Using Virtual Reality to Enhance Vertical Integration of Basic and Clinical Anatomical Knowledge

Principal Investigator: Dr Jian Yang, School of Biomedical Sciences
Co-investigators: Mr Chun Chung Cheung, Dr George Lim Tipoe

Educational technologies have created many new possibilities in the way we make learning happen in students. Since the advent of virtual reality (VR) technology, it has been gradually adapted into university education as an innovative educational intervention.

In the School of Biomedical Science, we are proposing the application of VR in undergraduate anatomy teaching to better integrate basic and clinical sciences. Coupled with our task-oriented practical approach, we aim to promote active learning, problem-solving and knowledge application instead of rote memorisation and didactic teaching and learning. The effectiveness of VR as a learning tool will first be assessed in conjunction with other existing learning modalities, followed by a large-scale application in dissection classes.

We believe this study will pioneer the development of VR application at the University of Hong Kong particularly health science education but more importantly inform us the general design principles in incorporating VR technology into learning activities. The study will have far-reaching bearing in our quest for teaching and learning excellence.

The Impact of a Student-driven Near-peer Teaching Initiative for Medical Students: An Exploratory Study

Principal Investigator: Dr Julie Yun Chen, Department of Family Medicine and Primary Care
Co-investigators: Dr Mei Li Khong, Dr Jannie Roed, Dr Kendrick Co Shih, Dr Tomasz Cecot, Ms Evelyn Chan, Ms Vernice Chan, Ms Joyce Tsang

Student-led academic support in which senior students offer tutorials, bedside teaching or examination preparation to their junior peers is a longstanding practice in medical education that has been offered on an ad-hoc basis. Building on earlier work that engaged students as teachers in formal curricular activities, this project explores the impact and experience of a wholly student-led near-peer teaching (NPT) initiative. MBBS Year 5 peer teachers (PT) will systematically develop and deliver tutorial sessions and undergo training in fundamental teaching skills to provide academic support for peer learners (PL) in Year 2. The NPT will add value and extend concepts learned, with deliberate care taken not to replace or to undermine the formal curriculum. A mixed-method quantitative-qualitative study will examine the impact of the initiative on both peer learners (PL) and peer teachers (PT). Structured questionnaire surveys will assess PL and PT self-efficacy and attitudes towards near-peer teaching. In-depth semi-structured focus group interviews will capture the lived experiences of the PLs as participants and the PTs as teachers of medicine and as learners of teaching practices. This will enable us to better understand the potential scope for student engagement in teaching and learning as we examine the possibilities for students-as-partners in medical education.

Chatbot is a communication stimulating computer programme which is used to mimic human conversation. This project incorporates the conversation-oriented chatbot technology into a semi-humanoid robot to provide unlimited opportunities in practicing conversation with digital clients in the nonclinical area for nursing students.

With the application of Clinical Judgement Model and retrieval-based learning strategy, students are able to build a scaffold for long-term knowledge before they apply them in a real clinical environment, it also allows flexible learning progress outside of the classroom. Furthermore, the permanent expandable database provides significant engagement with students in affective, cognitive and behavioral aspects.

The project aims to develop conversation oriented chatbot for the semi-humanoid robot to act as a digital client, to strengthen students’ clinical judgement, enhance systematic approach in performing assessment interview and understand the efficacy of learning by using the chatbot.