About the Journal
The Journal of AI-Enabled Learning and Engineering Innovation (JAILEI) is committed to publishing rigorously peer-reviewed, high-quality research that explores the development, integration, adoption, and responsible use of artificial intelligence in education, engineering training, technological innovation, and applied engineering systems. As an open-access journal, JAILEI ensures that all published content is freely available to readers worldwide, with the aim of advancing knowledge, supporting inclusive innovation, and promoting the dissemination of research with meaningful educational, technological, industrial, and societal impact.
JAILEI is dedicated to fostering interdisciplinary research at the intersection of artificial intelligence, digital learning, engineering education, data science, and sustainable innovation. The journal particularly welcomes studies that address the realities of emerging economies and resource-constrained environments, including limited connectivity, insufficient infrastructure, unequal access to educational technologies, evolving workforce requirements, and the need for locally relevant engineering solutions.
The journal serves as an international platform for researchers, educators, engineers, technology developers, policymakers, industry professionals, and institutional leaders to exchange ideas, methods, systems, and evidence-based practices. It welcomes empirical studies, computational research, educational interventions, intelligent systems, methodological frameworks, case studies, review articles, and policy-oriented contributions.
JAILEI does not charge any Article Processing Charges (APCs) until January 31, 2027. All submissions, peer reviews, editorial processing, and publications are entirely free of cost to authors during this period.
Key areas of focus include, but are not limited to:
- Artificial intelligence in education and engineering training
- Generative AI and large language models for teaching and learning
- Intelligent tutoring systems and adaptive learning environments
- Learning analytics and educational data mining
- AI-supported curriculum design and continuous curriculum improvement
- Reinforcement learning for educational and institutional decision-making
- Digital tools and technology adoption in education
- Mobile learning and low-connectivity educational technologies
- Virtual laboratories, simulations, and digital twins for engineering education
- Competency-based education and industry-academia alignment
- Engineering workforce development and future skills
- AI-enabled assessment, feedback, and personalized learning
- Responsible, explainable, trustworthy, and human-centered AI
- Ethics, privacy, accessibility, inclusion, and governance of educational AI
- Frugal AI and affordable intelligent systems for resource-constrained environments
- Artificial intelligence applications in health, aerospace, energy, manufacturing, infrastructure, and sustainable development
- Signal processing, machine learning, and intelligent engineering systems
- Digital transformation of educational and engineering institutions
- Engineering education for innovation, industrialization, and sustainable development
- Interdisciplinary AI applications with educational, engineering, or societal relevance
Editor-in-Chief
Prof. Moskolaï Ngossaha Justin
Founder, Publisher and Managing Editor
Dr. Bappa Muktar
Associate Editors
Dr. Vincent Fono
Dr. Adama Nouboukpo
Dr. Zongo Meyo
