Enhancing Mechanical Engineering Education Through a Virtual Instructor in an Ai-Driven Virtual Reality Fatigue Test Lab

Abstract

This thesis demonstrates the combination of virtual reality (VR) and artificial intelligence (AI) specifically exploring the practical application of Natural Language Processing (NLP) and GPT-based models in educational VR laboratories. The objective is to design a comprehensive learning environment where users can independently engage in laboratory experiments, deriving similar educational outcomes as they would from a traditional, physical laboratory setup, particularly within the realms of Science, Technology, Engineering, and Mathematics (STEM) disciplines. Using machine learning techniques and authentic virtual reality simulating educational experiments, we propose an advanced learning platform—Virtual Reality Instructional Laboratory Environment (VRILE). A key feature of the VRILE is an AI-powered instructor capable of not only guiding the learners through the tasks but also responding intelligently to their actions in real-time. The AI constituent of the VRILE uses the GPT-2 model for text generation in the field of Natural Language Processing (NLP). To ensure the generated instructions were contextually relevant and meaningful to lab participants, the model was trained on a dataset derived from an augmentation over user interactions within the VR environment. By pushing the boundaries of how AI can be utilized in educational VR environments, this research paves the way for broader adoption across other domains of engineering education. Furthermore, it provides a solid foundation for future research in this interdisciplinary field. It marks a significant stride in the integration of technology and education, encouraging more ventures into this promising frontier.