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

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: 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: K1, Tai Po-Shek-O Room, Lower Level 1

Presenter(s)

– Dr Laura ZHOU, Education Development Officer, Education Development Centre, The Hong Kong Polytechnic University

– Mr Leo WONG, Project Associate, Education Development Centre, The Hong Kong Polytechnic University

Abstract

The flipped learning and teaching approach redefines the traditional classroom dynamic by swapping the order of direct instruction and homework activities. In a flipped classroom, students engage with instructional materials (such as videos, readings, or podcasts) outside of class, freeing up valuable in-class time for active learning, collaborative activities, and deeper understanding. In our quest to promote effective flipped learning and teaching practices, we conducted comprehensive interviews with experienced teaching staff at PolyU, who have successfully integrated this methodology into their course. Their valuable insights were collected and compiled into case studies, which were then disseminated to all teaching staff members through e-newsletters and experience sharing workshops. These teaching cases serve as compelling examples, showcasing the versatility and impact of flipped learning and teaching. They underscore the significance of adapting pedagogical methods to enhance student learning experiences. By shifting the locus of content consumption outside the classroom, educators empower students to actively engage with the material during face-to-face sessions, fostering a deeper understanding and more meaningful interactions.

Theme: 1: Showcase Project Achievements

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