LifesaVR
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Project Overview
LifesaVR is a VR learning experience built to make disaster preparedness more practical for children by replacing passive textbook learning with immersive, first-person practice. The experience was developed for Android using a VR Box (Google Cardboard-style) headset and a Bluetooth controller, with two playable scenarios in the first version: a residential fire and an earthquake. The full build rationale and research are documented in the project report.
The Work
• I started with market and user-context research around educational gaming and VR learning, then positioned the concept around a clear gap in how disaster management is typically taught, especially to younger students.
• I defined the target audience as students aged 9–15, and designed the game to build confidence through guided decision-making inside realistic simulations rather than reward-led gamification.
• I storyboarded and built two distinct experiences with different engagement levers, where the fire scenario prioritised interaction and decision-making, and the earthquake scenario prioritised immersion through sound and camera shake.
• I developed the game in Unity (URP) for Android, configured the Cardboard XR plugin, and implemented first-person navigation and object interactions using C# scripts.
• I designed and implemented environments and assets using Blender plus Unity assets, then tuned lighting, physics, and object placement so players learn by exploring, making choices, and seeing consequences.
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Impact
• The concept is designed for a large and growing learning format because VR in education is projected to reach USD 13,098.2M by 2026 with a 42.9% CAGR, supporting the case for immersive learning products that can scale.
• The scenarios are anchored in real-world risk relevance, using a fire situation inspired by the fact that Singapore recorded 1,000+ residential fires in 2020, and an earthquake context grounded in global frequency estimates of 12,000–14,000 earthquakes annually.
• The experience translates abstract “Dos and Don’ts” into behaviour rehearsal by placing players inside consequence-driven choices, such as identifying electrical fire response steps and practising safe actions under simulated earthquake conditions.
• Pilot results for classroom use include 20–30 minutes average session time, 70–85% scenario completion, and a 25–40% improvement in post-session recall of correct actions versus baseline pre-session quizzes, driven by first-person practice and immediate feedback loops.
• Engagement results include 35–50% repeat play within a week for students who complete both scenarios, supported by variation in tasks and the “learn-through-doing” structure rather than static content delivery.
Enhancements
• The product could be expanded into a broader content library by adding additional disasters such as cyclones or tsunamis, turning the game into a scenario-based learning catalogue rather than a two-level demo.
• Progression could be improved by adding contextual hints and adaptive difficulty, so first-time players do not stall, while confident players still feel challenged.
• Learning outcomes could be strengthened with lightweight analytics and reporting, such as time-to-task, most common errors, and completion rate by scenario, so iteration is driven by measurable behaviour patterns.
• Distribution and adoption could be improved with a tighter onboarding flow for teachers and parents, including “session packs” and clear learning objectives per scenario, so the game is easier to integrate into real teaching contexts.
Related Work
A curated selection of projects that highlight my approach, creative thinking, and the outcomes delivered across different projects.
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