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: 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)

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)