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A Generative-AI Platform for Subject Specific Intelligent Tutoring Systems

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

Establishing a Shared Quality Assurance Framework and Standards for Online Learning and Teaching in a Hong Kong Context

Oral Presentation Time: 1400-1500
Venue: Rose Room, Lower Level II
Presenter(s)

– Dr Ronnie SHROFF, Principal Project Fellow, Teaching and Learning Centre, Lingnan University

Abstract

In response to the COVID-19 pandemic, the University Grants Committee (UGC) and the Quality Assurance Council (QAC) allocated dedicated funding to support the strategic long-term development of virtual teaching and learning (VTL) in Hong Kong’s eight UGC-funded universities. Lingnan University, as the lead institution of a consortium of six participating universities, secured funding to establish benchmarking practices and quality assurance standards on VTL that reference internationally accepted standards within the local context. This project aims to strengthen institutional capabilities and enhance the quality of VTL provision, including online teaching and learning, distance education delivery, and technology-enhanced learning. The project involves collaboration and funding from The University of Hong Kong, The Hong Kong University of Science and Technology and the City University of Hong Kong, as well as in-kind support from The Chinese University of Hong Kong and The Hong Kong Polytechnic University. The primary objective of this project is to establish a shared quality assurance framework and standards for online learning and teaching that align with local and global standards. By adopting a collaborative approach, this project seeks to enhance the quality of VTL as a key strategic focus area of institutional development and performance improvement. This presentation will provide an overview of the project’s key objectives, methodology and outcomes. It will also discuss the challenges encountered and lessons learned in developing quality assurance and benchmarking standards for VTL across universities. Finally, the presentation will conclude with recommendations for future collaborations to enhance the quality of VTL provision within the Hong Kong higher education context.

Theme: 1. Showcase Project Achievements

Sub-theme: Strategic Development of Virtual Teaching and Learning (VTL)

Gamification for Self-Regulation: Exploring the Impact of Personalized Performance Feedback in Massive Open Online Courses

Oral Presentation Time: 1400-1500
Venue: Camomile Room, Lower Level II
Team member(s)

– Professor Alvin Chung Man LEUNG, Associate Head & Associate Professor, Department of Information Systems, City University of Hong Kong

Abstract

The COVID-19 pandemic has highlighted the critical importance of online learning, where learners must engage in self-regulated learning (SRL) to achieve optimal outcomes. Gamification interventions have been implemented to improve SRL engagement in online environments, but the mixed results of these efforts have raised doubts about their efficacy. This study investigates whether the inconsistent findings can be attributed to a lack of consideration for individual learner characteristics during gamification design. Focusing on Massive Open Online Courses (MOOCs), we examined how gamified performance feedback interacted with learners’ goal orientation, an individual trait known to influence SRL and learning. By tracking the SRL engagement of 760 college students over five weeks using learning analytics, we found that positively framed performance feedback without social comparisons increased SRL engagement and learning outcomes for participants with a strong performance-avoidance goal orientation. Conversely, the same feedback had a negative impact on participants with a strong mastery goal orientation. These findings contribute to SRL theory by demonstrating that the effectiveness of gamification in online learning is contingent on aligning the design elements with individual learner characteristics and highlight the importance of personalized gamification approaches to optimize SRL and learning in MOOC.

Theme: 1. Showcase Project Achievements

Sub-theme: Teaching Development and Language Enhancement