JEDM - Journal of Educational Data Mining

The Journal of Educational Data Mining (JEDM; ISSN 2157-2100) is an international and interdisciplinary forum of research on computational approaches for analyzing electronic repositories of student data to answer educational questions. It is completely and permanently free and open-access to both authors and readers.


Educational Data Mining is an emerging discipline, concerned with developing methods for exploring the unique types of data that come from educational settings, and using those methods to better understand students, and the settings in which they learn.
 
The journal welcomes basic and applied papers describing mature work involving computational approaches of educational data mining. Specifically, it welcomes high-quality original work including but not limited to the following topics:
  • processes or methodologies followed to analyse educational data,
  • integrating the data mining with pedagogical theories,
  • describing the way findings are used for improving educational software or teacher support,
  • improving understanding of learners’ domain representations, and
  • improving assessment of learners’ engagement in the learning tasks.
From time to time, the journal also welcomes survey articles, theoretical articles, and position papers, in as much as these articles build on existing work and advance our understanding of the challenges and opportunities unique to this area of research.
 
All papers should describe the supporting evidence in ways that can be verified or replicated by other researchers to a large extent. It is encouraged, though not required, for researchers to make their data sets, software code, and intermediate results available to the community for inspection and re-use. Submitted papers should also detail the data mining/modeling/analysis component of the submitted work clearly and include discussions of the findings in relation to educational questions.
 
Editor: Michel C. Desmarais, Polytechnique Montreal, Canada
 
Associate Editors:
Ryan S. Baker, Teachers College Columbia University, USA
Agathe Merceron, University of Applied Sciences, Germany
Mykola Pechenizkiy, Technische Universiteit Eindhoven, Netherlands
Kalina Yacef, University of Sydney, Australia (Founding editor-in-chief 2008-2013)
 
 
Web Editor: Behzad Beheshti, Polytechnique Montreal, Canada
 
Author guidelines and submission guidelines can be found here. All other inquiries should be emailed to: jedm.editor@gmail.com.


Announcements

 

CALL FOR PAPERS

 
CALL FOR PAPERS: JEDM SPECIAL ISSUE: EDUCATIONAL DATA MINING WITH LONGITUDINAL DATA SETS  
Posted: 2014-04-28 More...
 
More Announcements...

Vol 6, No 1 (2014)

Table of Contents

Editorial acknowledgement PDF
Michel C. Desmarais, Ryan S. Baker, Agathe Merceron, Mykola Pechenizky, Kalina Yacef 1-2

Articles

Statistical Modeling of Student Performance to Improve Chinese Dictation Skills with an Intelligent Tutor PDF
John Kowalski, Yanhui Zhang, Geoffrey J. Gordon 3-27
Collaboration-Type Identification in Educational Datasets PDF
Andrew Waters, Christoph Studer, Richard Baraniuk 28-52
Study Navigator: An Algorithmically Generated Aid for Learning from Electronic Textbooks PDF
Rakesh Agrawal, Sreenivas Gollapudi, Anitha Kannan, Krishnaram Kenthapadi 53-75