Machine Learning: Teaching Procedural Knowledge to Nursing Candidates

Abstract

The purpose of this study is to design and develop a smart AR simulation support the practical learning of nursing students about the pre-operative processes. Within this scope, the simulation scenario consists nine major practical steps to arrange the surgical instruments on the Mayo table. 3D AR goggles have been used to render visuals and interaction in the simulation occured via physical hand movements. In this 3D AR simulation, it is possible to teach non-standard procedures that could be changed though the hospital, doctor or surgery types. Also, learners can walk around own their own and to look up working examples to examine specialists’ applications. The smart system is educated using the matrixes that considers inputs of the correct and incorrect arrangements of surgical instruments. Learners can get a summative feedback and it offers received percentage ratio of arrangement. This feedback is always updated using arrangements of specialists. The steps of design research methodology were referenced to design and develop this high fidelity immersive ARLE. The literature review shows that this ARLE is a unique learning system. It could be accepted as pioneering ARLE to improve the effectiveness of current MR environments and technologies to teach distinct procedures.

Presenters

Zeynep Tacgin

Details

Presentation Type

Paper Presentation in a Themed Session

Theme

CG - Technologies

KEYWORDS

Augmented Reality, Nursing Education, Smart Systems

Digital Media

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