Poster Presentation Time: 1225-1400; 1500-1600

Venue: I1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Selena YAN, Senior E-learning Assistant, Li Ka Shing Faculty of Medicine, The University of Hong Kong

– Ms Leah LI, Senior E-learning Assistant, School of Clinical Medicine, The University of Hong Kong

Abstract

Generative Artificial Intelligence (GenAI) is a transformative technology that fosters creativity, problem-solving, and critical thinking skills in various industries, including healthcare and medical education. At HKU Medicine, we appreciate the importance of advancing GenAI literacy and propose to develop and deliver a new online course that covers the latest advances, pitfalls, ethical and professional aspects of GenAI. We aim to advance AI and digital competency for all students, professoriates and clinicians at HKU Medicine and the Hong Kong medical community. To evaluate the effectiveness of this online GenAI literacy course, an assessment study will be conducted. We will use a mixed methods approach to collect both quantitative and qualitative data through pre- and post- surveys, individual interviews and practical exercises. The survey will be adapted from the “Scale for the Assessment of Non-Experts’ AI Literacy” (SNAIL), while the interviews will provide additional context and insights into participants’ experiences and challenges with GenAI. Practical exercises will provide objective data for evaluation. Target participants will be recruited through convenience sampling, and data analysis will include both statistical and thematic analyses. The study has already obtained ethical approval. Results from this study will be used to identify improvement needs for the online course and inform the integration of GenAI in medical and health sciences education and clinical practices. Overall, the project will contribute to the advancement of GenAI literacy in medical education and healthcare professions, supporting the ethical and effective application of GenAI technology in these fields.

Theme: 1: Showcase Project Achievements

Sub-theme: 1.2  Fund for Innovative Technology-in-Education (FITE)

Oral Presentation Time: 1400-1500
Poster Presentation Time: 1225-1400;1500-1600

Oral Presentation Venue: Rose Room, Lower Level II
Poster Presentation Venue: H1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Ir Dr H H CHEUNG, Senior Lecturer, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong

– Mr Derek TONG, Tutor, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong

– Mr Like WEN, Research Assistant, Department of Industrial and Manufacturing Systems Engineering, The University of Hong Kong

Abstract

The past social events and COVID-19 pandemic posed huge challenges to teaching and learning. The teaching team seized these challenges as opportunities to develop and incorporate e-learning in experiential projects and capstone courses, which otherwise mandate intensive face-to-face interactions. The team has developed the Digital Design House – An e-learning platform for collaborative product development – to facilitate experiential learning and hands-on projects in various courses that carry substantial components of innovative product design and development. The Digital Design House is a cloud-based experiential e-learning platform that provides remote access to CAD facilities for students to interact among group members and with teachers in virtual environments to share their ideas for product design and development. This e-learning platform integrates a set of advanced information and computing, 3D Hologram devices, virtual reality, mixed reality, and mobile devices with a suite of in-house developed applications for stereoscopic visualisation of virtual objects in an immersive virtual environment to facilitate systematic training and development of students’ innovative abilities through experiential learning. It not only allows students at different geographical regions and teachers to ubiquitously conduct teaching and learning, but also facilitates online lectures via video conferencing like Zoom or Microsoft Teams with more interactions in a virtually face-to-face environment. Indeed, this platform helps students understand what and how various knowledge and feasible technologies can be effectively integrated to create a feasible design/solution in a practical-and-innovative approach. As such, students are inspired with a stronger desire, self-initiative, and enthusiasm for exploring their potential in innovative creations.

Theme: 1. Showcase Project Achievements

Sub-theme: Strategic Development of Virtual Teaching and Learning (VTL)

Oral Presentation Time: 1400-1500
Poster Presentation Time: 1225-1400; 1500-1600

Oral Presentation Venue: Fanling Room, Lower Level I
Poster Presentation Venue: I2, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Ting Leung Albert LEE, Lecturer, Department of Electrical and Electronic Engineering, The University of Hong Kong

– Dr Victor LEE, Lecturer, Department of Electrical and Electronic Engineering, The University of Hong Kong

– Dr Zhengyuan WEI, Research Associate, Department of Electrical and Electronic Engineering, The University of Hong Kong

– Mr Alex KIANG, The University of Hong Kong

Abstract

Retrieval-augmented generation (RAG) has been demonstrated to be highly effective in generative AI applications, resulting in substantial improvement in accuracy and reliability of large language model responses. The success of this approach is accomplished through seamless integration of AI capabilities and practical knowledge base, which fosters an interactive learning mechanism conducive to automatic question-answering augmented with references and refined prompts, leading to a more vibrant and connected learning environment. Communication portals enable effective inquiry and prompt responses while the course-specific chatbot helps reduce teachers’ workload and streamline classroom management. In this project, the RAG approach is applied to a discipline-core course named Integrated Design Project (IDP) in the second semester 2023-24. This project-based course consists of 78 EEE undergraduate students with diverse programming experience. The IDP-specific AI chatbot is developed using the Coze platform with a Discord server. To name a few, the main contents of practical knowledge base include the procedures for setting up a Raspberry Pi webcam, the installation process of Jetson Inference library on Jetson Nano, how to use YOLO model for object detection, how to install Jetson inference library on Jetson Nano, etc. The anonymous feedback survey conducted at the end of the course shows high utilization and satisfaction of the chatbot, confirming the effectiveness of this approach in facilitating students’ learning.

Theme: 1. Showcase Project Achievements

Sub-theme: Innovative Technology-in-Education