About
EduAI Nexus: Journal of Artificial Intelligence in Education is an international, open-access, peer-reviewed journal that provides a global platform for researchers, developers, educators, and policymakers to critically engage with the intersection of artificial intelligence (AI) and educational transformation through interdisciplinary perspectives. The journal bridges computer science, learning sciences, technology ethics, and public policy to explore the multifaceted impact of AI on global educational systems.
Unlike existing journals that mainly focus on system design or instructional technology, EduAI Nexus uniquely highlights the ethical, policy-related, and equity-driven dimensions of AI integration in education, particularly within both developed and underrepresented contexts. The journal prioritizes research that promotes not only technological advancement but also global educational justice and social sustainability, addressing a critical gap in current AI-education discourse.
Aims and Scope
EduAI Nexus welcomes interdisciplinary and methodologically diverse contributions that critically examine the design, implementation, and impact of artificial intelligence in educational contexts. Topics of interest include, but are not limited to:
- Ethical, inclusive, and equity-centered design of AI-powered learning environments
- Educational policy analysis and governance frameworks for AI implementation
- AI-supported pedagogical transformation in developing countries
- Personalized learning and bridging educational disparities using AI
- AI-enabled decision-making systems in educational leadership and management
- Applications of AI in assessment, learning analytics, and emotion recognition
- Machine learning and educational data mining
- Philosophical and ethical critiques of AI in classroom settings
- Human-AI collaboration for enhancing learner engagement and achievement
- Empirical, qualitative, quantitative, or mixed-method studies on AI's impact in real-world settings
- Cross-national and cross-cultural comparative research on AI in education