[edm-announce] Educational Data Mining at ICALT07 Workshop 2nd call
- From: "Silvia Viola" <sr.viola@xxxxxxxxx>
- To: edm-announce@xxxxxxxxxxxxx
- Date: Fri, 2 Mar 2007 09:46:47 +0100
*** APOLOGIES FOR MULTIPLE POSTINGS ***
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International Workshop on Educational Data Mining (EDM@ICALT'07)
(http://www.educationaldatamining.org/ICALT2007.html) or (
http://www.win.tue.nl/~mpechen/conf/edm2007/)
as part of the 7th IEEE International Conference on Advanced Learning
Technologies (IEEE ICALT 2007)
(http://www.ask4research.info/icalt/2007/) Niigata, Japan, July 18-20, 2007
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*** Submission deadline extended: March 14
*** 2nd CALL FOR PAPERS ***
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.
As such, the EDM workshop invites 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 types of learning behavior (e.g. in online
systems), predicting the knowledge and interests of a user based on past
behavior, partitioning a heterogeneous group of users into homogeneous
clusters, etc.
Typically, educational data sources are quite heterogeneous (e.g., web log
files, interaction logs, source code, text and dialogue data, etc.), and
have a variety of different scales, grain-sizes, and spatial and temporal
resolution. Though the many types of educational data often differ
considerably from one another, they provide multiple types of insight on a
single domain or context and, above all, share the potential to reveal
unexpected and useful knowledge concerning learners and/or the process of
learning - if correctly and coherently analyzed. Applying methods to mine
the complex data that we can collect on educational situations requires the
development of new approaches that build upon techniques from a combination
of areas, including statistics, psychometrics, machine learning, and
scientific computing.
The EDM workshop at ICALT'07 aims at providing a focused international forum
for researchers to present, discuss and explore the state of the art of
mining educational data and evaluating usefulness of discovered patterns for
adaptation and personalization, as well as to outline promising future
research directions. The EDM workshop invites submissions addressing all
aspects of educational data mining with applications for adaptation and
personalization in e-learning systems.
The topics of special interest include, but are not restricted to:
* Methods and approached for EDM
* Characteristics of educational data and how to deal with them
* Learning browsing behavior; e.g., searching for patterns in log-data
* Data mining for predicting user (potentially changing) interests
* Mining differences in user's learning behavior (e.g. between two
systems)
* Mining data from A/B tests
* Application of discovered patterns for personalization and adaptation
* Description of applications
* Case studies and experiences
The workshop invites papers reporting experiences, case studies, surveys,
reflections and comparisons. The submission format is: either a full paper
of up to 10 pages, a short paper of up to 5 pages, or an abstract of up to 3
pages for a poster.
* IMPORTANT DATES *
March 14 (Extended), 2007 Submission of paper (IEEE 2-column, 10-pages
maximum)
March 30, 2007 Notification of acceptance
April 6, 2007 Final 2-pages summary for publication in main
ICALT proceedings camera-ready due
April 16, 2007 Author registration deadline
July 18-20, 2007 ICALT Conference
* SUBMISSION PROCEDURES *
Please submit your contribution (up to 10 pages) before the extended
submission deadline (March 14, 2007) to the EDM workshop chairs by e-mail:
edm.icalt07@xxxxxxxxxx Each submission will be reviewed by at least three
members of the workshop programme committee members.
All accepted workshop papers will be published in the online workshop
proceedings edited by the general workshop chairs. Beside this a short
version of each accepted paper (2 pages long, IEEE 2-column format) will be
published in the main IEEE proceedings.
* TRACK CHAIRS *
Joseph E. Beck Carnegie Mellon University, USA
Mykola Pechenizkiy Eindhoven University of Technology, the Netherlands
Toon Calders Eindhoven University of Technology, the Netherlands
Silvia Rita Viola U. Politecnica delle Marche and U. for Foreigners,
Perugia, Italy
* TRACK PROGRAM COMMITTEE *
Ivon Arroyo University of Massachusetts Amherst, USA
Ari Bader-Natal Brandeis University, USA
Ryan Baker University of Nottingham, UK
Mária Bieliková Slovak University of Technology, Slovakia
Hao Cen Carnegie Mellon University, USA
Raquel M. Crespo Garcia Carlos III University of Madrid,
Spain
Christophe Choquet Université du Maine, France
Rebecca Crowley University of Pittsburgh, USA
Paul De Bra Eindhoven University of Technology, the Netherlands
Mingyu Feng Worcester Polytechnic Institute, USA
Elena Gaudioso Universidad Nacional de Educación a Distanzia, Spain
Sabine Graf Vienna University of Technology, Austria
Wilhelmiina Hämälainen University of Joensuu, Finland
Judy Kay University of Sydney, Australia
Manolis Mavrikis University of Edinburgh, UK
Agathe Merceron University of Applied Sciences Berlin, Germany
Maria Milosavljevic Macquarie University, Sydney, Australia
Kaska Porayska-Pomsta London Knowledge Lab , UK
Genaro Rebolledo-Mendez University of Sussex, UK
Cristobal Romero Universidad de Córdoba, Spain
Amy Soller Institute for Defense Analyses, USA
Alexey Tsymbal Siemens AG, Germany
Marie-Helene Ng Cheong Vee Birkbeck University of London, UK
--
Silvia Rita Viola
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