Using AI to create open-world quests in multimedia educational complexes

Abstract

The article examines using artificial intelligence to create open-world quests in multimedia educational complexes, addressing limits of static content and the need for adaptive, agentic learning trajectories. Methodologically, it is conceptual: it synthesizes procedural content generation, machine learning, and large language models, aligning them with open-world game-design principles. It argues that AI serves as a “pedagogical orchestrator,” coordinating goals, learner capabilities, presentation, and assessment within quest environments. Personalization covers dynamic variation of difficulty, pacing, and modalities; generation of narratives, tasks, hints, and feedback. It outlines how multimedia, simulations, and VR/AR integrate into quests to raise engagement without losing didactic clarity, and sets requirements for adaptive delivery under computational and accessibility constraints. It presents an implementation framework: principles, ethics, quality control, scalability, and outcome monitoring. Expected effects include higher motivation, development of critical thinking, and support for personal pathways. Novelty lies in aligning AI-generated quests with multimedia complex architecture and treating AI as a co-ordinator of pedagogy, not merely a content generator. Limitations: theoretical emphasis, reliance on prior work, and absence of large-scale empirical validation; ethical and organizational issues are noted as directions for further testing.