Submissions

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Author Guidelines

Authors are invited to submit their manuscripts to NExAIE. Please note that providing an ORCID is required for all authors prior to publication.

All submissions are first assessed by an editor to determine alignment with the aims and scope of the journal, typically within our 3-Day Initial Screening window. An editor may desk-reject a submission at this stage if it does not meet minimum quality standards; therefore, authors should ensure the study design is logically structured, the title is concise, and the abstract is completely self-contained.

AI-Augmented Peer Review

Submissions that meet the journal's scope do not undergo traditional double-blind peer review. Instead, NExAIE utilizes an AI-Augmented Peer Review model:

  • Pure AI-Augmented Evaluation: Specialized AI agents perform all traditional blind review tasks to ensure the highest standards of rigorous research across all accepted publication formats. This comprehensive, multi-dimensional evaluation includes, but is not limited to:

    • Academic Merit & Originality: Assessing novelty, theoretical framing, and significance.

    • Methodological & Statistical Rigor: Evaluating study design, reproducibility, and instrument validity.

    • Data Integrity & Interpretation: Scrutinizing evidence-to-conclusion alignment.

    • Pedagogical Alignment: Verifying relevance to educational practice and learning theories.

    • Structural Quality: Reviewing logical flow and clarity of argumentation.

    • Citation Compliance: Ensuring accuracy and completeness of all references.

  • PEDAL Archive Transparency: All AI analysis prompts are version-controlled, tracked, and disclosed as a public dossier through the PEDAL Archive.

  • Editorial Synthesis: The AI-generated reports are submitted directly to our Human Expert Section Editors, who evaluate the findings, provide essential "sense-making" synthesis, and retain final "Accept/Reject" authority.

To ensure manuscripts perform well during the AI evaluation stage, authors are highly recommended to utilize our Preliminary AI Review Prompts. These prompts act as a Socratic mentor, allowing authors to stress-test and refine their work prior to formal submission.

Ethics and Declarations

Before making a submission, authors are responsible for the following:

  • Permissions & Consent: Securing permission to publish all included materials (e.g., photos, documents, datasets) and obtaining consent from all co-authors.

  • Ethics Approval: Ensuring the research has been approved by an appropriate ethics committee in accordance with the legal requirements of the study's origin country.

  • AI Disclosure: Including a required PEDAL AI-disclosure protocol detailing any generative AI usage during the research or writing process.

  • Mandatory End-Matter: Concluding the manuscript with a Declarations section that includes Funding, Author Contributions, a Data Availability Statement, and a Conflicts of Interest disclosure.

Templates, Formatting & Accessibility (WCAG 2.1)

To streamline the submission process and ensure all articles meet our rigorous technical and accessibility standards, authors must adhere to the following:

  • Official Templates: We accept submissions in both LaTeX and Microsoft Word (.docx). While LaTeX is highly encouraged to streamline the AI-Augmented Review process, we recognize the diverse technical backgrounds of educators and offer the following templates:

    • LaTeX (Highly Encouraged): The official template is available via GitHub and overleaf.com.

    • Microsoft Word: A simplified .docx template is available for direct download via our Publisher Library.

    • Google Docs: For authors who prefer collaborative writing in the Google Suite, a read-only template is available here https://docs.google.com/. Authors must go to File > Make a copy to save it to their personal Drive for editing, and must download the final manuscript as a Microsoft Word (.docx) file for formal submission.

    Important: Authors submitting via Word or Google Docs assume full responsibility for strict manual adherence to all formatting, structural, and referencing guidelines expected by the journal.

  • Technical Quality: All visuals must be publication-ready. For detailed technical workflows—such as generating required 300+ DPI Figures—please refer to our Technical Tips at: https://kahveci.pw/nex-aie/

  • Accessibility Standards: Submissions must comply with WCAG 2.1 guidelines to support screen readers. This requires:

    • Utilizing the designated \nexaieFigure LaTeX command with ActualText metadata for all visual elements.

    • Formatting tables strictly without merged cells.

    • Ensuring all hyperlinks are descriptive and visual elements maintain proper color contrast.

When you are satisfied that your manuscript meets these standards, please proceed to the submission checklist to finalize your upload.

Submission Preparation Checklist

All submissions must meet the following requirements.

  • Author Guidelines & ORCID: This submission meets all requirements outlined in the Author Guidelines, and an ORCID has been provided for the author(s).

  • Originality: This submission has not been previously published, nor is it before another journal for consideration.

  • Pre-Screening (Highly Recommended): The authors have utilized the Preliminary AI Review Prompts to self-screen, stress-test, and refine the manuscript prior to formal submission.

  • AI Transparency: Generative AI usage is documented via a PEDAL disclosure protocol in the manuscript header. A formal PEDAL Archive reference will be generated and integrated by the editorial office during the Augmented AI Review phase to ensure full transparency.

  • Formatting: The submission strictly adheres to an official NExAIE template (LaTeX via GitHub/Overleaf, or the simplified Word/Google Docs template). For non-LaTeX submissions, the author assumes full responsibility for manual structural compliance. Where applicable (e.g., Research Articles), the manuscript follows the IMRaD structure (Introduction, Methods, Results, and Discussion).

  • Accessibility (WCAG 2.1): The manuscript meets accessibility standards, including the use of non-color visual cues, unmerged table cells with clear row headers, descriptive hyperlinks, and the \nexaieFigure command for screen-reader compatibility.

  • Declarations: The manuscript includes all mandatory end-matter, including Author Contributions, a Data Availability Statement, and a Conflicts of Interest declaration.

  • References (APA 7th Edition): All references have been checked for accuracy and completeness according to APA 7th standards. For non-LaTeX submissions (.docx), authors have ensured manual compliance. DOIs are included where available (including specific citations for AI Prompt Artifacts).

  • Tables & Figures: All tables and figures have been numbered, labeled, and prepared at publication-ready resolution (e.g., 300+ DPI).

  • Permissions: Permission has been obtained to publish all photos, datasets, and other material provided with this submission, and appropriate ethics committee approval has been secured.

Research Articles

Submissions to this section must report original, unpublished research that contributes significant new knowledge to the intersection of AI and educational ecosystems. Manuscripts must follow the IMRaD (Introduction, Methods, Results, and Discussion) structure, include a PEDAL AI-disclosure protocol, and strictly adhere to the NExAIE LaTeX template.

Review Articles

Review articles provide a comprehensive and critical synthesis of existing literature or a major theoretical advancement in the field. These should not merely summarize previous work but provide new insights, meta-analyses, or future directions for AI-native research ecosystems.

STEM Education Research

This section publishes high-quality research focused on learning, instruction, and policy within Science, Technology, Engineering, and Mathematics (STEM) disciplines, with a specific emphasis on the transformative role of Artificial Intelligence. Submissions should emphasize theoretical grounding and robust methodology.

Technology Reports

This section is dedicated to reports on new software, AI models, or technological frameworks implemented in educational settings. Reports must include technical specifications, accessibility data (ADA/WCAG), and a clear demonstration of pedagogical utility or implementation results.

Communications

Brief reports of preliminary findings or urgent research breakthroughs that warrant rapid dissemination. Communications are limited in length and focus on a single, high-impact result that significantly advances the state of the art in AI-native education.

Laboratory Experiments

Descriptions of innovative laboratory or classroom activities that utilize AI to enhance STEM learning. Submissions must include instructor notes, student materials, and evidence of successful classroom implementation/evaluation.

Commentaries

Short, opinion-based pieces or discussions on current trends, ethical considerations, or policy shifts in AI and education. These are typically invited but unsolicited submissions are considered based on relevance to the journal’s focus and scope.

Privacy Statement

The names and email addresses entered in this journal site will be used exclusively for the stated purposes of this journal and will not be made available for any other purpose or to any other party.

Data Handling and AI Review Protocol: In alignment with our AI-Native Peer Review Protocol, manuscripts submitted to NExAIE are processed through specialized, version-controlled AI agents for initial technical and pedagogical analysis. NExAIE is committed to the highest standards of confidentiality and academic integrity:

  • Confidentiality: Manuscript data transmitted to AI platforms for review purposes is handled via professional API configurations designed to ensure that the content is not used to train public models or stored by third-party providers beyond the immediate review session.

  • Data Minimization: Only data necessary for the evaluation of the scientific and pedagogical merit of the work is processed.

  • User Rights: In compliance with international data protection standards, users registered on the Kahveci Nexus platform retain the right to access, rectify, or request the deletion of their personal data.

By submitting to NExAIE, authors acknowledge and consent to this hybrid AI-human editorial workflow, which is designed to enhance the speed and transparency of scholarly communication while safeguarding intellectual property.