BIMHSE News Issue 12

Teaching and Development Grants (TDG) TDGs are intended to support projects and activities that will have an impact on strategic development and the enhancement of Teaching and Learning (T&L). In the past year, grants were awarded to eleven projects. Project: The use of technology innovation ‘simulation ward’ teaching model to promote undergraduate nursing students’ clinical performance competence Principal Investigator: Dr Veronica SF Lam, School of Nursing (E: veronica@hku.hk ) Co-investigators: Ms Cecilia Kong, Mr John Fung, Ms Michelle Pang, Ms Vivien Tsang, Dr Maggie Pun, Mr Edmond Chan, Ms Stella Lo, Mr Vincent Chan, Mr Peter Lai, Dr Janet Wong The project aims to provide a simulation ward environment with mixed-human simulators to enhance students’ clinical competence, self-confidence and self-satisfaction. The mode of simulation teaching is usually related to the use of one simulator to a few participants. In reality, each nurse has to take care of more than 10 patients within a shift. Therefore, an innovative project is designed by using a new concept, Simulation Ward, in which students are required to provide nursing care to mixed- human simulators with patients with various conditions. This project engages Year 4 nursing students. They are required to participate in three to six sim ward sessions, and in each session they have to look after three to four mixed-human simulators, including high-fidelity, mid-fidelity simulators, and one standardized patient, with various clinical conditions. The outcome measures are to evaluate students’ clinical competence, clinical thinking, self- satisfaction and self-confidence. Project: A.I.natomy: Artificial Intelligence chatbots for blended learning in anatomy Principal Investigator: Dr Christopher YH See, School of Biomedical Sciences (E: drsee2@hku.hk ) Co-investigator: Dr Lap Ki Chan How do we give each student an individualised learning experience in the anatomy laboratory? Our solution is an Artificial Intelligence (AI) powered chatbot accessed via students’ mobile devices. As a digital companion whilst navigating real cadaveric specimens and models, it provides stimulating questions, instantaneous feedback and supplementary multimedia resources and can even answers students’ own questions, all in users’ natural language. This chatbot allows each student to learn at his or her own pace, with the freedom to make mistakes and learn from them. As an AI program, it gets better every year, as we generate more than 6,000 student-bot interactions in a single session to train our algorithm powered by Google’s DialogFlow AI software. MBBS year II and BDS year I students have already experienced this AI-era learning method, and MBBS students Cynthia Sin Nga Lam and Yik Sum Li are part of the research and programming team respectively. There is a short (around 1 min) demonstration video which readers might be interested in, accessible through QR code: https://drive.google.com/file/d/1jQK9UiHa-3l_O2jyT1m7YClNEIMvDHfj/view?usp=sharing Dr Veronica SF Lam Dr Christopher YH See 08