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: 1600-1700

Venue: Peony Room, Lower Level II

Presenters(s)

– Dr Joseph Yui-yip LAU, Interim Head of Student Affairs and Senior Lecturer, Division of Business and Hospitality Management, College of Professional and Continuing Education, The Hong Kong Polytechnic University

Abstract

A large number of students enrolled in sub-degree programmes and self-financing degree programmes in self-financing post-secondary institutions each year. As such, self-financing post-secondary institutions perform a significant role in the higher education sector in Hong Kong. To the best of the author’s knowledge, most of the students are eager to achieve whole-person development to equip themselves before graduation. In other words, they strive toward becoming a preferred graduate to establish a career path or articulate to the ‘desirable’ universities for further study. This study illustrates the Student Affairs Office to address the key challenges of developing whole person development programme, deliver successful cases of the formation of a structured whole-person development programme, and point out the roadmap to the future whole-person development programme in the forthcoming years. As expected, the study may provide valuable insights to policymakers, educators, higher education institutions, and researchers to develop a future research agenda and policy.

Theme: 2. Thematic Exploration

Sub-theme: Whole-person Development & Diversity and Inclusion Education

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