AI-Generated Content (AIGC) and Metaverse-Empowered Geography Education: Practical Exploration of an Immersive Scenario and Intelligent Tutoring Collaborative Teaching Model

Traditional geography teaching has long faced core challenges, such as difficulties in visualizing abstract concepts and the limitations of high-risk or high-cost practical activities. Although AI-generated content (AIGC) and metaverse technologies have individually shown educational potential, existing research is largely confined to single-technology applications. There is a lack of a cross-technology synergistic framework tailored to the three-dimensional attributes of geography ("spatial-temporal-process"), resulting in insufficient adaptation between technology and pedagogical needs. To address this gap, this study aimed to construct a novel geography teaching model synergistically empowered by "AIGC + Metaverse". Through empirical research, it sought to validate the effectiveness of the proposed model in enhancing students' core competencies, thereby providing a verified and systematic solution to overcome traditional teaching dilemmas an."d promote the intelligent transformation of geography education. This study developed a closed-loop teaching model consisting of "Scenario Immersion—Intelligent Guidance—Assessment Optimization". The model employed metaverse technology to create high-fidelity immersive geography scenarios (e.g., a digital twin environment of a dangerous rock mass), while leveraging AIGC to build an intelligent tutoring system that supported personalized guidance, intelligent Q&A, and formative assessment. Deep integration was achieved through data and pedagogical process synergy mechanisms. To validate the model's effectiveness, a quasi-experimental study was conducted over two academic years using the "Spatial Information Collection and Risk Assessment of Dangerous Rock Mass" experiment as a case study. A multidimensional dataset, including experimental scores, learning behavior data, and system logs, was collected to comprehensively compare outcomes between a traditional teaching group and an "AIGC + Metaverse" synergistic group. The empirical results demonstrated that the "AIGC + Metaverse" synergistic teaching model achieved significant improvements over the traditional model. In terms of practical operation ability, students' average scores in operational standardization and data completeness both increased by 12.5%. Improvements in spatial analysis ability were particularly prominent, with the average score for measurement accuracy increasing by 28.57% and the average score for analytical logic by 14.29%. Regarding innovative application ability, the average score for the quality of risk assessment reports rose by 28.57%, and the average score for thinking questions by 14.29%. Ultimately, the average score for comprehensive task ability improved by 11.25%. The study concluded that this synergistic model, by combining immersive metaverse scenarios with the intelligent AIGC feedback, effectively resolved the core contradictions of traditional geography teaching. It facilitated a shift in students' roles from passive recipients of knowledge to active explorers of capability, thereby achieving a fundamental paradigm shift from "knowledge transmission" to "capability empowerment." The contributions of this study are threefold. First, it offers theoretical innovation by constructing and validating a synergistic teaching framework integrating AIGC-generated content, metaverse-hosted scenarios, and real-time AI tutor interaction, thus filling the gap in existing research on cross-technology synergy and discipline-specific adaptation. Second, it provides a practical paradigm by delivering a replicable, scalable, and systematic teaching solution, serving as a concrete example for geography education reform. Third, it contributes to domain expansion by exploring a viable path for the deep integration of advanced intelligent technologies with subject teaching in the context of educational digitalization, offering theoretical references and practical insights for innovative teaching in related disciplines.