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Intelligent medical case based e-learning system

Citation

Ameen, S and Han, SC and Lin, Y and Lah, M and Kang, BH, Intelligent medical case based e-learning system, Proceedings from the Australasian Conference on Information Systems, 4-6 December, Hobart, Australia, pp. 1-12. (2017) [Refereed Conference Paper]


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Copyright Statement

Copyright 2017 Saleem Ameen, Soyeon Caren Han, Yingru Lin, Minjae Lah, and Byeong Ho Kang. Licensed under Creative Commons Attribution-NonCommercial 3.0 Australia (CC BY-NC 3.0 AU) https://creativecommons.org/licenses/by-nc/3.0/au/

Official URL: https://www.acis2017.org/

Abstract

Educational theory has purported the notion that student-centric modes of learning are more effective in enhancing student engagement and by extension, learning outcomes. However, the translation of this theoretical pedagogy of learning into an applied model for medical training has been fraught with difficulty due to the structural complexity of creating a classroom environment that enables students to exercise full autonomy. In this paper, we propose an intelligent computational e-learning platform for case-based learning (CBL) in Medicine that enriches and enhances the learning experiences of medical students by exposing them to simulated real-world clinical contexts. We argue that computational systems in Medicine should not merely provide a passive outlay of information, but instead promote active engagement through an immersive learning experience. This is achieved through a digital platform that renders a virtual patient simulation, which allows students to assess, diagnose, treat and test patients as they would in the real-world.

Item Details

Item Type:Refereed Conference Paper
Keywords:case-based learning, medical education, e-learning
Research Division:Health Sciences
Research Group:Health services and systems
Research Field:Health informatics and information systems
Objective Division:Information and Communication Services
Objective Group:Information systems, technologies and services
Objective Field:Information systems, technologies and services not elsewhere classified
UTAS Author:Ameen, S (Mr Saleem Ameen)
UTAS Author:Lin, Y (Dr Yingru Lin)
UTAS Author:Kang, BH (Professor Byeong Kang)
ID Code:123101
Year Published:2017
Deposited By:Information and Communication Technology
Deposited On:2017-12-15
Last Modified:2022-08-25
Downloads:61 View Download Statistics

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