Artificial Intelligence in Lifelong and Life-Course Education (AILLCE) focuses on advancing scholarly understanding of how artificial intelligence (AI) is designed, implemented, and evaluated within educational contexts across the entire lifespan. The journal emphasizes lifelong and life-course perspectives, addressing learning as a continuous process that spans early childhood, formal schooling, higher education, vocational education and training, adult learning, professional development, and later-life education. Its primary focus lies in examining the pedagogical, psychological, technological, and ethical dimensions of AI-supported education in formal, non-formal, and informal learning environments.

The journal publishes original research articles, theoretical analyses, methodological studies, and systematic reviews that address, but are not limited to, the following areas:

1. Artificial Intelligence Across the Life-Course
   AI applications in early childhood education, school education, higher education, vocational and professional education, adult education, and education for ageing populations; life-course transitions and longitudinal perspectives in AI-supported learning.
2. AI-Enhanced Lifelong Learning Systems
   Adaptive and personalized learning systems, intelligent tutoring systems, learning recommender systems, AI-driven assessment, learning analytics, educational data mining, and lifelong learning pathways supported by AI technologies.
3. Pedagogical, Psychological, and Developmental Perspectives
   The impact of AI on learning outcomes, motivation, self-regulated learning, academic emotions, cognitive processes, well-being, and learner agency across different developmental stages and educational contexts.
4. AI Literacy, Ethics, and Governance in Education
   AI literacy and digital competence across the lifespan; ethical, transparent, and trustworthy AI in education; issues of algorithmic bias, fairness, explainability, data privacy, and governance frameworks for AI-enabled educational systems.
5. Emerging Technologies and Innovative Learning Environments
   Integration of AI with immersive and interactive technologies, including virtual and augmented reality, game-based learning, workplace learning systems, open and community-based education, and informal learning environments.
6. Methodological and Design-Oriented Research
   Design-based research, design and development research, mixed-methods approaches, longitudinal studies, learning analytics methodologies, and the validation of AI-supported educational models, frameworks, and instruments.