Artificial Intelligence in Educational Decision Sciences (AIEDS) focuses on high-quality empirical, theoretical, and methodological research that examines the role of artificial intelligence in shaping, supporting, and optimizing decision-making processes within educational systems. The journal is explicitly positioned at the intersection of artificial intelligence, educational sciences, and decision sciences, emphasizing analytical rigor, theoretical grounding, and real-world relevance.

The journal publishes original research articles, systematic reviews, and conceptual papers within the following scopes:

1. AI-Based Educational Decision Systems
   Design and evaluation of decision support systems, predictive models, and optimization tools for instructional planning, assessment, curriculum design, and institutional decision-making.
2. Learning Analytics and Educational Data Science
   Applications of learning analytics, educational data mining, big data, and explainable AI (XAI) to inform academic, managerial, and policy decisions in education.
3. Intelligent and Adaptive Learning Technologies
   Intelligent tutoring systems, adaptive and personalized learning environments, recommender systems, and human–AI collaboration in learning and teaching processes.
4. Educational Management, Leadership, and Policy Analytics
   AI-driven analysis for educational leadership, governance, quality assurance, resource allocation, and evidence-based policy formulation and evaluation.
5. Ethics, Governance, and Trust in Educational AI
   Studies on algorithmic fairness, bias, transparency, accountability, ethical decision-making frameworks, and regulatory implications of AI use in education.
6. Lifelong Learning and Workforce-Oriented Decisions
   AI applications supporting lifelong and life-course education, vocational and higher education pathways, career guidance, employability analytics, and workforce development planning.

AIEDS welcomes interdisciplinary contributions that combine artificial intelligence techniques with decision science frameworks and educational perspectives, offering robust theoretical contributions and practical implications for research, practice, and policy.