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: F1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Ms Ka Yee Shirley CHAN, Lecturer, Centre for Language in Education, The Education University of Hong Kong

– Miss Mandy Xiao Ming YE, Research Assistant and student participant, Centre for Language in Education, The Education University of Hong Kong

Abstract

This poster-sharing session shares the outcomes collected in the first phase of a TDG project, “AI for Formative Assessment”, exploring how the Automated Speech Recognition (ASR) function in AI can possibly provide formative feedback in speaking assessments. In this phase of the project, language teachers from the Centre for Language in Education at the Education University of Hong Kong have applied the ASR function on Whatsapp, a daily social messenger platform for Hong Kong students, to provide formative feedback during a consultation session in a University speaking course: Skills for Language Test I. This project explores the effectiveness, challenges, and implications of using AI to provide formative feedback on pronouncing words and phrases.

Theme: 1. Showcase Project Achievements

Sub-theme: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)

Poster Presentation Time: 1225-1400; 1500-1600

Venue: I4, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Yanjie SONG, Associate Professor, Department of Mathematics and Information Technology, The Education University of Hong Kong

– Mr Kaiyi WU, Department of Mathematics and Information Technology, The Education University of Hong Kong

Abstract

Integrating artificial intelligence (AI) into educational settings is crucial for developing innovative teaching methods that enhance student learning. This study investigates the development and application of Learningverse, a 2D/3D metaverse platform that integrates digital humans with advanced Large Language Model Operations (LLMOps) to create AI teaching agents. Leveraging the capabilities of Large Language Models (LLMs) and Retrieval-Augmented Generation (RAG), we designed intelligent digital human teachers. These LLMOps system-constructed multi-agents, including Communication Encoder, Body Movement Coding Encoder, Eye Gaze Coding Encoder, and Expression Coding Encoder, provide personalized and strategic scaffolding to students, offering real-time feedback and support to improve their learning outcomes. Additionally, the platform utilizes GPT-SoVITS trained TTS to clone real teachers’ voices, enhancing the realism of digital human teachers. The platform can customize digital teachers and build scenarios based on different subject courses, adapting them to various thematic curricula. A pilot study evaluated the effectiveness of these digital teachers in enhancing student engagement and performance in Learningverse. Preliminary findings reveal a significant improvement in students’ interactions, motivation, and overall learning achievements. This research highlights the potential of LLMOps-integrated digital human teachers in transforming teaching practices and enriching educational experiences in the metaverse.

Theme: 1. Showcase Project Achievements

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

Poster Presentation Time: 1225-1400; 1500-1600

Venue: A4, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Ms Yi LI, Lecturer, Centre for Language in Education, The Education University of Hong Kong

Abstract

To enhance students’ proficiency in Putonghua and facilitate their integration into the workplace and life in the Greater Bay Area, the Centre for Language in Education at The Education University of Hong Kong is undertaking a Teaching Development Grant (TDG) project for 2023-2024. This project aims to engage professionals from various industries in the Greater Bay Area to conduct interviews on topics related to “work” and “life.” The interviews are categorized into four sections: “Job Hunting,” “Workplace Communication,” “Workplace Culture,” and “Life,” comprising a total of 20 topics. To provide comprehensive learning resources, the project team has recorded video interviews with experts, accompanied by textbook explanations. These valuable resources have been uploaded to EdUHK’s online learning platform, ensuring accessibility for all students. By utilizing this platform, students can enhance their learning experience and foster their understanding of the workplace environment in the Greater Bay Area. Through this initiative, students will gain valuable insights into the practical aspects of working and living in the Great Bay Area. The project aims to equip students with the essential language skills and cultural understanding required to excel in their future careers. This TDG project is designed to create an immersive and engaging learning environment by collaborating with industry professionals and leveraging an online platform. Collaborating with industry professionals and leveraging online platforms aims to create an immersive and engaging learning environment for students, preparing them for success in the dynamic Greater Bay Area.

Theme: 1. Showcase Project Achievements

Sub-theme: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)

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: 1225-1400; 1500-1600

Venue: I3, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Ms Winnie WONG, Educational Development Manager, Centre for Learning, Teaching and Technology, The Education University of Hong Kong

– Mr Vincent CHAN, Educational Development Assistant, Centre for Learning, Teaching and Technology, The Education University of Hong Kong

Abstract

Background and Objectives: This project aims to leverage the immersive capabilities of the metaverse to enhance data security and privacy awareness among students and staff at the Education University of Hong Kong. Develop a series of interactive and engaging educational materials to enhance the understanding of data security principles and data privacy policies. Design and implement a dynamic and user-friendly online platform (Metaverse Space) to host the educational materials, facilitating easy access and learning for target audiences. Methods and Findings: Within this metaverse-based platform, users are presented with practical scenarios that simulate real-world situations involving security-critical concepts. The educational virtual environment is strategically gamified to motivate users through rewarding challenges and progressive levels, bridging the gap between theory and practice. The dynamic simulation exercises allow participants to directly experience the impact of security failures and rehearse protective actions in a risk-free, controlled setting, nurturing applied skills alongside conceptual understanding. The survey results, based on responses from (n=20), indicate that the gamified metaverse prototype is both engaging and effective in teaching data security and privacy concepts. The interactive scenarios and simulations were particularly praised for their usefulness in understanding real-world data security issues. The navigation of the metaverse environment was generally considered easy. Overall, the positive responses suggest that the gamified metaverse is a valuable tool for learning data security, demonstrating its effectiveness in an educational context. Discussion and Perspectives: Leveraging Metaverses data security learning platform offers an innovative and immersive approach to addressing the limitations of traditional training methods, empowering users with comprehensive knowledge and applied skills to mitigate evolving cyber threats.

Theme: 1. Showcase Project Achievements

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

Poster Presentation Time: 1225-1400; 1500-1600

Venue: G3, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Professor Fraide A. Jr GANOTICE, Assistant Professor, Bau Institute of Medical and Health Sciences Education, Li Ka Shing Faculty of Medicine, The University of Hong Kong

Abstract

Disciplinary silos often perpetuate hierarchical relationships and competition, creating a significant barrier to teamwork and collaboration in healthcare. Students who are exclusively trained within the confines of their discipline and university miss out on opportunities to develop the interprofessional competencies necessary for managing complex medical conditions of patients. Therefore, cross-institutional interprofessional education is crucial to promote the sharing of expertise among professionals from different universities and to prepare students for clinical practice. This presentation will highlight the significant achievements of the project titled “Promoting cross-institutional collaboration through interprofessional education: Forging alliances in healthcare education.” Initiated by the University of Hong Kong (HKU) in partnership with the Hong Kong Polytechnic University (PolyU), this innovative project aims to break down educational silos and foster interprofessional competencies among healthcare students. The project’s core objective is to enhance patient-centered care by developing and implementing a model of interprofessional education that integrates various healthcare disciplines. Throughout the four phases of the project—Program Development, Pilot Testing, Actual Implementation, and Evaluation and Dissemination—numerous achievements have been documented. These include the successful integration of interprofessional education into the curricula, enhanced collaborative competencies among students. The project also pioneered the development of an evidence-based cross-institutional IPE Model, setting a benchmark for future educational endeavors in the healthcare sector. This presentation will delve into the methodologies employed, the collaborative initiatives between HKU and PolyU, and the positive impact on healthcare education highlighted by reduced medical errors and improved healthcare outcomes. By showcasing these achievements, the session aims to inspire continued progress in interprofessional education and collaboration across healthcare institutions globally.

Theme: 1: Showcase Project Achievements

Sub-theme: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)

Poster Presentation Time: 1225-1400; 1500-1600

Venue: A1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Ms Crystal LUO, Teaching and Learning Manager, Centre for Learning, Teaching and Technology, The Education University of Hong Kong

– Miss Pui Ying WONG, Educational Development Officer, Centre for Learning, Teaching and Technology, The Education University of Hong Kong

Abstract

The global pandemic prompted academic institutions to shift from traditional test-based assessments to alternative assessments, including methods such as self-assessments, peer evaluations, and digital technology-enhanced tasks. The effectiveness of alternative assessment hinges on students’ perceptions, which may subsequently influence their degree of engagement. This study was thus designed to investigate the relationship between students’ perceptions and their involvement in alternative assessment in a Hong Kong university. An online survey was administered to 177 students between November 2022 and February 2023, with the collected data undergoing quantitative analysis. The results show that students generally maintain moderate levels of positive perceptions and active involvement towards alternative assessments. Moreover, a statistically significant correlation was observed between their perceptions and involvement. Our findings not only provide evidence to support the relationship between students’ perceptions and their involvement in alternative assessment practices, but also provide insights into the importance of understanding the real-life applicability of such assessments, the facilitating role of technological tools, and the practical implementation of these assessments into courses.

Theme: 1. Showcase Project Achievements

Sub-theme: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)