Modernizing Engineering Education: Personalized Learning to Support Diverse Learning Needs Through AR/VR, Digital Twin, and AI-Assisted Technologies
Date and Time: May 2, 2025 | 1 p.m. PST
Location: CHBE 102
Refreshments will be served at 12:50 pm
Abstract
Virtual/augmented reality (VR/AR), and digital twin technologies are reshaping engineering education by enabling immersive, cost-effective training environments. VR can simulate rare or hazardous scenarios—such as equipment malfunctions or safety drills—while digital twins allow researchers to analyze workflows and task performance to better understand diverse user behaviors and learning experiences. This talk presents a multi-user VR system developed for the Unit Operations Lab, supporting gesture-, screen-, and controller-based interactions. It enables students to participate in lab activities remotely, fostering collaboration and preparing them for hands-on work. In-lab AR/VR tools further enhance learning through features such as 3D P&IDs and interactive walkthroughs, deepening students’ understanding of complex processes. Complementing the virtual lab experience are field trips and integrations with oncampus resources to support hands-on, experiential learning. Beyond the lab, we leverage artificial intelligence/machine learning (AI/ML), and large language models (LLMs) to gain insights into factors associated with student academic performance and to quantify the effectiveness of curricular changes. These data-driven approaches support the development of more inclusive and adaptable learning environments, promoting personalization and lifelong learning in engineering education.
Biography
Dr. Ariel is an Associate Professor, Teaching Stream, at the University of Toronto and a licensed professional engineer in Ontario, Canada. Her teaching and research focus on chemical process design, scale-up simulation, and modernizing laboratory education to create a more accessible, equitable, and inclusive learning environment. In 2018, she was awarded the U of T Engineering Dean’s Emerging Innovation in Teaching Professorship, which supports her ongoing development of interactive AR/VR digital twins with intelligent feedback systems for personalized laboratory learning. She also applies data analytics and AI to explore factors influencing engineering students’ academic performance and to investigate leaky pipeline effects among underrepresented groups. Her contributions to engineering education have been recognized with the Technology-Enhanced Active Learning Fellowship (2018), the Canadian Wighton Fellowship (2022), the Bill Burgess Teacher of the Year Award, and the Northrop Frye Award (2023).