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: Fanling Room, Lower Level I

Presenter(s)

– Dr Esther TONG, Principal Lecturer, Division Head, Divisions of Language and Communications, College of Professional Continuing Education, The Hong Kong Polytechnic University

– Professor Roger CHAN, Division Head, Divisions of Social Sciences, Humanities and Design, College of Professional Continuing Education, The Hong Kong Polytechnic University

Abstract

Effective Content and Language Integrated Learning (CLIL) praxis relies on the sustained efforts of members of the interdisciplinary community of practice in fostering shared aspirations in pedagogical improvement, developing awareness of a content-language link, sharing resources and practices, and co-constructing understanding of disciplinarity. Responding to the need to align higher education assessments with the real-world communication and professional requirements, faculty members across the College are summoned to redesign the assessments of language and disciplinary practices. While previous studies on integrated assessment of language and disciplinary content focus on the validity, reliability and teacher belief-practice dichotomy (Attar et. al, 2022; Lo & Leung, 2022; Otto, 2018), this paper explores the essence of successful Professional Communities of Practice (PCoP). Sustainable practices and challenges associated with co-designing integrated content and language assessments in business and social sciences disciplines will be explored. It positions CLIL assessment as a collaborative provision. The first part details the associated practices of a collaborative model in an adjunct English-across-the-curriculum project. The second part highlights the impactful dialogues within a social enterprise business idea pitching competition organised to foster interdisciplinary collaboration in a professional learning community. Recommendations for optimising collaboration and maximising the participatory impact of interdisciplinary communities of practice in higher education contexts will be shared.

Theme: 2. Thematic Exploration

Sub-theme: Community of Practice (CoP)

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