Human-AI Interaction and Gamification in Intelligent Learning Environments

The rapid evolution of Artificial Intelligence (AI) is no longer a peripheral trend in pedagogy; it is the new architecture of learning. However, as the field moves past the initial "hype" phase, there is a critical need to synthesize practical applications with robust theorization. This special issue aims to bridge the gap between technical AI implementation and educational psychology, specifically focusing on how AI-driven interfaces and game-based systems can foster deeper engagement and measurable learning outcomes.

The primary objective of this special issue is to move beyond the technical implementation of AI in education to establish a multidisciplinary synthesis of AI, game science, and pedagogical theory. This collection aims to provide a rigorous platform for researchers to move from "proof-of-concept" pilots to validated, scalable models of AI-enhanced learning. By focusing on the intersection of intelligent interfaces and gameful systems, we seek to define how AI can be utilized not just for efficiency, but for the profound enhancement of learner engagement and cognitive development.

We invite original research, systematic reviews, and meta-analyses that explore the convergence of AI with educational environments:

• Adaptive learning ecosystems: AI models that personalize curriculum based on real-time cognitive load and emotional state.
• AI in Serious Games: The use of Generative AI for procedural content generation, non-player character (NPC) interactions, and dynamic difficulty adjustment (DDA).
• Theorization and frameworks: New pedagogical models for Human-AI collaboration in the classroom.
• Intelligent interfaces: UX/UI design principles for AI tutors and educational dashboards that prioritize transparency and agency.
• Immersive intelligent learning environments: AI tutors that support interactive learning and adjust to learners' abilities in Augmented-/Virtual-reality-based environments.
• Empirical studies: Large-scale data analysis on the efficacy of AI-integrated gamification versus traditional methods.
• Ethics and inclusion: Addressing algorithmic bias in educational assessment and ensuring equitable access to AI-driven tools.