About the Journal

The Journal of Educational Data Mining (JEDM; ISSN: 2157-2100; see indexing) is published by the International Educational Data Mining Society (IEDMS). It 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 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. More information about the journal can be found here.
 
 
Editor: Agathe Merceron, Berlin University of Applied Sciences, Germany

Associate Editors:
Ryan S. Baker, University of Pennsylvania, United States
Min Chi, North Carolina State University, United States
Andrew M. Olney, University of Memphis, United States (editor, 2017-2021)
Luc Paquette, University of Illinois at Urbana-Champaign, United States
Anna N. Rafferty, Carleton College, United States
Olga C. Santos, Universidad Nacional de Educación a Distancia, Spain
Kalina Yacef, University of Sydney, Australia (founding editor, 2008-2013)
 
Accessibility Production Editor:
Nigel Bosch, University of Illinois Urbana-Champaign, USA
 

Former Editors:

Andrew M. Olney, University of Memphis, United States, 2017-2021
Michel Desmarais, Polytechnique Montreal, Canada, 2014-2016
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: 2023-12-26

Editorial Acknowledgment

Nigel Bosch, Mingyu Feng, Tanja Käser; Agathe Merceron
Abstract 115 | HTML Downloads 85 PDF Downloads 166
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Page i

Articles

Examining Algorithmic Fairness for First- Term College Grade Prediction Models Relying on Pre-matriculation Data

Takeshi Yanagiura, Shiho Yano, Masateru Kihira, Yukihiko Okada
Abstract 381 | HTML Downloads 259 PDF Downloads 318
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Page 1-25

Modelling Argument Quality in Technology-Mediated Peer Instruction

Sameer Bhatnagar, Michel Desmarais, Amal Zouaq
Abstract 132 | HTML Downloads 83 PDF Downloads 149
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Page 26-57

Extended Articles from the EDM 2023 Conference

Automated Search Improves Logistic Knowledge Tracing, Surpassing Deep Learning in Accuracy and Explainability

Philip Irvin Pavlik Jr., Luke G. Eglington
Abstract 203 | HTML Downloads 176 PDF Downloads 211
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Page 58-86