Adaptive Immersive Learning Environments for Teaching Industrial Robotics

Abstract: AI, robotics, and automation are reshaping many industries, including the Architecture, Engineering, and Construction (AEC) industries. For students aiming to enter these evolving fields, comprehensive and accessible training in high-tech roles is becoming increasingly important. Traditional robotics education, while often effective, usually necessitates small class sizes and specialized equipment. On-the-job training introduces safety risks, particularly for inexperienced individuals. The integration of advanced technologies for training presents an alternative that reduces the need for extensive physical resources and minimizes safety concerns. This paper introduces the Intelligent Learning Platform for Robotics Operations (IL-PRO), an innovative project that integrates the use of Artificial Intelligence (AI), Virtual Reality (VR), and game-assisted learning for teaching robotic arms operations. The goal of this project is to address the limitations of traditional training through the implementation of personalized learning strategies supported by Adaptive Learning Systems (ALS). These systems hold the potential to transform education by customizing content to cater to various levels of understanding, preferred learning styles, past experiences, and diverse linguistic and socio-cultural backgrounds.Central to IL-PRO is the development of its ALS, which uses student progress variables and multimodal machine learning to infer students’ level of understanding and automate task and feedback delivery. The curriculum is organized into modules, starting with fundamental robotic concepts, and advancing to complex motion planning and programming. The curriculum is guided by a learner model that is continuously refined through data collection. Furthermore, the project incorporates gaming elements into its VR learning approach to create an engaging educational environment. Thus, the learning content is designed to engage students with simulated robots and input devices to solve sequences of game-based challenges. The challenge sequences are designed similarly to levels in a game, each with increasing complexity, in order to systematically incrementally build students' knowledge, skills, and confidence in robotic operations. The project is conducted by a team of interdisciplinary faculty from Florida International University (FIU), the University of California Irvine (UCI), the University of Hawaii (UH) and the University of Kansas-Missouri (UKM). The collaboration between these institutions enables the sharing of resources and expertise that are essential for the development of this comprehensive learning platform.

Keywords: Adaptive Learning Systems, Robotics Training, Virtual Reality Learning, Personalized Learning, Game Assisted learning

DOI: 10.54941/ahfe1004411

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