International Workshop on Educational Data Mining (EDM @ ICALT'07)

as part of the 7th IEEE International Conference on Advanced Learning Technologies (IEEE ICALT 2007), Niigata, Japan, July 18-20, 2007

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.



March 14, 2007 (Expired) 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
April 30, 2007 Final camera-ready due
July 18-20, 2007 ICALT Conference


All submissions will be handled electronically. Please submit your contribution (up to 10 pages) before the submission deadline (March 14, 2007 - Extended deadline) to the EDM workshop chairs by e-mail:
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.
Therefore, authors of accepted papers will be asked to prepare an additional short-version camera-ready paper to be included in the main IEEE proceedings.

For Authors guidelines, please look at the IEEE Computer Society guidelines. Authors can also use Word Template and Format guidelines.

NEW!! Workshop Contributions
A Outliers Analysis of Learner's data based on User Interface Behaviors by Yong Se Kim, Tae Bok Yoon, Hyun Jin Cha, Young Mo Jung, Eric Wang and Jee Hyong Lee
A framework for using web usage mining to personalize e-learning
by Hafidh Ba-Omar, Ilias Petrounias, and Fahad Anwar
User session Models for Educational Systems based on Multiple Knowledge Structures
by Judit Jasso', and Alfredo Milani
Analyzing the data collected by Programming Tutors that Provide Post-Practice Reflection
by Amruth Kumar, and Peter Rutigliano


Joseph E. Beck
see also here
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



Ivon Arroyo University of Massachusetts Amherst, USA
Ari Bader-Natal Brandeis University, USA
Ryan Baker University of Nottingham, UK
Rahel Bekele Addis Ababa University, Ethiopia
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 USA
Alexey Tsymbal Siemens AG, Germany
Marie-Helene Ng Cheong Vee Birkbeck University of London, UK


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Recent News

  • Proceedings of the Eighth International Conference on Educational Data Mining now available here.
  • Journal of Educational Data Mining issue 7(2) now available here.