This practice paper introduces a framework for preparing engineering students for industrial collaborations. Engaging engineering students in industrial projects provides them with valuable hands-on working experience in an authentic learning environment. However, industrial collaborations come with challenges among various stakeholders, including discrepancy in expected outcomes, limited support, and shortfall in contemporary technical knowledge and hands-on competency. To establish an effective industrial collaboration, the Faculty of Engineering at the University of Hong Kong has established the Tam Wing Fan Innovation Wing (a.k.a. the HKU Inno Wing) [1]. This center is designed to engage students in real-life projects, providing them with hands-on experience.
We propose and implement the Inspire-Equip-Showcase (IES) framework to prepare students for successful industrial collaboration. In the 2023/24 academic year, a cohort of students underwent pre-collaboration training activities under IES with a focus on the theme of AI and robotics. The training covered fundamental competencies such as Robot Operating System (ROS), localization, auto-piloting, computer vision, object recognition, LiDAR control, and GPS. Following this training, these students were then paired with a local railway company, collaborating with professional engineers on the exploration of robotic solutions to address various maintenance challenges in modern railway operation.
The practice paper analyzes students' written reflections collected during the pilot run of the IES framework in 2023/24, revealing the impact of the framework and its various learning components in preparing students for industrial collaboration. The insights from this study offer valuable lessons that can be applied to adapt to other technology domains in upcoming cohorts.
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