educational Data
Held as part of the 17th ACM SIGKDD Conference on Knowledge Discovery and Data
Mining (KDD 2011)
San Diego, CA. August 21-24 - Workshop date: Sunday, August 21
https://pslcdatashop.web.cmu.edu/KDD2011/
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[Apologies for any potential cross-postings]
Following up on the success of the 2010 KDD Cup competition
(http://pslcdatashop.org/KDDCup), 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 from large educational datasets.
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 the nature of educational data and what factors are important in
determining student knowledge.
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 tremendous research opportunities for the
larger SIGKDD. These datasets are primarily from tutors focused on STEM
(Science, Technology, Engineering and Mathematics) topics such as Algebra,
Geometry, Physics, Chemistry and others.
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 educational data mining
problems that could benefit from the methods discussed and presented at SIGKDD.
Topics of Interest:
==============
We welcome papers describing original work. Areas of interest include but are
not limited to:
- regression and classification methods applied to large datasets
- clustering
- feature selection
- feature generation
- analyzing tutor effectiveness
- user models
- exploiting temporal aspects of educational data
- collaborative filtering
- student text response analysis
- online predictive models
- visualization
Important Dates
=============
Paper submission: June 18, 2011
Acceptance notification: July 3, 2011
Camera ready papers: July 17, 2011
Workshop: August 21, 2011
Submission Types
==============
There are two types of submission:
- Full papers: Maximum of 10 pages. Should describe substantial, unpublished
work
- Short papers: Maximum of 6 pages. Should describe works in process
All submissions should follow the ACM single column formatting guidelines.
Submission Instructions
===================
Submission is managed by EasyChair. You'll need to register (free and quick
procedure). To enter the conference submission section, please go to:
http://www.easychair.org/conferences/?conf=kddined2011
Authors of accepted papers will be invited to submit extended versions of
papers to an upcoming special issue of the Journal of Educational Data Mining
on the KDD 2011 Workshop on Knowledge Discovery in Educational Data.
PC Committee
============
John Stamper, Kenneth R. Koedinger, Geoff Gordon, Ryan Baker, Alexandru
Niculescu-Mizil, Chih-Jen Lin, Philip Pavlik, Ted Carmichael, Neil Heffernan,
Zach Pardos, Steve Ritter, Luo Si and Guatam Biswas.
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