Appendix A: Implementation Timeline

Phases	Description	Timeline	Deliverables
Phase l: Research & Preliminary Design	Collection of educational datasets and 3D assets. Initial design of the custom rendering and physics engine. Set up the development environment and tools.	December – February	Literature review report, preliminary design documentation, dataset collection report
Phase 2: Development & Prototyping	Develop the Generative AI model using deep learning techniques. Integrate the model with the VR platform. Develop 3D assets using vertex and geometry shaders.	February – March	Prototype of the AI-generated VR platform, development documentation
Implement the custom rendering and physics engine with features like ray tracing and collision detection. Initial testing and debugging.	May *Black Out period in April due to final examinations
Phase 3: Testing & Refinement	Comprehensive testing of the VR platform in various educational scenarios. Gather feedback from a select group of users (e.g., educators, students). Refine the Generative AI model based on feedback and testing result.	June – July	Testing report, refined VR platform, user feedback report.
Optimise the platform for performance and user experience. Address any technical challenges or issues that arise.	August – September
Phase 4: Deployment & Evaluation	Deploy the VR platform in select educational institutions for pilot testing. Provide training and support to educators and students.	October	Deployment report, evaluation report, final project report, recommendations for future work.
	Monitor the usage and gather data on the platform's impact on learning outcomes. Conduct surveys and interviews to evaluate the platform's effectiveness.	December *November is black out month due to examinations
	Analyse the data and feedback to evaluate the project's success. Prepare a comprehensive project report and recommendations for future work.	January