About the Journal

This journal is a leading forum for advancing research and innovation in educational data, AI-enhanced learning, and data-driven policymaking. Positioned at the intersection of technology, pedagogy, and governance, the journal provides a platform for scholars, practitioners, and policymakers to share best practices in harvesting, mining, and applying data to improve educational systems.

Aims & Scope

The journal aims to serve as a leading international forum for advancing research and innovation in educational data science, AI-enhanced learning, and data-driven policymaking. Positioned at the intersection of technology, pedagogy, and educational governance, the journal promotes the systematic use of data and analytics to improve the effectiveness, equity, and sustainability of educational systems.

The journal focuses on research that advances rigorous evidence-based inquiry and state-of-the-art analytical approaches to support informed decision-making, scalable educational innovation, and equitable learning outcomes across diverse educational contexts.

Scope of the Journal

The journal welcomes original contributions that address, but are not limited to, the following areas:

  • Educational Data Science and Analytics

    • Data labeling and annotation frameworks for education
    • Learning analytics and educational data mining
    • Data architectures, pipelines, and interoperability
    • FAIR data principles and educational data governance

  • Artificial Intelligence in Education

    • AI-assisted assessment and automated scoring
    • Large language models and generative AI in learning
    • Adaptive and personalized learning systems
    • Ethical, transparent, and responsible AI in education

  • Assessment, Measurement, and Evaluation

    • Innovations in psychometrics (IRT, CTT, hybrid models)
    • Technology-enhanced and formative assessment
    • National and large-scale assessment systems
    • Classroom-level diagnostic and feedback analytics

  • Curriculum, Pedagogy, and EdTech

    • Data-informed curriculum design and alignment
    • Digital and simulation-based learning environments
    • Evaluation of educational technologies and platforms
    • Teacher professional development supported by data and AI

  • Policy, Governance, and Systems Innovation

    • Data-driven educational policy and reform
    • Monitoring and evaluation of SDG-4 and equity outcomes
    • Institutional capacity building for data-informed governance
    • Ethical, legal, and regulatory aspects of educational data use

The journal publishes empirical studies, methodological contributions, systematic reviews, meta-analyses, dataset papers, technical notes, and policy-relevant research that contribute to the development of robust, transparent, and impactful educational data ecosystems