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- Oral Presentation ×
- Hong Kong Baptist University ×
- The University of Hong Kong ×
- Lingnan University ×
- The Hong Kong Polytechnic University ×
- 1. Showcase Project Achievements ×
- 1.2 Fund for Innovative Technology-in-Education (FITE) ×
- 2.1 Community of Practice (CoP) ×
- 2.4 Whole-Person Development ×
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3 posts found
Oral Presentation Time: 1400-1500
Venue: Fanling Room, Lower Level I
Presenter(s)
– Dr Richard Wing Cheung LUI, Senior Lecturer, Department of Computing, The Hong Kong Polytechnic University
Abstract
This presentation introduces the design and implementation of GPTutor, a Generative AI (GenAI) powered Intelligent Tutoring System (ITS) developed at the Hong Kong Polytechnic University (PolyU). GPTutor aims to enhance student learning experiences through personalised tutoring and interactive exploration. It helps students gain a deeper understanding of the course materials provided by their instructors. During the first phase of our implementation, we developed features for instructors to upload and manage their course content and to create learning scenarios based on the learning content. The system includes a conversational interface for students to ask questions and explore course content to deepen their understanding. As the answers are generated based on the instructor-uploaded content, GPTutor provides more factual responses, reduces hallucinations, and aligns better with the instructors’ intended learning outcomes (ILO). We will also share findings from our pilot study, which involved approximately 200 undergraduate and postgraduate students at PolyU. Finally, we will discuss our future plans for further development and enhancement of the platform.
Theme: 1. Showcase Project Achievements
Sub-theme: Innovative Technology-in-Education
Oral Presentation Time: 1400-1500
Venue: Fanling Room, Lower Level I
Presenter(s)
– Dr Theresa KWONG, Director, Centre for Holistic Teaching and Learning, Hong Kong Baptist University
Abstract
HKBU leads two UGC-funded projects to enhance digital citizenship education and promote digital ethics. The first project, “Enhancing Learning and Teaching of Digital Citizenship through Scenario-based AR Learning Trails”, pioneers innovative approaches, developing scenario-based AR learning trails to engage students as active partners in digital citizenship. With six university partners, the project team created a revised Digital Citizenship Framework and over 85 scenarios, implemented in the “AR-Trails” app. Initial findings from 2,045 students on a learning trail reveal a strong digital citizenship foundation. These insights led to the second initiative, the “Digital Ethics and Responsibilities (DEAR) Campaign”, which empowers stakeholders to make informed, responsible decisions in the digital world. The DEAR project leverages the Digital Citizenship project, creating a DEAR Hub, organizing digital ethics events, designing a micro-credential program, and curating educational content. Since January 2024, DEAR has made significant progress, including securing research ethics approval, developing an introductory micro-credential, and recording podcasts. The DEAR Hub is being established as a comprehensive digital ethics resource. These interlinked projects provide educators with professional development opportunities and resources. The presentation offers an overview of their progression and advancements, providing insights into digital citizenship education and promoting ethical, responsible digital practices.
Theme: 1. Showcase Project Achievements
Sub-theme: Innovative Technology-in-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