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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: 1.2Â Fund for Innovative Technology-in-Education (FITE)
Venue: Peony Room, Lower Level II
Presenter(s)
– Ms Nancy TING, Senior Lecturer, Early Childhood Education, Yew Chung College of Early Childhood Education
– Ms Mary Ann HOOD, Senior Lecturer, Early Childhood Education, Yew Chung College of Early Childhood Education
Abstract
The transition from kindergarten to primary school is an important time for children and parents. In addition, starting primary school is a significant milestone for children as the teaching and learning experiences, curriculum and classroom environment are markedly different to the kindergarten. For example, there are new rules and expectations to get used to. Coping well and adjusting to the changes is important and a successful start to primary school is associated with future learning success in school. The overall Kindergarten to Primary (K2P) project objective is to overcome stress brought by the K2P transition; provide a solid foundation for primary school stage and promote child readiness for school and school readiness for child and family. The project has four objectives that focus inter alia on the students, their parents, and in-service and pre-service teachers. This presentation will focus on objective 1 which is to equip students with a positive mindset and readiness for the new learning environment using a multi-step approach. This approach includes implementing lesson plans and home activities to develop and support children’s acquisition of 7 specific skillsets, namely Cognitive skills, Independent thinking, Collaborative learning, Empathetic thinking, Social-emotional skills/understanding challenges, Communication skills and Authority in learning.
Theme: 2. Thematic Exploration
Sub-theme: Whole-person Development & Diversity and Inclusion 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.