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)

Poster Presentation Time: 1225-1400; 1500-1600

Venue: J2, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Benjamin MOORHOUSE, Assistant Professor, Department of Education Studies, Hong Kong Baptist University

Abstract

The public release of ChatGPT sent shock waves through the education community. Since then, many generative AI (GenAI) tools that perform various human tasks have been launched. It is essential that higher education institutions are at the forefront of preparing graduates for the productive and responsible use of these tools. To make this a reality, instructors, as models of practice, must have the skills and knowledge to use GenAI tools. They need to understand how AI works (technological proficiency); they need to consider the ethical issues of the tools (critical and ethical awareness); they need the pedagogical awareness of how and when to use them (pedagogical capability); and they need prepare their students to use them. These skills can be considered ‘Professional Generative AI competence’ (P-GenAI-C). The Inter-institutional Collaborative Activities for Fund for Innovative Technology-in Education project presented in this poster aims to: (1) Identify the P-GenAI-C in different university subject disciplines; (2) Contextualize the P-GenAI-C within each universities’ policies and guidelines; (3) Develop training and continuous support for university instructors, and (4) Develop a developmental framework and reflective tool for evaluating P-GenAI-C. The first aim and discussion of the actualization of the remaining aims are presented.

Theme: 1. Showcase Project Achievements

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

Oral Presentation Time: 1600-1700
Poster Presentation Time: 1500-1600; 1700-1800

Oral Presentation Venue: Rose Room, Lower Level II
Poster Presentation Venue: E4, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Professor Joseph CHAN, Associate Director at Centre for Innovation and Entrepreneurship, HKU Business School, The University of Hong Kong

– Dr Jing LI, Lecturer and BBA (International Business and Global Management) Deputy Programme Director, HKU Business School, The University of Hong Kong

Abstract

Teaching and learning for innovation and entrepreneurship requires equipping students with the necessary skills for cross-disciplinary innovation: conducting academic research for scientific advancement, designing projects to translate research into applications, and connecting these to the value-chain for market adoption and commercialization. This TDG project aims at the third area – to train students for the entrepreneurial ecosystem, particularly the Greater Bay Area. The project utilizes interactive learning methods from business interviews of guest speakers to case discussions, including direct communication with industry professionals, for first-hand knowledge and perspectives to deepen students’ understanding of innovation and business strategies. The curriculum is further enhanced through tailor-made videos featuring interviews with senior management, offering practical insights into strategies and operations. This project establishes a hub of applied studies covering a spectrum of industries, to serve as a valuable resource for larger innovation community audience. The core in this pedagogical methodology is to bring industry into the classroom, and vice versa. Online and offline activities foster community building and knowledge exchange within the innovation ecosystem, while students’ reflection encourages them to apply their learning in the GBA.

Theme: 2. Thematic Exploration

Sub-theme: Community Engaged Learning & Community of Practice (CoP)

Poster Presentation Time: 1220-1400; 1500-1600

Venue: J3, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Mr Ryan MAN, Associate Dean (Undergraduate Studies), School of Business, Hong Kong Baptist University

Abstract

The Fund for Innovative Technology-in-Education (FITE) has catalyzed a transformative initiative within our School to future-proof business education. Our approach is three-pronged, with a focus on curriculum development, personalized e-learning, and pedagogical innovation. In anticipation of the 2024/25 academic year, a dedicated programme review team has been tasked with integrating AI across the BBA curriculum, introducing new core courses such as Business Coding, AI for Business, and AI Ethics and Governance. This integration extends to embedding AI applications into functional areas like marketing human resources management and finance. Besides, we have instituted a personalized e-learning graduation requirement, leveraging Industries 4.0 principles of IoT and AI in MOOCs, particularly LinkedIn Learning, to enhance engagement and digital literacy. Our metrics indicate promising uptake and substantial engagement in technology courses, underscoring the relevance of data analytics and AI in contemporary education. Supporting our pedagogical shift, the FITE-backed Fostering AI-Incorporated Learning team is pioneering AI and blended learning integration to elevate teaching quality. Our experimental initiatives range from incorporating Generative AI into Business Analytics education and piloting AI in HR teaching. These efforts signify our commitment to driving pedagogical transformation and curriculum innovation, preparing students for the evolving demands of the digital economy.

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: 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

Poster Presentation Time: 1500-1600; 1700-1800

Venue: E1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Bess Yue WANG, Senior Lecturer, Department of Journalism, School of Communication, Hong Kong Baptist University

– Dr Angela Dan WANG, Research Assistant Professor, Department of Journalism, School of Communication, Hong Kong Baptist University

Abstract

The proposed course equips students with cutting-edge skills in AI and cloud-based solutions to address real-world media management challenges faced by NGOs. Through a dynamic, experiential learning approach, students will become digitally competent, industry-ready, and socially responsible professionals. Partnering with the Institute of Endurance Science and Technology (IEST) and Huawei, the course offers a unique opportunity to bridge the gap between technological expertise and social impact. Students will gain hands-on experience by developing cloud-based solutions for IEST’s data management, publicity, and digital governance needs. The curriculum emphasizes: 1. Understanding NGO media challenges and translating them into practical cloud-based solutions. 2. Utilizing Huawei’s cloud infrastructure and receiving expert training from their engineers. 3. Developing a comprehensive cloud solution proposal addressing a real-world problem faced by IEST. Student competency will be assessed through a Huawei Cloud Practitioner certification exam and a final project proposal evaluated by industry experts and IEST. This ensures the learning experience is not only relevant but also potentially impactful, with successful proposals considered for adoption by IEST. This course exemplifies the power of technology in driving positive social change while providing students with invaluable skills for the future.

Theme: 2. Thematic Exploration

Sub-theme: 2.3  Community Engaged Learning

Poster Presentation Time: 1500-1600; 1700-1800

Venue: E3, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Christelle NOT, Senior Lecturer, Department of Earth Sciences, The Unviersity of Hong Kong

Abstract

This study explored how the emotional framing of climate change messages (hope appeal vs. fear appeal) impacted students’ emotions and sense of efficacy towards addressing climate change. Prior research had focused on the persuasive effects of hope and fear appeals, but lacked investigation into how audience perceptions influence the interpretation of these messages. The quantitative results showed that the hope-appeal group experienced a significantly greater increase in self-efficacy and collective efficacy compared to the fear-appeal group. Qualitative analysis provided potential explanations – hope-appeal videos shifted students’ attention towards messages about effective mitigation actions, while fear-appeal videos directed focus to the negative consequences of climate change. Importantly, before the intervention, many students believed individual efforts were negligible compared to collective action. However, the hope-appeal’s emphasis on efficacy allowed students to recognize the value of their individual contributions, boosting their self-efficacy and collective efficacy. The findings suggest that communicating climate solutions with hope and gain-framed messages, rather than fear appeals, may be more effective in empowering younger generations to take meaningful action against climate change.

Theme: 2. Thematic Exploration

Sub-theme: 2.3  Community Engaged Learning