About the Journal

The Journal of Educational Data Mining (JEDM; Impact factor: 3.68; 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
  • ►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.
 
 
Editor: Andrew M. Olney, University of Memphis, USA
 
Associate Editors:
Ryan S. Baker, University of Pennsylvania, USA
Michel C. Desmarais, Polytechnique Montreal, Canada (editor, 2013-2017)
Agathe Merceron, Beuth University of Applied Sciences Berlin, Germany
Kalina Yacef, University of Sydney, Australia (founding editor 2008-2013)
 
 
Author guidelines and submission guidelines can be found here. All other inquiries should be emailed to: info@jedm.educationaldatamining.org.
 

Current Issue

Published: 2019-06-24

Editorial Acknowledgment

Andrew Olney; Ryan S. Baker, Michel C. Desmarais, Agathe Merceron, Kalina Yacef
Abstract 101 | PDF Downloads 70

Page i-iii

Editorial Comment

Articles

Using a Latent Class Forest to Identify At-Risk Students in Higher Education

Kevin Pelaez, Richard Levine, Juanjuan Fan, Maureen Guarcello, Mark Laumakis
Abstract 277 | PDF Downloads 189

Page 18-46

Statistical Consequences of using Multi-armed Bandits to Conduct Adaptive Educational Experiments

Anna Rafferty, Huiji Ying, Joseph Williams
Abstract 171 | PDF Downloads 119

Page 47-79

Although JEDM is not currently indexed, we have calculated the two-year impact factor for 2017 using the Journal Citation Report (JCR) methodology with Google Scholar. Because Google Scholar includes a wide range of publication types, we applied additional criteria of excluding e-prints and technical reports. Even so, our impact factor is more permissive than JCR because it is not restricted to indexed sources.

JEDM's two-year impact factor in 2017 is 3.68