Poster Presentation Time: 1225-1400; 1500-1600

Venue: A3, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Professor Suntong QI, Assistant Professor of Teaching, Department of Marketing and International Business, Lingnan University

Abstract

As the adoption of AI-generated content (AIGC) continues to grow in educational settings, it is crucial to understand its impact on student learning experiences. Through surveys with undergraduate students, we explore students’ attitudes, perceptions, and expectations toward AIGC in their academic pursuits. By examining the student perspective, the presentation will provide valuable insights into the evolving landscape of AIGC in education. It will highlight the strategies and best practices that educational institutions can implement to ensure the responsible and ethical use of AIGC, empowering students to navigate this technological landscape effectively.

Theme: 1. Showcase Project Achievements

Sub-theme: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)

Poster Presentation Time: 1500-1600; 1700-1800

Venue: G1, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Dr Yuk Ming TANG, Senior Lecturer, Department of Indusial and System Engineering, The Hong Kong Polytechnic University

Abstract

STEM education is essential in today’s curriculum even for university students. However, traditional classroom-based instruction methods often lack interactivity and tailored experiences that foster student engagement and comprehension. The integration of Virtual Reality (VR) and Artificial Intelligence (AI) generative chatbots has emerged as a transformative influence on the teaching and learning process. Despite this, limited research has explored the impact of advanced technology on STEM learning outcomes. This study explores the potential of employing VR and AI as tools to facilitate teaching to enhance students’ learning outcomes. 120 university students are involved in this study to examine the difference in learning outcomes by utilizing three instructional approaches for learning projectile motion: (1) a traditional didactic classroom, (2) a game-based VR metaverse, and (3) a game-based VR metaverse enriched with a generative chatbot-based pedagogical agent. The study prudently evaluated alterations in student motivation, cognitive benefit, and learning outcomes. Preliminary findings suggest that incorporating VR and AI into teaching considerably enhances student engagement and cognitive participation. This study demonstrates how the integration of VR with AI can elevate student engagement, comprehension, and skill acquisition in STEM education, paving the way for a more captivating and effective learning environment in the Edu-metaverse.

Theme: 2. Thematic Exploration

Sub-theme: 2.1 Community of Practice (CoP)

Poster Presentation Time: 1225-1400; 1500-1600

Venue: A2, Tai Po-Shek-O Room, Lower Level I

Presenter(s)

– Professor Helen Hongyan GENG, Assistant Professor of Teaching, Science Unit, Lingnan University

Abstract

This study investigates the implementation of co-teaching in four general education courses — Earth Science, Environmental Science, Ecology, and Law—centered around the theme of carbon footprint. The project unfolds in two phases. Phase I engages Earth Science and Environmental Science in a structured debate on climate change, aiming to enhance students’ critical thinking by juxtaposing evidence supporting climate change against skeptical views. Phase II extends the co-teaching model to include Earth Science, Law, and Ecology, with a focus on groundwater pollution, to highlight a multidisciplinary approach to the issue. Throughout both phases, students from the co-teaching courses assimilated both face-to-face and online, concluding with individual research projects that analyze their co-teaching experiences. This study aims to promote curiosity-driven learning, nurture multidisciplinary education, and enhance students’ critical thinking and analytical competence.

Theme: 1. Showcase Project Achievements

Sub-theme: 1.1  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: 1.1  Teaching Development and Language Enhancement Grant (TDLEG)