2024 ASEE Annual Conference & Exposition

Optimizing Virtual Learning: Advanced Recommendations for an AI Teaching Assistant

Presented at Industrial Engineering Division (IND) Technical Session 3

Virtual reality (VR) has emerged as a promising tool for educating students on complex skills, providing a safe and immersive environment for practice, and learning from mistakes. However, VR training can be challenging, requiring students to navigate around the virtual environment and interact with objects in an effective way. This study presents the development of an AI teaching assistant to help students learn 3D printing operations using VR. Students’ gaze behavior and performance measures, such as task completion time and accuracy, have been tracked to develop the AI teaching assistant. The assistant provides personalized recommendations and support to help students improve their 3D printing skills. The findings of this study will have significant implications for the advancement of engineering education, providing a safer and more innovative learning experience for students. The research impact extends beyond 3D printing, with the methodology for the development of AI teaching assistants across different educational domains.

Authors
  1. Mr. Md Abdullah The University of Texas at Arlington [biography]
  2. Mr. Gowtham Nageshwara rao The University of Texas at Arlington [biography]
  3. Faith Lauren Sowell The University of Texas at Arlington [biography]
  4. Vibhav Nirmal The University of Texas at Arlington [biography]
  5. Dr. Shuchisnigdha Deb The University of Texas at Arlington [biography]
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