Oral Presentation Time: 1400-1500

Venue: Fanling Room, Lower Level I

Presenter(s)

– Mr Jac LEUNG, Lecturer, Division of Integrative Systems and Design, The Hong Kong University of Science and Technology

Abstract

This project explores the intersection of Generative AI, reflection and experiential learning, highlighting GenAI’s pivotal role in fostering deeper cognitive processes and the attainment of complex knowledge structures. In recognition of the multifaceted dimensions of reflection, we aim to examine GenAI’s role in promoting different focuses of reflection including technical reflection on efficiency of attaining goals; practical reflection on challenging assumptions and establishing identities; and critical reflection on reflecting within a broader consideration of socio-historical and political-cultural context. GenAI is widely praised for its ability to serve as agent to writing and agent to knowledge. This study explores GenAI’s potential as agent to reflect, offering a perspective transformation devoid of judgement and social bias. We adopt an action research approach to accommodate both the rapidly growing research area and state-of-the-art teaching innovations. To examine the roles of GenAI in various types of experiential learning contexts, a 3-year collaboration project consists of four local universities in Hong Kong was initiated in early 2024. Participating students are of diverse background in science, social science, engineering, business, and health profession (radiography). Reflective exercises are designed according to the course context and the type of experiences within entrepreneurship education, social innovation, and health professional training.

Theme: 1. Showcase Project Achievements

Sub-theme: Innovative Technology-in-Education

Oral Presentation Time: 1400-1500

Venue: Fanling Room, Lower Level I

Presenter(s)

– Mr Jungjin PARK, PhD student, Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technology

– Professor Larry LI, Associate Head & Associate Professor, Department of Mechanical and Aerospace Engineering, The Hong Kong University of Science and Technolog

Abstract

Immersive technologies come in various forms and names, such as virtual reality (VR), augmented reality (AR), and recently spatial computing. While higher education has always been at the forefront of experimenting with such technologies in the classroom, the ubiquity of smartphones and tablets – capable of creating robust AR experiences – has made it possible for wider adoption in recent years. In this presentation, we highlight lessons learned from a pilot project that leveraged AR to enhance aerospace laboratory training at the Hong Kong University of Science and Technology, and how this effort is being expanded across multiple disciplines such as pulmonary physiotherapy and forensic pathology. In particular, we share our vision to combine AR and large language models (LLMs) to design truly immersive learning experiences that can be effectively deployed into classrooms. When combined, the two technologies mutually benefit and supplement their respective advantages and limitations, thereby overcoming many of the current challenges faced by educators when deploying either on their own.

Theme: 1. Showcase Project Achievements

Sub-theme:  Innovative Technology-in-Education

Oral Presentation Time: 1400-1500

Venue: Peony Room, Lower Level II

Presenter(s)

– Ms Carrie Ka Yee CHENG, Head of Academic Programmes (Full-time), School of Continuing and Professional Studies, The Chinese University of Hong Kong

Abstract

Encompassing 20 Virtual Reality (VR) simulations across 15 academic disciplines for pre-internship training, InternVision – a dual platform of a VR head-mounted display system and a mobile application (app), is developed and launched for enhancing the work-readiness of all full-time students at School of Continuing and Professional Studies, The Chinese University of Hong Kong (CUSCS). InternVision envisages to be an ingenious and resourceful platform with interactive contents of real-life workplace scenarios for elevating job competency, enhancing professional related concepts, reactions and decision making at internships, and thus formulating an insightful immersive experience for empowering learners to a multitude of careers. This oral presentation endeavours to share ideas and success factors on how InternVision is designed, constituted and operated in line with our expected high effectiveness and promising satisfaction. Via seamlessly integrating technologies at the VR system and appending with its user-friendly mobile app, InternVision brings forth greater flexibility, confidence and motivation for students to gear up for their internships and maneuver their learning more freely beyond time and location constraints. By visualising the simulations, a deeper understanding of their roles regarding their own profession can be yielded for further self-reflection, and hence achieving the intended learning outcomes. InternVision can be framed as a comprehensive and impactful solution for enhancing internship preparation and consolidating student success for a world of future profession.

Theme: 1. Showcase Project Achievements

Sub-theme: Quality Education Fund (QEF), and Quality Enhancement Support Scheme (QESS)

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