Aims and Scope

Artificial Intelligence in Learning (AIL) is an international, peer-reviewed journal that promotes research and innovation in the field of artificial intelligence (AI) and its transformative applications in education. The journal serves as a global platform for scholars, practitioners, and technologists to explore how intelligent systems, data-driven models, and adaptive algorithms can enhance teaching, learning, and educational management across diverse contexts.

AIL focuses on the theoretical foundations and practical implementations of AI-driven learning environments, emphasizing the intersection between machine intelligence and human cognition. The journal encourages studies that investigate the design, development, and evaluation of intelligent educational systems, as well as research that addresses ethical, pedagogical, and socio-technical implications of AI in education.

Special consideration is given to research that integrates AI with learning analytics, personalized learning, gamification, and cognitive modeling to improve learner engagement and outcomes. The journal also welcomes interdisciplinary works connecting computer science, educational psychology, instructional design, and digital transformation in education.

Topics of interest include (but are not limited to):

• Adaptive learning systems, intelligent tutoring, and personalized education

• Learning analytics, educational data mining, and predictive modeling

• Gamification, motivation modeling, and behavioral data analysis

• Natural language processing, multimodal learning, and educational chatbots

• Cognitive computing, emotion recognition, and affective learning environments

• Ethics, bias, and explainability in AI-based education systems

• Educational technology innovation, digital pedagogy, and intelligent assessment

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