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- City University of Hong Kong ×
- The University of Hong Kong ×
- The Hong Kong Polytechnic University ×
- Yew Chung College of Early Childhood Education ×
- 1.1 Teaching Development and Language Enhancement Grant (TDLEG) ×
- 1.2 Fund for Innovative Technology-in-Education (FITE) ×
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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: Camomile Room, Lower Level II
Team member(s)
– Professor Alvin Chung Man LEUNG, Associate Head & Associate Professor, Department of Information Systems, City University of Hong Kong
Abstract
The COVID-19 pandemic has highlighted the critical importance of online learning, where learners must engage in self-regulated learning (SRL) to achieve optimal outcomes. Gamification interventions have been implemented to improve SRL engagement in online environments, but the mixed results of these efforts have raised doubts about their efficacy. This study investigates whether the inconsistent findings can be attributed to a lack of consideration for individual learner characteristics during gamification design. Focusing on Massive Open Online Courses (MOOCs), we examined how gamified performance feedback interacted with learners’ goal orientation, an individual trait known to influence SRL and learning. By tracking the SRL engagement of 760 college students over five weeks using learning analytics, we found that positively framed performance feedback without social comparisons increased SRL engagement and learning outcomes for participants with a strong performance-avoidance goal orientation. Conversely, the same feedback had a negative impact on participants with a strong mastery goal orientation. These findings contribute to SRL theory by demonstrating that the effectiveness of gamification in online learning is contingent on aligning the design elements with individual learner characteristics and highlight the importance of personalized gamification approaches to optimize SRL and learning in MOOC.
Theme: 1. Showcase Project Achievements
Sub-theme: Teaching Development and Language Enhancement
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
Oral Presentation Time: 1400-1500
Venue: Camomile Room, Lower Level II
Presenter(s)
– Professor Michael BOTELHO, Clinical Professor, Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong
– Ms Trinity JIAO, HKU SaP CoP Project Coordinator, Restorative Dental Sciences, Faculty of Dentistry, The University of Hong Kong
Abstract
The “Students as Partners (SaP)” support framework fosters active interdisciplinary collaboration. Key initiatives undertaken by the Students as Partners Community of Practice (SaP CoP) involve organizing seminar-sharing sessions, hosting internal CoP meetings, and conducting formal consultation sessions for those initiating SaP projects. These efforts offer valuable learning opportunities and continuous support for both educators and students. At HKU, the SaP CoP has developed a Scope, Process, and Levels framework for SaP activities. In partnership with TALIC, the SaP CoP has established a dedicated webpage and featured it in the HKU bulletin. These initiatives have been well-received by students and staff alike, providing meaningful experiences and practical guidelines that significantly contribute to their learning and engagement journey.
Theme: 1. Showcase Project Achievements