About the Journal

Focus and Scope

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. Such data types include student traces within interactive learning environments, learner test data and artefacts used for assessment, didactic material available in electronic form for mining, and usage traces left by students and instructors in learning management systems of all kinds.
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.
Submissions that extend previously published conference papers are welcome provided that the journal submission makes a substantive new contribution (at least 1/3 new content) and any copyright permission on previous material is obtained. Submissions that are extensions of previously published conference papers must be accompanied by a cover letter outlining the new contributions.
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.
There are no charges for published papers.

Use of Generative AI Software Tools while Preparing Your Manuscript

This policy concerns the use of generative AI software tools such as ChatGPT as you write your paper. This policy does not concern the use of generative AI software tools in your research; this will typically be described in a section called Methodology, or a similar name, within your manuscript.

We understand that generative AI software tools can be useful to improve the readability and clarity of your paper and agree with such use. This can be achieved with a prompt such as “Please revise grammar and style of this paragraph for a paper as a scholar without changing the meaning: [PARAGRAPH]”. However, generative AI software tools could be also used to write a complete part of your paper. This could be achieved with a prompt such as “I am writing a paper in sentiment analysis. Please summarize recent important research in this area”. Blindly copy/pasting the results of such a prompt into your paper is not allowed. However, the use of a generative AI software tool as a search engine to help you in finding related works that you review and synthesize yourself is allowed.

Because of the algorithms used in the present generative AI software tools, the text they generate is not guaranteed of being error or bias-free. In any case, human authors must review the automatically generated text, change it, amend it as necessary, and bear full responsibility for the content of their paper. A generative AI software tool/service cannot be an author. Therefore, our policy enforces that you precisely disclose the use of such tools: you describe which tools you have used, in which part of your paper, and what for, and you ensure that you bear full responsibility for your manuscript. Technically, this is realized by including a special section called “Declaration of generative AI software tools in the writing process” before the references with the following statement:

During the preparation of this work, the author(s) used [NAME TOOL(S) / SERVICE(S)] in the section(s) [mention precisely all parts where you used the tool(s) or services(s)] in order to [REASON(S)]. After using this tool(s)/service(s), the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the publication.

Note: This statement is adapted from Elsevier.

This policy will be revisited periodically to update it with best practices.

Peer Review Process

All articles that are elected for a full review undertake rigorous peer review by three anonymous referees. If an anonymized manuscript has been submitted, the review process will be double-blind. Editors will aim for a prompt overall reviewing process. It is the policy of the journal that no submission, or substantially overlapping submission, be published or be under review elsewhere. Papers extending previously published conference papers are acceptable, as long as the JEDM submission provides a significant contribution beyond the conference paper and that the overlap is explained clearly in the JEDM submission, with the unique contribution(s) of the JEDM submission contrasted with that of the other paper(s).
Upon submission, the editor will verify that the article can be read and is within the scope of the journal. Then an Associate Editor will take responsibility for handling the review process. The Associate Editor sends the title and abstract of the article to JEDM's Editorial Board as well as other qualified referees, in order to solicit volunteers for a review. The full article is then assigned to three carefully selected and balanced reviewers following JEDM's reviewing guidelines. The Associate Editor will study the reviews that are returned, and make an overall recommendation to the Editor. Upon the receipt of all reviews, the Associate Editor compiles a summary review in consultation with the Editor, and the summary review is then sent to both the authors and reviewers in anonymous form. When revisions are requested, authors should upload a revised manuscript addressing the points raised in the reviews as well as a detailed cover letter outlining how each point has been addressed. A process map of the editorial process can be viewed here.
This extensive exploitation of electronic communication and electronic publishing benefits the authors, the editor, the reviewers, and the publisher. Reviewers do not receive papers unexpectedly, but are informed about incoming submissions and can pick those papers in which they are interested and which they are willing to review within a certain period of time. Both the quality and the punctuality of the reviews are thereby considerably improved. JEDM aims at evaluating papers within three months.
The reviewers will be asked to answer the following questions:
  • ►How relevant is this submission to the scope of JEDM? (if applicable: to the targeted special issue?)
  • ►How novel is the described research? Are the authors aware of related work?
  • ►What is the scientific contribution of this submission? Is it clearly explained, in terms of how the paper advances the EDM field or contributes to related fields?
  • ►Is the work technically sound? Are there enough methodological details? Are claims convincingly substantiated, either through theoretical argument or empirical data?
  • ►Have the authors made their data sets, software code, and intermediate results available for inspection and re-use to the reviewers and, if appropriate, to the community? (not always required, but recommended when feasible)
  • ►Have the authors properly documented the use of generative AI software tools, if any? (optional section of the manuscript to be placed before the references)
  • ►Do the authors describe the limitations of their approach in a satisfactory manner?
  • ►How significant is the research? Will the paper be likely to have an impact on the community?
  • ►Does the title of this paper clearly and sufficiently reflect its contents?
  • ►Are the presentation, organization and length satisfactory?
  • ►Can you suggest additions, amendments, or reductions in the paper?
  • ►Are the illustrations and tables necessary and acceptable?
  • ►Are the key words and abstracts/summary informative?

Additionally, we appreciate it if reviewers give comments regarding fairness, equity, and positive social impacts of the submission when appropriate, see the guidelines worked out for the EDM 2022 conference.

Publication Ethics and Misconduct

JEDM adheres to the ethical standards set by the Committee on Publication Ethics (COPE), including:

Reviewers with competing interests and editorial team members with competing interests will remove themselves from the decision making process. When an editorial team member submits a paper, an external trusted special editor will be assigned to manage the entire review process and act as editor for that submision.  If the article proceeds to publication, it will be explicitly stated on the article that the editor who submitted the paper has had no involvement with the journal’s handling of this particular article, along with the reasons for this, and the name of the assigned editor. 

Authors are required to declare their compliance with JEDM's Author Guidelines and Submission Checklist, which includes declaring competing interests. In case of misconduct, plagiarism, or if a paper is found not to be original, it will be rejected or removed following the COPE retraction guidelines.


Complaints should be reported via the journal contact information page. Complaints will be investigated according to recommendations by the Committee on Publication Ethics. If complainants are unsatisfied with the response they may contact the International Educational Data Mining Society.

Open Access Policy

The Journal of Educational Data Mining is an open access journal and operates under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International license. Under this license and agreement, authors retain copyright and grant the journal the right of first publication. Please see our full statement on copyright.

This journal provides immediate open access to its content on the principle that making research freely available to the public supports a greater global exchange of knowledge.

There are no article processing charges, submissions fees, or any other costs required of authors to submit articles to this journal. 

Published articles are assigned a DOI and archived with Zenodo.


Articles published in the Journal of Educational Data Mining are indexed or discoverable by the following organizations:

Note that not all back issues are indexed by all organizations.

Publication Frequency

The Journal of Educational Data Mining publishes 2 regular issues a year in summer and winter. Additional special issues are released throughout the year.


JEDM is sponsored by the International Educational Data Mining Society and has no other source of revenue.

Journal History

JEDM is the official journal of the International Educational Data Mining Society.