About the Journal

The Educational Journal of Artificial Intelligence and Machine Learning (EJAIML) serves as a leading scholarly platform dedicated to advancing the understanding, dissemination, and application of artificial intelligence (AI) and machine learning (ML) in educational settings. This peer-reviewed journal focuses on the intersection of AI, ML, and education, providing a comprehensive space for researchers, educators, and practitioners to share insights, innovative approaches, and empirical findings.

EJAIML embraces a multidisciplinary approach, covering a wide range of topics within the realm of AI and ML in education. The journal explores the development and implementation of AI and ML technologies in educational environments, addressing issues such as intelligent tutoring systems, personalized learning, educational data mining, and adaptive assessment tools. It also delves into the ethical considerations surrounding AI and ML in education, ensuring a balanced exploration of the opportunities and challenges associated with these rapidly evolving fields.

Key areas of coverage in the Educational Journal of Artificial Intelligence and Machine Learning include:

  1. Innovative Pedagogical Approaches: EJAIML publishes research on novel teaching methods and learning strategies empowered by AI and ML, fostering a deeper understanding of how these technologies can enhance educational outcomes.

  2. Learning Analytics and Educational Data Mining: The journal investigates the use of AI and ML for analyzing large datasets in education, providing insights into student performance, learning patterns, and instructional effectiveness.

  3. Intelligent Tutoring Systems: Articles in EJAIML focus on the design, development, and evaluation of AI-driven tutoring systems that cater to individual learner needs, promoting personalized and effective learning experiences.

  4. Ethical and Social Implications: EJAIML contributes to the ethical discourse surrounding the use of AI and ML in education, examining issues such as privacy, bias, and fairness to ensure responsible and equitable deployment of these technologies.

  5. Emerging Technologies in Education: The journal explores cutting-edge AI and ML technologies, including natural language processing, machine learning algorithms, and computer vision, and their potential applications in educational contexts.

  6. Professional Development and Training: EJAIML publishes research on the role of AI and ML in teacher training and professional development, addressing how educators can leverage these technologies to enhance their instructional practices.

The Educational Journal of Artificial Intelligence and Machine Learning aims to foster collaboration between researchers, educators, and industry professionals, providing a valuable resource for those seeking to stay at the forefront of AI and ML-driven innovations in education. Through rigorous peer review and a commitment to high-quality scholarship, EJAIML contributes to the ongoing dialogue that shapes the future of AI and ML-enabled learning environments.

Articles we publish

Research Articles: These are detailed reports of original research findings. They typically include an abstract, introduction, methodology, results, discussion, and conclusion sections. Short articles; 2,000-3,500 words, Long articles; 6,000-7,000 words

Review Articles: These provide a comprehensive summary of research on a particular topic. They may analyze and synthesize existing literature, identify gaps in knowledge, and propose future research directions. Word count; 6,000-7,000

Short Communications: also known as a Brief Communication or Brief Report, is a concise research paper that presents significant findings or advancements in a specific field of study. Unlike full-length research articles, Short Communications are typically limited in length and scope, focusing on a single, well-defined aspect of a research project or a particular discovery. 1,000-2,000

Policy Briefs: offers concise information and recommendations on a specific policy issue, including background context, relevant data analysis if applicable, policy implications, actionable recommendations, and a call to action. Word count; 1,000-2,000

Editorials: short articles written by the editorial board or invited experts. They may provide commentary on current events, highlight recent research findings, or discuss trends in the field.

Journal templates

Use template-1 for the research article

Use template-2 for review article

Use template-3 for short communication

Use template-4 for a policy brief

Note: hyperlink underlined with attached template files

Peer Review

Educational Journal of Artificial Intelligence and Machine Learning upholds rigorous peer review standards to maintain the integrity and credibility of the research we publish. Through constructive feedback and critical appraisal, peer review helps authors refine their work and contributes to the advancement of knowledge in our field.

Ethics

Authors are expected to adhere to ethical guidelines, including protecting human subjects, and animal welfare, and avoiding plagiarism and conflicts of interest. Editors and reviewers play a vital role in upholding these standards by ensuring submissions meet ethical criteria and reporting any breaches. In our journal, we prioritize ethical integrity to safeguard the rights and welfare of research participants, uphold academic honesty, and maintain public trust in our publications.

Data Availability

We encourage authors to make their data openly accessible, either through supplementary materials, data repositories, or public archives. By sharing data, researchers facilitate verification, reuse, and synthesis of findings, accelerating the pace of discovery and innovation. In our journal, we support data-sharing practices to enhance the reliability and impact of research outcomes, fostering a culture of openness and collaboration within our scholarly community.

Publishing approach

Progressive. We believe in a progressive publication approach. When an article is accepted, it is promptly published online, ensuring valuable research is accessible to the academic community and the public without unnecessary delays. This approach allows readers to engage with cutting-edge research as soon as it becomes available.

Open Access

The journal embraces open-access principles to ensure that published research is freely available to a global audience, regardless of institutional affiliation or financial means. All articles are published under the Creative Commons Attribution (CC BY) license, allowing unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

Authors retain full copyright of their work. By submitting to this journal, authors grant the publisher a license to publish and disseminate the work online and in print. No copyright transfer is required.

This approach supports inclusivity, democratizes access to knowledge, and encourages innovation, in alignment with global open access policies.

Article Publication Charge (APC)

No Processing or Publication Fees: We are committed to fostering an open and accessible scholarly environment. Currently, the Educational Journal of Artificial Intelligence and Machine Learning does not charge any processing or publication fees. Our focus is on promoting the free exchange of knowledge and ideas in the field of education.

2025: APC= 0$

2027: APC= 1500$

Submission Guidelines

  • Manuscripts should be submitted electronically through our online submission system.
  • Submissions should follow the formatting guidelines outlined in our submission template.
  • Authors are encouraged to include clear and concise abstracts that highlight the significance of their research. For more information, see the full Author Guidelines
  • The journal follows a double-blind peer-review process to ensure the quality and rigor of published articles.

Repository Policy

Parabolum Publishing supports open dissemination of research and allows authors to deposit the final published version (Version of Record) of their article in any institutional or subject repository of their choice immediately upon publication, with no embargo. Authors are encouraged to:

  • Share the published version (VoR) freely, provided it includes proper citation and DOI.

  • Deposit in institutional, national, or general-purpose repositories (e.g., ResearchGate, Academia.edu, Zenodo).

  • Include a clear link to the article on the journal’s website and note that it is the final published version.

No restrictions are placed on repository deposit — our aim is to maximize accessibility and visibility through quick and open publishing.

Persistent Identifiers

All articles are assigned a DOI (Digital Object Identifier) to ensure permanent access and accurate citation.

Archiving and Digital Preservation Policy

Parabolum Publishing is committed to the long-term preservation of and access to the scholarly content it publishes. To ensure the enduring availability of our publications, we utilize the following digital preservation services:

  • LOCKSS (Lots of Copies Keep Stuff Safe): Our content is preserved through the LOCKSS program, which ensures that multiple copies of our publications are stored across a network of libraries.

  • CLOCKSS (Controlled LOCKSS): We participate in the CLOCKSS initiative, providing a decentralized and secure preservation system to safeguard our content.

  • PKP Preservation Network (PKP PN): Our journals are archived in the PKP PN, which offers a free preservation service for Open Journal Systems (OJS) users.

These measures guarantee that our published articles remain accessible and citable for future generations.

Contact Information

For inquiries, submissions, or any other communication, please contact the editorial team at info@parabolumpublishing.org.

Thank you for considering the Educational Journal of Artificial Intelligence and Machine Learning as a platform for your research. We look forward to receiving and sharing innovative contributions that enhance our understanding of technological practices and education as a whole.