Focus and Scope

Scope and Topics

ALSJ welcomes high-quality empirical studies, novel system architectures, algorithmic implementations, conceptual frameworks, and comprehensive survey papers. The scope encompasses, but is not limited to, the following domains:

• Algorithmic Personalization & AI Models: Machine learning models, predictive analytics, intelligent tutoring systems (ITS), knowledge tracing, and adaptive scaffolding algorithms.

• Cognitive Modeling & Learner Analytics: Student modeling, affective computing, cognitive load optimization, eye-tracking, and behavioral analytics in digital learning spaces.

• Data-Driven Instructional Design: Dynamic content generation, adaptive assessment paradigms, automated feedback loops, and personalized learning pathways.

• System Engineering & Architecture: Interoperability standards, scalable ed-tech infrastructures, open learner models, and cloud-native adaptive platforms.

• Ethics, Governance & Human-Centric Design: Algorithmic bias, explainable AI in education (XAI-Ed), student data privacy, accessibility, and human-in-the-loop adaptive systems.