This study explores the application of metaverse and VR technologies in engineering science popularization for teenagers (13–18 years old) and evaluates their impact on learning outcomes, engagement, and interest in engineering careers. We developed a metaverse-based engineering science popularization platform (EngiVerse) with VR modules (e.g., virtual mechanical assembly, civil engineering structure simulation) and conducted a quasi-experiment with 800 teenagers across 4 countries. Results indicate that teenagers using EngiVerse showed significantly higher engineering knowledge retention (M=82%, SD=7.3) than those in the traditional classroom group (M=65%, SD=9.8; t (798)=21.45, p<0.001) and 2D online group (M=71%, SD=8.5; t (798)=14.23, p<0.001). Immersion level (β=0.38, p<0.001) and interactive task design (β=0.29, p<0.001) were key predictors of learning outcomes. Additionally, 68% of EngiVerse users reported increased interest in pursuing engineering majors, compared to 42% in the traditional group. This study provides design guidelines for metaverse/VR science popularization tools tailored to teenagers and highlights their potential to address engineering talent pipeline gaps.

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This study explores how AI technologies enhance public scientific literacy through targeted education initiatives and interactive communication tools. Using a mixed-methods approach (2023–2025), it analyzes 11 AI-driven science education programs and 8 interactive tools across 9 urban centers (e.g., London, Delhi, Cape Town). Results show AI-assisted education increases scientific knowledge retention by 52% vs. traditional methods, with interactive tools (e.g., AI chatbots, VR science labs) boosting engagement by 47% among low-literacy groups. Key predictors of success include personalization (β=0.39, p<0.001) and cultural relevance (β=0.31, p<0.001). The research proposes a design framework for AI-enabled science communication tools and highlights their role in bridging urban scientific literacy gaps.

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This study explores the application of AI-driven scientific visualization in climate change communication and its impact on public perception. By developing a deep learning-based visualization system (ClimateVis-AI) that transforms complex climate datasets into interactive, context-aware visuals, we conducted a mixed-methods experiment with 1,200 participants across the U.S. Results show that ClimateVis-AI significantly improves public understanding of climate trends (p<0.01) and enhances pro-environmental behavioral intentions (β=0.38, p<0.001) compared to traditional static visuals. Ethical considerations regarding data accuracy and algorithmic bias in AI-generated visuals are also discussed.

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This study explores the integration of artificial intelligence (AI) in urban planning and its science communication mechanisms across 12 smart cities globally (2022–2025). By analyzing AI-driven mobility optimization, carbon neutrality governance, and public participation systems, it identifies three core communication pathways: data visualization, multi-agent simulation, and citizen co-creation. Results indicate that targeted science communication enhances public acceptance of AI urban projects by 47%. The research provides actionable frameworks for policymakers and communicators to bridge AI technology and urban sustainability.

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This study investigates the application of generative AI (GenAI) tools (e.g., ChatGPT-4, DALL-E 3) in communicating climate resilience strategies across 15 global cities (2023–2025). Through a mixed-methods analysis of 92 GenAI-driven communication campaigns, 180 stakeholder interviews, and a public survey (n=4,200), it evaluates GenAI’s impact on public awareness of urban climate risks and engagement with adaptation measures. Results show GenAI enhances message personalization by 63% and increases voluntary participation in resilience projects by 38% compared to traditional communication. However, ethical risks—including misinformation propagation and algorithmic bias—are identified in 41% of campaigns. The research proposes a GenAI Ethics Framework for urban climate communication to guide responsible deployment.

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