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- College of Professional and Continuing Education, The Hong Kong Polytechnic University ×
- The Education University of Hong Kong ×
- The Hong Kong Polytechnic University ×
- 1. Showcase Project Achievements ×
- 1.1 Teaching Development and Language Enhancement Grant (TDLEG) ×
- 1.2 Fund for Innovative Technology-in-Education (FITE) ×
- 2.1 Community of Practice (CoP) ×
- 2.3 Community Engaged Learning ×
- 2.4 Whole-Person Development ×
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7 posts found
Poster Presentation Time: 1225-1400; 1500-1600
Venue: F1, Tai Po-Shek-O Room, Lower Level I
Presenter(s)
– Ms Ka Yee Shirley CHAN, Lecturer, Centre for Language in Education, The Education University of Hong Kong
– Miss Mandy Xiao Ming YE, Research Assistant and student participant, Centre for Language in Education, The Education University of Hong Kong
Abstract
This poster-sharing session shares the outcomes collected in the first phase of a TDG project, “AI for Formative Assessment”, exploring how the Automated Speech Recognition (ASR) function in AI can possibly provide formative feedback in speaking assessments. In this phase of the project, language teachers from the Centre for Language in Education at the Education University of Hong Kong have applied the ASR function on Whatsapp, a daily social messenger platform for Hong Kong students, to provide formative feedback during a consultation session in a University speaking course: Skills for Language Test I. This project explores the effectiveness, challenges, and implications of using AI to provide formative feedback on pronouncing words and phrases.
Theme: 1. Showcase Project Achievements
Sub-theme: 1.1Â Teaching Development and Language Enhancement Grant (TDLEG)
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)
Poster Presentation Time: 1225-1400; 1500-1600
Venue: A4, Tai Po-Shek-O Room, Lower Level I
Presenter(s)
– Ms Yi LI, Lecturer, Centre for Language in Education, The Education University of Hong Kong
Abstract
To enhance students’ proficiency in Putonghua and facilitate their integration into the workplace and life in the Greater Bay Area, the Centre for Language in Education at The Education University of Hong Kong is undertaking a Teaching Development Grant (TDG) project for 2023-2024. This project aims to engage professionals from various industries in the Greater Bay Area to conduct interviews on topics related to “work” and “life.” The interviews are categorized into four sections: “Job Hunting,” “Workplace Communication,” “Workplace Culture,” and “Life,” comprising a total of 20 topics. To provide comprehensive learning resources, the project team has recorded video interviews with experts, accompanied by textbook explanations. These valuable resources have been uploaded to EdUHK’s online learning platform, ensuring accessibility for all students. By utilizing this platform, students can enhance their learning experience and foster their understanding of the workplace environment in the Greater Bay Area. Through this initiative, students will gain valuable insights into the practical aspects of working and living in the Great Bay Area. The project aims to equip students with the essential language skills and cultural understanding required to excel in their future careers. This TDG project is designed to create an immersive and engaging learning environment by collaborating with industry professionals and leveraging an online platform. Collaborating with industry professionals and leveraging online platforms aims to create an immersive and engaging learning environment for students, preparing them for success in the dynamic Greater Bay Area.
Theme: 1. Showcase Project Achievements
Sub-theme: 1.1Â Teaching Development and Language Enhancement Grant (TDLEG)
Poster Presentation Time: 1225-1400; 1500-1600
Venue: G4, Tai Po-Shek-O Room, Lower Level I
Presenter(s)
– Dr Hung-lin CHI, Associate Professor, Department of Building and Real Estate, The Hong Kong Polytechnic University
– Ms Junyu CHEN, Ph.D Student, Department of Building and Real Estate, The Hong Kong Polytechnic University
– Mr Haolei LIN, Ph.D Student, Department of Building and Real Estate, The Hong Kong Polytechnic University
Abstract
KnowLearn is an interactive learning assistant system designed for architecture, engineering, and construction (AEC) education, where personalized recommendations for students in virtual learning environments remain under-explored. An educational knowledge graph (KG) was constructed to contain multifaceted information by connecting pedagogical, learning performance, and learning feedback data as sub-graphs. A heterogeneous graph attention network (HAN) was implemented to infer latent information in the educational KG and identified essential factors shaping students’ acceptance of virtual learning environments. Based on sampling data of 107 students from the Hong Kong Polytechnic University, Department of Building and Real Estate, we found students’ self-efficacy, intention to use, and in-class quiz performance were significant predictors of final learning outcomes in subjects that adopt virtual learning environments. This project further deployed a local-based large language model (LLM) Qwen-7B and built an interactive graphical user interface (GUI) with Gradio. Utilizing the information preserved in the educational KG and learned from HAN as the basis, this LLM facilitated conversations between students and KnowLearn, enhancing personalized recommendations while securing student privacy. The developed system contributed to helping improve the learning experiences and performances of AEC students within virtual learning environments.
Theme: 1: Showcase Project Achievements
Sub-theme: 1.1Â Teaching Development and Language Enhancement Grant (TDLEG)
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: 1.2Â Fund for Innovative Technology-in-Education (FITE)
Poster Presentation Time: 1225-1400; 1500-1600
Venue: A1, Tai Po-Shek-O Room, Lower Level I
Presenter(s)
– Ms Crystal LUO, Teaching and Learning Manager, Centre for Learning, Teaching and Technology, The Education University of Hong Kong
– Miss Pui Ying WONG, Educational Development Officer, Centre for Learning, Teaching and Technology, The Education University of Hong Kong
Abstract
The global pandemic prompted academic institutions to shift from traditional test-based assessments to alternative assessments, including methods such as self-assessments, peer evaluations, and digital technology-enhanced tasks. The effectiveness of alternative assessment hinges on students’ perceptions, which may subsequently influence their degree of engagement. This study was thus designed to investigate the relationship between students’ perceptions and their involvement in alternative assessment in a Hong Kong university. An online survey was administered to 177 students between November 2022 and February 2023, with the collected data undergoing quantitative analysis. The results show that students generally maintain moderate levels of positive perceptions and active involvement towards alternative assessments. Moreover, a statistically significant correlation was observed between their perceptions and involvement. Our findings not only provide evidence to support the relationship between students’ perceptions and their involvement in alternative assessment practices, but also provide insights into the importance of understanding the real-life applicability of such assessments, the facilitating role of technological tools, and the practical implementation of these assessments into courses.
Theme: 1. Showcase Project Achievements
Sub-theme: 1.1Â Teaching Development and Language Enhancement Grant (TDLEG)
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